# import os
# import json
# import shutil
# from fastapi import APIRouter, HTTPException, UploadFile, Form, Request
# from crewai import Crew, Process
# from agents.design_phase import search_engine_agent, search_engine_task
# from schemas import DNAMetadata, OutlineInput
# from modules import TRUSTED_SITES

# router = APIRouter(prefix="/design", tags=["Design"])


# @router.post("/source_finder")
# async def run_training(request: Request, file: UploadFile, data: str = Form(...)):
#     """Uploads keywords JSON + metadata JSON, runs CrewAI search, returns download link"""

#     # ✅ Parse metadata JSON manually
#     try:
#         parsed_data = json.loads(data)
#         metadata = OutlineInput(**parsed_data)
#     except Exception as e:
#         raise HTTPException(
#             status_code=400, detail=f"Invalid JSON in 'data' field: {str(e)}"
#         )

#     # ✅ Save uploaded file
#     save_path = f"/tmp/{file.filename}"
#     with open(save_path, "wb") as buffer:
#         shutil.copyfileobj(file.file, buffer)

#     # ✅ Validate extension
#     ext = save_path.lower().split(".")[-1]
#     if ext != "json":
#         raise HTTPException(status_code=400, detail="File must be a JSON file")

#     # ✅ Load keywords file
#     with open(save_path, "r", encoding="utf-8") as f:
#         try:
#             units_data = json.load(f)
#         except json.JSONDecodeError:
#             raise HTTPException(status_code=400, detail="Invalid JSON file content")

#     # ✅ Initialize Crew
#     crew = Crew(
#         agents=[search_engine_agent],
#         tasks=[search_engine_task],
#         process=Process.sequential,
#     )

#     # ✅ Prepare static user input
#     user_inputs = DNAMetadata(
#         topic=metadata.topic,
#         domain=metadata.domain,
#         content_type=metadata.content_type,
#         audience=metadata.audience,
#         material_type=metadata.material_type,
#     ).dict()

#     all_results = []
#     # total_prompt = 0
#     # total_completion = 0

#     # ✅ Loop through each subtopic and query
#     for unit in units_data:
#         unit_title = unit["unit_title"]
#         subtopic_title = unit["subtopic_title"]
#         queries = unit["queries"]

#         for query in queries:
#             print(f"🔍 Running search for [{subtopic_title}] | Query: {query}")

#             merged_input = {
#                 **user_inputs,
#                 "score_th": 0.6,
#                 "no_links": 3,
#                 "queries": query,
#                 "unit_title": unit_title,
#                 "subtopic_title": subtopic_title,
#                 "TRUSTED_SITES": TRUSTED_SITES,
#             }

#             try:
#                 result = crew.kickoff(inputs=merged_input)
#                 all_results.append(result.json_dict) 

#                 # usage = result.token_usage  # CrewAI بيحسبها جاهز

#                 # total_prompt += usage["prompt_tokens"]
#                 # total_completion += usage["completion_tokens"]
#                 # total_tokens += usage["total_tokens"]

#             except Exception as e:
#                 print(f"⚠️ Error while running query '{query}': {e}")
#     output_data = {"results": all_results}
#     # ✅ Save results to file
#     output_file = f"/tmp/search_results"
#     with open(output_file, "w", encoding="utf-8") as f:
#         json.dump(output_data, f, ensure_ascii=False, indent=2)

#     # ✅ Create downloadable link
#     base_url = str(request.base_url).rstrip("/")
#     download_link = (
#         f"{base_url}/design/download?filename={os.path.basename(output_file)}"
#     )

#     return {
#         "message": "Search process completed successfully 🚀",
#         "total_queries": len(all_results),
#         # "total_prompt": total_prompt,
#         # "total_completion": total_completion,
#         # "total_tokens": total_tokens,
#         "download_link": download_link,
#         "result": all_results,
#         "json_dict": output_data,
#     }


# # ✅ New endpoint for downloading results
# @router.get("/download")
# async def download_file(filename: str):
#     file_path = f"/tmp/{filename}"

#     if not os.path.exists(file_path):
#         raise HTTPException(status_code=404, detail="File not found")

#     with open(file_path, "r", encoding="utf-8") as f:
#         data = json.load(f)

#     return data