Update app.py

app.py

@@ -42,53 +42,22 @@ def get_vector_store(chunks):
 
 # Function to get conversational chain
 def get_conversational_chain():
-    from langchain.prompts import PromptTemplate
-
-    # Map prompt
-    map_prompt = PromptTemplate(
-        template="""
-    Answer the following question based on the given context. If the answer isn't in the context, please say, "Answer is not available in the context." Do not provide information not included in the context.
-
-    Context:
-    {context}
-
-    Question:
-    {question}
-
+    prompt_template = """
+    Answer the question as detailed as possible from the provided context. 
+    If the answer is not in the provided context, just say, "answer is not available in the context".
+    Don't provide the wrong answer.\n\n
+    Context:\n {context}\n
+    Question:\n {question}\n
     Answer:
-    """,
-        input_variables=["context", "question"]
-    )
-
-    # Combine prompt
-    combine_prompt = PromptTemplate(
-        template="""
-    You are provided with several answers to a question from different parts of a document. Your task is to combine these answers into a single, coherent, and comprehensive response. If the answer isn't available, state "Answer is not available in the context."
-
-    Answers:
-    {summaries}
-
-    Question:
-    {question}
-
-    Final Answer:
-    """,
-        input_variables=["summaries", "question"]
-    )
-
+    """
     try:
         model = ChatGoogleGenerativeAI(model="gemini-pro", client=genai, temperature=0.3)
-        chain = load_qa_chain(
-            llm=model,
-            chain_type="map_reduce",
-            question_prompt=map_prompt,
-            combine_prompt=combine_prompt
-        )
+        prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+        chain = load_qa_chain(llm=model, chain_type="stuff", prompt=prompt)
         return chain
     except (GoogleAPIError, InvalidArgument):
         raise RuntimeError("Error creating conversational chain. Please try again in a minute.")
 
-
 # Function to clear chat history
 def clear_chat_history():
     st.session_state.messages = [
@@ -99,16 +68,13 @@ def user_input(user_question):
     try:
         embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")  # type: ignore
         new_db = FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
-        docs = new_db.similarity_search(user_question, k=4)  # Adjust k if needed
+        docs = new_db.similarity_search(user_question, k=4)
         chain = get_conversational_chain()
         response = chain({"input_documents": docs, "question": user_question}, return_only_outputs=True)
         return response
     except (GoogleAPIError, InvalidArgument):
         raise RuntimeError("لطفا پس از چند لحظه دوباره امتحان کنید ")
 
-
-
-
 # Main function to run the Streamlit app
 def main():
     st.set_page_config(