Metadata-Version: 2.4
Name: litserve
Version: 0.2.8.dev0
Summary: Lightweight AI server.
Home-page: https://github.com/Lightning-AI/litserve
Download-URL: https://github.com/Lightning-AI/litserve
Author: Lightning-AI et al.
Author-email: community@lightning.ai
License: Apache-2.0
Project-URL: Bug Tracker, https://github.com/Lightning-AI/litserve/issues
Project-URL: Documentation, https://lightning-ai.github.io/litserve/
Project-URL: Source Code, https://github.com/Lightning-AI/litserve
Keywords: deep learning,pytorch,AI
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: fastapi>=0.100
Requires-Dist: uvicorn[standard]>=0.29.0
Requires-Dist: pyzmq>=22.0.0
Requires-Dist: starlette
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: download-url
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

<div align='center'>

# Easily serve AI models Lightning fast ⚡    

<img alt="Lightning" src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/ls_banner2.png" width="800px" style="max-width: 100%;">

&nbsp;

<strong>Lightning-fast serving engine for AI models.</strong>    
Easy. Flexible. Enterprise-scale.    
</div>

----

**LitServe** is an easy-to-use, flexible serving engine for AI models built on FastAPI. It augments FastAPI with features like batching, streaming, and GPU autoscaling eliminate the need to rebuild a FastAPI server per model.  

LitServe is at least [2x faster](#performance) than plain FastAPI due to AI-specific multi-worker handling.    

<div align='center'>
  
<pre>
✅ (2x)+ faster serving  ✅ Easy to use               ✅ LLMs, non LLMs and more
✅ Bring your own model  ✅ PyTorch/JAX/TF/...        ✅ Built on FastAPI       
✅ GPU autoscaling       ✅ Batching, Streaming       ✅ Self-host or ⚡️ managed
✅ Compound AI           ✅ Integrate with vLLM, etc  ✅ Serverless             
   
</pre>

<div align='center'>

[![Discord](https://img.shields.io/discord/1077906959069626439?label=Get%20help%20on%20Discord)](https://discord.gg/WajDThKAur)
![cpu-tests](https://github.com/Lightning-AI/litserve/actions/workflows/ci-testing.yml/badge.svg)
[![codecov](https://codecov.io/gh/Lightning-AI/litserve/graph/badge.svg?token=SmzX8mnKlA)](https://codecov.io/gh/Lightning-AI/litserve)
[![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/Lightning-AI/litserve/blob/main/LICENSE)

</div>
</div>
<div align="center">
  <div style="text-align: center;">
    <a target="_blank" href="#quick-start" style="margin: 0 10px;">Quick start</a> •
    <a target="_blank" href="#featured-examples" style="margin: 0 10px;">Examples</a> •
    <a target="_blank" href="#features" style="margin: 0 10px;">Features</a> •
    <a target="_blank" href="#performance" style="margin: 0 10px;">Performance</a> •
    <a target="_blank" href="#hosting-options" style="margin: 0 10px;">Hosting</a> •
    <a target="_blank" href="https://lightning.ai/docs/litserve" style="margin: 0 10px;">Docs</a>
  </div>
</div>

&nbsp;

<div align="center">
<a target="_blank" href="https://lightning.ai/docs/litserve/home/get-started">
  <img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/get-started-badge.svg" height="36px" alt="Get started"/>
</a>
</div>

&nbsp; 

# Quick start

Install LitServe via pip ([more options](https://lightning.ai/docs/litserve/home/install)):

```bash
pip install litserve
```
    
### Define a server    
This toy example with 2 models (AI compound system) shows LitServe's flexibility ([see real examples](#examples)):    

```python
# server.py
import litserve as ls

# (STEP 1) - DEFINE THE API (compound AI system)
class SimpleLitAPI(ls.LitAPI):
    def setup(self, device):
        # setup is called once at startup. Build a compound AI system (1+ models), connect DBs, load data, etc...
        self.model1 = lambda x: x**2
        self.model2 = lambda x: x**3

    def decode_request(self, request):
        # Convert the request payload to model input.
        return request["input"] 

    def predict(self, x):
        # Easily build compound systems. Run inference and return the output.
        squared = self.model1(x)
        cubed = self.model2(x)
        output = squared + cubed
        return {"output": output}

    def encode_response(self, output):
        # Convert the model output to a response payload.
        return {"output": output} 

# (STEP 2) - START THE SERVER
if __name__ == "__main__":
    # scale with advanced features (batching, GPUs, etc...)
    server = ls.LitServer(SimpleLitAPI(), accelerator="auto", max_batch_size=1)
    server.run(port=8000)
```

Now run the server anywhere (local or cloud) via the command-line.

```bash
# Deploy to the cloud of your choice via Lightning AI (serverless, autoscaling, etc.)
lightning serve server.py

# Or run locally (self host anywhere)
lightning serve server.py --local
```
Learn more about managed hosting on [Lightning AI](#hosting-options).

You can also run the server manually:

```bash 
python server.py
```

### Test the server
Run the auto-generated test client:        
```bash
python client.py    
```

Or use this terminal command:
```bash
curl -X POST http://127.0.0.1:8000/predict -H "Content-Type: application/json" -d '{"input": 4.0}'
```

### LLM serving
LitServe isn’t *just* for LLMs like vLLM or Ollama; it serves any AI model with full control over internals ([learn more](https://lightning.ai/docs/litserve/features/serve-llms)).    
For easy LLM serving, integrate [vLLM with LitServe](https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api), or use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm) (built on LitServe). 

```
litgpt serve microsoft/phi-2
```

### Summary
- LitAPI lets you easily build complex AI systems with one or more models ([docs](https://lightning.ai/docs/litserve/api-reference/litapi)).
- Use the setup method for one-time tasks like connecting models, DBs, and loading data ([docs](https://lightning.ai/docs/litserve/api-reference/litapi#setup)).        
- LitServer handles optimizations like batching, GPU autoscaling, streaming, etc... ([docs](https://lightning.ai/docs/litserve/api-reference/litserver)).
- Self host on your machines or create a fully managed deployment with Lightning ([learn more](https://lightning.ai/docs/litserve/features/deploy-on-cloud)).

[Learn how to make this server 200x faster](https://lightning.ai/docs/litserve/home/speed-up-serving-by-200x).    

&nbsp;

# Featured examples    
Use LitServe to deploy any model or AI service: (Compound AI, Gen AI, classic ML, embeddings, LLMs, vision, audio, etc...)       
  
<pre>
<strong>Toy model:</strong>      <a target="_blank" href="#define-a-server">Hello world</a>
<strong>LLMs:</strong>           <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-llama-3-2-vision-with-litserve">Llama 3.2</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/openai-fault-tolerant-proxy-server">LLM Proxy server</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-ai-agent-with-tool-use">Agent with tool use</a>
<strong>RAG:</strong>            <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api">vLLM RAG (Llama 3.2)</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-1-rag-api">RAG API (LlamaIndex)</a>
<strong>NLP:</strong>            <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-any-hugging-face-model-instantly">Hugging face</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-hugging-face-bert-model">BERT</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-text-embedding-api-with-litserve">Text embedding API</a>
<strong>Multimodal:</strong>     <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-open-ai-clip-with-litserve">OpenAI Clip</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-multi-modal-llm-with-minicpm">MiniCPM</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-phi3-5-vision-api-with-litserve">Phi-3.5 Vision Instruct</a>, <a target="_blank" href="https://lightning.ai/bhimrajyadav/studios/deploy-and-chat-with-qwen2-vl-using-litserve">Qwen2-VL</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-multi-modal-llm-with-pixtral">Pixtral</a>
<strong>Audio:</strong>          <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-open-ai-s-whisper-model">Whisper</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-music-generation-api-with-meta-s-audio-craft">AudioCraft</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-audio-generation-api">StableAudio</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-noise-cancellation-api-with-deepfilternet">Noise cancellation (DeepFilterNet)</a>
<strong>Vision:</strong>         <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-private-api-for-stable-diffusion-2">Stable diffusion 2</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-image-generation-api-with-auraflow">AuraFlow</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-image-generation-api-with-flux">Flux</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-super-resolution-image-api-with-aura-sr">Image Super Resolution (Aura SR)</a>,
                <a target="_blank" href="https://lightning.ai/bhimrajyadav/studios/deploy-background-removal-api-with-litserve">Background Removal</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-controlled-image-generation-api-controlnet">Control Stable Diffusion (ControlNet)</a>
<strong>Speech:</strong>         <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-a-voice-clone-api-coqui-xtts-v2-model">Text-speech (XTTS V2)</a>, <a target="_blank" href="https://lightning.ai/bhimrajyadav/studios/deploy-a-speech-generation-api-using-parler-tts-powered-by-litserve">Parler-TTS</a>
<strong>Classical ML:</strong>   <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-random-forest-with-litserve">Random forest</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-xgboost-with-litserve">XGBoost</a>
<strong>Miscellaneous:</strong>  <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-an-media-conversion-api-with-ffmpeg">Media conversion API (ffmpeg)</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/deploy-both-pytorch-and-tensorflow-in-a-single-api">PyTorch + TensorFlow in one API</a>, <a target="_blank" href="https://lightning.ai/lightning-ai/studios/openai-fault-tolerant-proxy-server">LLM proxy server</a>
</pre>
</pre>

[Browse 100+ community-built templates](https://lightning.ai/studios?section=serving)

&nbsp;


# Hosting options   
Self host LitServe anywhere or deploy to your favorite cloud via [Lightning AI](http://lightning.ai/deploy).

https://github.com/user-attachments/assets/ff83dab9-0c9f-4453-8dcb-fb9526726344

Self-hosting is ideal for hackers, students, and DIY developers while fully managed hosting is ideal for enterprise developers needing easy autoscaling, security, release management, and 99.995% uptime and observability.

To host on [Lightning AI](https://lightning.ai/deploy), simply add the `--cloud` arg, login and choose the cloud of your choice.
```bash
lightning serve api server.py --cloud
```

&nbsp;

<div align='center'>

| [Feature](https://lightning.ai/docs/litserve/features)               | Self Managed                      | [Fully Managed on Lightning](https://lightning.ai/deploy)         |
|----------------------------------------------------------------------|-----------------------------------|------------------------------------|
| Docker-first deployment          | ✅ DIY                             | ✅ One-click deploy                |
| Cost                             | ✅ Free (DIY)                      | ✅ Generous [free tier](https://lightning.ai/pricing) with pay as you go                |
| Full control                     | ✅                                 | ✅                                 |
| Use any engine (vLLM, etc.)      | ✅                                 | ✅ vLLM, Ollama, LitServe, etc.    |
| Own VPC                          | ✅ (manual setup)                  | ✅ Connect your own VPC            |
| [(2x)+ faster than plain FastAPI](#performance)                                               | ✅       | ✅                                 |
| [Bring your own model](https://lightning.ai/docs/litserve/features/full-control)              | ✅       | ✅                                 |
| [Build compound systems (1+ models)](https://lightning.ai/docs/litserve/home)                 | ✅       | ✅                                 |
| [GPU autoscaling](https://lightning.ai/docs/litserve/features/gpu-inference)                  | ✅       | ✅                                 |
| [Batching](https://lightning.ai/docs/litserve/features/batching)                              | ✅       | ✅                                 |
| [Streaming](https://lightning.ai/docs/litserve/features/streaming)                            | ✅       | ✅                                 |
| [Worker autoscaling](https://lightning.ai/docs/litserve/features/autoscaling)                 | ✅       | ✅                                 |
| [Serve all models: (LLMs, vision, etc.)](https://lightning.ai/docs/litserve/examples)         | ✅       | ✅                                 |
| [Supports PyTorch, JAX, TF, etc...](https://lightning.ai/docs/litserve/features/full-control) | ✅       | ✅                                 |
| [OpenAPI compliant](https://www.openapis.org/)                                                | ✅       | ✅                                 |
| [Open AI compatibility](https://lightning.ai/docs/litserve/features/open-ai-spec)             | ✅       | ✅                                 |
| [Authentication](https://lightning.ai/docs/litserve/features/authentication)                  | ❌ DIY   | ✅ Token, password, custom         |
| GPUs                             | ❌ DIY                             | ✅ 8+ GPU types, H100s from $1.75  |
| Load balancing                   | ❌                                 | ✅ Built-in                        |
| Scale to zero (serverless)       | ❌                                 | ✅ No machine runs when idle       |
| Autoscale up on demand           | ❌                                 | ✅ Auto scale up/down              |
| Multi-node inference             | ❌                                 | ✅ Distribute across nodes         |
| Use AWS/GCP credits              | ❌                                 | ✅ Use existing cloud commits      |
| Versioning                       | ❌                                 | ✅ Make and roll back releases     |
| Enterprise-grade uptime (99.95%) | ❌                                 | ✅ SLA-backed                      |
| SOC2 / HIPAA compliance          | ❌                                 | ✅ Certified & secure              |
| Observability                    | ❌                                 | ✅ Built-in, connect 3rd party tools|
| CI/CD ready                      | ❌                                 | ✅ Lightning SDK                   |
| 24/7 enterprise support          | ❌                                 | ✅ Dedicated support               |
| Cost controls & audit logs       | ❌                                 | ✅ Budgets, breakdowns, logs       |
| Debug on GPUs                    | ❌                                 | ✅ Studio integration              |
| [20+ features](https://lightning.ai/docs/litserve/features)                    | -                                 | -                                  |

</div>

&nbsp;

# Performance  
LitServe is designed for AI workloads. Specialized multi-worker handling delivers a minimum **2x speedup over FastAPI**.    

Additional features like batching and GPU autoscaling can drive performance well beyond 2x, scaling efficiently to handle more simultaneous requests than FastAPI and TorchServe.
    
Reproduce the full benchmarks [here](https://lightning.ai/docs/litserve/home/benchmarks) (higher is better).  

<div align="center">
  <img alt="LitServe" src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/ls_charts_v6.png" width="1000px" style="max-width: 100%;">
</div> 

These results are for image and text classification ML tasks. The performance relationships hold for other ML tasks (embedding, LLM serving, audio, segmentation, object detection, summarization etc...).   
    
***💡 Note on LLM serving:*** For high-performance LLM serving (like Ollama/vLLM), integrate [vLLM with LitServe](https://lightning.ai/lightning-ai/studios/deploy-a-private-llama-3-2-rag-api), use [LitGPT](https://github.com/Lightning-AI/litgpt?tab=readme-ov-file#deploy-an-llm), or build your custom vLLM-like server with LitServe. Optimizations like kv-caching, which can be done with LitServe, are needed to maximize LLM performance.

&nbsp;


# Community
LitServe is a [community project accepting contributions](https://lightning.ai/docs/litserve/community) - Let's make the world's most advanced AI inference engine.

💬 [Get help on Discord](https://discord.com/invite/XncpTy7DSt)    
📋 [License: Apache 2.0](https://github.com/Lightning-AI/litserve/blob/main/LICENSE)    
