mirror of
https://github.com/outbackdingo/optimclaw.git
synced 2026-08-26 15:40:18 +00:00
fix: cost pricing, fire_manual workspace, heartbeat concurrency cap
Round 3 review fixes: - Cost tracking passes None for cost_per_token when model override is active, letting CostGuard look up pricing by model name instead of using the default provider's rates (serrrfirat). - fire_manual() now uses per-user workspace, matching spawn_fire() pattern (serrrfirat). - Removed MULTI_TENANT env var — multi-tenant mode is auto-detected solely from GATEWAY_USER_TOKENS presence (serrrfirat + Copilot). - Multi-user heartbeat capped at 8 concurrent tasks to avoid flooding the LLM provider (serrrfirat + Copilot). - Fixed inject_model_override doc comment accuracy (Copilot). - Added comment explaining multi-tenant notification routing priority (Copilot). Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
This commit is contained in:
@@ -544,6 +544,8 @@ impl Agent {
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// In multi-tenant mode, extract the owning user_id from
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// the response metadata so notifications reach the
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// correct user rather than the agent's owner.
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// This intentionally overrides the configured notify_target
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// because each user's heartbeat should notify that user.
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let effective_user = if is_multi_tenant {
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response
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.metadata
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+12
-6
@@ -397,11 +397,17 @@ impl<'a> LoopDelegate for ChatDelegate<'a> {
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};
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// Record cost and track token usage (global + per-user).
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// Use the override model name if set so cost attribution is accurate.
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let model_name = reason_ctx
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.model_override
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.clone()
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.unwrap_or_else(|| self.agent.llm().active_model_name());
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// When a model override is active, use the override name for attribution
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// and let CostGuard look up pricing via costs::model_cost() instead of
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// using the default provider's cost_per_token (which reflects the wrong model).
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let (model_name, cost_per_token) = if let Some(ref ovr) = reason_ctx.model_override {
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(ovr.clone(), None)
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} else {
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(
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self.agent.llm().active_model_name(),
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Some(self.agent.llm().cost_per_token()),
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)
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};
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let read_discount = self.agent.llm().cache_read_discount();
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let write_multiplier = self.agent.llm().cache_write_multiplier();
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let call_cost = self
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@@ -416,7 +422,7 @@ impl<'a> LoopDelegate for ChatDelegate<'a> {
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output.usage.cache_creation_input_tokens,
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read_discount,
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write_multiplier,
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Some(self.agent.llm().cost_per_token()),
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cost_per_token,
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)
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.await;
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tracing::debug!(
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+55
-38
@@ -574,8 +574,9 @@ pub fn spawn_multi_user_heartbeat(
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}
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};
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// Run all user heartbeats concurrently so one slow LLM call
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// doesn't block others.
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// Run user heartbeats concurrently so one slow LLM call doesn't
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// block others. Cap concurrency to avoid flooding the LLM provider.
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const MAX_CONCURRENT_HEARTBEATS: usize = 8;
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let mut join_set = tokio::task::JoinSet::new();
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for user_id in &user_ids {
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@@ -604,6 +605,13 @@ pub fn spawn_multi_user_heartbeat(
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}
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});
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// Drain completed tasks to stay within the concurrency cap.
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while join_set.len() >= MAX_CONCURRENT_HEARTBEATS {
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if let Some(join_result) = join_set.join_next().await {
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collect_heartbeat_result(join_result, &mut user_failures, &config);
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}
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}
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let uid = user_id.clone();
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let cfg = config.clone();
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let hyg = hygiene_config.clone();
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@@ -626,48 +634,57 @@ pub fn spawn_multi_user_heartbeat(
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});
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}
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// Collect results and update failure counts
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// Collect remaining results and update failure counts
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while let Some(join_result) = join_set.join_next().await {
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let (uid, result) = match join_result {
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Ok(pair) => pair,
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Err(e) => {
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tracing::error!("Multi-user heartbeat task panicked: {}", e);
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continue;
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}
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};
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match result {
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HeartbeatResult::Ok => {
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tracing::trace!(user_id = uid, "Multi-user heartbeat OK");
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user_failures.remove(&uid);
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}
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HeartbeatResult::NeedsAttention(_) => {
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tracing::info!(user_id = uid, "Multi-user heartbeat needs attention");
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user_failures.remove(&uid);
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}
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HeartbeatResult::Skipped => {}
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HeartbeatResult::Failed(err) => {
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let count = user_failures.entry(uid.clone()).or_insert(0);
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*count += 1;
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tracing::error!(
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user_id = uid,
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consecutive_failures = *count,
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"Multi-user heartbeat failed: {}",
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err
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);
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if *count >= config.max_failures {
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tracing::error!(
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user_id = uid,
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"Multi-user heartbeat disabled for user after {} consecutive failures",
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count
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);
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}
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}
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}
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collect_heartbeat_result(join_result, &mut user_failures, &config);
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}
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}
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})
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}
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/// Process a single JoinSet result from the multi-user heartbeat loop.
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fn collect_heartbeat_result(
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join_result: Result<(String, HeartbeatResult), tokio::task::JoinError>,
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user_failures: &mut std::collections::HashMap<String, u32>,
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config: &HeartbeatConfig,
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) {
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let (uid, result) = match join_result {
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Ok(pair) => pair,
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Err(e) => {
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tracing::error!("Multi-user heartbeat task panicked: {}", e);
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return;
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}
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};
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match result {
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HeartbeatResult::Ok => {
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tracing::trace!(user_id = uid, "Multi-user heartbeat OK");
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user_failures.remove(&uid);
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}
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HeartbeatResult::NeedsAttention(_) => {
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tracing::info!(user_id = uid, "Multi-user heartbeat needs attention");
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user_failures.remove(&uid);
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}
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HeartbeatResult::Skipped => {}
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HeartbeatResult::Failed(err) => {
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let count = user_failures.entry(uid.clone()).or_insert(0);
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*count += 1;
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tracing::error!(
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user_id = uid,
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consecutive_failures = *count,
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"Multi-user heartbeat failed: {}",
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err
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);
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if *count >= config.max_failures {
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tracing::error!(
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user_id = uid,
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"Multi-user heartbeat disabled for user after {} consecutive failures",
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count
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);
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}
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}
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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@@ -737,12 +737,19 @@ impl RoutineEngine {
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});
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}
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// Per-user workspace (same pattern as spawn_fire).
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let routine_workspace = if routine.user_id == self.workspace.user_id() {
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self.workspace.clone()
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} else {
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Arc::new(Workspace::new_with_db(&routine.user_id, self.store.clone()))
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};
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// Execute inline for manual triggers (caller wants to wait)
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let engine = EngineContext {
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config: self.config.clone(),
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store: self.store.clone(),
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llm: self.llm.clone(),
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workspace: self.workspace.clone(),
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workspace: routine_workspace,
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notify_tx: self.notify_tx.clone(),
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running_count: self.running_count.clone(),
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scheduler: self.scheduler.clone(),
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+3
-4
@@ -120,10 +120,9 @@ impl AgentConfig {
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"AGENT_MAX_TOKENS_PER_JOB",
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settings.agent.max_tokens_per_job,
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)?,
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multi_tenant: parse_bool_env(
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"MULTI_TENANT",
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optional_env("GATEWAY_USER_TOKENS")?.is_some(),
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)?,
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// Auto-detected from GATEWAY_USER_TOKENS presence. Not a separate
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// knob — multi-tenant mode is always implied by configuring user tokens.
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multi_tenant: optional_env("GATEWAY_USER_TOKENS")?.is_some(),
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})
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}
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}
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@@ -599,11 +599,12 @@ fn build_rig_request(
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/// Inject a per-request model override into the rig request's `additional_params`.
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///
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/// Rig-core bakes the model name at construction time. For OpenAI, Anthropic, and
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/// Ollama, the `model` field in the request body determines which model serves the
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/// request. Rig-core's `#[serde(flatten)]` on `additional_params` emits these fields
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/// AFTER the struct's own `model` field. Most API servers (Python, Go) use
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/// last-key-wins when deserializing duplicate JSON keys, so the override takes effect.
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/// Rig-core bakes the model name at construction time inside each provider's
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/// `CompletionModel` implementation. The actual HTTP request body includes a
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/// `model` field set by the provider. Rig-core's `#[serde(flatten)]` on
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/// `additional_params` emits these fields AFTER the provider's own fields.
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/// Most API servers (Python, Go) use last-key-wins when deserializing
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/// duplicate JSON keys, so the injected `model` value takes effect.
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fn inject_model_override(rig_req: &mut RigRequest, model_override: Option<&str>) {
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let Some(model) = model_override else {
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return;
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