1filellm
langchain
| 1filellm | langchain | |
|---|---|---|
| 6 | 152 | |
| 224 | 56,526 | |
| - | - | |
| 9.0 | 10.0 | |
| 10 days ago | 10 months ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
1filellm
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Show HN: FileKitty – Combine and label text files for LLM prompt contexts
I created something similar, https://github.com/jimmc414/1filellm
It converts papers, repositories, PRs and web docs into one text file for llm ingestion
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The lifecycle of a code AI completion
I created a cli tool that copies a GitHub or local repo into a text file for llm ingestion. It only pulls the filetypes you specify.
https://github.com/jimmc414/1filellm
- Show HN: Command Line Data Aggregation Tool for LLM Ingestion
- Show HN: Simple CLI to aggregate repos, papers and docs for LLM ingestion
- Code Repo-Prep for LLM Ingestion
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Show HN: GPT Repo Loader – load entire code repos into GPT prompts
Nice. I guess we are all thinking the same things. I created something similar today where you can choose the file extensions to pull and handles Jupiter notebooks pulling only text and code. I included a script to strip out superfluous characters, stop words, and converts everything to lowercase.
It also works if you supply a local folder of source files instead of a github repo.
https://github.com/jimmc414/onefilerepo
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?
gpt-repository-loader - Convert code repos into an LLM prompt-friendly format. Mostly built by GPT-4.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
llama_index - LlamaIndex is a data framework for your LLM applications
AutoPR - Run AI-powered workflows over your codebase
llama - Inference code for Llama models
aidev - AI developer: ask GPT-4 to modify an entire folder full of files
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]
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.
chatgpt-retrieval-plugin - The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.