updated prompt

app.py

@@ -46,20 +46,30 @@ def get_results(embeddings_model,input,df,num_of_results) -> pd.DataFrame:
 def get_llm_results(query,chat,results):   
 
     prompt_template = PromptTemplate.from_template(
-        """
+   """
+    your misssion is to rank the given answers based on their relevance to the given question.
+    Provide a relevancy score between 0 (not relevant) and 1 (highly relevant) for each possible answer.
+    the results should be in  the following JSON format: "answer": "score", "answer": "score" while answer is the possible answer's text and score is the relevancy score.
+    
     the question is: {query}
+
     the possible answers are:
     {answers}
 
     """   )
 
     messages = [
-        SystemMessage(content="You're a helpful assistant. given a question, filter and sort the possible answers to the given question by relevancy, drop the irrelevant answers and return the results in the following JSON format (scores are between 0 and 1): {\"answer\": \"score\", \"answer\": \"score\"}. "),
+        SystemMessage(content="""
+                      You're a helpful assistant.
+                      Return a JSON formatted string.
+                      """),
         HumanMessage(content=prompt_template.format(query=query, answers=str.join('\n', results['text'].head(10).tolist()))),
     ]
 
     response =  chat.invoke(messages)
     llm_results_df = pd.read_json(response.content, orient='index')
+    llm_results_df.rename(columns={0: 'score'}, inplace=True)
+    llm_results_df.sort_values(by='score', ascending=False, inplace=True)
     return llm_results_df
 
 
@@ -88,9 +98,13 @@ def run():
         results = get_results(embeddings_model,user_input,df,num_of_results)  
 
         if use_llm:
-            chat = get_chat_api(openAikey)
-            llm_results = get_llm_results(user_input,chat,results)
-            st.write(llm_results) 
+            if openAikey == None or openAikey=="":
+                st.write("לא הוכנס מפתח של OpenAI")
+
+            else:
+                chat = get_chat_api(openAikey)
+                llm_results = get_llm_results(user_input,chat,results)
+                st.write(llm_results) 
 
         else:
             st.write(results[['siman','sek','text']].head(10))