app.py

import os
import re
import time
import json
import io
import requests

import gradio as gr
import google.generativeai as genai

from huggingface_hub import create_repo, list_models, upload_file, constants
from huggingface_hub.utils import build_hf_headers, get_session, hf_raise_for_status

# --- Helper functions for Hugging Face integration ---

def show_profile(profile: gr.OAuthProfile | None) -> str:
    if profile is None:
        return "*Not logged in.*"
    return f"✅ Logged in as **{profile.username}**"

def list_private_models(
    profile: gr.OAuthProfile | None,
    oauth_token: gr.OAuthToken | None
) -> str:
    if profile is None or oauth_token is None:
        return "Please log in to see your models."
    try:
        models = [
            f"{m.id} ({'private' if m.private else 'public'})"
            for m in list_models(author=profile.username, token=oauth_token.token)
        ]
        return "No models found." if not models else "Models:\n\n" + "\n - ".join(models)
    except Exception as e:
        return f"Error listing models: {e}"

def create_space_action(repo_name: str, sdk: str, profile: gr.OAuthProfile, token: gr.OAuthToken):
    repo_id = f"{profile.username}/{repo_name}"
    try:
        create_repo(
            repo_id=repo_id,
            token=token.token,
            exist_ok=True,
            repo_type="space",
            space_sdk=sdk
        )
        url    = f"https://huggingface.co/spaces/{repo_id}"
        iframe = f'<iframe src="{url}" width="100%" height="500px"></iframe>'
        return repo_id, iframe
    except Exception as e:
        raise RuntimeError(f"Failed to create Space {repo_id}: {e}")

def upload_file_to_space_action(
    file_obj,
    path_in_repo: str,
    repo_id: str,
    profile: gr.OAuthProfile,
    token: gr.OAuthToken
) -> None:
    if not (profile and token and repo_id):
        raise ValueError("Hugging Face profile, token, or repo_id is missing.")
    try:
        upload_file(
            path_or_fileobj=file_obj,
            path_in_repo=path_in_repo,
            repo_id=repo_id,
            token=token.token,
            repo_type="space"
        )
    except Exception as e:
        raise RuntimeError(f"Failed to upload `{path_in_repo}` to {repo_id}: {e}")

def _fetch_space_logs_level(repo_id: str, level: str, token: str) -> str:
    if not repo_id or not token:
         return f"Cannot fetch {level} logs: repo_id or token missing."
    jwt_url  = f"{constants.ENDPOINT}/api/spaces/{repo_id}/jwt"
    try:
        r        = get_session().get(jwt_url, headers=build_hf_headers(token=token))
        hf_raise_for_status(r)
        jwt      = r.json()["token"]
        logs_url = f"https://api.hf.space/v1/{repo_id}/logs/{level}"
        lines, count = [], 0
        with get_session().get(logs_url, headers=build_hf_headers(token=jwt), stream=True, timeout=30) as resp:
            hf_raise_for_status(resp)
            for raw in resp.iter_lines():
                if count >= 200:
                    lines.append("... truncated ...")
                    break
                if not raw.startswith(b"data: "):
                    continue
                payload = raw[len(b"data: "):]
                try:
                    event = json.loads(payload.decode())
                    ts    = event.get("timestamp", "")
                    txt   = event.get("data", "").strip()
                    if txt:
                        lines.append(f"[{ts}] {txt}")
                        count += 1
                except json.JSONDecodeError:
                    continue
        return "\n".join(lines) if lines else f"No {level} logs found."
    except Exception as e:
        return f"Error fetching {level} logs: {e}"


def get_build_logs_action(repo_id, profile, token):
    if not (repo_id and profile and token):
        return "⚠️ Cannot fetch build logs: log in and create a Space first."
    time.sleep(5)
    return _fetch_space_logs_level(repo_id, "build", token.token)

def get_container_logs_action(repo_id, profile, token):
    if not (repo_id and profile and token):
        return "⚠️ Cannot fetch container logs: log in and create a Space first."
    time.sleep(10)
    return _fetch_space_logs_level(repo_id, "run", token.token)


# --- Google Gemini integration with model selection ---

def configure_gemini(api_key: str | None, model_name: str | None) -> str:
    if not api_key:
        return "Gemini API key is not set."
    if not model_name:
        return "Please select a Gemini model."
    try:
        genai.configure(api_key=api_key)
        genai.GenerativeModel(model_name).generate_content("ping", stream=False)
        return f"Gemini configured successfully with **{model_name}**."
    except Exception as e:
        return f"Error configuring Gemini: {e}"

def call_gemini(prompt: str, api_key: str, model_name: str) -> str:
    if not api_key or not model_name:
        raise ValueError("Gemini API key or model not set.")
    try:
        genai.configure(api_key=api_key)
        model = genai.GenerativeModel(model_name)
        response = model.generate_content(prompt, stream=False)
        return response.text or ""
    except Exception as e:
        raise RuntimeError(f"Gemini API call failed: {e}")


# --- AI workflow logic (State Machine) ---

# Define States
STATE_IDLE = "idle"
STATE_AWAITING_REPO_NAME = "awaiting_repo_name"
STATE_CREATING_SPACE = "creating_space"
STATE_GENERATING_CODE = "generating_code"
STATE_UPLOADING_APP_PY = "uploading_app_py"
STATE_GENERATING_REQUIREMENTS = "generating_requirements"
STATE_UPLOADING_REQUIREMENTS = "uploading_requirements"
STATE_GENERATING_README = "generating_readme"
STATE_UPLOADING_README = "uploading_readme"
STATE_CHECKING_LOGS_BUILD = "checking_logs_build"
STATE_CHECKING_LOGS_RUN = "checking_logs_run"
STATE_DEBUGGING_CODE = "debugging_code"
STATE_UPLOADING_FIXED_APP_PY = "uploading_fixed_app_py"
STATE_COMPLETE = "complete"

MAX_DEBUG_ATTEMPTS = 3

def add_bot_message(history: list[dict], bot_message: str) -> list[dict]:
    """Helper to add a new assistant message to the history."""
    history.append({"role": "assistant", "content": bot_message})
    return history

def ai_workflow_chat(
    message: str,
    history: list[dict],
    hf_profile: gr.OAuthProfile | None,
    hf_token:   gr.OAuthToken   | None,
    gemini_api_key: str         | None,
    gemini_model:   str         | None,
    repo_id_state:  str | None,
    workflow_state: str,
    space_sdk:      str,
    preview_html:   str,
    container_logs: str,
    build_logs:     str,
    debug_attempts_state: int,
    app_description_state: str | None,
    repo_name_state: str | None,
    generated_code_state: str | None,
    *args,
    **kwargs
) -> tuple[
    list[dict],
    str | None,
    str,
    str,
    str,
    str,
    int,
    str | None,
    str | None,
    str | None,
]:
    # Unpack state variables
    repo_id = repo_id_state
    state = workflow_state
    attempts = debug_attempts_state
    app_desc = app_description_state
    repo_name = repo_name_state
    generated_code = generated_code_state


    updated_preview = preview_html
    updated_build = build_logs
    updated_run = container_logs

    # Add user message to history in the new format
    user_message_entry = {"role": "user", "content": message}
    if hf_profile and hf_profile.username:
         user_message_entry["name"] = hf_profile.username
    history.append(user_message_entry)

    # Yield immediately to show user message
    yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


    try:
        # --- State Machine Logic ---

        if state == STATE_IDLE:
            # Check prerequisites within the state logic as well
            if not (hf_profile and hf_token):
                history = add_bot_message(history, "Workflow paused: Please log in to Hugging Face first.")
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code
                return
            if not (gemini_api_key and gemini_model):
                 history = add_bot_message(history, "Workflow paused: Please enter your API key and select a Gemini model.")
                 yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code
                 return

            # Look for commands
            reset_match = "reset" in message.lower()
            generate_match = re.search(r'generate (?:me )?(?:a|an) \w+ app called (\w+)', message, re.I)
            create_match = re.search(r'create (?:a|an)? space called (\w+)', message, re.I)

            if reset_match:
                history = add_bot_message(history, "Workflow reset.")
                yield history, None, STATE_IDLE, "<p>No Space created yet.</p>", "", "", 0, None, None, None
                return

            elif generate_match:
                new_repo_name = generate_match.group(1)
                new_app_desc = message
                history = add_bot_message(history, f"Acknowledged: '{message}'. Starting workflow to create Space `{hf_profile.username}/{new_repo_name}`.")
                state = STATE_CREATING_SPACE
                repo_name = new_repo_name
                app_desc = new_app_desc
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


            elif create_match:
                 new_repo_name = create_match.group(1)
                 history = add_bot_message(history, f"Acknowledged: '{message}'. Starting workflow to create Space `{hf_profile.username}/{new_repo_name}`.")
                 state = STATE_CREATING_SPACE
                 repo_name = new_repo_name
                 yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            elif "create" in message.lower() and not repo_id:
                history = add_bot_message(history, "Okay, what should the Space be called? (e.g., `my-awesome-app`)")
                state = STATE_AWAITING_REPO_NAME
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            else:
                history = add_bot_message(history, "Command not recognized. Try 'generate me a gradio app called myapp', or 'reset'.")
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code
                return


        if state == STATE_AWAITING_REPO_NAME:
            new_repo_name = message.strip()
            if not new_repo_name or re.search(r'[^a-zA-Z0-9_-]', new_repo_name):
                 history = add_bot_message(history, "Invalid name. Please provide a single word/slug for the Space name (letters, numbers, underscores, hyphens only).")
                 yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code
            else:
                history = add_bot_message(history, f"Using Space name `{new_repo_name}`. Creating Space `{hf_profile.username}/{new_repo_name}`...")
                state = STATE_CREATING_SPACE
                repo_name = new_repo_name
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


        elif state == STATE_CREATING_SPACE:
            if not repo_name:
                history = add_bot_message(history, "Internal error: Repo name missing for creation. Resetting.")
                yield history, None, STATE_IDLE, "<p>Error creating space.</p>", "", "", 0, None, None, None
                return

            try:
                new_repo_id, iframe_html = create_space_action(repo_name, space_sdk, hf_profile, hf_token)
                updated_preview = iframe_html
                repo_id = new_repo_id
                history = add_bot_message(history, f"✅ Space `{repo_id}` created. Click 'Send' to generate and upload code.")
                state = STATE_GENERATING_CODE
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            except Exception as e:
                history = add_bot_message(history, f"❌ Error creating space: {e}. Click 'reset'.")
                yield history, None, STATE_IDLE, "<p>Error creating space.</p>", "", "", 0, None, None, None


        elif state == STATE_GENERATING_CODE:
            prompt_desc = app_desc if app_desc else 'a Gradio image-blur test app with upload and slider controls'
            prompt = f"""
You are an AI assistant specializing in Hugging Face Spaces using the {space_sdk} SDK.
Generate a full, single-file Python app based on:
'{prompt_desc}'
Return **only** the python code block for app.py. Do not include any extra text, explanations, or markdown outside the code block.
"""
            try:
                history = add_bot_message(history, "🧠 Generating `app.py` code with Gemini...")
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

                code = call_gemini(prompt, gemini_api_key, gemini_model)
                code = code.strip()
                if code.startswith("```python"):
                    code = code[len("```python"):].strip()
                if code.endswith("```"):
                    code = code[:-len("```")].strip()

                if not code:
                     raise ValueError("Gemini returned empty code.")

                history = add_bot_message(history, "✅ `app.py` code generated. Click 'Send' to upload.")
                state = STATE_UPLOADING_APP_PY
                generated_code = code
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            except Exception as e:
                history = add_bot_message(history, f"❌ Error generating code: {e}. Click 'reset'.")
                yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None


        elif state == STATE_UPLOADING_APP_PY:
            if not generated_code:
                 history = add_bot_message(history, "Internal error: No code to upload. Resetting.")
                 yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None
                 return

            history = add_bot_message(history, "☁️ Uploading `app.py`...")
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            try:
                upload_file_to_space_action(io.StringIO(generated_code), "app.py", repo_id, hf_profile, hf_token)
                history = add_bot_message(history, "✅ Uploaded `app.py`. Click 'Send' to generate requirements.")
                state = STATE_GENERATING_REQUIREMENTS
                generated_code = None
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            except Exception as e:
                history = add_bot_message(history, f"❌ Error uploading app.py: {e}. Click 'reset'.")
                yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None


        elif state == STATE_GENERATING_REQUIREMENTS:
            history = add_bot_message(history, "📄 Generating `requirements.txt`...")
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            reqs_list = ["gradio"] if space_sdk == "gradio" else ["streamlit"]
            if "google.generativeai" in str(app_desc).lower() or "gemini" in str(app_desc).lower() or gemini_api_key:
                 reqs_list.append("google-generativeai")
            if "requests" in str(app_desc).lower():
                 reqs_list.append("requests")
            reqs_list.append("huggingface_hub")
            if "image" in str(app_desc).lower() or "upload" in str(app_desc).lower() or "blur" in str(app_desc).lower() or "vision" in str(app_desc).lower():
                reqs_list.append("Pillow")
            if "numpy" in str(app_desc).lower(): reqs_list.append("numpy")
            if "pandas" in str(app_desc).lower(): reqs_list.append("pandas")
            if "scikit-image" in str(app_desc).lower() or "skimage" in str(app_desc).lower() or "cv2" in str(app_desc).lower() or "opencv-python" in str(app_desc).lower():
                 reqs_list.append("scikit-image")
                 reqs_list.append("opencv-python")

            reqs_list = list(dict.fromkeys(reqs_list))

            reqs_content = "\n".join(reqs_list) + "\n"

            history = add_bot_message(history, "✅ `requirements.txt` generated. Click 'Send' to upload.")
            state = STATE_UPLOADING_REQUIREMENTS
            generated_code = reqs_content
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


        elif state == STATE_UPLOADING_REQUIREMENTS:
            reqs_content_to_upload = generated_code
            if not reqs_content_to_upload:
                 history = add_bot_message(history, "Internal error: No requirements content to upload. Resetting.")
                 yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None
                 return

            history = add_bot_message(history, "☁️ Uploading `requirements.txt`...")
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            try:
                upload_file_to_space_action(io.StringIO(reqs_content_to_upload), "requirements.txt", repo_id, hf_profile, hf_token)
                history = add_bot_message(history, "✅ Uploaded `requirements.txt`. Click 'Send' to generate README.")
                state = STATE_GENERATING_README
                generated_code = None
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


            except Exception as e:
                history = add_bot_message(history, f"❌ Error uploading requirements.txt: {e}. Click 'reset'.")
                yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None

        elif state == STATE_GENERATING_README:
            history = add_bot_message(history, "📝 Generating `README.md`...")
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            readme_title = repo_name if repo_name else "My Awesome Space"
            readme_description = app_desc if app_desc else f"This Hugging Face Space hosts an AI-generated {space_sdk} application."

            readme_content = f"# {readme_title}\n\n{readme_description}\n\n" \
                             "This Space was automatically generated by an AI workflow.\n\n" \
                             f"Built with the {space_sdk} SDK.\n"

            history = add_bot_message(history, "✅ `README.md` generated. Click 'Send' to upload.")
            state = STATE_UPLOADING_README
            generated_code = readme_content
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


        elif state == STATE_UPLOADING_README:
            readme_content_to_upload = generated_code
            if not readme_content_to_upload:
                 history = add_bot_message(history, "Internal error: No README content to upload. Resetting.")
                 yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None
                 return

            history = add_bot_message(history, "☁️ Uploading `README.md`...")
            yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

            try:
                upload_file_to_space_action(io.StringIO(readme_content_to_upload), "README.md", repo_id, hf_profile, hf_token)
                history = add_bot_message(history, "✅ Uploaded `README.md`. All files uploaded. Space is now building. Click 'Send' to check build logs.")
                state = STATE_CHECKING_LOGS_BUILD
                generated_code = None
                yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


            except Exception as e:
                history = add_bot_message(history, f"❌ Error uploading README.md: {e}. Click 'reset'.")
                yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None


        elif state == STATE_CHECKING_LOGS_BUILD:
             history = add_bot_message(history, "🔍 Fetching build logs...")
             yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             build_logs_text = get_build_logs_action(repo_id, hf_profile, hf_token)
             updated_build = build_logs_text

             if "Error" in updated_build or "Exception" in updated_build or "Build failed" in updated_build:
                  history = add_bot_message(history, "⚠️ Build logs indicate potential issues. Please inspect above. Click 'Send' to check container logs (app might still start).")
                  state = STATE_CHECKING_LOGS_RUN
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             else:
                  history = add_bot_message(history, "✅ Build logs fetched. Click 'Send' to check container logs.")
                  state = STATE_CHECKING_LOGS_RUN
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


        elif state == STATE_CHECKING_LOGS_RUN:
             history = add_bot_message(history, "🔍 Fetching container logs...")
             yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             container_logs_text = get_container_logs_action(repo_id, hf_profile, hf_token)
             updated_run = container_logs_text

             if ("Error" in updated_run or "Exception" in updated_run) and attempts < MAX_DEBUG_ATTEMPTS:
                  attempts += 1
                  history = add_bot_message(history, f"❌ Errors detected in container logs. Attempting debug fix #{attempts}/{MAX_DEBUG_ATTEMPTS}. Click 'Send' to proceed.")
                  state = STATE_DEBUGGING_CODE
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             elif ("Error" in updated_run or "Exception" in updated_run) and attempts >= MAX_DEBUG_ATTEMPTS:
                  history = add_bot_message(history, f"❌ Errors detected in container logs. Max debug attempts ({MAX_DEBUG_ATTEMPTS}) reached. Please inspect logs manually or click 'reset'.")
                  state = STATE_COMPLETE
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             else:
                  history = add_bot_message(history, "✅ App appears to be running successfully! Check the iframe above. Click 'reset' to start a new project.")
                  state = STATE_COMPLETE
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


        elif state == STATE_DEBUGGING_CODE:
             history = add_bot_message(history, f"🧠 Calling Gemini to generate fix based on logs...")
             yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             debug_prompt = f"""
You are debugging a {space_sdk} Space. The goal is to fix the code in `app.py` based on the container logs provided.

Here are the container logs:
{updated_run}

Generate the *complete, fixed* content for `app.py` based on these logs.
Return **only** the python code block for app.py. Do not include any extra text, explanations, or markdown outside the code block.
"""
             try:
                  fix_code = call_gemini(debug_prompt, gemini_api_key, gemini_model)
                  fix_code = fix_code.strip()
                  if fix_code.startswith("```python"):
                      fix_code = fix_code[len("```python"):].strip()
                  if fix_code.endswith("```"):
                      fix_code = fix_code[:-len("```")].strip()

                  if not fix_code:
                     raise ValueError("Gemini returned empty fix code.")

                  history = add_bot_message(history, "✅ Fix code generated. Click 'Send' to upload.")
                  state = STATE_UPLOADING_FIXED_APP_PY
                  generated_code = fix_code
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


             except Exception as e:
                  history = add_bot_message(history, f"❌ Error generating debug code: {e}. Click 'reset'.")
                  yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None

        elif state == STATE_UPLOADING_FIXED_APP_PY:
             fixed_code_to_upload = generated_code
             if not fixed_code_to_upload:
                  history = add_bot_message(history, "Internal error: No fixed code available to upload. Resetting.")
                  yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None
                 return

             history = add_bot_message(history, "☁️ Uploading fixed `app.py`...")
             yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code

             try:
                  upload_file_to_space_action(io.StringIO(fixed_code_to_upload), "app.py", repo_id, hf_profile, hf_token)
                  history = add_bot_message(history, "✅ Fixed `app.py` uploaded. Space will rebuild. Click 'Send' to check logs again.")
                  state = STATE_CHECKING_LOGS_RUN
                  generated_code = None
                  yield history, repo_id, state, updated_preview, updated_run, updated_build, attempts, app_desc, repo_name, generated_code


             except Exception as e:
                  history = add_bot_message(history, f"❌ Error uploading fixed app.py: {e}. Click 'reset'.")
                  yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None

        elif state == STATE_COMPLETE:
             pass


    except Exception as e:
        error_message = f"Workflow step failed unexpectedly ({state}): {e}. Click 'Send' to re-attempt this step or 'reset'."
        history = add_bot_message(history, error_message)
        print(f"Critical Error in state {state}: {e}")
        yield history, None, STATE_IDLE, updated_preview, updated_run, updated_build, 0, None, None, None
        return


# --- Build the Gradio UI ---

with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
    # State variables
    hf_profile   = gr.State(None)
    hf_token     = gr.State(None)
    gemini_key   = gr.State(None)
    gemini_model = gr.State("gemini-1.5-flash")
    repo_id      = gr.State(None)
    workflow     = gr.State(STATE_IDLE)
    sdk_state    = gr.State("gradio")
    debug_attempts = gr.State(0)
    app_description = gr.State(None)
    repo_name_state = gr.State(None)
    generated_code_state = gr.State(None)

    with gr.Row():
        # Sidebar
        with gr.Column(scale=1, min_width=300):
            gr.Markdown("## Hugging Face Login")
            login_status = gr.Markdown("*Not logged in.*")
            login_btn    = gr.LoginButton(variant="huggingface")

            # Initial load to check login status
            ai_builder_tab.load(show_profile, outputs=login_status)
            # Update status on login click
            login_btn.click(show_profile, outputs=login_status)

            gr.Markdown("## Google AI Studio API Key")
            gemini_input  = gr.Textbox(label="API Key", type="password", interactive=True)
            gemini_status = gr.Markdown("")

            gr.Markdown("## Gemini Model")
            model_selector = gr.Radio(
                choices=[
                    ("Gemini 1.5 Flash", "gemini-1.5-flash"),
                    ("Gemini 1.5 Pro", "gemini-1.5-pro"),
                    ("Gemini 1.0 Pro", "gemini-1.0-pro"),
                ],
                value="gemini-1.5-flash",
                label="Select model",
                interactive=True
            )

            # Configure Gemini status on load
            ai_builder_tab.load(
                configure_gemini,
                inputs=[gemini_key, gemini_model],
                outputs=[gemini_status]
            )

            gr.Markdown("## Space SDK")
            sdk_selector = gr.Radio(choices=["gradio","streamlit"], value="gradio", label="Template SDK", interactive=True)
            sdk_selector.change(lambda s: s, inputs=sdk_selector, outputs=sdk_state)

            gr.Markdown("## Workflow Status")
            status_text = gr.Textbox(label="Current State", value=STATE_IDLE, interactive=False)
            repo_id_text = gr.Textbox(label="Current Space ID", value="None", interactive=False)

            # --- Debugging Indicator ---
            prereq_status = gr.Markdown("Checking...")


        # Main content
        with gr.Column(scale=3):
            chatbot    = gr.Chatbot(type='messages', label="AI Workflow Chat")
            user_input = gr.Textbox(placeholder="Type your message…", interactive=True)
            send_btn   = gr.Button("Send", interactive=False)

            # Logic to enable send button only when logged in and API key is set
            def update_send_button_state(profile: gr.OAuthProfile | None, token: gr.OAuthToken | None, key: str | None, model: str | None, *args, **kwargs):
                """
                Gradio sometimes passes extra positional/keyword args (old_value, event, etc.),
                so we absorb them with *args/**kwargs.
                Returns Gradio.update for the button's interactive state and a status string.
                """
                is_logged_in    = profile is not None and token is not None
                is_gemini_ready = key     is not None and model is not None

                # Print states for debugging
                print(f"update_send_button_state called:")
                print(f"  Profile: {profile.username if profile else None}")
                print(f"  Token: {'Set' if token else 'None'}")
                print(f"  API Key: {'Set' if key else 'None'}")
                print(f"  Model: {model}")
                print(f"  Logged in: {is_logged_in}, Gemini Ready: {is_gemini_ready}")

                status_str = ""
                if is_logged_in and is_gemini_ready:
                    status_str = "✅ Ready to send commands."
                else: # Consolidated status checks
                     status_parts = []
                     if not is_logged_in:
                         status_parts.append("⚠️ Not logged in to Hugging Face.")
                     if not key:
                         status_parts.append("⚠️ Gemini API key not set.")
                     if not model:
                          status_parts.append("⚠️ Gemini model not selected.")
                     status_str = " ".join(status_parts)
                     if not status_str: # Should be ready if status_parts is empty
                          status_str = "✅ Ready to send commands."


                return gr.update(interactive=is_logged_in and is_gemini_ready), status_str

            # --- Implement Chained Events ---

            # 1. Login Button: Update profile/token state, THEN update send button state
            login_btn.click(
                 lambda x: (x[0], x[1]), # Extract profile and token from LoginButton output
                 inputs=[login_btn],
                 outputs=[hf_profile, hf_token]
            ).then( # Chain the next action after state is updated
                 update_send_button_state,
                 inputs=[hf_profile, hf_token, gemini_key, gemini_model],
                 outputs=[send_btn, prereq_status]
            )


            # 2. Gemini Key Input: Update key state, THEN configure Gemini, THEN update send button state
            gemini_input.change(
                lambda k: k, # Update gemini_key state
                inputs=[gemini_input],
                outputs=[gemini_key]
            ).then( # Chain configure_gemini after key is updated
                configure_gemini,
                inputs=[gemini_key, gemini_model],
                outputs=[gemini_status]
            ).then( # Chain update_send_button_state after config status is updated
                update_send_button_state,
                inputs=[hf_profile, hf_token, gemini_key, gemini_model],
                outputs=[send_btn, prereq_status]
            )


            # 3. Gemini Model Selector: Update model state, THEN configure Gemini, THEN update send button state
            model_selector.change(
                lambda m: m, # Update gemini_model state
                inputs=[model_selector],
                outputs=[gemini_model]
            ).then( # Chain configure_gemini after model is updated
                configure_gemini,
                inputs=[gemini_key, gemini_model],
                outputs=[gemini_status]
            ).then( # Chain update_send_button_state after config status is updated
                update_send_button_state,
                inputs=[hf_profile, hf_token, gemini_key, gemini_model],
                outputs=[send_btn, prereq_status]
            )

            # 4. Initial Load: Update send button state based on initial (or cached) state
            ai_builder_tab.load(
                update_send_button_state,
                inputs=[hf_profile, hf_token, gemini_key, gemini_model],
                outputs=[send_btn, prereq_status]
            )


            iframe    = gr.HTML("<p>No Space created yet.</p>")
            build_txt = gr.Textbox(label="Build Logs", lines=10, interactive=False, value="")
            run_txt   = gr.Textbox(label="Container Logs", lines=10, interactive=False, value="")

            # The main event handler for the Send button
            send_btn.click(
                ai_workflow_chat,
                inputs=[
                    user_input, chatbot,
                    hf_profile, hf_token,
                    gemini_key, gemini_model,
                    repo_id, workflow, sdk_state,
                    iframe, run_txt, build_txt,
                    debug_attempts, app_description, repo_name_state, generated_code_state
                ],
                outputs=[
                    chatbot,
                    repo_id, workflow,
                    iframe, run_txt, build_txt,
                    debug_attempts, app_description, repo_name_state, generated_code_state
                ]
            ).success(
                 lambda: gr.update(value=""),
                 inputs=None,
                 outputs=user_input
            )

            # Link state variables to UI status displays (reactive updates)
            workflow.change(lambda s: s, inputs=workflow, outputs=status_text)
            repo_id.change(lambda r: r if r else "None", inputs=repo_id, outputs=repo_id_text)


    # Add an initial message to the chatbot on load
    def greet():
        return [{"role": "assistant", "content": "Welcome! Please log in to Hugging Face and provide your Google AI Studio API key to start building Spaces. Once ready, type 'generate me a gradio app called myapp' or 'create' to begin."}]

    ai_builder_tab.load(greet, outputs=chatbot)


if __name__ == "__main__":
    # Optional: Configure retries for huggingface_hub requests
    # from requests.adapters import HTTPAdapter
    # from urllib3.util.retry import Retry
    # retry_strategy = Retry(total=5, backoff_factor=1, status_forcelist=[429, 500, 502, 503, 504])
    # adapter = HTTPAdapter(max_retries=retry_strategy)
    # get_session().mount("http://", adapter)
    # get_session().mount("https://", adapter)

    ai_builder_tab.launch()