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Do you have a recommendation of how to easily connect a language model to a python repl, apify, bash shell, and composable chaining structures if not langchain?
by yinser 3y ago
Do you have a recommendation of how to easily connect a language model to a python repl, apify, bash shell, and composable chaining structures if not langchain? I find those structures invaluable but am curious where else I could build these programs.
- ntonozzi 3y agoIt’s great for prototyping and seeing what is possible but for running in production you’ll likely need to write it yourself, and it will just take a few minutes.
- jmccarthy 3y agoCould be we're in a (short?) interregnum analogous to pre-Rails Ruby: there are lots of nascent frameworks, but the dominant one hasn't been born yet. FWIW - DIY is working well for me.
- kordlessagain 3y agoCheck out https://www.featurebase.com/blog/doctorgpt-harnessing-the-power-of-semantic-knowledge-graphs-for-unstructured-data https://www.featurebase.com/blog/doctorgpt-harnessing-the-po... and the DoctorGPT repo for doing some things with documents and LLMs, without a framework. I use simple templating and vectors to assemble prompts.
- ukuina 3y agoThe current trend for productionizing LLM-based applications is to write your own (really thin) wrappers around the actual LLM call. The majority of your code should be business logic independent of the LLM, anyway: information retrieval, user interface, response logging, and so on. In my experience with cloud-based and local models, LLM chaining compounds errors; I would urge you to look at few-shot, single-query interaction models for business applications using LLMs as a new unit of compute.