api.py

from fastapi import FastAPI, UploadFile, File, Form
from fastapi.middleware.cors import CORSMiddleware
from PIL import Image
from typing import List
from pydantic import BaseModel

from model_registry import get_model
from models.resnet_lstm_attention.schemas import CaptionResult, ImageResult, TextQuery

app = FastAPI(title="Multimodal Retrieval & Captioning API")

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

class InferenceRequest(BaseModel):
    model_name: str
    top_k: int = 5

@app.post("/caption")
async def caption_image(model_name: str = Form(...), file: UploadFile = File(...)):
    image = Image.open(file.file).convert("RGB")
    model = get_model(model_name)
    caption = model.generate_caption(image)
    return {"caption": caption}

@app.post("/search/text2img")
async def text_to_image(model_name: str = Form(...), query: str = Form(...), top_k: int = Form(5)):
    model = get_model(model_name)
    results = model.text_to_image(query, top_k)
    return results

@app.post("/search/img2text")
async def image_to_text(model_name: str = Form(...), file: UploadFile = File(...), top_k: int = Form(5)):
    image = Image.open(file.file).convert("RGB")
    model = get_model(model_name)
    results = model.image_to_text(image, top_k)
    return results

@app.post("/search/img2img")
async def image_to_image(model_name: str = Form(...), file: UploadFile = File(...), top_k: int = Form(5)):
    image = Image.open(file.file).convert("RGB")
    model = get_model(model_name)
    results = model.image_to_image(image, top_k)
    return results

@app.post("/search/text2text")
async def text_to_text(model_name: str = Form(...), query: str = Form(...), top_k: int = Form(5)):
    model = get_model(model_name)
    results = model.text_to_text(query, top_k)
    return results

@app.get("/health")
def health_check():
    return {"status": "healthy"}



# # api.py
# from fastapi import FastAPI, UploadFile, File, Form
# from fastapi.middleware.cors import CORSMiddleware
# from PIL import Image
# from typing import List
# from pydantic import BaseModel
# from models.resnet_lstm_attention.loader import load_captioning_model
# from models.resnet_lstm_attention.cap_mod_defs import EncoderCNN

# from model_registry import get_model
# from models.resnet_lstm_attention.schemas import CaptionResult, ImageResult, TextQuery

# app = FastAPI(title="Multimodal Retrieval & Captioning API")

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

# class InferenceRequest(BaseModel):
#     model_name: str
#     top_k: int = 5

# #@app.post("/caption", response_model=CaptionResult)
# @app.post("/caption")
# async def caption_image(model_name: str = Form(...), file: UploadFile = File(...)):
#     image = Image.open(file.file).convert("RGB")
#     model = get_model(model_name)
#     caption = model.generate_caption(image)
#     return {"caption": caption}

# #@app.post("/search/text2img", response_model=List[ImageResult])
# @app.post("/search/text2img")
# async def text_to_image(model_name: str = Form(...), query: str = Form(...), top_k: int = Form(5)):
#     model = get_model(model_name)
#     results = model.text_to_image(query, top_k)
#     return results

# @app.post("/search/img2text")
# async def image_to_text(model_name: str = Form(...), file: UploadFile = File(...), top_k: int = Form(5)):
#     image = Image.open(file.file).convert("RGB")
#     model = get_model(model_name)
#     results = model.image_to_text(image, top_k)
#     return results

# #@app.post("/search/img2img", response_model=List[ImageResult])
# @app.post("/search/img2img")
# async def image_to_image(model_name: str = Form(...), file: UploadFile = File(...), top_k: int = Form(5)):
#     image = Image.open(file.file).convert("RGB")
#     model = get_model(model_name)
#     results = model.image_to_image(image, top_k)
#     return results

# @app.post("/search/text2text")
# async def text_to_text(model_name: str = Form(...), query: str = Form(...), top_k: int = Form(5)):
#     model = get_model(model_name)
#     results = model.text_to_text(query, top_k)
#     return results

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