Chains in LLM Deployment

Rahul S
2 min readSep 6, 2024
Photo by Bryson Hammer on Unsplash

Go through this piece to get an introduction to Agents in LLM Apps:

To make these systems fully autonomous, we use LLM chains.

What Are LLM Chains?

LLM chains involve passing the output of one LLM as input to another. This setup allows us to break down complex tasks into simpler, manageable subtasks, each handled by a specialized LLM.

For example, in a content generation app, we might use one LLM to discover topics, another to generate content, and a third to review and improve that content.

Structure of LLM Chains

  1. Task Breakdown: We decompose the main task into subtasks. Each subtask is optimized for a specific LLM.
  2. Specialization: Different LLMs handle different stages. This improves performance as each LLM is specialized.
  3. Sequential Processing: Outputs from one LLM feed into the next. This sequence continues down the chain, with each LLM adding value.
  4. Feedback Mechanism: To enhance accuracy, we use…

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