Refactor capi.py: replace scattered match/case with provider pattern

Consolidate endpoint-specific logic (catalog path, response parsing,
tool-call detection, headers) into an APIProvider dataclass with a
hostname-keyed registry. Adding a new endpoint is now a single registry
entry instead of changes across three match/case blocks.

- Remove AI_API_ENDPOINT_ENUM StrEnum and strenum dependency
- Only send Copilot-Integration-Id header to Copilot endpoints
- Accept optional endpoint parameter in public functions
- Drop fragile "gpt-" substring heuristic for OpenAI tool-call check
- Update tests to use new provider API

Author: anticomputer

src/seclab_taskflow_agent/agent.py

@@ -6,7 +6,6 @@
 import os
 from collections.abc import Callable
 from typing import Any
-from urllib.parse import urlparse
 
 from agents import (
     Agent,
@@ -26,7 +25,7 @@
 from dotenv import find_dotenv, load_dotenv
 from openai import AsyncOpenAI
 
-from .capi import AI_API_ENDPOINT_ENUM, COPILOT_INTEGRATION_ID, get_AI_endpoint, get_AI_token
+from .capi import get_AI_endpoint, get_AI_token, get_provider
 
 __all__ = [
     "DEFAULT_MODEL",
@@ -39,17 +38,8 @@
 load_dotenv(find_dotenv(usecwd=True))
 
 api_endpoint = get_AI_endpoint()
-match urlparse(api_endpoint).netloc:
-    case AI_API_ENDPOINT_ENUM.AI_API_GITHUBCOPILOT:
-        default_model = "gpt-4.1"
-    case AI_API_ENDPOINT_ENUM.AI_API_MODELS_GITHUB:
-        default_model = "openai/gpt-4.1"
-    case AI_API_ENDPOINT_ENUM.AI_API_OPENAI:
-        default_model = "gpt-4.1"
-    case _:
-        default_model = "please-set-default-model-via-env"
-
-DEFAULT_MODEL = os.getenv("COPILOT_DEFAULT_MODEL", default=default_model)
+_default_provider = get_provider(api_endpoint)
+DEFAULT_MODEL = os.getenv("COPILOT_DEFAULT_MODEL", default=_default_provider.default_model)
 
 
 class TaskRunHooks(RunHooks):
@@ -186,10 +176,12 @@ def __init__(
         else:
             resolved_token = get_AI_token()
 
+        # Only send provider-specific headers to matching endpoints
+        provider = get_provider(resolved_endpoint)
         client = AsyncOpenAI(
             base_url=resolved_endpoint,
             api_key=resolved_token,
-            default_headers={"Copilot-Integration-Id": COPILOT_INTEGRATION_ID},
+            default_headers=provider.extra_headers or None,
         )
         set_tracing_disabled(True)
         self.run_hooks = run_hooks or TaskRunHooks()

src/seclab_taskflow_agent/capi.py

@@ -1,53 +1,152 @@
 # SPDX-FileCopyrightText: GitHub, Inc.
 # SPDX-License-Identifier: MIT
 
-"""AI API endpoint and token management (CAPI integration)."""
+"""AI API endpoint and token management.
+
+Supports multiple API providers (GitHub Copilot, GitHub Models, OpenAI, and
+custom endpoints).  All provider-specific behaviour is captured in a single
+``APIProvider`` dataclass so that adding a new provider only requires one
+registry entry instead of changes scattered across multiple match/case blocks.
+"""
+
+from __future__ import annotations
 
 import json
 import logging
 import os
+from dataclasses import dataclass, field
+from types import MappingProxyType
+from typing import Any
 from urllib.parse import urlparse
 
 import httpx
-from strenum import StrEnum
 
 __all__ = [
-    "AI_API_ENDPOINT_ENUM",
     "COPILOT_INTEGRATION_ID",
+    "APIProvider",
     "get_AI_endpoint",
     "get_AI_token",
+    "get_provider",
     "list_capi_models",
     "list_tool_call_models",
     "supports_tool_calls",
 ]
 
+COPILOT_INTEGRATION_ID = "vscode-chat"
 
-# Enumeration of currently supported API endpoints.
-class AI_API_ENDPOINT_ENUM(StrEnum):
-    AI_API_MODELS_GITHUB = "models.github.ai"
-    AI_API_GITHUBCOPILOT = "api.githubcopilot.com"
-    AI_API_OPENAI = "api.openai.com"
 
-    def to_url(self) -> str:
-        """Convert the endpoint to its full URL."""
-        match self:
-            case AI_API_ENDPOINT_ENUM.AI_API_GITHUBCOPILOT:
-                return f"https://{self}"
-            case AI_API_ENDPOINT_ENUM.AI_API_MODELS_GITHUB:
-                return f"https://{self}/inference"
-            case AI_API_ENDPOINT_ENUM.AI_API_OPENAI:
-                return f"https://{self}/v1"
-            case _:
-                raise ValueError(f"Unsupported endpoint: {self}")
+# ---------------------------------------------------------------------------
+# Provider abstraction
+# ---------------------------------------------------------------------------
 
+@dataclass(frozen=True)
+class APIProvider:
+    """Encapsulates all endpoint-specific behaviour in one place."""
 
-COPILOT_INTEGRATION_ID = "vscode-chat"
+    name: str
+    base_url: str
+    models_catalog: str = "models"
+    default_model: str = "gpt-4.1"
+    extra_headers: dict[str, str] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        # Freeze mutable headers so singleton providers can't be mutated
+        object.__setattr__(self, "extra_headers", MappingProxyType(self.extra_headers))
+
+    # -- response parsing -----------------------------------------------------
+
+    def parse_models_list(self, body: Any) -> list[dict]:
+        """Extract the models list from a catalog response body."""
+        if isinstance(body, list):
+            return body
+        if isinstance(body, dict):
+            return body.get("data", [])
+        return []
+
+    # -- tool-call capability check -------------------------------------------
+
+    def check_tool_calls(self, _model: str, model_info: dict) -> bool:
+        """Return True if *model* supports tool calls according to its catalog entry."""
+        # Default: optimistically assume support when present in catalog
+        return bool(model_info)
 
 
-# you can also set https://api.githubcopilot.com if you prefer
-# but beware that your taskflows need to reference the correct model id
-# since different APIs use their own id schema, use -l with your desired
-# endpoint to retrieve the correct id names to use for your taskflow
+class _CopilotProvider(APIProvider):
+    """GitHub Copilot API (api.githubcopilot.com)."""
+
+    def check_tool_calls(self, _model: str, model_info: dict) -> bool:
+        return (
+            model_info
+            .get("capabilities", {})
+            .get("supports", {})
+            .get("tool_calls", False)
+        )
+
+
+class _GitHubModelsProvider(APIProvider):
+    """GitHub Models API (models.github.ai)."""
+
+    def parse_models_list(self, body: Any) -> list[dict]:
+        # Models API returns a bare list, not {"data": [...]}
+        if isinstance(body, list):
+            return body
+        return super().parse_models_list(body)
+
+    def check_tool_calls(self, _model: str, model_info: dict) -> bool:
+        return "tool-calling" in model_info.get("capabilities", [])
+
+
+class _OpenAIProvider(APIProvider):
+    """OpenAI API (api.openai.com).
+
+    The OpenAI /v1/models catalog does not expose capability metadata, so
+    we maintain a prefix allowlist of known chat-completion model families.
+    """
+
+    _CHAT_PREFIXES = ("gpt-3.5", "gpt-4", "o1", "o3", "o4", "chatgpt-")
+
+    def check_tool_calls(self, _model: str, model_info: dict) -> bool:
+        model_id = model_info.get("id", "").lower()
+        return any(model_id.startswith(p) for p in self._CHAT_PREFIXES)
+# ---------------------------------------------------------------------------
+# Provider registry — add new providers here
+# ---------------------------------------------------------------------------
+
+_PROVIDERS: dict[str, APIProvider] = {
+    "api.githubcopilot.com": _CopilotProvider(
+        name="copilot",
+        base_url="https://api.githubcopilot.com",
+        default_model="gpt-4.1",
+        extra_headers={"Copilot-Integration-Id": COPILOT_INTEGRATION_ID},
+    ),
+    "models.github.ai": _GitHubModelsProvider(
+        name="github-models",
+        base_url="https://models.github.ai/inference",
+        models_catalog="catalog/models",
+        default_model="openai/gpt-4.1",
+    ),
+    "api.openai.com": _OpenAIProvider(
+        name="openai",
+        base_url="https://api.openai.com/v1",
+        default_model="gpt-4.1",
+    ),
+}
+
+def get_provider(endpoint: str | None = None) -> APIProvider:
+    """Return the ``APIProvider`` for the given (or configured) endpoint URL."""
+    url = endpoint or get_AI_endpoint()
+    netloc = urlparse(url).netloc
+    provider = _PROVIDERS.get(netloc)
+    if provider is not None:
+        return provider
+    # Unknown endpoint — return a generic provider with the given base URL
+    return APIProvider(name="custom", base_url=url)
+
+
+# ---------------------------------------------------------------------------
+# Endpoint / token helpers
+# ---------------------------------------------------------------------------
+
 def get_AI_endpoint() -> str:
     """Return the configured AI API endpoint URL."""
     return os.getenv("AI_API_ENDPOINT", default="https://models.github.ai/inference")
@@ -64,82 +163,54 @@ def get_AI_token() -> str:
     raise RuntimeError("AI_API_TOKEN environment variable is not set.")
 
 
-# assume we are >= python 3.9 for our type hints
-def list_capi_models(token: str) -> dict[str, dict]:
-    """Retrieve a dictionary of available CAPI models"""
-    models = {}
+# ---------------------------------------------------------------------------
+# Model catalog
+# ---------------------------------------------------------------------------
+
+def list_capi_models(token: str, endpoint: str | None = None) -> dict[str, dict]:
+    """Retrieve available models from the configured API endpoint.
+
+    Args:
+        token: Bearer token for authentication.
+        endpoint: Optional endpoint URL override (defaults to env config).
+    """
+    provider = get_provider(endpoint)
+    base = provider.base_url
+    models: dict[str, dict] = {}
     try:
-        api_endpoint = get_AI_endpoint()
-        netloc = urlparse(api_endpoint).netloc
-        match netloc:
-            case AI_API_ENDPOINT_ENUM.AI_API_GITHUBCOPILOT:
-                models_catalog = "models"
-            case AI_API_ENDPOINT_ENUM.AI_API_MODELS_GITHUB:
-                models_catalog = "catalog/models"
-            case AI_API_ENDPOINT_ENUM.AI_API_OPENAI:
-                models_catalog = "models"
-            case _:
-                # Unknown endpoint — try the OpenAI-style models catalog
-                models_catalog = "models"
+        headers = {
+            "Accept": "application/json",
+            "Authorization": f"Bearer {token}",
+            **provider.extra_headers,
+        }
         r = httpx.get(
-            httpx.URL(api_endpoint).join(models_catalog),
-            headers={
-                "Accept": "application/json",
-                "Authorization": f"Bearer {token}",
-                "Copilot-Integration-Id": COPILOT_INTEGRATION_ID,
-            },
+            httpx.URL(base).join(provider.models_catalog),
+            headers=headers,
         )
         r.raise_for_status()
-        # CAPI vs Models API
-        match netloc:
-            case AI_API_ENDPOINT_ENUM.AI_API_GITHUBCOPILOT:
-                models_list = r.json().get("data", [])
-            case AI_API_ENDPOINT_ENUM.AI_API_MODELS_GITHUB:
-                models_list = r.json()
-            case AI_API_ENDPOINT_ENUM.AI_API_OPENAI:
-                models_list = r.json().get("data", [])
-            case _:
-                # Unknown endpoint — try common response shapes
-                body = r.json()
-                if isinstance(body, dict):
-                    models_list = body.get("data", [])
-                elif isinstance(body, list):
-                    models_list = body
-                else:
-                    models_list = []
-        for model in models_list:
+        for model in provider.parse_models_list(r.json()):
             models[model.get("id")] = dict(model)
-    except httpx.RequestError:
-        logging.exception("Request error")
-    except json.JSONDecodeError:
-        logging.exception("JSON error")
-    except httpx.HTTPStatusError:
-        logging.exception("HTTP error")
+    except (httpx.RequestError, httpx.HTTPStatusError, json.JSONDecodeError):
+        logging.exception("Failed to list models from %s", base)
     return models
 
 
-def supports_tool_calls(model: str, models: dict[str, dict]) -> bool:
-    """Check whether the given model supports tool calls."""
-    api_endpoint = get_AI_endpoint()
-    netloc = urlparse(api_endpoint).netloc
-    match netloc:
-        case AI_API_ENDPOINT_ENUM.AI_API_GITHUBCOPILOT:
-            return models.get(model, {}).get("capabilities", {}).get("supports", {}).get("tool_calls", False)
-        case AI_API_ENDPOINT_ENUM.AI_API_MODELS_GITHUB:
-            return "tool-calling" in models.get(model, {}).get("capabilities", [])
-        case AI_API_ENDPOINT_ENUM.AI_API_OPENAI:
-            return "gpt-" in model.lower()
-        case _:
-            # Unknown endpoint — optimistically assume tool-call support
-            # if the model is present in the catalog.
-            return model in models
-
-
-def list_tool_call_models(token: str) -> dict[str, dict]:
+def supports_tool_calls(
+    model: str,
+    models: dict[str, dict],
+    endpoint: str | None = None,
+) -> bool:
+    """Check whether *model* supports tool calls."""
+    provider = get_provider(endpoint)
+    return provider.check_tool_calls(model, models.get(model, {}))
+
+
+def list_tool_call_models(token: str, endpoint: str | None = None) -> dict[str, dict]:
     """Return only models that support tool calls."""
-    models = list_capi_models(token)
-    tool_models: dict[str, dict] = {}
-    for model in models:
-        if supports_tool_calls(model, models) is True:
-            tool_models[model] = models[model]
-    return tool_models
+    models = list_capi_models(token, endpoint)
+    provider = get_provider(endpoint)
+    return {
+        mid: info
+        for mid, info in models.items()
+        if provider.check_tool_calls(mid, info)
+    }