parsee-datasets
llm-chatbot-rag
| parsee-datasets | llm-chatbot-rag | |
|---|---|---|
| 2 | 1 | |
| 15 | 38 | |
| - | - | |
| 6.4 | 6.1 | |
| 19 days ago | about 2 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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parsee-datasets
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FinRAG Datasets and Study
To test this, we created 3 different datasets, all based on the same selection of 1,156 randomly selected annual reports for the year 2023 of publicly listed US companies.
The resulting (fully labeled) datasets contain a combined total of 10,404 rows, 37,536,847 tokens and 1,156 images and can be found on Github and Huggingface: https://github.com/parsee-ai/parsee-datasets/tree/main/datas...
For our study, we are evaluating 8 state-of-the-art (M)LLMs on a subset of 100 reports with some interesting results.
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Parsee.ai – a framework to easily extract complex structured data with LLMs
Yes, another LLM framework. This one is specialized on extracting structured data from various document types (mainly PDFs, images and HTML files).
Comes with a new (separate) PDF extraction library that is focused on the extraction of numeric tables (tables with numbers, so especially for the financial domain): https://github.com/parsee-ai/parsee-pdf-reader
Helps to easily set up a dataset to evaluate the performance of various LLMs on data extraction tasks, e.g. extracting revenue figures from financial reports: https://github.com/parsee-ai/parsee-datasets/tree/main/datas...
llm-chatbot-rag
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Ask HN: What is the current (Apr. 2024) gold standard of running an LLM locally?
Paywall article: https://towardsdatascience.com/how-to-build-a-local-open-sou...
Source code: https://github.com/leoneversberg/llm-chatbot-rag
What are some alternatives?
ProTaska-GPT - Unleash the Potential of Datasets with Intelligent Tasks, Tutorials, and Algorithm Recommendations.
tiger - Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)
LangChain-SynData-RAG-Eval - LangChain, Llama2-Chat, and zero- and few-shot prompting are used to generate synthetic datasets for IR and RAG system evaluation
instinct.cpp - instinct.cpp provides ready to use alternatives to OpenAI Assistant API and built-in utilities for developing AI Agent applications (RAG, Chatbot, Code interpreter) powered by language models. Call it langchain.cpp if you like.