Update app.py

app.py

@@ -1107,7 +1107,40 @@ def multi_agent_with_langgraph(query: str, file=None) -> str:
     compiled_graph = graph.compile()
     result = graph.run(query)
     return result
+from langgraph.graph import StateGraph
+from langchain_core.runnables import RunnableLambda
+from langchain_core.runnables import RunnableConfig
+
+def build_langgraph_doc_qa_chain(llm, retriever, memory, prompt):
+    def retrieve_step(state):
+        docs = state['retriever'].get_relevant_documents(state['query'])
+        return {"docs": docs, **state}
+
+    def answer_step(state):
+        from langchain_core.prompts import PromptTemplate
+        from langchain.chains.combine_documents.stuff import StuffDocumentsChain
+        doc_prompt = PromptTemplate(input_variables=["page_content"], template="{page_content}")
+        doc_chain = StuffDocumentsChain(llm=state['llm'], prompt=state['prompt'])
+        answer = doc_chain.run(state['docs'])
+        return {"answer": answer, **state}
+
+    builder = StateGraph()
+    builder.add_node("Retrieve", retrieve_step)
+    builder.add_node("Answer", answer_step)
+    builder.set_entry_point("Retrieve")
+    builder.add_edge("Retrieve", "Answer")
+    builder.set_finish_point("Answer")
+    compiled = builder.compile()
+
+    def run(query):
+        return compiled.invoke({
+            "query": query,
+            "retriever": retriever,
+            "llm": llm,
+            "prompt": prompt
+        })
 
+    return run
 
 @traceable(name="Multi-Agent Chat")
 def multi_agent_chat_advanced(query: str, file=None) -> str:
@@ -1188,7 +1221,9 @@ def multi_agent_chat_advanced(query: str, file=None) -> str:
                 # If using QA Chain is appropriate
                 if use_file_chain:
                     try:
-                        answer = session_qa_chain.run(query)
+                        #answer = session_qa_chain.run(query)
+                        session_graph_chain = build_langgraph_doc_qa_chain(llm_gpt4, session_retriever, memory, custom_prompt)
+                        answer = session_graph_chain(query)["answer"]
 
                         # ✅ DeepEval 評估僅在 Tab1 文件 QA 的情況下觸發
                         if SHOW_EVAL:
@@ -1318,7 +1353,7 @@ Feel free to upload a document and ask related questions, or just type a questio
 demo = gr.TabbedInterface(
     interface_list=[
         gr.Interface(
-            fn=multi_agent_with_langgraph,
+            fn=multi_agent_chat_advanced,
             inputs=[
                 gr.Textbox(label="Enter your query"),
                 gr.File(label="Upload file (CSV, PDF, TXT, DOCX)", file_count="single")