66 lines
2.1 KiB
Rust
66 lines
2.1 KiB
Rust
use anyhow::anyhow;
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use tiktoken_rs::CoreBPE;
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use util::ResultExt;
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pub trait LanguageModel {
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fn name(&self) -> String;
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fn count_tokens(&self, content: &str) -> anyhow::Result<usize>;
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fn truncate(&self, content: &str, length: usize) -> anyhow::Result<String>;
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fn truncate_start(&self, content: &str, length: usize) -> anyhow::Result<String>;
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fn capacity(&self) -> anyhow::Result<usize>;
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}
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pub struct OpenAILanguageModel {
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name: String,
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bpe: Option<CoreBPE>,
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}
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impl OpenAILanguageModel {
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pub fn load(model_name: &str) -> Self {
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let bpe = tiktoken_rs::get_bpe_from_model(model_name).log_err();
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OpenAILanguageModel {
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name: model_name.to_string(),
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bpe,
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}
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}
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}
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impl LanguageModel for OpenAILanguageModel {
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fn name(&self) -> String {
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self.name.clone()
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}
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fn count_tokens(&self, content: &str) -> anyhow::Result<usize> {
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if let Some(bpe) = &self.bpe {
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anyhow::Ok(bpe.encode_with_special_tokens(content).len())
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} else {
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Err(anyhow!("bpe for open ai model was not retrieved"))
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}
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}
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fn truncate(&self, content: &str, length: usize) -> anyhow::Result<String> {
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if let Some(bpe) = &self.bpe {
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let tokens = bpe.encode_with_special_tokens(content);
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if tokens.len() > length {
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bpe.decode(tokens[..length].to_vec())
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} else {
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bpe.decode(tokens)
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}
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} else {
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Err(anyhow!("bpe for open ai model was not retrieved"))
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}
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}
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fn truncate_start(&self, content: &str, length: usize) -> anyhow::Result<String> {
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if let Some(bpe) = &self.bpe {
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let tokens = bpe.encode_with_special_tokens(content);
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if tokens.len() > length {
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bpe.decode(tokens[length..].to_vec())
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} else {
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bpe.decode(tokens)
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}
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} else {
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Err(anyhow!("bpe for open ai model was not retrieved"))
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}
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}
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fn capacity(&self) -> anyhow::Result<usize> {
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anyhow::Ok(tiktoken_rs::model::get_context_size(&self.name))
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}
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}
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