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update README for new org #117

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54 changes: 28 additions & 26 deletions README.md
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# Locallm
# AI Lab Recipes

This repo contains recipes for building and running containerized AI and LLM Applications locally with podman.
This repo contains recipes for building and running containerized AI and LLM Applications locally with [podman](https://podman.io/).

These containerized AI recipes can be used to help developers quickly prototype new AI and LLM based applications, without the need for relying on any other externally hosted services. Since they are already containerized, it also helps developers move quickly from prototype to production.
These containerized AI recipes can be used to help developers quickly prototype new AI and LLM based applications without the need to rely on any other externally hosted services. Since they are already containerized, it also helps developers move quickly from prototype to production.

## Current Recipes:
## Recipe Categories:

* [Model Service](#model-service)
* [Chatbot](#chatbot)
* [Text Summarization](#text-summarization)
* [Code Generation](#code-generation)
* [RAG](#rag-application) (Retrieval Augmented Generation)
* [Fine-tuning](#fine-tuning)
* [Model Service](#model-services)
* [Natural Language Processing](#natural-language-processing)
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I don't beleive this is a recipe?

* [Audio](#audio)
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Nit: Sort alphabetically

* [Computer Vision](#computer-vision)
* [Multimodal](#multimodal)

### Model service

A model service that can be used for various applications with various models is included in this repository.
Learn how to build and run the model service here: [Llamacpp_python model service](/model_servers/llamacpp_python/README.md).
### Model Services

### Chatbot
Model services can be used for various applications with various models to host endpoints developers can easily integrate into their applications.
* [Llamacpp_python](/model_servers/llamacpp_python/README.md)
* [Whispercpp](/model_servers/whispercpp/README.md)

A simple chatbot using the [Streamlit UI](https://docs.streamlit.io/). Learn how to build and run this application here: [Chatbot](/chatbot-langchain/).

### Text Summarization
### Natural Language Processing

An LLM app that can summarize arbitrarily long text inputs with the [Streamlit UI](https://docs.streamlit.io/). Learn how to build and run this application here:
[Text Summarization](/summarizer-langchain/).
* [Chatbot](/recipes/natural_language_processing/chatbot/)
* [Text Summarization](/recipes/natural_language_processing/summarizer/)
* [Code Generation](/recipes/natural_language_processing/code-generation/)
* [RAG (Retrieval Augmented Generation)](/recipes/natural_language_processing/rag/)

### Code generation
### Audio

A simple chatbot using the [Streamlit UI](https://docs.streamlit.io/). Learn how to build and run this application here: [Code Generation](/code-generation/).
* [Audio Transcription](/recipes/audio/audio-to-text/)

### Computer Vision

* [Object Detection](/recipes/computer_vision/object_detection/)

### Multimodal

* [Image Understanding](/recipes/multimodal/image_understanding/)

### RAG

A chatbot using the [Streamlit UI](https://docs.streamlit.io/) and Retrieval Augmented Generation. Learn how to build and run this application here: [RAG](/rag-langchain/).

### Fine Tuning

This application allows a user to select a model and a data set they'd like to fine-tune that model on.
Once the application finishes, it outputs a new fine-tuned model for the user to apply to other LLM services.
Learn how to build and run this model training job here: [Fine-tuning](/finetune/).

## Current Locallm Images built from this repository

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