Conversation-Based Few-Shot Example Selector

[Kirushikesh]

Checked

• I searched existing ideas and did not find a similar one
• I added a very descriptive title
• I've clearly described the feature request and motivation for it

Feature request

Implement a new example selector capable of handling multi-turn conversations for few-shot learning. This selector should compare and rank entire conversations, rather than single utterances, to provide more contextually relevant examples for complex, multi-turn scenarios.

Motivation

The current few-shot example selection in LangChain is limited to single utterance <input, output> pairs. However, many real-world applications, such as customer service chatbots or multi-step task assistants, require understanding and generating responses in the context of entire conversations. This limitation can lead to suboptimal performance in scenarios where the context and flow of a conversation are crucial for generating appropriate responses.

Proposal (If applicable)

No response