Update app.py

app.py

@@ -1,8 +1,8 @@
 import os
 import gradio as gr
-import openai
+import requests
 
-# We'll read the Hugging Face API key from environment variables (using Spaces "secrets").
+# Get the Hugging Face API key from Spaces secrets.
 HF_API_KEY = os.getenv("HF_API_KEY")
 
 # Model endpoints on Hugging Face
@@ -14,20 +14,32 @@ MODEL_ENDPOINTS = {
 
 def query_model(prompt, model_endpoint):
     """
-    Query a specific model using OpenAI-compatible ChatCompletion.
-    Since the Hugging Face Inference API is OpenAI-compatible,
-    we set openai.api_base to the model's endpoint.
+    Query a model via Hugging Face Inference API using a requests.post call.
+    This assumes an OpenAI-compatible endpoint structure.
     """
-    openai.api_key = HF_API_KEY
-    openai.api_base = model_endpoint
-
-    response = openai.ChatCompletion.create(
-        model="placeholder-model",
-        messages=[{"role": "user", "content": prompt}],
-        max_tokens=512,
-        temperature=0.7,
-    )
-    return response.choices[0].message["content"]
+    headers = {
+        "Authorization": f"Bearer {HF_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    data = {
+        "messages": [{"role": "user", "content": prompt}],
+        "max_tokens": 512,
+        "temperature": 0.7
+    }
+    
+    response = requests.post(model_endpoint, headers=headers, json=data)
+    try:
+        result = response.json()
+    except Exception:
+        return f"Error: Unable to parse JSON. Response: {response.text}"
+    
+    if "error" in result:
+        return f"Error: {result['error']}"
+    
+    try:
+        return result["choices"][0]["message"]["content"]
+    except Exception:
+        return f"Error: Unexpected response format: {result}"
 
 def chat_with_models(user_input, history):
     responses = []
@@ -39,8 +51,7 @@ def chat_with_models(user_input, history):
     return history, history
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Multi-LLM Chatbot using Hugging Face Inference API (OpenAI-compatible)")
-
+    gr.Markdown("# Multi-LLM Chatbot using Hugging Face Inference API")
     chatbot = gr.Chatbot()
     msg = gr.Textbox(label="Your Message")
     clear = gr.Button("Clear")