Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
| Date | Stars |
|---|---|
| 2026-07-24 | 12832 |
| 2026-07-25 | 12832 |
| 2026-07-28 | 12832 |
| 2026-07-30 | 12832 |
| 2026-08-06 | 12832 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<p align="center">
<a href="https://clip-as-service.jina.ai"><img src="https://github.com/jina-ai/clip-as-service/blob/main/docs/_static/logo-light.svg?raw=true" alt="CLIP-as-service logo: The data structure for unstructured data" width="200px"></a>
<br><br><br>
</p>
<p align=center>
<a href="https://pypi.org/project/clip_server/"><img alt="PyPI" src="https://img.shields.io/pypi/v/clip_server?label=Release&style=flat-square"></a>
<a href="https://discord.jina.ai"><img src="https://img.shields.io/discord/1106542220112302130?logo=discord&logoColor=white&style=flat-square"></a>
<a href="https://codecov.io/gh/jina-ai/clip-as-service"><img alt="Codecov branch" src="https://img.shields.io/codecov/c/github/jina-ai/clip-as-service/main?logo=Codecov&logoColor=white&style=flat-square"></a>
<a href="https://colab.research.google.com/github/jina-ai/clip-as-service/blob/main/docs/hosting/cas-on-colab.ipynb"><img src="https://img.shields.io/badge/Host-on%20Google%20Colab%20(GPU/TPU)-brightgreen?style=flat-square&logo=googlecolab&&logoColor=white" alt="Host on Google Colab with GPU/TPU support"></a>
</p>
<!-- start elevator-pitch -->
CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions.
⚡ **Fast**: Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS<sup>[*]</sup>. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks.
🫐 **Elastic**: Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing.
🐥 **Easy-to-use**: No learning curve, minimalist design on client and server. Intuitive and consistent API for image and sentence embedding.
👒 **Modern**: Async client support. Easily switch between gRPC, HTTP, WebSocket protocols with TLS and compression.
🍱 **Integration**: Smooth integration with neural search ecosystem including [Jina](https://github.com/jina-ai/jina) and [DocArray](https://github.com/jina-ai/docarray). Build cross-modal and multi-modal solutions in no time.
<sup>[*] with default config (single replica, PyTorch no JIT) on GeForce RTX 3090. </sup>
<!-- end elevator-pitch -->
### Text & image embedding
<table>
<tr>
<td> via HTTPS 🔐 </td>
<td> via gRPC 🔐⚡⚡ </td>
</tr>
<tr>
<td>
```bash
curl \
-X POST https://<your-inference-address>-http.wolf.jina.ai/post \
-H 'Content-Type: application/json' \
-H 'Authorization: <your access token>' \
-d '{"data":[{"text": "First do it"},
{"text": "then do it right"},
{"text": "then do it better"},
{"uri": "https://picsum.photos/200"}],
"execEndpoint":"/"}'
```
</td>
<td>
```python
# pip install clip-client
from clip_client import Client
c = Client(
'grpcs://<your-inference-address>-grpc.wolf.jina.ai',
credential={'Authorization': '<your access token>'},
)
r = c.encode(
[
'First do it',
'then do it right',
'then do it better',
'https://picsum.photos/200',
]
)
print(r)
```
</td>
</tr>
</table>
### Visual reasoning
There are four basic visual reasoning skills: object recognition, object counting, color recognition, and spatial relation understanding. Let's try some:
> You need to install [`jq` (a JSON processor)](https://stedolan.github.io/jq/) to prettify the results.
<table>
<tr>
<td> Image </td>
<td> via HTTPS 🔐 </td>
</tr>
<tr>
<td>
<img src="https://picsum.photos/id/1/300/300">
</td>
<td>
```bash
curl \
-X POST https://<your-inference-address>-http.wolf.jina.ai/post \
-H 'Content-Type: application/json' \
-H 'Authorization: <your access token>' \
-d '{"data":[{"uri": "https://picsum.photos/id/1/300/300",
"matches": [{"text": "there is a woman in the photo"},
{"text": "there is a man in the photo"}]}],
"execEndpoint":"/rank"}' \
| jq ".data[].matches[] | (.text, .scores.clip_score.value)"
```
gives:
```
"there is a woman in the photo"
0.626907229423523
"there is Excerpt of 22,162 characters
Read on GitHub
Han Xiao · @elastic · United States
261
Jina Dev Bot · @jina-ai
61
60
felix-wang · @elastic · Singapore
51
35
Gabriel Bianconi · United States
8
6
xiuyu yang · SJTU
5
4
Astariul · Snap Inc. · United Kingdom
3
3
3
Alex Shan
3
3
liamthunder · China
2
2
2
samsja · @PrimeIntellect-ai · United States
2
2
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2422367dffbf0e31, topic:deep-learning, topic:pytorch
matched fp:2422367dffbf0e31, topic:onnx