I've experimented with LangChain for my chatbot as well, but ultimately, I resorted to using custom Python. Here are a few issues I faced with LangChain:
- By developing your own solutions, you can engineer specific components that would be provided by LangChain to better suit your use case. For example, by fine-tuning to your use case you can have better results with converation history, context and summarization better by prompt engineering. If you look at prompts within langchain they are pretty basic.
- LangChain is designed around the idea that an entire chat logic resides within a single "REPL loop." In my use case, I had a single-page web app frontend, a standard web "RESTful" backend, and a separate chat service. Different parts of the information are stored and managed by these components. Using LangChain would have forced me to consolidate all logic into the chat service, which doesn't align with the overall architecture of my system beyond just the chat functionality.
Please note that I'm not a LangChain expert, so my assessment might not be entirely accurate about its capabilities. However, based on my evaluation, LangChain introduced too many constraints in comparison to what it provided.
This, I just pretty much ended up using the basic LLMChain and do my own custom flow. The built in agents are close to useless for anything but a toy project; it is simply way too unreliable.
- By developing your own solutions, you can engineer specific components that would be provided by LangChain to better suit your use case. For example, by fine-tuning to your use case you can have better results with converation history, context and summarization better by prompt engineering. If you look at prompts within langchain they are pretty basic.
- LangChain is designed around the idea that an entire chat logic resides within a single "REPL loop." In my use case, I had a single-page web app frontend, a standard web "RESTful" backend, and a separate chat service. Different parts of the information are stored and managed by these components. Using LangChain would have forced me to consolidate all logic into the chat service, which doesn't align with the overall architecture of my system beyond just the chat functionality.
Please note that I'm not a LangChain expert, so my assessment might not be entirely accurate about its capabilities. However, based on my evaluation, LangChain introduced too many constraints in comparison to what it provided.