I don't understand how the prompts work in llama_index – Langchain

The Problem:

The user is trying to query a local PDF file using Large Language Model (LLM) embedding with the llama_index library. However, when attempting to query the index, the user encounters a ValueError stating that the "prompt" argument is expected to be a string rather than an instance of the "llama_index.prompts.base.Prompt" class. The user has provided relevant code snippets to illustrate the issue and has asked the community for assistance in understanding how to correctly use prompts in the llama_index library.

The Solutions:

Solution 1: Fixed Service Context Setup

The code you provided has an outdated service context setup. The main issue is that you’re setting the llm_predictor parameter to the llm object. Instead, you should pass the llm object directly as a keyword argument.

Here’s the corrected service context setup:

service_context = ServiceContext.from_defaults(
    chunk_size=1024,
    llm=llm,  # This is updated
    prompt_helper=prompt_helper,
    embed_model=embed_model,
)

You can refer to the documentation for more details: https://gpt-index.readthedocs.io/en/stable/core_modules/model_modules/llms/usage_custom.html#example-changing-the-underlying-llm

Additionally, if you pass in an llm from langchain like this:

from llama_index.llms import LangChainLLM

llm = LangChainLLM(langchain_llm)

The service context will automatically detect this and wrap it with the LangChain wrapper. This is useful because other parts of llama-index, such as agents and chat engines, may expect an LLM object as input and won’t wrap it for you.

Video Explanation:

The following video, titled "”Ed", provides additional insights and in-depth exploration related to the topics discussed in this post.

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