>"Lesson 2: You don’t need langchain. You probably don’t even need anything else OpenAI has released in their API in the last year. Just chat API. That’s it.
Langchain is the perfect example of premature abstraction. We started out thinking we had to use it because the internet said so. Instead, millions of tokens later, and probably 3-4 very diverse LLM features in production, and our openai_service file still has only one, 40-line function in it:
The only API we use is chat. We always extract json. We don’t need JSON mode, or function calling, or assistants (though we do all that). Heck, we don’t even use system prompts (maybe we should…). When a gpt-4-turbo was released, we updated one string in the codebase.
This is the beauty of a powerful generalized model – less is more."
Langchain is the perfect example of premature abstraction. We started out thinking we had to use it because the internet said so. Instead, millions of tokens later, and probably 3-4 very diverse LLM features in production, and our openai_service file still has only one, 40-line function in it:
def extract_json(prompt, variable_length_input, number_retries)
The only API we use is chat. We always extract json. We don’t need JSON mode, or function calling, or assistants (though we do all that). Heck, we don’t even use system prompts (maybe we should…). When a gpt-4-turbo was released, we updated one string in the codebase.
This is the beauty of a powerful generalized model – less is more."
Well said!