added openai language model tokenizer and LanguageModel trait

This commit is contained in:
KCaverly 2023-10-17 16:21:03 -04:00
parent ad92fe49c7
commit a874a09b7e
4 changed files with 102 additions and 44 deletions

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@ -1,3 +1,4 @@
pub mod completion;
pub mod embedding;
pub mod models;
pub mod templates;

49
crates/ai/src/models.rs Normal file
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@ -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))
}
}

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@ -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

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@ -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))
}
}
}