app.py

app.py

@@ -2,65 +2,49 @@ import gradio as gr
 import requests
 import os
 
-# Hugging Face token from Secrets
-HF_TOKEN = os.getenv("HF_API_TOKEN")
-MODEL_ID = "bigcode/starcoder2-3b"  # Free multi-language code model
+# Read API key from environment variable
+API_KEY = os.getenv("OPENAI_API_KEY")
 
 languages = ["Python", "C", "C++", "Java", "JavaScript", "Solidity", "SQL", "Bash"]
 
 def code_assistant(prompt, language="Python"):
-    if not HF_TOKEN:
-        return "Error: Hugging Face API token not set. Please add HF_API_TOKEN in Space Secrets and restart the Space."
-
-    # Prepend language info to prompt for multi-language generation
-    full_prompt = f"# Language: {language}\n{prompt}"
-
-    headers = {
-        "Authorization": f"Bearer {HF_TOKEN}",
-        "Content-Type": "application/json"
-    }
-    payload = {
-        "inputs": full_prompt,
-        "options": {"use_cache": False}  # optional
-    }
+    # Check if API key exists
+    if not API_KEY:
+        return "Error: API key not set. Please add your OPENAI_API_KEY in Space Secrets and restart the Space."
 
+    system_prompt = f"You are an expert {language} programmer. Only respond with code or explanation as requested. Wrap code in Markdown-style code blocks."
+    
     try:
         response = requests.post(
-            f"https://router.huggingface.co/models/{MODEL_ID}",
-            headers=headers,
-            json=payload,
-            timeout=60
+            "https://api.openai.com/v1/chat/completions",
+            headers={"Authorization": f"Bearer {API_KEY}"},
+            json={
+                "model": "gpt-4o-mini",
+                "messages": [
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": prompt}
+                ]
+            }
         )
 
-        data = response.json()
+        text = response.json()["choices"][0]["message"]["content"]
 
-        # HF router returns list with generated_text
-        if isinstance(data, dict) and "generated_text" in data:
-            text = data["generated_text"]
-        elif isinstance(data, dict) and "error" in data:
-            return f"Error from model: {data['error']}"
-        else:
-            text = str(data)
-
-        # Wrap in Markdown code block
+        # Ensure output is wrapped in Markdown code block
         if not text.startswith("```"):
             text = f"```{language.lower()}\n{text}\n```"
-
         return text
 
     except Exception as e:
-        return f"Error: {e}"
+        return f"Error: {e}\nResponse: {response.text if 'response' in locals() else 'No response'}"
 
 # Gradio UI
 iface = gr.Interface(
     fn=code_assistant,
-    inputs=[
-        gr.Textbox(label="Your Prompt", placeholder="Write, explain, or debug code..."),
-        gr.Dropdown(languages, label="Language")
-    ],
-    outputs=gr.Markdown(label="Output"),
-    title="TheWizard 💬 — Free Code Assistant",
-    description="Ask for code, explanations, or debugging in multiple languages using free HF models."
+    inputs=[gr.Textbox(label="Your Prompt", placeholder="Write, explain, or debug code..."),
+            gr.Dropdown(languages, label="Language")],
+    outputs=gr.Textbox(label="Output", lines=20, interactive=False),
+    title="TheWizard 💬 — Code Assistant",
+    description="Ask for code, explanations, or debugging in multiple languages. Focused only on coding."
 )
 
 iface.launch()

requirements.txt

@@ -1,3 +1 @@
-gradio>=6.6.0
-requests
-python-dotenv
+huggingface_hub==0.22.2