langchain VS haystack

Compare langchain vs haystack and see what are their differences.

langchain

πŸ¦œπŸ”— Build context-aware reasoning applications (by langchain-ai)

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. (by deepset-ai)
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langchain haystack
31 55
83,220 13,633
6.5% 5.8%
10.0 9.9
4 days ago 4 days ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

langchain

Posts with mentions or reviews of langchain. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-10.

haystack

Posts with mentions or reviews of haystack. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-28.

What are some alternatives?

When comparing langchain and haystack you can also consider the following projects:

llama_index - LlamaIndex is a data framework for your LLM applications

langchain - ⚑ Building applications with LLMs through composability ⚑ [Moved to: https://github.com/langchain-ai/langchain]

semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps

gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

griptape - Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.

BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!

text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks

jina - ☁️ Build multimodal AI applications with cloud-native stack

langchain4j - Java version of LangChain

BERT-pytorch - Google AI 2018 BERT pytorch implementation