diff --git a/.env.example b/.env.example index 7a5243459..a077eb57b 100644 --- a/.env.example +++ b/.env.example @@ -89,10 +89,20 @@ MODEL_DEFAULT={"connection":"vertex-prod","model":"gemini-3.5-flash"} # Provider credential for an Anthropic connection. # ANTHROPIC_API_KEY= +# OpenAI-compatible endpoints may use distinct keys. Each connection's +# api_key_env names the environment variable holding its secret; omit it for an +# unauthenticated endpoint. +# OPENROUTER_API_KEY= +# MODEL_CONNECTIONS={"openrouter":{"backend":"openai-compatible","base_url":"https://openrouter.ai/api/v1","api_key_env":"OPENROUTER_API_KEY","allowed_models":["your-model"],"capabilities":["tools"]}} +# MODEL_DEFAULT={"connection":"openrouter","model":"your-model"} + # Legacy single-model configuration. Use only when MODEL_CONNECTIONS and # MODEL_DEFAULT are not set. # LLM_BACKEND=vertex-ai # LLM_MODEL=gemini-3.5-flash +# For a legacy single OpenAI-compatible endpoint: +# OPENAI_BASE_URL=http://model-gateway.internal/v1 +# OPENAI_API_KEY= # Model for container tasks (code implementation) # Can use a different model than orchestrator (e.g., for cost/rate limit reasons) diff --git a/README.md b/README.md index bf6f73ece..9015e7ef4 100644 --- a/README.md +++ b/README.md @@ -50,7 +50,7 @@ Forge connects Jira, GitHub, and AI coding agents into one event-driven workflow Forge is built on [Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview) and passes agents a LangChain chat model instance. -The built-in model factory supports direct Anthropic API credentials and Google Vertex AI-backed models. Because the agent layer is model-object based, Forge can be extended to any LangChain-compatible chat model by adding it to the model factory. +The built-in model factory supports direct Anthropic, Google Gemini, Vertex AI, and OpenAI-compatible Chat Completions endpoints. Named compatible connections can use distinct base URLs and environment-backed credentials. Because the agent layer is model-object based, Forge can be extended to other LangChain-compatible chat models by adding them to the model factory. ## Where Forge Is Different diff --git a/containers/Containerfile b/containers/Containerfile index 28559d0a0..daf16646f 100644 --- a/containers/Containerfile +++ b/containers/Containerfile @@ -24,6 +24,7 @@ RUN pip install --no-cache-dir \ deepagents \ anthropic \ langchain-anthropic \ + langchain-openai \ langchain-google-genai \ langchain-google-vertexai \ langchain-mcp-adapters \ diff --git a/containers/README.md b/containers/README.md index 851af629b..df06bef9d 100644 --- a/containers/README.md +++ b/containers/README.md @@ -104,11 +104,13 @@ Passed automatically by the orchestrator: | Variable | Description | |----------|-------------| -| `LLM_BACKEND` | Required: `vertex-ai`, `google-genai`, or `anthropic` | +| `LLM_BACKEND` | Required: `vertex-ai`, `google-genai`, `anthropic`, or `openai-compatible` | | `GOOGLE_API_KEY` | Gemini API key for `google-genai` | | `GOOGLE_CLOUD_PROJECT` | GCP project for `vertex-ai` | | `GOOGLE_CLOUD_LOCATION` | Vertex AI location | | `ANTHROPIC_API_KEY` | API key for `anthropic` | +| `OPENAI_BASE_URL` | Required base URL for `openai-compatible` | +| `OPENAI_API_KEY` | API key for `openai-compatible`; Forge supplies a placeholder for unauthenticated endpoints | | `LLM_MODEL` | Required model name (for example, `gemini-3.5-flash`) | | `CONTAINER_LLM_MODEL` | Optional container model override; it must be compatible with `LLM_BACKEND` because containers do not support a separate backend | | `CONTAINER_COMMAND_TIMEOUT` | Maximum execution time in seconds for individual commands: agent tasks, reviewer commands, and fallback tests (default: `600`, must not exceed `CONTAINER_TIMEOUT`) | @@ -141,7 +143,7 @@ Example: `forge-AISOS-189-installer-12345` ## Task Execution The entrypoint runs a Deep Agent with `LocalShellBackend`. The built-in model -factory supports the Gemini API, Vertex AI, and the Anthropic API. Because the +factory supports the Gemini API, Vertex AI, Anthropic, and OpenAI-compatible endpoints. Because the agent receives a LangChain chat model instance, additional providers can be added by extending the model factory. diff --git a/containers/entrypoint.py b/containers/entrypoint.py index 6f739478e..ac5958b0a 100644 --- a/containers/entrypoint.py +++ b/containers/entrypoint.py @@ -442,9 +442,7 @@ def _create_llm_model(max_tokens_default: int = 16384): else: from langchain_google_vertexai.model_garden import ChatAnthropicVertex - logger.info( - f"Using Vertex AI Anthropic model: {model_name}, max_tokens={max_tokens}" - ) + logger.info(f"Using Vertex AI Anthropic model: {model_name}, max_tokens={max_tokens}") model = ChatAnthropicVertex( model_name=model_name, project=vertex_project, @@ -483,6 +481,20 @@ def _create_llm_model(max_tokens_default: int = 16384): max_tokens=max_tokens, **tuning, ) + elif backend_name == "openai-compatible": + base_url = os.environ.get("OPENAI_BASE_URL") + if not base_url: + raise RuntimeError("OPENAI_BASE_URL is required for the openai-compatible backend") + from langchain_openai import ChatOpenAI + + logger.info("Using OpenAI-compatible model %s at %s", model_name, base_url) + model = ChatOpenAI( + model=model_name, + base_url=base_url, + api_key=os.environ.get("OPENAI_API_KEY") or "not-required", + max_tokens=max_tokens, + **tuning, + ) else: raise RuntimeError(f"Unsupported LLM_BACKEND: {backend_name}") diff --git a/docs/architecture/overview.md b/docs/architecture/overview.md index 8d1357751..7bee334fa 100644 --- a/docs/architecture/overview.md +++ b/docs/architecture/overview.md @@ -82,4 +82,4 @@ flowchart TD **Podman Container**: Ephemeral rootless containers that execute implementation tasks. Each container receives the repo at `/workspace` (read-write), a task file at `/task.json` (read-only), and LLM credentials. Runs Deep Agents with MCP tool access. The orchestrator handles pushing and PR creation after the container exits. -**LLM Backends**: Claude and Gemini models called by both orchestrator nodes (planning, review) and container agents (code generation). Supports Anthropic direct API and Google Vertex AI, selected automatically based on configured credentials. +**LLM Backends**: Claude, Gemini, and OpenAI-compatible models called by both orchestrator nodes (planning, review) and container agents (code generation). Supports Anthropic direct API, Google APIs and Vertex AI, and configured OpenAI-compatible Chat Completions endpoints. diff --git a/docs/reference/config.md b/docs/reference/config.md index 5edd93598..a6cb99c3a 100644 --- a/docs/reference/config.md +++ b/docs/reference/config.md @@ -53,6 +53,19 @@ native credential environment variables. MODEL_DEFAULT={"connection":"anthropic-prod","model":"claude-sonnet-4-6"} ``` +=== "OpenAI-compatible endpoint" + + ```bash + GATEWAY_API_KEY=your-gateway-key + MODEL_CONNECTIONS={"gateway":{"backend":"openai-compatible","base_url":"https://gateway.example/v1","api_key_env":"GATEWAY_API_KEY","allowed_models":["your-model"],"capabilities":["tools"]}} + MODEL_DEFAULT={"connection":"gateway","model":"your-model"} + ``` + + `api_key_env` contains an environment-variable name, never the credential. + Different connections can reference different keys. Omit `api_key_env` for + endpoints that do not authenticate. Compatible endpoints must implement the + OpenAI Chat Completions API and tool calling for agentic stages. + Forge validates the backend, credentials, model allowlist, capabilities, and default target at startup. @@ -67,6 +80,9 @@ default target at startup. LLM_MODEL=gemini-3.5-flash ``` + For one OpenAI-compatible endpoint, set `LLM_BACKEND=openai-compatible`, + `OPENAI_BASE_URL`, `LLM_MODEL`, and optionally `OPENAI_API_KEY`. + `LLM_BACKEND` and `LLM_MODEL` are required together when `MODEL_CONNECTIONS` and `MODEL_DEFAULT` are not configured. Provider credentials must use the provider-native variables shown above; legacy diff --git a/pyproject.toml b/pyproject.toml index f0769dca8..d8f865d16 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -29,12 +29,14 @@ dependencies = [ "anthropic[vertex]>=0.40.0", "deepagents>=0.1.0", "langchain-anthropic>=0.3.0", + "langchain-openai>=0.3.0", "langchain-google-genai>=4.0.0", "langchain-google-vertexai>=2.0.0", "gitpython>=3.1.0", "httpx>=0.27.0", "pydantic>=2.9.0", "pydantic-settings>=2.6.0", + "python-dotenv>=1.0.0", "langfuse>=2.50.0", "langchain-mcp-adapters>=0.2.2", "prometheus-client>=0.21.0", diff --git a/src/forge/cli.py b/src/forge/cli.py index 78cfb4d53..e07b2fe9a 100644 --- a/src/forge/cli.py +++ b/src/forge/cli.py @@ -1254,6 +1254,8 @@ async def cmd_health(_args: argparse.Namespace) -> int: print("[OK] Using Anthropic API") else: print("[WARN] Anthropic selected but ANTHROPIC_API_KEY is not configured") + elif settings.llm_backend == "openai-compatible": + print(f"[OK] Using OpenAI-compatible endpoint: {settings.openai_base_url}") else: print("[WARN] No LLM backend configured") diff --git a/src/forge/config.py b/src/forge/config.py index 5d5572b26..5df4ca28b 100644 --- a/src/forge/config.py +++ b/src/forge/config.py @@ -1,10 +1,12 @@ """Configuration management using Pydantic settings.""" import logging +import os from functools import cached_property, lru_cache from pathlib import Path from typing import TYPE_CHECKING, Any, Literal +from dotenv import dotenv_values from pydantic import Field, SecretStr, model_validator from pydantic_settings import BaseSettings, SettingsConfigDict @@ -154,8 +156,8 @@ def known_repos(self) -> list[str]: # Model backend configuration. Provider-specific credentials stay at the # adapter boundary; the rest of Forge consumes the resolved backend/model. - llm_backend: Literal["google-genai", "vertex-ai", "anthropic"] = Field( - description="Model backend: vertex-ai, google-genai, or anthropic", + llm_backend: Literal["google-genai", "vertex-ai", "anthropic", "openai-compatible"] = Field( + description="Model backend: vertex-ai, google-genai, anthropic, or openai-compatible", ) google_api_key: SecretStr = Field( default=SecretStr(""), @@ -173,6 +175,14 @@ def known_repos(self) -> list[str]: default=SecretStr(""), description="Anthropic API key for the anthropic backend", ) + openai_api_key: SecretStr = Field( + default=SecretStr(""), + description="API key for a legacy single OpenAI-compatible connection", + ) + openai_base_url: str = Field( + default="", + description="Base URL for a legacy single OpenAI-compatible connection", + ) llm_model: str = Field( description="Model for orchestrator agents", ) @@ -234,6 +244,8 @@ def derive_legacy_model_fields(cls, values: Any) -> Any: if backend == "vertex-ai": derived["google_cloud_project"] = connection.get("project") or "" derived["google_cloud_location"] = connection.get("location") or "global" + elif backend == "openai-compatible": + derived["openai_base_url"] = connection.get("base_url") or "" return derived @property @@ -305,6 +317,10 @@ def validate_llm_configuration(self) -> "Settings": self._validate_model_policy(ModelPolicyResolver) return self + if self.llm_backend == "openai-compatible": + self._validate_model_policy(ModelPolicyResolver) + return self + if not self.anthropic_api_key.get_secret_value(): raise ValueError("ANTHROPIC_API_KEY is required for anthropic") incompatible = [m for m in models if self.detect_model_provider(m) != "anthropic"] @@ -325,6 +341,24 @@ def _validate_model_policy(self, resolver_type: type) -> None: raise ValueError("GOOGLE_API_KEY is required by a google-genai model connection") if connection.backend == "anthropic" and not self.anthropic_api_key.get_secret_value(): raise ValueError("ANTHROPIC_API_KEY is required by an anthropic model connection") + if connection.backend == "openai-compatible" and connection.api_key_env: + self.resolve_openai_api_key(connection.api_key_env) + + def resolve_openai_api_key(self, api_key_env: str | None) -> str: + """Resolve a compatible endpoint credential without serializing it into policy.""" + if not api_key_env: + return self.openai_api_key.get_secret_value() + value = os.environ.get(api_key_env) + if value is None: + env_file = self.model_config.get("env_file") + if isinstance(env_file, str): + dotenv_value = dotenv_values(env_file).get(api_key_env) + value = str(dotenv_value) if dotenv_value is not None else None + if value is None: + raise ValueError( + f"Environment variable '{api_key_env}' referenced by api_key_env is not set" + ) + return value @property def effective_model_connections(self) -> dict[str, Any]: @@ -342,6 +376,8 @@ def effective_model_connections(self) -> dict[str, Any]: project=self.google_cloud_project, location=self.google_cloud_location, ) + elif self.llm_backend == "openai-compatible": + connection.update(base_url=self.openai_base_url) return {"default": connection} @property diff --git a/src/forge/integrations/agents/agent.py b/src/forge/integrations/agents/agent.py index cd7c9b6cc..ec1cde795 100644 --- a/src/forge/integrations/agents/agent.py +++ b/src/forge/integrations/agents/agent.py @@ -18,6 +18,7 @@ from deepagents import create_deep_agent from deepagents.backends.filesystem import FilesystemBackend from langchain_anthropic import ChatAnthropic +from langchain_openai import ChatOpenAI from langgraph.checkpoint.memory import MemorySaver # Optional MCP support @@ -156,7 +157,7 @@ def _ensure_api_key(self) -> None: api_key = self.settings.google_api_key.get_secret_value() if api_key and not os.environ.get("GOOGLE_API_KEY"): os.environ["GOOGLE_API_KEY"] = api_key - elif not os.environ.get("ANTHROPIC_API_KEY"): + elif self.settings.llm_backend == "anthropic" and not os.environ.get("ANTHROPIC_API_KEY"): api_key = self.settings.anthropic_api_key.get_secret_value() if api_key: os.environ["ANTHROPIC_API_KEY"] = api_key @@ -261,6 +262,22 @@ def _create_model( **({"temperature": temperature} if temperature is not None else {}), ) + if backend == "openai-compatible": + base_url = model_target.base_url if model_target else self.settings.openai_base_url + if not base_url: + raise ValueError("OPENAI_BASE_URL is required for openai-compatible") + api_key = self.settings.resolve_openai_api_key( + model_target.api_key_env if model_target else None + ) + logger.info("Creating OpenAI-compatible model %s at %s", model, base_url) + return ChatOpenAI( + model=model, + base_url=base_url, + api_key=api_key or "not-required", + max_tokens=max_tokens, + **({"temperature": temperature} if temperature is not None else {}), + ) + raise ValueError(f"Unsupported LLM backend: {backend}") def _get_skill_paths(self, ticket_key: str | None = None) -> list[str]: @@ -999,6 +1016,8 @@ def _get_setting_value(self, var_name: str) -> str: "ATLASSIAN_AUTH_BASE64": lambda: self.settings.atlassian_auth_base64, "AGENT_WORKING_DIRECTORY": lambda: self.settings.agent_working_directory or os.getcwd(), "ANTHROPIC_API_KEY": lambda: self.settings.anthropic_api_key.get_secret_value(), + "OPENAI_API_KEY": lambda: self.settings.openai_api_key.get_secret_value(), + "OPENAI_BASE_URL": lambda: self.settings.openai_base_url, } if var_name in var_mapping: diff --git a/src/forge/models/model_policy.py b/src/forge/models/model_policy.py index bd9941ba5..cc2ab8814 100644 --- a/src/forge/models/model_policy.py +++ b/src/forge/models/model_policy.py @@ -4,11 +4,13 @@ credentials remain in :mod:`forge.config` and are resolved at the adapter boundary. """ +import re from typing import Any, Literal +from urllib.parse import urlparse from pydantic import BaseModel, ConfigDict, Field, model_validator -Backend = Literal["google-genai", "vertex-ai", "anthropic"] +Backend = Literal["google-genai", "vertex-ai", "anthropic", "openai-compatible"] MAX_MODEL_OUTPUT_TOKENS = 131_072 @@ -20,6 +22,8 @@ class ModelConnection(BaseModel): backend: Backend project: str | None = None location: str | None = None + base_url: str | None = None + api_key_env: str | None = None allowed_models: list[str] = Field(default_factory=lambda: ["*"]) capabilities: set[str] = Field(default_factory=set) allow_project_override: bool = True @@ -28,6 +32,14 @@ class ModelConnection(BaseModel): def validate_connection(self) -> "ModelConnection": if self.backend == "vertex-ai" and not self.project: raise ValueError("vertex-ai connections require project") + if self.backend == "openai-compatible": + parsed = urlparse(self.base_url or "") + if parsed.scheme not in {"http", "https"} or not parsed.netloc: + raise ValueError( + "openai-compatible connections require an absolute HTTP(S) base_url" + ) + if self.api_key_env and not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", self.api_key_env): + raise ValueError("api_key_env must be a valid environment variable name") return self @@ -51,6 +63,8 @@ class ResolvedModelTarget(ModelTarget): policy_source: Literal["project", "project_default", "global", "default"] project: str | None = None location: str | None = None + base_url: str | None = None + api_key_env: str | None = None def trace_metadata(self) -> dict[str, Any]: return { @@ -193,6 +207,8 @@ def _model_matches_backend(model: str, backend: Backend) -> bool: # Anthropic models. Direct-provider backends accept only their family. if backend == "vertex-ai": return True + if backend == "openai-compatible": + return True return is_gemini == (backend == "google-genai") def _validate_target( @@ -269,6 +285,8 @@ def resolve( backend=connection.backend, project=connection.project, location=connection.location, + base_url=connection.base_url, + api_key_env=connection.api_key_env, policy_key=key, policy_source=source, ) diff --git a/src/forge/sandbox/runner.py b/src/forge/sandbox/runner.py index a650cedbf..ce7e8f2b9 100644 --- a/src/forge/sandbox/runner.py +++ b/src/forge/sandbox/runner.py @@ -240,7 +240,7 @@ def _build_env_vars( Returns: Dict of environment variables. """ - env = {} + env: dict[str, str] = {} selected_backend = model_target.backend if model_target else self.settings.llm_backend if not selected_backend: @@ -255,6 +255,14 @@ def _build_env_vars( anthropic_api_key = self.settings.anthropic_api_key.get_secret_value() if anthropic_api_key: env["ANTHROPIC_API_KEY"] = anthropic_api_key + elif selected_backend == "openai-compatible": + env["OPENAI_BASE_URL"] = ( + model_target.base_url if model_target else self.settings.openai_base_url + ) or "" + api_key = self.settings.resolve_openai_api_key( + model_target.api_key_env if model_target else None + ) + env["OPENAI_API_KEY"] = api_key or "not-required" # Pass Vertex AI credentials if selected_backend == "vertex-ai": diff --git a/tests/unit/containers/test_entrypoint_llm_config.py b/tests/unit/containers/test_entrypoint_llm_config.py index 7dad3e82e..de4bfcefc 100644 --- a/tests/unit/containers/test_entrypoint_llm_config.py +++ b/tests/unit/containers/test_entrypoint_llm_config.py @@ -23,6 +23,8 @@ def clear_model_env(monkeypatch): "LLM_MODEL", "GOOGLE_API_KEY", "ANTHROPIC_API_KEY", + "OPENAI_API_KEY", + "OPENAI_BASE_URL", ): monkeypatch.delenv(name, raising=False) @@ -50,3 +52,11 @@ def test_explicit_backend_and_model_take_precedence(entrypoint_module, monkeypat assert entrypoint_module.resolve_llm_backend() == "vertex-ai" assert entrypoint_module.resolve_llm_model() == "gemini-custom" + + +def test_openai_compatible_requires_base_url(entrypoint_module, monkeypatch): + monkeypatch.setenv("LLM_BACKEND", "openai-compatible") + monkeypatch.setenv("LLM_MODEL", "custom-model") + + with pytest.raises(RuntimeError, match="OPENAI_BASE_URL is required"): + entrypoint_module._create_llm_model() diff --git a/tests/unit/integrations/agents/test_agent.py b/tests/unit/integrations/agents/test_agent.py index 066264094..8fbd28da7 100644 --- a/tests/unit/integrations/agents/test_agent.py +++ b/tests/unit/integrations/agents/test_agent.py @@ -2,7 +2,10 @@ from unittest.mock import ANY, AsyncMock, MagicMock, patch +import httpx import pytest +import respx +from langchain_openai import ChatOpenAI from forge.integrations.agents.agent import ForgeAgent @@ -15,9 +18,11 @@ def _model_agent(backend: str, model: str) -> ForgeAgent: llm_max_tokens=16384, google_cloud_project="project", google_cloud_location="global", + openai_base_url="https://gateway.example/v1", ) agent.settings.google_api_key.get_secret_value.return_value = "google-key" agent.settings.anthropic_api_key.get_secret_value.return_value = "anthropic-key" + agent.settings.resolve_openai_api_key.return_value = "gateway-key" return agent @@ -69,6 +74,81 @@ def test_create_model_rejects_backend_model_mismatch(): agent._create_model() +def test_create_model_uses_openai_compatible_backend(): + agent = _model_agent("openai-compatible", "custom-model") + + with patch("forge.integrations.agents.agent.ChatOpenAI") as model_class: + agent._create_model() + + model_class.assert_called_once_with( + model="custom-model", + base_url="https://gateway.example/v1", + api_key="gateway-key", + max_tokens=16384, + ) + + +@respx.mock +def test_openai_compatible_chat_completions_tool_call_contract(): + route = respx.post("https://gateway.example/v1/chat/completions").mock( + return_value=httpx.Response( + 200, + json={ + "id": "chatcmpl-test", + "object": "chat.completion", + "created": 1, + "model": "custom-model", + "choices": [ + { + "index": 0, + "finish_reason": "tool_calls", + "message": { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call-1", + "type": "function", + "function": { + "name": "lookup", + "arguments": '{"query":"forge"}', + }, + } + ], + }, + } + ], + "usage": {"prompt_tokens": 4, "completion_tokens": 3, "total_tokens": 7}, + }, + ) + ) + model = ChatOpenAI( + model="custom-model", + base_url="https://gateway.example/v1", + api_key="gateway-secret", + ).bind_tools( + [ + { + "name": "lookup", + "description": "Look up a value", + "parameters": { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + }, + } + ] + ) + + response = model.invoke("Find forge") + + assert response.tool_calls == [ + {"name": "lookup", "args": {"query": "forge"}, "id": "call-1", "type": "tool_call"} + ] + assert route.calls[0].request.headers["authorization"] == "Bearer gateway-secret" + assert b'"tools"' in route.calls[0].request.content + + @pytest.mark.asyncio async def test_answer_question(): """ForgeAgent can answer questions about artifacts.""" diff --git a/tests/unit/models/test_model_policy.py b/tests/unit/models/test_model_policy.py index 028b63304..fa33bb304 100644 --- a/tests/unit/models/test_model_policy.py +++ b/tests/unit/models/test_model_policy.py @@ -158,6 +158,52 @@ def test_provider_neutral_options_flow_to_resolved_target( assert resolved.max_output_tokens == 8192 +def test_openai_compatible_connection_flows_endpoint_without_secret() -> None: + resolver = ModelPolicyResolver( + connections={ + "gateway": { + "backend": "openai-compatible", + "base_url": "https://gateway.example/v1", + "api_key_env": "GATEWAY_API_KEY", + "capabilities": ["tools"], + } + }, + policy={}, + default={"connection": "gateway", "model": "custom-model"}, + ) + + resolved = resolver.resolve("implement_task") + + assert resolved.base_url == "https://gateway.example/v1" + assert resolved.api_key_env == "GATEWAY_API_KEY" + assert "api_key" not in resolved.model_dump() + + +@pytest.mark.parametrize("base_url", ["", "gateway.example/v1", "ftp://gateway.example/v1"]) +def test_openai_compatible_connection_requires_http_url(base_url: str) -> None: + with pytest.raises(ValueError, match="absolute HTTP.*base_url"): + ModelPolicyResolver( + connections={"gateway": {"backend": "openai-compatible", "base_url": base_url}}, + policy={}, + default={"connection": "gateway", "model": "custom-model"}, + ) + + +def test_openai_compatible_connection_validates_api_key_env() -> None: + with pytest.raises(ValueError, match="valid environment variable"): + ModelPolicyResolver( + connections={ + "gateway": { + "backend": "openai-compatible", + "base_url": "https://gateway.example/v1", + "api_key_env": "not-valid!", + } + }, + policy={}, + default={"connection": "gateway", "model": "custom-model"}, + ) + + def test_invalid_default_connection_fails_eagerly() -> None: with pytest.raises(ValueError, match="unknown connection"): ModelPolicyResolver( diff --git a/tests/unit/sandbox/test_runner_llm_backend.py b/tests/unit/sandbox/test_runner_llm_backend.py index 769778700..6f799862c 100644 --- a/tests/unit/sandbox/test_runner_llm_backend.py +++ b/tests/unit/sandbox/test_runner_llm_backend.py @@ -21,9 +21,11 @@ def _settings(backend: str) -> MagicMock: log_level="INFO", google_cloud_project="project", google_cloud_location="global", + openai_base_url="https://gateway.example/v1", ) settings.google_api_key = SecretStr("google-key") settings.anthropic_api_key = SecretStr("anthropic-key") + settings.resolve_openai_api_key.return_value = "gateway-key" return settings @@ -37,6 +39,14 @@ def _settings(backend: str) -> MagicMock: {"GOOGLE_CLOUD_PROJECT": "project", "GOOGLE_CLOUD_LOCATION": "global"}, "GOOGLE_API_KEY", ), + ( + "openai-compatible", + { + "OPENAI_BASE_URL": "https://gateway.example/v1", + "OPENAI_API_KEY": "gateway-key", + }, + "ANTHROPIC_API_KEY", + ), ], ) def test_build_env_vars_passes_only_selected_backend_credentials( diff --git a/tests/unit/test_config_prd.py b/tests/unit/test_config_prd.py index e077ce551..8efe0e3c4 100644 --- a/tests/unit/test_config_prd.py +++ b/tests/unit/test_config_prd.py @@ -14,6 +14,8 @@ def clear_prd_proposal_env(monkeypatch): monkeypatch.delenv("GOOGLE_CLOUD_PROJECT", raising=False) monkeypatch.delenv("GOOGLE_CLOUD_LOCATION", raising=False) monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False) + monkeypatch.delenv("OPENAI_API_KEY", raising=False) + monkeypatch.delenv("OPENAI_BASE_URL", raising=False) monkeypatch.delenv("LLM_MODEL", raising=False) monkeypatch.delenv("CONTAINER_LLM_MODEL", raising=False) monkeypatch.delenv("MODEL_CONNECTIONS", raising=False) @@ -265,6 +267,47 @@ def test_anthropic_configuration_is_explicit(self): assert settings.llm_model == "claude-sonnet-4-6" assert settings.anthropic_api_key.get_secret_value() == "anthropic-key" + def test_openai_compatible_named_connection_resolves_its_credential(self, monkeypatch): + monkeypatch.setenv("GATEWAY_API_KEY", "gateway-secret") + settings = Settings( + _env_file=None, + jira_base_url="https://test.atlassian.net", + jira_api_token="test", + jira_user_email="test@example.com", + github_token="test", + model_connections={ + "gateway": { + "backend": "openai-compatible", + "base_url": "https://gateway.example/v1", + "api_key_env": "GATEWAY_API_KEY", + "capabilities": ["tools"], + } + }, + model_default={"connection": "gateway", "model": "custom-model"}, + ) + + assert settings.llm_backend == "openai-compatible" + assert 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