Merge branch 'main' of https://github.com/bucolucas/cyclop

path/to/PersonaTool.py

@@ -0,0 +1,4 @@
+class PersonaTool:
+    def get_functions(self):
+        # Implementation to return functions in JSON format
+        pass

telegram_inference_bot.py

@@ -1,3 +1,15 @@
+"""
+telegram_inference_bot.py
+
+This module implements a Telegram bot that processes user messages and
+images, interacts with the OpenAI API to provide intelligent responses,
+and manages conversation history and temporary file storage for images.
+
+It supports the following commands:
+- /start: Initializes the bot and welcomes the user.
+- /clear: Clears the user's conversation history and any uploaded images.
+"""
+
 import json
 import os
 import importlib
@@ -62,10 +74,25 @@ for tool in tools:
     functions.extend(tool.get_functions())
 
 async def start(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
+    """
+    Handles the /start command. Sends a welcome message to the user.
+    
+    Args:
+        update (Update): Incoming update containing the message.
+        context (ContextTypes.DEFAULT_TYPE): Context for the callback.
+    """
     logging.info("Bot started")
     await update.message.reply_text("Hello! I'm your AI assistant. How can I help you today? You can send me images and then ask questions about them.")
 
 async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
+    """
+    Handles the /clear command. Clears the user's conversation history
+    and any uploaded images.
+
+    Args:
+        update (Update): Incoming update containing the message.
+        context (ContextTypes.DEFAULT_TYPE): Context for the callback.
+    """
     user_id = update.effective_user.id
     if user_id in conversation_history:
         del conversation_history[user_id]
@@ -76,6 +103,14 @@ async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
     await update.message.reply_text("Conversation history and image cleared. Let's start fresh!")
 
 async def handle_image(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
+    """
+    Handles image uploads from users. Downloads the largest photo to 
+    a temporary file for further processing.
+
+    Args:
+        update (Update): Incoming update containing the image.
+        context (ContextTypes.DEFAULT_TYPE): Context for the callback.
+    """
     user_id = update.effective_user.id
     
     # Get the largest available photo
@@ -93,6 +128,14 @@ async def handle_image(update: Update, context: ContextTypes.DEFAULT_TYPE) -> No
     await update.message.reply_text("I've received your image. What would you like to know about it?")
 
 async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
+    """
+    Processes incoming text messages from users, calls the OpenAI API 
+    for inference, and sends the assistant's reply back to the user.
+
+    Args:
+        update (Update): Incoming update containing the text message.
+        context (ContextTypes.DEFAULT_TYPE): Context for the callback.
+    """
     try:
         user_id = update.effective_user.id
         user_message = update.message.text

tools/persona_tool.py

@@ -0,0 +1,58 @@
+import openai
+import json
+from tools.base_tool import BaseTool
+
+class PersonaTool(BaseTool):
+    def __init__(self, api_key: str):
+        super().__init__()
+        openai.api_key = api_key
+
+    def generate_response(self, persona_description: str, query: str) -> str:
+        """
+        Makes a call to the OpenAI API using the persona as a system prompt.
+        
+        Parameters:
+            persona_description (str): Description of the persona.
+            query (str): Query to be processed.
+        
+        Returns:
+            str: The response generated by the OpenAI API.
+        """
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": persona_description},
+                {"role": "user", "content": query}
+            ]
+        )
+        return response.choices[0].message['content']
+
+    def get_functions(self):
+        return json.dumps({
+            "functions": [
+                {
+                    "name": "generate_response",
+                    "description": "Generates a response based on a persona description and a user query.",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "persona_description": {
+                                "type": "string",
+                                "description": "Description of the persona."
+                            },
+                            "query": {
+                                "type": "string",
+                                "description": "User's query to be processed."
+                            }
+                        },
+                        "required": ["persona_description", "query"]
+                    }
+                }
+            ]
+        })
+
+    def execute(self, function_name, **kwargs):
+        if function_name == "generate_response":
+            return self.generate_response(kwargs.get("persona_description"), kwargs.get("query"))
+        else:
+            raise ValueError(f"Function {function_name} not found")