langchain
dust
| langchain | dust | |
|---|---|---|
| 152 | 12 | |
| 56,526 | 862 | |
| - | 3.4% | |
| 10.0 | 10.0 | |
| 10 months ago | 5 days ago | |
| Python | TypeScript | |
| MIT License | MIT License |
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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
dust
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What are the best AI tools you've ACTUALLY used?
Dust: An encrypted messaging app.
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Apparently You can Perform a Tree of Thought Like Prompt with a single ChatGPT prompt
do you think it is at all similar to how dust.tt has implemented it?
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Hackathon Ideas? Gen AI
Examples of apps using LLMs https://github.com/openai/openai-cookbook https://gpt-index.readthedocs.io/en/latest/gallery/app_showcase.html https://dust.tt/
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What’s your biggest complaint about langchain?
I will also look at https://www.pinecone.io/learn/ https://github.com/openai/openai-cookbook https://gpt-index.readthedocs.io/en/latest/gallery/app_showcase.html https://dust.tt/ (some of them do not use langchain but follow a similar pattern)
- Dust.tt: Design and Deploy Large Language Model Apps
- Dust.tt: Large Language Model Orchestration
- Compiling a list of tools for building LLM apps
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Uminal - Extending GPT-3 with new apps/skills that are auto-composable
[1] https://dust.tt — https://github.com/dust-tt/dust
- Show HN: Uminal – Large language model anyone can extend with new apps/skills
What are some alternatives?
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
langchain - 🦜🔗 Build context-aware reasoning applications
llama_index - LlamaIndex is a data framework for your LLM applications
AgentGPT - 🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
llama - Inference code for Llama models
chatGPTBox - Integrating ChatGPT into your browser deeply, everything you need is here
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
AGiXT - AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.
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]
tree-of-thought-puzzle-solver - The Tree of Thoughts (ToT) framework for solving complex reasoning tasks using LLMs
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.
dev-gpt - Your Virtual Development Team