updated names of bots

openai_generic_telegram_inference_bot.py

@@ -9,13 +9,15 @@ from telegram.ext import Application, CommandHandler, MessageHandler, filters, C
 from dotenv import load_dotenv
 from tools.base_tool import BaseTool
 from tools.metrics_tool import MetricsTool
-import openai
+from openai import OpenAI
 
 # Load environment variables
 load_dotenv()
 
-openai.api_key = os.environ.get("OPENAI_API_KEY")
-openai.api_base = os.environ.get("OPENAI_API_BASE", "https://api.openai.com/v1")
+openai_client = OpenAI(
+    api_key=os.environ.get("GLHF_CHAT_API_KEY"), 
+    base_url=os.environ.get("GLHF_CHAT_API_BASE", "https://api.openai.com/v1")
+)
 
 # Set up logging to console and file
 logging.basicConfig(level=logging.WARNING, handlers=[
@@ -55,7 +57,7 @@ for tool in tools:
 async def start(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
     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."
+        "Hello! I'm your AI assistant. How can I help you today?"
     )
 
 async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
@@ -65,8 +67,8 @@ async def clear(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
     for tool in tools:
         tool.clear()
 
-    logging.info(f"Cleared conversation history and image for user {user_id}")
-    await update.message.reply_text("Conversation history and image cleared. Let's start fresh!")
+    logging.info(f"Cleared conversation history for user {user_id}")
+    await update.message.reply_text("Conversation history cleared. Let's start fresh!")
 
 async def update_status_message(context: ContextTypes.DEFAULT_TYPE, chat_id: int, message_id: int, status: str):
     keyboard = [
@@ -99,8 +101,12 @@ async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE) ->
         messages = conversation_history[user_id]
 
         response = get_chat_response(messages)
-        tool_calls = response.get('tool_calls', [])
-        assistant_message = response.get('content', '')
+        tool_calls = []
+        for choice in response.choices:
+            if choice.finish_reason == "tool_calls":
+                tool_calls.append(choice)
+            else:
+                assistant_message = choice.message.content
                 messages.append({"role": "assistant", "content": assistant_message})
 
         toolUseCount = 0
@@ -153,22 +159,19 @@ def call_tool(function_call):
             return tool.execute(function_name, **function_args)
 
 def get_chat_response(messages):
-    return get_openai_response(messages)
-
-def get_openai_response(messages):
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",  # You can change this to your desired model
+        response = openai_client.chat.completions.create(
+            model="hf:meta-llama/Meta-Llama-3.1-405B-Instruct",  # You can change this to your desired model
             messages=[{"role": "system", "content": system_prompt}] + messages,
-            max_tokens=1000,
-            temperature=0.7,
+            max_tokens=4096,
+            temperature=0.6,
             top_p=1,
             frequency_penalty=0,
             presence_penalty=0,
-            functions=functions,
-            function_call="auto"
+            tools=functions
+            #tool_choice={  }
         )
-        return response['choices'][0]['message']
+        return response
     except Exception as e:
         logging.error(f"An error occurred: {str(e)}")
         return None