init,llm gateway & import_analyse

app/providers/openai.py

@@ -0,0 +1,66 @@
+from __future__ import annotations
+
+from typing import Any, Dict, List
+
+import httpx
+
+from app.exceptions import ProviderAPICallError
+from app.models import LLMChoice, LLMMessage, LLMProvider, LLMRequest, LLMResponse
+from app.providers.base import LLMProviderClient
+
+
+class OpenAIProvider(LLMProviderClient):
+    name = LLMProvider.OPENAI.value
+    api_key_env = "OPENAI_API_KEY"
+    supports_stream = True
+    base_url = "https://api.openai.com/v1/chat/completions"
+
+    async def chat(
+        self, request: LLMRequest, client: httpx.AsyncClient
+    ) -> LLMResponse:
+        self.ensure_stream_supported(request.stream)
+
+        payload = self.merge_payload(
+            {
+                "model": request.model,
+                "messages": [msg.model_dump() for msg in request.messages],
+                "temperature": request.temperature,
+                "top_p": request.top_p,
+                "max_tokens": request.max_tokens,
+                "stream": request.stream,
+            },
+            request.extra_params,
+        )
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        try:
+            response = await client.post(self.base_url, json=payload, headers=headers)
+            response.raise_for_status()
+        except httpx.HTTPError as exc:
+            raise ProviderAPICallError(f"OpenAI request failed: {exc}") from exc
+
+        data: Dict[str, Any] = response.json()
+        choices = self._build_choices(data.get("choices", []))
+
+        return LLMResponse(
+            provider=LLMProvider.OPENAI,
+            model=data.get("model", request.model),
+            choices=choices,
+            raw=data,
+        )
+
+    @staticmethod
+    def _build_choices(choices: List[dict[str, Any]]) -> List[LLMChoice]:
+        built: List[LLMChoice] = []
+        for choice in choices:
+            message_data = choice.get("message") or {}
+            message = LLMMessage(
+                role=message_data.get("role", "assistant"),  # fallback to assistant
+                content=message_data.get("content", ""),
+            )
+            built.append(LLMChoice(index=choice.get("index", len(built)), message=message))
+        return built