Sameer360/Document_based_chatbot

1### retriever.py ###2from langchain.memory import ConversationBufferMemory3 4 5def retrieve_context(query, db, memory):6    # print("Debug: retrieve_context function started")7    retriever = db.as_retriever(8        search_type="similarity", search_kwargs={"k": 7}9    )10    relevant_docs = retriever.invoke(query)11    # print(f"Debug: Number of relevant documents found: {len(relevant_docs)}") # number of docs12 13    # for i, doc in enumerate(relevant_docs):14        # print(f"Debug: Relevant document {i + 1}:")15        # print(f"Debug:   Source: {doc.metadata.get('source', 'Unknown')}") # source of the doc16        # print(f"Debug:   Content (first 100 chars): {doc.page_content[:100]}...") # content of the doc17    conversation_history = memory.load_memory_variables({})["history"]18 19    combined_input = (20        f"Conversation History: {conversation_history}\n"21        f"User Query: {query}\n"22        "Relevant Documents:\n"23        + "\n".join(doc.page_content for doc in relevant_docs if doc.page_content)24        + "\nPlease provide a concise answer based only on the provided documents. "25        "If the answer is not found in the documents, respond with 'I'm not sure'."26    )27 28    memory.save_context({"input": query}, {"output": "Retrieving relevant context..."})29 30    # Get the sources31    sources = []32    for doc in relevant_docs:33        source = doc.metadata.get("source", "Unknown Source")34        if source not in sources:35            sources.append(source)36    # print(f"Debug: sources found : {sources}") # source found37    # print("Debug: retrieve_context function ended")38    return combined_input, ", ".join(sources)39