Create app.py

app.py

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+import os
+
+# Create requirements.txt content
+requirements_content = """gradio>=4.0.0
+groq>=0.4.0
+"""
+
+# Create app.py content (modifying the user's working Colab code slightly for HF Spaces environment variable safety)
+app_content = """import gradio as gr
+import os
+from groq import Groq
+
+# Initialize the Groq client
+# On Hugging Face Spaces, set GROQ_API_KEY as a Secret in the Space Settings
+api_key = os.environ.get("GROQ_API_KEY")
+if not api_key:
+    raise ValueError("GROQ_API_KEY environment variable not found. Please add it as a Secret in your Space Settings.")
+
+client = Groq(api_key=api_key)
+
+# Custom CSS to give it a sleek, modern look
+custom_css = \"\"\"
+.gradio-container { background-color: #0b0f19; font-family: 'Inter', sans-serif; }
+#title-header { text-align: center; margin-bottom: 20px; }
+#title-header h1 { color: #38bdf8; font-weight: 800; font-size: 2.2rem; }
+.sidebar-panel { background: #111827 !important; border: 1px solid #1f2937 !important; border-radius: 12px !important; }
+.chat-window { border: 1px solid #1f2937 !important; border-radius: 12px !important; background: #111827 !important; }
+\"\"\"
+
+def chat_stream(message, history, model, system_prompt, temperature, max_tokens):
+    \"\"\"
+    Custom chat function built for gr.Chatbot component format.
+    history is a list of dicts or tuples depending on older/newer Gradio versions.
+    \"\"\"
+    # 1. Start with the custom system prompt
+    messages = [{"role": "system", "content": system_prompt}]
+
+    # 2. Append the conversation history
+    for turn in history:
+        # Check if history format is dict or list/tuple
+        if isinstance(turn, dict):
+            messages.append({"role": turn["role"], "content": turn["content"]})
+        else:
+            messages.append({"role": "user", "content": turn[0]})
+            messages.append({"role": "assistant", "content": turn[1]})
+
+    # 3. Append current user message
+    messages.append({"role": "user", "content": message})
+
+    # 4. Stream response from Groq
+    try:
+        stream = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature,
+            max_tokens=max_tokens,
+            stream=True,
+        )
+
+        partial_response = ""
+        for chunk in stream:
+            if chunk.choices[0].delta.content:
+                partial_response += chunk.choices[0].delta.content
+                yield partial_response
+
+    except Exception as e:
+        yield f"⚠️ Error connecting to Groq: {str(e)}"
+
+
+# Building the Interactive Interface using Blocks
+with gr.Blocks() as demo:
+
+    # Title Section
+    gr.Markdown("# 🚀 Personal AI ChatBot", elem_id="title-header")
+    gr.Markdown("A fully customizable, hyper-fast LLM workspace.")
+
+    with gr.Row():
+        # --- LEFT COLUMN: CONTROL PANEL ---
+        with gr.Column(scale=1, elem_classes="sidebar-panel"):
+            gr.Markdown("### ⚙️ Engine Configurations")
+
+            model_select = gr.Dropdown(
+                choices=["llama-3.3-70b-versatile", "llama-3.1-8b-instant"],
+                value="llama-3.3-70b-versatile",
+                label="Select AI Model"
+            )
+
+            system_input = gr.Textbox(
+                value="You are a helpful, brilliant, and concise AI assistant.",
+                label="System Prompt / AI Persona",
+                lines=3,
+                placeholder="Ex: Act as a cynical senior developer..."
+            )
+
+            gr.Markdown("---")
+            gr.Markdown("### 🧠 Hyperparameters")
+
+            temp_slider = gr.Slider(
+                minimum=0.0, maximum=2.0, value=0.7, step=0.1,
+                label="Temperature", info="Higher = more creative, Lower = more factual"
+            )
+
+            tokens_slider = gr.Slider(
+                minimum=128, maximum=4096, value=1024, step=128,
+                label="Max Output Tokens"
+            )
+
+            gr.Markdown("---")
+            gr.Markdown("**Status:** 🟢 Connected to Groq API")
+
+        # --- RIGHT COLUMN: CHAT INTERFACE ---
+        with gr.Column(scale=3):
+            chatbot = gr.Chatbot(elem_classes="chat-window")
+
+            # Textbox and setup for user interaction
+            msg_input = gr.Textbox(
+                placeholder="Type your message here and press Enter...",
+                show_label=False,
+                container=False
+            )
+
+            # Wrap everything into Gradio's chat system
+            gr.ChatInterface(
+                fn=chat_stream,
+                chatbot=chatbot,
+                textbox=msg_input,
+                additional_inputs=[model_select, system_input, temp_slider, tokens_slider]
+            )
+
+if __name__ == "__main__":
+    demo.launch(css=custom_css, theme=gr.themes.Soft())
+"""
+
+# Write files to disk
+with open("requirements.txt", "w", encoding="utf-8") as f:
+    f.write(requirements_content.strip())
+
+with open("app.py", "w", encoding="utf-8") as f:
+    f.write(app_content.strip())
+
+print("Files created successfully.")