From fd5219bb24b72c4dc96bf5b61cb3a3b1120de81e Mon Sep 17 00:00:00 2001 From: Venkatesh Date: Mon, 28 Oct 2024 22:20:44 +0530 Subject: [PATCH] Update README.md with latest enhancements, new models, use cases, and optimizations --- README.md | 70 +++++++++++++++++++++++++++++++++++++++++++------------ 1 file changed, 55 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index c8386c28..6218cbfa 100644 --- a/README.md +++ b/README.md @@ -622,36 +622,76 @@ if __name__ == "__main__": ``` +## 🔥 Latest Enhancements and Features 🔥 -## 🔥 What's New? 🔥 +### Model Capabilities & Benchmarks --**Benchmarking Small Model Capabilities** - see [benchmark results](https://medium.com/@darrenoberst/best-small-language-models-for-accuracy-and-enterprise-use-cases-benchmark-results-cf71964759c8) and [model_ranking example](fast_start/agents/agents-15-get_model_benchmarks.py) +- **Benchmarking Small Model Capabilities** + Explore the latest benchmark results for small language models focusing on accuracy and enterprise use cases. + - [Read benchmark results](https://medium.com/@darrenoberst/best-small-language-models-for-accuracy-and-enterprise-use-cases-benchmark-results-cf71964759c8) + - [Example code for model ranking](fast_start/agents/agents-15-get_model_benchmarks.py) --**Using Qwen2 Models for RAG, Function Calling and Chat** - get started in minutes - see [example](https://github.com/llmware-ai/llmware/tree/main/examples/Models/using-qwen2-models.py) +### New Models and Functionality --**New Phi-3 Function Calling Models** - get started in minutes - see [example](https://github.com/llmware-ai/llmware/tree/main/examples/Models/using-phi-3-function-calls.py) +- **Qwen2 Models for RAG, Function Calling, and Chat** + Start using Qwen2 models quickly with resources for Retrieval-Augmented Generation (RAG), function calling, and chat functionalities. + - [Quickstart example](https://github.com/llmware-ai/llmware/tree/main/examples/Models/using-qwen2-models.py) --**BizBot - RAG + SQL Local Chatbot** - see [example](https://github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/biz_bot.py) and [video](https://youtu.be/4nBYDEjxxTE?si=o6PDPbu0PVcT-tYd) +- **Phi-3 Function Calling Models** + Get started in minutes with Phi-3 models designed for function calling. + - [Quickstart example](https://github.com/llmware-ai/llmware/tree/main/examples/Models/using-phi-3-function-calls.py) -**Lecture Tool Use Case - ask questions to a voice recording** - see [lecture_tool](https://github.com/llmware-ai/llmware/blob/main/examples/Use_Cases/lecture_tool/) +### New Use Cases & Applications --**Web Services with Agent Calls for Financial Research** - end-to-end scenario - [video](https://youtu.be/l0jzsg1_Ik0?si=hmLhpT1iv_rxpkHo) and [example](examples/Use_Cases/web_services_slim_fx.py) +- **BizBot: RAG + SQL Local Chatbot** + Implement a local chatbot for business intelligence using RAG and SQL. + - [Code example](https://github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/biz_bot.py) | [Demo video](https://youtu.be/4nBYDEjxxTE?si=o6PDPbu0PVcT-tYd) --**Voice Transcription with WhisperCPP** - [getting_started](examples/Models/using-whisper-cpp-getting-started.py), [using_sample_files](examples/Models/using-whisper-cpp-sample-files.py), and [analysis_use_case](examples/Use_Cases/parsing_great_speeches.py) with [great_speeches_video](https://youtu.be/5y0ez5ZBpPE?si=KVxsXXtX5TzvlEws) +- **Lecture Tool** + Enables Q&A on voice recordings for education and lecture analysis. + - [Lecture tool code](https://github.com/llmware-ai/llmware/blob/main/examples/Use_Cases/lecture_tool/) --**Phi-3 GGUF Streaming Local Chatbot with UI** - setup your own Phi-3-gguf chatbot on your laptop in minutes - [example](examples/UI/gguf_streaming_chatbot.py) with [video](https://youtu.be/gzzEVK8p3VM?si=8cNn_do0oxSzCEnM) +- **Web Services for Financial Research** + An end-to-end example demonstrating web services with agent calls for financial research. + - [Demo video](https://youtu.be/l0jzsg1_Ik0?si=hmLhpT1iv_rxpkHo) | [Code example](examples/Use_Cases/web_services_slim_fx.py) --**Natural Language Query to CSV End to End example** - using the slim-sql model - [video](https://youtu.be/z48z5XOXJJg?si=V-CX1w-7KRioI4Bi) and [example](examples/SLIM-Agents/text2sql-end-to-end-2.py) and now using Custom Tables on Postgres [example](https://github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/agent_with_custom_tables.py) +### Audio & Text Processing --**Multi-Model Agents with SLIM models** - multi-step Agents with SLIMs on CPU - [video](https://www.youtube.com/watch?v=cQfdaTcmBpY) - [example](examples/SLIM-Agents) +- **Voice Transcription with WhisperCPP** + Start transcription projects with WhisperCPP, featuring tools for sample file usage and famous speeches. + - [Getting started guide](examples/Models/using-whisper-cpp-getting-started.py) | [Parsing great speeches](examples/Use_Cases/parsing_great_speeches.py) | [Demo video](https://youtu.be/5y0ez5ZBpPE?si=KVxsXXtX5TzvlEws) --**OCR Embedded Document Images Example** - systematically extract text from images embedded in documents [example](examples/Parsing/ocr_embedded_doc_images.py) +- **Natural Language Query to CSV** + Convert natural language queries to CSV with Slim-SQL, supporting custom Postgres tables. + - [Demo video](https://youtu.be/z48z5XOXJJg?si=V-CX1w-7KRioI4Bi) | [End-to-end example](examples/SLIM-Agents/text2sql-end-to-end-2.py) | [Custom table usage](https://github.com/llmware-ai/llmware/tree/main/examples/Use_Cases/agent_with_custom_tables.py) --**Enhanced Parser Functions for PDF, Word, Powerpoint and Excel** - new text-chunking controls and strategies, extract tables, images, header text - [example](examples/Parsing/pdf_parser_new_configs.py) +### Multi-Model Agents + +- **Multi-Model Agents with SLIM** + Use SLIM models on CPU for multi-step agents in complex workflows. + - [Demo video](https://www.youtube.com/watch?v=cQfdaTcmBpY) | [Example directory](examples/SLIM-Agents) + +### Document & OCR Processing + +- **OCR Embedded Document Images** + Extract text systematically from images embedded in documents for enhanced document processing. + - [OCR example](examples/Parsing/ocr_embedded_doc_images.py) + +- **Enhanced Document Parsing for PDFs, Word, PowerPoint, and Excel** + Improved text-chunking controls, table extraction, and content parsing. + - [Parsing example](examples/Parsing/pdf_parser_new_configs.py) + +### Deployment & Optimization + +- **Agent Inference Server** + Set up an inference server for multi-model agents to optimize deployments. + - [Server setup example](https://github.com/llmware-ai/llmware/tree/main/examples/SLIM-Agents/agent_api_endpoint.py) + +- **Optimizing Accuracy of RAG Prompts** + Tutorials for tuning RAG prompt settings for increased accuracy. + - [Settings example](examples/Models/adjusting_sampling_settings.py) | Videos: [Part I](https://youtu.be/7oMTGhSKuNY?si=14mS2pftk7NoKQbC), [Part II](https://youtu.be/iXp1tj-pPjM?si=T4teUAISnSWgtThu) --**Agent Inference Server** - set up multi-model Agents over Inference Server [example](https://github.com/llmware-ai/llmware/tree/main/examples/SLIM-Agents/agent_api_endpoint.py) --**Optimizing Accuracy of RAG Prompts** - check out [example](examples/Models/adjusting_sampling_settings.py) and videos - [part I](https://youtu.be/7oMTGhSKuNY?si=14mS2pftk7NoKQbC) and [part II](https://youtu.be/iXp1tj-pPjM?si=T4teUAISnSWgtThu) ## 🌱 Getting Started