Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update on docs and poetry #265

Merged
merged 2 commits into from
Jun 13, 2024
Merged
Show file tree
Hide file tree
Changes from 1 commit
Commits
File filter

Filter by extension

Filter by extension


Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions docs/docs/integrations.md
Original file line number Diff line number Diff line change
@@ -1,5 +1,11 @@
# Python Integrations

## Cognita
https://github.com/truefoundry/cognita

## RagFlow
https://github.com/infiniflow/ragflow

## Langchain (from running server)
Infinity has an official integration into `pip install langchain>=0.342`.
You can find more documentation on that here:
Expand Down
74 changes: 58 additions & 16 deletions docs/docs/python_engine.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,22 +6,22 @@ Use asynchronous programming in Python using `asyncio` for flexible and efficien

```python
import asyncio
from infinity_emb import AsyncEmbeddingEngine, EngineArgs
from infinity_emb import AsyncEngineArray, EngineArgs, AsyncEmbeddingEngine
from infinity_emb.log_handler import logger
logger.setLevel(5) # Debug

# Define sentences for embedding
sentences = ["Embed this sentence via Infinity.", "Paris is in France."]
# Initialize the embedding engine with model specifications
engine = AsyncEmbeddingEngine.from_args(
array = AsyncEngineArray.from_args([
EngineArgs(
model_name_or_path="BAAI/bge-small-en-v1.5",
engine="torch",
lengths_via_tokenize=True
)
)]
)

async def main():
async def embed_image(engine: AsyncEmbeddingEngine):
await engine.astart() # initializes the engine
job1 = asyncio.create_task(engine.embed(sentences=sentences))
# submit a second job in parallel
Expand All @@ -34,7 +34,7 @@ async def main():
await engine.astop()

asyncio.run(
main()
embed_image(array["BAAI/bge-small-en-v1.5"])
)
```

Expand All @@ -46,15 +46,16 @@ Please select a model from huggingface that is a AutoModelForSequenceClassificat

```python
import asyncio
from infinity_emb import AsyncEmbeddingEngine, EngineArgs
from infinity_emb import AsyncEngineArray, EngineArgs, AsyncEmbeddingEngine
query = "What is the python package infinity_emb?"
docs = ["This is a document not related to the python package infinity_emb, hence...",
"Paris is in France!",
"infinity_emb is a package for sentence embeddings and rerankings using transformer models in Python!"]
engine_args = EngineArgs(model_name_or_path = "mixedbread-ai/mxbai-rerank-xsmall-v1", engine="torch")
array = AsyncEmbeddingEngine.from_args(
[EngineArgs(model_name_or_path = "mixedbread-ai/mxbai-rerank-xsmall-v1", engine="torch")]
)

engine = AsyncEmbeddingEngine.from_args(engine_args)
async def main():
async def rerank(engine: AsyncEmbeddingEngine):
async with engine:
ranking, usage = await engine.rerank(query=query, docs=docs)
print(list(zip(ranking, docs)))
Expand All @@ -63,34 +64,75 @@ async def main():
ranking, usage = await engine.rerank(query=query, docs=docs)
await engine.astop()

asyncio.run(main())
asyncio.run(rerank(array[0]))
```

When using the CLI, use this command to launch rerankers:
```bash
infinity_emb v2 --model-id mixedbread-ai/mxbai-rerank-xsmall-v1
```

Example models:
- [mixedbread-ai/mxbai-rerank-xsmall-v1](https://huggingface.co/mixedbread-ai/mxbai-rerank-xsmall-v1)
- [BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)
- [jinaai/jina-reranker-v1-turbo-en](https://huggingface.co/jinaai/jina-reranker-v1-turbo-en)

## CLIP models

CLIP models are able to encode images and text at the same time.

```python
import asyncio
from infinity_emb import AsyncEngineArray, EngineArgs, AsyncEmbeddingEngine

sentences = ["This is awesome.", "I am bored."]
images = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
engine_args = EngineArgs(
model_name_or_path = "wkcn/TinyCLIP-ViT-8M-16-Text-3M-YFCC15M",
engine="torch"
)
array = AsyncEngineArray.from_args([engine_args])

async def embed(engine: AsyncEmbeddingEngine):
await engine.astart()
embeddings, usage = await engine.embed(sentences=sentences)
embeddings_image, _ = await engine.image_embed(images=images)
await engine.astop()

asyncio.run(embed(array["wkcn/TinyCLIP-ViT-8M-16-Text-3M-YFCC15M"]))
```

Example models:
- [wkcn/TinyCLIP-ViT-8M-16-Text-3M-YFCC15M](https://huggingface.co/wkcn/TinyCLIP-ViT-8M-16-Text-3M-YFCC15M)
- [jinaai/jina-clip-v1](https://huggingface.co/jinaai/jina-clip-v1) (requires `pip install timm`)
- Currently no support for pure vision models: nomic-ai/nomic-embed-vision-v1.5, ..


## Text Classification

Use text classification with Infinity's `classify` feature, which allows for sentiment analysis, emotion detection, and more classification tasks.

```python
import asyncio
from infinity_emb import AsyncEmbeddingEngine, EngineArgs
from infinity_emb import AsyncEngineArray, EngineArgs, AsyncEmbeddingEngine

sentences = ["This is awesome.", "I am bored."]
engine_args = EngineArgs(model_name_or_path = "SamLowe/roberta-base-go_emotions",
engine_args = EngineArgs(
model_name_or_path = "SamLowe/roberta-base-go_emotions",
engine="torch", model_warmup=True)
engine = AsyncEmbeddingEngine.from_args(engine_args)
async def main():
array = AsyncEngineArray.from_args([engine_args])

async def classifier():
async with engine:
predictions, usage = await engine.classify(sentences=sentences)
# or handle the async start / stop yourself.
await engine.astart()
predictions, usage = await engine.classify(sentences=sentences)
await engine.astop()
asyncio.run(main())
asyncio.run(classifier(array["SamLowe/roberta-base-go_emotions"]))
```

Running via CLI requires a new FastAPI schema and server integration - PR's are also welcome there.
Example models:
- [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert)
- [SamLowe/roberta-base-go_emotions](SamLowe/roberta-base-go_emotions)

Loading
Loading