mirror of
https://github.com/zed-industries/zed.git
synced 2024-12-28 21:43:45 +03:00
added openai language model tokenizer and LanguageModel trait
This commit is contained in:
parent
ad92fe49c7
commit
a874a09b7e
@ -1,3 +1,4 @@
|
||||
pub mod completion;
|
||||
pub mod embedding;
|
||||
pub mod models;
|
||||
pub mod templates;
|
||||
|
49
crates/ai/src/models.rs
Normal file
49
crates/ai/src/models.rs
Normal file
@ -0,0 +1,49 @@
|
||||
use anyhow::anyhow;
|
||||
use tiktoken_rs::CoreBPE;
|
||||
use util::ResultExt;
|
||||
|
||||
pub trait LanguageModel {
|
||||
fn name(&self) -> String;
|
||||
fn count_tokens(&self, content: &str) -> anyhow::Result<usize>;
|
||||
fn truncate(&self, content: &str, length: usize) -> anyhow::Result<String>;
|
||||
fn capacity(&self) -> anyhow::Result<usize>;
|
||||
}
|
||||
|
||||
struct OpenAILanguageModel {
|
||||
name: String,
|
||||
bpe: Option<CoreBPE>,
|
||||
}
|
||||
|
||||
impl OpenAILanguageModel {
|
||||
pub fn load(model_name: String) -> Self {
|
||||
let bpe = tiktoken_rs::get_bpe_from_model(&model_name).log_err();
|
||||
OpenAILanguageModel {
|
||||
name: model_name,
|
||||
bpe,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl LanguageModel for OpenAILanguageModel {
|
||||
fn name(&self) -> String {
|
||||
self.name.clone()
|
||||
}
|
||||
fn count_tokens(&self, content: &str) -> anyhow::Result<usize> {
|
||||
if let Some(bpe) = &self.bpe {
|
||||
anyhow::Ok(bpe.encode_with_special_tokens(content).len())
|
||||
} else {
|
||||
Err(anyhow!("bpe for open ai model was not retrieved"))
|
||||
}
|
||||
}
|
||||
fn truncate(&self, content: &str, length: usize) -> anyhow::Result<String> {
|
||||
if let Some(bpe) = &self.bpe {
|
||||
let tokens = bpe.encode_with_special_tokens(content);
|
||||
bpe.decode(tokens[..length].to_vec())
|
||||
} else {
|
||||
Err(anyhow!("bpe for open ai model was not retrieved"))
|
||||
}
|
||||
}
|
||||
fn capacity(&self) -> anyhow::Result<usize> {
|
||||
anyhow::Ok(tiktoken_rs::model::get_context_size(&self.name))
|
||||
}
|
||||
}
|
@ -1,17 +1,11 @@
|
||||
use std::fmt::Write;
|
||||
use std::{cmp::Reverse, sync::Arc};
|
||||
use std::cmp::Reverse;
|
||||
use std::sync::Arc;
|
||||
|
||||
use util::ResultExt;
|
||||
|
||||
use crate::models::LanguageModel;
|
||||
use crate::templates::repository_context::PromptCodeSnippet;
|
||||
|
||||
pub trait LanguageModel {
|
||||
fn name(&self) -> String;
|
||||
fn count_tokens(&self, content: &str) -> usize;
|
||||
fn truncate(&self, content: &str, length: usize) -> String;
|
||||
fn capacity(&self) -> usize;
|
||||
}
|
||||
|
||||
pub(crate) enum PromptFileType {
|
||||
Text,
|
||||
Code,
|
||||
@ -73,7 +67,7 @@ impl PromptChain {
|
||||
pub fn generate(&self, truncate: bool) -> anyhow::Result<(String, usize)> {
|
||||
// Argsort based on Prompt Priority
|
||||
let seperator = "\n";
|
||||
let seperator_tokens = self.args.model.count_tokens(seperator);
|
||||
let seperator_tokens = self.args.model.count_tokens(seperator)?;
|
||||
let mut sorted_indices = (0..self.templates.len()).collect::<Vec<_>>();
|
||||
sorted_indices.sort_by_key(|&i| Reverse(&self.templates[i].0));
|
||||
|
||||
@ -81,7 +75,7 @@ impl PromptChain {
|
||||
|
||||
// If Truncate
|
||||
let mut tokens_outstanding = if truncate {
|
||||
Some(self.args.model.capacity() - self.args.reserved_tokens)
|
||||
Some(self.args.model.capacity()? - self.args.reserved_tokens)
|
||||
} else {
|
||||
None
|
||||
};
|
||||
@ -111,7 +105,7 @@ impl PromptChain {
|
||||
}
|
||||
|
||||
let full_prompt = prompts.join(seperator);
|
||||
let total_token_count = self.args.model.count_tokens(&full_prompt);
|
||||
let total_token_count = self.args.model.count_tokens(&full_prompt)?;
|
||||
anyhow::Ok((prompts.join(seperator), total_token_count))
|
||||
}
|
||||
}
|
||||
@ -131,10 +125,10 @@ pub(crate) mod tests {
|
||||
) -> anyhow::Result<(String, usize)> {
|
||||
let mut content = "This is a test prompt template".to_string();
|
||||
|
||||
let mut token_count = args.model.count_tokens(&content);
|
||||
let mut token_count = args.model.count_tokens(&content)?;
|
||||
if let Some(max_token_length) = max_token_length {
|
||||
if token_count > max_token_length {
|
||||
content = args.model.truncate(&content, max_token_length);
|
||||
content = args.model.truncate(&content, max_token_length)?;
|
||||
token_count = max_token_length;
|
||||
}
|
||||
}
|
||||
@ -152,10 +146,10 @@ pub(crate) mod tests {
|
||||
) -> anyhow::Result<(String, usize)> {
|
||||
let mut content = "This is a low priority test prompt template".to_string();
|
||||
|
||||
let mut token_count = args.model.count_tokens(&content);
|
||||
let mut token_count = args.model.count_tokens(&content)?;
|
||||
if let Some(max_token_length) = max_token_length {
|
||||
if token_count > max_token_length {
|
||||
content = args.model.truncate(&content, max_token_length);
|
||||
content = args.model.truncate(&content, max_token_length)?;
|
||||
token_count = max_token_length;
|
||||
}
|
||||
}
|
||||
@ -169,26 +163,22 @@ pub(crate) mod tests {
|
||||
capacity: usize,
|
||||
}
|
||||
|
||||
impl DummyLanguageModel {
|
||||
fn set_capacity(&mut self, capacity: usize) {
|
||||
self.capacity = capacity
|
||||
}
|
||||
}
|
||||
|
||||
impl LanguageModel for DummyLanguageModel {
|
||||
fn name(&self) -> String {
|
||||
"dummy".to_string()
|
||||
}
|
||||
fn count_tokens(&self, content: &str) -> usize {
|
||||
content.chars().collect::<Vec<char>>().len()
|
||||
fn count_tokens(&self, content: &str) -> anyhow::Result<usize> {
|
||||
anyhow::Ok(content.chars().collect::<Vec<char>>().len())
|
||||
}
|
||||
fn truncate(&self, content: &str, length: usize) -> String {
|
||||
content.chars().collect::<Vec<char>>()[..length]
|
||||
.into_iter()
|
||||
.collect::<String>()
|
||||
fn truncate(&self, content: &str, length: usize) -> anyhow::Result<String> {
|
||||
anyhow::Ok(
|
||||
content.chars().collect::<Vec<char>>()[..length]
|
||||
.into_iter()
|
||||
.collect::<String>(),
|
||||
)
|
||||
}
|
||||
fn capacity(&self) -> usize {
|
||||
self.capacity
|
||||
fn capacity(&self) -> anyhow::Result<usize> {
|
||||
anyhow::Ok(self.capacity)
|
||||
}
|
||||
}
|
||||
|
||||
@ -215,7 +205,7 @@ pub(crate) mod tests {
|
||||
.to_string()
|
||||
);
|
||||
|
||||
assert_eq!(model.count_tokens(&prompt), token_count);
|
||||
assert_eq!(model.count_tokens(&prompt).unwrap(), token_count);
|
||||
|
||||
// Testing with Truncation Off
|
||||
// Should ignore capacity and return all prompts
|
||||
@ -242,7 +232,7 @@ pub(crate) mod tests {
|
||||
.to_string()
|
||||
);
|
||||
|
||||
assert_eq!(model.count_tokens(&prompt), token_count);
|
||||
assert_eq!(model.count_tokens(&prompt).unwrap(), token_count);
|
||||
|
||||
// Testing with Truncation Off
|
||||
// Should ignore capacity and return all prompts
|
||||
|
@ -4,31 +4,49 @@ use std::fmt::Write;
|
||||
struct EngineerPreamble {}
|
||||
|
||||
impl PromptTemplate for EngineerPreamble {
|
||||
fn generate(&self, args: &PromptArguments, max_token_length: Option<usize>) -> String {
|
||||
let mut prompt = String::new();
|
||||
fn generate(
|
||||
&self,
|
||||
args: &PromptArguments,
|
||||
max_token_length: Option<usize>,
|
||||
) -> anyhow::Result<(String, usize)> {
|
||||
let mut prompts = Vec::new();
|
||||
|
||||
match args.get_file_type() {
|
||||
PromptFileType::Code => {
|
||||
writeln!(
|
||||
prompt,
|
||||
prompts.push(format!(
|
||||
"You are an expert {} engineer.",
|
||||
args.language_name.clone().unwrap_or("".to_string())
|
||||
)
|
||||
.unwrap();
|
||||
));
|
||||
}
|
||||
PromptFileType::Text => {
|
||||
writeln!(prompt, "You are an expert engineer.").unwrap();
|
||||
prompts.push("You are an expert engineer.".to_string());
|
||||
}
|
||||
}
|
||||
|
||||
if let Some(project_name) = args.project_name.clone() {
|
||||
writeln!(
|
||||
prompt,
|
||||
prompts.push(format!(
|
||||
"You are currently working inside the '{project_name}' in Zed the code editor."
|
||||
)
|
||||
.unwrap();
|
||||
));
|
||||
}
|
||||
|
||||
prompt
|
||||
if let Some(mut remaining_tokens) = max_token_length {
|
||||
let mut prompt = String::new();
|
||||
let mut total_count = 0;
|
||||
for prompt_piece in prompts {
|
||||
let prompt_token_count =
|
||||
args.model.count_tokens(&prompt_piece)? + args.model.count_tokens("\n")?;
|
||||
if remaining_tokens > prompt_token_count {
|
||||
writeln!(prompt, "{prompt_piece}").unwrap();
|
||||
remaining_tokens -= prompt_token_count;
|
||||
total_count += prompt_token_count;
|
||||
}
|
||||
}
|
||||
|
||||
anyhow::Ok((prompt, total_count))
|
||||
} else {
|
||||
let prompt = prompts.join("\n");
|
||||
let token_count = args.model.count_tokens(&prompt)?;
|
||||
anyhow::Ok((prompt, token_count))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user