Update app.py

app.py

@@ -1,70 +1,151 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from groq import Groq
+from dotenv import load_dotenv
+import os, datetime, re
 
+# === Load API key ===
+load_dotenv()
+client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    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(token=hf_token.token, model="openai/gpt-oss-20b")
+# === Helper Functions ===
+def sanitize_filename(name):
+    return re.sub(r"[^a-zA-Z0-9_-]", "_", name)
 
-    messages = [{"role": "system", "content": system_message}]
+def save_code(code, language):
+    os.makedirs("outputs", exist_ok=True)
+    ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+    filename = f"outputs/{sanitize_filename(language)}_{ts}.txt"
+    with open(filename, "w", encoding="utf-8") as f:
+        f.write(code)
+    return f" Code saved to `{filename}`"
 
-    messages.extend(history)
+# === Simple Heuristic Language Detector ===
+def detect_language(prompt_or_code):
+    text = prompt_or_code.lower()
+    if "python" in text or "def " in text or "import " in text:
+        return "python"
+    elif "#include" in text or "printf" in text:
+        return "c"
+    elif "iostream" in text or "cout" in text:
+        return "cpp"
+    elif "public static void main" in text or "System.out.println" in text:
+        return "java"
+    elif "console.log" in text or "function(" in text:
+        return "javascript"
+    else:
+        return "python"  # default fallback
 
-    messages.append({"role": "user", "content": message})
+# === Code Generation ===
+def generate_code(prompt, language, history):
+    try:
+        # Auto-detect language if none selected
+        if language == "auto" or not language:
+            language = detect_language(prompt)
 
-    response = ""
+        response = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=[
+                {"role": "system", "content": "You are an expert software engineer."},
+                {"role": "user", "content": f"Write a {language} program for: {prompt}"}
+            ],
+            temperature=0.4
+        )
+        text = response.choices[0].message.content.strip()
+        text = re.sub(r"```[a-zA-Z]*", "", text).replace("```", "").strip()
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
+        history.append({"action": "Generated", "prompt": prompt, "language": language, "code": text})
+        return text, history, language
+    except Exception as e:
+        return f"Error: {e}", history, language
 
-        response += token
-        yield response
+# === Debugging & Explanation ===
+def debug_code(code, error_message, language, history):
+    try:
+        # Auto-detect language from code
+        if language == "auto" or not language:
+            language = detect_language(code)
 
+        debug_prompt = f"""
+You are a professional {language} developer and debugger.
+Here is the user's code that produced an error:
 
+CODE:
+{code}
+
+ERROR MESSAGE / OUTPUT:
+{error_message}
+
+Please identify and fix the issue. Return only the corrected code.
 """
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
+        response = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=[
+                {"role": "system", "content": "You are an expert code debugger."},
+                {"role": "user", "content": debug_prompt}
+            ],
+            temperature=0.3
+        )
+        fixed_code = response.choices[0].message.content.strip()
+        fixed_code = re.sub(r"```[a-zA-Z]*", "", fixed_code).replace("```", "").strip()
+
+        # Explain fix
+        exp_prompt = f"Explain briefly (under 100 words) what was wrong in this {language} code and how it was fixed."
+        exp_response = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=[
+                {"role": "system", "content": "You are an expert software explainer."},
+                {"role": "user", "content": f"{exp_prompt}\n\nOriginal Code:\n{code}\n\nFixed Code:\n{fixed_code}"}
+            ],
+            temperature=0.4
+        )
+        explanation = exp_response.choices[0].message.content.strip()
+
+        history.append({
+            "action": "Debugged",
+            "language": language,
+            "error": error_message,
+            "fixed_code": fixed_code,
+            "explanation": explanation
+        })
+        return fixed_code, explanation, history, language
+    except Exception as e:
+        return f"Error: {e}", "Could not generate explanation.", history, language
+
+# === GUI ===
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="violet", neutral_hue="gray"), title="LLaMA 3.1 Code Assistant") as demo:
+    gr.HTML("<h1 style='text-align:center;'>🧠 LLaMA 3.1 Code Assistant + Debugger + Explainer</h1>")
+    gr.Markdown("An intelligent, debugging-friendly AI tool built with **Groq API (LLaMA 3.1)** — generate, debug, and learn code effortlessly.")
+
+    history = gr.State([])
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            gr.Markdown("### Code Generation")
+            prompt = gr.Textbox(label="Enter your programming request", placeholder="e.g., Write a Python program to check palindrome", lines=3)
+            language = gr.Dropdown(
+                ["auto", "python", "c", "cpp", "java", "javascript"],
+                label="Select Language (auto-detect default)",
+                value="auto"
+            )
+            run_btn = gr.Button("Generate Code", variant="primary")
+            output = gr.Code(label="Generated Code", language="python", interactive=False)
+            save_btn = gr.Button("Save Code")
+            save_status = gr.Markdown("")
+        with gr.Column(scale=2):
+            gr.Markdown("### Debugging & Explanation")
+            error_box = gr.Textbox(label="Paste Error Message / Output", lines=3, placeholder="e.g., segmentation fault, syntax error...")
+            debug_btn = gr.Button("Debug Code")
+            debugged_output = gr.Code(label="Fixed Code", language="python", interactive=False)
+            explanation_box = gr.Textbox(label="Explanation", interactive=False, lines=4)
+
+    # Event Bindings
+    run_btn.click(fn=generate_code, inputs=[prompt, language, history], outputs=[output, history, language])
+    save_btn.click(fn=save_code, inputs=[output, language], outputs=save_status)
+    debug_btn.click(fn=debug_code, inputs=[output, error_box, language, history], outputs=[debugged_output, explanation_box, history, language])
 
+    with gr.Accordion("Session Memory (History)", open=False):
+        gr.JSON(history)
 
+# === Launch ===
 if __name__ == "__main__":
     demo.launch()