import gradio as gr
from huggingface_hub import InferenceClient

AGENT_NAME    = "Test-subject"
MODEL_ID      = "mistralai/Mistral-7B-Instruct-v0.3"
SYSTEM_PROMPT = "You are Test-subject, a helpful AI assistant powered by mistralai/Mistral-7B-Instruct-v0.3. Be friendly, concise, and helpful."
BRIDGE        = ['🤗 Hugging Face']

client = InferenceClient(model=MODEL_ID)

def chat(message, history):
    msgs = [{"role": "system", "content": SYSTEM_PROMPT}]
    for h in history:
        msgs.append({"role": "user",      "content": h[0]})
        msgs.append({"role": "assistant", "content": h[1]})
    msgs.append({"role": "user", "content": message})
    response = ""
    for chunk in client.chat_completion(messages=msgs, max_tokens=1024, stream=True):
        delta = chunk.choices[0].delta.content
        if delta:
            response += delta
            yield response

bridge_note = ("\n\n🌉 **Bridge Connect:** " + " · ".join(BRIDGE)) if BRIDGE else ""

demo = gr.ChatInterface(
    fn=chat,
    title=f"💬 {AGENT_NAME}",
    description=f"Your personal AI agent powered by `{MODEL_ID}`.{bridge_note}",
    examples=["Hello! What can you do?", "Tell me something interesting.", "Help me brainstorm ideas."],
)

if __name__ == "__main__":
    demo.launch()