gpt_index
langchain
gpt_index | langchain | |
---|---|---|
48 | 152 | |
7,332 | 56,526 | |
- | - | |
9.8 | 10.0 | |
about 1 year ago | 9 months ago | |
Python | Python | |
MIT License | MIT License |
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gpt_index
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Basic links to get started with Prompt Programming
LLAMA Index Github repository
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Leak: Metas GPT-Herausforderer LLaMA als Torrent verfügbar
Zuwendungen kommen auch so langsam ( LLamaIndex ) https://github.com/jerryjliu/gpt_index
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Large language models are having their Stable Diffusion moment
This is exactly what LlamaIndex is meant to solve!
A set of data structures to augment LLM's with your data: https://github.com/jerryjliu/gpt_index
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ChatGPT's API Is So Good and Cheap, It Makes Most Text Generating AI Obsolete
This is what we've designed LlamaIndex for! https://github.com/jerryjliu/gpt_index. Designed to help you "index" over a large doc corpus in different ways for use with LLM prompts.
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Is there a way I can have ChatGPT look at a document of mine?
https://github.com/jerryjliu/gpt_index might be close to what you need.
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AI is making it easier to create more noise, when all I want is good search
I would start with https://gpt-index.readthedocs.io/en/latest/ and https://langchain.readthedocs.io/en/latest/
- GitHub - jerryjliu/gpt_index: LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data.
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Using OpenAI with self hosted knowledge database
People have been doing this with https://github.com/jerryjliu/gpt_index
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Long form content
Here is a link to the repository. Take a look at the overview section of the readme. https://github.com/jerryjliu/gpt_index
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LLaMA: A foundational, 65B-parameter large language model
(creator of gpt index / llamaindex here https://github.com/jerryjliu/gpt_index)
Funny that we had just rebranded our tool from GPT Index to LlamaIndex about a week ago to avoid potential trademark issues with OpenAI, and turns out Meta has similar ideas around LLM+llama puns :). Must mean the name is good though!
Also very excited to try plugging in the LLaMa model into LlamaIndex, will report the results.
langchain
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🗣️🤖 Ask to your Neo4J knowledge base in NLP & get KPIs
Langchain and the implementation of Custom Tools also is a great (and very efficient) way to setup a dedicated Q&A (for example for chat purpose) agent.
- LangChain – Some quick, high level thoughts on improvements/changes
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Claude 2 Internal API Client and CLI
We're using it via langchain talking to Amazon Bedrock which is hosting Claude 1.x. It's comparable to GPT3.x, not bad. The integration doesn't seem to be fully there though, I think langchain is expecting "Human:" and "AI:", but Claude uses "Assistant:".
https://github.com/hwchase17/langchain/issues/2638
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Any better alternatives to fine-tuning GPT-3 yet to create a custom chatbot persona based on provided knowledge for others to use?
Depending on how much work you want to put into it, you can get started at HuggingFace with their models and datasets, but you'd need compute power, multiple MLOps, etc. I was introduced to the concept in this video, since Google has their Vertex AI tools on Google Cloud, and there's always LangChain but I'm not sure about anything recent.
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langchain VS griptape - a user suggested alternative
2 projects | 11 Jul 20232 projects | 9 Jul 2023
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Vector storage is coming to Meilisearch to empower search through AI
a documentation chatbot proof of concept using GPT3.5 and LangChain
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ChatPDF: What ChatGPT Can't Do, This Can!
I encourage everyone to pay attention to the Langchain open-source project and leverage it to achieve tasks that ChatGPT cannot handle.
- LangChain Arbitrary Command Execution - CVE-2023-34541
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Langchain Is Pointless
Yeah I never know where memory goes exactly in langchain, it's not exactly clear all the time. But sure, the main insight I remember is this, take a look at their MULTI_PROMPT_ROUTER_TEMPLATE: https://github.com/hwchase17/langchain/blob/560c4dfc98287da1...
It's a lot of instructions for an LLM, they seem to forget an LLM is an auto-completion machine, and which data it is trained on. Using <<>> for sections is not a normal thing, it's not markdown, which probably the thing read way more often on the internet, instead of open json comments, why not type signatures, instead of so many rules, why not give it examples? It is an autocomplete machine!
They are relying too much on the LLM being smart because they probably only test stuff in GPT-4 and 3.5, but with GPT4All models this prompt was not working at all, so I had to rewrite it, for simple routing, we don't even need json, carying the `next_inputs` here is weird if you don't need it.
So this is my version of it: https://gist.github.com/rogeriochaves/b67676977eebb1936b9b5c...
It's so basic it's dumb, yet it is more powerful, as it does not rely on GPT-4 level intelligence, it's just what I needed
What are some alternatives?
llama - Inference code for Llama models
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better.
llama_index - LlamaIndex is a data framework for your LLM applications
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
openai-cookbook - Examples and guides for using the OpenAI API
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.