llama-hub
langchain
llama-hub | langchain | |
---|---|---|
5 | 36 | |
3,359 | 84,994 | |
- | 5.2% | |
9.6 | 10.0 | |
3 months ago | 4 days ago | |
Jupyter Notebook | 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.
llama-hub
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LlamaCloud and LlamaParse
mean_faithfulness_score 0.667
Notably, the faithfulness score I measured for the baseline solution was actually higher than that reported for your proprietary LlamaParse based solution.
[1] https://github.com/run-llama/llama-hub/tree/main/llama_hub/l...
- Llama Hub
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A Comprehensive Guide for Building Rag-Based LLM Applications
My favorite example is the asana loader[0] for llama-index. It's literally just the most basic wrapper around the Asana SDK to concatenate some strings.
[0] - https://github.com/emptycrown/llama-hub/blob/main/llama_hub/...
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Outlook local calendar loader for LlamaIndex now in LLamaHub
My loader to get events from the local version of an Outlook calendar into documents suitable for LLamaIndex indexing is now available on github.. Like other loaders (there are a lot of them), it's available at https://github.com/emptycrown/llama-hub To make it easy for developers, this loader has a superset of the functions the Google calandar loader has and the same defaults. Since it works off the local calendar, however, no apikeys are needed. This is Windows only.
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Hello, is there a "BEST OF" prompts list here somewhere?
LLAMA GitHub repository
langchain
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Deploy LangServe Application to AWS
Limited by the current packaging method of Pluto, it does not yet support LangChain's Template Ecosystem. Coming soon
- Construyendo un asistente genAI de WhatsApp con Amazon Bedrock
- Show HN: SpRAG – Open-source RAG implementation for challenging real-world tasks
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Aider: AI pair programming in your terminal
Big fan of Aider.
We are interesting in integrating Aider as a tool for Dosu https://dosu.dev/ to help it navigate and modify a codebase on issues like this https://github.com/langchain-ai/langchain/issues/8263#issuec...
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🦙 Llama-2-GGML-CSV-Chatbot 🤖
Developed using Langchain and Streamlit technologies for enhanced performance.
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Building a WhatsApp generative AI assistant with Amazon Bedrock and Python
Tip: Kenton Blacutt, an AWS Associate Cloud App Developer, collaborated with Langchain, creating the Amazon Dynamodb based memory class that allows us to store the history of a langchain agent in an Amazon DynamoDB.
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👑 Top Open Source Projects of 2023 🚀
LangChain was first released in October 2022 as an open-source side project, a framework that makes developing AI applications more flexible. It got so popular that it was promptly turned into a startup.
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Fuck You, Show Me the Prompt
> Furthermore, the prompt has a spelling error (Let'w) and also overly focuses on the negative about identifying errors - which makes me skeptical that this prompt has been optimized or tested.
Fixed in https://github.com/langchain-ai/langchain/commit/7c6009b76f0...
- LangChain Repository Disappeared
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🆓 Local & Open Source AI: a kind ollama & LlamaIndex intro
Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects
What are some alternatives?
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]
llama_index - LlamaIndex is a data framework for your LLM applications
LLMStack - No-code platform to build LLM Agents, workflows and applications with your data
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
model.nvim - Neovim plugin for interacting with LLM's and building editor integrated prompts.
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.
vectara-answer - LLM-powered Conversational AI experience using Vectara
griptape - Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.
llm-applications - A comprehensive guide to building RAG-based LLM applications for production.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
langchain - âš¡ Building applications with LLMs through composability âš¡ [Moved to: https://github.com/langchain-ai/langchain]
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks