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faiss_rag_enterprise
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hailin 2025-05-11 00:59:49 +08:00
parent bca56cc457
commit f992ca30c6
1 changed files with 9 additions and 5 deletions
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14
app/api/search.py
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@ -3,7 +3,7 @@ from pydantic import BaseModel
from app.core.embedding import embedder from app.core.embedding import embedder
from app.core.config import settings from app.core.config import settings
from llama_index.vector_stores.faiss import FaissVectorStore from llama_index.vector_stores.faiss import FaissVectorStore
from llama_index import VectorStoreIndex, ServiceContext from llama_index import VectorStoreIndex, ServiceContext, StorageContext
import os import os
import logging import logging
import faiss # 引入faiss import faiss # 引入faiss
@ -44,15 +44,19 @@ def search_docs(request: QueryRequest, user_id: str = Query(..., description="
vector_store = FaissVectorStore(faiss_index=faiss_index) vector_store = FaissVectorStore(faiss_index=faiss_index)
logger.info("FaissVectorStore created successfully.") logger.info("FaissVectorStore created successfully.")
# 创建 StorageContext 实例（确保同时加载文本和向量）
storage_context = StorageContext.from_defaults(persist_dir=index_path, vector_store=vector_store)
logger.info("Storage context created successfully.")
# 创建 ServiceContext 实例 # 创建 ServiceContext 实例
service_context = ServiceContext.from_defaults(embed_model=embedder, llm=None) service_context = ServiceContext.from_defaults(embed_model=embedder, llm=None)
logger.info("Service context created successfully.") logger.info("Service context created successfully.")
# 创建 VectorStoreIndex # 创建 VectorStoreIndex 并加载文本与向量
index = VectorStoreIndex.from_vector_store(vector_store, service_context=service_context) index = VectorStoreIndex.from_storage_context(storage_context)
logger.info("VectorStoreIndex created successfully.") logger.info("VectorStoreIndex created successfully.")
# 检索结果（真实文本） # 检索结果（包含文本）
retriever = index.as_retriever(similarity_top_k=settings.TOP_K) retriever = index.as_retriever(similarity_top_k=settings.TOP_K)
logger.info(f"Retrieving top {settings.TOP_K} results for query: {request.query}") logger.info(f"Retrieving top {settings.TOP_K} results for query: {request.query}")
nodes = retriever.retrieve(request.query) nodes = retriever.retrieve(request.query)
@ -62,7 +66,7 @@ def search_docs(request: QueryRequest, user_id: str = Query(..., description="
"user_id": user_id, "user_id": user_id,
"query": request.query, "query": request.query,
"results": [ "results": [
{"score": float(node.score or 0), "text": node.get_content()} {"score": float(node.score or 0), "text": node.get_content()} # 确保从 Node 中获取文本
for node in nodes for node in nodes
] ]
} }