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from fastapi import APIRouter, HTTPException, Body, UploadFile, File, Form, Request
from pydantic import BaseModel
from typing import Optional, List
from app.ai_agent.agent import handle_user_query, create_medical_agent, search_cases_with_timeout, register_attachment
import logging
import asyncio
logger = logging.getLogger(__name__)
router = APIRouter()
# Basic size limits (bytes)
MAX_IMAGE_BYTES = 6_000_000 # ~6 MB
MAX_AUDIO_BYTES = 10 * 1024 * 1024 # 10 MB
MAX_FILE_BYTES = 2 * 1024 * 1024 # 2 MB
class AIRequest(BaseModel):
text: Optional[str] = None
image: Optional[str] = None # URL ou base64
images: Optional[List[str]] = None # URLs ou base64 multiples
audio: Optional[str] = None # URL ou base64
audios: Optional[List[str]] = None # URLs ou base64 multiples
want_stats: Optional[bool] = False
location: Optional[str] = None # Pour la recherche d'établissements
files: Optional[List[str]] = None # URLs ou base64 de fichiers (petits)
file_names: Optional[List[str]] = None # Noms des fichiers correspondants
agent_mode: Optional[str] = None # 'messages' (zero-shot), 'string', or 'legacy'
class AIResponse(BaseModel):
result: str
stats: Optional[dict] = None
@router.post("/ai", response_model=AIResponse)
async def ai_endpoint(req: AIRequest = Body(...)):
# Construction de la requête utilisateur pour l'agent
user_query = ""
if req.text:
user_query += req.text + "\n"
if req.image:
user_query += f"[Image fournie]\n"
if req.audio:
user_query += f"[Audio fourni]\n"
if req.location:
user_query += f"[Localisation: {req.location}]\n"
# Appel à l'agent LangChain dans un thread pour éviter de bloquer l'event loop
result = await asyncio.to_thread(
handle_user_query,
user_query,
req.location,
req.image,
req.audio,
req.files or [],
req.file_names or [],
req.images or [],
req.audios or [],
req.agent_mode,
)
stats = None
if req.want_stats:
stats = {}
if req.text:
stats["word_count"] = len(req.text.split())
if req.image:
stats["image_url_or_b64_length"] = len(req.image)
if req.images:
stats["images_count"] = len(req.images)
if req.audio:
stats["audio_url_or_b64_length"] = len(req.audio)
if req.audios:
stats["audios_count"] = len(req.audios)
if req.files:
stats["files_count"] = len(req.files)
# Ajoute d'autres stats pertinentes ici
return AIResponse(result=result, stats=stats)
# =============================================================================
# Multipart/form-data endpoint for uploads
# =============================================================================
@router.post("/ai/form", response_model=AIResponse)
async def ai_form_endpoint(
request: Request,
text: Optional[str] = Form(None),
location: Optional[str] = Form(None),
want_stats: Optional[bool] = Form(False),
agent_mode: Optional[str] = Form(None),
):
# Parse the raw form to accept both UploadFile and string references
try:
form = await request.form()
except Exception:
form = None
image_refs: List[str] = []
audio_refs: List[str] = []
file_refs: List[str] = []
file_names: List[str] = []
if form:
# Helpers to iterate possible single/plural fields
def _iter_values(keys: List[str]):
for key in keys:
for v in form.getlist(key):
yield v
# Images
for v in _iter_values(["image", "images"]):
if isinstance(v, UploadFile):
try:
data = await v.read()
if data and len(data) > MAX_IMAGE_BYTES:
raise HTTPException(status_code=413, detail=f"Image '{v.filename}' trop volumineuse (> 6 Mo)")
ref = register_attachment(data, filename=v.filename, mime=v.content_type)
image_refs.append(ref)
finally:
await v.close()
elif isinstance(v, str) and v.strip():
image_refs.append(v.strip())
# Audios
for v in _iter_values(["audio", "audios"]):
if isinstance(v, UploadFile):
try:
data = await v.read()
if data and len(data) > MAX_AUDIO_BYTES:
raise HTTPException(status_code=413, detail=f"Audio '{v.filename}' trop volumineux (> 10 Mo)")
ref = register_attachment(data, filename=v.filename, mime=v.content_type)
audio_refs.append(ref)
finally:
await v.close()
elif isinstance(v, str) and v.strip():
audio_refs.append(v.strip())
# Files (text/PDF)
string_file_names = form.getlist("file_names") if "file_names" in form else []
string_file_index = 0
for v in _iter_values(["file", "files"]):
if isinstance(v, UploadFile):
try:
data = await v.read()
if data and len(data) > MAX_FILE_BYTES:
raise HTTPException(status_code=413, detail=f"Fichier '{v.filename}' trop volumineux (> 2 Mo)")
ref = register_attachment(data, filename=v.filename, mime=v.content_type)
file_refs.append(ref)
file_names.append(v.filename or "file")
finally:
await v.close()
elif isinstance(v, str) and v.strip():
file_refs.append(v.strip())
# try map a provided filename
name = None
if string_file_names and string_file_index < len(string_file_names):
maybe = string_file_names[string_file_index]
if isinstance(maybe, str) and maybe.strip():
name = maybe.strip()
file_names.append(name or "file")
string_file_index += 1
# Validate agent_mode if provided
if agent_mode and agent_mode.lower() not in {"messages", "string", "legacy"}:
raise HTTPException(status_code=400, detail="agent_mode invalide: utilisez 'messages', 'string' ou 'legacy'")
# Construct user query summary (all inputs optional)
user_query = (text or "").strip()
if image_refs:
user_query += ("\n" if user_query else "") + "[Image(s) fournie(s)]"
if audio_refs:
user_query += ("\n" if user_query else "") + "[Audio(s) fourni(s)]"
if location:
user_query += ("\n" if user_query else "") + f"[Localisation: {location}]"
# All inputs are optional; proceed even if user_query is empty.
# Invoke agent with attach:// references
result = await asyncio.to_thread(
handle_user_query,
user_query,
location,
None, # single image param not used here
None, # single audio param not used here
file_refs,
file_names,
image_refs,
audio_refs,
agent_mode,
)
stats = None
if want_stats:
stats = {
"word_count": len(text.split()) if text else 0,
"images_count": len(image_refs),
"audios_count": len(audio_refs),
"files_count": len(file_refs),
}
return AIResponse(result=result, stats=stats)
# =============================================================================
# DEBUG ENDPOINTS to isolate the hanging issue
# =============================================================================
@router.get("/ai/debug/create-agent", tags=["AI Debug"])
async def debug_create_agent():
"""Tests if creating the medical agent works without hanging."""
logger.info("--- DEBUG: Testing agent creation ---")
try:
agent = create_medical_agent()
if agent:
logger.info("--- DEBUG: Agent creation successful ---")
return {"status": "Agent created successfully"}
else:
logger.error("--- DEBUG: Agent creation failed, returned None ---")
raise HTTPException(status_code=500, detail="Agent creation returned None")
except Exception as e:
logger.error(f"--- DEBUG: Agent creation failed with exception: {e} ---", exc_info=True)
raise HTTPException(status_code=500, detail=f"Agent creation failed: {e}")
@router.get("/ai/debug/search-data", tags=["AI Debug"])
async def debug_search_data(q: str = "fever and headache"):
"""Tests if the clinical data search works without hanging."""
logger.info(f"--- DEBUG: Testing data search with query: '{q}' ---")
try:
context = search_cases_with_timeout(q, timeout=15)
logger.info("--- DEBUG: Data search successful ---")
return {"status": "Data search completed", "context_found": bool(context), "context": context}
except Exception as e:
logger.error(f"--- DEBUG: Data search failed with exception: {e} ---", exc_info=True)
raise HTTPException(status_code=500, detail=f"Data search failed: {e}")
@router.get("/ai/debug/invoke-agent", tags=["AI Debug"])
async def debug_invoke_agent(q: str = "hello, how are you?"):
"""Tests if invoking the agent with a simple query works without hanging."""
logger.info(f"--- DEBUG: Testing agent invocation with query: '{q}' ---")
try:
agent = create_medical_agent()
logger.info("--- DEBUG: Agent created, invoking... ---")
response = await asyncio.to_thread(agent.invoke, {"input": q})
logger.info("--- DEBUG: Agent invocation successful ---")
return {"status": "Agent invoked successfully", "response": response}
except Exception as e:
logger.error(f"--- DEBUG: Agent invocation failed with exception: {e} ---", exc_info=True)
raise HTTPException(status_code=500, detail=f"Agent invocation failed: {e}")
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