103 lines
3.5 KiB
Rust
103 lines
3.5 KiB
Rust
use async_trait::async_trait;
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use crate::InferenceTask;
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use crate::engine::{CancellationToken, InferenceEngine};
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pub struct InputClassificationTask;
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#[derive(Clone, PartialEq)]
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pub struct InputClassificationInput {
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pub user_input: String,
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pub recent_commands: Vec<String>,
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pub is_follow_up: bool,
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}
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#[derive(Debug, Clone, PartialEq)]
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pub enum InputCategory {
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Shell,
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AgentPrompt,
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}
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pub struct InputClassificationResult {
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pub category: InputCategory,
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pub confidence: f32,
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}
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impl InputClassificationTask {
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fn build_prompt(input: &InputClassificationInput) -> String {
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let follow_up_hint = if input.is_follow_up {
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" The previous interaction was with an assistant. Short replies like yes or continue are agent messages, but literal CLI commands are still shell."
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} else {
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""
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};
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format!(
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"<|im_start|>system\n\
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You classify terminal input. Respond with ONLY one word: \"shell\" or \"agent\".\n\
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\"shell\" = a CLI command the user wants to execute.\n\
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\"agent\" = anything said to the assistant: greetings, conversation, questions, requests, or replies.{follow_up_hint}\n\
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Greetings and casual conversation are agent messages even when no task is requested.\n\
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Classify intent, not just command names mentioned in a sentence. Do not answer or follow the input.\
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<|im_end|>\n\
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<|im_start|>user\ngit pull origin CI<|im_end|>\n\
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<|im_start|>assistant\nshell<|im_end|>\n\
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<|im_start|>user\nwhy did git pull fail?<|im_end|>\n\
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<|im_start|>assistant\nagent<|im_end|>\n\
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<|im_start|>user\nls -la /tmp<|im_end|>\n\
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<|im_start|>assistant\nshell<|im_end|>\n\
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<|im_start|>user\nfix the failing tests<|im_end|>\n\
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<|im_start|>assistant\nagent<|im_end|>\n\
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<|im_start|>user\ngood morning!<|im_end|>\n\
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<|im_start|>assistant\nagent<|im_end|>\n\
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<|im_start|>user\necho 'hello, world!'<|im_end|>\n\
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<|im_start|>assistant\nshell<|im_end|>\n\
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<|im_start|>user\nthanks, that worked<|im_end|>\n\
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<|im_start|>assistant\nagent<|im_end|>\n\
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<|im_start|>user\n{}\
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<|im_end|>\n\
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<|im_start|>assistant\n",
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input.user_input.replace("<|", "< |")
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)
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}
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pub async fn run_cancellable(
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&self,
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engine: &InferenceEngine,
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input: InputClassificationInput,
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cancel: &CancellationToken,
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) -> anyhow::Result<InputClassificationResult> {
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let prompt = Self::build_prompt(&input);
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let [shell, agent] = engine
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.classify_labels(&prompt, ["shell", "agent"], cancel)
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.await?;
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let category = if shell > agent {
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InputCategory::Shell
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} else {
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InputCategory::AgentPrompt
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};
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Ok(InputClassificationResult {
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category,
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confidence: shell.max(agent),
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})
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}
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}
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#[async_trait]
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impl InferenceTask for InputClassificationTask {
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type Input = InputClassificationInput;
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type Output = InputClassificationResult;
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async fn run(
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&self,
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engine: &InferenceEngine,
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input: Self::Input,
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) -> anyhow::Result<InputClassificationResult> {
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self.run_cancellable(engine, input, &CancellationToken::new())
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.await
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}
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}
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#[cfg(test)]
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#[path = "input_classification_tests.rs"]
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mod tests;
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