add few shot example (#148)

docs/glossary.md

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-# Glossary
-
-This is a collection of terminology commonly used when developing LLM applications.
-It contains reference to external papers or sources where the concept was first introduced, 
-as well as to places in LangChain where the concept is used.
-
-### 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.
-
-Resources:
-- [Chain-of-Thought Paper](https://arxiv.org/pdf/2201.11903.pdf)
-- [Step-by-Step Paper](https://arxiv.org/abs/2112.00114)
-
-### 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](https://arxiv.org/pdf/2112.09332.pdf)
-- [SayCan Paper](https://say-can.github.io/assets/palm_saycan.pdf)
-
-### ReAct Prompting
-
-A prompting technique that combines Chain-of-Thought prompting with action plan generation. 
-This induces the to model to think about what action to take, then take it. 
-
-Resources:
-- [Paper](https://arxiv.org/pdf/2210.03629.pdf)
-- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/react.ipynb)
-
-### Self-ask
-
-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:
-- [Paper](https://ofir.io/self-ask.pdf)
-- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/self_ask_with_search.ipynb)
-
-### Prompt Chaining
-
-Combining multiple LLM calls together, with the output of one step being the input to the next. 
-
-Resources: 
-- [PromptChainer Paper](https://arxiv.org/pdf/2203.06566.pdf)
-- [Language Model Cascades](https://arxiv.org/abs/2207.10342)
-- [ICE Primer Book](https://primer.ought.org/)
-- [Socratic Models](https://socraticmodels.github.io/)
-
-### Memetic Proxy
-
-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](https://arxiv.org/pdf/2102.07350.pdf)
-
-### 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](https://arxiv.org/pdf/2203.11171.pdf)
-
-### 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](https://twitter.com/goodside/status/1583262455207460865?s=20&t=8Hz7XBnK1OF8siQrxxCIGQ)