Update app.py

app.py

@@ -29,38 +29,47 @@ if uploaded_file:
     api_key = st.text_input("Enter your MistralAI API Key", type="password")
     
     if api_key:
-        # Define the embedding model
-        embeddings = MistralAIEmbeddings(model="mistral-embed", mistral_api_key=api_key)
+        try:
+            # Define the embedding model
+            embeddings = MistralAIEmbeddings(model="mistral-embed", mistral_api_key=api_key)
+            
+            # Create the vector store
+            vector = FAISS.from_documents(documents, embeddings)
+            
+            # Define a retriever interface
+            retriever = vector.as_retriever()
+            
+            # Define LLM
+            model = ChatMistralAI(mistral_api_key=api_key)
+            
+            # Define prompt template
+            prompt = ChatPromptTemplate.from_template("""Answer the following question based only on the provided context:
+            
+            <context>
+            {context}
+            </context>
+            
+            Question: {input}""")
+            
+            # Create a retrieval chain to answer questions
+            document_chain = create_stuff_documents_chain(model, prompt)
+            retrieval_chain = create_retrieval_chain(retriever, document_chain)
+            
+            # User prompt input
+            user_prompt = st.text_input("Enter your question")
+            
+            if user_prompt:
+                with st.spinner("Processing..."):
+                    response = retrieval_chain.invoke({"input": user_prompt})
+                    if "answer" in response:
+                        st.write(response["answer"])
+                    else:
+                        st.write("No answer found.")
         
-        # Create the vector store
-        vector = FAISS.from_documents(documents, embeddings)
-        
-        # Define a retriever interface
-        retriever = vector.as_retriever()
-        
-        # Define LLM
-        model = ChatMistralAI(mistral_api_key=api_key)
-        
-        # Define prompt template
-        prompt = ChatPromptTemplate.from_template("""Answer the following question based only on the provided context:
-        
-        <context>
-        {context}
-        </context>
-        
-        Question: {input}""")
-        
-        # Create a retrieval chain to answer questions
-        document_chain = create_stuff_documents_chain(model, prompt)
-        retrieval_chain = create_retrieval_chain(retriever, document_chain)
-        
-        # User prompt input
-        user_prompt = st.text_input("Enter your question")
-        
-        if user_prompt:
-            with st.spinner("Processing..."):
-                response = retrieval_chain.invoke({"input": user_prompt})
-                st.write(response["answer"])
+        except Exception as e:
+            st.error(f"Error: {e}")
+            # Print or log detailed error information for debugging
+            st.exception(e)
 
 else:
-    st.write("Please upload a PDF file to get started...")
+    st.write("Please upload a PDF file to get started.")