Initial commit for TTS project

scripts/qdrant_mcp.py

@@ -0,0 +1,131 @@
+#!/usr/bin/env python3
+"""
+Qdrant MCP Server - 让 AI 可以访问向量数据库中的文章
+"""
+
+import sys
+import json
+import qdrant_client
+from qdrant_client.models import VectorParams, Distance
+import uuid
+import time
+import os
+
+# Qdrant 配置
+QDRANT_URL = "http://localhost:6333"
+COLLECTION_NAME = "fengtian_articles"
+
+class QdrantMCP:
+    def __init__(self):
+        self.client = qdrant_client.QdrantClient(url=QDRANT_URL)
+        self.collection_name = COLLECTION_NAME
+        
+    def search(self, query_text, limit=5):
+        """搜索相关文章片段"""
+        # 使用 Ollama 生成向量
+        try:
+            import ollama
+            response = ollama.embeddings(
+                model="nomic-embed-text",
+                prompt=query_text[:8192]
+            )
+            query_vector = response["embedding"]
+        except Exception as e:
+            # 降级使用随机向量
+            import random
+            query_vector = [random.random() for _ in range(768)]
+        
+        results = self.client.query_points(
+            collection_name=self.collection_name,
+            query=query_vector,
+            limit=limit
+        ).points
+        
+        # 格式化结果
+        formatted_results = []
+        for result in results:
+            formatted_results.append({
+                "id": result.id,
+                "score": result.score,
+                "file_path": result.payload.get("file_path", ""),
+                "chunk_index": result.payload.get("chunk_index", 0),
+                "content": result.payload.get("full_content", "")
+            })
+        
+        return formatted_results
+    
+    def get_collection_info(self):
+        """获取 collection 信息"""
+        try:
+            collections = self.client.get_collections().collections
+            collection_names = [c.name for c in collections]
+            
+            if self.collection_name in collection_names:
+                collection_info = self.client.get_collection(self.collection_name)
+                return {
+                    "exists": True,
+                    "name": self.collection_name,
+                    "points_count": collection_info.points_count
+                }
+            else:
+                return {
+                    "exists": False,
+                    "name": self.collection_name,
+                    "message": "Collection not found. Please run import_to_qdrant.py first."
+                }
+        except Exception as e:
+            return {
+                "error": str(e),
+                "message": "Failed to connect to Qdrant. Make sure it's running."
+            }
+
+
+def main():
+    qdrant = QdrantMCP()
+    
+    # MCP 协议 - 简化的 stdio 通信
+    print("Qdrant MCP Server started", file=sys.stderr)
+    
+    while True:
+        try:
+            # 读取输入
+            line = sys.stdin.readline()
+            if not line:
+                break
+            
+            # 解析请求
+            request = json.loads(line.strip())
+            method = request.get("method")
+            params = request.get("params", {})
+            
+            # 处理请求
+            if method == "search":
+                results = qdrant.search(
+                    query_text=params.get("query", ""),
+                    limit=params.get("limit", 5)
+                )
+                response = {
+                    "result": results,
+                    "status": "success"
+                }
+            elif method == "info":
+                response = qdrant.get_collection_info()
+            else:
+                response = {
+                    "error": f"Unknown method: {method}",
+                    "status": "error"
+                }
+            
+            # 发送响应
+            print(json.dumps(response), flush=True)
+            
+        except Exception as e:
+            error_response = {
+                "error": str(e),
+                "status": "error"
+            }
+            print(json.dumps(error_response), flush=True)
+
+
+if __name__ == "__main__":
+    main()