actually call OLLAMA and log the errors

agent-py-bot/agent.py

@@ -41,50 +41,32 @@ async def echo(update: Update, context):
     await context.bot.send_message(chat_id=update.effective_chat.id, text=update.message.text)
 
 
-def query_llm(user_message):
+async def query_llm_simple(user_message):
     """Query the LLM with the user's message."""
     data = {
         "model": "llama2",
-        "messages": [{"role": "user", "content": user_message}]
+        "messages": [{"role": "user", "content": user_message}],
+        "stream": "false"
     }
     response = requests.post(LLM_ENDPOINT, json=data)
     if response.status_code == 200:
-        response_data = response.json()
-        return response_data.get('message', {}).get('content', 'No response')
-    else:
+            response_data = response.json()
+            if "error" in response_data:
+                error_message = response_data.get('error', 'Unknown error')
+                # Log the error
+                logger.error(f"LLM Error: {error_message}")
+                # Return a user-friendly error message
+                return "Sorry, there was an error processing your request."
+            return response_data.get('message', {}).get('content', 'No response')
+    else:    
+        logger.error(f"Error reaching LLM: {response.text}")
         return "Error: Unable to reach LLM"
+    
 
-def ask(update, context):
+async def ask(update, context):
     user_message = ' '.join(context.args)
-    llm_response = query_llm(user_message)
-    update.message.reply_text(llm_response)
-
-async def screenshot(update, context):
-    """Take a screenshot of a webpage."""
-    url = ' '.join(context.args)
-    update.message.reply_text('This will noramlly get a screenshot from: '.url)# url.', but currently under development')
-
-
-    # driver.get(url)
-    # screenshot = driver.get_screenshot_as_png()
-    # image_stream = BytesIO(screenshot)
-    # image_stream.seek(0)
-    # image = Image.open(image_stream)
-    # image_stream.close()
-    # image.save('screenshot.png')
-    # update.message.reply_photo(photo=open('screenshot.png', 'rb'))
-
-async def error_handler(update: Update): #context: CallbackContext
-    """Handle errors occurred during the execution of commands."""
-    # Log the error before we do anything else
-    # logger.error(f"An error occurred: {context.error}")
-    logger.error(f"An error occurred:")
-
-    # Send a message to the user
-    # error_message = "Sorry, an unexpected error occurred. Please try again later."
-    # if update.effective_message:
-    #     await context.bot.send_message(chat_id=update.effective_chat.id, text=error_message)
-
+    llm_response = await query_llm_simple(user_message)
+    await update.message.reply_text(llm_response)
 
 async def main():
     """Start the bot."""
@@ -94,21 +76,50 @@ async def main():
     # Add handlers to the application
     # Command handlers should be registered before the generic message handler
     application.add_handler(CommandHandler("start", start))
-    application.add_handler(CommandHandler("screenshot", screenshot)) # Ensure screenshot function is async
-    application.add_handler(CommandHandler("ai", ask))
+    # application.add_handler(CommandHandler("screenshot", screenshot)) # Ensure screenshot function is async
+    application.add_handler(CommandHandler("ai", query_llm_simple))
     application.add_handler(CommandHandler("ask", ask))
-    application.add_handler(CommandHandler("llm", ask))
     
     # This handler should be last as it's the most generic
     application.add_handler(MessageHandler(filters.TEXT, echo))
 
     # Register the error handler
-    application.add_error_handler(error_handler)
+    # application.add_error_handler(error_handler)
 
     # Run the bot
     await application.run_polling()
 
 
+# oldasync def query_llm(user_message):
+    """Query the LLM with the user's message."""
+    data = {
+        "model": "llama2",
+        "messages": [{"role": "user", "content": user_message}]
+    }
+    response = requests.post(LLM_ENDPOINT, json=data)
+    
+    if response.status_code == 200:
+        # Split the response into individual JSON objects
+        response_parts = response.text.split('\n')
+
+        # Aggregate the content from each part
+        full_response = ''
+        for part in response_parts:
+            try:
+                json_part = json.loads(part)
+                if 'message' in json_part and 'content' in json_part['message']:
+                    full_response += json_part['message']['content'] + ' '
+                if json_part.get('done', False):
+                    break
+            except json.JSONDecodeError:
+                # Handle possible JSON decode error
+                continue
+
+        return full_response.strip()
+    else:
+        return "Error: Unable to reach LLM"
+
+
 if __name__ == '__main__':
     loop = asyncio.get_event_loop()
     if loop.is_running():

agent-py-bot/cmd.sh

@@ -13,3 +13,10 @@ pip install ....
 
 
 cd agent-py-bot/
+
+
+# ToDo
+make the telegram bot think while getting the response
+
+/ask who are you
+/ai test