Update app.py

app.py

@@ -1,19 +1,63 @@
 import gradio as gr
+from openai import OpenAI
 from huggingface_hub import InferenceClient
+from tenacity import retry, wait_random_exponential, stop_after_attempt
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+OPENAI_KEY = os.getenv("OPENAI_KEY")
+client = OpenAI(api_key=OPEN_AI_KEY)
+
+def get_current_weather(location, unit="celsius"):
+    """Get the current weather in a given location"""
+    if "taipei" in location.lower():
+        return json.dumps({"location": "Taipei", "temperature": "10", "unit": unit})
+    else:
+        return json.dumps({"location": location, "temperature": "unknown"})
+
+@retry(wait=wait_random_exponential(multiplier=1, max=40), stop=stop_after_attempt(3))
+def chat_completion_request(messages, tools=None, tool_choice=None, model=GPT_MODEL):
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            tools=tools,
+            tool_choice=tool_choice,
+        )
+        return response
+    except Exception as e:
+        print("Unable to generate ChatCompletion response")
+        print(f"Exception: {e}")
+        return e
+        
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_current_weather",
+            "description": "Get the current weather",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "The city and state, e.g. San Francisco, CA",
+                    },
+                    "unit": {
+                        "type": "string",
+                        "enum": ["celsius", "fahrenheit"],
+                        "description": "The temperature unit to use. Infer this from the users location.",
+                    },
+                },
+                "required": ["location", "unit"],
+            },
+        }
+    }
+]
 
 
 def respond(
     message,
     history: list[tuple[str, str]],
     system_message,
-    max_tokens,
-    temperature,
-    top_p,
 ):
     messages = [{"role": "system", "content": system_message}]
 
@@ -25,19 +69,34 @@ def respond(
 
     messages.append({"role": "user", "content": message})
 
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    response = chat_completion_request(messages, tools=tools, tool_choice='auto')
 
-        response += token
-        yield response
+    response_message = response.choices[0].message
+    tool_calls = response_message.tool_calls
+    if tool_calls:
+        available_functions = {
+            "get_current_weather": get_current_weather,
+        } 
+        messages.append(response_message)
+        for tool_call in tool_calls:
+            function_name = tool_call.function.name
+            function_to_call = available_functions[function_name]
+            function_args = json.loads(tool_call.function.arguments)
+            function_response = function_to_call(
+                location=function_args.get("location"),
+                unit=function_args.get("unit"),
+            )
+            messages.append(
+                {
+                    "tool_call_id": tool_call.id,
+                    "role": "tool",
+                    "name": function_name,
+                    "content": function_response,
+                }
+            )  
+        second_response = chat_completion_request(messages)
+        print(second_response)
+        return second_response
 
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
@@ -45,7 +104,7 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value="", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(