Upload app.py

app.py

@@ -1,70 +1,82 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
-
-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")
-
-    messages = [{"role": "system", "content": system_message}]
-
-    messages.extend(history)
-
-    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,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-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()
-
-
-if __name__ == "__main__":
-    demo.launch()
+import gradio as gr
+import os
+import requests
+
+# Load GROQ API key from Hugging Face Secrets
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+MODEL_NAME = "llama3-8b-8192"
+
+# System Prompt (Chatbot Personality)
+SYSTEM_PROMPT = """
+You are CodeMentor AI, a friendly and expert programming tutor.
+You help students learn programming concepts clearly and patiently.
+
+Your behavior:
+- Explain concepts step-by-step
+- Use simple language
+- Give Python examples when possible
+- Encourage learning and curiosity
+- Correct mistakes politely
+"""
+
+def query_groq(message, chat_history, temperature):
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+
+    for user, bot in chat_history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": bot})
+
+    messages.append({"role": "user", "content": message})
+
+    response = requests.post(
+        GROQ_API_URL,
+        headers=headers,
+        json={
+            "model": MODEL_NAME,
+            "messages": messages,
+            "temperature": temperature
+        }
+    )
+
+    if response.status_code == 200:
+        return response.json()["choices"][0]["message"]["content"]
+    else:
+        return f"Error {response.status_code}: {response.text}"
+
+def respond(message, chat_history, temperature):
+    bot_reply = query_groq(message, chat_history, temperature)
+    chat_history.append((message, bot_reply))
+    return "", chat_history
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 💻 CodeMentor AI – Your Programming Tutor")
+
+    chatbot = gr.Chatbot(height=400)
+    state = gr.State([])
+
+    with gr.Row():
+        msg = gr.Textbox(label="Ask a programming question")
+    
+    # UI Improvement (Requirement #4)
+    temperature = gr.Slider(
+        0.1, 1.0, value=0.7, step=0.1,
+        label="Response Creativity Level"
+    )
+
+    with gr.Row():
+        send = gr.Button("Send")
+        clear = gr.Button("Clear Chat")
+
+    send.click(respond, [msg, state, temperature], [msg, chatbot])
+    msg.submit(respond, [msg, state, temperature], [msg, chatbot])
+    clear.click(lambda: ([], []), None, [chatbot, state])
+
+demo.launch()
+