feat: Add base project structure with API and web components

api/app/core/models/rerank.py

@@ -0,0 +1,80 @@
+
+from typing import Any, Dict, List, Optional, Sequence, Type, Union
+from copy import deepcopy
+from urllib.parse import urlparse
+from langchain_core.documents import BaseDocumentCompressor, Document
+from langchain_core.runnables import RunnableSerializable
+from langchain_core.callbacks import Callbacks
+from app.core.models.base import RedBearModelConfig, get_provider_rerank_class, RedBearModelFactory
+from app.models import ModelProvider
+
+class RedBearRerank(BaseDocumentCompressor):
+    """ Rerank → 作为 Runnable 插入任意 LCEL 链"""
+    def __init__(self, config: RedBearModelConfig):
+        self._model = self._create_model(config)
+        self._config = config
+
+    def _create_model(self, config: RedBearModelConfig):
+        """创建内部模型实例"""
+        model_class = get_provider_rerank_class(config.provider)
+        model_params = RedBearModelFactory.get_rerank_model_params(config)
+        print(model_params)
+        return model_class(**model_params)
+
+    def compress_documents(
+        self,
+        documents: Sequence[Document],
+        query: str,
+        callbacks: Optional[Callbacks] = None,
+    ) -> Sequence[Document]:
+        """
+        Compress documents using Jina's Rerank API.
+
+        Args:
+            documents: A sequence of documents to compress.
+            query: The query to use for compressing the documents.
+            callbacks: Callbacks to run during the compression process.
+
+        Returns:
+            A sequence of compressed documents.
+        """
+        compressed = []
+        for res in self.rerank(documents, query):
+            doc = documents[res["index"]]
+            doc_copy = Document(doc.page_content, metadata=deepcopy(doc.metadata))
+            doc_copy.metadata["relevance_score"] = res["relevance_score"]
+            compressed.append(doc_copy)
+        return compressed
+
+
+    def rerank(
+        self,
+        documents: Sequence[Union[str, Document, dict]],
+        query: str,
+        *,
+        top_n: Optional[int] = -1,
+    ) -> List[Dict[str, Any]]:   
+        provider = self._config.provider.lower()      
+        if provider in [ModelProvider.XINFERENCE, ModelProvider.GPUSTACK] :
+            import langchain_community.document_compressors.jina_rerank as jina_mod
+            # 规范化：如果不以 /v1/rerank 结尾，则补齐；若已以 /v1 结尾，则补 /rerank
+            def _normalize_jina_base(base_url: Optional[str]) -> Optional[str]:
+                if not base_url:
+                    return None
+                url = base_url.rstrip('/')
+                if url.endswith("/v1/rerank"):
+                    return url
+                if url.endswith("/v1"):
+                    return url + "/rerank"
+                return url + "/v1/rerank"
+
+            jina_base = _normalize_jina_base(self._config.base_url)
+            if jina_base:
+                # 设置完整的 rerank 端点，例如 http://host:port/v1/rerank
+                jina_mod.JINA_API_URL = jina_base
+            from langchain_community.document_compressors import JinaRerank
+            model_instance : JinaRerank = self._model
+            return model_instance.rerank(documents = documents, query = query, top_n=top_n)     
+        else:
+            raise ValueError(f"不支持的模型提供商: {provider}")
+