Fix SSE route dependency and align architecture docs

backend/app/infrastructure/embedding/openai_compatible_embedding_provider.py

@@ -0,0 +1,59 @@
+"""Implement infrastructure support for openai compatible embedding provider."""
+
+from __future__ import annotations
+
+import os
+
+import httpx
+
+from app.config.settings import settings
+from app.domain.retrieval import EmbeddingProvider
+# Keep adapter behavior explicit so integration details remain easy to audit.
+
+
+
+class OpenAICompatibleEmbeddingProvider(EmbeddingProvider):
+    """Provide the Open A I Compatible Embedding Provider provider."""
+    def __init__(self) -> None:
+        """Initialize the Open A I Compatible Embedding Provider instance."""
+        self.base_url = settings.embedding_base_url.rstrip("/")
+        self.api_key = (
+            settings.embedding_api_key
+            or os.getenv("OPENAI_API_KEY", "")
+            or os.getenv("QWEN_API_KEY", "")
+            or os.getenv("DEEPSEEK_API_KEY", "")
+        )
+        self.model = settings.embedding_model
+        self.timeout = settings.embedding_timeout_seconds
+        self.dimension = settings.embedding_dim
+
+    def _request(self, texts: list[str]) -> list[list[float]]:
+        """Handle request for this module for the Open A I Compatible Embedding Provider instance."""
+        if not self.api_key:
+            raise ValueError("缺少 EMBEDDING_API_KEY / OPENAI_API_KEY")
+        response = httpx.post(
+            f"{self.base_url}/embeddings",
+            headers={
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json",
+            },
+            json={"model": self.model, "input": texts},
+            timeout=self.timeout,
+        )
+        response.raise_for_status()
+        data = response.json()
+        vectors = [item["embedding"] for item in sorted(data.get("data", []), key=lambda item: item["index"])]
+        if any(len(vector) != self.dimension for vector in vectors):
+            raise ValueError(f"embedding 维度不匹配，期望 {self.dimension}")
+        return vectors
+
+    def embed_texts(self, texts: list[str]) -> list[list[float]]:
+        """Embed texts for the Open A I Compatible Embedding Provider instance."""
+        if not texts:
+            return []
+        return self._request(texts)
+
+    def embed_query(self, text: str) -> list[float]:
+        """Embed query for the Open A I Compatible Embedding Provider instance."""
+        vectors = self._request([text])
+        return vectors[0]