Update document_chat.py

document_chat.py

@@ -8,7 +8,7 @@ from langchain.memory import ConversationBufferMemory
 from langchain.llms import HuggingFaceHub
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-from langchain.chains.combine_documents import DocumentCompressor
+from langchain.chains.combine_documents import StuffDocumentsChain  # Corrected import
 
 # Constants
 CHROMA_DB_PATH = "chroma_db"
@@ -50,8 +50,8 @@ def process_query_with_memory(query, chat_history=[]):
     question_generator_template = "Generate a question based on the user's request: {query}"
     question_generator = LLMChain(llm=llm, prompt=PromptTemplate(template=question_generator_template, input_variables=["query"]))
 
-    # Document combiner (example: just concatenate documents)
-    combine_docs_chain = DocumentCompressor(combine_fn=lambda docs: " ".join([doc.page_content for doc in docs]))
+    # Use StuffDocumentsChain to combine the retrieved documents
+    combine_docs_chain = StuffDocumentsChain(llm=llm)  # Corrected use of StuffDocumentsChain
 
     # Create a ConversationalRetrievalChain with the loaded model and retriever
     qa_chain = ConversationalRetrievalChain(
@@ -65,4 +65,3 @@ def process_query_with_memory(query, chat_history=[]):
     # Run the query with the current chat history and return the response
     response = qa_chain.run({"question": query, "chat_history": chat_history})
     return response
-