Create app.py

app.py

@@ -0,0 +1,206 @@
+import os
+from collections.abc import Generator
+from typing import Any
+
+import gradio as gr
+from dotenv import load_dotenv
+from groq import Groq
+
+# Loads GROQ_API_KEY from a local .env file when running on your computer.
+# On Hugging Face Spaces, add GROQ_API_KEY under Settings > Secrets.
+load_dotenv()
+
+DEFAULT_SYSTEM_PROMPT = (
+    "You are a helpful, accurate, and friendly AI assistant. "
+    "Answer clearly, use Markdown when helpful, and admit uncertainty when needed."
+)
+
+MODEL_CHOICES = [
+    "openai/gpt-oss-20b",
+    "openai/gpt-oss-120b",
+]
+
+CUSTOM_CSS = """
+.gradio-container {
+    max-width: 1050px !important;
+    margin: 0 auto !important;
+}
+#app-header {
+    text-align: center;
+    padding: 12px 0 4px 0;
+}
+#app-subtitle {
+    text-align: center;
+    opacity: 0.8;
+    margin-bottom: 10px;
+}
+footer {
+    display: none !important;
+}
+"""
+
+
+def _text_history(history: list[dict[str, Any]]) -> list[dict[str, str]]:
+    """Keep only plain-text user and assistant messages for the Groq API."""
+    cleaned: list[dict[str, str]] = []
+
+    for item in history or []:
+        role = item.get("role")
+        content = item.get("content")
+
+        if role in {"user", "assistant"} and isinstance(content, str):
+            cleaned.append({"role": role, "content": content})
+
+    return cleaned
+
+
+def chat_with_groq(
+    message: str,
+    history: list[dict[str, Any]],
+    model: str,
+    system_prompt: str,
+    temperature: float,
+    max_tokens: int,
+) -> Generator[str, None, None]:
+    """Stream a Groq response to the Gradio chat interface."""
+    api_key = os.getenv("GROQ_API_KEY")
+
+    if not api_key:
+        yield (
+            "### Missing API key\n\n"
+            "Add a Hugging Face Space secret named `GROQ_API_KEY`, then restart the Space."
+        )
+        return
+
+    user_message = (message or "").strip()
+    if not user_message:
+        yield "Please enter a message."
+        return
+
+    selected_model = model if model in MODEL_CHOICES else MODEL_CHOICES[0]
+    instructions = (system_prompt or "").strip() or DEFAULT_SYSTEM_PROMPT
+
+    messages: list[dict[str, str]] = [
+        {"role": "system", "content": instructions},
+        *_text_history(history),
+        {"role": "user", "content": user_message},
+    ]
+
+    try:
+        client = Groq(api_key=api_key)
+        stream = client.chat.completions.create(
+            model=selected_model,
+            messages=messages,
+            temperature=float(temperature),
+            max_completion_tokens=int(max_tokens),
+            stream=True,
+        )
+
+        response = ""
+        for chunk in stream:
+            delta = chunk.choices[0].delta.content
+            if delta:
+                response += delta
+                yield response
+
+        if not response:
+            yield "The model returned an empty response. Please try again."
+
+    except Exception as error:
+        # Show a useful message without exposing the API key or other secrets.
+        error_name = type(error).__name__
+        yield (
+            "### Request failed\n\n"
+            f"`{error_name}`: {error}\n\n"
+            "Check your Groq API key, model access, account limits, and network connection."
+        )
+
+
+with gr.Blocks(title="Groq AI Chat") as demo:
+    gr.Markdown("# ⚡ Groq AI Chat", elem_id="app-header")
+    gr.Markdown(
+        "A fast, streaming chatbot powered by Groq and built with Gradio.",
+        elem_id="app-subtitle",
+    )
+
+    with gr.Accordion("Chat settings", open=False):
+        model_input = gr.Dropdown(
+            choices=MODEL_CHOICES,
+            value=MODEL_CHOICES[0],
+            label="Groq model",
+            info="GPT-OSS 20B is faster; GPT-OSS 120B is stronger for complex tasks.",
+        )
+        system_prompt_input = gr.Textbox(
+            value=DEFAULT_SYSTEM_PROMPT,
+            label="System prompt",
+            lines=3,
+        )
+        with gr.Row():
+            temperature_input = gr.Slider(
+                minimum=0.0,
+                maximum=2.0,
+                value=0.7,
+                step=0.1,
+                label="Temperature",
+            )
+            max_tokens_input = gr.Slider(
+                minimum=128,
+                maximum=4096,
+                value=1024,
+                step=128,
+                label="Maximum response tokens",
+            )
+
+    chatbot = gr.Chatbot(
+        label="Conversation",
+        placeholder="Ask anything to begin the conversation.",
+        height=520,
+    )
+
+    gr.ChatInterface(
+        fn=chat_with_groq,
+        chatbot=chatbot,
+        additional_inputs=[
+            model_input,
+            system_prompt_input,
+            temperature_input,
+            max_tokens_input,
+        ],
+        examples=[
+            [
+                "Explain artificial intelligence in simple words.",
+                MODEL_CHOICES[0],
+                DEFAULT_SYSTEM_PROMPT,
+                0.7,
+                1024,
+            ],
+            [
+                "Write a professional email requesting a meeting.",
+                MODEL_CHOICES[0],
+                DEFAULT_SYSTEM_PROMPT,
+                0.7,
+                1024,
+            ],
+            [
+                "Create a beginner-friendly Python learning plan.",
+                MODEL_CHOICES[1],
+                DEFAULT_SYSTEM_PROMPT,
+                0.5,
+                1536,
+            ],
+        ],
+        editable=True,
+        save_history=True,
+        flagging_mode="never",
+        api_visibility="private",
+        concurrency_limit=5,
+        fill_height=True,
+        fill_width=True,
+    )
+
+
+if __name__ == "__main__":
+    demo.queue(default_concurrency_limit=5).launch(
+        theme=gr.themes.Soft(),
+        css=CUSTOM_CSS,
+    )