feat: add cold start

app.py

@@ -48,6 +48,7 @@ def greet_json():
 
 @app.post("/v1/generateTripPlan", response_model=PlanResponse)
 def generate_trip_plan(request: PlanRequest):
+    data_importer.coldStartDatabase()
     try:
         trip_plan = asyncio.run(agent.query_with_rag(request))
         return PlanResponse(tripOverview=trip_plan.tripOverview,

class_mod/rest_qdrant.py

@@ -19,7 +19,7 @@ class RestQdrantClient:
         r = self.session.get(f"{self.url}/collections/{collection_name}", timeout=self.timeout)
         r.raise_for_status()
         return r.json()
-    def search(self, collection_name, query_vector, limit=10, with_payload=True):
+    def search(self, collection_name, query_vector, limit=10, with_payload=True,timeout=1):
         payload = {
             "vector": query_vector,
             "limit": limit,
@@ -28,7 +28,7 @@ class RestQdrantClient:
         r = self.session.post(
             f"{self.url}/collections/{collection_name}/points/search",
             json=payload,
-            timeout=self.timeout
+            timeout=timeout
         )
         r.raise_for_status()
         return r.json()

data_importer.py

@@ -57,8 +57,8 @@ class DataImporter:
     def insert_text(self, text: str, metadata: Optional[Dict] = None, custom_id: Optional[str] = None) -> str:
         point_id = custom_id or str(uuid.uuid4())
         embedding = self.encode_text(text)[0]
-        
         payload = {"text": text}
+        
         if metadata:
             payload.update(metadata)
         
@@ -101,7 +101,7 @@ class DataImporter:
             print(f"Error extracting from YouTube: {e}")
             return None
     
-    def search_similar(self, query: str, limit: int = 5) -> List[Dict]:
+    def search_similar(self, query: str, limit: int = 1) -> List[Dict]:
         """Search with Qdrant availability check - always returns a list"""
         if not self.qdrant_available or not self.client:
             print("Warning: Qdrant not available, returning empty results")
@@ -113,7 +113,8 @@ class DataImporter:
             results = self.client.search(
                 collection_name=self.collection_name,
                 query_vector=query_embedding,
-                limit=limit
+                limit=limit,
+                timeout=15
             )
             print(f"Search results: {results}")
             return [
@@ -128,3 +129,19 @@ class DataImporter:
         except Exception as e:
             print(f"Error searching: {e}")
             raise ValueError(f"Search failed: {str(e)}")
+
+    def coldStartDatabase(self):
+        coldstart_texts = "I want to go to Chiang Mai"
+        try:
+            query_embedding = self.encode_text(coldstart_texts)[0]
+            results = self.client.search(
+                collection_name=self.collection_name,
+                query_vector=query_embedding,
+                limit=1,
+                timeout=1
+            )
+            print(f"Cold start results: {results}")
+        except Exception as e:
+            print(f"finish cold start, with error: {e}")
+
+        

utils/llm_caller.py

@@ -96,6 +96,7 @@ class LLMCaller:
                 query_vector=query_embedding,
                 limit=top_k,
                 with_payload=True,
+                timeout=15
             )
             
             # 4. Convert search results to RetrievedItem format