# import logging
# from fastapi import FastAPI, HTTPException
# from fastapi.middleware.cors import CORSMiddleware
# from pydantic import BaseModel
# from services import queue_manager
# import os
# from pathlib import Path

# # CACHE PATCH BLOCK: place FIRST in pipeline.py!
# HF_CACHE_DIR = Path("/tmp/hf_cache")
# HF_CACHE_DIR.mkdir(parents=True, exist_ok=True)
# os.environ.update({
#     "HF_HOME": str(HF_CACHE_DIR),
#     "HF_HUB_CACHE": str(HF_CACHE_DIR),
#     "DIFFUSERS_CACHE": str(HF_CACHE_DIR),
#     "TRANSFORMERS_CACHE": str(HF_CACHE_DIR),
#     "XDG_CACHE_HOME": str(HF_CACHE_DIR),
#     "HF_DATASETS_CACHE": str(HF_CACHE_DIR),
#     "HF_MODULES_CACHE": str(HF_CACHE_DIR),
#     "TMPDIR": str(HF_CACHE_DIR),
#     "CACHE_DIR": str(HF_CACHE_DIR),
#     "TORCH_HOME": str(HF_CACHE_DIR),
#     "HOME": str(HF_CACHE_DIR)
# })
# import os.path
# if not hasattr(os.path, "expanduser_original"):
#     os.path.expanduser_original = os.path.expanduser
# def safe_expanduser(path):
#     if (
#         path.startswith("~") or 
#         path.startswith("/.cache") or 
#         path.startswith("/root/.cache")
#     ):
#         return str(HF_CACHE_DIR)
#     return os.path.expanduser_original(path)
# os.path.expanduser = safe_expanduser


# logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

# app = FastAPI(title="AI ADD Generator", version="1.0")

# app.add_middleware(
#     CORSMiddleware,
#     allow_origins=["*"],
#     allow_credentials=True,
#     allow_methods=["*"],
#     allow_headers=["*"],
# )

# # ---------------------------
# # Pydantic models
# # ---------------------------
# class IdeaRequest(BaseModel):
#     idea: str

# class ConfirmationRequest(BaseModel):
#     task_id: str
#     confirm: bool

# # ---------------------------
# # API endpoints
# # ---------------------------
# @app.post("/submit_idea")
# async def submit_idea(request: IdeaRequest):
#     task_id = await queue_manager.add_task(request.idea)
#     return {"status": "submitted", "task_id": task_id}

# @app.post("/confirm")
# async def confirm_task(request: ConfirmationRequest):
#     task = queue_manager.get_task_status(request.task_id)
#     if not task:
#         raise HTTPException(status_code=404, detail="Task not found")
#     if task["status"] != queue_manager.TaskStatus.WAITING_CONFIRMATION:
#         raise HTTPException(status_code=400, detail="Task not waiting for confirmation")

#     await queue_manager.confirm_task(request.task_id)
#     return {"status": "confirmed", "task": task}

# @app.get("/status/{task_id}")
# async def status(task_id: str):
#     task = queue_manager.get_task_status(task_id)
#     if not task:
#         raise HTTPException(status_code=404, detail="Task not found")
#     return task

# @app.get("/")
# async def health():
#     return {"status": "running"}


# import logging
# from fastapi import FastAPI, HTTPException
# from fastapi.middleware.cors import CORSMiddleware
# from pydantic import BaseModel
# from services import queue_manager
# import os
# from pathlib import Path
# from typing import Optional


# # CACHE PATCH BLOCK: place FIRST in pipeline.py!
# HF_CACHE_DIR = Path("/tmp/hf_cache")
# HF_CACHE_DIR.mkdir(parents=True, exist_ok=True)
# os.environ.update({
#     "HF_HOME": str(HF_CACHE_DIR),
#     "HF_HUB_CACHE": str(HF_CACHE_DIR),
#     "DIFFUSERS_CACHE": str(HF_CACHE_DIR),
#     "TRANSFORMERS_CACHE": str(HF_CACHE_DIR),
#     "XDG_CACHE_HOME": str(HF_CACHE_DIR),
#     "HF_DATASETS_CACHE": str(HF_CACHE_DIR),
#     "HF_MODULES_CACHE": str(HF_CACHE_DIR),
#     "TMPDIR": str(HF_CACHE_DIR),
#     "CACHE_DIR": str(HF_CACHE_DIR),
#     "TORCH_HOME": str(HF_CACHE_DIR),
#     "HOME": str(HF_CACHE_DIR)
# })
# import os.path
# if not hasattr(os.path, "expanduser_original"):
#     os.path.expanduser_original = os.path.expanduser
# def safe_expanduser(path):
#     if (
#         path.startswith("~") or 
#         path.startswith("/.cache") or 
#         path.startswith("/root/.cache")
#     ):
#         return str(HF_CACHE_DIR)
#     return os.path.expanduser_original(path)
# os.path.expanduser = safe_expanduser


# logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

# app = FastAPI(title="AI ADD Generator", version="1.0")

# app.add_middleware(
#     CORSMiddleware,
#     allow_origins=["*"],
#     allow_credentials=True,
#     allow_methods=["*"],
#     allow_headers=["*"],
# )

# # ---------------------------
# # Pydantic models
# # ---------------------------
# class IdeaRequest(BaseModel):
#     idea: str

# class ConfirmationRequest(BaseModel):
#     task_id: str
#     confirm: bool
#     edited_script: Optional[str] = None

# # ---------------------------
# # API endpoints
# # ---------------------------
# @app.post("/submit_idea")
# async def submit_idea(request: IdeaRequest):
#     task_id = await queue_manager.add_task(request.idea)
#     return {"status": "submitted", "task_id": task_id}

# @app.post("/confirm")
# async def confirm_task(request: ConfirmationRequest):
#     task = queue_manager.get_task_status(request.task_id)
#     if not task:
#         raise HTTPException(status_code=404, detail="Task not found")
#     # status values are stored as strings by queue_manager/pipeline
#     if task["status"] != queue_manager.TaskStatus.WAITING_CONFIRMATION.value:
#         raise HTTPException(status_code=400, detail="Task not waiting for confirmation")

#     # if frontend supplied an edited script, persist it before unblocking the pipeline
#     if request.edited_script:
#         task["result"]["script"] = request.edited_script

#     await queue_manager.confirm_task(request.task_id)
#     return {"status": "confirmed", "task": task}

# @app.get("/status/{task_id}")
# async def status(task_id: str):
#     task = queue_manager.get_task_status(task_id)
#     if not task:
#         raise HTTPException(status_code=404, detail="Task not found")
#     return task

# @app.get("/")
# async def health():
#     return {"status": "running"}




import logging
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from services import queue_manager
import os
from pathlib import Path
from typing import Optional


# CACHE PATCH BLOCK: place FIRST in pipeline.py!
HF_CACHE_DIR = Path("/tmp/hf_cache")
HF_CACHE_DIR.mkdir(parents=True, exist_ok=True)
os.environ.update({
    "HF_HOME": str(HF_CACHE_DIR),
    "HF_HUB_CACHE": str(HF_CACHE_DIR),
    "DIFFUSERS_CACHE": str(HF_CACHE_DIR),
    "TRANSFORMERS_CACHE": str(HF_CACHE_DIR),
    "XDG_CACHE_HOME": str(HF_CACHE_DIR),
    "HF_DATASETS_CACHE": str(HF_CACHE_DIR),
    "HF_MODULES_CACHE": str(HF_CACHE_DIR),
    "TMPDIR": str(HF_CACHE_DIR),
    "CACHE_DIR": str(HF_CACHE_DIR),
    "TORCH_HOME": str(HF_CACHE_DIR),
    "HOME": str(HF_CACHE_DIR)
})
import os.path
if not hasattr(os.path, "expanduser_original"):
    os.path.expanduser_original = os.path.expanduser
def safe_expanduser(path):
    if (
        path.startswith("~") or 
        path.startswith("/.cache") or 
        path.startswith("/root/.cache")
    ):
        return str(HF_CACHE_DIR)
    return os.path.expanduser_original(path)
os.path.expanduser = safe_expanduser


logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

app = FastAPI(title="AI ADD Generator", version="1.0")

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# ---------------------------
# Pydantic models
# ---------------------------
class IdeaRequest(BaseModel):
    idea: str

class ConfirmationRequest(BaseModel):
    task_id: str
    confirm: bool
    edited_script: Optional[str] = None

# ---------------------------
# API endpoints
# ---------------------------
@app.post("/submit_idea")
async def submit_idea(request: IdeaRequest):
    task_id = await queue_manager.add_task(request.idea)
    return {"status": "submitted", "task_id": task_id}

@app.post("/confirm")
async def confirm_task(request: ConfirmationRequest):
    task = queue_manager.get_task_status(request.task_id)
    if not task:
        raise HTTPException(status_code=404, detail="Task not found")
    # status values are stored as strings by queue_manager/pipeline
    if task["status"] != queue_manager.TaskStatus.WAITING_CONFIRMATION.value:
        raise HTTPException(status_code=400, detail="Task not waiting for confirmation")

    # if frontend supplied an edited script, persist it before unblocking the pipeline
    if request.edited_script:
        task["result"]["script"] = request.edited_script

    await queue_manager.confirm_task(request.task_id)
    return {"status": "confirmed", "task": task}

@app.get("/status/{task_id}")
async def status(task_id: str):
    task = queue_manager.get_task_status(task_id)
    if not task:
        raise HTTPException(status_code=404, detail="Task not found")
    return task

@app.get("/")
async def health():
    return {"status": "running"}