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When using two prompts on one LLM query, the prompts are combined in a way that maintains the context and structure of the query. The LLM is designed to handle complex queries and understand the context provided by the prompts. The prompts are carefully crafted to ensure that the LLM can generate a meaningful response based on the given context.
In the case of LlamaIndex, the prompts are used to build the index, perform traversal during querying, and synthesize the final answer. The LlamaIndex uses a finite set of prompt types, and all index classes, along with their associated queries, utilize a subset of these prompts (
source (
https://gpt-index.readthedocs.io/en/latest/how_to/customization/custom_prompts.html)).
When using a custom agent with LlamaIndex, the agent prompt is combined with the LlamaIndex prompt to create a single, coherent query for the LLM. This allows the LLM to understand the context and generate a response that takes into account both the agent's requirements and the LlamaIndex tool's functionality.
In summary, the LLM is designed to handle complex queries and understand the context provided by multiple prompts. The prompts are combined in a way that maintains the context and structure of the query, allowing the LLM to generate meaningful responses.
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