Update app.py

app.py

@@ -684,7 +684,7 @@ def answer_template(language="english"):
 
 chain = ConversationalRetrievalChain.from_llm(
     condense_question_prompt=standalone_question_prompt,
-    combine_docs_chain_kwargs={'prompt': answer_prompt},
+    combine_docs_chain_kwargs={'prompt': ChatPromptTemplate.from_template(answer_template())},
     condense_question_llm=instantiate_LLM(
         LLM_provider="Google",api_key=google_api_key,temperature=0.1,
         model_name="gemini-pro"),
@@ -781,8 +781,8 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
 
     global prompt_template_name
     prompt_template_name = prompt_template
-    print(prompt_template)  # prints who is responding if I move to multiple experts
-    print(prompt_templates[prompt_template])
+    #print(prompt_template)  # prints who is responding if I move to multiple experts
+    #print(prompt_templates[prompt_template])
     
     
 
@@ -799,15 +799,21 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
     #state.append(completion.copy())
     
     completion = { "content": completion }
-    print("completion text")
+    
     
     for document in completion['content']['source_documents']:
+
+
+          
+        print("Prompt/question:", prompt)
         page_content = document.page_content  # Use dot notation to access an attribute
         print("Page_content:", page_content)
         metadata = document.metadata  # Use dot notation to access an attribute
         print("Metadata:", metadata)
         similarity_score = document.state['query_similarity_score']  
         print("Similarity_score:", similarity_score)
+        answer = completion['content']['answer']
+        print("Answer:", answer)
         print("")