Few-Shot Prompting

FewShotChatMessagePromptTemplate injects example conversations into a prompt for few-shot learning. Each example is a pair of human input and AI output, formatted as alternating Human and AI messages. An optional system prefix message can be prepended.

Basic Usage

Create the template with a list of FewShotExample values and a suffix PromptTemplate for the user's actual query:

use std::collections::HashMap;
use synaptic::prompts::{
    FewShotChatMessagePromptTemplate, FewShotExample, PromptTemplate,
};

let template = FewShotChatMessagePromptTemplate::new(
    vec![
        FewShotExample {
            input: "What is 2+2?".to_string(),
            output: "4".to_string(),
        },
        FewShotExample {
            input: "What is 3+3?".to_string(),
            output: "6".to_string(),
        },
    ],
    PromptTemplate::new("{{ question }}"),
);

let values = HashMap::from([
    ("question".to_string(), "What is 4+4?".to_string()),
]);
let messages = template.format(&values).unwrap();

// messages[0] => Human("What is 2+2?")  -- example 1 input
// messages[1] => AI("4")                 -- example 1 output
// messages[2] => Human("What is 3+3?")  -- example 2 input
// messages[3] => AI("6")                 -- example 2 output
// messages[4] => Human("What is 4+4?")  -- actual query (suffix)

Each FewShotExample has two fields:

• input -- the human message for this example
• output -- the AI response for this example

The suffix template is rendered with the user-provided variables and appended as the final human message.

Adding a System Prefix

Use with_prefix() to prepend a system message before the examples:

use std::collections::HashMap;
use synaptic::prompts::{
    FewShotChatMessagePromptTemplate, FewShotExample, PromptTemplate,
};

let template = FewShotChatMessagePromptTemplate::new(
    vec![FewShotExample {
        input: "hi".to_string(),
        output: "hello".to_string(),
    }],
    PromptTemplate::new("{{ input }}"),
)
.with_prefix(PromptTemplate::new("You are a polite assistant."));

let values = HashMap::from([("input".to_string(), "hey".to_string())]);
let messages = template.format(&values).unwrap();

// messages[0] => System("You are a polite assistant.")  -- prefix
// messages[1] => Human("hi")                            -- example input
// messages[2] => AI("hello")                            -- example output
// messages[3] => Human("hey")                           -- actual query

The prefix template supports {{ variable }} interpolation, so you can parameterize the system message too.

Using as a Runnable

FewShotChatMessagePromptTemplate implements Runnable<HashMap<String, String>, Vec<Message>>, so you can call invoke() or compose it in pipelines:

use std::collections::HashMap;
use synaptic::core::RunnableConfig;
use synaptic::prompts::{
    FewShotChatMessagePromptTemplate, FewShotExample, PromptTemplate,
};
use synaptic::runnables::Runnable;

let template = FewShotChatMessagePromptTemplate::new(
    vec![FewShotExample {
        input: "x".to_string(),
        output: "y".to_string(),
    }],
    PromptTemplate::new("{{ q }}"),
);

let config = RunnableConfig::default();
let values = HashMap::from([("q".to_string(), "z".to_string())]);
let messages = template.invoke(values, &config).await?;
// 3 messages: Human("x"), AI("y"), Human("z")

Note: The Runnable implementation for FewShotChatMessagePromptTemplate takes HashMap<String, String>, while ChatPromptTemplate takes HashMap<String, serde_json::Value>. This difference reflects their underlying template rendering: few-shot templates use PromptTemplate::render() which works with string values.