add readme, 0.3.0 release

libs/embed_package/README.md

@@ -0,0 +1,91 @@
+# embed
+A stable, blazing fast and easy-to-use inference library with a focus on a sync-to-async API
+
+[![ci][ci-shield]][ci-url]
+[![Downloads][pepa-shield]][pepa-url]
+
+## Installation
+```bash
+pip install embed
+```
+
+## Why embed?
+
+Embed makes it easy to load any embedding, classification and reranking models from Huggingface. 
+It leverages [Infinity](https://github.com/michaelfeil/infinity) as backend for async computation, batching, and Flash-Attention-2.
+
+![CPU Benchmark Diagram](docs/l4_cpu.png)
+Benchmarking on an Nvidia-L4 instance. Note: CPU uses bert-small, CUDA uses Bert-large. [Methodology](https://michaelfeil.eu/infinity/0.0.51/benchmarking/).
+
+```python
+from embed import BatchedInference
+from concurrent.futures import Future
+
+# Run any model
+register = BatchedInference(
+    model_id=[
+        # sentence-embeddings
+        "michaelfeil/bge-small-en-v1.5",
+        # sentence-embeddings and image-embeddings
+        "jinaai/jina-clip-v1",
+        # classification models
+        "philschmid/tiny-bert-sst2-distilled",
+        # rerankers
+        "mixedbread-ai/mxbai-rerank-xsmall-v1",
+    ],
+    # engine to `torch` or `optimum`
+    engine="torch",
+    # device `cuda` (Nvidia/AMD) or `cpu`
+    device="cpu",
+)
+
+sentences = ["Paris is in France.", "Berlin is in Germany.", "A image of two cats."]
+images = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
+question = "Where is Paris?"
+
+future: "Future" = register.embed(
+    sentences=sentences, model_id="michaelfeil/bge-small-en-v1.5"
+)
+future.result()
+register.rerank(
+    query=question, docs=sentences, model_id="mixedbread-ai/mxbai-rerank-xsmall-v1"
+)
+register.classify(model_id="philschmid/tiny-bert-sst2-distilled", sentences=sentences)
+register.image_embed(model_id="jinaai/jina-clip-v1", images=images)
+
+# manually stop the register upon termination to free model memory.
+register.stop()
+```
+
+All functions return `Futures(vector_embedding, token_usage)`, enables you to `wait` for them and removes batching logic from your code.
+
+```python
+>>> embedding_fut = register.embed(sentences=sentences, model_id="michaelfeil/bge-small-en-v1.5")
+>>> print(embedding_fut)
+<Future at 0x7fa0e97e8a60 state=pending>
+>>> time.sleep(1) and print(embedding_fut)
+<Future at 0x7fa0e97e9c30 state=finished returned tuple>
+>>> embedding_fut.result()
+([array([-3.35943862e-03, ..., -3.22808176e-02], dtype=float32)], 19)
+```
+
+# Licence and Contributions
+embed is licensed as MIT. All contribrutions need to adhere to the MIT License. Contributions are welcome.
+
+
+<!-- MARKDOWN LINKS & IMAGES -->
+<!-- https://www.markdownguide.org/basic-syntax/#reference-style-links -->
+[contributors-shield]: https://img.shields.io/github/contributors/michaelfeil/embed.svg?style=for-the-badge
+[contributors-url]: https://github.com/michaelfeil/embed/graphs/contributors
+[forks-shield]: https://img.shields.io/github/forks/michaelfeil/embed.svg?style=for-the-badge
+[forks-url]: https://github.com/michaelfeil/embed/network/members
+[stars-shield]: https://img.shields.io/github/stars/michaelfeil/embed.svg?style=for-the-badge
+[stars-url]: https://github.com/michaelfeil/embed/stargazers
+[issues-shield]: https://img.shields.io/github/issues/michaelfeil/embed.svg?style=for-the-badge
+[issues-url]: https://github.com/michaelfeil/embed/issues
+[license-shield]: https://img.shields.io/github/license/michaelfeil/embed.svg?style=for-the-badge
+[license-url]: https://github.com/michaelfeil/embed/blob/master/LICENSE.txt
+[pepa-shield]: https://static.pepy.tech/badge/embed
+[pepa-url]: https://www.pepy.tech/projects/embed
+[ci-shield]: https://github.com/michaelfeil/infinity/actions/workflows/ci.yaml/badge.svg
+[ci-url]: https://github.com/michaelfeil/infinity/actions

libs/embed_package/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "embed"
-version = "0.2.0"
+version = "0.3.0"
 description = "A stable, fast and easy-to-use inference library with a focus on a sync-to-async API"
 authors = ["michaelfeil <me@michaelfeil.eu>"]
 readme = "README.md"