llama_index
langchain
| llama_index | langchain | |
|---|---|---|
| 78 | 69 | |
| 40,945 | 105,855 | |
| 4.1% | 3.8% | |
| 9.9 | 10.0 | |
| 7 days ago | 4 days ago | |
| Python | Jupyter Notebook | |
| 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_index
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Complete Large Language Model (LLM) Learning Roadmap
Resource: LlamaIndex Documentation
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Quick tip: Replace MongoDB® Atlas with SingleStore Kai in LlamaIndex
The notebook is adapted from the LlamaIndex GitHub repo.
- Show HN: Route your prompts to the best LLM
- LlamaIndex: A data framework for your LLM applications
- FLaNK AI - 01 April 2024
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Show HN: Ragdoll Studio (fka Arthas.AI) is the FOSS alternative to character.ai
For anyone curious llamaindex's "prompt mixins", they're actually dead simple: https://github.com/run-llama/llama_index/blob/8a8324008764a7... - and maybe no longer supported.
I basically reinvented this wheel in ragdoll but made it more dynamic: https://github.com/bennyschmidt/ragdoll/blob/master/src/util...
- LlamaIndex is a data framework for your LLM applications
- How to verify that a snippet of Python code doesn't access protected members
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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
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I made an app that runs Mistral 7B 0.2 LLM locally on iPhone Pros
Mistral Instruct does use a system prompt.
You can see the raw format here: https://www.promptingguide.ai/models/mistral-7b#chat-templat... and you can see how LllamaIndex uses it here (as an example): https://github.com/run-llama/llama_index/blob/1d861a9440cdc9...
langchain
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AI Agents and the Future of App Development: A Beginner's Guide (101)
🛠️ Want to try building your own AI agent? Frameworks like LangChain and LangGraph give you building blocks for AI workflows. LangChain connects agents to tools and data. LangGraph lets you design agent-based systems using stateful workflows, memory, retries, and branching logic.
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15,000 lines of verified cryptography now in Python
Yeah.
Even patch version upgrade from 3.12.3 to 3.12.4 broke a lot of packages.
https://github.com/langchain-ai/langchain/issues/22692
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Everything about AI Function Calling (MCP), the keyword for Agentic AI
But what about today? Has function calling conquered the world? No—rather than function calling, agent workflow-driven development has become dominant in the AI development ecosystem. langchain is perhaps the most representative framework in this workflow ecosystem.
- Construyendo un sistema RAG para búsqueda y análisis de contenido de video
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Building a RAG System for Video Content Search and Analysis
In the code you'll find a modification of the langchain custom Retriever that allows you to retrieve images and text as the context.
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Build an Instant HR Policy Q&A Bot with Chainlit
langchain, langchain-openai, openai: For LLM interaction and RAG components (LangChain Docs).
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Build AI Agent Memory From Scratch — Tutorial For Dummies
Vector Store Retriever Memory
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Function Calling vs. Model Context Protocol (MCP): What You Need to Know
Each model formats function calls differently, meaning there’s no universal standard yet. However, tools like LangChain help developers work with multiple LLMs by handling these variations.
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Streamlining Routine ML Tasks with LangChain: A Hacker News Comment Analysis Example
LangChain and its companion framework LangGraph are synonymous with building autonomous "agents" capable of complex interactions -- retrieving external data, chaining multiple tools together, to name just a few. While that's certainly the case, I noticed they streamline more mundane day-to-day ML tasks.
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LangChain + FalkorDB: Building AI Agents with Memory
FalkorDB’s integration with Langchain enables developers to create AI agents with memory, enhancing their ability to maintain context and provide more nuanced responses over time.
What are some alternatives?
gpt-llama.cpp - A llama.cpp drop-in replacement for OpenAI's GPT endpoints, allowing GPT-powered apps to run off local llama.cpp models instead of OpenAI.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
text-generation-webui - A Gradio web UI for Large Language Models with support for multiple inference backends.
langflow - Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
langchain4j - Java version of LangChain