Update actions/actions.py

actions/actions.py

@@ -31,27 +31,37 @@ secret_value_0 = os.environ.get("openai")
 openai.api_key = secret_value_0
 # Provide your OpenAI API key
 
-def generate_openai_response(query, model_engine="text-davinci-003", max_tokens=124, temperature=0.8):
-    """Generate a response using the OpenAI API."""
+def generate_openai_response(user_queries, model_engine="gpt-3.5-turbo", max_tokens=100, temperature=0.5):
+    """Generate a response using the OpenAI API.""" 
     
-    # Run the main function from search_content.py and store the results in a variable
-    results = main_search(query)
-
+    # Send last two user queries for vector search
+    if len(user_queries) >= 2:
+        results = main_search(user_queries[-1]+user_queries[-2])
+    else:
+        results = main_search(user_queries[-1])
+  
     # Create context from the results
     context = "".join([f"#{str(i)}" for i in results])[:2014] # Trim the context to 2014 characters - Modify as necessory
-    prompt_template = f"Relevant context: {context}\n\n Answer the question in detail: {query}"
-
-    # Generate a response using the OpenAI API
-    response = openai.Completion.create(
-        engine=model_engine,
-        prompt=prompt_template,
-        max_tokens=max_tokens,
-        temperature=temperature,
-        n=1,
-        stop=None,
+    
+    messages=[
+    {"role": "system", "content": f"You are a helpful assistant tasked to answer user queries using the following context: {context}"}
+             ] 
+    max_user_queries_to_include = min(1,len(user_queries))
+    # The latest query is at the end of the list
+    for i in range(len(user_queries)):
+        if i<max_user_queries_to_include:
+            messages.append({"role": "user", "content": user_queries[-max_user_queries_to_include+i]})
+    
+    response = openai.ChatCompletion.create(
+    model="gpt-3.5-turbo",
+    messages= messages,
+    max_tokens=124,
+    temperature=0,
+    top_p=1,
+    frequency_penalty=0,
+    presence_penalty=0
     )
-
-    return response.choices[0].text.strip()
+    return response.choices[0]['message']['content'].strip()#+"Debug Info:            Openai-input_1:   "+str(messages_1)+"         Openai_input_0"+str( messages_0)+"  user_queries: "+str(user_queries)
 
 class GetOpenAIResponse(Action):
 
@@ -63,12 +73,25 @@ class GetOpenAIResponse(Action):
             tracker: Tracker,
             domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
 
+        # Extract conversation data
+        conversation_history = tracker.events
+
+        user_queries = []
+        bot_responses = []
+
+        for event in conversation_history:
+            if event.get("event") == "user":
+                user_queries.append(event.get("text"))
+            elif event.get("event") == "bot":
+                bot_responses.append(event.get("text"))
+
         # Use OpenAI API to generate a response
-        query = tracker.latest_message.get('text')
-        response = generate_openai_response(query)
+        #query = tracker.latest_message.get('text')
+        response = generate_openai_response(user_queries)
                 
         # Output the generated response to user
-        dispatcher.utter_message(text=response)
+        dispatcher.utter_message(text=str(response))
+ 
                 
 class GeneralHelp(Action):
     def name(self) -> Text: