init,llm gateway & import_analyse

app/providers/qwen.py

@@ -0,0 +1,87 @@
+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 QwenProvider(LLMProviderClient):
+    name = LLMProvider.QWEN.value
+    api_key_env = "QWEN_API_KEY"
+    base_url = (
+        "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation"
+    )
+
+    async def chat(
+        self, request: LLMRequest, client: httpx.AsyncClient
+    ) -> LLMResponse:
+        self.ensure_stream_supported(request.stream)
+
+        parameters = {
+            "temperature": request.temperature,
+            "top_p": request.top_p,
+        }
+        if request.max_tokens is not None:
+            parameters["max_output_tokens"] = request.max_tokens
+
+        # Strip None values from parameters
+        parameters = {k: v for k, v in parameters.items() if v is not None}
+
+        payload: Dict[str, Any] = {
+            "model": request.model,
+            "input": {"messages": [msg.model_dump() for msg in request.messages]},
+        }
+        if parameters:
+            payload["parameters"] = parameters
+
+        payload = self.merge_payload(payload, 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"Qwen request failed: {exc}") from exc
+
+        data: Dict[str, Any] = response.json()
+        choices = self._build_choices(data.get("output", {}))
+
+        return LLMResponse(
+            provider=LLMProvider.QWEN,
+            model=request.model,
+            choices=choices,
+            raw=data,
+        )
+
+    @staticmethod
+    def _build_choices(output: Dict[str, Any]) -> List[LLMChoice]:
+        choices_payload = output.get("choices", [])
+        if not choices_payload and output.get("text"):
+            return [
+                LLMChoice(
+                    index=0,
+                    message=LLMMessage(role="assistant", content=output["text"]),
+                )
+            ]
+
+        choices: List[LLMChoice] = []
+        for idx, choice in enumerate(choices_payload):
+            message_data = choice.get("message") or {}
+            message = LLMMessage(
+                role=message_data.get("role", "assistant"),
+                content=message_data.get("content", ""),
+            )
+            choices.append(LLMChoice(index=choice.get("index", idx), message=message))
+        if not choices:
+            choices.append(
+                LLMChoice(index=0, message=LLMMessage(role="assistant", content=""))
+            )
+        return choices