Files
tkmind_go/crates/goose/src/model.rs
T
2026-01-05 18:43:20 -08:00

392 lines
12 KiB
Rust

use once_cell::sync::Lazy;
use serde::{Deserialize, Serialize};
use thiserror::Error;
use utoipa::ToSchema;
const DEFAULT_CONTEXT_LIMIT: usize = 128_000;
#[derive(Error, Debug)]
pub enum ConfigError {
#[error("Environment variable '{0}' not found")]
EnvVarMissing(String),
#[error("Invalid value for '{0}': '{1}' - {2}")]
InvalidValue(String, String, String),
#[error("Value for '{0}' is out of valid range: {1}")]
InvalidRange(String, String),
}
static MODEL_SPECIFIC_LIMITS: Lazy<Vec<(&'static str, usize)>> = Lazy::new(|| {
vec![
// openai
("gpt-5.2-codex", 400_000), // auto-compacting context
("gpt-5.2", 400_000), // auto-compacting context
("gpt-5.1-codex-max", 256_000),
("gpt-5.1-codex-mini", 256_000),
("gpt-4-turbo", 128_000),
("gpt-4.1", 1_000_000),
("gpt-4-1", 1_000_000),
("gpt-4o", 128_000),
("o4-mini", 200_000),
("o3-mini", 200_000),
("o3", 200_000),
// anthropic - all 200k
("claude", 200_000),
// google
("gemini-1.5-flash", 1_000_000),
("gemini-1", 128_000),
("gemini-2", 1_000_000),
("gemma-3-27b", 128_000),
("gemma-3-12b", 128_000),
("gemma-3-4b", 128_000),
("gemma-3-1b", 32_000),
("gemma3-27b", 128_000),
("gemma3-12b", 128_000),
("gemma3-4b", 128_000),
("gemma3-1b", 32_000),
("gemma-2-27b", 8_192),
("gemma-2-9b", 8_192),
("gemma-2-2b", 8_192),
("gemma2-", 8_192),
("gemma-7b", 8_192),
("gemma-2b", 8_192),
("gemma1", 8_192),
("gemma", 8_192),
// facebook
("llama-2-1b", 32_000),
("llama", 128_000),
// qwen
("qwen3-coder", 262_144),
("qwen2-7b", 128_000),
("qwen2-14b", 128_000),
("qwen2-32b", 131_072),
("qwen2-70b", 262_144),
("qwen2", 128_000),
("qwen3-32b", 131_072),
// xai
("grok-4", 256_000),
("grok-code-fast-1", 256_000),
("grok", 131_072),
// other
("kimi-k2", 131_072),
]
});
#[derive(Debug, Clone, Serialize, Deserialize, ToSchema)]
pub struct ModelConfig {
pub model_name: String,
pub context_limit: Option<usize>,
pub temperature: Option<f32>,
pub max_tokens: Option<i32>,
pub toolshim: bool,
pub toolshim_model: Option<String>,
pub fast_model: Option<String>,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ModelLimitConfig {
pub pattern: String,
pub context_limit: usize,
}
impl ModelConfig {
pub fn new(model_name: &str) -> Result<Self, ConfigError> {
Self::new_with_context_env(model_name.to_string(), None)
}
pub fn new_with_context_env(
model_name: String,
context_env_var: Option<&str>,
) -> Result<Self, ConfigError> {
let context_limit = Self::parse_context_limit(&model_name, None, context_env_var)?;
let temperature = Self::parse_temperature()?;
let max_tokens = Self::parse_max_tokens()?;
let toolshim = Self::parse_toolshim()?;
let toolshim_model = Self::parse_toolshim_model()?;
Ok(Self {
model_name,
context_limit,
temperature,
max_tokens,
toolshim,
toolshim_model,
fast_model: None,
})
}
fn parse_context_limit(
model_name: &str,
fast_model: Option<&str>,
custom_env_var: Option<&str>,
) -> Result<Option<usize>, ConfigError> {
// First check if there's an explicit environment variable override
if let Some(env_var) = custom_env_var {
if let Ok(val) = std::env::var(env_var) {
return Self::validate_context_limit(&val, env_var).map(Some);
}
}
if let Ok(val) = std::env::var("GOOSE_CONTEXT_LIMIT") {
return Self::validate_context_limit(&val, "GOOSE_CONTEXT_LIMIT").map(Some);
}
// Get the model's limit
let model_limit = Self::get_model_specific_limit(model_name);
// If there's a fast_model, get its limit and use the minimum
if let Some(fast_model_name) = fast_model {
let fast_model_limit = Self::get_model_specific_limit(fast_model_name);
// Return the minimum of both limits (if both exist)
match (model_limit, fast_model_limit) {
(Some(m), Some(f)) => Ok(Some(m.min(f))),
(Some(m), None) => Ok(Some(m)),
(None, Some(f)) => Ok(Some(f)),
(None, None) => Ok(None),
}
} else {
Ok(model_limit)
}
}
fn validate_context_limit(val: &str, env_var: &str) -> Result<usize, ConfigError> {
let limit = val.parse::<usize>().map_err(|_| {
ConfigError::InvalidValue(
env_var.to_string(),
val.to_string(),
"must be a positive integer".to_string(),
)
})?;
if limit < 4 * 1024 {
return Err(ConfigError::InvalidRange(
env_var.to_string(),
"must be greater than 4K".to_string(),
));
}
Ok(limit)
}
fn parse_temperature() -> Result<Option<f32>, ConfigError> {
if let Ok(val) = std::env::var("GOOSE_TEMPERATURE") {
let temp = val.parse::<f32>().map_err(|_| {
ConfigError::InvalidValue(
"GOOSE_TEMPERATURE".to_string(),
val.clone(),
"must be a valid number".to_string(),
)
})?;
if temp < 0.0 {
return Err(ConfigError::InvalidRange(
"GOOSE_TEMPERATURE".to_string(),
val,
));
}
Ok(Some(temp))
} else {
Ok(None)
}
}
fn parse_max_tokens() -> Result<Option<i32>, ConfigError> {
match crate::config::Config::global().get_param::<i32>("GOOSE_MAX_TOKENS") {
Ok(tokens) => {
if tokens <= 0 {
return Err(ConfigError::InvalidRange(
"goose_max_tokens".to_string(),
"must be greater than 0".to_string(),
));
}
Ok(Some(tokens))
}
Err(crate::config::ConfigError::NotFound(_)) => Ok(None),
Err(e) => Err(ConfigError::InvalidValue(
"goose_max_tokens".to_string(),
String::new(),
e.to_string(),
)),
}
}
fn parse_toolshim() -> Result<bool, ConfigError> {
if let Ok(val) = std::env::var("GOOSE_TOOLSHIM") {
match val.to_lowercase().as_str() {
"1" | "true" | "yes" | "on" => Ok(true),
"0" | "false" | "no" | "off" => Ok(false),
_ => Err(ConfigError::InvalidValue(
"GOOSE_TOOLSHIM".to_string(),
val,
"must be one of: 1, true, yes, on, 0, false, no, off".to_string(),
)),
}
} else {
Ok(false)
}
}
fn parse_toolshim_model() -> Result<Option<String>, ConfigError> {
match std::env::var("GOOSE_TOOLSHIM_OLLAMA_MODEL") {
Ok(val) if val.trim().is_empty() => Err(ConfigError::InvalidValue(
"GOOSE_TOOLSHIM_OLLAMA_MODEL".to_string(),
val,
"cannot be empty if set".to_string(),
)),
Ok(val) => Ok(Some(val)),
Err(_) => Ok(None),
}
}
fn get_model_specific_limit(model_name: &str) -> Option<usize> {
MODEL_SPECIFIC_LIMITS
.iter()
.find(|(pattern, _)| model_name.contains(pattern))
.map(|(_, limit)| *limit)
}
pub fn get_all_model_limits() -> Vec<ModelLimitConfig> {
MODEL_SPECIFIC_LIMITS
.iter()
.map(|(pattern, context_limit)| ModelLimitConfig {
pattern: pattern.to_string(),
context_limit: *context_limit,
})
.collect()
}
pub fn with_context_limit(mut self, limit: Option<usize>) -> Self {
if limit.is_some() {
self.context_limit = limit;
}
self
}
pub fn with_temperature(mut self, temp: Option<f32>) -> Self {
self.temperature = temp;
self
}
pub fn with_max_tokens(mut self, tokens: Option<i32>) -> Self {
self.max_tokens = tokens;
self
}
pub fn with_toolshim(mut self, toolshim: bool) -> Self {
self.toolshim = toolshim;
self
}
pub fn with_toolshim_model(mut self, model: Option<String>) -> Self {
self.toolshim_model = model;
self
}
pub fn with_fast(mut self, fast_model: String) -> Self {
self.fast_model = Some(fast_model);
self
}
pub fn use_fast_model(&self) -> Self {
if let Some(fast_model) = &self.fast_model {
let mut config = self.clone();
config.model_name = fast_model.clone();
config
} else {
self.clone()
}
}
pub fn context_limit(&self) -> usize {
// If we have an explicit context limit set, use it
if let Some(limit) = self.context_limit {
return limit;
}
// Otherwise, get the model's default limit
let main_limit =
Self::get_model_specific_limit(&self.model_name).unwrap_or(DEFAULT_CONTEXT_LIMIT);
// If we have a fast_model, also check its limit and use the minimum
if let Some(fast_model) = &self.fast_model {
let fast_limit =
Self::get_model_specific_limit(fast_model).unwrap_or(DEFAULT_CONTEXT_LIMIT);
main_limit.min(fast_limit)
} else {
main_limit
}
}
pub fn new_or_fail(model_name: &str) -> ModelConfig {
ModelConfig::new(model_name)
.unwrap_or_else(|_| panic!("Failed to create model config for {}", model_name))
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_parse_max_tokens_valid() {
let _guard = env_lock::lock_env([("GOOSE_MAX_TOKENS", Some("4096"))]);
let result = ModelConfig::parse_max_tokens().unwrap();
assert_eq!(result, Some(4096));
}
#[test]
fn test_parse_max_tokens_not_set() {
let _guard = env_lock::lock_env([("GOOSE_MAX_TOKENS", None::<&str>)]);
let result = ModelConfig::parse_max_tokens().unwrap();
assert_eq!(result, None);
}
#[test]
fn test_parse_max_tokens_invalid_string() {
let _guard = env_lock::lock_env([("GOOSE_MAX_TOKENS", Some("not_a_number"))]);
let result = ModelConfig::parse_max_tokens();
assert!(result.is_err());
assert!(matches!(result.unwrap_err(), ConfigError::InvalidValue(..)));
}
#[test]
fn test_parse_max_tokens_zero() {
let _guard = env_lock::lock_env([("GOOSE_MAX_TOKENS", Some("0"))]);
let result = ModelConfig::parse_max_tokens();
assert!(result.is_err());
assert!(matches!(result.unwrap_err(), ConfigError::InvalidRange(..)));
}
#[test]
fn test_parse_max_tokens_negative() {
let _guard = env_lock::lock_env([("GOOSE_MAX_TOKENS", Some("-100"))]);
let result = ModelConfig::parse_max_tokens();
assert!(result.is_err());
assert!(matches!(result.unwrap_err(), ConfigError::InvalidRange(..)));
}
#[test]
fn test_model_config_with_max_tokens_env() {
let _guard = env_lock::lock_env([
("GOOSE_MAX_TOKENS", Some("8192")),
("GOOSE_TEMPERATURE", None::<&str>),
("GOOSE_CONTEXT_LIMIT", None::<&str>),
("GOOSE_TOOLSHIM", None::<&str>),
("GOOSE_TOOLSHIM_OLLAMA_MODEL", None::<&str>),
]);
let config = ModelConfig::new("test-model").unwrap();
assert_eq!(config.max_tokens, Some(8192));
}
#[test]
fn test_model_config_without_max_tokens_env() {
let _guard = env_lock::lock_env([
("GOOSE_MAX_TOKENS", None::<&str>),
("GOOSE_TEMPERATURE", None::<&str>),
("GOOSE_CONTEXT_LIMIT", None::<&str>),
("GOOSE_TOOLSHIM", None::<&str>),
("GOOSE_TOOLSHIM_OLLAMA_MODEL", None::<&str>),
]);
let config = ModelConfig::new("test-model").unwrap();
assert_eq!(config.max_tokens, None);
}
}