I got the chance to try Langchain as part of a hiring process. I was already having my eye on it for a personal projects though.
The moment I tried it and went through the docs, the entire abstraction feels weird for me. I know a bit here and there about LLM, but Langchain make me feels like Im learning something entirely new.
How agent and tools work and how to write one wasnt straightforward from the docs, and the idea of having an AI attach itself to an eval or writing its own error/hallucination-prone API request based on a docs doesnt give me a lot of confidence.
The hiring assignment specifically mentioned to use Langchain thought, so I did. But just as a glorified abstraction to call GPT and parses the NL output as JSON.
I did the actual API call, post-processing, etc. manually. Which I have granular control over it. Also cheaper in terms of token usages. You could say I ended writing my own agent/tool that doesnt exactly match Langchain specifications but it works.
I guess Langchain had its use case. But it feels pretty weird to use for me.
The moment I tried it and went through the docs, the entire abstraction feels weird for me. I know a bit here and there about LLM, but Langchain make me feels like Im learning something entirely new.
How agent and tools work and how to write one wasnt straightforward from the docs, and the idea of having an AI attach itself to an eval or writing its own error/hallucination-prone API request based on a docs doesnt give me a lot of confidence.
The hiring assignment specifically mentioned to use Langchain thought, so I did. But just as a glorified abstraction to call GPT and parses the NL output as JSON.
I did the actual API call, post-processing, etc. manually. Which I have granular control over it. Also cheaper in terms of token usages. You could say I ended writing my own agent/tool that doesnt exactly match Langchain specifications but it works.
I guess Langchain had its use case. But it feels pretty weird to use for me.