Update handler.py

handler.py

@@ -2,7 +2,6 @@ from pydantic import BaseModel
 import openai
 from environs import Env
 from typing import List, Dict, Any
-import json
 
 
 import requests
@@ -18,171 +17,148 @@ env_file_url = "https://www.dropbox.com/scl/fi/21ldek2cdsak2v3mhyy5x/openai.env?
 local_env_path = "openai.env"
 download_env_file(env_file_url, local_env_path)
 
+
 # Load environment variables
 env = Env()
 env.read_env("openai.env")
 openai.api_key = env.str("OPENAI_API_KEY")
 
 # Constants
-SYSTEM_PROMPT_SUGG = env.str("SYSTEM_PROMPT_SUGG", "generate 3 different friendly short conversation starter for a user to another unknown user.")
-SYSTEM_PROMPT_CHAT = env.str("SYSTEM_PROMPT_CHAT", "Suggest a suitable reply for a user in a dating conversation context.")
 MODEL = env.str("MODEL", "gpt-3.5-turbo")
-NUMBER_OF_MESSAGES_FOR_CONTEXT_SUGG = min(env.int("NUMBER_OF_MESSAGES_FOR_CONTEXT_SUGG", 4), 10)
-NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT = min(env.int("NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT", 4), 10)
 AI_RESPONSE_TIMEOUT = env.int("AI_RESPONSE_TIMEOUT", 20)
 
-class ConversationPayloadSugg(BaseModel):
-    fromusername: str
-    tousername: str
-    FromUserKavasQuestions: list
-    ToUserKavasQuestions: list
-    Chatmood: str
-
-class LastChatMessage(BaseModel):
-    fromUser: str
-    touser: str
-
-class ConversationPayloadChat(BaseModel):
-    fromusername: str
-    tousername: str
-    zodiansign: str
-    LastChatMessages: List[dict]
-    Chatmood: str
-
-def create_conversation_starter_prompt(user_questions, chatmood):
-    formatted_info = " ".join([f"{qa['Question']} - {qa['Answer']}" for qa in user_questions if qa['Answer']])
-    prompt = (f"Based on user profile info and a {chatmood} mood, "
-              f"generate 3 subtle and very short conversation starters. "
-              f"Explore various topics like travel, hobbies, movies, and not just culinary tastes. "
-              f"\nProfile Info: {formatted_info}")
-    return prompt
-
-def generate_conversation_starters(prompt):
-    try:
-        response = openai.ChatCompletion.create(
-            model=MODEL,
-            messages=[{"role": "system", "content": prompt}],
-            temperature=0.7,
-            max_tokens=100,
-            n=1,
-            request_timeout=AI_RESPONSE_TIMEOUT
-        )
-        return response.choices[0].message["content"]
-    except openai.error.OpenAIError as e:
-        raise Exception(f"OpenAI API error: {str(e)}")
-    except Exception as e:
-        raise Exception(f"Unexpected error: {str(e)}")
-
-def transform_messages(last_chat_messages):
-    t_messages = []
-    for chat in last_chat_messages:
-        if "fromUser" in chat:
-            from_user = chat['fromUser']
-            message = chat.get('touser', '')
-            t_messages.append(f"{from_user}: {message}")
-        elif "touser" in chat:
-            to_user = chat['touser']
-            message = chat.get('fromUser', '')
-            t_messages.append(f"{to_user}: {message}")
-    
-    if t_messages and "touser" in last_chat_messages[-1]:
-        latest_message = t_messages[-1]
-        latest_message = f"Q: {latest_message}"
-        t_messages[-1] = latest_message
-    
-    return t_messages
-
-def generate_system_prompt(last_chat_messages, fromusername, tousername, zodiansign=None, chatmood=None):
-    prompt = ""
-    if not last_chat_messages or ("touser" not in last_chat_messages[-1]):
-        prompt = f"Suggest a casual and friendly message for {fromusername} to start a conversation with {tousername} or continue naturally, as if talking to a good friend. Strictly avoid replying to messages from {fromusername} or answering their questions."
-    else:
-        prompt = f"Suggest a warm and friendly reply for {fromusername} to respond to the last message from {tousername}, as if responding to a dear friend. Strictly avoid replying to messages from {fromusername} or answering their questions."
-    
-    if zodiansign:
-        prompt += f" Keep in mind {tousername}'s {zodiansign} zodiac sign."
-    if chatmood:
-        prompt += f" Consider the {chatmood} mood."
-    
-    return prompt
-
-def get_conversation_suggestions(last_chat_messages):
-    fromusername = last_chat_messages[-1].get("fromusername", "")
-    tousername = last_chat_messages[-1].get("tousername", "")
-    zodiansign = last_chat_messages[-1].get("zodiansign", "")
-    chatmood = last_chat_messages[-1].get("Chatmood", "")
-    
-    messages = transform_messages(last_chat_messages)
-    
-    system_prompt = generate_system_prompt(last_chat_messages, fromusername, tousername, zodiansign, chatmood)
-    messages_final = [{"role": "system", "content": system_prompt}]
-    
-    if messages:
-        messages_final.extend([{"role": "user", "content": m} for m in messages])
-    else:
-        # If there are no messages, add a default message to ensure a response is generated
-        default_message = f"{tousername}: Hi there!"
-        messages_final.append({"role": "user", "content": default_message})
-    
-    try:
-        response = openai.ChatCompletion.create(
-            model=MODEL,
-            messages=messages_final,
-            temperature=0.7,
-            max_tokens=150,
-            n=3,
-            request_timeout=AI_RESPONSE_TIMEOUT
-        )
-        
-        formatted_replies = []
-        for idx, choice in enumerate(response.choices):
-            formatted_replies.append({
-                "type": "TEXT",
-                "body": choice.message['content'],
-                "title": f"AI Reply {idx + 1}",
-                "confidence": 1,
-            })
-        
-        return formatted_replies
-    
-    except openai.error.Timeout as e:
-        formatted_reply = [{
-            "type": "TEXT",
-            "body": "Request to the AI response generator has timed out. Please try again later.",
-            "title": "AI Response Error",
-            "confidence": 1
-        }]
-        return formatted_reply
-
-def process_json_input(json_data):
-    if "FromUserKavasQuestions" in json_data and "Chatmood" in json_data:
-        prompt = create_conversation_starter_prompt(
-            json_data["FromUserKavasQuestions"],
-            json_data["Chatmood"]
-        )
-        starter_suggestion = generate_conversation_starters(prompt)
-        return {"conversation_starter": starter_suggestion}
-    elif "LastChatMessages" in json_data:
-        last_chat_messages = json_data["LastChatMessages"][-NUMBER_OF_MESSAGES_FOR_CONTEXT_CHAT:]
-        response = {
-            "version": "1.0.0-alpha",
-            "suggested_responses": get_conversation_suggestions(last_chat_messages)
-        }
-        return response
-    else:
-        raise ValueError("Invalid JSON structure.")
-
 class EndpointHandler:
-    def __init__(self, model_dir):
-        super().__init__()
-        self.model_dir = model_dir
+    def __init__(self):
+        pass
 
     def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
         try:
-            json_data = data
-            output = process_json_input(json_data)
+            output = self.process_json_input(data)
             return output
         except ValueError as e:
             return {"error": str(e)}
         except Exception as e:
-            return {"error": f"Unexpected error: {str(e)}"}
+            return {"error": str(e)}
+
+    def process_json_input(self, json_data):
+        if "FromUserKavasQuestions" in json_data and "Chatmood" in json_data:
+            prompt = self.create_conversation_starter_prompt(
+                json_data["FromUserKavasQuestions"],
+                json_data["Chatmood"]
+            )
+            starter_suggestion = self.generate_conversation_starters(prompt)
+            return {"conversation_starter": starter_suggestion}
+        elif "LastChatMessages" in json_data:
+            last_chat_messages = json_data["LastChatMessages"][-4:]
+            response = {
+                "version": "1.0.0-alpha",
+                "suggested_responses": self.get_conversation_suggestions(last_chat_messages)
+            }
+            return response
+        else:
+            raise ValueError("Invalid JSON structure.")
+
+    def create_conversation_starter_prompt(self, user_questions, chatmood):
+        formatted_info = " ".join([f"{qa['Question']} - {qa['Answer']}" for qa in user_questions if qa['Answer']])
+        prompt = (f"Based on user profile info and a {chatmood} mood, "
+                  f"generate 3 subtle and very short conversation starters. "
+                  f"Explore various topics like travel, hobbies, movies, and not just culinary tastes. "
+                  f"\nProfile Info: {formatted_info}")
+        return prompt
+
+    def generate_conversation_starters(self, prompt):
+        try:
+            response = openai.ChatCompletion.create(
+                model=MODEL,
+                messages=[{"role": "system", "content": prompt}],
+                temperature=0.7,
+                max_tokens=100,
+                n=1,
+                request_timeout=AI_RESPONSE_TIMEOUT
+            )
+            return response.choices[0].message["content"]
+        except openai.error.OpenAIError as e:
+            raise Exception(f"OpenAI API error: {str(e)}")
+        except Exception as e:
+            raise Exception(f"Unexpected error: {str(e)}")
+
+    def transform_messages(self, last_chat_messages):
+        t_messages = []
+        for chat in last_chat_messages:
+            if "fromUser" in chat:
+                from_user = chat['fromUser']
+                message = chat.get('touser', '')
+                t_messages.append(f"{from_user}: {message}")
+            elif "touser" in chat:
+                to_user = chat['touser']
+                message = chat.get('fromUser', '')
+                t_messages.append(f"{to_user}: {message}")
+        
+        if t_messages and "touser" in last_chat_messages[-1]:
+            latest_message = t_messages[-1]
+            latest_message = f"Q: {latest_message}"
+            t_messages[-1] = latest_message
+        
+        return t_messages
+
+    def generate_system_prompt(self, last_chat_messages, fromusername, tousername, zodiansign=None, chatmood=None):
+        prompt = ""
+        if not last_chat_messages or ("touser" not in last_chat_messages[-1]):
+            prompt = f"Suggest a casual and friendly message for {fromusername} to start a conversation with {tousername} or continue naturally, as if talking to a good friend. Strictly avoid replying to messages from {fromusername} or answering their questions."
+        else:
+            prompt = f"Suggest a warm and friendly reply for {fromusername} to respond to the last message from {tousername}, as if responding to a dear friend. Strictly avoid replying to messages from {fromusername} or answering their questions."
+        
+        if zodiansign:
+            prompt += f" Keep in mind {tousername}'s {zodiansign} zodiac sign."
+        if chatmood:
+            prompt += f" Consider the {chatmood} mood."
+        
+        return prompt
+
+    def get_conversation_suggestions(self, last_chat_messages):
+        fromusername = last_chat_messages[-1].get("fromusername", "")
+        tousername = last_chat_messages[-1].get("tousername", "")
+        zodiansign = last_chat_messages[-1].get("zodiansign", "")
+        chatmood = last_chat_messages[-1].get("Chatmood", "")
+        
+        messages = self.transform_messages(last_chat_messages)
+        
+        system_prompt = self.generate_system_prompt(last_chat_messages, fromusername, tousername, zodiansign, chatmood)
+        messages_final = [{"role": "system", "content": system_prompt}]
+        
+        if messages:
+            messages_final.extend([{"role": "user", "content": m} for m in messages])
+        else:
+            # If there are no messages, add a default message to ensure a response is generated
+            default_message = f"{tousername}: Hi there!"
+            messages_final.append({"role": "user", "content": default_message})
+        
+        try:
+            response = openai.ChatCompletion.create(
+                model=MODEL,
+                messages=messages_final,
+                temperature=0.7,
+                max_tokens=150,
+                n=3,
+                request_timeout=AI_RESPONSE_TIMEOUT
+            )
+            
+            formatted_replies = []
+            for idx, choice in enumerate(response.choices):
+                formatted_replies.append({
+                    "type": "TEXT",
+                    "body": choice.message['content'],
+                    "title": f"AI Reply {idx + 1}",
+                    "confidence": 1,
+                })
+            
+            return formatted_replies
+        
+        except openai.error.Timeout as e:
+            formatted_reply = [{
+                "type": "TEXT",
+                "body": "Request to the AI response generator has timed out. Please try again later.",
+                "title": "AI Response Error",
+                "confidence": 1
+            }]
+            return formatted_reply