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Update app.py
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app.py
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from __future__ import annotations
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from fastapi import FastAPI, File, HTTPException, Query, UploadFile
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from fastapi.responses import
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from pydantic import BaseModel
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from typing import List
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from pathlib import Path
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from PIL import Image
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import io
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app = FastAPI(title="Image Tagger API", version="0.
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class TagOut(BaseModel):
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filename: str
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caption: str
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tags: List[str]
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<form action="/upload" method="post" enctype="multipart/form-data" style="display:grid;gap:12px">
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<input type="file" name="file" accept="image/png,image/jpeg,image/webp" required />
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<label>top_k:
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<input type="number" name="top_k" value="5" min="1" max="20">
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</label>
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<button type="submit" style="padding:.6rem 1rem;border-radius:10px;border:1px solid #ddd;background:#111;color:#fff">Upload</button>
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</form>
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</body></html>
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"""
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@app.get("/healthz")
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def healthz():
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return {"ok": True}
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@app.post("/upload", response_model=TagOut)
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async def upload(
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file: UploadFile = File(...),
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top_k: int = Query(5, ge=1, le=20, description="Max number of tags"),
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):
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if file.content_type not in {"image/png", "image/jpeg", "image/webp"}:
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raise HTTPException(
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#
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try:
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data = await file.read()
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img = Image.open(io.BytesIO(data)).convert("RGB")
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@@ -54,9 +61,42 @@ async def upload(
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stem = Path(file.filename).stem or "upload"
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try:
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caption, tags = tag_pil_image(img, stem, top_k=top_k)
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Tagging failed: {e}")
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return JSONResponse({"filename": file.filename, "caption": caption, "tags": tags})
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from __future__ import annotations
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# FastAPI REST API + a Gradio UI mounted at /ui
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# Endpoints:
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# GET /healthz
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# POST /upload (multipart image -> {filename, caption, tags})
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# UI:
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# /ui (upload image, choose top_k, see caption + tags)
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from fastapi import FastAPI, File, HTTPException, Query, UploadFile
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from fastapi.responses import JSONResponse, RedirectResponse
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from pydantic import BaseModel
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from typing import List
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from pathlib import Path
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from PIL import Image
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import io
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import gradio as gr
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from tagger import tag_pil_image # returns (caption: str, tags: List[str])
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app = FastAPI(title="Image Tagger API", version="0.4.0")
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# ---------- Pydantic model for OpenAPI ----------
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class TagOut(BaseModel):
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filename: str
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caption: str
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tags: List[str]
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# ---------- Basic routes ----------
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@app.get("/", include_in_schema=False)
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def root_redirect():
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# Send users to the nicer UI
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return RedirectResponse(url="/ui", status_code=302)
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@app.get("/healthz")
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def healthz():
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return {"ok": True}
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# ---------- REST endpoint ----------
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@app.post("/upload", response_model=TagOut)
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async def upload(
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file: UploadFile = File(...),
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top_k: int = Query(5, ge=1, le=20, description="Max number of tags"),
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):
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# MIME guard
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if file.content_type not in {"image/png", "image/jpeg", "image/webp"}:
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raise HTTPException(
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status_code=415, detail="Only PNG, JPEG, or WebP images are supported"
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)
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# Decode image
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try:
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data = await file.read()
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img = Image.open(io.BytesIO(data)).convert("RGB")
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stem = Path(file.filename).stem or "upload"
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# Tag
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try:
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caption, tags = tag_pil_image(img, stem, top_k=top_k)
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Tagging failed: {e}")
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return JSONResponse({"filename": file.filename, "caption": caption, "tags": tags})
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# ---------- Gradio UI (mounted at /ui) ----------
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def _ui_tag(image: Image.Image, top_k: int):
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if image is None:
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return "", []
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caption, tags = tag_pil_image(image.convert("RGB"), "upload", top_k=top_k)
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return caption, tags
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with gr.Blocks(title="Image Tagger", analytics_enabled=False) as gr_app:
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gr.Markdown(
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"## 🏷️ Image Tagger\n"
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"Upload an image to get a caption and top-k tags. "
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"Programmatic API is available at **/docs**."
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)
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with gr.Row():
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with gr.Column(scale=1):
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inp = gr.Image(
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type="pil", label="Upload image", sources=["upload"], height=360
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)
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k = gr.Slider(1, 20, value=5, step=1, label="Top-k tags")
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btn = gr.Button("Tag it")
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with gr.Column(scale=1):
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cap = gr.Textbox(label="Caption", lines=2)
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tags = gr.Tags(label="Tags")
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btn.click(_ui_tag, inputs=[inp, k], outputs=[cap, tags])
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# Mount Gradio on the same FastAPI app
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app = gr.mount_gradio_app(app, gr_app, path="/ui")
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