3 ms·

What are some better options?

• minimaxir 3y ago
  Not using an abstraction at all and avoiding the technical debt it causes.
• hospitalJail 3y ago
  Don't use langchain, just make the calls? Its what I ended up doing.
• dragonwriter 3y ago
  Have a fairly thin layer than wraps the underlying LLM behind a common API (e.g., Ollama as being discussed here, Oobabooga, etc.) and leaves the application-level stuff for the application rather than a framework like LangChain. (Better for certain use cases, that is, I’m not saying LangChain doesn't have uses.)
• bdcs 3y ago
  https://www.llamaindex.ai/ https://www.llamaindex.ai/ is much better IMO, but it's definitely a case of boilerplate-y, well-supported incumbent vs smaller, better, less supported (e.g. Java vs Python in the 00s or something like that). Depends on your team and your needs. Also Autogen seems popular and well-ish liked https://microsoft.github.io/autogen/ https://microsoft.github.io/autogen/ LangChain definitely has the most market-/mind- share. For example, GCP has a blog post on supporting it: https://cloud.google.com/blog/products/ai-machine-learning/deploy-langchain-on-cloud-run-with-langserve https://cloud.google.com/blog/products/ai-machine-learning/d...
• v3ss0n 3y ago
  Haystack is much better option and way alot flexible, scalable