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# 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"} |