app.py

# main.py

import os
import json
import uuid
import gradio as gr

from google import genai
from google.genai import types
from google.genai.types import Tool, GoogleSearch
from huggingface_hub import create_repo, HfApi

# ——— Configuration ———
MODEL_ID = "gemini-2.5-flash-preview-04-17"
WORKSPACE_DIR = "workspace"
SYSTEM_INSTRUCTION = (
    "You are a helpful coding assistant that scaffolds a complete Hugging Face Space app. "
    "Based on the user's request, decide between Gradio or Streamlit (whichever fits best), "
    "and respond with exactly one JSON object with keys:\n"
    "  • \"framework\": either \"gradio\" or \"streamlit\"\n"
    "  • \"files\": a map of relative file paths to file contents\n"
    "  • \"message\": a human-readable summary\n"
    "Do not include extra text or markdown."
)

# In-memory session store: maps session IDs to state dicts
state_store = {}


def start_app(gemini_key, hf_token, hf_username, repo_name):
    os.makedirs(WORKSPACE_DIR, exist_ok=True)
    client = genai.Client(api_key=gemini_key)
    config = types.GenerateContentConfig(system_instruction=SYSTEM_INSTRUCTION)
    tools = [Tool(google_search=GoogleSearch())]
    chat = client.chats.create(model=MODEL_ID, config=config, tools=tools)

    local_path = os.path.join(WORKSPACE_DIR, repo_name)
    os.makedirs(local_path, exist_ok=True)

    state = {
        "chat": chat,
        "hf_token": hf_token,
        "hf_username": hf_username,
        "repo_name": repo_name,
        "created": False,
        "repo_id": None,
        "local_path": local_path,
        "logs": [f"Initialized workspace at {WORKSPACE_DIR}/{repo_name}."],
    }
    return state


def handle_message(user_msg, state):
    chat = state["chat"]
    logs = state.get("logs", [])
    logs.append(f"> User: {user_msg}")

    resp = chat.send_message(user_msg)
    logs.append("Received response from Gemini.")
    text = resp.text

    try:
        data = json.loads(text)
        framework = data["framework"]
        files = data.get("files", {})
        reply_msg = data.get("message", "")
    except Exception:
        logs.append("⚠️ Failed to parse assistant JSON.\n" + text)
        state["logs"] = logs
        return "⚠️ Parsing error. Check logs.", state

    if not state["created"]:
        full_repo = f"{state['hf_username']}/{state['repo_name']}"
        logs.append(f"Creating HF Space '{full_repo}' with template '{framework}'.")
        create_repo(
            repo_id=full_repo,
            token=state["hf_token"],
            exist_ok=True,
            repo_type="space",
            space_sdk=framework
        )
        state["created"] = True
        state["repo_id"] = full_repo
        state["embed_url"] = f"https://huggingface.co/spaces/{full_repo}"

    if files:
        logs.append(f"Writing {len(files)} file(s): {list(files.keys())}")
        for relpath, content in files.items():
            dest = os.path.join(state["local_path"], relpath)
            os.makedirs(os.path.dirname(dest), exist_ok=True)
            with open(dest, "w", encoding="utf-8") as f:
                f.write(content)

    logs.append("Uploading snapshot to Hugging Face...")
    api = HfApi(token=state["hf_token"])
    api.upload_folder(
        folder_path=state["local_path"],
        repo_id=state["repo_id"],
        repo_type="space"
    )
    logs.append("Snapshot upload complete.")

    state["logs"] = logs
    return reply_msg, state


# ——— Gradio UI ———
with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column(scale=1):
            gemini_key = gr.Textbox(label="Gemini API Key", type="password")
            hf_token   = gr.Textbox(label="Hugging Face Token", type="password")
            hf_user    = gr.Textbox(label="HF Username")
            repo_name  = gr.Textbox(label="New App (repo) name")
            session_id = gr.Textbox(value="", visible=False)
            start_btn  = gr.Button("Start a new app")

        with gr.Column(scale=3):
            chatbot = gr.Chatbot(type="messages")
            logs_display   = gr.Textbox(label="Operation Logs", interactive=False, lines=8)
            preview_iframe = gr.HTML("<p>No deployed app yet.</p>")

            user_msg = gr.Textbox(label="Your message")
            send_btn = gr.Button("Send")

    def on_start(g_key, h_token, h_user, r_name):
        new_id = str(uuid.uuid4())
        state = start_app(g_key, h_token, h_user, r_name)
        state_store[new_id] = state
        logs = "\n".join(state["logs"])
        return new_id, logs, "<p>Awaiting first instruction...</p>"

    start_btn.click(
        on_start,
        inputs=[gemini_key, hf_token, hf_user, repo_name],
        outputs=[session_id, logs_display, preview_iframe]
    )

    def on_send(msg, chat_history, sess_id):
        if not sess_id or sess_id not in state_store:
            err = "Error: No API found. Please start a new app."
            return chat_history + [("", err)], sess_id, "", ""
        state = state_store[sess_id]
        reply, new_state = handle_message(msg, state)
        state_store[sess_id] = new_state
        chat_history = chat_history + [(msg, reply)]
        logs = "\n".join(new_state.get("logs", []))
        embed = ""
        if new_state.get("embed_url"):
            embed = f'<iframe src="{new_state["embed_url"]}" width="100%" height="500px"></iframe>'
        return chat_history, sess_id, logs, embed

    send_btn.click(
        on_send,
        inputs=[user_msg, chatbot, session_id],
        outputs=[chatbot, session_id, logs_display, preview_iframe]
    )
    user_msg.submit(
        on_send,
        inputs=[user_msg, chatbot, session_id],
        outputs=[chatbot, session_id, logs_display, preview_iframe]
    )

    demo.launch()