ragas
Local-LLM-Langchain
ragas | Local-LLM-Langchain | |
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10 | 1 | |
4,874 | 207 | |
17.7% | - | |
9.6 | 6.4 | |
3 days ago | 11 months ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | - |
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ragas
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Show HN: Ragas โ the de facto open-source standard for evaluating RAG pipelines
congrats on launching! i think my continuing struggle with looking at Ragas as a company rather than an oss library is that the core of it is like 8 metrics (https://github.com/explodinggradients/ragas/tree/main/src/ra...) that are each 1-200 LOC. i can inline that easily in my app and retain full control, or model that in langchain or haystack or whatever.
why is Ragas a library and a company, rather than an overall "standard" or philosophy (eg like Heroku's 12 Factor Apps) that could maybe be more robust?
(just giving an opp to pitch some underappreciated benefits of using this library)
- FLaNK 04 March 2024
- FLaNK Stack 05 Feb 2024
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SuperDuperDB - how to use it to talk to your documents locally using llama 7B or Mistral 7B?
Also, at some point you'll need to get serious about evaluation (trust me, you will). You may be interested in https://github.com/explodinggradients/ragas
- Ragas โ Framework for RAG Evaluation
- Ragas: Open-source Evaluation framework for RAG pipelines
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Building a customer support chatbot using GPT-3.5 and lLamaIndex๐
The problem becomes worse if you want to inspect outputs from not just one, but several different queries. Luckily, there are several free open source packages such as ragas and DeepEval that can help evaluate your chatbot so you don't have to manually do it ๐
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Patterns for Building LLM-Based Systems and Products
We have build RAGAS framework for this https://github.com/explodinggradients/ragas
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[R] All about evaluating Large language models
Hi u/thecuteturtle, I am building open-source projects for evaluating LLM-based applications. Check it out https://github.com/explodinggradients/ragas and if you like to collaborate let me know :)
Local-LLM-Langchain
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New AutoVicuna projects seems to be chugging along well
Which works, but produces nonsense 90% of the time for me. There's also that one notebook/colab for testing langchain but is above my abilities to use. And there's Auto-Vicuna of course, whose development however seems stalled
What are some alternatives?
deepeval - The LLM Evaluation Framework
text-generation-webui-colab - A colab gradio web UI for running Large Language Models
chameleon-llm - Codes for "Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models".
Anima - 33B Chinese LLM, DPO QLORA, 100K context, AirLLM 70B inference with single 4GB GPU
FastLoRAChat - Instruct-tune LLaMA on consumer hardware with shareGPT data
Auto-Vicuna
agenta - The all-in-one LLM developer platform: prompt management, evaluation, human feedback, and deployment all in one place.
KoAlpaca - KoAlpaca: ํ๊ตญ์ด ๋ช ๋ น์ด๋ฅผ ์ดํดํ๋ ์คํ์์ค ์ธ์ด๋ชจ๋ธ
hngpt - Collecting my favoritet Hacker News stories by LangChain
ReAct - [ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models
babyagi - LangChain + llamaCPP + babyAGI implementation