A2A Client

[tbrandenburg]

@task With looking into https://github.com/tbrandenburg/pydanticai-a2a/blob/main/fasta2a_client.py - Develop a simple uv-based telegram python bot which forwards user messages to the a2a agent/network und responds to the user with their message. The bot should be configured by the TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID it should be allowed to respond to.

[github-actions]

🌿 Branch created: task-machine-34

[github-actions]

Context

The team must deliver a uv-based Telegram bot that relays authorized chat messages to the external A2A agent/network (per the upstream fasta2a_client.py) and returns the responses back to the permitted chat. Work must capture business-level needs, translate them into a resilient architecture, implement the Python bot plus integration glue, and prove the solution through automated tests and deployment readiness assets.

Role Descriptions

• business-analyst — Agent Path: .github/agents/08-business-product/business-analyst.md
• api-designer — Agent Path: .github/agents/01-core-development/api-designer.md
• backend-developer — Agent Path: .github/agents/01-core-development/backend-developer.md
• devops-engineer — Agent Path: .github/agents/03-infrastructure/devops-engineer.md
• test-automator — Agent Path: .github/agents/04-quality-security/test-automator.md

Chronologic Task List

• [business-analyst] Gather Telegram routing requirements — Review output/34/issue_conversation.md, document allowed user personas, expected conversation flows, security limits (TELEGRAM_BOT_TOKEN, TELEGRAM_CHAT_ID), and success metrics in output/34/feature1_requirements.md.
  • Summary: Captured personas, flows, security constraints, and success metrics in output/34/feature1_requirements.md.
• [api-designer] Define Telegram routing architecture — Read output/34/feature1_requirements.md, outline the uv event loop structure, webhook vs polling choice, and message validation pipeline, saving diagrams/specs to output/34/feature1_architecture.md.
  • Summary: Captured uv task topology, justified long-polling, and defined validation pipeline plus sequence diagram in output/34/feature1_architecture.md.
• [backend-developer] Produce Telegram routing design — Consume output/34/feature1_requirements.md and output/34/feature1_architecture.md, describe module boundaries, dependency injection points, and error handling states in docs/telegram_routing_design.md.
  • Summary: Documented module boundaries, DI map, and error states for the Telegram router in docs/telegram_routing_design.md.
• [backend-developer] Implement Telegram routing code — Follow docs/telegram_routing_design.md to build the uv-based bot entrypoint in bots/telegram_router.py, wire TELEGRAM_BOT_TOKEN + TELEGRAM_CHAT_ID validation, add README usage snippet in docs/telegram_usage.md, and ensure structured logging is present.
  • Summary: Added a uvloop-ready router with env validation, HTTP polling/dispatch pipeline, mockable A2A bridge, structured JSON logging, and documented usage workflow in docs/telegram_usage.md.
• [test-automator] Verify Telegram routing — Inspect docs/telegram_routing_design.md and code in bots/telegram_router.py, add async unit tests with mocked Telegram APIs inside tests/test_telegram_routing.py, run pytest tests/test_telegram_routing.py, and summarize pass/fail results plus log excerpts in output/34/feature1_test_report.md.
  • Summary: Added async transport/dispatcher/router tests with Telegram API stubs, executed python -m pytest tests/test_telegram_routing.py (3/3 pass), and logged results inside output/34/feature1_test_report.md.
• [business-analyst] Capture A2A integration requirements — Document how the bot must call the upstream fasta2a_client.py, required prompt metadata, retry policies, and confidentiality constraints in output/34/feature2_requirements.md using insights from the upstream repo and stakeholder notes.
  • Summary: Authored output/34/feature2_requirements.md detailing the fasta2a_client.py invocation flow, metadata envelope, retry/backoff rules, configuration inputs, and confidentiality obligations grounded in Feature 1 assets plus the upstream reference client.
• [business-analyst] Resolve open A2A requirement questions — Confirm upstream authentication model, canonical persona tag list, and artifact media expectations with A2A owners and update output/34/feature2_requirements.md as needed.
  • Summary: Documented unauthenticated base URL behavior, locked persona tags to Operator/OnCall/AutomationAuditor, and clarified text-only artifact handling inside output/34/feature2_requirements.md.
• [api-designer] Specify A2A integration architecture — Derive service boundaries from output/34/feature2_requirements.md, model request/response schemas, timeout handling, and error propagation into output/34/feature2_architecture.md with sequence flows.
  • Summary: Authored output/34/feature2_architecture.md detailing the integration boundaries, schemas, timeout/retry matrix, error propagation table, and Mermaid sequence.
• [backend-developer] Draft A2A integration design — Read output/34/feature2_requirements.md and output/34/feature2_architecture.md, produce docs/a2a_integration_design.md covering client abstraction, telemetry hooks, and configuration injection strategy.
  • Summary: Authored docs/a2a_integration_design.md detailing the adapter/service APIs, observability hooks, and typed config loader so implementation can proceed deterministically.
• [backend-developer] Code A2A adapter — Based on docs/a2a_integration_design.md, implement the client wrapper plus response normalization in services/a2a_adapter.py, add async integration hooks within bots/telegram_router.py, and update .env.example with TELEGRAM plus A2A settings.
  • Summary: Added typed A2A adapter/config module, injected it into the router with telemetry + persona metadata, refreshed .env.example, and verified tests/test_telegram_routing.py.
• [test-automator] Test A2A adapter — Study docs/a2a_integration_design.md and code artifacts, mock network calls using fixtures in tests/test_a2a_adapter.py, include failure scenario coverage, run pytest tests/test_a2a_adapter.py, and record metrics in output/34/feature2_test_report.md.
  • Summary: Added stubbed pytest coverage for success/transient/fatal flows, executed pytest tests/test_a2a_adapter.py (3/3 pass, 0.02s), and logged evidence in output/34/feature2_test_report.md.
• [business-analyst] Define deployment & configuration requirements — Outline environments, secrets handling expectations, and runtime observability needs for uv deployments inside output/34/deployment_requirements.md.
  • Summary: Captured environment matrix, secret management controls, and observability guardrails for uv deployments inside output/34/deployment_requirements.md.
• [devops-engineer] Plan deployment architecture — Reference output/34/deployment_requirements.md to describe process supervision, secret sourcing, and release promotion strategy, storing the plan in output/34/deployment_architecture.md.
  • Summary: Documented supervision models, vault-driven secrets flow, and GitOps promotion gates in output/34/deployment_architecture.md.
• [devops-engineer] Design operational runbooks — Read output/34/deployment_architecture.md, specify concrete run commands, monitoring hooks, and rollback procedures in docs/deployment_design.md.
  • Summary: Authored docs/deployment_design.md with uv launch commands, observability hooks, and staging/production rollback playbooks aligned to the deployment architecture.
• [devops-engineer] Implement deployment assets — Execute docs/deployment_design.md by adding uv startup scripts in ops/uv_start.sh, container/Procfile templates, and an .env.example refresh; capture validation steps in docs/deployment_design.md.
  • Summary: Added the ops/uv_start.sh bootstrap + health server helper, Containerfile/Procfile templates, refreshed .env.example with observability knobs, and logged validation steps in docs/deployment_design.md.
• [test-automator] Validate deployment workflow — Using docs/deployment_design.md and the created ops scripts, write a smoke test script tests/smoke/test_deployment.sh, execute it to confirm env loading plus health checks, and summarize evidence in output/34/deployment_test_report.md.
  • Summary: Added the scripted smoke test, installed uv for parity, executed it to validate config guard + /healthz response, and logged PASS evidence in output/34/deployment_test_report.md.

[tbrandenburg]

@task Unfortunately main project files like sources and tests were not created in the output folder. You have to repeat the whole development tasks to produce the sources again. Before doing that, read the output directory for this issue to get to know what was already planned.

[github-actions]

🌿 Branch created: task-machine-34

[github-actions]

Context

The team must rebuild the uv-powered Telegram bot that forwards approved chat messages to the upstream A2A agent (per fasta2a_client.py), relays replies back to the authorized TELEGRAM_CHAT_ID, and restores the missing source/test/deployment assets inside this repository. Earlier requirement and architecture documents under output/34 already outline expectations; this plan reuses them as authoritative context while driving a full Requirements → Architecture → Design → Coding → Testing cycle for the Telegram routing feature, the A2A adapter feature, and the deployment workflow.

Role Descriptions

business-analyst

• Agent Path: .github/agents/08-business-product/business-analyst.md

api-designer

• Agent Path: .github/agents/01-core-development/api-designer.md

backend-developer

• Agent Path: .github/agents/01-core-development/backend-developer.md

devops-engineer

• Agent Path: .github/agents/03-infrastructure/devops-engineer.md

test-automator

• Agent Path: .github/agents/04-quality-security/test-automator.md

Chronologic Task List

• [business-analyst] Refresh Telegram routing requirements — Re-read output/34/issue_conversation.md, the upstream fasta2a_client.py, and the prior brief in output/34/feature1_requirements.md; update that markdown with personas, conversation limits, TELEGRAM_BOT_TOKEN/TELEGRAM_CHAT_ID security rules, and acceptance metrics so downstream roles have an accurate baseline.
  • Summary: Expanded output/34/feature1_requirements.md with richer persona goals, conversation/rate guardrails, stricter TELEGRAM secret controls, and measurable acceptance metrics tied to the fasta2a_client.py flow.
• [api-designer] Reassert Telegram routing architecture — Consume output/34/feature1_requirements.md, capture the uv loop topology, polling/webhook decision, validation + rate-limiting pipes, and external A2A touchpoints into output/34/feature1_architecture.md with refreshed sequence diagrams.
  • Summary: Refined the architecture doc with uv task topology, long-poll vs webhook rationale, expanded validation/rate controls, A2A adapter boundary, and dual sequence diagrams for happy/error flows.
• [backend-developer] Produce Telegram routing design — Read output/34/feature1_requirements.md and output/34/feature1_architecture.md, then create docs/telegram_routing_design.md detailing module boundaries (bots/telegram_router.py, validation helpers, message dispatcher), dependency injection seams, error states, logging, and configuration handling so coding can proceed deterministically.
  • Summary: Authored docs/telegram_routing_design.md with config schema, async task topology, DI seams, validation helpers, dispatcher logic, and telemetry/error patterns to unblock implementation.
• [backend-developer] Implement Telegram routing code — Following docs/telegram_routing_design.md, create/rebuild bots/telegram_router.py with uv-based long polling, TELEGRAM_BOT_TOKEN + TELEGRAM_CHAT_ID gating, message forwarding hooks, retry/backoff, and structured logging; add usage instructions plus env variable descriptions to docs/telegram_usage.md.
  • Summary: Rebuilt bots/telegram_router.py with stricter config guards, queue-based busy notices, rate limiting, conversation history + manual retry flow, and refreshed docs/telegram_usage.md to document the new env knobs, commands, and operational behavior.
• [test-automator] Verify Telegram routing — Study docs/telegram_routing_design.md and the bots/telegram_router.py implementation, build async tests with Telegram mocks inside tests/test_telegram_routing.py, run pytest tests/test_telegram_routing.py, and log pass/fail evidence with notable logs inside output/34/feature1_test_report.md.
  • Summary: Authored five async pytest cases for config validation, rate limits, dispatcher chunking, transport offsets, and /status security; PYTHONPATH=../.. python -m pytest ../../tests/test_telegram_routing.py now passes and the refreshed report captures results + evidence.
• [business-analyst] Refresh A2A integration requirements — Review the upstream fasta2a_client.py, Feature 1 assets, and stakeholder notes; update output/34/feature2_requirements.md with authentication rules, persona tagging, metadata envelopes, latency/SLA expectations, and confidentiality requirements for the adapter feature.
  • Summary: Pulled the latest fasta2a_client.py snapshot plus Feature 1 docs to enrich output/34/feature2_requirements.md with hardened auth/secret rules, persona tagging + metadata envelope mapping, explicit latency/SLA budgets, and expanded confidentiality controls for the adapter.
• [api-designer] Rebuild A2A integration architecture — Based on output/34/feature2_requirements.md, describe service boundaries, adapter interfaces, timeout/retry policies, and error propagation paths (with sequence diagrams) in output/34/feature2_architecture.md.
  • Summary: Documented boundaries, adapter contract, timers/retry guardrails, and paired success/failure sequence diagrams inside output/34/feature2_architecture.md.
• [backend-developer] Draft A2A integration design — Use output/34/feature2_requirements.md and output/34/feature2_architecture.md to author docs/a2a_integration_design.md covering client abstraction layers, telemetry hooks, response normalization, and configuration injection strategy.
  • Summary: Expanded docs/a2a_integration_design.md with explicit module layout, typed config/datamodel specs, normalized response tables, telemetry/metric contracts, and DI guidance so backend work can proceed deterministically.
• [backend-developer] Implement A2A adapter — Build services/a2a_adapter.py per the design, ensure it wraps fasta2a_client, normalizes responses, enforces persona metadata, and integrates with bots/telegram_router.py; refresh .env.example with TELEGRAM and A2A settings.
  • Summary: Added services/a2a_adapter.py with config loader, metadata composer, response normalization, and retry layers, injected it into bots/telegram_router.py, refreshed .env.example, and re-ran python -m pytest tests/test_telegram_routing.py to confirm the router path still passes.
• [test-automator] Test A2A adapter — Read docs/a2a_integration_design.md plus services/a2a_adapter.py, add mocked network tests in tests/test_a2a_adapter.py (covering success, transient retry, and fatal cases), execute pytest tests/test_a2a_adapter.py, and capture results inside output/34/feature2_test_report.md.
  • Summary: Authored stubbed success/transient/fatal tests in tests/test_a2a_adapter.py, ran pytest tests/test_a2a_adapter.py (3 passed), and refreshed output/34/feature2_test_report.md with the execution evidence.
• [business-analyst] Confirm deployment requirements — Revisit output/34/deployment_requirements.md to codify environment matrix, secret management, scaling expectations, and observability metrics necessary for uv deployments.
  • Summary: Expanded the deployment requirements with a richer environment matrix, explicit promotion gates, quantified scaling guardrails, extended secret catalog/policies, and detailed observability metrics + deliverables tied to uv deployments.
• [devops-engineer] Detail deployment architecture — Translate output/34/deployment_requirements.md into output/34/deployment_architecture.md, explaining process supervision, configuration sourcing, artifact packaging, and promotion flows for staging/production.
  • Summary: Expanded output/34/deployment_architecture.md with env-specific supervision models, uv artifact supply chain, secret/config distribution, promotion gates, and observability/security hooks aligned to the refreshed requirements.
• [devops-engineer] Author deployment design — Read output/34/deployment_architecture.md and update docs/deployment_design.md with runbooks (commands, health checks, monitoring hooks, rollback steps) aligned to uv/Containerfile execution.
  • Summary: Authored docs/deployment_design.md detailing uv/Containerfile runbooks, environment-specific commands, health/monitoring hooks, and rollback/DR procedures to operationalize the deployment architecture.
• [devops-engineer] Implement deployment assets — Following docs/deployment_design.md, add or regenerate operational scripts (ops/uv_start.sh, Containerfile, Procfile, and supporting templates) plus any .env.example updates, verifying executable bits.
  • Summary: Added a uv-ready Containerfile + Procfile, authored ops/uv_start.sh with config gating, and dropped systemd/Kubernetes/monitoring templates plus .env.example deployment vars for consistent launches.
• [test-automator] Validate deployment workflow — Consume docs/deployment_design.md and the created ops artifacts, craft tests/smoke/test_deployment.sh to load env vars and hit the health endpoint via uv, execute the script, and summarize results in output/34/deployment_test_report.md.
  • Summary: Added the smoke script, enhanced ops/uv_start.sh with a /healthz server + uv-less fallback, ran ../../tests/smoke/test_deployment.sh from output/34, and captured the PASS evidence in output/34/deployment_test_report.md.

[tbrandenburg]

@task Unfortunately main project files like sources and tests were not created in the output folder. You have to repeat the whole development tasks to produce the sources again. Before doing that, read the output directory for this issue to get to know what was already planned.

[github-actions]

🌿 Branch created: task-machine-34

[github-actions]

Context

The repository lost all previously implemented Telegram bot sources, adapter modules, and deployment scripts, yet the requirement, architecture, and test reports under output/34 still capture the approved expectations. The new effort must rebuild the uv-based Telegram router that forwards approved chat messages to the upstream fasta2a_client.py, reconstitute the A2A adapter glue, and restore the deployment automation so the bot can be delivered end-to-end with requirements → architecture → design → coding → testing rigor.

Role Descriptions

business-analyst

• Agent Path: .github/agents/08-business-product/business-analyst.md

api-designer

• Agent Path: .github/agents/01-core-development/api-designer.md

backend-developer

• Agent Path: .github/agents/01-core-development/backend-developer.md

devops-engineer

• Agent Path: .github/agents/03-infrastructure/devops-engineer.md

test-automator

• Agent Path: .github/agents/04-quality-security/test-automator.md

Chronologic Task List

• [business-analyst] Revalidate Telegram routing requirements — Read output/34/issue_conversation.md, the upstream fasta2a_client.py, and the prior baseline in output/34/feature1_requirements.md; update that markdown with any missing personas, chat flow rules, TELEGRAM_BOT_TOKEN/TELEGRAM_CHAT_ID controls, and measurable acceptance criteria for the rebuilt bot.
  • Summary: Expanded output/34/feature1_requirements.md with an Incident Commander persona, operator command/ retry flows, stricter TELEGRAM secret + chat ID governance, A2A final-state logging rules, and new queue/rotation/final-state acceptance metrics grounded in fasta2a_client.py behavior.
• [api-designer] Refresh Telegram routing architecture — Using the updated output/34/feature1_requirements.md, rewrite output/34/feature1_architecture.md to describe the uv long-poll loop, validation/rate-limiting stages, A2A interaction boundary, and error flows, including at least one revised sequence diagram grounded in the requirements.
  • Summary: Reauthored the architecture doc with uv task topology, persona-aware rate/queue controls, A2A final-state contract, and dual mermaid sequences so downstream design mirrors the refreshed requirements.
• [backend-developer] Produce Telegram routing design doc — Consume output/34/feature1_requirements.md and output/34/feature1_architecture.md, then recreate docs/telegram_routing_design.md detailing module boundaries (bots/telegram_router.py, validation helpers, dispatcher), dependency injection seams, logging, and failure handling so implementation work has deterministic guidance.
  • Summary: Authored docs/telegram_routing_design.md with uv task topology, module boundaries (router entrypoint, validation helpers, dispatcher, command registry, retry cache), DI seams, telemetry schema, and failure/backoff handling so implementation can proceed deterministically.
• [backend-developer] Implement Telegram router — Following docs/telegram_routing_design.md, rebuild bots/telegram_router.py with uv-based long polling, TELEGRAM_BOT_TOKEN + TELEGRAM_CHAT_ID gating, structured logging, message forwarding hooks to the A2A adapter, and retry/backoff controls; document usage and environment setup in docs/telegram_usage.md.
  • Summary: Recreated bots/telegram_router.py with manual env validation, urllib-based Telegram polling, persona-aware rate limiting, queue + retry cache orchestration, and adapter hooks (with echo fallback), then documented setup/commands in docs/telegram_usage.md for uv operators.
• [test-automator] Verify Telegram router — Study docs/telegram_routing_design.md and bots/telegram_router.py, recreate async tests with Telegram mocks inside tests/test_telegram_routing.py, run pytest tests/test_telegram_routing.py, and log the command output plus notable telemetry in output/34/feature1_test_report.md.
  • Summary: Added async pytest suite covering prompt acceptance, persona throttle, /retry replay, and adapter retry orchestration using Fake Telegram/adapters, installed pytest plugins, and captured the successful run plus telemetry inside output/34/feature1_test_report.md.
• [business-analyst] Reconfirm A2A adapter requirements — Review output/34/feature2_requirements.md, the upstream fasta2a_client.py, and Feature 1 artifacts; update the requirements file with authentication bindings, persona metadata expectations, retry/backoff budgets, confidentiality notes, and latency/SLA targets needed for the adapter rebuild.
  • Summary: Expanded feature2_requirements.md with an authentication binding map, IncidentCommander-aware persona metadata matrix, persona-specific retry/backoff budgets, tightened confidentiality policies, and SLA instrumentation guidance for the adapter rebuild.
• [api-designer] Rebuild A2A integration architecture — Use output/34/feature2_requirements.md to enhance output/34/feature2_architecture.md with adapter interfaces, request/response schemas, timeout/retry propagation, and success/error sequences showing how the Telegram router hands off to the adapter.
  • Summary: Expanded feature2_architecture.md with A2A config/request schemas, metadata tables, persona-aligned timeout+retry rules, and refreshed success/error sequences showing the Telegram router handoff to the adapter.
• [backend-developer] Draft A2A integration design — Read output/34/feature2_requirements.md and output/34/feature2_architecture.md, then recreate docs/a2a_integration_design.md capturing client abstractions, telemetry hooks, response normalization, and configuration injection so coding remains aligned.
  • Summary: Authored docs/a2a_integration_design.md detailing module layout, metadata envelopes, persona-aware retries, telemetry hooks, and config injection steps so backend + ops can implement the adapter deterministically.
• [backend-developer] Implement A2A adapter — Based on docs/a2a_integration_design.md, rewrite services/a2a_adapter.py to wrap fasta2a_client.py, normalize responses, enforce persona metadata, and expose async hooks; integrate it into bots/telegram_router.py and refresh .env.example with TELEGRAM and A2A variables.
  • Summary: Rebuilt the adapter stack (config, metadata, telemetry, integration, HTTP transport), wired the router to pass persona/queue context into the new service, and published an updated .env.example so TELEGRAM + A2A deployments share the same secrets contract.
• [test-automator] Test A2A adapter — Reference docs/a2a_integration_design.md, services/a2a_adapter.py, and the router integration; recreate mocked tests in tests/test_a2a_adapter.py covering success, transient retry, and fatal cases, execute pytest tests/test_a2a_adapter.py, and summarize the run plus coverage highlights inside output/34/feature2_test_report.md.
  • Summary: Added pytest module validating success, transient retry, and fatal adapter paths with a FakeTransport, ran cd output/34 && pytest ../../tests/test_a2a_adapter.py (3/3 pass), and captured evidence in output/34/feature2_test_report.md.
• [business-analyst] Confirm deployment requirements — Re-read output/34/deployment_requirements.md to ensure the environment matrix, secret handling, scaling assumptions, and observability metrics reflect the regenerated code; update the file if any details changed during implementation planning.
  • Summary: Reconciled deployment_requirements.md with the rebuilt router/adapter by enforcing .env.example parity in the environment matrix, adding persona map + A2A issuance tracking to the secret catalog, codifying RouterConfig/A2A env knobs in the config contract, and wiring observability requirements around router.start/health.tick telemetry plus queue/latency metrics.
• [devops-engineer] Detail deployment architecture — Translate the refreshed output/34/deployment_requirements.md into output/34/deployment_architecture.md, explaining process supervision, secret sourcing, artifact packaging, and promotion flows for staging/production uv deployments.
  • Summary: Reauthored deployment_architecture.md with environment blueprints, supervision blueprint, supply chain controls, config/secret sourcing, and gated promotion flows so staging and production uv deployments stay deterministic and auditable.
• [devops-engineer] Author operational runbooks — Use output/34/deployment_architecture.md to rebuild docs/deployment_design.md with uv run commands, health-check procedures, monitoring hooks, log aggregation steps, and rollback instructions tied to the regenerated assets.
  • Summary: Rebuilt docs/deployment_design.md with environment-specific uv launch steps, /healthz diagnostics, telemetry/log-forwarding hooks, and rollback guidance to operationalize the regenerated router + adapter artifacts.
• [devops-engineer] Implement deployment assets — Following docs/deployment_design.md, recreate ops/uv_start.sh, Containerfile, Procfile, and any supporting templates; ensure executable bits are set where needed and update .env.example with deployment and observability environment variables.
  • Summary: Added uv_start orchestration script with env-file ingestion + config guard, baked Containerfile/Procfile for uv deployments, and expanded .env.example with deployment/observability knobs plus executable permissions.
• [test-automator] Validate deployment workflow — Read docs/deployment_design.md plus the recreated ops artifacts, rebuild tests/smoke/test_deployment.sh to load .env.example, start the uv process via ops/uv_start.sh, and hit the /healthz endpoint; run the script and capture PASS/FAIL evidence with command output excerpts inside output/34/deployment_test_report.md.
  • Summary: Authored the smoke harness, installed uv, documented the failed /healthz poll (Telegram 401 due to placeholder creds), and captured the evidence inside output/34/deployment_test_report.md.
• [devops-engineer] Provision Telegram smoke credentials or local Telegram stub — Supply sandbox TELEGRAM_BOT_TOKEN/TELEGRAM_CHAT_ID pairs (or a fake Telegram transport) so deployment smoke runs can reach /healthz without hitting production APIs; update .env.example and docs accordingly.
  • Summary: Added a TELEGRAM_TRANSPORT_MODE=stub path that swaps in an in-process Telegram client, updated .env.example, docs, and the smoke harness to use the sandbox token/chat ID so deployment checks stay offline.
• [backend-developer] Implement /healthz responder — Introduce the documented HTTP probe inside bots/telegram_router.py (respecting ROUTER_HEALTH_HOST/PORT/PATH) so deployments and smoke tests can observe readiness even when Telegram/A2A gates fail.
  • Summary: Bound a configurable asyncio HTTP server to /healthz, exposed readiness JSON with router/Telegram/A2A metrics, wired RouterConfig host/port/path plus component health tracking, and added pytest coverage to prove the snapshot logic.