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fix: persist model name to .env so dotted names survive restart (#426)

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* fix: persist model name to .env so dotted names survive restart (#400)

The setup wizard saved selected_model to the DB but not to .env.
Since Config::from_env_with_toml() runs before the DB connects, the
model name was lost on restart -- backends fell back to hardcoded
defaults, truncating names like "llama3.2" to "llama3".

- Add LlmBackend::model_env_var() as single source of truth for the
  backend-to-env-var mapping
- Write the model env var in write_bootstrap_env() using the new method
- Add selected_model fallback to all 6 backends (was missing from
  OpenAI, Anthropic, Ollama, and Tinfoil)

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* refactor: extract resolve_model() helper to reduce duplication

Address review feedback: the env → settings → default model resolution
pattern was repeated across all 6 backends.  Centralise it in a single
LlmConfig::resolve_model() helper.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

---------

Co-authored-by: Claude Opus 4.6 <[email protected]>
This commit is contained in:
Zaki Manian
2026-03-01 08:32:59 +00:00
committed by GitHub
co-authored by Claude Opus 4.6
parent 914f3cd075
commit f62937d482
2 changed files with 125 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/config/llm.rs
+111 -11
View File
@@ -60,6 +60,23 @@ impl std::fmt::Display for LlmBackend {
}
}
impl LlmBackend {
/// The environment variable that configures the model name for this backend.
///
/// Used by both `LlmConfig::resolve()` (reads the var) and the setup wizard
/// (writes the var to `.env`). Centralised here so the two stay in sync.
pub fn model_env_var(&self) -> &'static str {
match self {
Self::NearAi => "NEARAI_MODEL",
Self::OpenAi => "OPENAI_MODEL",
Self::Anthropic => "ANTHROPIC_MODEL",
Self::Ollama => "OLLAMA_MODEL",
Self::OpenAiCompatible => "LLM_MODEL",
Self::Tinfoil => "TINFOIL_MODEL",
}
}
}
/// Configuration for direct OpenAI API access.
#[derive(Debug, Clone)]
pub struct OpenAiDirectConfig {
@@ -178,6 +195,17 @@ pub struct NearAiConfig {
}
impl LlmConfig {
/// Resolve a model name from env var → settings.selected_model → hardcoded default.
fn resolve_model(
env_var: &str,
settings: &Settings,
default: &str,
) -> Result<String, ConfigError> {
Ok(optional_env(env_var)?
.or_else(|| settings.selected_model.clone())
.unwrap_or_else(|| default.to_string()))
}
pub(crate) fn resolve(settings: &Settings) -> Result<Self, ConfigError> {
// Determine backend: env var > settings > default (NearAi)
let backend: LlmBackend = if let Some(b) = optional_env("LLM_BACKEND")? {
@@ -205,9 +233,7 @@ impl LlmConfig {
let nearai_api_key = optional_env("NEARAI_API_KEY")?.map(SecretString::from);
let nearai = NearAiConfig {
model: optional_env("NEARAI_MODEL")?
.or_else(|| settings.selected_model.clone())
.unwrap_or_else(|| "zai-org/GLM-latest".to_string()),
model: Self::resolve_model("NEARAI_MODEL", settings, "zai-org/GLM-latest")?,
cheap_model: optional_env("NEARAI_CHEAP_MODEL")?,
base_url: optional_env("NEARAI_BASE_URL")?.unwrap_or_else(|| {
if nearai_api_key.is_some() {
@@ -248,7 +274,7 @@ impl LlmConfig {
key: "OPENAI_API_KEY".to_string(),
hint: "Set OPENAI_API_KEY when LLM_BACKEND=openai".to_string(),
})?;
let model = optional_env("OPENAI_MODEL")?.unwrap_or_else(|| "gpt-4o".to_string());
let model = Self::resolve_model("OPENAI_MODEL", settings, "gpt-4o")?;
let base_url = optional_env("OPENAI_BASE_URL")?;
Some(OpenAiDirectConfig {
api_key,
@@ -266,8 +292,8 @@ impl LlmConfig {
key: "ANTHROPIC_API_KEY".to_string(),
hint: "Set ANTHROPIC_API_KEY when LLM_BACKEND=anthropic".to_string(),
})?;
let model = optional_env("ANTHROPIC_MODEL")?
.unwrap_or_else(|| "claude-sonnet-4-20250514".to_string());
let model =
Self::resolve_model("ANTHROPIC_MODEL", settings, "claude-sonnet-4-20250514")?;
let base_url = optional_env("ANTHROPIC_BASE_URL")?;
Some(AnthropicDirectConfig {
api_key,
@@ -282,7 +308,7 @@ impl LlmConfig {
let base_url = optional_env("OLLAMA_BASE_URL")?
.or_else(|| settings.ollama_base_url.clone())
.unwrap_or_else(|| "http://localhost:11434".to_string());
let model = optional_env("OLLAMA_MODEL")?.unwrap_or_else(|| "llama3".to_string());
let model = Self::resolve_model("OLLAMA_MODEL", settings, "llama3")?;
Some(OllamaConfig { base_url, model })
} else {
None
@@ -296,9 +322,7 @@ impl LlmConfig {
hint: "Set LLM_BASE_URL when LLM_BACKEND=openai_compatible".to_string(),
})?;
let api_key = optional_env("LLM_API_KEY")?.map(SecretString::from);
let model = optional_env("LLM_MODEL")?
.or_else(|| settings.selected_model.clone())
.unwrap_or_else(|| "default".to_string());
let model = Self::resolve_model("LLM_MODEL", settings, "default")?;
let extra_headers = optional_env("LLM_EXTRA_HEADERS")?
.map(|val| parse_extra_headers(&val))
.transpose()?
@@ -320,7 +344,7 @@ impl LlmConfig {
key: "TINFOIL_API_KEY".to_string(),
hint: "Set TINFOIL_API_KEY when LLM_BACKEND=tinfoil".to_string(),
})?;
let model = optional_env("TINFOIL_MODEL")?.unwrap_or_else(|| "kimi-k2-5".to_string());
let model = Self::resolve_model("TINFOIL_MODEL", settings, "kimi-k2-5")?;
Some(TinfoilConfig { api_key, model })
} else {
None
@@ -506,4 +530,80 @@ mod tests {
]
);
}
/// Clear all ollama-related env vars.
fn clear_ollama_env() {
// SAFETY: Only called under ENV_MUTEX in tests.
unsafe {
std::env::remove_var("LLM_BACKEND");
std::env::remove_var("OLLAMA_BASE_URL");
std::env::remove_var("OLLAMA_MODEL");
}
}
#[test]
fn ollama_uses_selected_model_when_ollama_model_unset() {
let _guard = ENV_MUTEX.lock().expect("env mutex poisoned");
clear_ollama_env();
let settings = Settings {
llm_backend: Some("ollama".to_string()),
selected_model: Some("llama3.2".to_string()),
..Default::default()
};
let cfg = LlmConfig::resolve(&settings).expect("resolve should succeed");
let ollama = cfg.ollama.expect("ollama config should be present");
assert_eq!(ollama.model, "llama3.2");
}
#[test]
fn ollama_model_env_overrides_selected_model() {
let _guard = ENV_MUTEX.lock().expect("env mutex poisoned");
clear_ollama_env();
// SAFETY: Under ENV_MUTEX.
unsafe {
std::env::set_var("OLLAMA_MODEL", "mistral:latest");
}
let settings = Settings {
llm_backend: Some("ollama".to_string()),
selected_model: Some("llama3.2".to_string()),
..Default::default()
};
let cfg = LlmConfig::resolve(&settings).expect("resolve should succeed");
let ollama = cfg.ollama.expect("ollama config should be present");
assert_eq!(ollama.model, "mistral:latest");
// SAFETY: Under ENV_MUTEX.
unsafe {
std::env::remove_var("OLLAMA_MODEL");
}
}
#[test]
fn openai_compatible_preserves_dotted_model_name() {
let _guard = ENV_MUTEX.lock().expect("env mutex poisoned");
clear_openai_compatible_env();
let settings = Settings {
llm_backend: Some("openai_compatible".to_string()),
openai_compatible_base_url: Some("http://localhost:11434/v1".to_string()),
selected_model: Some("llama3.2".to_string()),
..Default::default()
};
let cfg = LlmConfig::resolve(&settings).expect("resolve should succeed");
let compat = cfg
.openai_compatible
.expect("openai-compatible config should be present");
assert_eq!(
compat.model, "llama3.2",
"model name with dot must not be truncated"
);
}
}
src/setup/wizard.rs
+14
View File
@@ -2040,6 +2040,20 @@ impl SetupWizard {
env_vars.push(("OLLAMA_BASE_URL", url.clone()));
}
// Model name: same chicken-and-egg — Config::from_env() resolves the
// model before the DB is connected, so we must persist it to .env.
// Write the backend-specific env var so the correct resolution path
// picks it up.
if let Some(ref model) = self.settings.selected_model {
let backend: crate::config::LlmBackend = self
.settings
.llm_backend
.as_deref()
.and_then(|s| s.parse().ok())
.unwrap_or_default();
env_vars.push((backend.model_env_var(), model.clone()));
}
// Preserve NEARAI_API_KEY if present (set by API key auth flow)
if let Ok(api_key) = std::env::var("NEARAI_API_KEY")
&& !api_key.is_empty()