Update tools.py

tools.py

@@ -146,6 +146,13 @@ def build_graph(csv_file_path: str = "embeddings.csv"):
     chat_model = ChatHuggingFace(llm=llm)
     llm_with_tools = chat_model.bind_tools(tools=tools)
 
+    from sentence_transformers import SentenceTransformer
+
+    embedding_model = SentenceTransformer("all-MiniLM-L6-v2")
+    
+    def get_query_embedding(query: str) -> np.ndarray:
+        return embedding_model.encode(query)
+
 
 
     
@@ -156,14 +163,14 @@ def build_graph(csv_file_path: str = "embeddings.csv"):
         query_embedding = get_query_embedding(query)
         docs = vector_store.similarity_search(query_embedding, k=2)
         
-        content_blocks = [
+        context = "\n\n---\n\n".join(
             f"<Document metadata={doc.metadata}>\n{doc.page_content}\n</Document>"
             for doc in docs
-        ]
-        combined_doc_text = "\n\n---\n\n".join(content_blocks)
-        
-        system_prefix = SystemMessage(content=combined_doc_text)
-        return {"messages": [system_prefix] + state["messages"]}
+        )
+        combined_content = f"{system_prompt}\n\nHere are relevant documents:\n\n{context}"
+        system_message = SystemMessage(content=combined_content)
+        return {"messages": [system_message, last_human_msg]}
+
     
     # Node function for assistant
     def call_llm(state: MessagesState) -> MessagesState: