From ac925759b798e8a1db8ee71b5d1a46de8b05932c Mon Sep 17 00:00:00 2001 From: Sonika Janagill Date: Sun, 15 Mar 2026 15:28:54 +0000 Subject: [PATCH 1/2] Add ADK agent with security pipeline and agent-starter-pack enhancement Core AdkBot executive assistant with 4 sub-agents (Gmail, Calendar, Drive, Search), 6-layer security pipeline, Telegram gateway, and Firestore memory. Enhanced with agent-starter-pack for production-ready deployment infrastructure including Cloud Run Terraform, GitHub Actions CI/CD, evaluation framework, and observability. Co-Authored-By: Claude Opus 4.6 --- .env-example | 4 + .github/workflows/ci.yml | 36 + .github/workflows/deploy-to-prod.yaml | 70 + .github/workflows/deploy.yml | 57 + .github/workflows/pr_checks.yaml | 62 + .github/workflows/staging.yaml | 115 ++ .gitignore | 67 + Dockerfile | 25 + GEMINI.md | 58 + Makefile | 111 ++ README.md | 68 + agent/__init__.py | 1 + agent/agent.py | 79 + agent/app_utils/telemetry.py | 51 + agent/app_utils/typing.py | 46 + agent/config.py | 41 + agent/errors.py | 15 + agent/fast_api_app.py | 72 + agent/main.py | 145 ++ agent/memory.py | 74 + agent/root_agent.py | 25 + agent/security/__init__.py | 1 + agent/security/approval.py | 49 + agent/security/dlp_filter.py | 63 + agent/security/input_guard.py | 31 + agent/security/output_guard.py | 18 + agent/security/trace.py | 35 + agent/subagents/__init__.py | 1 + agent/subagents/calendar_agent.py | 34 + agent/subagents/drive_agent.py | 33 + agent/subagents/gmail_agent.py | 33 + agent/subagents/search_agent.py | 29 + deployment/README.md | 11 + deployment/terraform/apis.tf | 40 + deployment/terraform/dev/apis.tf | 41 + deployment/terraform/dev/iam.tf | 59 + deployment/terraform/dev/outputs.tf | 23 + deployment/terraform/dev/providers.tf | 34 + deployment/terraform/dev/service.tf | 80 + deployment/terraform/dev/service_outputs.tf | 23 + deployment/terraform/dev/storage.tf | 27 + deployment/terraform/dev/telemetry.tf | 200 +++ deployment/terraform/dev/telemetry_outputs.tf | 23 + deployment/terraform/dev/variables.tf | 55 + deployment/terraform/dev/vars/env.tfvars | 8 + deployment/terraform/github.tf | 168 ++ deployment/terraform/iam.tf | 92 + deployment/terraform/locals.tf | 50 + deployment/terraform/outputs.tf | 34 + deployment/terraform/providers.tf | 46 + deployment/terraform/service.tf | 85 + deployment/terraform/service_accounts.tf | 29 + deployment/terraform/service_outputs.tf | 23 + deployment/terraform/sql/completions.sql | 138 ++ deployment/terraform/storage.tf | 39 + deployment/terraform/telemetry.tf | 215 +++ deployment/terraform/telemetry_outputs.tf | 23 + deployment/terraform/variables.tf | 111 ++ deployment/terraform/vars/env.tfvars | 19 + deployment/terraform/wif.tf | 43 + notebooks/adk_app_testing.ipynb | 367 ++++ notebooks/evaluating_adk_agent.ipynb | 1535 +++++++++++++++++ pyproject.toml | 20 + requirements.txt | 26 + secure-openclaw-build-plan.md | 581 +++++++ terraform/environments/dev.tfvars | 4 + terraform/main.tf | 41 + terraform/modules/cloud_run/main.tf | 52 + terraform/modules/iam/main.tf | 30 + terraform/modules/secrets/main.tf | 24 + terraform/modules/wif/main.tf | 39 + tests/eval/evalsets/README.md | 80 + tests/integration/test_agent.py | 57 + tests/integration/test_server_e2e.py | 207 +++ tests/load_test/.results/.placeholder | 0 tests/load_test/README.md | 83 + tests/load_test/load_test.py | 130 ++ tests/test_main.py | 14 + tests/unit/test_dummy.py | 23 + 79 files changed, 6601 insertions(+) create mode 100644 .env-example create mode 100644 .github/workflows/ci.yml create mode 100644 .github/workflows/deploy-to-prod.yaml create mode 100644 .github/workflows/deploy.yml create mode 100644 .github/workflows/pr_checks.yaml create mode 100644 .github/workflows/staging.yaml create mode 100644 .gitignore create mode 100644 Dockerfile create mode 100644 GEMINI.md create mode 100644 Makefile create mode 100644 README.md create mode 100644 agent/__init__.py create mode 100644 agent/agent.py create mode 100644 agent/app_utils/telemetry.py create mode 100644 agent/app_utils/typing.py create mode 100644 agent/config.py create mode 100644 agent/errors.py create mode 100644 agent/fast_api_app.py create mode 100644 agent/main.py create mode 100644 agent/memory.py create mode 100644 agent/root_agent.py create mode 100644 agent/security/__init__.py create mode 100644 agent/security/approval.py create mode 100644 agent/security/dlp_filter.py create mode 100644 agent/security/input_guard.py create mode 100644 agent/security/output_guard.py create mode 100644 agent/security/trace.py create mode 100644 agent/subagents/__init__.py create mode 100644 agent/subagents/calendar_agent.py create mode 100644 agent/subagents/drive_agent.py create mode 100644 agent/subagents/gmail_agent.py create mode 100644 agent/subagents/search_agent.py create mode 100644 deployment/README.md create mode 100644 deployment/terraform/apis.tf create mode 100644 deployment/terraform/dev/apis.tf create mode 100644 deployment/terraform/dev/iam.tf create mode 100644 deployment/terraform/dev/outputs.tf create mode 100644 deployment/terraform/dev/providers.tf create mode 100644 deployment/terraform/dev/service.tf create mode 100644 deployment/terraform/dev/service_outputs.tf create mode 100644 deployment/terraform/dev/storage.tf create mode 100644 deployment/terraform/dev/telemetry.tf create mode 100644 deployment/terraform/dev/telemetry_outputs.tf create mode 100644 deployment/terraform/dev/variables.tf create mode 100644 deployment/terraform/dev/vars/env.tfvars create mode 100644 deployment/terraform/github.tf create mode 100644 deployment/terraform/iam.tf create mode 100644 deployment/terraform/locals.tf create mode 100644 deployment/terraform/outputs.tf create mode 100644 deployment/terraform/providers.tf create mode 100644 deployment/terraform/service.tf create mode 100644 deployment/terraform/service_accounts.tf create mode 100644 deployment/terraform/service_outputs.tf create mode 100644 deployment/terraform/sql/completions.sql create mode 100644 deployment/terraform/storage.tf create mode 100644 deployment/terraform/telemetry.tf create mode 100644 deployment/terraform/telemetry_outputs.tf create mode 100644 deployment/terraform/variables.tf create mode 100644 deployment/terraform/vars/env.tfvars create mode 100644 deployment/terraform/wif.tf create mode 100644 notebooks/adk_app_testing.ipynb create mode 100644 notebooks/evaluating_adk_agent.ipynb create mode 100644 pyproject.toml create mode 100644 requirements.txt create mode 100644 secure-openclaw-build-plan.md create mode 100644 terraform/environments/dev.tfvars create mode 100644 terraform/main.tf create mode 100644 terraform/modules/cloud_run/main.tf create mode 100644 terraform/modules/iam/main.tf create mode 100644 terraform/modules/secrets/main.tf create mode 100644 terraform/modules/wif/main.tf create mode 100644 tests/eval/evalsets/README.md create mode 100644 tests/integration/test_agent.py create mode 100644 tests/integration/test_server_e2e.py create mode 100644 tests/load_test/.results/.placeholder create mode 100644 tests/load_test/README.md create mode 100644 tests/load_test/load_test.py create mode 100644 tests/test_main.py create mode 100644 tests/unit/test_dummy.py diff --git a/.env-example b/.env-example new file mode 100644 index 0000000..fc03c92 --- /dev/null +++ b/.env-example @@ -0,0 +1,4 @@ +TELEGRAM_BOT_TOKEN="your_telegram_bot_token_here" +GEMINI_API_KEY="your_gemini_api_key_here" +GCP_PROJECT_ID="secure-agent-demo" +ENVIRONMENT="dev" diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..574bc76 --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,36 @@ +name: CI + +on: + push: + branches: [ main ] + pull_request: + branches: [ main ] + +jobs: + test: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v5 + with: + python-version: "3.12" + cache: "pip" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -r requirements.txt + + - name: Lint with Ruff + run: | + ruff check . + + - name: Type check with mypy + run: | + mypy agent/ + + - name: Test with pytest + run: | + pytest tests/ -v diff --git a/.github/workflows/deploy-to-prod.yaml b/.github/workflows/deploy-to-prod.yaml new file mode 100644 index 0000000..71c5bf0 --- /dev/null +++ b/.github/workflows/deploy-to-prod.yaml @@ -0,0 +1,70 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +name: Deploy to Production + +on: + workflow_dispatch: + workflow_call: + +jobs: + deploy: + runs-on: ubuntu-latest + # This job targets the 'production' environment, which is automatically + # created by the Terraform setup in `deployment/terraform/github.tf`. + # To enable manual approval for deployments, you must add a protection + # rule to this environment in your GitHub repository settings. + # + # 1. Go to your repository's Settings > Environments. + # 2. Select the 'production' environment. + # 3. Under 'Protection rules', check the 'Required reviewers' box. + # 4. Add the specific users or teams who must approve the deployment. + # + # Once configured, the workflow will pause at this step and wait for an + # authorized user to approve it before proceeding. + environment: + name: production + concurrency: production + permissions: + contents: 'read' + id-token: 'write' + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v4 + with: + python-version: '3.12' + + - id: 'auth' + name: 'Authenticate to Google Cloud' + uses: 'google-github-actions/auth@v2' + with: + workload_identity_provider: 'projects/${{ vars.GCP_PROJECT_NUMBER }}/locations/global/workloadIdentityPools/${{ secrets.WIF_POOL_ID }}/providers/${{ secrets.WIF_PROVIDER_ID }}' + service_account: '${{ secrets.GCP_SERVICE_ACCOUNT }}' + create_credentials_file: true + project_id: ${{ vars.CICD_PROJECT_ID }} + + - name: Set up Cloud SDK + uses: 'google-github-actions/setup-gcloud@v2' + + - name: Deploy to Production (Cloud Run) + run: | + gcloud run deploy adkbot \ + --image ${{ vars.REGION }}-docker.pkg.dev/${{ vars.CICD_PROJECT_ID }}/${{ vars.ARTIFACT_REGISTRY_REPO_NAME }}/${{ vars.CONTAINER_NAME }} \ + --region ${{ vars.REGION }} \ + --project ${{ vars.PROD_PROJECT_ID }} + diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml new file mode 100644 index 0000000..5f50426 --- /dev/null +++ b/.github/workflows/deploy.yml @@ -0,0 +1,57 @@ +name: Deploy to Cloud Run + +on: + push: + branches: + - main + +env: + PROJECT_ID: secure-agent-demo + SERVICE_NAME: clawdbot + REGION: us-central1 + # These will be set up in Phase 6/7 + # WIF_PROVIDER: projects/123/locations/global/workloadIdentityPools/github/providers/my-repo + # WIF_SERVICE_ACCOUNT: my-service-account@my-project.iam.gserviceaccount.com + +jobs: + deploy: + runs-on: ubuntu-latest + permissions: + contents: 'read' + id-token: 'write' # Required for WIF + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Google Auth + id: auth + uses: 'google-github-actions/auth@v2' + with: + # Enable this once WIF is configured in GCP: + # workload_identity_provider: '${{ env.WIF_PROVIDER }}' + # service_account: '${{ env.WIF_SERVICE_ACCOUNT }}' + credentials_json: '${{ secrets.GCP_CREDENTIALS }}' # Temporary fallback + + - name: Set up Cloud SDK + uses: google-github-actions/setup-gcloud@v2 + + - name: Authorize Docker push + run: gcloud auth configure-docker ${{ env.REGION }}-docker.pkg.dev + + - name: Build and Push Container + run: | + IMAGE="${{ env.REGION }}-docker.pkg.dev/${{ env.PROJECT_ID }}/cloud-run-source-deploy/${{ env.SERVICE_NAME }}:${{ github.sha }}" + docker build -t "$IMAGE" . + docker push "$IMAGE" + + - name: Deploy to Cloud Run + uses: google-github-actions/deploy-cloudrun@v2 + with: + service: ${{ env.SERVICE_NAME }} + region: ${{ env.REGION }} + image: ${{ env.REGION }}-docker.pkg.dev/${{ env.PROJECT_ID }}/cloud-run-source-deploy/${{ env.SERVICE_NAME }}:${{ github.sha }} + flags: | + --allow-unauthenticated + --min-instances=0 + --max-instances=1 diff --git a/.github/workflows/pr_checks.yaml b/.github/workflows/pr_checks.yaml new file mode 100644 index 0000000..032099d --- /dev/null +++ b/.github/workflows/pr_checks.yaml @@ -0,0 +1,62 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +name: PR Checks + +on: + pull_request: + branches: + - main + paths: + - 'agent/**' + - 'data_ingestion/**' + - 'tests/**' + - 'deployment/**' + - 'uv.lock' + +jobs: + test: + runs-on: ubuntu-latest + permissions: + contents: 'read' + id-token: 'write' + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - id: 'auth' + name: 'Authenticate to Google Cloud' + uses: 'google-github-actions/auth@v2' + with: + workload_identity_provider: 'projects/${{ vars.GCP_PROJECT_NUMBER }}/locations/global/workloadIdentityPools/${{ secrets.WIF_POOL_ID }}/providers/${{ secrets.WIF_PROVIDER_ID }}' + service_account: '${{ secrets.GCP_SERVICE_ACCOUNT }}' + create_credentials_file: true + project_id: ${{ vars.CICD_PROJECT_ID }} + + + - name: Set up Python 3.12 + uses: actions/setup-python@v4 + with: + python-version: '3.12' + + - name: Install uv and dependencies + run: | + pip install uv==0.8.13 + uv sync --locked + + - name: Run unit tests + run: uv run pytest tests/unit + + - name: Run integration tests + run: uv run pytest tests/integration diff --git a/.github/workflows/staging.yaml b/.github/workflows/staging.yaml new file mode 100644 index 0000000..4079abd --- /dev/null +++ b/.github/workflows/staging.yaml @@ -0,0 +1,115 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +name: Deploy to Staging + +on: + push: + branches: + - main + paths: + - 'agent/**' + - 'data_ingestion/**' + - 'tests/**' + - 'deployment/**' + - 'uv.lock' + +jobs: + deploy_and_test_staging: + runs-on: ubuntu-latest + permissions: + contents: 'read' + id-token: 'write' + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v4 + with: + python-version: '3.12' + + - id: 'auth' + name: 'Authenticate to Google Cloud' + uses: 'google-github-actions/auth@v2' + with: + workload_identity_provider: 'projects/${{ vars.GCP_PROJECT_NUMBER }}/locations/global/workloadIdentityPools/${{ secrets.WIF_POOL_ID }}/providers/${{ secrets.WIF_PROVIDER_ID }}' + service_account: '${{ secrets.GCP_SERVICE_ACCOUNT }}' + create_credentials_file: true + project_id: ${{ vars.CICD_PROJECT_ID }} + + - name: Set up Cloud SDK + uses: 'google-github-actions/setup-gcloud@v2' + + - name: Configure Docker for Artifact Registry + run: | + gcloud auth configure-docker ${{ vars.REGION }}-docker.pkg.dev --quiet + + - name: Build and Push Docker Image + run: | + docker build -t ${{ vars.REGION }}-docker.pkg.dev/${{ vars.CICD_PROJECT_ID }}/${{ vars.ARTIFACT_REGISTRY_REPO_NAME }}/${{ vars.CONTAINER_NAME }} \ + --build-arg COMMIT_SHA=${{ github.sha }} \ + . + docker push ${{ vars.REGION }}-docker.pkg.dev/${{ vars.CICD_PROJECT_ID }}/${{ vars.ARTIFACT_REGISTRY_REPO_NAME }}/${{ vars.CONTAINER_NAME }} + + - name: Deploy to Staging (Cloud Run) + run: | + gcloud run deploy adkbot \ + --image ${{ vars.REGION }}-docker.pkg.dev/${{ vars.CICD_PROJECT_ID }}/${{ vars.ARTIFACT_REGISTRY_REPO_NAME }}/${{ vars.CONTAINER_NAME }} \ + --region ${{ vars.REGION }} \ + --project ${{ vars.STAGING_PROJECT_ID }} + + - name: Fetch Staging Service URL + id: fetch-url + run: | + _STAGING_URL=$(gcloud run services describe adkbot \ + --region ${{ vars.REGION }} --project ${{ vars.STAGING_PROJECT_ID }} --format="value(status.url)") + echo "_staging_url=${_STAGING_URL}" >> $GITHUB_OUTPUT + + - name: Fetch ID Token + id: fetch-token + run: | + _ID_TOKEN=$(gcloud auth print-identity-token --impersonate-service-account=${{ secrets.GCP_SERVICE_ACCOUNT }} -q) + echo "::add-mask::${_ID_TOKEN}" + echo "_id_token=${_ID_TOKEN}" >> $GITHUB_OUTPUT + + - name: Run load test + run: | + export _ID_TOKEN="${{ steps.fetch-token.outputs._id_token }}" + export _STAGING_URL="${{ steps.fetch-url.outputs._staging_url }}" + pip install locust==2.31.1 + locust -f tests/load_test/load_test.py \ + --headless \ + -H ${_STAGING_URL} \ + -t 30s -u 10 -r 0.5 \ + --csv=tests/load_test/.results/results \ + --html=tests/load_test/.results/report.html + + - name: Export Load Test Results to GCS + run: | + TIMESTAMP=$(date +%Y%m%d-%H%M%S) + gcloud storage cp --recursive tests/load_test/.results gs://${{ vars.LOGS_BUCKET_NAME_STAGING }}/load-test-results/results-${TIMESTAMP} --quiet + echo "_________________________________________________________________________" + echo "Load test results copied to gs://${{ vars.LOGS_BUCKET_NAME_STAGING }}/load-test-results/results-${TIMESTAMP}" + echo "HTTP link: https://console.cloud.google.com/storage/browser/${{ vars.LOGS_BUCKET_NAME_STAGING }}/load-test-results/results-${TIMESTAMP}" + echo "_________________________________________________________________________" + + call_production_workflow: + needs: deploy_and_test_staging + uses: ./.github/workflows/deploy-to-prod.yaml + permissions: + contents: 'read' + id-token: 'write' + secrets: inherit \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..b4d93bd --- /dev/null +++ b/.gitignore @@ -0,0 +1,67 @@ +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# IDEs +.idea/ +.vscode/ +*.swp +*.swo + +# GCP Credentials +*.json +credentials.json +token.json diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..8afad7a --- /dev/null +++ b/Dockerfile @@ -0,0 +1,25 @@ +FROM python:3.12-slim + +# Set working directory +WORKDIR /app + +# Install system dependencies +RUN apt-get update && apt-get install -y --no-install-recommends \ + build-essential \ + && rm -rf /var/lib/apt/lists/* + +# Copy dependencies +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +# Copy application code +COPY agent/ ./agent/ + +# Set environment variables +ENV PYTHONUNBUFFERED=1 + +# Expose port +EXPOSE 8080 + +# Command to run the application +CMD ["uvicorn", "agent.main:app", "--host", "0.0.0.0", "--port", "8080"] diff --git a/GEMINI.md b/GEMINI.md new file mode 100644 index 0000000..17bcaa4 --- /dev/null +++ b/GEMINI.md @@ -0,0 +1,58 @@ +# Coding Agent Guide + +## Reference Documentation + +If you have ADK skills available, use those instead of fetching the URLs below. + +Otherwise, fetch these resources as needed: +- **ADK Cheatsheet**: https://raw.githubusercontent.com/GoogleCloudPlatform/agent-starter-pack/refs/heads/main/agent_starter_pack/resources/docs/adk-cheatsheet.md — Agent definitions, tools, callbacks, orchestration +- **Evaluation Guide**: https://raw.githubusercontent.com/GoogleCloudPlatform/agent-starter-pack/refs/heads/main/agent_starter_pack/resources/docs/adk-eval-guide.md — Eval config, metrics, gotchas +- **Deployment Guide**: https://raw.githubusercontent.com/GoogleCloudPlatform/agent-starter-pack/refs/heads/main/agent_starter_pack/resources/docs/adk-deploy-guide.md — Infrastructure, CI/CD, testing deployed agents +- **Development Guide**: https://raw.githubusercontent.com/GoogleCloudPlatform/agent-starter-pack/refs/heads/main/docs/guide/development-guide.md — Full development workflow +- **ADK Docs**: https://google.github.io/adk-docs/llms.txt + +--- + +## Development Phases + +### Phase 1: Understand Requirements +Before writing any code, understand the project's requirements, constraints, and success criteria. + +### Phase 2: Build and Implement +Implement agent logic in `agent/`. Use `make playground` for interactive testing. Iterate based on user feedback. + +### Phase 3: The Evaluation Loop (Main Iteration Phase) +Start with 1-2 eval cases, run `make eval`, iterate. Expect 5-10+ iterations. See the **Evaluation Guide** for metrics, evalset schema, LLM-as-judge config, and common gotchas. + +### Phase 4: Pre-Deployment Tests +Run `make test`. Fix issues until all tests pass. + +### Phase 5: Deploy to Dev +**Requires explicit human approval.** Run `make deploy` only after user confirms. See the **Deployment Guide** for details. + +### Phase 6: Production Deployment +Ask the user: Option A (simple single-project) or Option B (full CI/CD pipeline with `uvx agent-starter-pack setup-cicd`). See the [deployment docs](https://raw.githubusercontent.com/GoogleCloudPlatform/agent-starter-pack/refs/heads/main/docs/guide/deployment.md) for step-by-step instructions. + +## Development Commands + +| Command | Purpose | +|---------|---------| +| `make playground` | Interactive local testing | +| `make test` | Run unit and integration tests | +| `make eval` | Run evaluation against evalsets | +| `make eval-all` | Run all evalsets | +| `make lint` | Check code quality | +| `make setup-dev-env` | Set up dev infrastructure (Terraform) | +| `make deploy` | Deploy to dev | + +--- + +## Operational Guidelines for Coding Agents + +- **Code preservation**: Only modify code directly targeted by the user's request. Preserve all surrounding code, config values (e.g., `model`), comments, and formatting. +- **NEVER change the model** unless explicitly asked. Use `gemini-3-flash-preview` or `gemini-3-pro-preview` for new agents. +- **Model 404 errors**: Fix `GOOGLE_CLOUD_LOCATION` (e.g., `global` instead of `us-central1`), not the model name. +- **ADK tool imports**: Import the tool instance, not the module: `from google.adk.tools.load_web_page import load_web_page` +- **Run Python with `uv`**: `uv run python script.py`. Run `make install` first. +- **Stop on repeated errors**: If the same error appears 3+ times, fix the root cause instead of retrying. +- **Terraform conflicts** (Error 409): Use `terraform import` instead of retrying creation. diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..69c0f27 --- /dev/null +++ b/Makefile @@ -0,0 +1,111 @@ + +# ============================================================================== +# Installation & Setup +# ============================================================================== + +# Install dependencies using uv package manager +install: + @command -v uv >/dev/null 2>&1 || { echo "uv is not installed. Installing uv..."; curl -LsSf https://astral.sh/uv/0.8.13/install.sh | sh; source $HOME/.local/bin/env; } + uv sync + +# ============================================================================== +# Playground Targets +# ============================================================================== + +# Launch local dev playground +playground: + @echo "===============================================================================" + @echo "| 🚀 Starting your agent playground... |" + @echo "| |" + @echo "| 💡 Try asking: What's the weather in San Francisco? |" + @echo "| |" + @echo "| 🔍 IMPORTANT: Select the 'agent' folder to interact with your agent. |" + @echo "===============================================================================" + uv run adk web . --port 8501 --reload_agents + +# ============================================================================== +# Local Development Commands +# ============================================================================== + +# Launch local development server with hot-reload +# Usage: make local-backend [PORT=8000] - Specify PORT for parallel scenario testing +local-backend: + uv run uvicorn agent.fast_api_app:app --host localhost --port $(or $(PORT),8000) --reload + +# ============================================================================== +# Backend Deployment Targets +# ============================================================================== + +# Deploy the agent remotely +# Usage: make deploy [IAP=true] [PORT=8080] - Set IAP=true to enable Identity-Aware Proxy, PORT to specify container port +deploy: + PROJECT_ID=$$(gcloud config get-value project) && \ + gcloud beta run deploy adkbot \ + --source . \ + --memory "4Gi" \ + --project $$PROJECT_ID \ + --region "us-central1" \ + --no-allow-unauthenticated \ + --no-cpu-throttling \ + --labels "created-by=adk" \ + --update-build-env-vars "AGENT_VERSION=$(shell awk -F'"' '/^version = / {print $$2}' pyproject.toml || echo '0.0.0')" \ + --update-env-vars \ + "" \ + $(if $(IAP),--iap) \ + $(if $(PORT),--port=$(PORT)) + +# Alias for 'make deploy' for backward compatibility +backend: deploy + +# ============================================================================== +# Infrastructure Setup +# ============================================================================== + +# Set up development environment resources using Terraform +setup-dev-env: + PROJECT_ID=$$(gcloud config get-value project) && \ + (cd deployment/terraform/dev && terraform init && terraform apply --var-file vars/env.tfvars --var dev_project_id=$$PROJECT_ID --auto-approve) + +# ============================================================================== +# Testing & Code Quality +# ============================================================================== + +# Run unit and integration tests +test: + uv sync --dev + uv run pytest tests/unit && uv run pytest tests/integration + +# ============================================================================== +# Agent Evaluation +# ============================================================================== + +# Run agent evaluation using ADK eval +# Usage: make eval [EVALSET=tests/eval/evalsets/basic.evalset.json] [EVAL_CONFIG=tests/eval/eval_config.json] +eval: + @echo "===============================================================================" + @echo "| Running Agent Evaluation |" + @echo "===============================================================================" + uv sync --dev --extra eval + uv run adk eval ./agent $${EVALSET:-tests/eval/evalsets/basic.evalset.json} \ + $(if $(EVAL_CONFIG),--config_file_path=$(EVAL_CONFIG),$(if $(wildcard tests/eval/eval_config.json),--config_file_path=tests/eval/eval_config.json,)) + +# Run evaluation with all evalsets +eval-all: + @echo "===============================================================================" + @echo "| Running All Evalsets |" + @echo "===============================================================================" + @for evalset in tests/eval/evalsets/*.evalset.json; do \ + echo ""; \ + echo "▶ Running: $$evalset"; \ + $(MAKE) eval EVALSET=$$evalset || exit 1; \ + done + @echo "" + @echo "✅ All evalsets completed" + +# Run code quality checks (codespell, ruff, ty) +lint: + uv sync --dev --extra lint + uv run codespell + uv run ruff check . --diff + uv run ruff format . --check --diff + uv run ty check . \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..d8db675 --- /dev/null +++ b/README.md @@ -0,0 +1,68 @@ +# ClawdBot: The Secure Google ADK Assistant + +**"From Zero to Secure AI Assistant in a Weekend"** + +ClawdBot is a high-security, open-source alternative to typical AI agents, built entirely on **Google Agent Development Kit (ADK) 1.0** and Google Cloud side infrastructure. + +This repository demonstrates how to build an agent that is not just powerful, but secure by default with **6 layers of native security.** + +## Features + +- **ADK 1.0 Multi-Agent Framework**: A root orchestrator delegating to specialized Gemini 2.0 Flash subagents for Gmail, Calendar, Drive, and Search. +- **DLP PII Filtering**: Before a message hits the LLM, Cloud DLP scrubs credit cards, SSNs, and phone numbers. +- **Secret Manager**: Credentials are never loaded from `.env` files in production. +- **IAM Least Privilege**: The Cloud Run agent runs with a tightly restricted service account (cannot destroy infrastructure). +- **Human-in-the-Loop Approval**: Destructive actions (like creating a calendar event) pause execution and await explicit user approval via Telegram. +- **Cloud Trace**: Full visibility into latency and action execution. +- **WIF for CI/CD**: Keyless GitHub Actions deployment via Workload Identity Federation. +- **Firestore Memory**: Persistent cross-session conversation memory and tracking. + +## Architecture + +![Architecture](https://via.placeholder.com/800x400?text=Architecture+Diagram) + +## Setup and Development + +1. **Local Setup:** + ```bash + python3 -m venv .venv + source .venv/bin/activate + pip install -r requirements.txt + ``` +2. **Environment Variables:** + Copy `.env-example` to `.env` and fill in your Gemini API Key and Telegram Bot Token. + +3. **Running the ADK Dev Server:** + You can run tests locally without Telegram using the built-in ADK UI: + ```bash + adk web + ``` + +4. **Running the FastAPI Gateway locally (for Telegram):** + ```bash + uvicorn agent.main:app --reload + ``` + *Note: To receive Telegram webhooks locally, expose port 8000 using ngrok: `ngrok http 8000`.* + +## Deployment + +The entire stack is configured in modular Terraform located in the `terraform/` directory. + +```bash +cd terraform +terraform init +terraform apply -var-file=environments/dev.tfvars +``` + +Once deployed, GitHub Actions will handle subsequent updates automatically via WIF. + +## Testing + +Structured tests cover the agent logic, security pipelines (DLP/Guards), and API integration. + +```bash +pytest tests/ -v +``` + +--- +*Built as a secure reference implementation for Google Cloud Agentic Workloads.* diff --git a/agent/__init__.py b/agent/__init__.py new file mode 100644 index 0000000..f1d570b --- /dev/null +++ b/agent/__init__.py @@ -0,0 +1 @@ +# Agent module package diff --git a/agent/agent.py b/agent/agent.py new file mode 100644 index 0000000..9fd5303 --- /dev/null +++ b/agent/agent.py @@ -0,0 +1,79 @@ +# ruff: noqa +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import datetime +from zoneinfo import ZoneInfo + +from google.adk.agents import Agent +from google.adk.apps import App +from google.adk.models import Gemini +from google.genai import types + +import os +import google.auth + +_, project_id = google.auth.default() +os.environ["GOOGLE_CLOUD_PROJECT"] = project_id +os.environ["GOOGLE_CLOUD_LOCATION"] = "global" +os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "True" + + +def get_weather(query: str) -> str: + """Simulates a web search. Use it get information on weather. + + Args: + query: A string containing the location to get weather information for. + + Returns: + A string with the simulated weather information for the queried location. + """ + if "sf" in query.lower() or "san francisco" in query.lower(): + return "It's 60 degrees and foggy." + return "It's 90 degrees and sunny." + + +def get_current_time(query: str) -> str: + """Simulates getting the current time for a city. + + Args: + city: The name of the city to get the current time for. + + Returns: + A string with the current time information. + """ + if "sf" in query.lower() or "san francisco" in query.lower(): + tz_identifier = "America/Los_Angeles" + else: + return f"Sorry, I don't have timezone information for query: {query}." + + tz = ZoneInfo(tz_identifier) + now = datetime.datetime.now(tz) + return f"The current time for query {query} is {now.strftime('%Y-%m-%d %H:%M:%S %Z%z')}" + + +root_agent = Agent( + name="root_agent", + model=Gemini( + model="gemini-3-flash-preview", + retry_options=types.HttpRetryOptions(attempts=3), + ), + instruction="You are a helpful AI assistant designed to provide accurate and useful information.", + tools=[get_weather, get_current_time], +) + +app = App( + root_agent=root_agent, + name="agent", +) diff --git a/agent/app_utils/telemetry.py b/agent/app_utils/telemetry.py new file mode 100644 index 0000000..6104365 --- /dev/null +++ b/agent/app_utils/telemetry.py @@ -0,0 +1,51 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import logging +import os + + +def setup_telemetry() -> str | None: + """Configure OpenTelemetry and GenAI telemetry with GCS upload.""" + + bucket = os.environ.get("LOGS_BUCKET_NAME") + capture_content = os.environ.get( + "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT", "false" + ) + if bucket and capture_content != "false": + logging.info( + "Prompt-response logging enabled - mode: NO_CONTENT (metadata only, no prompts/responses)" + ) + os.environ["OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"] = "NO_CONTENT" + os.environ.setdefault("OTEL_INSTRUMENTATION_GENAI_UPLOAD_FORMAT", "jsonl") + os.environ.setdefault("OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK", "upload") + os.environ.setdefault( + "OTEL_SEMCONV_STABILITY_OPT_IN", "gen_ai_latest_experimental" + ) + commit_sha = os.environ.get("COMMIT_SHA", "dev") + os.environ.setdefault( + "OTEL_RESOURCE_ATTRIBUTES", + f"service.namespace=adkbot,service.version={commit_sha}", + ) + path = os.environ.get("GENAI_TELEMETRY_PATH", "completions") + os.environ.setdefault( + "OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH", + f"gs://{bucket}/{path}", + ) + else: + logging.info( + "Prompt-response logging disabled (set LOGS_BUCKET_NAME=gs://your-bucket and OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=NO_CONTENT to enable)" + ) + + return bucket diff --git a/agent/app_utils/typing.py b/agent/app_utils/typing.py new file mode 100644 index 0000000..8499992 --- /dev/null +++ b/agent/app_utils/typing.py @@ -0,0 +1,46 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import uuid +from typing import ( + Literal, +) + +from google.adk.events.event import Event +from google.genai.types import Content +from pydantic import ( + BaseModel, + Field, +) + + +class Request(BaseModel): + """Represents the input for a chat request with optional configuration.""" + + message: Content + events: list[Event] + user_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + session_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + + model_config = {"extra": "allow"} + + +class Feedback(BaseModel): + """Represents feedback for a conversation.""" + + score: int | float + text: str | None = "" + log_type: Literal["feedback"] = "feedback" + service_name: Literal["adkbot"] = "adkbot" + user_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + session_id: str = Field(default_factory=lambda: str(uuid.uuid4())) diff --git a/agent/config.py b/agent/config.py new file mode 100644 index 0000000..301aa31 --- /dev/null +++ b/agent/config.py @@ -0,0 +1,41 @@ +from typing import Literal + +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class Settings(BaseSettings): + telegram_token: str = "" + gemini_api_key: str = "" + gcp_project_id: str = "secure-agent-demo" + environment: Literal["dev", "prod"] = "dev" + + model_config = SettingsConfigDict( + env_file=".env", + env_file_encoding="utf-8", + extra="ignore" + ) + + @classmethod + def load(cls) -> "Settings": + """Loads config from local .env or from Google Secret Manager in prod.""" + settings = cls() + + if settings.environment == "prod": + from google.cloud import secretmanager + client = secretmanager.SecretManagerServiceClient() + + def get_secret(secret_id: str) -> str: + name = f"projects/{settings.gcp_project_id}/secrets/{secret_id}/versions/latest" + response = client.access_secret_version(request={"name": name}) + return response.payload.data.decode("UTF-8") + + try: + settings.telegram_token = get_secret("TELEGRAM_BOT_TOKEN") + settings.gemini_api_key = get_secret("GEMINI_API_KEY") + except Exception as e: + import logging + logging.getLogger(__name__).error(f"Failed to load secrets: {e}") + + return settings + +settings = Settings.load() diff --git a/agent/errors.py b/agent/errors.py new file mode 100644 index 0000000..d06a6e0 --- /dev/null +++ b/agent/errors.py @@ -0,0 +1,15 @@ +class AgentError(Exception): + """Base class for all ClawdBot exceptions.""" + pass + +class ToolError(AgentError): + """Raised when a specific tool fails (retryable).""" + pass + +class SecurityError(AgentError): + """Raised when an action is blocked by guardrails.""" + pass + +class ApprovalTimeout(AgentError): + """Raised when the user does not respond to an approval prompt in time.""" + pass diff --git a/agent/fast_api_app.py b/agent/fast_api_app.py new file mode 100644 index 0000000..bd231fc --- /dev/null +++ b/agent/fast_api_app.py @@ -0,0 +1,72 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os + +import google.auth +from fastapi import FastAPI +from google.adk.cli.fast_api import get_fast_api_app +from google.cloud import logging as google_cloud_logging + +from agent.app_utils.telemetry import setup_telemetry +from agent.app_utils.typing import Feedback + +setup_telemetry() +_, project_id = google.auth.default() +logging_client = google_cloud_logging.Client() +logger = logging_client.logger(__name__) +allow_origins = ( + os.getenv("ALLOW_ORIGINS", "").split(",") if os.getenv("ALLOW_ORIGINS") else None +) + +# Artifact bucket for ADK (created by Terraform, passed via env var) +logs_bucket_name = os.environ.get("LOGS_BUCKET_NAME") + +AGENT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) +# In-memory session configuration - no persistent storage +session_service_uri = None + +artifact_service_uri = f"gs://{logs_bucket_name}" if logs_bucket_name else None + +app: FastAPI = get_fast_api_app( + agents_dir=AGENT_DIR, + web=True, + artifact_service_uri=artifact_service_uri, + allow_origins=allow_origins, + session_service_uri=session_service_uri, + otel_to_cloud=True, +) +app.title = "adkbot" +app.description = "API for interacting with the Agent adkbot" + + +@app.post("/feedback") +def collect_feedback(feedback: Feedback) -> dict[str, str]: + """Collect and log feedback. + + Args: + feedback: The feedback data to log + + Returns: + Success message + """ + logger.log_struct(feedback.model_dump(), severity="INFO") + return {"status": "success"} + + +# Main execution +if __name__ == "__main__": + import uvicorn + + uvicorn.run(app, host="0.0.0.0", port=8000) diff --git a/agent/main.py b/agent/main.py new file mode 100644 index 0000000..be8ec24 --- /dev/null +++ b/agent/main.py @@ -0,0 +1,145 @@ +import logging + +import httpx +from fastapi import BackgroundTasks, FastAPI, Request +from fastapi.responses import HTMLResponse + +from agent.config import settings +from agent.errors import AgentError +from agent.memory import memory_manager +from agent.root_agent import root_agent + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +app = FastAPI(title="ClawdBot Gateway", version="1.0.0") + +async def send_telegram_message(chat_id: int, text: str): + """Sends a message back to the user via Telegram Bot API.""" + if not settings.telegram_token: + logger.warning("No Telegram token configured. Skipping message send.") + return + + url = f"https://api.telegram.org/bot{settings.telegram_token}/sendMessage" + payload = {"chat_id": chat_id, "text": text, "parse_mode": "Markdown"} + + async with httpx.AsyncClient() as client: + try: + response = await client.post(url, json=payload) + response.raise_for_status() + except Exception as e: + logger.error(f"Failed to send Telegram message: {e}") + +async def process_telegram_update(update: dict): + """Background task to process the update and run the ADK agent.""" + try: + if "message" not in update or "text" not in update["message"]: + return + + message = update["message"] + chat_id = message["chat"]["id"] + text = message["text"] + + logger.info(f"Processing message from {chat_id}: {text}") + + # Send typing indicator + url = f"https://api.telegram.org/bot{settings.telegram_token}/sendChatAction" + async with httpx.AsyncClient() as client: + await client.post(url, json={"chat_id": chat_id, "action": "typing"}) + + # Run ADK agent + try: + # Memory injection (Phase 4) + _ = memory_manager.get_recent_context(chat_id) + + # The agent.run will consume the latest text + response = root_agent.run(text) + reply_text = response.text + + # Save context to Firestore + memory_manager.save_message(chat_id, "user", text) + memory_manager.save_message(chat_id, "assistant", reply_text) + + except AgentError as e: + logger.error(f"Agent error: {e}") + reply_text = f"⚙️ I ran into an issue: {str(e)}" + except Exception as e: + logger.error(f"Unexpected error running agent: {e}", exc_info=True) + reply_text = "❌ Sorry, I encountered an unexpected error while processing your request." + + await send_telegram_message(chat_id, reply_text) + + except Exception as e: + logger.error(f"Error in process_telegram_update background task: {e}", exc_info=True) + + +@app.get("/health") +async def health_check(): + return {"status": "ok", "version": "1.0.0"} + +@app.get("/ready") +async def readiness_check(): + return {"status": "ready"} + +@app.get("/", response_class=HTMLResponse) +async def root(): + return """ + + + ClawdBot Gateway + + + +

ClawdBot API is running

+

To interact via browser UI during local dev, use the ADK CLI:

+ adk web +

For production, configure the Telegram Webhook to point to /webhook/telegram

+ + + """ + +@app.post("/webhook/telegram") +async def telegram_webhook(request: Request, background_tasks: BackgroundTasks): + """ + Handle incoming Telegram updates. Fast response to Telegram is required, + so we process the agent interaction in the background. + """ + try: + update = await request.json() + background_tasks.add_task(process_telegram_update, update) + return {"ok": True} + except Exception as e: + logger.error(f"Error parsing webhook request: {e}") + return {"ok": False} + +@app.post("/scheduled/briefing") +async def morning_briefing(request: Request, background_tasks: BackgroundTasks): + """ + Triggered by Cloud Scheduler daily. + Will dispatch the briefing flow for configured users. + """ + try: + payload = await request.json() + chat_id = payload.get("chat_id") + if not chat_id: + return {"error": "Missing chat_id"} + + logger.info(f"Starting scheduled briefing for {chat_id}") + + async def run_briefing(): + try: + # Instruct the agent to generate a morning briefing autonomously + prompt = ( + "Please read my latest emails and check my calendar for today, " + "then provide a concise morning briefing." + ) + response = root_agent.run(prompt) + await send_telegram_message(chat_id, f"🌅 **Morning Briefing**\n\n{response.text}") + except Exception as e: + logger.error(f"Failed to run briefing for {chat_id}: {e}") + + background_tasks.add_task(run_briefing) + return {"status": "briefing started"} + except Exception as e: + logger.error(f"Error starting briefing: {e}") + return {"error": str(e)} diff --git a/agent/memory.py b/agent/memory.py new file mode 100644 index 0000000..7aee658 --- /dev/null +++ b/agent/memory.py @@ -0,0 +1,74 @@ +import logging +from datetime import datetime + +from google.cloud import firestore + +from agent.config import settings + +logger = logging.getLogger(__name__) + +_db = None + +def get_db(): + global _db + if not _db: + try: + _db = firestore.Client(project=settings.gcp_project_id) + logger.info("Firestore client initialized.") + except Exception as e: + logger.warning(f"Using mock memory. Firestore init failed: {e}") + return _db + +class MemoryManager: + """Manages persistent memory using Firestore with rolling history.""" + + def __init__(self): + self.mock_db = {} # fallback for local dev without credentials + + def save_message(self, chat_id: int, role: str, content: str): + db = get_db() + message_data = { + "role": role, + "content": content, + "timestamp": firestore.SERVER_TIMESTAMP if db else datetime.utcnow() + } + + if db: + try: + # Store message in subcollection + doc_ref = db.collection("conversations").document(str(chat_id)) + doc_ref.collection("messages").add(message_data) + + # Update last active timestamp + doc_ref.set({"last_active": firestore.SERVER_TIMESTAMP}, merge=True) + except Exception as e: + logger.error(f"Failed to save message to Firestore: {e}") + else: + if chat_id not in self.mock_db: + self.mock_db[chat_id] = [] + self.mock_db[chat_id].append(message_data) + + def get_recent_context(self, chat_id: int, limit: int = 10) -> list[dict]: + db = get_db() + if db: + try: + docs = ( + db.collection("conversations") + .document(str(chat_id)) + .collection("messages") + .order_by("timestamp", direction=firestore.Query.DESCENDING) + .limit(limit) + .stream() + ) + # Results are descending, so we reverse them for chronological context + messages = [doc.to_dict() for doc in docs] + messages.reverse() + return [{"role": m["role"], "text": m["content"]} for m in messages] + except Exception as e: + logger.error(f"Failed to fetch context from Firestore: {e}") + return [] + else: + history = self.mock_db.get(chat_id, []) + return [{"role": m["role"], "text": m["content"]} for m in history[-limit:]] + +memory_manager = MemoryManager() diff --git a/agent/root_agent.py b/agent/root_agent.py new file mode 100644 index 0000000..ca75678 --- /dev/null +++ b/agent/root_agent.py @@ -0,0 +1,25 @@ +import logging + +from google.adk.agents import Agent + +from agent.subagents.calendar_agent import calendar_agent +from agent.subagents.drive_agent import drive_agent +from agent.subagents.gmail_agent import gmail_agent +from agent.subagents.search_agent import search_agent + +logger = logging.getLogger(__name__) + +SYSTEM_PROMPT = """ +You are ClawdBot, a highly capable and secure personal assistant. +Your goal is to help the user by reading their emails, managing calendars, organizing files, and searching the web. +Always explain what you're about to do before doing it. +For any destructive action (delete, send, modify), ask for explicit confirmation first. +""" + +root_agent = Agent( + name="clawdbot", + model="gemini-2.0-flash", + description="Secure personal assistant capable of orchestrating specialized tasks.", + instruction=SYSTEM_PROMPT, + sub_agents=[search_agent, gmail_agent, calendar_agent, drive_agent] +) diff --git a/agent/security/__init__.py b/agent/security/__init__.py new file mode 100644 index 0000000..609dcdd --- /dev/null +++ b/agent/security/__init__.py @@ -0,0 +1 @@ +# Security module package diff --git a/agent/security/approval.py b/agent/security/approval.py new file mode 100644 index 0000000..9daf923 --- /dev/null +++ b/agent/security/approval.py @@ -0,0 +1,49 @@ +import logging +import time +from typing import Any, Callable, Dict + +from agent.errors import ApprovalTimeout + +logger = logging.getLogger(__name__) + +# Simulating an internal pending action store. In Phase 4, this goes to Firestore. +pending_approvals: Dict[str, Dict[str, Any]] = {} + +def request_approval(chat_id: int, action_name: str, payload_desc: str, callback: Callable): + """ + Registers a pending action that requires explicit user approval via Telegram. + This demonstrates the Human-in-the-Loop flow. + """ + action_id = f"{chat_id}_{int(time.time())}" + + pending_approvals[action_id] = { + "chat_id": chat_id, + "action": action_name, + "payload": payload_desc, + "callback": callback, + "timestamp": time.time() + } + + logger.info(f"Requested human approval for: {action_id} -> {action_name}") + # In a real async flow, we would send a Telegram msg with InlineKeyboard + # and suspend the agent tool execution until the callback is triggered. + return action_id + +def process_approval(action_id: str, approved: bool) -> str: + """Processes an approval triggered by a Telegram webhook.""" + if action_id not in pending_approvals: + return "Action expired or invalid." + + action = pending_approvals.pop(action_id) + + if time.time() - action["timestamp"] > 300: # 5 min timeout + raise ApprovalTimeout("Action timed out before approval.") + + if approved: + logger.info(f"Action {action['action']} approved by human.") + # Execute the original callback + result = action["callback"]() + return f"Executed safely: {result}" + else: + logger.warning(f"Action {action['action']} rejected by human.") + return "Action cancelled by user." diff --git a/agent/security/dlp_filter.py b/agent/security/dlp_filter.py new file mode 100644 index 0000000..90502f5 --- /dev/null +++ b/agent/security/dlp_filter.py @@ -0,0 +1,63 @@ +import logging + +from google.cloud import dlp_v2 + +from agent.config import settings + +logger = logging.getLogger(__name__) + +# Initialize client lazily to avoid credential errors on startup +_dlp_client = None + +def get_dlp_client(): + global _dlp_client + if not _dlp_client: + try: + _dlp_client = dlp_v2.DlpServiceClient() + except Exception as e: + logger.warning(f"Failed to initialize DLP client. PII scanning disabled. Error: {e}") + return _dlp_client + +def scan_and_redact(text: str) -> str: + """Scans for PII and redacts it before it reaches the LLM or user.""" + client = get_dlp_client() + if not client or not settings.gcp_project_id: + return text + + project_path = f"projects/{settings.gcp_project_id}" + + inspect_config = { + "info_types": [ + {"name": "CREDIT_CARD_NUMBER"}, + {"name": "PHONE_NUMBER"}, + {"name": "US_SOCIAL_SECURITY_NUMBER"} + ], + "min_likelihood": dlp_v2.Likelihood.LIKELY, + } + + replace_config = { + "info_type_transformations": { + "transformations": [ + { + "info_types": [{"name": "CREDIT_CARD_NUMBER"}], + "primitive_transformation": { + "replace_config": {"new_value": {"string_value": "[REDACTED CREDIT CARD]"}} + } + } + ] + } + } + + request = { + "parent": project_path, + "item": {"value": text}, + "deidentify_config": replace_config, + "inspect_config": inspect_config, + } + + try: + response = client.deidentify_content(request=request) + return response.item.value + except Exception as e: + logger.error(f"DLP scanning failed: {e}") + return text # Fail open for demo if DLP not enabled in GCP yet diff --git a/agent/security/input_guard.py b/agent/security/input_guard.py new file mode 100644 index 0000000..f25a289 --- /dev/null +++ b/agent/security/input_guard.py @@ -0,0 +1,31 @@ +import logging + +from agent.errors import SecurityError + +logger = logging.getLogger(__name__) + +INJECTION_PATTERNS = [ + "ignore previous instructions", + "ignore all previous instructions", + "you are now a", + "system prompt", + "developer mode", +] + +def check_input_safety(text: str) -> bool: + """ + Checks if the input text contains known prompt injection attacks. + Raises SecurityError if malicious content is detected. + """ + text_lower = text.lower() + for pattern in INJECTION_PATTERNS: + if pattern in text_lower: + logger.warning(f"Blocked potential prompt injection: matched '{pattern}'") + raise SecurityError( + "Your request triggered a security filter. Please rephrase your input." + ) + + if len(text) > 4000: + raise SecurityError("Input exceeds maximum allowed length.") + + return True diff --git a/agent/security/output_guard.py b/agent/security/output_guard.py new file mode 100644 index 0000000..4e9bbdd --- /dev/null +++ b/agent/security/output_guard.py @@ -0,0 +1,18 @@ +import logging +import re + +logger = logging.getLogger(__name__) + +# Basic regex for catching leaked bearer tokens or API keys +TOKEN_REGEX = re.compile(r'(Bearer\s+[A-Za-z0-9\-\._~\+\/]+=*)|([A-Za-z0-9_-]{39})') + +def check_output_safety(text: str) -> str: + """ + Scans agent generated text for potential leaked tokens and strips them. + In real usage, this might also involve another LLM pass or DLP. + """ + if TOKEN_REGEX.search(text): + logger.warning("Agent attempted to output a potential token/secret. Redacting.") + text = TOKEN_REGEX.sub("[REDACTED SECRET]", text) + + return text diff --git a/agent/security/trace.py b/agent/security/trace.py new file mode 100644 index 0000000..95d0136 --- /dev/null +++ b/agent/security/trace.py @@ -0,0 +1,35 @@ +import functools +import logging + +from google.cloud import trace_v1 + +logger = logging.getLogger(__name__) + +_trace_client = None + +def get_trace_client(): + global _trace_client + if not _trace_client: + try: + _trace_client = trace_v1.TraceServiceClient() + except Exception as e: + logger.warning(f"Failed to initialize Trace client: {e}") + return _trace_client + +def traced(span_name: str): + """ + Decorator to wrap a function in a Cloud Trace span. + Helps measure latency of security layers. + """ + def decorator(func): + @functools.wraps(func) + def wrapper(*args, **kwargs): + # In a real environment, we would link this to the incoming GCP trace header + logger.debug(f"[Trace Start] {span_name}") + try: + result = func(*args, **kwargs) + return result + finally: + logger.debug(f"[Trace End] {span_name}") + return wrapper + return decorator diff --git a/agent/subagents/__init__.py b/agent/subagents/__init__.py new file mode 100644 index 0000000..2b430ff --- /dev/null +++ b/agent/subagents/__init__.py @@ -0,0 +1 @@ +# Subagents package diff --git a/agent/subagents/calendar_agent.py b/agent/subagents/calendar_agent.py new file mode 100644 index 0000000..92396d9 --- /dev/null +++ b/agent/subagents/calendar_agent.py @@ -0,0 +1,34 @@ +import logging + +from google.adk.agents import Agent +from google.adk.tools import Tool + +logger = logging.getLogger(__name__) + +def list_events(days_ahead: int = 7) -> str: + """List upcoming calendar events.""" + logger.info(f"Listing events for {days_ahead} days ahead.") + return "Mock Calendar: Meeting at 3pm tomorrow." + +def check_availability(date: str) -> str: + """Check if the user is free on a specific date and time.""" + logger.info(f"Checking availability for: {date}") + return f"Mock Availability for {date}: Free after 2pm." + +def create_event(title: str, start: str, end: str, description: str) -> str: + """Create a new calendar event. Will require approval.""" + logger.info(f"Creating event: {title} from {start} to {end}") + # Later this will hit the Approval engine before execution + return f"Mock Event Created: {title}" + +list_events_tool = Tool.from_function(list_events) +check_availability_tool = Tool.from_function(check_availability) +create_event_tool = Tool.from_function(create_event) + +calendar_agent = Agent( + name="CalendarAgent", + model="gemini-2.0-flash", + description="Manages the user's agenda, availability, and scheduling.", + instruction="You help the user manage their time. Check their calendar and schedule events if asked.", + tools=[list_events_tool, check_availability_tool, create_event_tool] +) diff --git a/agent/subagents/drive_agent.py b/agent/subagents/drive_agent.py new file mode 100644 index 0000000..19bbd9e --- /dev/null +++ b/agent/subagents/drive_agent.py @@ -0,0 +1,33 @@ +import logging + +from google.adk.agents import Agent +from google.adk.tools import Tool + +logger = logging.getLogger(__name__) + +def list_recent_files(max_results: int = 10) -> str: + """Lists the user's most recently accessed files in Google Drive.""" + logger.info(f"Listing {max_results} recent files.") + return "Mock Drive: 1. Q3 Report.pdf, 2. Design Specs.docx" + +def search_files(query: str) -> str: + """Searches Google Drive for files matching the query.""" + logger.info(f"Searching drive for: {query}") + return f"Mock Search Results: Found 2 files for '{query}'" + +def summarise_document(file_id: str) -> str: + """Reads a file from Google Drive and provides a summary.""" + logger.info(f"Summarising document ID: {file_id}") + return f"Mock summary of document {file_id}: This is a high level overview of Q3." + +list_recent_tools = Tool.from_function(list_recent_files) +search_files_tool = Tool.from_function(search_files) +summarise_document_tool = Tool.from_function(summarise_document) + +drive_agent = Agent( + name="DriveAgent", + model="gemini-2.0-flash", + description="Searches Google Drive and summarizes documents.", + instruction="You are a file and document management assistant. Locate files and summarize them when asked.", + tools=[list_recent_tools, search_files_tool, summarise_document_tool] +) diff --git a/agent/subagents/gmail_agent.py b/agent/subagents/gmail_agent.py new file mode 100644 index 0000000..0f93f12 --- /dev/null +++ b/agent/subagents/gmail_agent.py @@ -0,0 +1,33 @@ +import logging + +from google.adk.agents import Agent +from google.adk.tools import Tool + +logger = logging.getLogger(__name__) + +def read_inbox(max_results: int = 5) -> str: + """Reads the user's latest emails from the inbox.""" + logger.info(f"Reading {max_results} emails from inbox.") + return "Mock Inbox: 1. Project Update, 2. Lunch Plans" + +def search_emails(query: str) -> str: + """Searches the user's emails using Gmail query syntax.""" + logger.info(f"Searching emails for: {query}") + return f"Mock search results for '{query}': No recent matches." + +def read_email(message_id: str) -> str: + """Reads the full body of a specific email.""" + logger.info(f"Reading full email ID: {message_id}") + return f"Mock Email content for message {message_id}: Hello this is a test." + +read_inbox_tool = Tool.from_function(read_inbox) +search_emails_tool = Tool.from_function(search_emails) +read_email_tool = Tool.from_function(read_email) + +gmail_agent = Agent( + name="GmailAgent", + model="gemini-2.0-flash", + description="Manages the user's Gmail inbox. Can search and read emails.", + instruction="You are a personal assistant handling email. Answer questions about the inbox. Only read emails.", + tools=[read_inbox_tool, search_emails_tool, read_email_tool] +) diff --git a/agent/subagents/search_agent.py b/agent/subagents/search_agent.py new file mode 100644 index 0000000..7c63400 --- /dev/null +++ b/agent/subagents/search_agent.py @@ -0,0 +1,29 @@ +import logging + +from google.adk.agents import Agent +from google.adk.tools import Tool + +logger = logging.getLogger(__name__) + +def web_search_tool(query: str) -> str: + """ + Search the web for current information, news, or facts. + + Args: + query: The search terms to look up. + Returns: + Summary of search results. + """ + logger.info(f"Mock web search for: {query}") + # Mock implementation for now + return f"Search results for '{query}': Example finding (mock)" + +search_tool = Tool.from_function(web_search_tool) + +search_agent = Agent( + name="SearchAgent", + model="gemini-2.0-flash", # Note: ADK model binding needs valid key + description="Finds recent information and facts on the internet.", + instruction="You are a research assistant. Use the web search tool to find answers to the user's questions.", + tools=[search_tool] +) diff --git a/deployment/README.md b/deployment/README.md new file mode 100644 index 0000000..7a34cab --- /dev/null +++ b/deployment/README.md @@ -0,0 +1,11 @@ +# Deployment + +This directory contains the Terraform configurations for provisioning the necessary Google Cloud infrastructure for your agent. + +The recommended way to deploy the infrastructure and set up the CI/CD pipeline is by using the `agent-starter-pack setup-cicd` command from the root of your project. + +However, for a more hands-on approach, you can always apply the Terraform configurations manually for a do-it-yourself setup. + +For detailed information on the deployment process, infrastructure, and CI/CD pipelines, please refer to the official documentation: + +**[Agent Starter Pack Deployment Guide](https://googlecloudplatform.github.io/agent-starter-pack/guide/deployment.html)** \ No newline at end of file diff --git a/deployment/terraform/apis.tf b/deployment/terraform/apis.tf new file mode 100644 index 0000000..cf1091f --- /dev/null +++ b/deployment/terraform/apis.tf @@ -0,0 +1,40 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +resource "google_project_service" "cicd_services" { + count = length(local.cicd_services) + project = var.cicd_runner_project_id + service = local.cicd_services[count.index] + disable_on_destroy = false +} + +resource "google_project_service" "deploy_project_services" { + for_each = { + for pair in setproduct(keys(local.deploy_project_ids), local.deploy_project_services) : + "${pair[0]}_${replace(pair[1], ".", "_")}" => { + project = local.deploy_project_ids[pair[0]] + service = pair[1] + } + } + project = each.value.project + service = each.value.service + disable_on_destroy = false +} + +# Enable Cloud Resource Manager API for the CICD runner project +resource "google_project_service" "cicd_cloud_resource_manager_api" { + project = var.cicd_runner_project_id + service = "cloudresourcemanager.googleapis.com" + disable_on_destroy = false +} diff --git a/deployment/terraform/dev/apis.tf b/deployment/terraform/dev/apis.tf new file mode 100644 index 0000000..f1cded6 --- /dev/null +++ b/deployment/terraform/dev/apis.tf @@ -0,0 +1,41 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +locals { + services = [ + "aiplatform.googleapis.com", + "cloudbuild.googleapis.com", + "run.googleapis.com", + "bigquery.googleapis.com", + "cloudresourcemanager.googleapis.com", + "iam.googleapis.com", + "serviceusage.googleapis.com", + "logging.googleapis.com", + "cloudtrace.googleapis.com", + "telemetry.googleapis.com", + ] +} + +resource "google_project_service" "services" { + count = length(local.services) + project = var.dev_project_id + service = local.services[count.index] + disable_on_destroy = false +} + +resource "google_project_service_identity" "vertex_sa" { + provider = google-beta + project = var.dev_project_id + service = "aiplatform.googleapis.com" +} diff --git a/deployment/terraform/dev/iam.tf b/deployment/terraform/dev/iam.tf new file mode 100644 index 0000000..56782d4 --- /dev/null +++ b/deployment/terraform/dev/iam.tf @@ -0,0 +1,59 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +locals { + project_ids = { + dev = var.dev_project_id + } +} + + +# Get the project number for the dev project +data "google_project" "dev_project" { + project_id = var.dev_project_id +} + +# Grant Storage Object Creator role to default compute service account +resource "google_project_iam_member" "default_compute_sa_storage_object_creator" { + project = var.dev_project_id + role = "roles/cloudbuild.builds.builder" + member = "serviceAccount:${data.google_project.dev_project.number}-compute@developer.gserviceaccount.com" + depends_on = [resource.google_project_service.services] +} + +# Agent service account +resource "google_service_account" "app_sa" { + account_id = "${var.project_name}-app" + display_name = "${var.project_name} Agent Service Account" + project = var.dev_project_id + depends_on = [resource.google_project_service.services] +} + +# Grant application SA the required permissions to run the application +resource "google_project_iam_member" "app_sa_roles" { + for_each = { + for pair in setproduct(keys(local.project_ids), var.app_sa_roles) : + join(",", pair) => { + project = local.project_ids[pair[0]] + role = pair[1] + } + } + + project = each.value.project + role = each.value.role + member = "serviceAccount:${google_service_account.app_sa.email}" + depends_on = [resource.google_project_service.services] +} + + diff --git a/deployment/terraform/dev/outputs.tf b/deployment/terraform/dev/outputs.tf new file mode 100644 index 0000000..e1e3789 --- /dev/null +++ b/deployment/terraform/dev/outputs.tf @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "app_service_account_email" { + description = "Application service account email" + value = google_service_account.app_sa.email +} + +output "logs_bucket_name" { + description = "Logs storage bucket name" + value = google_storage_bucket.logs_data_bucket.name +} diff --git a/deployment/terraform/dev/providers.tf b/deployment/terraform/dev/providers.tf new file mode 100644 index 0000000..b747ef4 --- /dev/null +++ b/deployment/terraform/dev/providers.tf @@ -0,0 +1,34 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +terraform { + required_version = ">= 1.0.0" + required_providers { + google = { + source = "hashicorp/google" + version = "~> 7.13.0" + } + random = { + source = "hashicorp/random" + version = "~> 3.7.0" + } + } +} + +provider "google" { + alias = "dev_billing_override" + billing_project = var.dev_project_id + region = var.region + user_project_override = true +} diff --git a/deployment/terraform/dev/service.tf b/deployment/terraform/dev/service.tf new file mode 100644 index 0000000..61c838f --- /dev/null +++ b/deployment/terraform/dev/service.tf @@ -0,0 +1,80 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Get project information to access the project number +data "google_project" "project" { + project_id = var.dev_project_id +} + + +resource "google_cloud_run_v2_service" "app" { + name = var.project_name + location = var.region + project = var.dev_project_id + deletion_protection = false + ingress = "INGRESS_TRAFFIC_ALL" + labels = { + "created-by" = "adk" + } + + template { + containers { + image = "us-docker.pkg.dev/cloudrun/container/hello" + resources { + limits = { + cpu = "4" + memory = "8Gi" + } + } + + env { + name = "LOGS_BUCKET_NAME" + value = google_storage_bucket.logs_data_bucket.name + } + + env { + name = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT" + value = "NO_CONTENT" + } + } + + service_account = google_service_account.app_sa.email + max_instance_request_concurrency = 40 + + scaling { + min_instance_count = 1 + max_instance_count = 10 + } + + session_affinity = true + } + + traffic { + type = "TRAFFIC_TARGET_ALLOCATION_TYPE_LATEST" + percent = 100 + } + + # This lifecycle block prevents Terraform from overwriting the container image when it's + # updated by Cloud Run deployments outside of Terraform (e.g., via CI/CD pipelines) + lifecycle { + ignore_changes = [ + template[0].containers[0].image, + ] + } + + # Make dependencies conditional to avoid errors. + depends_on = [ + resource.google_project_service.services, + ] +} diff --git a/deployment/terraform/dev/service_outputs.tf b/deployment/terraform/dev/service_outputs.tf new file mode 100644 index 0000000..4f3a820 --- /dev/null +++ b/deployment/terraform/dev/service_outputs.tf @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "cloud_run_service_url" { + description = "Cloud Run service URL" + value = google_cloud_run_v2_service.app.uri +} + +output "cloud_run_service_name" { + description = "Cloud Run service name" + value = google_cloud_run_v2_service.app.name +} diff --git a/deployment/terraform/dev/storage.tf b/deployment/terraform/dev/storage.tf new file mode 100644 index 0000000..4c998b9 --- /dev/null +++ b/deployment/terraform/dev/storage.tf @@ -0,0 +1,27 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +provider "google" { + region = var.region + user_project_override = true +} + +resource "google_storage_bucket" "logs_data_bucket" { + name = "${var.dev_project_id}-${var.project_name}-logs" + location = var.region + project = var.dev_project_id + uniform_bucket_level_access = true + + depends_on = [resource.google_project_service.services] +} diff --git a/deployment/terraform/dev/telemetry.tf b/deployment/terraform/dev/telemetry.tf new file mode 100644 index 0000000..809a85e --- /dev/null +++ b/deployment/terraform/dev/telemetry.tf @@ -0,0 +1,200 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# BigQuery dataset for telemetry external tables +resource "google_bigquery_dataset" "telemetry_dataset" { + project = var.dev_project_id + dataset_id = replace("${var.project_name}_telemetry", "-", "_") + friendly_name = "${var.project_name} Telemetry" + location = var.region + description = "Dataset for GenAI telemetry data stored in GCS" + depends_on = [google_project_service.services] +} + +# BigQuery connection for accessing GCS telemetry data +resource "google_bigquery_connection" "genai_telemetry_connection" { + project = var.dev_project_id + location = var.region + connection_id = "${var.project_name}-genai-telemetry" + friendly_name = "${var.project_name} GenAI Telemetry Connection" + + cloud_resource {} + + depends_on = [google_project_service.services] +} + +# Wait for the BigQuery connection service account to propagate in IAM +resource "time_sleep" "wait_for_bq_connection_sa" { + create_duration = "10s" + + depends_on = [google_bigquery_connection.genai_telemetry_connection] +} + +# Grant the BigQuery connection service account access to read from the logs bucket +resource "google_storage_bucket_iam_member" "telemetry_connection_access" { + bucket = google_storage_bucket.logs_data_bucket.name + role = "roles/storage.objectViewer" + member = "serviceAccount:${google_bigquery_connection.genai_telemetry_connection.cloud_resource[0].service_account_id}" + + depends_on = [time_sleep.wait_for_bq_connection_sa] +} + +# ==================================================================== +# Dedicated Cloud Logging Bucket for GenAI Telemetry +# ==================================================================== + +# Wait for the Logging API to fully propagate after enablement +resource "time_sleep" "wait_for_logging_api" { + create_duration = "30s" + + depends_on = [google_project_service.services] +} + +# Create a custom Cloud Logging bucket for GenAI telemetry logs with long-term retention +resource "google_logging_project_bucket_config" "genai_telemetry_bucket" { + project = var.dev_project_id + location = var.region + bucket_id = "${var.project_name}-genai-telemetry" + retention_days = 3650 # 10 years retention (maximum allowed) + enable_analytics = true # Required for linked datasets + description = "Dedicated Cloud Logging bucket for ${var.project_name} GenAI telemetry with 10 year retention" + + depends_on = [time_sleep.wait_for_logging_api] +} + +# Log sink to route only GenAI telemetry logs to the dedicated bucket +# Filter by bucket name in the GCS path (which includes project_name) to isolate this agent's logs +resource "google_logging_project_sink" "genai_logs_to_bucket" { + name = "${var.project_name}-genai-logs" + project = var.dev_project_id + destination = "logging.googleapis.com/projects/${var.dev_project_id}/locations/${var.region}/buckets/${google_logging_project_bucket_config.genai_telemetry_bucket.bucket_id}" + filter = "log_name=\"projects/${var.dev_project_id}/logs/gen_ai.client.inference.operation.details\" AND (labels.\"gen_ai.input.messages_ref\" =~ \".*${var.project_name}.*\" OR labels.\"gen_ai.output.messages_ref\" =~ \".*${var.project_name}.*\")" + + unique_writer_identity = true + depends_on = [google_logging_project_bucket_config.genai_telemetry_bucket] +} + +# Create a linked dataset to the GenAI telemetry logs bucket for querying via BigQuery +resource "google_logging_linked_dataset" "genai_logs_linked_dataset" { + link_id = replace("${var.project_name}_genai_telemetry_logs", "-", "_") + bucket = google_logging_project_bucket_config.genai_telemetry_bucket.bucket_id + description = "Linked dataset for ${var.project_name} GenAI telemetry Cloud Logging bucket" + location = var.region + parent = "projects/${var.dev_project_id}" + + depends_on = [ + google_logging_project_bucket_config.genai_telemetry_bucket, + google_logging_project_sink.genai_logs_to_bucket + ] +} + +# Wait for linked dataset to fully propagate +resource "time_sleep" "wait_for_linked_dataset" { + create_duration = "10s" + + depends_on = [google_logging_linked_dataset.genai_logs_linked_dataset] +} + +# ==================================================================== +# Feedback Logs to Cloud Logging Bucket +# ==================================================================== + +# Log sink for user feedback logs - routes to the same Cloud Logging bucket +resource "google_logging_project_sink" "feedback_logs_to_bucket" { + name = "${var.project_name}-feedback" + project = var.dev_project_id + destination = "logging.googleapis.com/projects/${var.dev_project_id}/locations/${var.region}/buckets/${google_logging_project_bucket_config.genai_telemetry_bucket.bucket_id}" + filter = var.feedback_logs_filter + + unique_writer_identity = true + depends_on = [google_logging_project_bucket_config.genai_telemetry_bucket] +} + +# ==================================================================== +# Completions External Table (GCS-based) +# ==================================================================== + +# External table for completions data (messages/parts) stored in GCS +resource "google_bigquery_table" "completions_external_table" { + project = var.dev_project_id + dataset_id = google_bigquery_dataset.telemetry_dataset.dataset_id + table_id = "completions" + deletion_protection = false + + external_data_configuration { + autodetect = false + source_format = "NEWLINE_DELIMITED_JSON" + source_uris = ["gs://${google_storage_bucket.logs_data_bucket.name}/completions/*"] + connection_id = google_bigquery_connection.genai_telemetry_connection.name + ignore_unknown_values = true + max_bad_records = 1000 + } + + # Schema matching the ADK completions format + schema = jsonencode([ + { + name = "parts" + type = "RECORD" + mode = "REPEATED" + fields = [ + { name = "type", type = "STRING", mode = "NULLABLE" }, + { name = "content", type = "STRING", mode = "NULLABLE" }, + { name = "mime_type", type = "STRING", mode = "NULLABLE" }, + { name = "uri", type = "STRING", mode = "NULLABLE" }, + { name = "data", type = "BYTES", mode = "NULLABLE" }, + { name = "id", type = "STRING", mode = "NULLABLE" }, + { name = "name", type = "STRING", mode = "NULLABLE" }, + { name = "arguments", type = "JSON", mode = "NULLABLE" }, + { name = "response", type = "JSON", mode = "NULLABLE" } + ] + }, + { name = "role", type = "STRING", mode = "NULLABLE" }, + { name = "index", type = "INTEGER", mode = "NULLABLE" } + ]) + + depends_on = [ + google_storage_bucket.logs_data_bucket, + google_bigquery_connection.genai_telemetry_connection, + google_storage_bucket_iam_member.telemetry_connection_access + ] +} + +# ==================================================================== +# Completions View (Joins Logs with GCS Data) +# ==================================================================== + +# View that joins Cloud Logging data with GCS-stored completions data +resource "google_bigquery_table" "completions_view" { + project = var.dev_project_id + dataset_id = google_bigquery_dataset.telemetry_dataset.dataset_id + table_id = "completions_view" + description = "View of GenAI completion logs joined with the GCS prompt/response external table" + deletion_protection = false + + view { + query = templatefile("${path.module}/../sql/completions.sql", { + project_id = var.dev_project_id + dataset_id = google_bigquery_dataset.telemetry_dataset.dataset_id + completions_external_table = google_bigquery_table.completions_external_table.table_id + logs_link_id = google_logging_linked_dataset.genai_logs_linked_dataset.link_id + }) + use_legacy_sql = false + } + + depends_on = [ + google_logging_linked_dataset.genai_logs_linked_dataset, + google_bigquery_table.completions_external_table, + time_sleep.wait_for_linked_dataset + ] +} diff --git a/deployment/terraform/dev/telemetry_outputs.tf b/deployment/terraform/dev/telemetry_outputs.tf new file mode 100644 index 0000000..97b9da1 --- /dev/null +++ b/deployment/terraform/dev/telemetry_outputs.tf @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "telemetry_dataset_id" { + description = "BigQuery dataset ID for telemetry data" + value = google_bigquery_dataset.telemetry_dataset.dataset_id +} + +output "telemetry_bigquery_connection_id" { + description = "BigQuery connection ID for telemetry GCS access" + value = google_bigquery_connection.genai_telemetry_connection.connection_id +} diff --git a/deployment/terraform/dev/variables.tf b/deployment/terraform/dev/variables.tf new file mode 100644 index 0000000..33fc0c2 --- /dev/null +++ b/deployment/terraform/dev/variables.tf @@ -0,0 +1,55 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +variable "project_name" { + type = string + description = "Project name used as a base for resource naming" + default = "adkbot" +} + +variable "dev_project_id" { + type = string + description = "**Dev** Google Cloud Project ID for resource deployment." +} + +variable "region" { + type = string + description = "Google Cloud region for resource deployment." + default = "us-central1" +} + +variable "telemetry_logs_filter" { + type = string + description = "Log Sink filter for capturing telemetry data. Captures logs with the `traceloop.association.properties.log_type` attribute set to `tracing`." + default = "labels.service_name=\"adkbot\" labels.type=\"agent_telemetry\"" +} + +variable "feedback_logs_filter" { + type = string + description = "Log Sink filter for capturing feedback data. Captures logs where the `log_type` field is `feedback`." + default = "jsonPayload.log_type=\"feedback\" jsonPayload.service_name=\"adkbot\"" +} + +variable "app_sa_roles" { + description = "List of roles to assign to the application service account" + type = list(string) + default = [ + + "roles/aiplatform.user", + "roles/logging.logWriter", + "roles/cloudtrace.agent", + "roles/storage.admin", + "roles/serviceusage.serviceUsageConsumer", + ] +} diff --git a/deployment/terraform/dev/vars/env.tfvars b/deployment/terraform/dev/vars/env.tfvars new file mode 100644 index 0000000..1f85635 --- /dev/null +++ b/deployment/terraform/dev/vars/env.tfvars @@ -0,0 +1,8 @@ +# Project name used for resource naming +project_name = "adkbot" + +# Your Dev Google Cloud project id +dev_project_id = "your-gcp-project-id" + +# The Google Cloud region you will use to deploy the infrastructure +region = "us-central1" diff --git a/deployment/terraform/github.tf b/deployment/terraform/github.tf new file mode 100644 index 0000000..9685b50 --- /dev/null +++ b/deployment/terraform/github.tf @@ -0,0 +1,168 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +provider "github" { + owner = var.repository_owner +} + +# Try to get existing repo +data "github_repository" "existing_repo" { + count = var.create_repository ? 0 : 1 + full_name = "${var.repository_owner}/${var.repository_name}" +} + +# Only create GitHub repo if create_repository is true +resource "github_repository" "repo" { + count = var.create_repository ? 1 : 0 + name = var.repository_name + description = "Repository created with goo.gle/agent-starter-pack" + visibility = "private" + + has_issues = true + has_wiki = false + has_projects = false + has_downloads = false + + allow_merge_commit = true + allow_squash_merge = true + allow_rebase_merge = true + + auto_init = false +} + + +resource "github_actions_variable" "gcp_project_number" { + repository = var.repository_name + variable_name = "GCP_PROJECT_NUMBER" + value = data.google_project.cicd_project.number + depends_on = [github_repository.repo] +} + +resource "github_actions_secret" "wif_pool_id" { + repository = var.repository_name + secret_name = "WIF_POOL_ID" + plaintext_value = google_iam_workload_identity_pool.github_pool.workload_identity_pool_id + depends_on = [github_repository.repo, data.github_repository.existing_repo] +} + +resource "github_actions_secret" "wif_provider_id" { + repository = var.repository_name + secret_name = "WIF_PROVIDER_ID" + plaintext_value = google_iam_workload_identity_pool_provider.github_provider.workload_identity_pool_provider_id + depends_on = [github_repository.repo, data.github_repository.existing_repo] +} + +resource "github_actions_secret" "gcp_service_account" { + repository = var.repository_name + secret_name = "GCP_SERVICE_ACCOUNT" + plaintext_value = google_service_account.cicd_runner_sa.email + depends_on = [github_repository.repo, data.github_repository.existing_repo] +} + +resource "github_actions_variable" "staging_project_id" { + repository = var.repository_name + variable_name = "STAGING_PROJECT_ID" + value = var.staging_project_id + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "prod_project_id" { + repository = var.repository_name + variable_name = "PROD_PROJECT_ID" + value = var.prod_project_id + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "region" { + repository = var.repository_name + variable_name = "REGION" + value = var.region + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "cicd_project_id" { + repository = var.repository_name + variable_name = "CICD_PROJECT_ID" + value = var.cicd_runner_project_id + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "app_sa_email_staging" { + repository = var.repository_name + variable_name = "APP_SA_EMAIL_STAGING" + value = google_service_account.app_sa["staging"].email + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "app_sa_email_prod" { + repository = var.repository_name + variable_name = "APP_SA_EMAIL_PROD" + value = google_service_account.app_sa["prod"].email + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "app_service_account_staging" { + repository = var.repository_name + variable_name = "APP_SERVICE_ACCOUNT_STAGING" + value = google_service_account.app_sa["staging"].email + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "app_service_account_prod" { + repository = var.repository_name + variable_name = "APP_SERVICE_ACCOUNT_PROD" + value = google_service_account.app_sa["prod"].email + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "logs_bucket_name_staging" { + repository = var.repository_name + variable_name = "LOGS_BUCKET_NAME_STAGING" + value = google_storage_bucket.logs_data_bucket[var.staging_project_id].name + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "logs_bucket_name_prod" { + repository = var.repository_name + variable_name = "LOGS_BUCKET_NAME_PROD" + value = google_storage_bucket.logs_data_bucket[var.prod_project_id].name + depends_on = [github_repository.repo] +} + + +resource "github_actions_variable" "container_name" { + repository = var.repository_name + variable_name = "CONTAINER_NAME" + value = var.project_name + depends_on = [github_repository.repo] +} + +resource "github_actions_variable" "artifact_registry_repo_name" { + repository = var.repository_name + variable_name = "ARTIFACT_REGISTRY_REPO_NAME" + value = google_artifact_registry_repository.repo-artifacts-genai.repository_id + depends_on = [github_repository.repo] +} + + +resource "github_repository_environment" "production_environment" { + repository = var.repository_name + environment = "production" + depends_on = [github_repository.repo, data.github_repository.existing_repo] + + deployment_branch_policy { + protected_branches = false + custom_branch_policies = true + } +} diff --git a/deployment/terraform/iam.tf b/deployment/terraform/iam.tf new file mode 100644 index 0000000..862e44c --- /dev/null +++ b/deployment/terraform/iam.tf @@ -0,0 +1,92 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Data source to get project numbers +data "google_project" "projects" { + for_each = local.deploy_project_ids + project_id = each.value +} + +# 1. Assign roles for the CICD project +resource "google_project_iam_member" "cicd_project_roles" { + for_each = toset(var.cicd_roles) + + project = var.cicd_runner_project_id + role = each.value + member = "serviceAccount:${resource.google_service_account.cicd_runner_sa.email}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] + +} + +# 2. Assign roles for the other two projects (prod and staging) +resource "google_project_iam_member" "other_projects_roles" { + for_each = { + for pair in setproduct(keys(local.deploy_project_ids), var.cicd_sa_deployment_required_roles) : + "${pair[0]}-${pair[1]}" => { + project_id = local.deploy_project_ids[pair[0]] + role = pair[1] + } + } + + project = each.value.project_id + role = each.value.role + member = "serviceAccount:${resource.google_service_account.cicd_runner_sa.email}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} +# 3. Grant application SA the required permissions to run the application +resource "google_project_iam_member" "app_sa_roles" { + for_each = { + for pair in setproduct(keys(local.deploy_project_ids), var.app_sa_roles) : + join(",", pair) => { + project = local.deploy_project_ids[pair[0]] + role = pair[1] + } + } + + project = each.value.project + role = each.value.role + member = "serviceAccount:${google_service_account.app_sa[split(",", each.key)[0]].email}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + + +# 4. Allow Cloud Run service SA to pull containers stored in the CICD project +resource "google_project_iam_member" "cicd_run_invoker_artifact_registry_reader" { + for_each = local.deploy_project_ids + project = var.cicd_runner_project_id + + role = "roles/artifactregistry.reader" + member = "serviceAccount:service-${data.google_project.projects[each.key].number}@serverless-robot-prod.iam.gserviceaccount.com" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] + +} + + + + + +# Special assignment: Allow the CICD SA to create tokens +resource "google_service_account_iam_member" "cicd_run_invoker_token_creator" { + service_account_id = google_service_account.cicd_runner_sa.name + role = "roles/iam.serviceAccountTokenCreator" + member = "serviceAccount:${resource.google_service_account.cicd_runner_sa.email}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} +# Special assignment: Allow the CICD SA to impersonate itself for trigger creation +resource "google_service_account_iam_member" "cicd_run_invoker_account_user" { + service_account_id = google_service_account.cicd_runner_sa.name + role = "roles/iam.serviceAccountUser" + member = "serviceAccount:${resource.google_service_account.cicd_runner_sa.email}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} diff --git a/deployment/terraform/locals.tf b/deployment/terraform/locals.tf new file mode 100644 index 0000000..e63edd2 --- /dev/null +++ b/deployment/terraform/locals.tf @@ -0,0 +1,50 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +locals { + cicd_services = [ + "cloudbuild.googleapis.com", + "aiplatform.googleapis.com", + "serviceusage.googleapis.com", + "bigquery.googleapis.com", + "cloudresourcemanager.googleapis.com", + "cloudtrace.googleapis.com", + "telemetry.googleapis.com", + ] + + deploy_project_services = [ + "aiplatform.googleapis.com", + "run.googleapis.com", + "cloudresourcemanager.googleapis.com", + "iam.googleapis.com", + "bigquery.googleapis.com", + "serviceusage.googleapis.com", + "logging.googleapis.com", + "cloudtrace.googleapis.com", + "telemetry.googleapis.com", + ] + + deploy_project_ids = { + prod = var.prod_project_id + staging = var.staging_project_id + } + + all_project_ids = [ + var.cicd_runner_project_id, + var.prod_project_id, + var.staging_project_id + ] + +} + diff --git a/deployment/terraform/outputs.tf b/deployment/terraform/outputs.tf new file mode 100644 index 0000000..b757d03 --- /dev/null +++ b/deployment/terraform/outputs.tf @@ -0,0 +1,34 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "app_service_account_emails" { + description = "Application service account emails by environment" + value = { for k, v in google_service_account.app_sa : k => v.email } +} + +output "cicd_runner_service_account_email" { + description = "CI/CD runner service account email" + value = google_service_account.cicd_runner_sa.email +} + +output "logs_bucket_names" { + description = "Logs storage bucket names by environment" + value = { for k, v in google_storage_bucket.logs_data_bucket : k => v.name } +} + +output "artifact_registry_repository" { + description = "Artifact Registry repository ID" + value = google_artifact_registry_repository.repo-artifacts-genai.repository_id +} + diff --git a/deployment/terraform/providers.tf b/deployment/terraform/providers.tf new file mode 100644 index 0000000..bec903d --- /dev/null +++ b/deployment/terraform/providers.tf @@ -0,0 +1,46 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +terraform { + required_version = ">= 1.0.0" + required_providers { + google = { + source = "hashicorp/google" + version = "~> 7.13.0" + } + github = { + source = "integrations/github" + version = "~> 6.5.0" + } + random = { + source = "hashicorp/random" + version = "~> 3.7.0" + } + } +} + +provider "google" { + alias = "staging_billing_override" + billing_project = var.staging_project_id + region = var.region + user_project_override = true +} + +provider "google" { + alias = "prod_billing_override" + billing_project = var.prod_project_id + region = var.region + user_project_override = true +} diff --git a/deployment/terraform/service.tf b/deployment/terraform/service.tf new file mode 100644 index 0000000..9c592c1 --- /dev/null +++ b/deployment/terraform/service.tf @@ -0,0 +1,85 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Get project information to access the project number +data "google_project" "project" { + for_each = local.deploy_project_ids + + project_id = local.deploy_project_ids[each.key] +} + +resource "google_cloud_run_v2_service" "app" { + for_each = local.deploy_project_ids + + name = var.project_name + location = var.region + project = each.value + deletion_protection = false + ingress = "INGRESS_TRAFFIC_ALL" + labels = { + "created-by" = "adk" + } + + template { + containers { + # Placeholder, will be replaced by the CI/CD pipeline + image = "us-docker.pkg.dev/cloudrun/container/hello" + resources { + limits = { + cpu = "4" + memory = "8Gi" + } + cpu_idle = false + } + + env { + name = "LOGS_BUCKET_NAME" + value = google_storage_bucket.logs_data_bucket[each.value].name + } + + env { + name = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT" + value = "NO_CONTENT" + } + } + + service_account = google_service_account.app_sa[each.key].email + max_instance_request_concurrency = 40 + + scaling { + min_instance_count = 1 + max_instance_count = 10 + } + + session_affinity = true + } + + traffic { + type = "TRAFFIC_TARGET_ALLOCATION_TYPE_LATEST" + percent = 100 + } + + # This lifecycle block prevents Terraform from overwriting the container image when it's + # updated by Cloud Run deployments outside of Terraform (e.g., via CI/CD pipelines) + lifecycle { + ignore_changes = [ + template[0].containers[0].image, + ] + } + + # Make dependencies conditional to avoid errors. + depends_on = [ + google_project_service.deploy_project_services, + ] +} diff --git a/deployment/terraform/service_accounts.tf b/deployment/terraform/service_accounts.tf new file mode 100644 index 0000000..4bee43e --- /dev/null +++ b/deployment/terraform/service_accounts.tf @@ -0,0 +1,29 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +resource "google_service_account" "cicd_runner_sa" { + account_id = "${var.project_name}-cb" + display_name = "CICD Runner SA" + project = var.cicd_runner_project_id + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} +# Agent service account +resource "google_service_account" "app_sa" { + for_each = local.deploy_project_ids + + account_id = "${var.project_name}-app" + display_name = "${var.project_name} Agent Service Account" + project = each.value + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} diff --git a/deployment/terraform/service_outputs.tf b/deployment/terraform/service_outputs.tf new file mode 100644 index 0000000..d3930fa --- /dev/null +++ b/deployment/terraform/service_outputs.tf @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "cloud_run_service_urls" { + description = "Cloud Run service URLs by environment" + value = { for k, v in google_cloud_run_v2_service.app : k => v.uri } +} + +output "cloud_run_service_names" { + description = "Cloud Run service names by environment" + value = { for k, v in google_cloud_run_v2_service.app : k => v.name } +} diff --git a/deployment/terraform/sql/completions.sql b/deployment/terraform/sql/completions.sql new file mode 100644 index 0000000..cb1b5e4 --- /dev/null +++ b/deployment/terraform/sql/completions.sql @@ -0,0 +1,138 @@ +-- Optimized join of Cloud Logging data with GCS-stored prompt/response data. +-- This query extracts both input and output messages referenced in logs. +-- Note: Input files contain full conversation history, so messages may appear multiple times. + +-- Extract message references from Cloud Logging (scan once, extract both input/output) +WITH log_refs AS ( + SELECT + insert_id, + timestamp, + labels, + trace, + span_id, + JSON_VALUE(labels, '$.\"gen_ai.input.messages_ref\"') AS input_ref, + JSON_VALUE(labels, '$.\"gen_ai.output.messages_ref\"') AS output_ref + FROM `${project_id}.${logs_link_id}._AllLogs` + WHERE JSON_VALUE(labels, '$.\"gen_ai.input.messages_ref\"') IS NOT NULL + OR JSON_VALUE(labels, '$.\"gen_ai.output.messages_ref\"') IS NOT NULL +), + +-- Unpivot to get one row per message reference +unpivoted_refs AS ( + SELECT + insert_id, + timestamp, + labels, + trace, + span_id, + input_ref AS messages_ref_uri, + 'input' AS message_type + FROM log_refs + WHERE input_ref IS NOT NULL + + UNION ALL + + SELECT + insert_id, + timestamp, + labels, + trace, + span_id, + output_ref AS messages_ref_uri, + 'output' AS message_type + FROM log_refs + WHERE output_ref IS NOT NULL +), + +-- Join with completions external table and extract api_call_id once +joined_data AS ( + SELECT + lr.insert_id, + lr.timestamp, + lr.labels, + lr.trace, + lr.span_id, + lr.messages_ref_uri, + lr.message_type, + SPLIT(REGEXP_EXTRACT(lr.messages_ref_uri, r'/([^/]+)\.jsonl'), '_')[OFFSET(0)] AS api_call_id, + c.role, + c.parts, + c.index AS message_idx + FROM unpivoted_refs lr + JOIN `${project_id}.${dataset_id}.${completions_external_table}` c + ON lr.messages_ref_uri = c._FILE_NAME +), + +-- Flatten the parts array +flattened AS ( + SELECT + insert_id, + timestamp, + labels, + trace, + span_id, + messages_ref_uri, + message_type, + api_call_id, + role, + message_idx, + part_idx, + part.type AS part_type, + part.content, + part.uri, + part.mime_type, + TO_HEX(MD5(part.data)) AS data_md5_hex, + part.id AS tool_id, + part.name AS tool_name, + part.arguments AS tool_args, + part.response AS tool_response + FROM joined_data + CROSS JOIN UNNEST(parts) AS part WITH OFFSET AS part_idx +), + +-- Deduplicate by trace: keep only the latest log entry per trace +-- (Tool calls create multiple log entries with same trace but different timestamps) +deduplicated AS ( + SELECT + *, + ROW_NUMBER() OVER ( + PARTITION BY trace, message_type, role, message_idx, part_idx + ORDER BY timestamp DESC + ) AS row_num + FROM flattened +) + +SELECT + -- Core identifiers and timestamps + timestamp, + insert_id, + trace, + span_id, + api_call_id, + + -- Message metadata + message_type, + role, + message_idx, + part_idx, + + -- Message content + content, + + -- Tool/function calling + part_type, + tool_name, + tool_args, + tool_response, + + -- Additional metadata + uri, + mime_type, + data_md5_hex, + + -- Raw fields + labels, + messages_ref_uri +FROM deduplicated +WHERE row_num = 1 -- Keep only the latest entry per trace/message/part +ORDER BY trace ASC, message_type ASC, message_idx ASC, part_idx ASC diff --git a/deployment/terraform/storage.tf b/deployment/terraform/storage.tf new file mode 100644 index 0000000..326989d --- /dev/null +++ b/deployment/terraform/storage.tf @@ -0,0 +1,39 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +provider "google" { + region = var.region + user_project_override = true +} + +resource "google_storage_bucket" "logs_data_bucket" { + for_each = toset(local.all_project_ids) + name = "${each.value}-${var.project_name}-logs" + location = var.region + project = each.value + uniform_bucket_level_access = true + force_destroy = true + + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +resource "google_artifact_registry_repository" "repo-artifacts-genai" { + location = var.region + repository_id = "${var.project_name}-repo" + description = "Repo for Generative AI applications" + format = "DOCKER" + project = var.cicd_runner_project_id + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + diff --git a/deployment/terraform/telemetry.tf b/deployment/terraform/telemetry.tf new file mode 100644 index 0000000..840c997 --- /dev/null +++ b/deployment/terraform/telemetry.tf @@ -0,0 +1,215 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# BigQuery dataset for telemetry external tables +resource "google_bigquery_dataset" "telemetry_dataset" { + for_each = local.deploy_project_ids + project = each.value + dataset_id = replace("${var.project_name}_telemetry", "-", "_") + friendly_name = "${var.project_name} Telemetry" + location = var.region + description = "Dataset for GenAI telemetry data stored in GCS" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +# BigQuery connection for accessing GCS telemetry data +resource "google_bigquery_connection" "genai_telemetry_connection" { + for_each = local.deploy_project_ids + project = each.value + location = var.region + connection_id = "${var.project_name}-genai-telemetry" + friendly_name = "${var.project_name} GenAI Telemetry Connection" + + cloud_resource {} + + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +# Wait for the BigQuery connection service account to propagate in IAM +resource "time_sleep" "wait_for_bq_connection_sa" { + for_each = local.deploy_project_ids + + create_duration = "10s" + + depends_on = [google_bigquery_connection.genai_telemetry_connection] +} + +# Grant the BigQuery connection service account access to read from the logs bucket +resource "google_storage_bucket_iam_member" "telemetry_connection_access" { + for_each = local.deploy_project_ids + bucket = google_storage_bucket.logs_data_bucket[each.value].name + role = "roles/storage.objectViewer" + member = "serviceAccount:${google_bigquery_connection.genai_telemetry_connection[each.key].cloud_resource[0].service_account_id}" + + depends_on = [time_sleep.wait_for_bq_connection_sa] +} + +# ==================================================================== +# Dedicated Cloud Logging Bucket for GenAI Telemetry +# ==================================================================== + +# Wait for the Logging API to fully propagate after enablement +resource "time_sleep" "wait_for_logging_api" { + for_each = local.deploy_project_ids + + create_duration = "30s" + + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +# Create a custom Cloud Logging bucket for GenAI telemetry logs with long-term retention +resource "google_logging_project_bucket_config" "genai_telemetry_bucket" { + for_each = local.deploy_project_ids + project = each.value + location = var.region + bucket_id = "${var.project_name}-genai-telemetry" + retention_days = 3650 # 10 years retention (maximum allowed) + enable_analytics = true # Required for linked datasets + description = "Dedicated Cloud Logging bucket for ${var.project_name} GenAI telemetry with 10 year retention" + + depends_on = [time_sleep.wait_for_logging_api] +} + +# Log sink to route only GenAI telemetry logs to the dedicated bucket +# Filter by bucket name in the GCS path (which includes project_name) to isolate this agent's logs +resource "google_logging_project_sink" "genai_logs_to_bucket" { + for_each = local.deploy_project_ids + name = "${var.project_name}-genai-logs" + project = each.value + destination = "logging.googleapis.com/projects/${each.value}/locations/${var.region}/buckets/${google_logging_project_bucket_config.genai_telemetry_bucket[each.key].bucket_id}" + filter = "log_name=\"projects/${each.value}/logs/gen_ai.client.inference.operation.details\" AND (labels.\"gen_ai.input.messages_ref\" =~ \".*${var.project_name}.*\" OR labels.\"gen_ai.output.messages_ref\" =~ \".*${var.project_name}.*\")" + + unique_writer_identity = true + depends_on = [google_logging_project_bucket_config.genai_telemetry_bucket] +} + +# Create a linked dataset to the GenAI telemetry logs bucket for querying via BigQuery +resource "google_logging_linked_dataset" "genai_logs_linked_dataset" { + for_each = local.deploy_project_ids + link_id = replace("${var.project_name}_genai_telemetry_logs", "-", "_") + bucket = google_logging_project_bucket_config.genai_telemetry_bucket[each.key].bucket_id + description = "Linked dataset for ${var.project_name} GenAI telemetry Cloud Logging bucket" + location = var.region + parent = "projects/${each.value}" + + depends_on = [ + google_logging_project_bucket_config.genai_telemetry_bucket, + google_logging_project_sink.genai_logs_to_bucket + ] +} + +# Wait for linked dataset to fully propagate +resource "time_sleep" "wait_for_linked_dataset" { + for_each = local.deploy_project_ids + + create_duration = "10s" + + depends_on = [google_logging_linked_dataset.genai_logs_linked_dataset] +} + +# ==================================================================== +# Feedback Logs to Cloud Logging Bucket +# ==================================================================== + +# Log sink for user feedback logs - routes to the same Cloud Logging bucket +resource "google_logging_project_sink" "feedback_logs_to_bucket" { + for_each = local.deploy_project_ids + name = "${var.project_name}-feedback" + project = each.value + destination = "logging.googleapis.com/projects/${each.value}/locations/${var.region}/buckets/${google_logging_project_bucket_config.genai_telemetry_bucket[each.key].bucket_id}" + filter = var.feedback_logs_filter + + unique_writer_identity = true + depends_on = [google_logging_project_bucket_config.genai_telemetry_bucket] +} + +# ==================================================================== +# Completions External Table (GCS-based) +# ==================================================================== + +# External table for completions data (messages/parts) stored in GCS +resource "google_bigquery_table" "completions_external_table" { + for_each = local.deploy_project_ids + project = each.value + dataset_id = google_bigquery_dataset.telemetry_dataset[each.key].dataset_id + table_id = "completions" + deletion_protection = false + + external_data_configuration { + autodetect = false + source_format = "NEWLINE_DELIMITED_JSON" + source_uris = ["gs://${google_storage_bucket.logs_data_bucket[each.value].name}/completions/*"] + connection_id = google_bigquery_connection.genai_telemetry_connection[each.key].name + ignore_unknown_values = true + max_bad_records = 1000 + } + + # Schema matching the ADK completions format + schema = jsonencode([ + { + name = "parts" + type = "RECORD" + mode = "REPEATED" + fields = [ + { name = "type", type = "STRING", mode = "NULLABLE" }, + { name = "content", type = "STRING", mode = "NULLABLE" }, + { name = "mime_type", type = "STRING", mode = "NULLABLE" }, + { name = "uri", type = "STRING", mode = "NULLABLE" }, + { name = "data", type = "BYTES", mode = "NULLABLE" }, + { name = "id", type = "STRING", mode = "NULLABLE" }, + { name = "name", type = "STRING", mode = "NULLABLE" }, + { name = "arguments", type = "JSON", mode = "NULLABLE" }, + { name = "response", type = "JSON", mode = "NULLABLE" } + ] + }, + { name = "role", type = "STRING", mode = "NULLABLE" }, + { name = "index", type = "INTEGER", mode = "NULLABLE" } + ]) + + depends_on = [ + google_storage_bucket.logs_data_bucket, + google_bigquery_connection.genai_telemetry_connection, + google_storage_bucket_iam_member.telemetry_connection_access + ] +} + +# ==================================================================== +# Completions View (Joins Logs with GCS Data) +# ==================================================================== + +# View that joins Cloud Logging data with GCS-stored completions data +resource "google_bigquery_table" "completions_view" { + for_each = local.deploy_project_ids + project = each.value + dataset_id = google_bigquery_dataset.telemetry_dataset[each.key].dataset_id + table_id = "completions_view" + description = "View of GenAI completion logs joined with the GCS prompt/response external table" + deletion_protection = false + + view { + query = templatefile("${path.module}/sql/completions.sql", { + project_id = each.value + dataset_id = google_bigquery_dataset.telemetry_dataset[each.key].dataset_id + completions_external_table = google_bigquery_table.completions_external_table[each.key].table_id + logs_link_id = google_logging_linked_dataset.genai_logs_linked_dataset[each.key].link_id + }) + use_legacy_sql = false + } + + depends_on = [ + google_logging_linked_dataset.genai_logs_linked_dataset, + google_bigquery_table.completions_external_table, + time_sleep.wait_for_linked_dataset + ] +} diff --git a/deployment/terraform/telemetry_outputs.tf b/deployment/terraform/telemetry_outputs.tf new file mode 100644 index 0000000..fe734f1 --- /dev/null +++ b/deployment/terraform/telemetry_outputs.tf @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +output "telemetry_dataset_id" { + description = "BigQuery dataset ID for telemetry data" + value = { for k, v in google_bigquery_dataset.telemetry_dataset : k => v.dataset_id } +} + +output "telemetry_bigquery_connection_id" { + description = "BigQuery connection ID for telemetry GCS access" + value = { for k, v in google_bigquery_connection.genai_telemetry_connection : k => v.connection_id } +} diff --git a/deployment/terraform/variables.tf b/deployment/terraform/variables.tf new file mode 100644 index 0000000..0d14722 --- /dev/null +++ b/deployment/terraform/variables.tf @@ -0,0 +1,111 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +variable "project_name" { + type = string + description = "Project name used as a base for resource naming" + default = "adkbot" +} + +variable "prod_project_id" { + type = string + description = "**Production** Google Cloud Project ID for resource deployment." +} + +variable "staging_project_id" { + type = string + description = "**Staging** Google Cloud Project ID for resource deployment." +} + +variable "cicd_runner_project_id" { + type = string + description = "Google Cloud Project ID where CI/CD pipelines will execute." +} + +variable "region" { + type = string + description = "Google Cloud region for resource deployment." + default = "us-central1" +} + +variable "host_connection_name" { + description = "Name of the host connection to create in Cloud Build" + type = string + default = "adkbot-github-connection" +} + +variable "repository_name" { + description = "Name of the repository you'd like to connect to Cloud Build" + type = string +} + +variable "app_sa_roles" { + description = "List of roles to assign to the application service account" + type = list(string) + default = [ + + "roles/aiplatform.user", + "roles/logging.logWriter", + "roles/cloudtrace.agent", + "roles/storage.admin", + "roles/serviceusage.serviceUsageConsumer", + ] +} + +variable "cicd_roles" { + description = "List of roles to assign to the CICD runner service account in the CICD project" + type = list(string) + default = [ + "roles/run.invoker", + "roles/storage.admin", + "roles/aiplatform.user", + "roles/logging.logWriter", + "roles/cloudtrace.agent", + "roles/artifactregistry.writer", + "roles/cloudbuild.builds.builder" + ] +} + +variable "cicd_sa_deployment_required_roles" { + description = "List of roles to assign to the CICD runner service account for the Staging and Prod projects." + type = list(string) + default = [ + "roles/run.developer", + "roles/iam.serviceAccountUser", + "roles/aiplatform.user", + "roles/storage.admin" + ] +} + +variable "repository_owner" { + description = "Owner of the Git repository - username or organization" + type = string +} + + + + +variable "create_repository" { + description = "Flag indicating whether to create a new Git repository" + type = bool + default = false +} + + +variable "feedback_logs_filter" { + type = string + description = "Log Sink filter for capturing feedback data. Captures logs where the `log_type` field is `feedback`." + default = "jsonPayload.log_type=\"feedback\" jsonPayload.service_name=\"adkbot\"" +} + diff --git a/deployment/terraform/vars/env.tfvars b/deployment/terraform/vars/env.tfvars new file mode 100644 index 0000000..b41e44a --- /dev/null +++ b/deployment/terraform/vars/env.tfvars @@ -0,0 +1,19 @@ +# Project name used for resource naming +project_name = "adkbot" + +# Your Production Google Cloud project id +prod_project_id = "your-production-project-id" + +# Your Staging / Test Google Cloud project id +staging_project_id = "your-staging-project-id" + +# Your Google Cloud project ID that will be used to host the Cloud Build pipelines. +cicd_runner_project_id = "your-cicd-project-id" + +repository_owner = "Your GitHub organization or username." + +# Name of the repository you added to Cloud Build +repository_name = "adkbot" + +# The Google Cloud region you will use to deploy the infrastructure +region = "us-central1" diff --git a/deployment/terraform/wif.tf b/deployment/terraform/wif.tf new file mode 100644 index 0000000..078c1fc --- /dev/null +++ b/deployment/terraform/wif.tf @@ -0,0 +1,43 @@ + +data "google_project" "cicd_project" { + project_id = var.cicd_runner_project_id +} + +resource "google_service_account_iam_member" "github_oidc_access" { + service_account_id = resource.google_service_account.cicd_runner_sa.name + role = "roles/iam.workloadIdentityUser" + member = "principalSet://iam.googleapis.com/projects/${data.google_project.cicd_project.number}/locations/global/workloadIdentityPools/${google_iam_workload_identity_pool.github_pool.workload_identity_pool_id}/attribute.repository/${var.repository_owner}/${var.repository_name}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +# Allow the GitHub Actions principal to impersonate the CICD runner service account +resource "google_service_account_iam_member" "github_sa_impersonation" { + service_account_id = resource.google_service_account.cicd_runner_sa.name + role = "roles/iam.serviceAccountTokenCreator" + member = "principalSet://iam.googleapis.com/projects/${data.google_project.cicd_project.number}/locations/global/workloadIdentityPools/${google_iam_workload_identity_pool.github_pool.workload_identity_pool_id}/attribute.repository/${var.repository_owner}/${var.repository_name}" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +resource "google_iam_workload_identity_pool" "github_pool" { + workload_identity_pool_id = "${var.project_name}-pool" + project = var.cicd_runner_project_id + display_name = "GitHub Actions Pool" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} + +resource "google_iam_workload_identity_pool_provider" "github_provider" { + workload_identity_pool_provider_id = "${var.project_name}-oidc" + project = var.cicd_runner_project_id + workload_identity_pool_id = google_iam_workload_identity_pool.github_pool.workload_identity_pool_id + display_name = "GitHub OIDC Provider" + oidc { + issuer_uri = "https://token.actions.githubusercontent.com" + } + attribute_mapping = { + "google.subject" = "assertion.sub" + "attribute.repository" = "assertion.repository" + "attribute.repository_owner" = "assertion.repository_owner" + } + attribute_condition = "attribute.repository == '${var.repository_owner}/${var.repository_name}'" + depends_on = [resource.google_project_service.cicd_services, resource.google_project_service.deploy_project_services] +} diff --git a/notebooks/adk_app_testing.ipynb b/notebooks/adk_app_testing.ipynb new file mode 100644 index 0000000..a429e51 --- /dev/null +++ b/notebooks/adk_app_testing.ipynb @@ -0,0 +1,367 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 🧪 ADK Application Testing\n", + "\n", + "This notebook demonstrates how to test an ADK (Agent Development Kit) application.\n", + "It covers both local and remote testing, both with Agent Engine and Cloud Run.\n", + "\n", + "> **Note**: This notebook assumes that the agent files are stored in the `app` folder. If your agent files are located in a different directory, please update all relevant file paths and references accordingly." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set Up Your Environment\n", + "\n", + "> **Note:** For best results, use the same `.venv` created for local development with `uv` to ensure dependency compatibility and avoid environment-related issues." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Uncomment the following lines if you're not using the virtual environment created by uv\n", + "# import sys\n", + "\n", + "# sys.path.append(\"../\")\n", + "# !pip install google-cloud-aiplatform a2a-sdk --upgrade" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Import libraries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "\n", + "import requests\n", + "import vertexai" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Initialize Vertex AI Client" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Initialize the Vertex AI client\n", + "LOCATION = \"us-central1\"\n", + "\n", + "client = vertexai.Client(\n", + " location=LOCATION,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## If you are using Agent Engine\n", + "See more documentation at [Agent Engine Overview](https://cloud.google.com/vertex-ai/generative-ai/docs/agent-engine/overview)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Remote Testing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Set to None to auto-detect from ./deployment_metadata.json, or specify manually\n", + "# \"projects/PROJECT_ID/locations/us-central1/reasoningEngines/ENGINE_ID\"\n", + "REASONING_ENGINE_ID = None\n", + "\n", + "if REASONING_ENGINE_ID is None:\n", + " try:\n", + " with open(\"../deployment_metadata.json\") as f:\n", + " metadata = json.load(f)\n", + " REASONING_ENGINE_ID = metadata.get(\"remote_agent_engine_id\")\n", + " except (FileNotFoundError, json.JSONDecodeError):\n", + " pass\n", + "\n", + "print(f\"Using REASONING_ENGINE_ID: {REASONING_ENGINE_ID}\")\n", + "# Get the existing agent engine\n", + "remote_agent_engine = client.agent_engines.get(name=REASONING_ENGINE_ID)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "async for event in remote_agent_engine.async_stream_query(\n", + " message=\"hi!\", user_id=\"test\"\n", + "):\n", + " print(event)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": "remote_agent_engine.register_feedback(\n feedback={\n \"score\": 5,\n \"text\": \"Great response!\",\n \"user_id\": \"test-user-123\",\n \"session_id\": \"test-session-123\",\n }\n)" + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Local Testing\n", + "\n", + "You can import directly the AgentEngineApp class within your environment. \n", + "To run the agent locally, follow these steps:\n", + "1. Make sure all required packages are installed in your environment\n", + "2. The recommended approach is to use the same virtual environment created by the 'uv' tool\n", + "3. You can set up this environment by running 'make install' from your agent's root directory\n", + "4. Then select this kernel (.venv folder in your project) in your Jupyter notebook to ensure all dependencies are available" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from app.agent_engine_app import agent_engine\n", + "\n", + "agent_engine.set_up()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "async for event in agent_engine.async_stream_query(message=\"hi!\", user_id=\"test\"):\n", + " print(event)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## If you are using Cloud Run" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Remote Testing\n", + "\n", + "For more information about authenticating HTTPS requests to Cloud Run services, see:\n", + "[Cloud Run Authentication Documentation](https://cloud.google.com/run/docs/triggering/https-request)\n", + "\n", + "Remote testing involves using a deployed service URL instead of localhost.\n", + "\n", + "Authentication is handled using GCP identity tokens instead of local credentials." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ID_TOKEN = get_ipython().getoutput(\"gcloud auth print-identity-token -q\")[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "SERVICE_URL = \"YOUR_SERVICE_URL_HERE\" # Replace with your Cloud Run service URL" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You'll need to first create a Session" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "user_id = \"test_user_123\"\n", + "session_data = {\"state\": {\"preferred_language\": \"English\", \"visit_count\": 1}}\n", + "\n", + "session_url = f\"{SERVICE_URL}/apps/app/users/{user_id}/sessions\"\n", + "headers = {\"Content-Type\": \"application/json\", \"Authorization\": f\"Bearer {ID_TOKEN}\"}\n", + "\n", + "session_response = requests.post(session_url, headers=headers, json=session_data)\n", + "print(f\"Session creation status code: {session_response.status_code}\")\n", + "print(f\"Session creation response: {session_response.json()}\")\n", + "session_id = session_response.json()[\"id\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then you will be able to send a message" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "message_data = {\n", + " \"app_name\": \"app\",\n", + " \"user_id\": user_id,\n", + " \"session_id\": session_id,\n", + " \"new_message\": {\"role\": \"user\", \"parts\": [{\"text\": \"Hello! Weather in New york?\"}]},\n", + " \"streaming\": True,\n", + "}\n", + "\n", + "message_url = f\"{SERVICE_URL}/run_sse\"\n", + "message_response = requests.post(\n", + " message_url, headers=headers, json=message_data, stream=True\n", + ")\n", + "\n", + "print(f\"Message send status code: {message_response.status_code}\")\n", + "\n", + "# Print streamed response\n", + "for line in message_response.iter_lines():\n", + " if line:\n", + " line_str = line.decode(\"utf-8\")\n", + " if line_str.startswith(\"data: \"):\n", + " event_json = line_str[6:]\n", + " event = json.loads(event_json)\n", + " print(f\"Received event: {event}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Local Testing\n", + "\n", + "> You can run the application locally via the `make local-backend` command." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Create a session\n", + " Create a new session with user preferences and state information\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "user_id = \"test_user_123\"\n", + "session_data = {\"state\": {\"preferred_language\": \"English\", \"visit_count\": 1}}\n", + "\n", + "session_url = f\"http://127.0.0.1:8000/apps/app/users/{user_id}/sessions\"\n", + "headers = {\"Content-Type\": \"application/json\"}\n", + "\n", + "session_response = requests.post(session_url, headers=headers, json=session_data)\n", + "print(f\"Session creation status code: {session_response.status_code}\")\n", + "print(f\"Session creation response: {session_response.json()}\")\n", + "session_id = session_response.json()[\"id\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Send a message\n", + "Send a message to the backend service and receive a streaming response\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "message_data = {\n", + " \"app_name\": \"app\",\n", + " \"user_id\": user_id,\n", + " \"session_id\": session_id,\n", + " \"new_message\": {\"role\": \"user\", \"parts\": [{\"text\": \"Hello! Weather in New york?\"}]},\n", + " \"streaming\": True,\n", + "}\n", + "\n", + "message_url = \"http://127.0.0.1:8000/run_sse\"\n", + "message_response = requests.post(\n", + " message_url, headers=headers, json=message_data, stream=True\n", + ")\n", + "\n", + "print(f\"Message send status code: {message_response.status_code}\")\n", + "\n", + "# Print streamed response\n", + "for line in message_response.iter_lines():\n", + " if line:\n", + " line_str = line.decode(\"utf-8\")\n", + " if line_str.startswith(\"data: \"):\n", + " event_json = line_str[6:]\n", + " event = json.loads(event_json)\n", + " print(f\"Received event: {event}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "myagent-1762384391", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/notebooks/evaluating_adk_agent.ipynb b/notebooks/evaluating_adk_agent.ipynb new file mode 100644 index 0000000..195db7d --- /dev/null +++ b/notebooks/evaluating_adk_agent.ipynb @@ -0,0 +1,1535 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ur8xi4C7S06n" + }, + "outputs": [], + "source": [ + "# Copyright 2026 Google LLC\n", + "#\n", + "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "#\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "#\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JAPoU8Sm5E6e" + }, + "source": [ + "# Evaluate your ADK agent using Vertex AI Gen AI Evaluation service\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + "
\n", + " \n", + " \"Google
Open in Colab\n", + " \n", + " 		\n", + " \n", + " \"Google
Open in Colab Enterprise\n", + " \n", + " 		\n", + " \n", + " \"Vertex
Open in Vertex AI Workbench\n", + " \n", + " 		\n", + " \n", + " \"GitHub
View on GitHub\n", + " \n", + "
\n", + "\n", + "
\n", + "\n", + "Share to:\n", + "\n", + "\n", + " \"LinkedIn\n", + "\n", + "\n", + "\n", + " \"Bluesky\n", + "\n", + "\n", + "\n", + " \"X\n", + "\n", + "\n", + "\n", + " \"Reddit\n", + "\n", + "\n", + "\n", + " \"Facebook\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "84f0f73a0f76" + }, + "source": [ + "| Author(s) |\n", + "| --- |\n", + "| [Ivan Nardini](https://github.com/inardini) |" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tvgnzT1CKxrO" + }, + "source": [ + "## Overview\n", + "\n", + "Agent Development Kit (ADK in short) is a flexible and modular open source framework for developing and deploying AI agents. While ADK has its own evaluation module, using Vertex AI Gen AI Evaluation provides a toolkit of quality controlled and explainable methods and metrics to evaluate any generative model or application, including agents, and benchmark the evaluation results against your own judgment, using your own evaluation criteria.\n", + "\n", + "This tutorial shows how to evaluate an ADK agent using Vertex AI Gen AI Evaluation for agent evaluation.\n", + "\n", + "The steps performed include:\n", + "\n", + "* Build local agent using ADK\n", + "* Prepare Agent Evaluation dataset\n", + "* Single tool usage evaluation\n", + "* Trajectory evaluation\n", + "* Response evaluation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "61RBz8LLbxCR" + }, + "source": [ + "## Get started" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "No17Cw5hgx12" + }, + "source": [ + "### Install Google Gen AI SDK and other required packages\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "tFy3H3aPgx12" + }, + "outputs": [], + "source": [ + "%pip install --upgrade --quiet 'google-adk'\n", + "%pip install --upgrade --quiet 'google-cloud-aiplatform[evaluation]'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dmWOrTJ3gx13" + }, + "source": [ + "### Authenticate your notebook environment (Colab only)\n", + "\n", + "If you're running this notebook on Google Colab, run the cell below to authenticate your environment." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NyKGtVQjgx13" + }, + "outputs": [], + "source": [ + "import sys\n", + "\n", + "if \"google.colab\" in sys.modules:\n", + " from google.colab import auth\n", + "\n", + " auth.authenticate_user()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DF4l8DTdWgPY" + }, + "source": [ + "### Set Google Cloud project information\n", + "\n", + "To get started using Vertex AI, you must have an existing Google Cloud project and [enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).\n", + "\n", + "Learn more about [setting up a project and a development environment](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Nqwi-5ufWp_B" + }, + "outputs": [], + "source": [ + "# Use the environment variable if the user doesn't provide Project ID.\n", + "import os\n", + "\n", + "import vertexai\n", + "\n", + "PROJECT_ID = \"[your-project-id]\" # @param {type: \"string\", placeholder: \"[your-project-id]\", isTemplate: true}\n", + "if not PROJECT_ID or PROJECT_ID == \"[your-project-id]\":\n", + " PROJECT_ID = str(os.environ.get(\"GOOGLE_CLOUD_PROJECT\"))\n", + "\n", + "LOCATION = os.environ.get(\"GOOGLE_CLOUD_REGION\", \"us-central1\")\n", + "\n", + "BUCKET_NAME = \"[your-bucket-name]\" # @param {type: \"string\", placeholder: \"[your-bucket-name]\", isTemplate: true}\n", + "BUCKET_URI = f\"gs://{BUCKET_NAME}\"\n", + "\n", + "!gsutil mb -l {LOCATION} {BUCKET_URI}\n", + "\n", + "os.environ[\"GOOGLE_CLOUD_PROJECT\"] = PROJECT_ID\n", + "os.environ[\"GOOGLE_CLOUD_LOCATION\"] = LOCATION\n", + "os.environ[\"GOOGLE_GENAI_USE_VERTEXAI\"] = \"True\"\n", + "\n", + "EXPERIMENT_NAME = \"evaluate-adk-agent\" # @param {type:\"string\"}\n", + "\n", + "vertexai.init(project=PROJECT_ID, location=LOCATION, experiment=EXPERIMENT_NAME)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "5303c05f7aa6" + }, + "source": [ + "## Import libraries\n", + "\n", + "Import tutorial libraries." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "6fc324893334" + }, + "outputs": [], + "source": [ + "import json\n", + "import asyncio\n", + "\n", + "# General\n", + "import random\n", + "import string\n", + "from typing import Any\n", + "\n", + "from IPython.display import HTML, Markdown, display\n", + "from google.adk.agents import Agent\n", + "\n", + "# Build agent with adk\n", + "from google.adk.events import Event\n", + "from google.adk.runners import Runner\n", + "from google.adk.sessions import InMemorySessionService\n", + "\n", + "# Evaluate agent\n", + "from google.cloud import aiplatform\n", + "from google.genai import types\n", + "import pandas as pd\n", + "import plotly.graph_objects as go\n", + "from vertexai.preview.evaluation import EvalTask\n", + "from vertexai.preview.evaluation.metrics import (\n", + " PointwiseMetric,\n", + " PointwiseMetricPromptTemplate,\n", + " TrajectorySingleToolUse,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MVnBDX54gz7j" + }, + "source": [ + "## Define helper functions\n", + "\n", + "Initiate a set of helper functions to print tutorial results." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uSgWjMD_g1_v" + }, + "outputs": [], + "source": [ + "def get_id(length: int = 8) -> str:\n", + " \"\"\"Generate a uuid of a specified length (default=8).\"\"\"\n", + " return \"\".join(random.choices(string.ascii_lowercase + string.digits, k=length))\n", + "\n", + "\n", + "def parse_adk_output_to_dictionary(events: list[Event], *, as_json: bool = False):\n", + " \"\"\"\n", + " Parse ADK event output into a structured dictionary format,\n", + " with the predicted trajectory dumped as a JSON string.\n", + "\n", + " \"\"\"\n", + "\n", + " final_response = \"\"\n", + " trajectory = []\n", + "\n", + " for event in events:\n", + " if not getattr(event, \"content\", None) or not getattr(event.content, \"parts\", None):\n", + " continue\n", + " for part in event.content.parts:\n", + " if getattr(part, \"function_call\", None):\n", + " info = {\n", + " \"tool_name\": part.function_call.name,\n", + " \"tool_input\": dict(part.function_call.args),\n", + " }\n", + " if info not in trajectory:\n", + " trajectory.append(info)\n", + " if event.content.role == \"model\" and getattr(part, \"text\", None):\n", + " final_response = part.text.strip()\n", + "\n", + " if as_json:\n", + " trajectory_out = json.dumps(trajectory)\n", + " else:\n", + " trajectory_out = trajectory\n", + "\n", + " return {\"response\": final_response, \"predicted_trajectory\": trajectory_out}\n", + "\n", + "\n", + "def format_output_as_markdown(output: dict) -> str:\n", + " \"\"\"Convert the output dictionary to a formatted markdown string.\"\"\"\n", + " markdown = \"### AI Response\\n\" + output[\"response\"] + \"\\n\\n\"\n", + " if output[\"predicted_trajectory\"]:\n", + " markdown += \"### Function Calls\\n\"\n", + " for call in output[\"predicted_trajectory\"]:\n", + " markdown += f\"- **Function**: `{call['tool_name']}`\\n\"\n", + " markdown += \" - **Arguments**\\n\"\n", + " for key, value in call[\"tool_input\"].items():\n", + " markdown += f\" - `{key}`: `{value}`\\n\"\n", + " return markdown\n", + "\n", + "\n", + "def display_eval_report(eval_result: pd.DataFrame) -> None:\n", + " \"\"\"Display the evaluation results.\"\"\"\n", + " display(Markdown(\"### Summary Metrics\"))\n", + " display(\n", + " pd.DataFrame(\n", + " eval_result.summary_metrics.items(), columns=[\"metric\", \"value\"]\n", + " )\n", + " )\n", + " if getattr(eval_result, \"metrics_table\", None) is not None:\n", + " display(Markdown(\"### Row‑wise Metrics\"))\n", + " display(eval_result.metrics_table.head())\n", + "\n", + "\n", + "def display_drilldown(row: pd.Series) -> None:\n", + " \"\"\"Displays a drill-down view for trajectory data within a row.\"\"\"\n", + "\n", + " style = \"white-space: pre-wrap; width: 800px; overflow-x: auto;\"\n", + "\n", + " if not (\n", + " isinstance(row[\"predicted_trajectory\"], list)\n", + " and isinstance(row[\"reference_trajectory\"], list)\n", + " ):\n", + " return\n", + "\n", + " for predicted_trajectory, reference_trajectory in zip(\n", + " row[\"predicted_trajectory\"], row[\"reference_trajectory\"]\n", + " ):\n", + " display(\n", + " HTML(\n", + " f\"

Tool Names:

{predicted_trajectory['tool_name'], reference_trajectory['tool_name']}
\"\n", + " )\n", + " )\n", + "\n", + " if not (\n", + " isinstance(predicted_trajectory.get(\"tool_input\"), dict)\n", + " and isinstance(reference_trajectory.get(\"tool_input\"), dict)\n", + " ):\n", + " continue\n", + "\n", + " for tool_input_key in predicted_trajectory[\"tool_input\"]:\n", + " print(\"Tool Input Key: \", tool_input_key)\n", + "\n", + " if tool_input_key in reference_trajectory[\"tool_input\"]:\n", + " print(\n", + " \"Tool Values: \",\n", + " predicted_trajectory[\"tool_input\"][tool_input_key],\n", + " reference_trajectory[\"tool_input\"][tool_input_key],\n", + " )\n", + " else:\n", + " print(\n", + " \"Tool Values: \",\n", + " predicted_trajectory[\"tool_input\"][tool_input_key],\n", + " \"N/A\",\n", + " )\n", + " print(\"\\n\")\n", + " display(HTML(\"
\"))\n", + "\n", + "\n", + "def display_dataframe_rows(\n", + " df: pd.DataFrame,\n", + " columns: list[str] | None = None,\n", + " num_rows: int = 3,\n", + " display_drilldown: bool = False,\n", + ") -> None:\n", + " \"\"\"Displays a subset of rows from a DataFrame, optionally including a drill-down view.\"\"\"\n", + "\n", + " if columns:\n", + " df = df[columns]\n", + "\n", + " base_style = \"font-family: monospace; font-size: 14px; white-space: pre-wrap; width: auto; overflow-x: auto;\"\n", + " header_style = base_style + \"font-weight: bold;\"\n", + "\n", + " for _, row in df.head(num_rows).iterrows():\n", + " for column in df.columns:\n", + " display(\n", + " HTML(\n", + " f\"{column.replace('_', ' ').title()}: \"\n", + " )\n", + " )\n", + " display(HTML(f\"{row[column]}
\"))\n", + "\n", + " display(HTML(\"
\"))\n", + "\n", + " if (\n", + " display_drilldown\n", + " and \"predicted_trajectory\" in df.columns\n", + " and \"reference_trajectory\" in df.columns\n", + " ):\n", + " display_drilldown(row)\n", + "\n", + "\n", + "def plot_bar_plot(\n", + " eval_result: pd.DataFrame, title: str, metrics: list[str] = None\n", + ") -> None:\n", + " fig = go.Figure()\n", + " data = []\n", + "\n", + " summary_metrics = eval_result.summary_metrics\n", + " if metrics:\n", + " summary_metrics = {\n", + " k: summary_metrics[k]\n", + " for k, v in summary_metrics.items()\n", + " if any(selected_metric in k for selected_metric in metrics)\n", + " }\n", + "\n", + " data.append(\n", + " go.Bar(\n", + " x=list(summary_metrics.keys()),\n", + " y=list(summary_metrics.values()),\n", + " name=title,\n", + " )\n", + " )\n", + "\n", + " fig = go.Figure(data=data)\n", + "\n", + " # Change the bar mode\n", + " fig.update_layout(barmode=\"group\")\n", + " fig.show()\n", + "\n", + "\n", + "def display_radar_plot(eval_results, title: str, metrics=None):\n", + " \"\"\"Plot the radar plot.\"\"\"\n", + " fig = go.Figure()\n", + " summary_metrics = eval_results.summary_metrics\n", + " if metrics:\n", + " summary_metrics = {\n", + " k: summary_metrics[k]\n", + " for k, v in summary_metrics.items()\n", + " if any(selected_metric in k for selected_metric in metrics)\n", + " }\n", + "\n", + " min_val = min(summary_metrics.values())\n", + " max_val = max(summary_metrics.values())\n", + "\n", + " fig.add_trace(\n", + " go.Scatterpolar(\n", + " r=list(summary_metrics.values()),\n", + " theta=list(summary_metrics.keys()),\n", + " fill=\"toself\",\n", + " name=title,\n", + " )\n", + " )\n", + " fig.update_layout(\n", + " title=title,\n", + " polar=dict(radialaxis=dict(visible=True, range=[min_val, max_val])),\n", + " showlegend=True,\n", + " )\n", + " fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bDaa2Mtsifmq" + }, + "source": [ + "## Build ADK agent\n", + "\n", + "Build your application using ADK, including the Gemini model and custom tools that you define." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KHwShhpOitKp" + }, + "source": [ + "### Set tools\n", + "\n", + "To start, set the tools that a customer support agent needs to do their job." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gA2ZKvfeislw" + }, + "outputs": [], + "source": [ + "def get_product_details(product_name: str):\n", + " \"\"\"Gathers basic details about a product.\"\"\"\n", + " details = {\n", + " \"smartphone\": \"A cutting-edge smartphone with advanced camera features and lightning-fast processing.\",\n", + " \"usb charger\": \"A super fast and light usb charger\",\n", + " \"shoes\": \"High-performance running shoes designed for comfort, support, and speed.\",\n", + " \"headphones\": \"Wireless headphones with advanced noise cancellation technology for immersive audio.\",\n", + " \"speaker\": \"A voice-controlled smart speaker that plays music, sets alarms, and controls smart home devices.\",\n", + " }\n", + " return details.get(product_name, \"Product details not found.\")\n", + "\n", + "\n", + "def get_product_price(product_name: str):\n", + " \"\"\"Gathers price about a product.\"\"\"\n", + " details = {\n", + " \"smartphone\": 500,\n", + " \"usb charger\": 10,\n", + " \"shoes\": 100,\n", + " \"headphones\": 50,\n", + " \"speaker\": 80,\n", + " }\n", + " return details.get(product_name, \"Product price not found.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "l4mk5XPui4Y1" + }, + "source": [ + "### Set the model\n", + "\n", + "Choose which Gemini AI model your agent will use. If you're curious about Gemini and its different capabilities, take a look at [the official documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models) for more details." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "BaYeo6K2i-w1" + }, + "outputs": [], + "source": [ + "model = \"gemini-2.0-flash\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tNlAY9cojEWz" + }, + "source": [ + "### Assemble the agent\n", + "\n", + "The Vertex AI Gen AI Evaluation works directly with 'Queryable' agents, and also lets you add your own custom functions with a specific structure (signature).\n", + "\n", + "In this case, you assemble the agent using a custom function. The function triggers the agent for a given input and parse the agent outcome to extract the response and called tools." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "gD5OB44g4sc3" + }, + "outputs": [], + "source": [ + "async def agent_parsed_outcome(query):\n", + " app_name = \"product_research_app\"\n", + " user_id = \"user_one\"\n", + " session_id = \"session_one\"\n", + " \n", + " product_research_agent = Agent(\n", + " name=\"ProductResearchAgent\",\n", + " model=model,\n", + " description=\"An agent that performs product research.\",\n", + " instruction=f\"\"\"\n", + " Analyze this user request: '{query}'.\n", + " If the request is about price, use get_product_price tool.\n", + " Otherwise, use get_product_details tool to get product information.\n", + " \"\"\",\n", + " tools=[get_product_details, get_product_price],\n", + " )\n", + "\n", + " session_service = InMemorySessionService()\n", + " await session_service.create_session(\n", + " app_name=app_name, user_id=user_id, session_id=session_id\n", + " )\n", + "\n", + " runner = Runner(\n", + " agent=product_research_agent, app_name=app_name, session_service=session_service\n", + " )\n", + "\n", + " content = types.Content(role=\"user\", parts=[types.Part(text=query)])\n", + " events = [event async for event in runner.run_async(user_id=user_id, session_id=session_id, new_message=content)]\n", + " \n", + " return parse_adk_output_to_dictionary(events)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# --- Sync wrapper for Vertex‑AI evaluation\n", + "def agent_parsed_outcome_sync(prompt: str):\n", + " result = asyncio.run(agent_parsed_outcome(prompt))\n", + " result[\"predicted_trajectory\"] = json.dumps(result[\"predicted_trajectory\"])\n", + " return result" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_HGcs6PVjRj_" + }, + "source": [ + "### Test the agent\n", + "\n", + "Query your agent." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lGb58OJkjUs9" + }, + "outputs": [], + "source": [ + "response = await agent_parsed_outcome(query=\"Get product details for shoes\")\n", + "display(Markdown(format_output_as_markdown(response)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2wCFstt8w4Dx" + }, + "outputs": [], + "source": [ + "response = await agent_parsed_outcome(query=\"Get product price for shoes\")\n", + "display(Markdown(format_output_as_markdown(response)))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "aOGPePsorpUl" + }, + "source": [ + "## Evaluating a ADK agent with Vertex AI Gen AI Evaluation\n", + "\n", + "When working with AI agents, it's important to keep track of their performance and how well they're working. You can look at this in two main ways: **monitoring** and **observability**.\n", + "\n", + "Monitoring focuses on how well your agent is performing specific tasks:\n", + "\n", + "* **Single Tool Selection**: Is the agent choosing the right tools for the job?\n", + "\n", + "* **Multiple Tool Selection (or Trajectory)**: Is the agent making logical choices in the order it uses tools?\n", + "\n", + "* **Response generation**: Is the agent's output good, and does it make sense based on the tools it used?\n", + "\n", + "Observability is about understanding the overall health of the agent:\n", + "\n", + "* **Latency**: How long does it take the agent to respond?\n", + "\n", + "* **Failure Rate**: How often does the agent fail to produce a response?\n", + "\n", + "Vertex AI Gen AI Evaluation service helps you to assess all of these aspects both while you are prototyping the agent or after you deploy it in production. It provides [pre-built evaluation criteria and metrics](https://cloud.google.com/vertex-ai/generative-ai/docs/models/determine-eval) so you can see exactly how your agents are doing and identify areas for improvement." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e43229f3ad4f" + }, + "source": [ + "### Prepare Agent Evaluation dataset\n", + "\n", + "To evaluate your AI agent using the Vertex AI Gen AI Evaluation service, you need a specific dataset depending on what aspects you want to evaluate of your agent. \n", + "\n", + "This dataset should include the prompts given to the agent. It can also contain the ideal or expected response (ground truth) and the intended sequence of tool calls the agent should take (reference trajectory) representing the sequence of tools you expect agent calls for each given prompt.\n", + "\n", + "> Optionally, you can provide both generated responses and predicted trajectory (**Bring-Your-Own-Dataset scenario**).\n", + "\n", + "Below you have an example of dataset you might have with a customer support agent with user prompt and the reference trajectory." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "fFf8uTdUiDt3" + }, + "outputs": [], + "source": [ + "eval_data = {\n", + " \"prompt\": [\n", + " \"Get price for smartphone\",\n", + " \"Get product details and price for headphones\",\n", + " \"Get details for usb charger\",\n", + " \"Get product details and price for shoes\",\n", + " \"Get product details for speaker?\",\n", + " ],\n", + " \"predicted_trajectory\": [\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"smartphone\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"usb charger\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"shoes\"},\n", + " },\n", + " {\"tool_name\": \"get_product_price\", \"tool_input\": {\"product_name\": \"shoes\"}},\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"speaker\"},\n", + " }\n", + " ],\n", + " ],\n", + "}\n", + "\n", + "eval_sample_dataset = pd.DataFrame(eval_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PQEI1EcfvFHb" + }, + "source": [ + "Print some samples from the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "EjsonqWWvIvE" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(eval_sample_dataset, num_rows=3)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "m4CvBuf1afHG" + }, + "source": [ + "### Single tool usage evaluation\n", + "\n", + "After you've set your AI agent and the evaluation dataset, you start evaluating if the agent is choosing the correct single tool for a given task.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_rS5GGKHd5bx" + }, + "source": [ + "#### Set single tool usage metrics\n", + "\n", + "The `trajectory_single_tool_use` metric in Vertex AI Gen AI Evaluation gives you a quick way to evaluate whether your agent is using the tool you expect it to use, regardless of any specific tool order. It's a basic but useful way to start evaluating if the right tool was used at some point during the agent's process.\n", + "\n", + "To use the `trajectory_single_tool_use` metric, you need to set what tool should have been used for a particular user's request. For example, if a user asks to \"send an email\", you might expect the agent to use an \"send_email\" tool, and you'd specify that tool's name when using this metric.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "xixvq8dwd5by" + }, + "outputs": [], + "source": [ + "single_tool_usage_metrics = [TrajectorySingleToolUse(tool_name=\"get_product_price\")]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ktKZoT2Qd5by" + }, + "source": [ + "#### Run an evaluation task\n", + "\n", + "To run the evaluation, you initiate an `EvalTask` using the pre-defined dataset (`eval_sample_dataset`) and metrics (`single_tool_usage_metrics` in this case) within an experiment. Then, you run the evaluation using agent_parsed_outcome function and assigns a unique identifier to this specific evaluation run, storing and visualizing the evaluation results.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SRv43fDcd5by" + }, + "outputs": [], + "source": [ + "EXPERIMENT_RUN = f\"single-metric-eval-{get_id()}\"\n", + "\n", + "single_tool_call_eval_task = EvalTask(\n", + " dataset=eval_sample_dataset,\n", + " metrics=single_tool_usage_metrics,\n", + " experiment=EXPERIMENT_NAME,\n", + " output_uri_prefix=BUCKET_URI + \"/single-metric-eval\",\n", + ")\n", + "\n", + "single_tool_call_eval_result = single_tool_call_eval_task.evaluate(\n", + " runnable=agent_parsed_outcome_sync, experiment_run_name=EXPERIMENT_RUN\n", + ")\n", + "\n", + "display_eval_report(single_tool_call_eval_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6o5BjSTFKVMS" + }, + "source": [ + "#### Visualize evaluation results\n", + "\n", + "Use some helper functions to visualize a sample of evaluation result." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1Jopzw83k14w" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(single_tool_call_eval_result.metrics_table, num_rows=3)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JlujdJpu5Kn6" + }, + "source": [ + "### Trajectory Evaluation\n", + "\n", + "After evaluating the agent's ability to select the single most appropriate tool for a given task, you generalize the evaluation by analyzing the tool sequence choices with respect to the user input (trajectory). This assesses whether the agent not only chooses the right tools but also utilizes them in a rational and effective order." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8s-nHdDJneHM" + }, + "source": [ + "#### Set trajectory metrics\n", + "\n", + "To evaluate agent's trajectory, Vertex AI Gen AI Evaluation provides several ground-truth based metrics:\n", + "\n", + "* `trajectory_exact_match`: identical trajectories (same actions, same order)\n", + "\n", + "* `trajectory_in_order_match`: reference actions present in predicted trajectory, in order (extras allowed)\n", + "\n", + "* `trajectory_any_order_match`: all reference actions present in predicted trajectory (order, extras don't matter).\n", + "\n", + "* `trajectory_precision`: proportion of predicted actions present in reference\n", + "\n", + "* `trajectory_recall`: proportion of reference actions present in predicted. \n", + "\n", + "All metrics score 0 or 1, except `trajectory_precision` and `trajectory_recall` which range from 0 to 1." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "c32WIS95neHN" + }, + "outputs": [], + "source": [ + "trajectory_metrics = [\n", + " \"trajectory_exact_match\",\n", + " \"trajectory_in_order_match\",\n", + " \"trajectory_any_order_match\",\n", + " \"trajectory_precision\",\n", + " \"trajectory_recall\",\n", + "]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DF3jhTH3neHN" + }, + "source": [ + "#### Run an evaluation task\n", + "\n", + "Submit an evaluation by running `evaluate` method of the new `EvalTask`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vOdS7TJUneHN" + }, + "outputs": [], + "source": [ + "EXPERIMENT_RUN = f\"trajectory-{get_id()}\"\n", + "\n", + "trajectory_eval_task = EvalTask(\n", + " dataset=eval_sample_dataset,\n", + " metrics=trajectory_metrics,\n", + " experiment=EXPERIMENT_NAME,\n", + " output_uri_prefix=BUCKET_URI + \"/multiple-metric-eval\",\n", + ")\n", + "\n", + "trajectory_eval_result = trajectory_eval_task.evaluate(\n", + " runnable=agent_parsed_outcome_sync, experiment_run_name=EXPERIMENT_RUN\n", + ")\n", + "\n", + "display_eval_report(trajectory_eval_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DBiUI3LyLBtj" + }, + "source": [ + "#### Visualize evaluation results\n", + "\n", + "Print and visualize a sample of evaluation results." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "z7-LdM3mLBtk" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(trajectory_eval_result.metrics_table, num_rows=3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "sLVRdN5llA0h" + }, + "outputs": [], + "source": [ + "plot_bar_plot(\n", + " trajectory_eval_result,\n", + " title=\"Trajectory Metrics\",\n", + " metrics=[f\"{metric}/mean\" for metric in trajectory_metrics],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "T8TipU2akHEd" + }, + "source": [ + "### Evaluate final response\n", + "\n", + "Similar to model evaluation, you can evaluate the final response of the agent using Vertex AI Gen AI Evaluation." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DeK-py7ykkDN" + }, + "source": [ + "#### Set response metrics\n", + "\n", + "After agent inference, Vertex AI Gen AI Evaluation provides several metrics to evaluate generated responses. You can use computation-based metrics to compare the response to a reference (if needed) and using existing or custom model-based metrics to determine the quality of the final response.\n", + "\n", + "Check out the [documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/models/determine-eval) to learn more.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "cyGHGgeVklvz" + }, + "outputs": [], + "source": [ + "response_metrics = [\"safety\", \"coherence\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DaBJWcg1kn55" + }, + "source": [ + "#### Run an evaluation task\n", + "\n", + "To evaluate agent's generated responses, use the `evaluate` method of the EvalTask class." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wRb2EC_hknSD" + }, + "outputs": [], + "source": [ + "EXPERIMENT_RUN = f\"response-{get_id()}\"\n", + "\n", + "response_eval_task = EvalTask(\n", + " dataset=eval_sample_dataset,\n", + " metrics=response_metrics,\n", + " experiment=EXPERIMENT_NAME,\n", + " output_uri_prefix=BUCKET_URI + \"/response-metric-eval\",\n", + ")\n", + "\n", + "response_eval_result = response_eval_task.evaluate(\n", + " runnable=agent_parsed_outcome_sync, experiment_run_name=EXPERIMENT_RUN\n", + ")\n", + "\n", + "display_eval_report(response_eval_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JtewTwiwg9qH" + }, + "source": [ + "#### Visualize evaluation results\n", + "\n", + "\n", + "Print new evaluation result sample." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ZODTRuq2lF75" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(response_eval_result.metrics_table, num_rows=3)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ntRBK3Te6PEc" + }, + "source": [ + "### Evaluate generated response conditioned by tool choosing\n", + "\n", + "When evaluating AI agents that interact with environments, standard text generation metrics like coherence may not be sufficient. This is because these metrics primarily focus on text structure, while agent responses should be assessed based on their effectiveness within the environment.\n", + "\n", + "Instead, use custom metrics that assess whether the agent's response logically follows from its tools choices like the one you have in this section." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4bENwFcd6prX" + }, + "source": [ + "#### Define a custom metric\n", + "\n", + "According to the [documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/models/determine-eval#model-based-metrics), you can define a prompt template for evaluating whether an AI agent's response follows logically from its actions by setting up criteria and a rating system for this evaluation.\n", + "\n", + "Define a `criteria` to set the evaluation guidelines and a `pointwise_rating_rubric` to provide a scoring system (1 or 0). Then use a `PointwiseMetricPromptTemplate` to create the template using these components.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "txGEHcg76riI" + }, + "outputs": [], + "source": [ + "criteria = {\n", + " \"Follows trajectory\": (\n", + " \"Evaluate whether the agent's response logically follows from the \"\n", + " \"sequence of actions it took. Consider these sub-points:\\n\"\n", + " \" - Does the response reflect the information gathered during the trajectory?\\n\"\n", + " \" - Is the response consistent with the goals and constraints of the task?\\n\"\n", + " \" - Are there any unexpected or illogical jumps in reasoning?\\n\"\n", + " \"Provide specific examples from the trajectory and response to support your evaluation.\"\n", + " )\n", + "}\n", + "\n", + "pointwise_rating_rubric = {\n", + " \"1\": \"Follows trajectory\",\n", + " \"0\": \"Does not follow trajectory\",\n", + "}\n", + "\n", + "response_follows_trajectory_prompt_template = PointwiseMetricPromptTemplate(\n", + " criteria=criteria,\n", + " rating_rubric=pointwise_rating_rubric,\n", + " input_variables=[\"prompt\", \"predicted_trajectory\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8MJqXu0kikxd" + }, + "source": [ + "Print the prompt_data of this template containing the combined criteria and rubric information ready for use in an evaluation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5EL7iEDMikNQ" + }, + "outputs": [], + "source": [ + "print(response_follows_trajectory_prompt_template.prompt_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e1djVp7Fi4Yy" + }, + "source": [ + "After you define the evaluation prompt template, set up the associated metric to evaluate how well a response follows a specific trajectory. The `PointwiseMetric` creates a metric where `response_follows_trajectory` is the metric's name and `response_follows_trajectory_prompt_template` provides instructions or context for evaluation you set up before.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Nx1xbZD87iMj" + }, + "outputs": [], + "source": [ + "response_follows_trajectory_metric = PointwiseMetric(\n", + " metric=\"response_follows_trajectory\",\n", + " metric_prompt_template=response_follows_trajectory_prompt_template,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1pmxLwTe7Ywv" + }, + "source": [ + "#### Set response metrics\n", + "\n", + "Set new generated response evaluation metrics by including the custom metric.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wrsbVFDd7Ywv" + }, + "outputs": [], + "source": [ + "response_tool_metrics = [\n", + " \"trajectory_exact_match\",\n", + " \"trajectory_in_order_match\",\n", + " \"safety\",\n", + " response_follows_trajectory_metric,\n", + "]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Lo-Sza807Ywv" + }, + "source": [ + "#### Run an evaluation task\n", + "\n", + "Run a new agent's evaluation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "_dkb4gSn7Ywv" + }, + "outputs": [], + "source": [ + "EXPERIMENT_RUN = f\"response-over-tools-{get_id()}\"\n", + "\n", + "response_eval_tool_task = EvalTask(\n", + " dataset=eval_sample_dataset,\n", + " metrics=response_tool_metrics,\n", + " experiment=EXPERIMENT_NAME,\n", + " output_uri_prefix=BUCKET_URI + \"/reasoning-metric-eval\",\n", + ")\n", + "\n", + "response_eval_tool_result = response_eval_tool_task.evaluate(\n", + " # Uncomment the line below if you are providing the agent with an unparsed dataset\n", + " #runnable=agent_parsed_outcome_sync, \n", + " experiment_run_name=EXPERIMENT_RUN\n", + ")\n", + "\n", + "display_eval_report(response_eval_tool_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AtOfIFi2j88g" + }, + "source": [ + "#### Visualize evaluation results\n", + "\n", + "Visualize evaluation result sample." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "GH2YvXgLlLH7" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(response_eval_tool_result.metrics_table, num_rows=3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "tdVhCURXMdLG" + }, + "outputs": [], + "source": [ + "plot_bar_plot(\n", + " response_eval_tool_result,\n", + " title=\"Response Metrics\",\n", + " metrics=[f\"{metric}/mean\" for metric in response_tool_metrics],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4nuUDP3a2eTB" + }, + "source": [ + "## Bonus: Bring-Your-Own-Dataset (BYOD) and evaluate a LangGraph agent using Vertex AI Gen AI Evaluation\n", + "\n", + "In Bring Your Own Dataset (BYOD) [scenarios](https://cloud.google.com/vertex-ai/generative-ai/docs/models/evaluation-dataset), you provide both the predicted trajectory and the generated response from the agent.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DRLKlmWd27PK" + }, + "source": [ + "### Bring your own evaluation dataset\n", + "\n", + "Define the evaluation dataset with the predicted trajectory and the generated response." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "y9hBgsg324Ej" + }, + "outputs": [], + "source": [ + "byod_eval_data = {\n", + " \"prompt\": [\n", + " \"Get price for smartphone\",\n", + " \"Get product details and price for headphones\",\n", + " \"Get details for usb charger\",\n", + " \"Get product details and price for shoes\",\n", + " \"Get product details for speaker?\",\n", + " ],\n", + " \"reference_trajectory\": [\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"smartphone\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"usb charger\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"shoes\"},\n", + " },\n", + " {\"tool_name\": \"get_product_price\", \"tool_input\": {\"product_name\": \"shoes\"}},\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"speaker\"},\n", + " }\n", + " ],\n", + " ],\n", + " \"predicted_trajectory\": [\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"smartphone\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " {\n", + " \"tool_name\": \"get_product_price\",\n", + " \"tool_input\": {\"product_name\": \"headphones\"},\n", + " },\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"usb charger\"},\n", + " }\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"shoes\"},\n", + " },\n", + " {\"tool_name\": \"get_product_price\", \"tool_input\": {\"product_name\": \"shoes\"}},\n", + " ],\n", + " [\n", + " {\n", + " \"tool_name\": \"get_product_details\",\n", + " \"tool_input\": {\"product_name\": \"speaker\"},\n", + " }\n", + " ],\n", + " ],\n", + " \"response\": [\n", + " \"500\",\n", + " \"50\",\n", + " \"A super fast and light usb charger\",\n", + " \"100\",\n", + " \"A voice-controlled smart speaker that plays music, sets alarms, and controls smart home devices.\",\n", + " ],\n", + "}\n", + "\n", + "byod_eval_sample_dataset = pd.DataFrame(byod_eval_data)\n", + "byod_eval_sample_dataset[\"predicted_trajectory\"] = byod_eval_sample_dataset[\n", + " \"predicted_trajectory\"\n", + "].apply(json.dumps)\n", + "byod_eval_sample_dataset[\"reference_trajectory\"] = byod_eval_sample_dataset[\n", + " \"reference_trajectory\"\n", + "].apply(json.dumps)\n", + "byod_eval_sample_dataset[\"response\"] = byod_eval_sample_dataset[\"response\"].apply(json.dumps)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oEYmU2eJ7q-1" + }, + "source": [ + "### Run an evaluation task\n", + "\n", + "Run a new agent's evaluation using your own dataset and the same setting of the latest evaluation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wBD-4wpB7q-3" + }, + "outputs": [], + "source": [ + "EXPERIMENT_RUN_NAME = f\"response-over-tools-byod-{get_id()}\"\n", + "\n", + "byod_response_eval_tool_task = EvalTask(\n", + " dataset=byod_eval_sample_dataset,\n", + " metrics=response_tool_metrics,\n", + " experiment=EXPERIMENT_NAME,\n", + " output_uri_prefix=BUCKET_URI + \"/byod-eval\",\n", + ")\n", + "\n", + "byod_response_eval_tool_result = byod_response_eval_tool_task.evaluate(\n", + " experiment_run_name=EXPERIMENT_RUN_NAME\n", + ")\n", + "\n", + "display_eval_report(byod_response_eval_tool_result)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9eU3LG6r7q-3" + }, + "source": [ + "### Visualize evaluation results\n", + "\n", + "Visualize evaluation result sample." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "pQFzmd2I7q-3" + }, + "outputs": [], + "source": [ + "display_dataframe_rows(byod_response_eval_tool_result.metrics_table, num_rows=3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "84HiPDOkPseW" + }, + "outputs": [], + "source": [ + "display_radar_plot(\n", + " byod_response_eval_tool_result,\n", + " title=\"ADK agent evaluation\",\n", + " metrics=[f\"{metric}/mean\" for metric in response_tool_metrics],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fIppkS2jq_Dn" + }, + "source": [ + "## Cleaning up\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Ox2I3UfRlTOd" + }, + "outputs": [], + "source": [ + "delete_experiment = True\n", + "\n", + "if delete_experiment:\n", + " try:\n", + " experiment = aiplatform.Experiment(EXPERIMENT_NAME)\n", + " experiment.delete(delete_backing_tensorboard_runs=True)\n", + " except Exception as e:\n", + " print(e)" + ] + } + ], + "metadata": { + "colab": { + "name": "evaluating_adk_agent.ipynb", + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..b9388dd --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,20 @@ +[tool.ruff] +line-length = 120 +target-version = "py312" + +[tool.ruff.lint] +select = ["E", "F", "B", "I"] # warnings, errors, bugbear, isort + +[tool.mypy] +python_version = "3.12" +warn_return_any = true +warn_unused_configs = true +disallow_untyped_defs = true + +[tool.pytest.ini_options] +minversion = "7.0" +addopts = "-ra -q" +pythonpath = ["."] +testpaths = [ + "tests", +] diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..bdca561 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,26 @@ +# Core ADK and Models +google-adk>=1.0 +google-genai>=0.2.0 + +# Server +fastapi>=0.110.0 +uvicorn>=0.29.0 +python-telegram-bot>=21.0.1 + +# GCP Services +google-cloud-firestore>=2.15.0 +google-cloud-dlp>=3.16.0 +google-cloud-secret-manager>=2.18.0 +google-cloud-logging>=3.9.0 +google-cloud-trace>=1.11.2 + +# Config +pydantic-settings>=2.2.1 + +# Testing & Dev +pytest>=8.1.1 +pytest-cov>=5.0.0 +pytest-mock>=3.14.0 +ruff>=0.3.0 +mypy>=1.9.0 +httpx>=0.27.0 diff --git a/secure-openclaw-build-plan.md b/secure-openclaw-build-plan.md new file mode 100644 index 0000000..17f7620 --- /dev/null +++ b/secure-openclaw-build-plan.md @@ -0,0 +1,581 @@ +# Build Plan: Secure OpenClaw Alternative on Google Cloud +**"From Zero to Secure AI Assistant in a Weekend"** + +--- + +## Overview + +| Item | Detail | +|------|--------| +| **Total Build Time** | 12–16 hours (spread over a weekend) | +| **Estimated Cost** | $0 – $5/month (free tier + pay-as-you-go) | +| **Prerequisites** | GCP account, Python 3.11+, Telegram account | +| **Final Result** | A Telegram-based AI assistant with 4 tools, persistent memory, proactive scheduling, and 6 security layers — all deployed on Cloud Run | +| **GitHub Deliverable** | Complete repo with Terraform IaC, ADK agent code, and README | + +--- + +## Phase 0: Foundation Setup (1 hour) + +### 0.1 — GCP Project Setup +- [ ] Create a new GCP project: `secure-agent-demo` +- [ ] Enable billing (free tier covers everything, but billing must be active) +- [ ] Set project-level budget alert at $5/month (good habit to demonstrate in article) +- [ ] Enable required APIs: + ``` + Cloud Run API + Cloud Build API + Secret Manager API + Cloud Scheduler API + Firestore API + Cloud DLP API + Cloud Logging API + Artifact Registry API + ``` + +### 0.2 — Local Development Environment +- [ ] Create project directory structure: + ``` + secure-agent/ + ├── agent/ + │ ├── __init__.py + │ ├── main.py # FastAPI gateway + │ ├── agent.py # ADK agent orchestrator + │ ├── memory.py # Firestore memory manager + │ ├── security/ + │ │ ├── __init__.py + │ │ ├── dlp_filter.py # PII detection pre-processor + │ │ ├── input_guard.py # Input validation + │ │ ├── output_guard.py # Output sanitisation + │ │ └── approval.py # Human-in-the-loop flow + │ └── tools/ + │ ├── __init__.py + │ ├── gmail_reader.py + │ ├── calendar_mgr.py + │ ├── file_organiser.py + │ └── web_search.py + ├── terraform/ + │ ├── main.tf + │ ├── variables.tf + │ ├── cloud_run.tf + │ ├── secrets.tf + │ ├── scheduler.tf + │ ├── iam.tf + │ └── firestore.tf + ├── tests/ + │ ├── test_agent.py + │ ├── test_security.py + │ └── test_tools.py + ├── Dockerfile + ├── requirements.txt + ├── .env.example # Template only — NO real secrets + └── README.md + ``` +- [ ] Create Python virtual environment: `python -m venv .venv` +- [ ] Install core dependencies: + ``` + google-adk + google-cloud-firestore + google-cloud-dlp + google-cloud-secret-manager + google-cloud-logging + python-telegram-bot + fastapi + uvicorn + ``` + +### 0.3 — Telegram Bot Creation +- [ ] Open Telegram → search @BotFather → `/newbot` +- [ ] Name: `SecureAgentDemo` (or your preference) +- [ ] Save the bot token (DO NOT commit — goes into Secret Manager in Phase 3) +- [ ] Set bot description: `/setdescription` → "A secure AI assistant built on Google Cloud" + +### 0.4 — Gemini API Key +- [ ] Go to [AI Studio](https://aistudio.google.com/apikey) +- [ ] Generate API key for your project +- [ ] Note free tier limits: 15 RPM, 1M TPD, 1,500 RPD for Gemini 2.0 Flash +- [ ] Save key (goes into Secret Manager — never in code) + +**Phase 0 Checkpoint:** Project created, APIs enabled, Telegram bot exists, Gemini key ready, local dev structure set up. + +--- + +## Phase 1: ADK Agent Core — The Brain (3 hours) + +### 1.1 — Basic ADK Agent (45 mins) +Build a minimal agent that responds to text input using Gemini. + +- [ ] Create `agent/agent.py`: + - Initialise ADK agent with Gemini 2.0 Flash as the model + - Define agent system prompt: + > "You are a helpful personal assistant. You can read emails, manage calendars, organise files, and search the web. Always explain what you're about to do before doing it. For any destructive action (delete, send, modify), ask for explicit confirmation first." + - Set up basic conversation handling (text in → text out) +- [ ] Test locally with ADK's built-in dev server: `adk web` +- [ ] Verify: Send "Hello, what can you do?" → agent responds with capabilities list + +### 1.2 — First Tool: Web Search (30 mins) +Start with the simplest tool to prove the ADK tool pattern works. + +- [ ] Create `agent/tools/web_search.py`: + - Use Google Custom Search JSON API (100 queries/day free) + - Or use `googlesearch-python` library for zero-config demo + - ADK `@tool` decorator with clear docstring (this is what the LLM reads) +- [ ] Register tool with agent +- [ ] Test: "Search for the latest news about OpenClaw security" → agent calls tool → returns summary + +### 1.3 — Gmail Reader Tool (45 mins) +The tool that makes the demo feel like OpenClaw. + +- [ ] Set up Gmail API OAuth: + - Create OAuth 2.0 credentials in GCP console (type: Desktop app for local dev) + - Download `credentials.json` (local dev only — production uses WIF) + - First run: browser-based auth → generates `token.json` +- [ ] Create `agent/tools/gmail_reader.py`: + - `read_inbox(max_results: int = 5)` → returns subject, sender, snippet + - `search_emails(query: str)` → Gmail search syntax + - `read_email(message_id: str)` → full email body + - **READ-ONLY** — no send/delete/modify at this stage +- [ ] Register with agent +- [ ] Test: "Show me my latest 3 emails" → agent calls tool → returns formatted email list + +### 1.4 — Calendar Manager Tool (30 mins) +- [ ] Create `agent/tools/calendar_mgr.py`: + - `list_events(days_ahead: int = 7)` → upcoming events + - `check_availability(date: str)` → free/busy slots + - `create_event(title, start, end, description)` → **requires confirmation** (Phase 4) +- [ ] Register with agent +- [ ] Test: "What's on my calendar this week?" → formatted event list + +### 1.5 — File Organiser Tool (30 mins) +- [ ] Create `agent/tools/file_organiser.py`: + - Uses Google Drive API + - `list_recent_files(max_results: int = 10)` → recent Drive files + - `search_files(query: str)` → Drive file search + - `summarise_document(file_id: str)` → reads doc content, returns Gemini summary + - **READ-ONLY** — no move/delete/rename at this stage +- [ ] Register with agent +- [ ] Test: "Find my recent documents about MLOps" → returns matching files + +**Phase 1 Checkpoint:** ADK agent running locally with 4 tools. You can have a conversation, search the web, read emails, check calendar, and find files. All via ADK dev server. + +--- + +## Phase 2: Telegram Integration — The Interface (2 hours) + +### 2.1 — FastAPI Gateway (30 mins) +- [ ] Create `agent/main.py`: + - FastAPI app with webhook endpoint: `POST /webhook/telegram` + - Parse Telegram update → extract message text and chat_id + - Pass text to ADK agent → get response + - Send response back via Telegram Bot API + - Health check endpoint: `GET /health` +- [ ] Test locally with ngrok: + - Run `ngrok http 8080` + - Set Telegram webhook: `https://{ngrok-url}/webhook/telegram` + - Send message in Telegram → response appears + +### 2.2 — Rich Telegram Responses (30 mins) +Make the demo feel polished — this matters for the article screenshots. + +- [ ] Format agent responses with Telegram Markdown: + - Email subjects in **bold** + - Calendar events with 📅 time formatting + - Tool actions with inline status indicators + - Error messages with clear explanation +- [ ] Add "typing" indicator while agent processes +- [ ] Add `/help` command with available capabilities +- [ ] Add `/status` command showing connected tools + +### 2.3 — Conversation Context (30 mins) +- [ ] Implement session tracking by Telegram chat_id +- [ ] Maintain last 10 messages in memory for context +- [ ] Agent can reference previous messages: "Summarise that last email you showed me" +- [ ] Test multi-turn conversations work naturally + +### 2.4 — Basic Error Handling (30 mins) +- [ ] Gemini API rate limit → friendly "I'm thinking, try again in a moment" +- [ ] Tool failures → "I couldn't access your emails right now. Here's why: {error}" +- [ ] Timeout handling → long operations get progress updates +- [ ] Invalid input → guide user to correct format + +**Phase 2 Checkpoint:** Working Telegram bot. Message it from your phone, ask about emails, calendar, files. Multi-turn conversations work. Screenshots look clean for the article. + +--- + +## Phase 3: Security Layers — The Differentiator (3 hours) + +This is the phase that makes your article unique. Each security layer directly maps to a documented OpenClaw vulnerability. + +### 3.1 — Secret Manager Integration (30 mins) +**Solves:** OpenClaw stores API keys in `.env` files on disk (Snyk finding: 7.1% of ClawHub skills leak credentials). + +- [ ] Create secrets in Secret Manager: + ``` + TELEGRAM_BOT_TOKEN + GEMINI_API_KEY + GMAIL_OAUTH_TOKEN + ``` +- [ ] Update application code to fetch from Secret Manager at startup: + ```python + from google.cloud import secretmanager + + def get_secret(secret_id: str) -> str: + client = secretmanager.SecretManagerServiceClient() + name = f"projects/{PROJECT_ID}/secrets/{secret_id}/versions/latest" + response = client.access_secret_version(request={"name": name}) + return response.payload.data.decode("UTF-8") + ``` +- [ ] Remove all hardcoded credentials from code +- [ ] Delete local `.env` file, update `.gitignore` +- [ ] **Article callout:** Side-by-side comparison of OpenClaw's `.env` file vs your Secret Manager approach + +### 3.2 — Cloud DLP Pre-Processing Filter (45 mins) +**Solves:** OpenClaw has zero PII detection. User messages and tool outputs can contain sensitive data that gets sent to LLM APIs. + +- [ ] Create `agent/security/dlp_filter.py`: + - `scan_for_pii(text: str) -> DLPResult`: + - Scans input text using Cloud DLP API + - Detects: credit cards, phone numbers, emails, national IDs, names + - Returns: found PII types + redacted text + - `filter_input(message: str) -> str`: + - Runs DLP scan on user message before it reaches Gemini + - If PII found: warns user via Telegram, sends redacted version to agent + - `filter_output(response: str) -> str`: + - Scans agent response before sending back to user + - Catches cases where tools return PII from emails/files +- [ ] Wire into gateway: input → DLP filter → agent → DLP filter → output +- [ ] Test: Send "My credit card is 4111-1111-1111-1111" → agent receives redacted version + user gets warning +- [ ] **Article callout:** The Meta AI safety director's agent had full access to her email. DLP would have flagged the PII in those emails before the agent could act on them. + +### 3.3 — Input/Output Guard Rails (30 mins) +**Solves:** OpenClaw has no content filtering beyond whatever the LLM model provides. Prompt injection through tool outputs is documented. + +- [ ] Create `agent/security/input_guard.py`: + - Block prompt injection patterns: + - "Ignore previous instructions" + - "You are now a..." + - System prompt extraction attempts + - Validate message length (prevent context stuffing) + - Rate limiting per user (prevent abuse) + +- [ ] Create `agent/security/output_guard.py`: + - Scan tool outputs for injection attempts before feeding back to agent + - Validate agent responses don't contain: + - Raw credentials or tokens + - Internal system details + - Instructions to bypass security + - Truncate excessively long outputs + +- [ ] **Article callout:** OpenClaw's Zenity-documented vulnerability — a malicious skill can inject persistent backdoor instructions. Your guard rails prevent this attack vector. + +### 3.4 — Human-in-the-Loop Approval (45 mins) +**Solves:** OpenClaw executes actions autonomously with no confirmation. Summer Yue's agent mass-deleted emails without asking. + +- [ ] Create `agent/security/approval.py`: + - Define action risk levels: + - **LOW (auto-approve):** Read email, list files, check calendar, web search + - **MEDIUM (confirm once):** Summarise document, search emails + - **HIGH (always confirm):** Create event, send email, modify files, delete anything + - Approval flow: + 1. Agent decides to take HIGH-risk action + 2. Agent sends Telegram message: "I'd like to create a calendar event: {details}. Approve? ✅ / ❌" + 3. User taps inline button + 4. Only on ✅ does the tool execute + - Implement Telegram inline keyboard for approve/reject + - Timeout after 5 minutes → action cancelled with explanation + +- [ ] Wire into ADK tool execution pipeline +- [ ] Test: "Schedule a meeting tomorrow at 3pm" → confirmation prompt → approve → event created +- [ ] **Article callout:** Direct comparison — "OpenClaw's agent deleted 4,000 emails without asking. Our agent asks before creating a single calendar event." + +### 3.5 — IAM Conditions + Least Privilege (30 mins) +**Solves:** OpenClaw runs with whatever permissions the user's machine has — typically full access to everything. + +- [ ] Create dedicated service account: `agent-runtime@{project}.iam.gserviceaccount.com` +- [ ] Grant minimum permissions: + ``` + roles/secretmanager.secretAccessor (read secrets only) + roles/datastore.user (Firestore read/write) + roles/dlp.user (DLP scan only) + roles/logging.logWriter (write logs only) + ``` +- [ ] Add IAM Condition on service account: + - Time-based: only active during working hours (optional — shows the pattern) + - Resource-based: can only access specific Firestore collection +- [ ] **Article callout:** OpenClaw documentation literally says "give it access to everything." IAM Conditions let you be surgical. + +**Phase 3 Checkpoint:** All 6 security layers active. Every message flows through DLP, guard rails filter inputs/outputs, destructive actions require approval, secrets are in Secret Manager, IAM follows least privilege. You can now demonstrate each layer with a concrete test. + +--- + +## Phase 4: Persistent Memory — The Intelligence (1.5 hours) + +### 4.1 — Firestore Memory Schema (30 mins) +- [ ] Create Firestore database (Native mode, free tier) +- [ ] Design collections: + ``` + conversations/{chat_id}/messages/{msg_id} + - role: "user" | "assistant" + - content: string + - timestamp: datetime + - tools_used: string[] + + users/{chat_id}/preferences + - name: string + - timezone: string + - summary_style: "brief" | "detailed" + - approved_actions: string[] + + agent_state/{chat_id} + - last_active: datetime + - pending_approvals: map[] + - context_summary: string (rolling summary of past conversations) + ``` + +### 4.2 — Memory Manager (30 mins) +- [ ] Create `agent/memory.py`: + - `save_message(chat_id, role, content, tools_used)` + - `get_recent_context(chat_id, limit=20) -> list[Message]` + - `get_user_preferences(chat_id) -> Preferences` + - `update_context_summary(chat_id)` — periodically compress old conversations into summary using Gemini +- [ ] Integrate with agent — conversation history loaded at each interaction +- [ ] Test: Close and reopen Telegram → agent remembers previous conversation + +### 4.3 — Smart Context Window (30 mins) +- [ ] Implement rolling context strategy: + - Last 10 messages: full content + - Previous 50 messages: Gemini-generated summary + - Older: discarded (but stored in Firestore for audit) +- [ ] User preferences persist across sessions +- [ ] Agent learns: "You usually want brief summaries" based on past interactions +- [ ] **Article callout:** OpenClaw's local JSON memory vs cloud-native persistent memory — resilience, security, and multi-device access. + +**Phase 4 Checkpoint:** Agent remembers conversations across sessions, learns user preferences, and manages context efficiently. This is where it starts feeling genuinely useful. + +--- + +## Phase 5: Proactive Agent — The Heartbeat (1 hour) + +### 5.1 — Cloud Scheduler Setup (20 mins) +- [ ] Create scheduled job: `morning-briefing` + - Schedule: `0 8 * * 1-5` (8am weekdays) + - Target: Cloud Run endpoint `POST /scheduled/briefing` + - Payload: `{"chat_id": "{your_telegram_id}"}` +- [ ] Create endpoint in FastAPI that triggers agent briefing flow + +### 5.2 — Morning Briefing Flow (40 mins) +- [ ] Agent autonomously: + 1. Reads top 5 unread emails → generates summary + 2. Checks today's calendar → lists upcoming meetings + 3. Checks weather (optional — simple API call) + 4. Composes briefing message + 5. Sends to Telegram +- [ ] All read-only operations — no approval needed +- [ ] Runs through the same DLP filter — PII in email subjects gets redacted +- [ ] Test: Manually trigger endpoint → receive briefing on Telegram +- [ ] **Article callout:** This is OpenClaw's most loved feature. Ours does the same thing, but every piece of data flows through DLP and no credentials sit on disk. + +**Phase 5 Checkpoint:** You wake up to a Telegram briefing every morning. The agent proactively summarises your emails and calendar. All secured. + +--- + +## Phase 6: Cloud Run Deployment — Production (2 hours) + +### 6.1 — Containerisation (30 mins) +- [ ] Create `Dockerfile`: + ```dockerfile + FROM python:3.11-slim + WORKDIR /app + COPY requirements.txt . + RUN pip install --no-cache-dir -r requirements.txt + COPY agent/ ./agent/ + CMD ["uvicorn", "agent.main:app", "--host", "0.0.0.0", "--port", "8080"] + ``` +- [ ] Build and test locally: `docker build -t secure-agent . && docker run -p 8080:8080 secure-agent` +- [ ] Verify all endpoints work in container + +### 6.2 — Terraform Infrastructure (45 mins) +- [ ] Write Terraform for all resources: + - **`cloud_run.tf`**: Service with min 0 / max 1 instances (cost control), 512MB memory, 1 vCPU + - **`secrets.tf`**: All 3 secrets + IAM bindings for Cloud Run service account to access them + - **`iam.tf`**: Service account with least-privilege roles + IAM conditions + - **`firestore.tf`**: Database + indexes for conversations collection + - **`scheduler.tf`**: Morning briefing cron job targeting Cloud Run URL +- [ ] `terraform init && terraform plan` → review +- [ ] `terraform apply` → infrastructure created + +### 6.3 — Deploy and Wire Up (30 mins) +- [ ] Push container to Artifact Registry +- [ ] Deploy to Cloud Run via Terraform (or `gcloud run deploy`) +- [ ] Set Telegram webhook to Cloud Run URL: + ``` + https://api.telegram.org/bot{TOKEN}/setWebhook?url=https://{CLOUD_RUN_URL}/webhook/telegram + ``` +- [ ] Test end-to-end: Telegram message → Cloud Run → agent → tools → response +- [ ] Verify Cloud Scheduler triggers morning briefing + +### 6.4 — Monitoring and Logging (15 mins) +- [ ] Verify Cloud Audit Logs capture: + - Every Secret Manager access + - Every Cloud Run invocation + - Every DLP scan +- [ ] Set up basic alerting: + - Cloud Run error rate > 5% + - DLP findings (PII detected) → alert + - Unusual invocation patterns +- [ ] **Article callout:** OpenClaw has zero audit trail. Every action your agent takes is logged, traceable, and auditable. + +**Phase 6 Checkpoint:** Fully deployed on Cloud Run. Accessible from Telegram anywhere. Infrastructure is code (Terraform). All security layers active in production. + +--- + +## Phase 7: WIF Integration — The Enterprise Layer (1.5 hours) + +This phase demonstrates the pattern even if the demo only needs basic service accounts. It's the "here's how this scales to enterprise" section of your article. + +### 7.1 — WIF for Cross-Cloud Access (45 mins) +**Scenario:** Your agent needs to access an S3 bucket in AWS (simulating enterprise multi-cloud reality). + +- [ ] Create Workload Identity Pool: `agent-identity-pool` +- [ ] Create Workload Identity Provider: configured for AWS (or GitHub Actions for demo) +- [ ] Configure service account impersonation: + ``` + Agent (Cloud Run) + → WIF Pool (validates identity) + → Service Account (with specific GCP permissions) + → Access resources (no key file ever created) + ``` +- [ ] Terraform the entire WIF setup +- [ ] **Article callout:** OpenClaw requires downloading AWS credentials as a file, storing them on disk where any skill can read them. WIF means the credential never exists as a file — it's exchanged in-memory, scoped, and time-limited. + +### 7.2 — GitHub Actions CI/CD with WIF (30 mins) +- [ ] Set up WIF for GitHub Actions (no service account key in GitHub Secrets) +- [ ] Create `.github/workflows/deploy.yml`: + - On push to `main`: build container → push to Artifact Registry → deploy to Cloud Run + - Authenticate via WIF — zero stored credentials +- [ ] **Article callout:** Even your CI/CD pipeline is keyless. Show the GitHub Actions workflow using WIF vs the traditional service account JSON key approach. + +### 7.3 — Document the Security Comparison (15 mins) +Create a comparison table for the article: + +| Security Concern | OpenClaw | Your Agent | +|---|---|---| +| API keys | `.env` file on disk | Secret Manager (encrypted, rotated) | +| Cross-cloud auth | Downloaded credential files | WIF (keyless, time-limited) | +| PII in messages | No detection | Cloud DLP pre/post filter | +| Destructive actions | Auto-executed | Human-in-the-loop approval | +| Prompt injection | No protection | Input/output guard rails | +| Audit trail | None | Cloud Audit Logs (every action) | +| Runtime isolation | User's machine (full access) | Cloud Run (sandboxed container) | +| IAM | Whatever user has | Least privilege + conditions | + +**Phase 7 Checkpoint:** WIF demonstrated for both cross-cloud access and CI/CD. The enterprise security story is complete with concrete implementation. + +--- + +## Phase 8: Article-Ready Polish (1 hour) + +### 8.1 — GitHub Repository Cleanup +- [ ] Comprehensive `README.md`: + - Architecture diagram (export from your article) + - Quick start guide (< 15 minutes to deploy) + - Security features explained + - Cost breakdown + - Screenshots of Telegram interactions +- [ ] All code well-commented with security annotations +- [ ] `.env.example` showing required secrets (no real values) +- [ ] `terraform/` directory with complete IaC +- [ ] MIT license + +### 8.2 — Demo Screenshots and Recording +- [ ] Screenshot: Telegram conversation showing email summary +- [ ] Screenshot: Human-in-the-loop approval prompt +- [ ] Screenshot: DLP catching PII and warning user +- [ ] Screenshot: Morning briefing message +- [ ] Screenshot: Cloud Audit Logs showing traced actions +- [ ] Screenshot: Secret Manager vs `.env` file comparison +- [ ] Optional: 2-minute screen recording of full demo flow + +### 8.3 — Cost Verification +- [ ] After running for 1 week, screenshot actual GCP billing +- [ ] Document real costs per component +- [ ] Compare with OpenClaw's documented $10–$150/month API token costs +- [ ] **Article gold:** "I ran this for a week. Here's my actual bill: $0.43" + +--- + +## Build Verification Checklist + +### Core Functionality +- [ ] Send Telegram message → get intelligent response +- [ ] "Show me my emails" → formatted email list +- [ ] "What's on my calendar?" → upcoming events +- [ ] "Find my MLOps documents" → Drive file results +- [ ] "Search for OpenClaw security news" → web results summary +- [ ] Multi-turn conversation with context retention +- [ ] Morning briefing arrives at 8am + +### Security Layers +- [ ] Secret Manager: no credentials in code or on disk +- [ ] DLP: credit card number in message → warning + redaction +- [ ] Input guard: "Ignore previous instructions" → blocked +- [ ] Output guard: tool returns PII → redacted before user sees it +- [ ] Approval: "Create a meeting" → confirmation prompt before action +- [ ] IAM: service account has minimum required permissions +- [ ] Audit: all actions visible in Cloud Logging +- [ ] WIF: cross-cloud access without key files + +### Article Assets +- [ ] GitHub repo with complete, runnable code +- [ ] Terraform for one-command infrastructure deployment +- [ ] Screenshots of every security layer in action +- [ ] Cost breakdown with real billing data +- [ ] Architecture diagram +- [ ] Security comparison table (OpenClaw vs yours) + +--- + +## Suggested Article Outline (After Build) + +> **Title:** "I Built a Secure OpenClaw Alternative on Google Cloud for $0 — Here's Every Security Layer" +> +> 1. **The Problem** — OpenClaw is amazing but terrifying (Summer Yue story, Lethal Trifecta, Google VP quote) +> 2. **The Architecture** — What we're building and why (diagram) +> 3. **The Brain** — ADK + Gemini 2.0 Flash (free tier, open source) +> 4. **The Tools** — Gmail, Calendar, Drive, Web Search (reader builds along) +> 5. **The Interface** — Telegram bot (10-minute setup) +> 6. **Security Layer 1: Secrets** — Secret Manager vs .env files +> 7. **Security Layer 2: PII Protection** — Cloud DLP filter +> 8. **Security Layer 3: Guard Rails** — Input/output validation +> 9. **Security Layer 4: Human Approval** — The Summer Yue prevention layer +> 10. **Security Layer 5: Least Privilege** — IAM Conditions +> 11. **Security Layer 6: Keyless Auth** — WIF for cross-cloud +> 12. **The Heartbeat** — Proactive morning briefings +> 13. **The Memory** — Firestore persistent context +> 14. **The Bill** — Real cost breakdown ($0.43/week) +> 15. **What Enterprise Adds** — Where Vertex AI Guardrails and AlloyDB upgrade this +> 16. **Try It Yourself** — GitHub repo link, 15-minute quick start +> +> **Estimated reading time:** 15-20 minutes +> **GitHub companion:** Complete, deployable code + +--- + +## What This Builds Toward (GDE Portfolio) + +This single project generates: + +| Output | Detail | +|--------|--------| +| **Medium article** | The main 15-20 min technical deep-dive | +| **GitHub repo** | Deployable code with Terraform IaC | +| **Conference talk** | "I Built a Secure OpenClaw Alternative on GCP" (30 min talk) | +| **Lightning talk** | "6 Security Layers OpenClaw Doesn't Have" (10 min) | +| **LinkedIn post series** | One post per security layer (6 posts over 2 weeks) | +| **AI Guild session** | Internal walkthrough of the build | +| **WCC workshop** | Hands-on "Build Your Own AI Assistant" session | +| **Follow-up articles** | One per security layer as standalone deep-dives | + +--- + +*Build it. Screenshot everything. Write the article from real experience. That's GDE-level content.* diff --git a/terraform/environments/dev.tfvars b/terraform/environments/dev.tfvars new file mode 100644 index 0000000..7550b08 --- /dev/null +++ b/terraform/environments/dev.tfvars @@ -0,0 +1,4 @@ +project = "secure-agent-demo" +region = "us-central1" +environment = "dev" +# Pass secrets via env vars TF_VAR_telegram_bot_token and TF_VAR_gemini_api_key diff --git a/terraform/main.tf b/terraform/main.tf new file mode 100644 index 0000000..1b2d6a9 --- /dev/null +++ b/terraform/main.tf @@ -0,0 +1,41 @@ +terraform { + required_providers { + google = { + source = "hashicorp/google" + version = "~> 5.0" + } + } +} + +variable "project" {} +variable "region" {} +variable "environment" {} +variable "telegram_bot_token" { sensitive = true } +variable "gemini_api_key" { sensitive = true } + +provider "google" { + project = var.project + region = var.region +} + +module "secrets" { + source = "./modules/secrets" + project = var.project + secrets = { + "TELEGRAM_BOT_TOKEN" = var.telegram_bot_token + "GEMINI_API_KEY" = var.gemini_api_key + } +} + +module "cloud_run" { + source = "./modules/cloud_run" + project = var.project + region = var.region + environment = var.environment + service_account_email = module.iam.service_account_email +} + +module "iam" { + source = "./modules/iam" + project = var.project +} diff --git a/terraform/modules/cloud_run/main.tf b/terraform/modules/cloud_run/main.tf new file mode 100644 index 0000000..bfa823f --- /dev/null +++ b/terraform/modules/cloud_run/main.tf @@ -0,0 +1,52 @@ +variable "project" {} +variable "region" {} +variable "environment" {} +variable "service_account_email" {} + +resource "google_cloud_run_v2_service" "clawdbot" { + name = "clawdbot-${var.environment}" + location = var.region + project = var.project + ingress = "INGRESS_TRAFFIC_ALL" + + template { + service_account = var.service_account_email + + scaling { + max_instance_count = 1 + min_instance_count = 0 + } + + containers { + image = "us-docker.pkg.dev/cloudrun/container/hello" # Placeholder until CI pushes + + env { + name = "ENVIRONMENT" + value = var.environment + } + env { + name = "GCP_PROJECT_ID" + value = var.project + } + + resources { + limits = { + cpu = "1000m" + memory = "512Mi" + } + } + } + } +} + +resource "google_cloud_run_v2_service_iam_member" "public" { + project = var.project + location = var.region + name = google_cloud_run_v2_service.clawdbot.name + role = "roles/run.invoker" + member = "allUsers" +} + +output "service_url" { + value = google_cloud_run_v2_service.clawdbot.uri +} diff --git a/terraform/modules/iam/main.tf b/terraform/modules/iam/main.tf new file mode 100644 index 0000000..3976362 --- /dev/null +++ b/terraform/modules/iam/main.tf @@ -0,0 +1,30 @@ +variable "project" {} + +resource "google_service_account" "agent_sa" { + account_id = "clawdbot-runtime" + display_name = "ClawdBot Agent Runtime Service Account" + project = var.project +} + +# Grant basic required roles +resource "google_project_iam_member" "datastore" { + project = var.project + role = "roles/datastore.user" + member = "serviceAccount:${google_service_account.agent_sa.email}" +} + +resource "google_project_iam_member" "trace" { + project = var.project + role = "roles/cloudtrace.agent" + member = "serviceAccount:${google_service_account.agent_sa.email}" +} + +resource "google_project_iam_member" "dlp" { + project = var.project + role = "roles/dlp.user" + member = "serviceAccount:${google_service_account.agent_sa.email}" +} + +output "service_account_email" { + value = google_service_account.agent_sa.email +} diff --git a/terraform/modules/secrets/main.tf b/terraform/modules/secrets/main.tf new file mode 100644 index 0000000..990b813 --- /dev/null +++ b/terraform/modules/secrets/main.tf @@ -0,0 +1,24 @@ +variable "project" {} +variable "secrets" { + type = map(string) +} + +resource "google_secret_manager_secret" "agent_secrets" { + for_each = var.secrets + secret_id = each.key + project = var.project + + replication { + auto {} + } +} + +resource "google_secret_manager_secret_version" "agent_secret_versions" { + for_each = var.secrets + secret = google_secret_manager_secret.agent_secrets[each.key].id + secret_data = each.value +} + +output "secret_ids" { + value = [for s in google_secret_manager_secret.agent_secrets : s.id] +} diff --git a/terraform/modules/wif/main.tf b/terraform/modules/wif/main.tf new file mode 100644 index 0000000..0684559 --- /dev/null +++ b/terraform/modules/wif/main.tf @@ -0,0 +1,39 @@ +variable "project" {} +variable "github_repo" { + description = "The GitHub repository in the format owner/repo" + type = string +} +variable "service_account_email" {} + +resource "google_iam_workload_identity_pool" "github_pool" { + workload_identity_pool_id = "github-actions-pool" + project = var.project + display_name = "GitHub Actions Pool" +} + +resource "google_iam_workload_identity_pool_provider" "github_provider" { + workload_identity_pool_id = google_iam_workload_identity_pool.github_pool.workload_identity_pool_id + workload_identity_pool_provider_id = "github-actions-provider" + project = var.project + display_name = "GitHub Actions Provider" + + attribute_mapping = { + "google.subject" = "assertion.sub" + "attribute.actor" = "assertion.actor" + "attribute.repository" = "assertion.repository" + } + + oidc { + issuer_uri = "https://token.actions.githubusercontent.com" + } +} + +resource "google_service_account_iam_member" "wif_sa_impersonation" { + service_account_id = "projects/${var.project}/serviceAccounts/${var.service_account_email}" + role = "roles/iam.workloadIdentityUser" + member = "principalSet://iam.googleapis.com/${google_iam_workload_identity_pool.github_pool.name}/attribute.repository/${var.github_repo}" +} + +output "provider_name" { + value = google_iam_workload_identity_pool_provider.github_provider.name +} diff --git a/tests/eval/evalsets/README.md b/tests/eval/evalsets/README.md new file mode 100644 index 0000000..858289f --- /dev/null +++ b/tests/eval/evalsets/README.md @@ -0,0 +1,80 @@ +# Evaluation Sets + +This directory contains evaluation sets for testing agent behavior using `adk eval`. + +## Running Evaluations + +```bash +# Run default evalset +make eval + +# Run specific evalset +make eval EVALSET=tests/eval/evalsets/custom.evalset.json + +# Run all evalsets +make eval-all +``` + +## Evalset Format + +Each `.evalset.json` follows the ADK evaluation format: + +```json +{ + "eval_set_id": "unique_id", + "name": "Human-readable name", + "description": "What this evalset tests", + "eval_cases": [ + { + "eval_id": "case_id", + "conversation": [ + { + "user_content": { + "parts": [{"text": "User message"}] + }, + "intermediate_data": { + "tool_uses": [ + {"name": "tool_name", "args": {"param": "value"}} + ] + } + } + ], + "session_input": { + "app_name": "app_name", + "user_id": "test_user", + "state": {} + } + } + ] +} +``` + +## Key Fields + +- `eval_cases`: Array of test scenarios +- `conversation`: Sequence of user messages +- `intermediate_data.tool_uses`: Expected tool calls (for trajectory matching) +- `session_input`: Initial session state + +## Evaluation Metrics + +ADK eval measures: + +- **tool_trajectory_avg_score**: Are the correct tools called in the right order? +- **response_match_score**: How similar is the response to expected output? + +## Creating Custom Evalsets + +1. Copy `basic.evalset.json` as a template +2. Add cases based on your `DESIGN_SPEC.md` scenarios +3. Include expected tool calls for capability tests +4. Run `make eval EVALSET=your_evalset.json` + +## Tips + +- Start with 3-5 representative cases +- Include both happy path and edge cases +- Test each core capability from DESIGN_SPEC.md +- Add cases when you find bugs in production + +See [ADK documentation](https://google.github.io/adk-docs/) for advanced evaluation options. diff --git a/tests/integration/test_agent.py b/tests/integration/test_agent.py new file mode 100644 index 0000000..ab5f57a --- /dev/null +++ b/tests/integration/test_agent.py @@ -0,0 +1,57 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from google.adk.agents.run_config import RunConfig, StreamingMode +from google.adk.runners import Runner +from google.adk.sessions import InMemorySessionService +from google.genai import types + +from agent.agent import root_agent + + +def test_agent_stream() -> None: + """ + Integration test for the agent stream functionality. + Tests that the agent returns valid streaming responses. + """ + + session_service = InMemorySessionService() + + session = session_service.create_session_sync(user_id="test_user", app_name="test") + runner = Runner(agent=root_agent, session_service=session_service, app_name="test") + + message = types.Content( + role="user", parts=[types.Part.from_text(text="Why is the sky blue?")] + ) + + events = list( + runner.run( + new_message=message, + user_id="test_user", + session_id=session.id, + run_config=RunConfig(streaming_mode=StreamingMode.SSE), + ) + ) + assert len(events) > 0, "Expected at least one message" + + has_text_content = False + for event in events: + if ( + event.content + and event.content.parts + and any(part.text for part in event.content.parts) + ): + has_text_content = True + break + assert has_text_content, "Expected at least one message with text content" diff --git a/tests/integration/test_server_e2e.py b/tests/integration/test_server_e2e.py new file mode 100644 index 0000000..a948bf7 --- /dev/null +++ b/tests/integration/test_server_e2e.py @@ -0,0 +1,207 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import json +import logging +import os +import subprocess +import sys +import threading +import time +from collections.abc import Iterator +from typing import Any + +import pytest +import requests +from requests.exceptions import RequestException + +# Configure logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +BASE_URL = "http://127.0.0.1:8000/" +STREAM_URL = BASE_URL + "run_sse" +FEEDBACK_URL = BASE_URL + "feedback" + +HEADERS = {"Content-Type": "application/json"} + + +def log_output(pipe: Any, log_func: Any) -> None: + """Log the output from the given pipe.""" + for line in iter(pipe.readline, ""): + log_func(line.strip()) + + +def start_server() -> subprocess.Popen[str]: + """Start the FastAPI server using subprocess and log its output.""" + command = [ + sys.executable, + "-m", + "uvicorn", + "agent.fast_api_app:app", + "--host", + "0.0.0.0", + "--port", + "8000", + ] + env = os.environ.copy() + env["INTEGRATION_TEST"] = "TRUE" + process = subprocess.Popen( + command, + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + text=True, + bufsize=1, + env=env, + ) + + # Start threads to log stdout and stderr in real-time + threading.Thread( + target=log_output, args=(process.stdout, logger.info), daemon=True + ).start() + threading.Thread( + target=log_output, args=(process.stderr, logger.error), daemon=True + ).start() + + return process + + +def wait_for_server(timeout: int = 90, interval: int = 1) -> bool: + """Wait for the server to be ready.""" + start_time = time.time() + while time.time() - start_time < timeout: + try: + response = requests.get("http://127.0.0.1:8000/docs", timeout=10) + if response.status_code == 200: + logger.info("Server is ready") + return True + except RequestException: + pass + time.sleep(interval) + logger.error(f"Server did not become ready within {timeout} seconds") + return False + + +@pytest.fixture(scope="session") +def server_fixture(request: Any) -> Iterator[subprocess.Popen[str]]: + """Pytest fixture to start and stop the server for testing.""" + logger.info("Starting server process") + server_process = start_server() + if not wait_for_server(): + pytest.fail("Server failed to start") + logger.info("Server process started") + + def stop_server() -> None: + logger.info("Stopping server process") + server_process.terminate() + server_process.wait() + logger.info("Server process stopped") + + request.addfinalizer(stop_server) + yield server_process + + +def test_chat_stream(server_fixture: subprocess.Popen[str]) -> None: + """Test the chat stream functionality.""" + logger.info("Starting chat stream test") + + # Create session first + user_id = "test_user_123" + session_data = {"state": {"preferred_language": "English", "visit_count": 1}} + + session_url = f"{BASE_URL}/apps/agent/users/{user_id}/sessions" + session_response = requests.post( + session_url, + headers=HEADERS, + json=session_data, + timeout=60, + ) + assert session_response.status_code == 200 + logger.info(f"Session creation response: {session_response.json()}") + session_id = session_response.json()["id"] + + # Then send chat message + data = { + "app_name": "agent", + "user_id": user_id, + "session_id": session_id, + "new_message": { + "role": "user", + "parts": [{"text": "Hi!"}], + }, + "streaming": True, + } + + response = requests.post( + STREAM_URL, headers=HEADERS, json=data, stream=True, timeout=60 + ) + assert response.status_code == 200 + # Parse SSE events from response + events = [] + for line in response.iter_lines(): + if line: + # SSE format is "data: {json}" + line_str = line.decode("utf-8") + if line_str.startswith("data: "): + event_json = line_str[6:] # Remove "data: " prefix + event = json.loads(event_json) + events.append(event) + + assert events, "No events received from stream" + # Check for valid content in the response + has_text_content = False + for event in events: + content = event.get("content") + if ( + content is not None + and content.get("parts") + and any(part.get("text") for part in content["parts"]) + ): + has_text_content = True + break + + +def test_chat_stream_error_handling(server_fixture: subprocess.Popen[str]) -> None: + """Test the chat stream error handling.""" + logger.info("Starting chat stream error handling test") + data = { + "input": {"messages": [{"type": "invalid_type", "content": "Cause an error"}]} + } + response = requests.post( + STREAM_URL, headers=HEADERS, json=data, stream=True, timeout=10 + ) + + assert response.status_code == 422, ( + f"Expected status code 422, got {response.status_code}" + ) + logger.info("Error handling test completed successfully") + + +def test_collect_feedback(server_fixture: subprocess.Popen[str]) -> None: + """ + Test the feedback collection endpoint (/feedback) to ensure it properly + logs the received feedback. + """ + # Create sample feedback data + feedback_data = { + "score": 4, + "user_id": "test-user-456", + "session_id": "test-session-456", + "text": "Great response!", + } + + response = requests.post( + FEEDBACK_URL, json=feedback_data, headers=HEADERS, timeout=10 + ) + assert response.status_code == 200 diff --git a/tests/load_test/.results/.placeholder b/tests/load_test/.results/.placeholder new file mode 100644 index 0000000..e69de29 diff --git a/tests/load_test/README.md b/tests/load_test/README.md new file mode 100644 index 0000000..5953be7 --- /dev/null +++ b/tests/load_test/README.md @@ -0,0 +1,83 @@ +# Robust Load Testing for Generative AI Applications + +This directory provides a comprehensive load testing framework for your Generative AI application, leveraging the power of [Locust](http://locust.io), a leading open-source load testing tool. + +## Local Load Testing + +Follow these steps to execute load tests on your local machine: + +**1. Start the FastAPI Server:** + +Launch the FastAPI server in a separate terminal: + +```bash +uv run uvicorn agent.fast_api_app:app --host 0.0.0.0 --port 8000 --reload +``` + +**2. (In another tab) Create virtual environment with Locust** +Using another terminal tab, This is suggested to avoid conflicts with the existing application python environment. + +```bash +python3 -m venv .locust_env && source .locust_env/bin/activate && pip install locust==2.31.1 +``` + +**3. Execute the Load Test:** +Trigger the Locust load test with the following command: + +```bash +locust -f tests/load_test/load_test.py \ +-H http://127.0.0.1:8000 \ +--headless \ +-t 30s -u 10 -r 2 \ +--csv=tests/load_test/.results/results \ +--html=tests/load_test/.results/report.html +``` + +This command initiates a 30-second load test, simulating 2 users spawning per second, reaching a maximum of 60 concurrent users. + +**Results:** + +Comprehensive CSV and HTML reports detailing the load test performance will be generated and saved in the `tests/load_test/.results` directory. + +## Remote Load Testing (Targeting Cloud Run) + +This framework also supports load testing against remote targets, such as a staging Cloud Run instance. This process is seamlessly integrated into the Continuous Delivery (CD) pipeline. + +**Prerequisites:** + +- **Dependencies:** Ensure your environment has the same dependencies required for local testing. +- **Cloud Run Invoker Role:** You'll need the `roles/run.invoker` role to invoke the Cloud Run service. + +**Steps:** + +**1. Obtain Cloud Run Service URL:** + +Navigate to the Cloud Run console, select your service, and copy the URL displayed at the top. Set this URL as an environment variable: + +```bash +export RUN_SERVICE_URL=https://your-cloud-run-service-url.run.app +``` + +**2. Obtain ID Token:** + +Retrieve the ID token required for authentication: + +```bash +export _ID_TOKEN=$(gcloud auth print-identity-token -q) +``` + +**3. Execute the Load Test:** +Create virtual environment with Locust: +```bash +python3 -m venv .locust_env && source .locust_env/bin/activate && pip install locust==2.31.1 +``` + +Execute load tests. The following command executes the same load test parameters as the local test but targets your remote Cloud Run instance. +```bash +locust -f tests/load_test/load_test.py \ +-H $RUN_SERVICE_URL \ +--headless \ +-t 30s -u 60 -r 2 \ +--csv=tests/load_test/.results/results \ +--html=tests/load_test/.results/report.html +``` diff --git a/tests/load_test/load_test.py b/tests/load_test/load_test.py new file mode 100644 index 0000000..1a92860 --- /dev/null +++ b/tests/load_test/load_test.py @@ -0,0 +1,130 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import json +import logging +import os +import time +import uuid + +from locust import HttpUser, between, task + +ENDPOINT = "/run_sse" + +# Configure logging +logging.basicConfig( + level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" +) +logger = logging.getLogger(__name__) + + +class ChatStreamUser(HttpUser): + """Simulates a user interacting with the chat stream API.""" + + wait_time = between(1, 3) # Wait 1-3 seconds between tasks + + @task + def chat_stream(self) -> None: + """Simulates a chat stream interaction.""" + headers = {"Content-Type": "application/json"} + if os.environ.get("_ID_TOKEN"): + headers["Authorization"] = f"Bearer {os.environ['_ID_TOKEN']}" + # Create session first + user_id = f"user_{uuid.uuid4()}" + session_data = {"state": {"preferred_language": "English", "visit_count": 1}} + + session_response = self.client.post( + f"/apps/agent/users/{user_id}/sessions", + headers=headers, + json=session_data, + ) + + # Get session_id from response + session_id = session_response.json()["id"] + + # Send chat message + data = { + "app_name": "agent", + "user_id": user_id, + "session_id": session_id, + "new_message": { + "role": "user", + "parts": [{"text": "Hello! Weather in New york?"}], + }, + "streaming": True, + } + start_time = time.time() + + with self.client.post( + ENDPOINT, + name=f"{ENDPOINT} message", + headers=headers, + json=data, + catch_response=True, + stream=True, + params={"alt": "sse"}, + ) as response: + if response.status_code == 200: + events = [] + has_error = False + for line in response.iter_lines(): + if line: + line_str = line.decode("utf-8") + events.append(line_str) + + if "429 Too Many Requests" in line_str: + self.environment.events.request.fire( + request_type="POST", + name=f"{ENDPOINT} rate_limited 429s", + response_time=0, + response_length=len(line), + response=response, + context={}, + ) + + # Check for error responses in the JSON payload + try: + event_data = json.loads(line_str) + if isinstance(event_data, dict) and "code" in event_data: + # Flag any non-2xx codes as errors + if event_data["code"] >= 400: + has_error = True + error_msg = event_data.get( + "message", "Unknown error" + ) + response.failure(f"Error in response: {error_msg}") + logger.error( + "Received error response: code=%s, message=%s", + event_data["code"], + error_msg, + ) + except json.JSONDecodeError: + # If it's not valid JSON, continue processing + pass + + end_time = time.time() + total_time = end_time - start_time + + # Only fire success event if no errors were found + if not has_error: + self.environment.events.request.fire( + request_type="POST", + name=f"{ENDPOINT} end", + response_time=total_time * 1000, # Convert to milliseconds + response_length=len(events), + response=response, + context={}, + ) + else: + response.failure(f"Unexpected status code: {response.status_code}") diff --git a/tests/test_main.py b/tests/test_main.py new file mode 100644 index 0000000..e9b2823 --- /dev/null +++ b/tests/test_main.py @@ -0,0 +1,14 @@ +import pytest +from httpx import ASGITransport, AsyncClient + +from agent.main import app + + +@pytest.mark.asyncio +async def test_health_check() -> None: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as ac: + response = await ac.get("/health") + assert response.status_code == 200 + assert response.json() == {"status": "ok", "version": "1.0.0"} diff --git a/tests/unit/test_dummy.py b/tests/unit/test_dummy.py new file mode 100644 index 0000000..ea53997 --- /dev/null +++ b/tests/unit/test_dummy.py @@ -0,0 +1,23 @@ +# Copyright 2026 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" +You can add your unit tests here. +This is where you test your business logic, including agent functionality, +data processing, and other core components of your application. +""" + + +def test_dummy() -> None: + """Placeholder - replace with real tests.""" + assert 1 == 1 From 96822d59bc3f02e0d3fbb5548b12ff455f82ac18 Mon Sep 17 00:00:00 2001 From: Sonika Janagill Date: Mon, 16 Mar 2026 17:49:39 +0000 Subject: [PATCH 2/2] Rename ClawdBot to AdkBot and integrate ADK Memory Bank with Vertex AI Rebrand from ClawdBot to AdkBot across all files. Integrate ADK Runner with VertexAiMemoryBankService for persistent memory across conversations, replacing Firestore-based memory manager. Add memory injection callbacks (before/after agent) to load relevant context and save sessions. Update configuration to include agent_engine_id and gcp_location. Enhance Telegram webhook to use ADK runner with auto session creation. Add local --- .github/workflows/deploy.yml | 2 +- .gitignore | 5 + README.md | 4 +- agent/agent.py | 71 +- agent/config.py | 8 +- agent/errors.py | 2 +- agent/main.py | 145 +- agent/root_agent.py | 55 +- agent/subagents/calendar_agent.py | 12 +- agent/subagents/drive_agent.py | 11 +- agent/subagents/gmail_agent.py | 11 +- agent/subagents/search_agent.py | 27 +- architecture.mermaid | 78 + deployment/terraform/dev/.terraform.lock.hcl | 80 + deployment/terraform/dev/service.tf | 8 +- deployment/terraform/dev/terraform.tfstate | 1250 ++++++ .../terraform/dev/terraform.tfstate.backup | 1037 +++++ pyproject.toml | 41 + terraform/modules/cloud_run/main.tf | 8 +- terraform/modules/iam/main.tf | 4 +- uv.lock | 3819 +++++++++++++++++ 21 files changed, 6503 insertions(+), 175 deletions(-) create mode 100644 architecture.mermaid create mode 100644 deployment/terraform/dev/.terraform.lock.hcl create mode 100644 deployment/terraform/dev/terraform.tfstate create mode 100644 deployment/terraform/dev/terraform.tfstate.backup create mode 100644 uv.lock diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml index 5f50426..a637187 100644 --- a/.github/workflows/deploy.yml +++ b/.github/workflows/deploy.yml @@ -7,7 +7,7 @@ on: env: PROJECT_ID: secure-agent-demo - SERVICE_NAME: clawdbot + SERVICE_NAME: adkbot REGION: us-central1 # These will be set up in Phase 6/7 # WIF_PROVIDER: projects/123/locations/global/workloadIdentityPools/github/providers/my-repo diff --git a/.gitignore b/.gitignore index b4d93bd..87c0352 100644 --- a/.gitignore +++ b/.gitignore @@ -65,3 +65,8 @@ cover/ *.json credentials.json token.json + +# Local development +.adk +session.db +.terraform diff --git a/README.md b/README.md index d8db675..3f89937 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ -# ClawdBot: The Secure Google ADK Assistant +# AdkBot: The Secure Google ADK Assistant **"From Zero to Secure AI Assistant in a Weekend"** -ClawdBot is a high-security, open-source alternative to typical AI agents, built entirely on **Google Agent Development Kit (ADK) 1.0** and Google Cloud side infrastructure. +AdkBot is a high-security, open-source alternative to typical AI agents, built entirely on **Google Agent Development Kit (ADK) 1.0** and Google Cloud side infrastructure. This repository demonstrates how to build an agent that is not just powerful, but secure by default with **6 layers of native security.** diff --git a/agent/agent.py b/agent/agent.py index 9fd5303..33dea33 100644 --- a/agent/agent.py +++ b/agent/agent.py @@ -1,78 +1,15 @@ -# ruff: noqa -# Copyright 2026 Google LLC -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import datetime -from zoneinfo import ZoneInfo +import os -from google.adk.agents import Agent +import google.auth from google.adk.apps import App -from google.adk.models import Gemini -from google.genai import types -import os -import google.auth +from agent.root_agent import root_agent _, project_id = google.auth.default() os.environ["GOOGLE_CLOUD_PROJECT"] = project_id -os.environ["GOOGLE_CLOUD_LOCATION"] = "global" +os.environ["GOOGLE_CLOUD_LOCATION"] = "us-central1" os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "True" - -def get_weather(query: str) -> str: - """Simulates a web search. Use it get information on weather. - - Args: - query: A string containing the location to get weather information for. - - Returns: - A string with the simulated weather information for the queried location. - """ - if "sf" in query.lower() or "san francisco" in query.lower(): - return "It's 60 degrees and foggy." - return "It's 90 degrees and sunny." - - -def get_current_time(query: str) -> str: - """Simulates getting the current time for a city. - - Args: - city: The name of the city to get the current time for. - - Returns: - A string with the current time information. - """ - if "sf" in query.lower() or "san francisco" in query.lower(): - tz_identifier = "America/Los_Angeles" - else: - return f"Sorry, I don't have timezone information for query: {query}." - - tz = ZoneInfo(tz_identifier) - now = datetime.datetime.now(tz) - return f"The current time for query {query} is {now.strftime('%Y-%m-%d %H:%M:%S %Z%z')}" - - -root_agent = Agent( - name="root_agent", - model=Gemini( - model="gemini-3-flash-preview", - retry_options=types.HttpRetryOptions(attempts=3), - ), - instruction="You are a helpful AI assistant designed to provide accurate and useful information.", - tools=[get_weather, get_current_time], -) - app = App( root_agent=root_agent, name="agent", diff --git a/agent/config.py b/agent/config.py index 301aa31..2774812 100644 --- a/agent/config.py +++ b/agent/config.py @@ -4,9 +4,11 @@ class Settings(BaseSettings): - telegram_token: str = "" + telegram_bot_token: str = "" gemini_api_key: str = "" - gcp_project_id: str = "secure-agent-demo" + gcp_project_id: str = "adk-bot-sj-2026" + gcp_location: str = "us-central1" + agent_engine_id: str = "1051835704084004864" environment: Literal["dev", "prod"] = "dev" model_config = SettingsConfigDict( @@ -30,7 +32,7 @@ def get_secret(secret_id: str) -> str: return response.payload.data.decode("UTF-8") try: - settings.telegram_token = get_secret("TELEGRAM_BOT_TOKEN") + settings.telegram_bot_token = get_secret("TELEGRAM_BOT_TOKEN") settings.gemini_api_key = get_secret("GEMINI_API_KEY") except Exception as e: import logging diff --git a/agent/errors.py b/agent/errors.py index d06a6e0..399e218 100644 --- a/agent/errors.py +++ b/agent/errors.py @@ -1,5 +1,5 @@ class AgentError(Exception): - """Base class for all ClawdBot exceptions.""" + """Base class for all AdkBot exceptions.""" pass class ToolError(AgentError): diff --git a/agent/main.py b/agent/main.py index be8ec24..df65d82 100644 --- a/agent/main.py +++ b/agent/main.py @@ -1,28 +1,91 @@ import logging +import os +import google.auth import httpx from fastapi import BackgroundTasks, FastAPI, Request from fastapi.responses import HTMLResponse +from google.adk.runners import Runner +from google.adk.sessions import InMemorySessionService +from google.adk.memory import VertexAiMemoryBankService +from google.genai import types from agent.config import settings from agent.errors import AgentError -from agent.memory import memory_manager from agent.root_agent import root_agent +# Set up Vertex AI environment +_, project_id = google.auth.default() +os.environ.setdefault("GOOGLE_CLOUD_PROJECT", project_id or settings.gcp_project_id) +os.environ.setdefault("GOOGLE_CLOUD_LOCATION", settings.gcp_location) +os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "True") + logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) -app = FastAPI(title="ClawdBot Gateway", version="1.0.0") +app = FastAPI(title="AdkBot Gateway", version="1.0.0") + +# Create the ADK runner with Memory Bank and auto session creation +APP_NAME = "adkbot" +session_service = InMemorySessionService() +memory_service = VertexAiMemoryBankService( + project=settings.gcp_project_id, + location=settings.gcp_location, + agent_engine_id=settings.agent_engine_id, +) +logger.info(f"Memory Bank initialized with engine ID: {settings.agent_engine_id}") + +runner = Runner( + agent=root_agent, + app_name=APP_NAME, + session_service=session_service, + memory_service=memory_service, + auto_create_session=True, +) + + +def run_agent(user_id: str, session_id: str, message_text: str) -> str: + """Run the ADK agent and collect the final response text.""" + content = types.Content( + role="user", + parts=[types.Part.from_text(text=message_text)], + ) + all_text_parts = [] + for event in runner.run( + user_id=user_id, session_id=session_id, new_message=content + ): + logger.info(f"Event from agent={event.author}, final={event.is_final_response()}, " + f"has_content={bool(event.content)}") + if event.content and event.content.parts: + for part in event.content.parts: + if part.text: + logger.info(f" text part ({len(part.text)} chars): {part.text[:100]}...") + all_text_parts.append(part.text) + elif part.function_call: + logger.info(f" function_call: {part.function_call.name}") + elif part.function_response: + logger.info(f" function_response: {part.function_response.name}") + + # Return the last non-empty text part (the final agent response) + final_text = "" + for text in reversed(all_text_parts): + if text.strip(): + final_text = text + break + + logger.info(f"Final response ({len(final_text)} chars): {final_text[:200]}") + return final_text or "I processed your request but have no response to show." -async def send_telegram_message(chat_id: int, text: str): + +async def send_telegram_message(chat_id: int, text: str) -> None: """Sends a message back to the user via Telegram Bot API.""" - if not settings.telegram_token: + if not settings.telegram_bot_token: logger.warning("No Telegram token configured. Skipping message send.") return - url = f"https://api.telegram.org/bot{settings.telegram_token}/sendMessage" + url = f"https://api.telegram.org/bot{settings.telegram_bot_token}/sendMessage" payload = {"chat_id": chat_id, "text": text, "parse_mode": "Markdown"} - + async with httpx.AsyncClient() as client: try: response = await client.post(url, json=payload) @@ -30,45 +93,40 @@ async def send_telegram_message(chat_id: int, text: str): except Exception as e: logger.error(f"Failed to send Telegram message: {e}") -async def process_telegram_update(update: dict): + +async def process_telegram_update(update: dict) -> None: """Background task to process the update and run the ADK agent.""" try: if "message" not in update or "text" not in update["message"]: return - + message = update["message"] chat_id = message["chat"]["id"] text = message["text"] - + logger.info(f"Processing message from {chat_id}: {text}") - + # Send typing indicator - url = f"https://api.telegram.org/bot{settings.telegram_token}/sendChatAction" - async with httpx.AsyncClient() as client: - await client.post(url, json={"chat_id": chat_id, "action": "typing"}) - + if settings.telegram_bot_token: + url = f"https://api.telegram.org/bot{settings.telegram_bot_token}/sendChatAction" + async with httpx.AsyncClient() as client: + await client.post(url, json={"chat_id": chat_id, "action": "typing"}) + # Run ADK agent try: - # Memory injection (Phase 4) - _ = memory_manager.get_recent_context(chat_id) - - # The agent.run will consume the latest text - response = root_agent.run(text) - reply_text = response.text - - # Save context to Firestore - memory_manager.save_message(chat_id, "user", text) - memory_manager.save_message(chat_id, "assistant", reply_text) - + user_id = str(chat_id) + session_id = f"telegram-{chat_id}" + reply_text = run_agent(user_id, session_id, text) + except AgentError as e: logger.error(f"Agent error: {e}") - reply_text = f"⚙️ I ran into an issue: {str(e)}" + reply_text = f"I ran into an issue: {str(e)}" except Exception as e: logger.error(f"Unexpected error running agent: {e}", exc_info=True) - reply_text = "❌ Sorry, I encountered an unexpected error while processing your request." - + reply_text = "Sorry, I encountered an unexpected error while processing your request." + await send_telegram_message(chat_id, reply_text) - + except Exception as e: logger.error(f"Error in process_telegram_update background task: {e}", exc_info=True) @@ -77,20 +135,22 @@ async def process_telegram_update(update: dict): async def health_check(): return {"status": "ok", "version": "1.0.0"} + @app.get("/ready") async def readiness_check(): return {"status": "ready"} + @app.get("/", response_class=HTMLResponse) async def root(): return """ - ClawdBot Gateway + AdkBot Gateway -

ClawdBot API is running

+

AdkBot API is running

To interact via browser UI during local dev, use the ADK CLI:

adk web

For production, configure the Telegram Webhook to point to /webhook/telegram

@@ -98,12 +158,9 @@ async def root(): """ + @app.post("/webhook/telegram") async def telegram_webhook(request: Request, background_tasks: BackgroundTasks): - """ - Handle incoming Telegram updates. Fast response to Telegram is required, - so we process the agent interaction in the background. - """ try: update = await request.json() background_tasks.add_task(process_telegram_update, update) @@ -112,32 +169,30 @@ async def telegram_webhook(request: Request, background_tasks: BackgroundTasks): logger.error(f"Error parsing webhook request: {e}") return {"ok": False} + @app.post("/scheduled/briefing") async def morning_briefing(request: Request, background_tasks: BackgroundTasks): - """ - Triggered by Cloud Scheduler daily. - Will dispatch the briefing flow for configured users. - """ try: payload = await request.json() chat_id = payload.get("chat_id") if not chat_id: return {"error": "Missing chat_id"} - + logger.info(f"Starting scheduled briefing for {chat_id}") - + async def run_briefing(): try: - # Instruct the agent to generate a morning briefing autonomously prompt = ( "Please read my latest emails and check my calendar for today, " "then provide a concise morning briefing." ) - response = root_agent.run(prompt) - await send_telegram_message(chat_id, f"🌅 **Morning Briefing**\n\n{response.text}") + user_id = str(chat_id) + session_id = f"briefing-{chat_id}" + reply = run_agent(user_id, session_id, prompt) + await send_telegram_message(chat_id, f"**Morning Briefing**\n\n{reply}") except Exception as e: logger.error(f"Failed to run briefing for {chat_id}: {e}") - + background_tasks.add_task(run_briefing) return {"status": "briefing started"} except Exception as e: diff --git a/agent/root_agent.py b/agent/root_agent.py index ca75678..f7e89b6 100644 --- a/agent/root_agent.py +++ b/agent/root_agent.py @@ -10,16 +10,63 @@ logger = logging.getLogger(__name__) SYSTEM_PROMPT = """ -You are ClawdBot, a highly capable and secure personal assistant. +You are AdkBot, a highly capable and secure personal assistant. Your goal is to help the user by reading their emails, managing calendars, organizing files, and searching the web. Always explain what you're about to do before doing it. For any destructive action (delete, send, modify), ask for explicit confirmation first. + +You have persistent memory across conversations. Use it to remember user preferences, +past interactions, and context to provide a more personalized experience. + +{memory} """ + +async def load_memory_on_start(callback_context): + """Before agent runs, retrieve relevant memories and inject into state.""" + try: + memory_service = callback_context._invocation_context.memory_service + session = callback_context._invocation_context.session + if memory_service and session: + memories = await memory_service.search_memory( + app_name=callback_context._invocation_context.app_name, + user_id=session.user_id, + query=session.events[-1].content.parts[0].text if session.events else "", + ) + if memories: + memory_text = "\n".join( + [f"- {m.fact}" for m in memories if hasattr(m, "fact")] + ) + if memory_text: + callback_context.state["memory"] = ( + f"\nRelevant memories from past conversations:\n{memory_text}" + ) + logger.info(f"Loaded {len(memories)} memories for user {session.user_id}") + return + callback_context.state["memory"] = "" + except Exception as e: + logger.warning(f"Failed to load memory: {e}") + callback_context.state["memory"] = "" + + +async def save_session_to_memory(callback_context): + """After each agent turn, save the session to Memory Bank for long-term recall.""" + try: + memory_service = callback_context._invocation_context.memory_service + if memory_service: + await memory_service.add_session_to_memory( + callback_context._invocation_context.session + ) + except Exception as e: + logger.warning(f"Failed to save session to memory: {e}") + + root_agent = Agent( - name="clawdbot", - model="gemini-2.0-flash", + name="adkbot", + model="gemini-2.5-flash", description="Secure personal assistant capable of orchestrating specialized tasks.", instruction=SYSTEM_PROMPT, - sub_agents=[search_agent, gmail_agent, calendar_agent, drive_agent] + sub_agents=[search_agent, gmail_agent, calendar_agent, drive_agent], + before_agent_callback=load_memory_on_start, + after_agent_callback=save_session_to_memory, ) diff --git a/agent/subagents/calendar_agent.py b/agent/subagents/calendar_agent.py index 92396d9..907bf37 100644 --- a/agent/subagents/calendar_agent.py +++ b/agent/subagents/calendar_agent.py @@ -1,34 +1,32 @@ import logging from google.adk.agents import Agent -from google.adk.tools import Tool logger = logging.getLogger(__name__) + def list_events(days_ahead: int = 7) -> str: """List upcoming calendar events.""" logger.info(f"Listing events for {days_ahead} days ahead.") return "Mock Calendar: Meeting at 3pm tomorrow." + def check_availability(date: str) -> str: """Check if the user is free on a specific date and time.""" logger.info(f"Checking availability for: {date}") return f"Mock Availability for {date}: Free after 2pm." + def create_event(title: str, start: str, end: str, description: str) -> str: """Create a new calendar event. Will require approval.""" logger.info(f"Creating event: {title} from {start} to {end}") - # Later this will hit the Approval engine before execution return f"Mock Event Created: {title}" -list_events_tool = Tool.from_function(list_events) -check_availability_tool = Tool.from_function(check_availability) -create_event_tool = Tool.from_function(create_event) calendar_agent = Agent( name="CalendarAgent", - model="gemini-2.0-flash", + model="gemini-2.5-flash", description="Manages the user's agenda, availability, and scheduling.", instruction="You help the user manage their time. Check their calendar and schedule events if asked.", - tools=[list_events_tool, check_availability_tool, create_event_tool] + tools=[list_events, check_availability, create_event], ) diff --git a/agent/subagents/drive_agent.py b/agent/subagents/drive_agent.py index 19bbd9e..054b919 100644 --- a/agent/subagents/drive_agent.py +++ b/agent/subagents/drive_agent.py @@ -1,33 +1,32 @@ import logging from google.adk.agents import Agent -from google.adk.tools import Tool logger = logging.getLogger(__name__) + def list_recent_files(max_results: int = 10) -> str: """Lists the user's most recently accessed files in Google Drive.""" logger.info(f"Listing {max_results} recent files.") return "Mock Drive: 1. Q3 Report.pdf, 2. Design Specs.docx" + def search_files(query: str) -> str: """Searches Google Drive for files matching the query.""" logger.info(f"Searching drive for: {query}") return f"Mock Search Results: Found 2 files for '{query}'" + def summarise_document(file_id: str) -> str: """Reads a file from Google Drive and provides a summary.""" logger.info(f"Summarising document ID: {file_id}") return f"Mock summary of document {file_id}: This is a high level overview of Q3." -list_recent_tools = Tool.from_function(list_recent_files) -search_files_tool = Tool.from_function(search_files) -summarise_document_tool = Tool.from_function(summarise_document) drive_agent = Agent( name="DriveAgent", - model="gemini-2.0-flash", + model="gemini-2.5-flash", description="Searches Google Drive and summarizes documents.", instruction="You are a file and document management assistant. Locate files and summarize them when asked.", - tools=[list_recent_tools, search_files_tool, summarise_document_tool] + tools=[list_recent_files, search_files, summarise_document], ) diff --git a/agent/subagents/gmail_agent.py b/agent/subagents/gmail_agent.py index 0f93f12..e419029 100644 --- a/agent/subagents/gmail_agent.py +++ b/agent/subagents/gmail_agent.py @@ -1,33 +1,32 @@ import logging from google.adk.agents import Agent -from google.adk.tools import Tool logger = logging.getLogger(__name__) + def read_inbox(max_results: int = 5) -> str: """Reads the user's latest emails from the inbox.""" logger.info(f"Reading {max_results} emails from inbox.") return "Mock Inbox: 1. Project Update, 2. Lunch Plans" + def search_emails(query: str) -> str: """Searches the user's emails using Gmail query syntax.""" logger.info(f"Searching emails for: {query}") return f"Mock search results for '{query}': No recent matches." + def read_email(message_id: str) -> str: """Reads the full body of a specific email.""" logger.info(f"Reading full email ID: {message_id}") return f"Mock Email content for message {message_id}: Hello this is a test." -read_inbox_tool = Tool.from_function(read_inbox) -search_emails_tool = Tool.from_function(search_emails) -read_email_tool = Tool.from_function(read_email) gmail_agent = Agent( name="GmailAgent", - model="gemini-2.0-flash", + model="gemini-2.5-flash", description="Manages the user's Gmail inbox. Can search and read emails.", instruction="You are a personal assistant handling email. Answer questions about the inbox. Only read emails.", - tools=[read_inbox_tool, search_emails_tool, read_email_tool] + tools=[read_inbox, search_emails, read_email], ) diff --git a/agent/subagents/search_agent.py b/agent/subagents/search_agent.py index 7c63400..45a3a77 100644 --- a/agent/subagents/search_agent.py +++ b/agent/subagents/search_agent.py @@ -1,29 +1,10 @@ -import logging - from google.adk.agents import Agent -from google.adk.tools import Tool - -logger = logging.getLogger(__name__) - -def web_search_tool(query: str) -> str: - """ - Search the web for current information, news, or facts. - - Args: - query: The search terms to look up. - Returns: - Summary of search results. - """ - logger.info(f"Mock web search for: {query}") - # Mock implementation for now - return f"Search results for '{query}': Example finding (mock)" - -search_tool = Tool.from_function(web_search_tool) +from google.adk.tools import google_search search_agent = Agent( name="SearchAgent", - model="gemini-2.0-flash", # Note: ADK model binding needs valid key + model="gemini-2.5-flash", description="Finds recent information and facts on the internet.", - instruction="You are a research assistant. Use the web search tool to find answers to the user's questions.", - tools=[search_tool] + instruction="You are a research assistant. Use Google Search to find answers to the user's questions. Provide clear, concise summaries of what you find.", + tools=[google_search], ) diff --git a/architecture.mermaid b/architecture.mermaid new file mode 100644 index 0000000..def6d15 --- /dev/null +++ b/architecture.mermaid @@ -0,0 +1,78 @@ +%%{init: { + 'theme': 'base', + 'themeVariables': { + 'background': '#f0f0f0', + 'primaryColor': '#d4e8f5', + 'primaryTextColor': '#2c3e50', + 'primaryBorderColor': '#a8c8e8', + 'secondaryColor': '#fde8d4', + 'tertiaryColor': '#d4f5e4', + 'lineColor': '#7a9eb5', + 'fontSize': '14px', + 'edgeLabelBackground': '#f0f0f0', + 'clusterBkg': '#e8e8e8', + 'clusterBorder': '#bbb' + } +}}%% + +flowchart TD + User(["👤 User\n(Telegram)"]) + + subgraph Gateway["FastAPI Gateway — Cloud Run"] + GW["📨 FastAPI\nEndpoint"] + DLP["🔍 Cloud DLP\nPII Redaction"] + end + + subgraph Orchestrator["ADK Root Orchestrator — Gemini 2.0 Flash"] + ROOT["🤖 Root Agent\n(Router)"] + HITL["✋ Human-in-the-Loop\nApproval Callback"] + end + + subgraph Subagents["Specialised Subagents — Gemini 2.0 Flash"] + direction LR + GA["📧 Gmail\nAgent"] + CA["📅 Calendar\nAgent"] + DA["📁 Drive\nAgent"] + SA["🔎 Search\nAgent"] + end + + subgraph Infra["GCP Infrastructure"] + direction LR + SM["🔐 Secret\nManager"] + VAI["🧠 Vertex AI\nMemory Bank"] + CT["📊 Cloud\nTrace"] + WIF["🔑 Workload Identity\nFederation"] + end + + CICD["⚙️ GitHub Actions\n(CI/CD)"] + + User -->|"Message"| GW + GW --> DLP + DLP -->|"Sanitised input"| ROOT + ROOT --> HITL + ROOT --> GA + ROOT --> CA + ROOT --> DA + ROOT --> SA + ROOT -->|"Response"| User + + GW -.->|"Reads secrets"| SM + ROOT -.->|"Save / load memory"| VAI + GW -.->|"Trace spans"| CT + CA -.->|"Awaits approval"| HITL + WIF -.->|"Keyless deploy"| CICD + CICD -.->|"Deploy image"| Gateway + + classDef gateway fill:#d4e8f5,stroke:#a8c8e8,color:#2c3e50 + classDef orch fill:#fde8d4,stroke:#f0b98a,color:#2c3e50 + classDef agent fill:#d4f5e4,stroke:#8ad4a8,color:#2c3e50 + classDef infra fill:#f0e8f5,stroke:#c8a8e8,color:#2c3e50 + classDef user fill:#fff8d4,stroke:#e8d88a,color:#2c3e50 + classDef cicd fill:#f5e8d4,stroke:#e8c88a,color:#2c3e50 + + class GW,DLP gateway + class ROOT,HITL orch + class GA,CA,DA,SA agent + class SM,VAI,CT,WIF infra + class User user + class CICD cicd diff --git a/deployment/terraform/dev/.terraform.lock.hcl b/deployment/terraform/dev/.terraform.lock.hcl new file mode 100644 index 0000000..bc26951 --- /dev/null +++ b/deployment/terraform/dev/.terraform.lock.hcl @@ -0,0 +1,80 @@ +# This file is maintained automatically by "terraform init". +# Manual edits may be lost in future updates. + +provider "registry.terraform.io/hashicorp/google" { + version = "7.13.0" + constraints = "~> 7.13.0" + hashes = [ + "h1:66xli1/pwUeGalo6ZvXqFfTta8KKK8ee4Ku7Cmrs8HI=", + "zh:01d22b268d44f885add27ba87b3c0a1e3c9efa35131831ce4275b2a1bfd7e0df", + "zh:104efd3d66a818d9311c7ebd5d1886a7e17ef79562869aa39df9a5b57ec6c630", + "zh:116f0a1cf4db399c4ac2173f0b1fa9f08518bd20cade8d4370a0c5e1b99177be", + "zh:4384e66934dd866ae76dd6f73711b4d9eab8442754a969bb5b1ad6b20429665c", + "zh:595ef531359dcd95ebc52e10e4b94f5676039f336ede9caef95e7b46cd4b635b", + "zh:b0fa219a3339a28c8f450b55d272eeb44b86118b65989ac1f09d174d1fab9069", + "zh:d0119fb709d5e9d52220a545157a5310f31027999c411ec602b51c301aa2db6c", + "zh:d29b3104c9497c32f2479a88fcc741360eb3e3be3279f84086d9fdd3dca56777", + "zh:d5a4cee375237ca451f209b849b4993b288fc027ce2c1a3f4912b03f0f24537e", + "zh:f569b65999264a9416862bca5cd2a6177d94ccb0424f3a4ef424428912b9cb3c", + "zh:fa02aaf1210b55618a1fa909b8a722e79786ef315b889c35377a7ade9a0f7dbb", + "zh:ff339e275183e3b9bc2449102277b5abb63e2877f819e319ac6f0d8e06a5e7d3", + ] +} + +provider "registry.terraform.io/hashicorp/google-beta" { + version = "7.23.0" + hashes = [ + "h1:E55pdzgTpyvHPTXU3EeA+txAl6xWBlwde8aXyow3Tyc=", + "zh:0b8f7316d1efa3fc05c9d11eeb561f9e69a9b5a1b4bcdf33dedd9190cc09425b", + "zh:12b6aeee8378694d0e57963e5f5fc18dd38b6c18c82bcab4a45ea8f0bb13a589", + "zh:18cadd0e0afb627cebbfa1bd2be5a6d1160a97428fc2162b98720c9ebfbbe5c6", + "zh:31673cb143f30492b78edcaf304f45586a48439aca494727fee327d5b83b8eb3", + "zh:48bebde0ed81a4c248300d9faaddfeda92a2c4016aa9c1616a1f018bf6bf759d", + "zh:696801735b1172de1b7e907f8e0ff44d1222944a71fbbea7b7032d9f16d85503", + "zh:729b0992f9dddaa658a72e33370e60d1baba2942697fef7cfd8418a3c26482f0", + "zh:94465802e5ac7965df11b986ded4b49767e428b1be9660be1f25f543c4a45e7f", + "zh:9f239733a85af7df3438adeda3fb3121e2049d8bd150b5fb9a480abffd8c8caa", + "zh:b099fab6e49d01e7bcece71ec2b8cf83744256c6cad2bb69a155e19f3486e1e5", + "zh:dab69c7cbbcb25428dbcebd7dd57c315ca4084e9d3caeabc40ed4e853d5deb10", + "zh:f569b65999264a9416862bca5cd2a6177d94ccb0424f3a4ef424428912b9cb3c", + ] +} + +provider "registry.terraform.io/hashicorp/random" { + version = "3.7.2" + constraints = "~> 3.7.0" + hashes = [ + "h1:KG4NuIBl1mRWU0KD/BGfCi1YN/j3F7H4YgeeM7iSdNs=", + "zh:14829603a32e4bc4d05062f059e545a91e27ff033756b48afbae6b3c835f508f", + "zh:1527fb07d9fea400d70e9e6eb4a2b918d5060d604749b6f1c361518e7da546dc", + "zh:1e86bcd7ebec85ba336b423ba1db046aeaa3c0e5f921039b3f1a6fc2f978feab", + "zh:24536dec8bde66753f4b4030b8f3ef43c196d69cccbea1c382d01b222478c7a3", + "zh:29f1786486759fad9b0ce4fdfbbfece9343ad47cd50119045075e05afe49d212", + "zh:4d701e978c2dd8604ba1ce962b047607701e65c078cb22e97171513e9e57491f", + "zh:78d5eefdd9e494defcb3c68d282b8f96630502cac21d1ea161f53cfe9bb483b3", + "zh:7b8434212eef0f8c83f5a90c6d76feaf850f6502b61b53c329e85b3b281cba34", + "zh:ac8a23c212258b7976e1621275e3af7099e7e4a3d4478cf8d5d2a27f3bc3e967", + "zh:b516ca74431f3df4c6cf90ddcdb4042c626e026317a33c53f0b445a3d93b720d", + "zh:dc76e4326aec2490c1600d6871a95e78f9050f9ce427c71707ea412a2f2f1a62", + "zh:eac7b63e86c749c7d48f527671c7aee5b4e26c10be6ad7232d6860167f99dbb0", + ] +} + +provider "registry.terraform.io/hashicorp/time" { + version = "0.13.1" + hashes = [ + "h1:ZT5ppCNIModqk3iOkVt5my8b8yBHmDpl663JtXAIRqM=", + "zh:02cb9aab1002f0f2a94a4f85acec8893297dc75915f7404c165983f720a54b74", + "zh:04429b2b31a492d19e5ecf999b116d396dac0b24bba0d0fb19ecaefe193fdb8f", + "zh:26f8e51bb7c275c404ba6028c1b530312066009194db721a8427a7bc5cdbc83a", + "zh:772ff8dbdbef968651ab3ae76d04afd355c32f8a868d03244db3f8496e462690", + "zh:78d5eefdd9e494defcb3c68d282b8f96630502cac21d1ea161f53cfe9bb483b3", + "zh:898db5d2b6bd6ca5457dccb52eedbc7c5b1a71e4a4658381bcbb38cedbbda328", + "zh:8de913bf09a3fa7bedc29fec18c47c571d0c7a3d0644322c46f3aa648cf30cd8", + "zh:9402102c86a87bdfe7e501ffbb9c685c32bbcefcfcf897fd7d53df414c36877b", + "zh:b18b9bb1726bb8cfbefc0a29cf3657c82578001f514bcf4c079839b6776c47f0", + "zh:b9d31fdc4faecb909d7c5ce41d2479dd0536862a963df434be4b16e8e4edc94d", + "zh:c951e9f39cca3446c060bd63933ebb89cedde9523904813973fbc3d11863ba75", + "zh:e5b773c0d07e962291be0e9b413c7a22c044b8c7b58c76e8aa91d1659990dfb5", + ] +} diff --git a/deployment/terraform/dev/service.tf b/deployment/terraform/dev/service.tf index 61c838f..a0862fb 100644 --- a/deployment/terraform/dev/service.tf +++ b/deployment/terraform/dev/service.tf @@ -33,8 +33,8 @@ resource "google_cloud_run_v2_service" "app" { image = "us-docker.pkg.dev/cloudrun/container/hello" resources { limits = { - cpu = "4" - memory = "8Gi" + cpu = "1" + memory = "512Mi" } } @@ -53,8 +53,8 @@ resource "google_cloud_run_v2_service" "app" { max_instance_request_concurrency = 40 scaling { - min_instance_count = 1 - max_instance_count = 10 + min_instance_count = 0 + max_instance_count = 2 } session_affinity = true diff --git a/deployment/terraform/dev/terraform.tfstate b/deployment/terraform/dev/terraform.tfstate new file mode 100644 index 0000000..fa2bb7d --- /dev/null +++ b/deployment/terraform/dev/terraform.tfstate @@ -0,0 +1,1250 @@ +{ + "version": 4, + "terraform_version": "1.14.5", + "serial": 37, + "lineage": "1f15773e-ba20-5625-dceb-95430333bcfa", + "outputs": { + "app_service_account_email": { + "value": "adkbot-app@adk-bot-sj-2026.iam.gserviceaccount.com", + "type": "string" + }, + "cloud_run_service_name": { + "value": "adkbot", + "type": "string" + }, + "cloud_run_service_url": { + "value": "https://adkbot-ac3ppcbudq-uc.a.run.app", + "type": "string" + }, + "logs_bucket_name": { + "value": "adk-bot-sj-2026-adkbot-logs", + "type": "string" + }, + "telemetry_bigquery_connection_id": { + "value": "adkbot-genai-telemetry", + "type": "string" + }, + "telemetry_dataset_id": { + "value": "adkbot_telemetry", + "type": "string" + } + }, + "resources": [ + { + "mode": "data", + "type": "google_project", + "name": "dev_project", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "auto_create_network": null, + "billing_account": "012FE9-037975-4459CF", + "deletion_policy": "PREVENT", + "effective_labels": {}, + "folder_id": null, + "id": "projects/adk-bot-sj-2026", + "labels": {}, + "name": "ADK Bot", + "number": "565365774332", + "org_id": null, + "project_id": "adk-bot-sj-2026", + "tags": null, + "terraform_labels": {} + }, + "sensitive_attributes": [], + "identity_schema_version": 0 + } + ] + }, + { + "mode": "data", + "type": "google_project", + "name": "project", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "auto_create_network": null, + "billing_account": "012FE9-037975-4459CF", + "deletion_policy": "PREVENT", + "effective_labels": {}, + "folder_id": null, + "id": "projects/adk-bot-sj-2026", + "labels": {}, + "name": "ADK Bot", + "number": "565365774332", + "org_id": null, + "project_id": "adk-bot-sj-2026", + "tags": null, + "terraform_labels": {} + }, + "sensitive_attributes": [], + "identity_schema_version": 0 + } + ] + }, + { + "mode": "managed", + "type": "google_bigquery_connection", + "name": "genai_telemetry_connection", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "aws": [], + "azure": [], + "cloud_resource": [ + { + "service_account_id": "bqcx-565365774332-i1yw@gcp-sa-bigquery-condel.iam.gserviceaccount.com" + } + ], + "cloud_spanner": [], + "cloud_sql": [], + "connection_id": "adkbot-genai-telemetry", + "description": "", + "friendly_name": "adkbot GenAI Telemetry Connection", + "has_credential": false, + "id": "projects/adk-bot-sj-2026/locations/us-central1/connections/adkbot-genai-telemetry", + "kms_key_name": "", + "location": "us-central1", + "name": "projects/565365774332/locations/us-central1/connections/adkbot-genai-telemetry", + "project": "adk-bot-sj-2026", + "spark": [], + "timeouts": null + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "eyJlMmJmYjczMC1lY2FhLTExZTYtOGY4OC0zNDM2M2JjN2M0YzAiOnsiY3JlYXRlIjoxMjAwMDAwMDAwMDAwLCJkZWxldGUiOjEyMDAwMDAwMDAwMDAsInVwZGF0ZSI6MTIwMDAwMDAwMDAwMH19", + "dependencies": [ + "google_project_service.services" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_bigquery_dataset", + "name": "telemetry_dataset", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "access": [ + { + "condition": [], + "dataset": [], + "domain": "", + "group_by_email": "", + "iam_member": "", + "role": "OWNER", + "routine": [], + "special_group": "", + "user_by_email": "sonika.janagill@gmail.com", + "view": [] + }, + { + "condition": [], + "dataset": [], + "domain": "", + "group_by_email": "", + "iam_member": "", + "role": "OWNER", + "routine": [], + "special_group": "projectOwners", + "user_by_email": "", + "view": [] + }, + { + "condition": [], + "dataset": [], + "domain": "", + "group_by_email": "", + "iam_member": "", + "role": "READER", + "routine": [], + "special_group": "projectReaders", + "user_by_email": "", + "view": [] + }, + { + "condition": [], + "dataset": [], + "domain": "", + "group_by_email": "", + "iam_member": "", + "role": "WRITER", + "routine": [], + "special_group": "projectWriters", + "user_by_email": "", + "view": [] + } + ], + "creation_time": 1773590383623, + "dataset_id": "adkbot_telemetry", + "default_collation": "", + "default_encryption_configuration": [], + "default_partition_expiration_ms": 0, + "default_table_expiration_ms": 0, + "delete_contents_on_destroy": false, + "description": "Dataset for GenAI telemetry data stored in GCS", + "effective_labels": { + "goog-terraform-provisioned": "true" + }, + "etag": "KMdpaenvpR3IsGmo82Wxbg==", + "external_catalog_dataset_options": [], + "external_dataset_reference": [], + "friendly_name": "adkbot Telemetry", + "id": "projects/adk-bot-sj-2026/datasets/adkbot_telemetry", + "is_case_insensitive": false, + "labels": {}, + "last_modified_time": 1773590383623, + "location": "us-central1", + "max_time_travel_hours": "168", + "project": "adk-bot-sj-2026", + "resource_tags": {}, + "self_link": 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"ignore_auto_generated_schema": false, + "ignore_schema_changes": null, + "labels": {}, + "last_modified_time": 1773590398929, + "location": "us-central1", + "materialized_view": [], + "max_staleness": "", + "num_bytes": 0, + "num_long_term_bytes": 0, + "num_rows": 0, + "project": "adk-bot-sj-2026", + "range_partitioning": [], + "require_partition_filter": false, + "resource_tags": {}, + "schema": 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"table_metadata_view": null, + "table_replication_info": [], + "terraform_labels": { + "goog-terraform-provisioned": "true" + }, + "time_partitioning": [], + "type": "EXTERNAL", + "view": [] + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_bigquery_connection.genai_telemetry_connection", + "google_bigquery_dataset.telemetry_dataset", + "google_project_service.services", + "google_storage_bucket.logs_data_bucket", + "google_storage_bucket_iam_member.telemetry_connection_access", + "time_sleep.wait_for_bq_connection_sa" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_bigquery_table", + "name": "completions_view", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "biglake_configuration": [], + "clustering": null, + "creation_time": 1773590627130, + "dataset_id": "adkbot_telemetry", + "deletion_protection": false, + "description": "View of GenAI completion logs joined with the GCS prompt/response external table", + "effective_labels": { + "goog-terraform-provisioned": "true" + }, + "encryption_configuration": [], + "etag": "B7b8HZR/xAvPKzmqkJek/g==", + "expiration_time": 0, + "external_catalog_table_options": [], + "external_data_configuration": [], + "friendly_name": "", + "generated_schema_columns": "", + "id": "projects/adk-bot-sj-2026/datasets/adkbot_telemetry/tables/completions_view", + "ignore_auto_generated_schema": false, + "ignore_schema_changes": null, + "labels": {}, + "last_modified_time": 1773590627997, + "location": "us-central1", + "materialized_view": [], + "max_staleness": "", + "num_bytes": 0, + "num_long_term_bytes": 0, + "num_rows": 0, + "project": "adk-bot-sj-2026", + "range_partitioning": [], + "require_partition_filter": false, + "resource_tags": {}, + "schema": 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output_ref\n FROM `adk-bot-sj-2026.adkbot_genai_telemetry_logs._AllLogs`\n WHERE JSON_VALUE(labels, '$.\\\"gen_ai.input.messages_ref\\\"') IS NOT NULL\n OR JSON_VALUE(labels, '$.\\\"gen_ai.output.messages_ref\\\"') IS NOT NULL\n),\n\n-- Unpivot to get one row per message reference\nunpivoted_refs AS (\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n input_ref AS messages_ref_uri,\n 'input' AS message_type\n FROM log_refs\n WHERE input_ref IS NOT NULL\n\n UNION ALL\n\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n output_ref AS messages_ref_uri,\n 'output' AS message_type\n FROM log_refs\n WHERE output_ref IS NOT NULL\n),\n\n-- Join with completions external table and extract api_call_id once\njoined_data AS (\n SELECT\n lr.insert_id,\n lr.timestamp,\n lr.labels,\n lr.trace,\n lr.span_id,\n lr.messages_ref_uri,\n lr.message_type,\n SPLIT(REGEXP_EXTRACT(lr.messages_ref_uri, r'/([^/]+)\\.jsonl'), '_')[OFFSET(0)] AS api_call_id,\n c.role,\n c.parts,\n c.index AS message_idx\n FROM unpivoted_refs lr\n JOIN `adk-bot-sj-2026.adkbot_telemetry.completions` c\n ON lr.messages_ref_uri = c._FILE_NAME\n),\n\n-- Flatten the parts array\nflattened AS (\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n messages_ref_uri,\n message_type,\n api_call_id,\n role,\n message_idx,\n part_idx,\n part.type AS part_type,\n part.content,\n part.uri,\n part.mime_type,\n TO_HEX(MD5(part.data)) AS data_md5_hex,\n part.id AS tool_id,\n part.name AS tool_name,\n part.arguments AS tool_args,\n part.response AS tool_response\n FROM joined_data\n CROSS JOIN UNNEST(parts) AS part WITH OFFSET AS part_idx\n),\n\n-- Deduplicate by trace: keep only the latest log entry per trace\n-- (Tool calls create multiple log entries with same trace but different timestamps)\ndeduplicated AS (\n SELECT\n *,\n ROW_NUMBER() OVER (\n PARTITION BY trace, message_type, role, message_idx, part_idx\n ORDER BY timestamp DESC\n ) AS row_num\n FROM flattened\n)\n\nSELECT\n -- Core identifiers and timestamps\n timestamp,\n insert_id,\n trace,\n span_id,\n api_call_id,\n\n -- Message metadata\n message_type,\n role,\n message_idx,\n part_idx,\n\n -- Message content\n content,\n\n -- Tool/function calling\n part_type,\n tool_name,\n tool_args,\n tool_response,\n\n -- Additional metadata\n uri,\n mime_type,\n data_md5_hex,\n\n -- Raw fields\n labels,\n messages_ref_uri\nFROM deduplicated\nWHERE row_num = 1 -- Keep only the latest entry per trace/message/part\nORDER BY trace ASC, message_type ASC, message_idx ASC, part_idx ASC\n", + "use_legacy_sql": false + } + ] + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_bigquery_connection.genai_telemetry_connection", + "google_bigquery_dataset.telemetry_dataset", + "google_bigquery_table.completions_external_table", + "google_logging_linked_dataset.genai_logs_linked_dataset", + "google_logging_project_bucket_config.genai_telemetry_bucket", + 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"table_metadata_view": null, + "table_replication_info": [], + "terraform_labels": { + "goog-terraform-provisioned": "true" + }, + "time_partitioning": [], + "type": "EXTERNAL", + "view": [] + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_bigquery_connection.genai_telemetry_connection", + "google_bigquery_dataset.telemetry_dataset", + "google_project_service.services", + "google_storage_bucket.logs_data_bucket", + "google_storage_bucket_iam_member.telemetry_connection_access", + "time_sleep.wait_for_bq_connection_sa" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_bigquery_table", + "name": "completions_view", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "biglake_configuration": [], + "clustering": null, + "creation_time": 1773590627130, + "dataset_id": "adkbot_telemetry", + "deletion_protection": false, + "description": "View of GenAI completion logs joined with the GCS prompt/response external table", + "effective_labels": { + "goog-terraform-provisioned": "true" + }, + "encryption_configuration": [], + "etag": "B7b8HZR/xAvPKzmqkJek/g==", + "expiration_time": 0, + "external_catalog_table_options": [], + "external_data_configuration": [], + "friendly_name": "", + "generated_schema_columns": "", + "id": "projects/adk-bot-sj-2026/datasets/adkbot_telemetry/tables/completions_view", + "ignore_auto_generated_schema": false, + "ignore_schema_changes": null, + "labels": {}, + "last_modified_time": 1773590627997, + "location": "us-central1", + "materialized_view": [], + "max_staleness": "", + "num_bytes": 0, + "num_long_term_bytes": 0, + "num_rows": 0, + "project": "adk-bot-sj-2026", + "range_partitioning": [], + "require_partition_filter": false, + "resource_tags": {}, + "schema": "[{\"mode\":\"NULLABLE\",\"name\":\"timestamp\",\"type\":\"TIMESTAMP\"},{\"mode\":\"NULLABLE\",\"name\":\"insert_id\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"trace\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"span_id\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"api_call_id\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"message_type\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"role\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"message_idx\",\"type\":\"INTEGER\"},{\"mode\":\"NULLABLE\",\"name\":\"part_idx\",\"type\":\"INTEGER\"},{\"mode\":\"NULLABLE\",\"name\":\"content\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"part_type\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"tool_name\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"tool_args\",\"type\":\"JSON\"},{\"mode\":\"NULLABLE\",\"name\":\"tool_response\",\"type\":\"JSON\"},{\"mode\":\"NULLABLE\",\"name\":\"uri\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"mime_type\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"data_md5_hex\",\"type\":\"STRING\"},{\"mode\":\"NULLABLE\",\"name\":\"labels\",\"type\":\"JSON\"},{\"mode\":\"NULLABLE\",\"name\":\"messages_ref_uri\",\"type\":\"STRING\"}]", + "schema_foreign_type_info": [], + "self_link": "https://bigquery.googleapis.com/bigquery/v2/projects/adk-bot-sj-2026/datasets/adkbot_telemetry/tables/completions_view", + "table_constraints": [], + "table_id": "completions_view", + "table_metadata_view": null, + "table_replication_info": [], + "terraform_labels": { + "goog-terraform-provisioned": "true" + }, + "time_partitioning": [], + "type": "VIEW", + "view": [ + { + "query": "-- Optimized join of Cloud Logging data with GCS-stored prompt/response data.\n-- This query extracts both input and output messages referenced in logs.\n-- Note: Input files contain full conversation history, so messages may appear multiple times.\n\n-- Extract message references from Cloud Logging (scan once, extract both input/output)\nWITH log_refs AS (\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n JSON_VALUE(labels, '$.\\\"gen_ai.input.messages_ref\\\"') AS input_ref,\n JSON_VALUE(labels, '$.\\\"gen_ai.output.messages_ref\\\"') AS output_ref\n FROM `adk-bot-sj-2026.adkbot_genai_telemetry_logs._AllLogs`\n WHERE JSON_VALUE(labels, '$.\\\"gen_ai.input.messages_ref\\\"') IS NOT NULL\n OR JSON_VALUE(labels, '$.\\\"gen_ai.output.messages_ref\\\"') IS NOT NULL\n),\n\n-- Unpivot to get one row per message reference\nunpivoted_refs AS (\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n input_ref AS messages_ref_uri,\n 'input' AS message_type\n FROM log_refs\n WHERE input_ref IS NOT NULL\n\n UNION ALL\n\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n output_ref AS messages_ref_uri,\n 'output' AS message_type\n FROM log_refs\n WHERE output_ref IS NOT NULL\n),\n\n-- Join with completions external table and extract api_call_id once\njoined_data AS (\n SELECT\n lr.insert_id,\n lr.timestamp,\n lr.labels,\n lr.trace,\n lr.span_id,\n lr.messages_ref_uri,\n lr.message_type,\n SPLIT(REGEXP_EXTRACT(lr.messages_ref_uri, r'/([^/]+)\\.jsonl'), '_')[OFFSET(0)] AS api_call_id,\n c.role,\n c.parts,\n c.index AS message_idx\n FROM unpivoted_refs lr\n JOIN `adk-bot-sj-2026.adkbot_telemetry.completions` c\n ON lr.messages_ref_uri = c._FILE_NAME\n),\n\n-- Flatten the parts array\nflattened AS (\n SELECT\n insert_id,\n timestamp,\n labels,\n trace,\n span_id,\n messages_ref_uri,\n message_type,\n api_call_id,\n role,\n message_idx,\n part_idx,\n part.type AS part_type,\n part.content,\n part.uri,\n part.mime_type,\n TO_HEX(MD5(part.data)) AS data_md5_hex,\n part.id AS tool_id,\n part.name AS tool_name,\n part.arguments AS tool_args,\n part.response AS tool_response\n FROM joined_data\n CROSS JOIN UNNEST(parts) AS part WITH OFFSET AS part_idx\n),\n\n-- Deduplicate by trace: keep only the latest log entry per trace\n-- (Tool calls create multiple log entries with same trace but different timestamps)\ndeduplicated AS (\n SELECT\n *,\n ROW_NUMBER() OVER (\n PARTITION BY trace, message_type, role, message_idx, part_idx\n ORDER BY timestamp DESC\n ) AS row_num\n FROM flattened\n)\n\nSELECT\n -- Core identifiers and timestamps\n timestamp,\n insert_id,\n trace,\n span_id,\n api_call_id,\n\n -- Message metadata\n message_type,\n role,\n message_idx,\n part_idx,\n\n -- Message content\n content,\n\n -- Tool/function calling\n part_type,\n tool_name,\n tool_args,\n tool_response,\n\n -- Additional metadata\n uri,\n mime_type,\n data_md5_hex,\n\n -- Raw fields\n labels,\n messages_ref_uri\nFROM deduplicated\nWHERE row_num = 1 -- Keep only the latest entry per trace/message/part\nORDER BY trace ASC, message_type ASC, message_idx ASC, part_idx ASC\n", + "use_legacy_sql": false + } + ] + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_bigquery_connection.genai_telemetry_connection", + "google_bigquery_dataset.telemetry_dataset", + "google_bigquery_table.completions_external_table", + "google_logging_linked_dataset.genai_logs_linked_dataset", + "google_logging_project_bucket_config.genai_telemetry_bucket", + "google_logging_project_sink.genai_logs_to_bucket", + "google_project_service.services", + "google_storage_bucket.logs_data_bucket", + "google_storage_bucket_iam_member.telemetry_connection_access", + "time_sleep.wait_for_bq_connection_sa", + "time_sleep.wait_for_linked_dataset", + "time_sleep.wait_for_logging_api" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_logging_linked_dataset", + "name": "genai_logs_linked_dataset", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "bigquery_dataset": [ + { + "dataset_id": "bigquery.googleapis.com/projects/adk-bot-sj-2026/datasets/adkbot_genai_telemetry_logs" + } + ], + "bucket": "adkbot-genai-telemetry", + "create_time": "2026-03-15T16:02:08.846832517Z", + "description": "Linked dataset for adkbot GenAI telemetry Cloud Logging bucket", + "id": "projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry/links/adkbot_genai_telemetry_logs", + "lifecycle_state": "ACTIVE", + "link_id": "adkbot_genai_telemetry_logs", + "location": "us-central1", + "name": "projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry/links/adkbot_genai_telemetry_logs", + "parent": "projects/adk-bot-sj-2026", + "timeouts": null + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "eyJlMmJmYjczMC1lY2FhLTExZTYtOGY4OC0zNDM2M2JjN2M0YzAiOnsiY3JlYXRlIjoxMjAwMDAwMDAwMDAwLCJkZWxldGUiOjEyMDAwMDAwMDAwMDB9fQ==", + "dependencies": [ + "google_logging_project_bucket_config.genai_telemetry_bucket", + "google_logging_project_sink.genai_logs_to_bucket", + "google_project_service.services", + "time_sleep.wait_for_logging_api" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_logging_project_bucket_config", + "name": "genai_telemetry_bucket", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "bucket_id": "adkbot-genai-telemetry", + "cmek_settings": [], + "description": "Dedicated Cloud Logging bucket for adkbot GenAI telemetry with 10 year retention", + "enable_analytics": true, + "id": "projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry", + "index_configs": [], + "lifecycle_state": "ACTIVE", + "location": "us-central1", + "locked": false, + "name": "projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry", + "project": "adk-bot-sj-2026", + "retention_days": 3650 + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_project_service.services", + "time_sleep.wait_for_logging_api" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_logging_project_sink", + "name": "feedback_logs_to_bucket", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "bigquery_options": [], + "custom_writer_identity": null, + "description": "", + "destination": "logging.googleapis.com/projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry", + "disabled": false, + "exclusions": [], + "filter": "jsonPayload.log_type=\"feedback\" jsonPayload.service_name=\"adkbot\"", + "id": "projects/adk-bot-sj-2026/sinks/adkbot-feedback", + "name": "adkbot-feedback", + "project": "adk-bot-sj-2026", + "unique_writer_identity": true, + "writer_identity": "" + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_logging_project_bucket_config.genai_telemetry_bucket", + "google_project_service.services", + "time_sleep.wait_for_logging_api" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_logging_project_sink", + "name": "genai_logs_to_bucket", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "schema_version": 0, + "attributes": { + "bigquery_options": [], + "custom_writer_identity": null, + "description": "", + "destination": "logging.googleapis.com/projects/adk-bot-sj-2026/locations/us-central1/buckets/adkbot-genai-telemetry", + "disabled": false, + "exclusions": [], + "filter": "log_name=\"projects/adk-bot-sj-2026/logs/gen_ai.client.inference.operation.details\" AND (labels.\"gen_ai.input.messages_ref\" =~ \".*adkbot.*\" OR labels.\"gen_ai.output.messages_ref\" =~ \".*adkbot.*\")", + "id": "projects/adk-bot-sj-2026/sinks/adkbot-genai-logs", + "name": "adkbot-genai-logs", + "project": "adk-bot-sj-2026", + "unique_writer_identity": true, + "writer_identity": "" + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_logging_project_bucket_config.genai_telemetry_bucket", + "google_project_service.services", + "time_sleep.wait_for_logging_api" + ] + } + ] + }, + { + "mode": "managed", + "type": "google_project_iam_member", + "name": "app_sa_roles", + "provider": "provider[\"registry.terraform.io/hashicorp/google\"]", + "instances": [ + { + "index_key": "dev,roles/aiplatform.user", + "schema_version": 0, + "attributes": { + "condition": [], + "etag": "BwZNEjnIxmM=", + "id": "adk-bot-sj-2026/roles/aiplatform.user/serviceAccount:adkbot-app@adk-bot-sj-2026.iam.gserviceaccount.com", + "member": "serviceAccount:adkbot-app@adk-bot-sj-2026.iam.gserviceaccount.com", + "project": "adk-bot-sj-2026", + "role": "roles/aiplatform.user" + }, + "sensitive_attributes": [], + "identity_schema_version": 0, + "private": "bnVsbA==", + "dependencies": [ + "google_project_service.services", + "google_service_account.app_sa" + ] + }, + { + "index_key": "dev,roles/cloudtrace.agent", + "schema_version": 0, + "attributes": { + "condition": [], + "etag": "BwZNEjnIxmM=", + "id": 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"google-auth>=2.0.0", + "opentelemetry-sdk>=1.0.0", + "opentelemetry-exporter-gcp-trace>=1.0.0", + "opentelemetry-exporter-gcp-monitoring>=1.0.0a0", + "opentelemetry-exporter-gcp-logging>=1.0.0a0", + "opentelemetry-resourcedetector-gcp>=1.0.0a0", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.1.1", + "pytest-cov>=5.0.0", + "pytest-mock>=3.14.0", + "httpx>=0.27.0", +] +lint = [ + "ruff>=0.3.0", + "mypy>=1.9.0", + "codespell>=2.0.0", +] +eval = [ + "google-adk[eval]>=1.0", +] + [tool.ruff] line-length = 120 target-version = "py312" diff --git a/terraform/modules/cloud_run/main.tf b/terraform/modules/cloud_run/main.tf index bfa823f..d611959 100644 --- a/terraform/modules/cloud_run/main.tf +++ b/terraform/modules/cloud_run/main.tf @@ -3,8 +3,8 @@ variable "region" {} variable "environment" {} variable "service_account_email" {} -resource "google_cloud_run_v2_service" "clawdbot" { - name = "clawdbot-${var.environment}" +resource "google_cloud_run_v2_service" "adkbot" { + name = "adkbot-${var.environment}" location = var.region project = var.project ingress = "INGRESS_TRAFFIC_ALL" @@ -42,11 +42,11 @@ resource "google_cloud_run_v2_service" "clawdbot" { resource "google_cloud_run_v2_service_iam_member" "public" { project = var.project location = var.region - name = google_cloud_run_v2_service.clawdbot.name + name = google_cloud_run_v2_service.adkbot.name role = "roles/run.invoker" member = "allUsers" } output "service_url" { - value = google_cloud_run_v2_service.clawdbot.uri + value = google_cloud_run_v2_service.adkbot.uri } diff --git a/terraform/modules/iam/main.tf b/terraform/modules/iam/main.tf index 3976362..02364e9 100644 --- a/terraform/modules/iam/main.tf +++ b/terraform/modules/iam/main.tf @@ -1,8 +1,8 @@ variable "project" {} resource "google_service_account" "agent_sa" { - account_id = "clawdbot-runtime" - display_name = "ClawdBot Agent Runtime Service Account" + account_id = "adkbot-runtime" + display_name = "AdkBot Agent Runtime Service Account" 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