Track cache_read_tokens and cache_write_tokens end-to-end: parse from provider responses (OpenAI, DeepSeek, Grok, Gemini), persist to SQLite, apply cache-aware pricing from the model registry, and surface in API responses and the dashboard. - Add cache fields to ProviderResponse, StreamUsage, RequestLog structs - Parse cached_tokens (OpenAI/Grok), prompt_cache_hit/miss (DeepSeek), cachedContentTokenCount (Gemini) from provider responses - Send stream_options.include_usage for streaming; capture real usage from final SSE chunk in AggregatingStream - ALTER TABLE migration for cache_read_tokens/cache_write_tokens columns - Cache-aware cost formula using registry cache_read/cache_write rates - Update Provider trait calculate_cost signature across all providers - Add cache_read_tokens/cache_write_tokens to Usage API response - Dashboard: cache hit rate card, cache columns in pricing and usage tables, cache token aggregation in SQL queries - Remove API debug panel and verbose console logging from api.js - Bump static asset cache-bust to v5
335 lines
12 KiB
Rust
335 lines
12 KiB
Rust
use crate::client::ClientManager;
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use crate::errors::AppError;
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use crate::logging::{RequestLog, RequestLogger};
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use crate::models::ToolCall;
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use crate::providers::{Provider, ProviderStreamChunk, StreamUsage};
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use crate::state::ModelConfigCache;
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use crate::utils::tokens::estimate_completion_tokens;
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use futures::stream::Stream;
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use std::pin::Pin;
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use std::sync::Arc;
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use std::task::{Context, Poll};
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/// Configuration for creating an AggregatingStream.
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pub struct StreamConfig {
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pub client_id: String,
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pub provider: Arc<dyn Provider>,
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pub model: String,
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pub prompt_tokens: u32,
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pub has_images: bool,
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pub logger: Arc<RequestLogger>,
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pub client_manager: Arc<ClientManager>,
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pub model_registry: Arc<crate::models::registry::ModelRegistry>,
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pub model_config_cache: ModelConfigCache,
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}
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pub struct AggregatingStream<S> {
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inner: S,
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client_id: String,
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provider: Arc<dyn Provider>,
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model: String,
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prompt_tokens: u32,
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has_images: bool,
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accumulated_content: String,
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accumulated_reasoning: String,
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accumulated_tool_calls: Vec<ToolCall>,
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/// Real usage data from the provider's final stream chunk (when available).
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real_usage: Option<StreamUsage>,
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logger: Arc<RequestLogger>,
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client_manager: Arc<ClientManager>,
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model_registry: Arc<crate::models::registry::ModelRegistry>,
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model_config_cache: ModelConfigCache,
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start_time: std::time::Instant,
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has_logged: bool,
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}
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impl<S> AggregatingStream<S>
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where
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S: Stream<Item = Result<ProviderStreamChunk, AppError>> + Unpin,
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{
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pub fn new(inner: S, config: StreamConfig) -> Self {
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Self {
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inner,
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client_id: config.client_id,
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provider: config.provider,
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model: config.model,
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prompt_tokens: config.prompt_tokens,
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has_images: config.has_images,
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accumulated_content: String::new(),
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accumulated_reasoning: String::new(),
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accumulated_tool_calls: Vec::new(),
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real_usage: None,
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logger: config.logger,
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client_manager: config.client_manager,
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model_registry: config.model_registry,
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model_config_cache: config.model_config_cache,
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start_time: std::time::Instant::now(),
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has_logged: false,
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}
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}
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fn finalize(&mut self) {
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if self.has_logged {
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return;
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}
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self.has_logged = true;
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let duration = self.start_time.elapsed();
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let client_id = self.client_id.clone();
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let provider_name = self.provider.name().to_string();
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let model = self.model.clone();
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let logger = self.logger.clone();
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let client_manager = self.client_manager.clone();
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let provider = self.provider.clone();
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let estimated_prompt_tokens = self.prompt_tokens;
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let has_images = self.has_images;
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let registry = self.model_registry.clone();
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let config_cache = self.model_config_cache.clone();
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let real_usage = self.real_usage.take();
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// Estimate completion tokens (including reasoning if present)
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let estimated_content_tokens = estimate_completion_tokens(&self.accumulated_content, &model);
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let estimated_reasoning_tokens = if !self.accumulated_reasoning.is_empty() {
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estimate_completion_tokens(&self.accumulated_reasoning, &model)
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} else {
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0
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};
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let estimated_completion = estimated_content_tokens + estimated_reasoning_tokens;
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// Spawn a background task to log the completion
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tokio::spawn(async move {
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// Use real usage from the provider when available, otherwise fall back to estimates
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let (prompt_tokens, completion_tokens, total_tokens, cache_read_tokens, cache_write_tokens) =
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if let Some(usage) = &real_usage {
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(
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usage.prompt_tokens,
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usage.completion_tokens,
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usage.total_tokens,
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usage.cache_read_tokens,
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usage.cache_write_tokens,
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)
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} else {
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(
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estimated_prompt_tokens,
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estimated_completion,
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estimated_prompt_tokens + estimated_completion,
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0u32,
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0u32,
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)
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};
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// Check in-memory cache for cost overrides (no SQLite hit)
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let cost = if let Some(cached) = config_cache.get(&model).await {
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if let (Some(p), Some(c)) = (cached.prompt_cost_per_m, cached.completion_cost_per_m) {
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// Cost override doesn't have cache-aware pricing, use simple formula
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(prompt_tokens as f64 * p / 1_000_000.0) + (completion_tokens as f64 * c / 1_000_000.0)
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} else {
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provider.calculate_cost(
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&model,
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prompt_tokens,
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completion_tokens,
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cache_read_tokens,
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cache_write_tokens,
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®istry,
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)
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}
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} else {
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provider.calculate_cost(
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&model,
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prompt_tokens,
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completion_tokens,
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cache_read_tokens,
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cache_write_tokens,
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®istry,
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)
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};
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// Log to database
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logger.log_request(RequestLog {
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timestamp: chrono::Utc::now(),
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client_id: client_id.clone(),
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provider: provider_name,
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model,
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prompt_tokens,
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completion_tokens,
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total_tokens,
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cache_read_tokens,
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cache_write_tokens,
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cost,
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has_images,
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status: "success".to_string(),
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error_message: None,
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duration_ms: duration.as_millis() as u64,
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});
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// Update client usage
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let _ = client_manager
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.update_client_usage(&client_id, total_tokens as i64, cost)
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.await;
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});
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}
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}
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impl<S> Stream for AggregatingStream<S>
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where
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S: Stream<Item = Result<ProviderStreamChunk, AppError>> + Unpin,
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{
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type Item = Result<ProviderStreamChunk, AppError>;
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fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>> {
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let result = Pin::new(&mut self.inner).poll_next(cx);
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match &result {
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Poll::Ready(Some(Ok(chunk))) => {
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self.accumulated_content.push_str(&chunk.content);
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if let Some(reasoning) = &chunk.reasoning_content {
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self.accumulated_reasoning.push_str(reasoning);
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}
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// Capture real usage from the provider when present (typically on the final chunk)
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if let Some(usage) = &chunk.usage {
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self.real_usage = Some(usage.clone());
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}
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// Accumulate tool call deltas into complete tool calls
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if let Some(deltas) = &chunk.tool_calls {
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for delta in deltas {
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let idx = delta.index as usize;
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// Grow the accumulated_tool_calls vec if needed
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while self.accumulated_tool_calls.len() <= idx {
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self.accumulated_tool_calls.push(ToolCall {
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id: String::new(),
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call_type: "function".to_string(),
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function: crate::models::FunctionCall {
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name: String::new(),
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arguments: String::new(),
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},
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});
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}
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let tc = &mut self.accumulated_tool_calls[idx];
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if let Some(id) = &delta.id {
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tc.id.clone_from(id);
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}
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if let Some(ct) = &delta.call_type {
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tc.call_type.clone_from(ct);
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}
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if let Some(f) = &delta.function {
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if let Some(name) = &f.name {
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tc.function.name.push_str(name);
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}
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if let Some(args) = &f.arguments {
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tc.function.arguments.push_str(args);
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}
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}
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}
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}
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}
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Poll::Ready(Some(Err(_))) => {
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// If there's an error, we might still want to log what we got so far?
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// For now, just finalize if we have content
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if !self.accumulated_content.is_empty() {
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self.finalize();
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}
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}
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Poll::Ready(None) => {
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self.finalize();
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}
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Poll::Pending => {}
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}
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result
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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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use anyhow::Result;
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use futures::stream::{self, StreamExt};
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// Simple mock provider for testing
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struct MockProvider;
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#[async_trait::async_trait]
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impl Provider for MockProvider {
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fn name(&self) -> &str {
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"mock"
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}
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fn supports_model(&self, _model: &str) -> bool {
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true
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}
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fn supports_multimodal(&self) -> bool {
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false
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}
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async fn chat_completion(
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&self,
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_req: crate::models::UnifiedRequest,
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) -> Result<crate::providers::ProviderResponse, AppError> {
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unimplemented!()
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}
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async fn chat_completion_stream(
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&self,
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_req: crate::models::UnifiedRequest,
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) -> Result<futures::stream::BoxStream<'static, Result<ProviderStreamChunk, AppError>>, AppError> {
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unimplemented!()
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}
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fn estimate_tokens(&self, _req: &crate::models::UnifiedRequest) -> Result<u32> {
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Ok(10)
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}
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fn calculate_cost(&self, _model: &str, _p: u32, _c: u32, _cr: u32, _cw: u32, _r: &crate::models::registry::ModelRegistry) -> f64 {
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0.05
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}
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}
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#[tokio::test]
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async fn test_aggregating_stream() {
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let chunks = vec![
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Ok(ProviderStreamChunk {
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content: "Hello".to_string(),
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reasoning_content: None,
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finish_reason: None,
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tool_calls: None,
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model: "test".to_string(),
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usage: None,
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}),
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Ok(ProviderStreamChunk {
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content: " World".to_string(),
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reasoning_content: None,
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finish_reason: Some("stop".to_string()),
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tool_calls: None,
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model: "test".to_string(),
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usage: None,
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}),
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];
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let inner_stream = stream::iter(chunks);
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let pool = sqlx::SqlitePool::connect("sqlite::memory:").await.unwrap();
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let (dashboard_tx, _) = tokio::sync::broadcast::channel(16);
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let logger = Arc::new(RequestLogger::new(pool.clone(), dashboard_tx));
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let client_manager = Arc::new(ClientManager::new(pool.clone()));
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let registry = Arc::new(crate::models::registry::ModelRegistry {
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providers: std::collections::HashMap::new(),
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});
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let mut agg_stream = AggregatingStream::new(
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inner_stream,
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StreamConfig {
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client_id: "client_1".to_string(),
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provider: Arc::new(MockProvider),
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model: "test".to_string(),
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prompt_tokens: 10,
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has_images: false,
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logger,
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client_manager,
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model_registry: registry,
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model_config_cache: ModelConfigCache::new(pool.clone()),
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},
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);
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while let Some(item) = agg_stream.next().await {
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assert!(item.is_ok());
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}
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assert_eq!(agg_stream.accumulated_content, "Hello World");
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assert!(agg_stream.has_logged);
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}
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}
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