LangChain Glossary

Chain of Thought Prompting

A prompting technique used to encourage the model to generate a series of intermediate reasoning steps. A less formal way to induce this behavior is to include “Let’s think step-by-step” in the prompt.

Action Plan Generation

A prompt usage that uses a language model to generate actions to take. The results of these actions can then be fed back into the language model to generate a subsequent action.

Resources:

WebGPT Paper

SayCan Paper

ReAct Prompting

LangChain Example

Self-ask

Explicitly have question text generated and use an external search engine

A prompting method that builds on top of chain-of-thought prompting. In this method, the model explicitly asks itself follow-up questions, which are then answered by an external search engine.

Resources:

LangChain Example

Prompt Chaining

Combining multiple LLM calls together, with the output of one-step being the input to the next.

Resources:

PromptChainer Paper

Language Model Cascades

ICE Primer Book

Socratic Models

Memetic Proxy

Make them behave in a specific context by having them play a role.

Encouraging the LLM to respond in a certain way framing the discussion in a context that the model knows of and that will result in that type of response. For example, as a conversation between a student and a teacher.

Resources:

Paper

Self Consistency

A decoding strategy that samples a diverse set of reasoning paths and then selects the most consistent answer. Is most effective when combined with Chain-of-thought prompting.

Resources:

Paper

Inception

Also called “First Person Instruction”. Encouraging the model to think a certain way by including the start of the model’s response in the prompt.

Resources:

Example

MemPrompt

MemPrompt maintains a memory of errors and user feedback, and uses them to prevent repetition of mistakes.

Resources:

Paper

---