Image caption
Paste a public image URL and get an accessibility-style alt-text caption plus a
Showcase — Image caption
Paste a public image URL and get an accessibility-style alt-text caption plus a short description. It's the simplest multimodal call: one message whose content is an instruction text part and an image part, reasoned over together.
Run
bash bootstrap-secrets.sh # reads ../../../../.env, writes secrets/
docker compose up --build # default: PROVIDER=openai
Open http://localhost:3000. Gemini: PROVIDER=gemini docker compose up --build.
What's where
backend/ai_openai.py— passes the image URL directly to the model.backend/ai_gemini.py— downloads the image and passes it as inline bytes.frontend/app/page.tsx— URL box + caption.
Stop
docker compose down
Run locally
Download the project as a ZIP and run it with Docker. Brings up a FastAPI backend + Next.js frontend on localhost:3000.
unzip image-caption.zip
cd image-caption
bash bootstrap-secrets.sh # one-time: pulls API keys into ./secrets
docker compose up --build # default provider: openai
# or: PROVIDER=gemini docker compose up --build
Type some input, pick a provider, and run the same code shown in Source against the live API. Sign-in required.
The same modules the Run button hits. The whole project (frontend, Dockerfile, compose) is in the ZIP under README.
backend/ai_openai.py
"""Showcase 1 (OpenAI): image captioning from a URL.
Paste a public image URL and get an accessibility-style caption plus a short
description. One multimodal message: an instruction text part and an image part.
"""
from openai import OpenAI
_client = OpenAI()
_MODEL = "gpt-5.4-nano"
_PROMPT = (
"Write a concise one-sentence alt-text caption for this image, then a "
"2-3 sentence description of what's in it. Label them 'Alt text:' and "
"'Description:'."
)
def run(image_url: str) -> str:
url = image_url.strip()
if not url.startswith("http"):
return "Paste a public image URL (starting with http:// or https://)."
response = _client.responses.create(
model=_MODEL,
input=[{
"role": "user",
"content": [
{"type": "input_text", "text": _PROMPT},
{"type": "input_image", "image_url": url},
],
}],
)
return response.output_text
backend/ai_gemini.py
"""Showcase 1 (Gemini): image captioning from a URL.
Same captioning prompt; Gemini takes the image as downloaded bytes.
"""
import os
import urllib.request
from google import genai
from google.genai import types
_client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
_MODEL = "gemini-3.1-flash-lite"
_PROMPT = (
"Write a concise one-sentence alt-text caption for this image, then a "
"2-3 sentence description of what's in it. Label them 'Alt text:' and "
"'Description:'."
)
def _mime(url: str) -> str:
u = url.lower()
if u.endswith(".png"):
return "image/png"
if u.endswith(".webp"):
return "image/webp"
return "image/jpeg"
def run(image_url: str) -> str:
url = image_url.strip()
if not url.startswith("http"):
return "Paste a public image URL (starting with http:// or https://)."
image_bytes = urllib.request.urlopen(urllib.request.Request(url, headers={"User-Agent": "Mozilla/5.0"})).read()
response = _client.models.generate_content(
model=_MODEL,
contents=[types.Part.from_bytes(data=image_bytes, mime_type=_mime(url)), _PROMPT],
)
return response.text or ""
Project files
.gitignoreREADME.es.mdREADME.mdbackend/Dockerfilebackend/ai_gemini.pybackend/ai_openai.pybackend/main.pybackend/requirements.txtbootstrap-secrets.shdocker-compose.ymlfrontend/Dockerfilefrontend/app/layout.tsxfrontend/app/page.tsxfrontend/next.config.tsfrontend/package.jsonfrontend/tsconfig.json