release/v1.5.6
claude/github-issue-40-0au5ua
claude/linked-issue-acp-tui-u4vvpa
claude/minor-release-cut-vkugow
claude/sigit-acp-local-chat-cx6380
claude/sigit-cloud-agent-expansion-reox0a
claude/tool-permission-system
claude/zen-feynman-0u78dk
development
feature/acp-cancel-request
feature/acp-session-list-cursor
feature/acp-v1-conformance
feature/agent-tools-multiedit-glob-todos-remember
feature/cargo-workspace
feature/hooks
feature/load-local-model-explicitly
feature/sigit-agent-profile
feature/sigit-code-cloud
feature/xcode-mcp-server
fix/acp-replay-loaded-session-history
fix/acp-replay-reasoning-and-attachments
fix/dsml-doubled-bar-markers
main
release/v1.5.10
release/v1.5.6
release/v1.6.1
| 1 | //! Inference backend abstraction. |
| 2 | //! |
| 3 | //! The agent loop only needs to send a turn (optionally with tools) and return |
| 4 | //! tool results. This module defines that seam as the `InferenceBackend` trait |
| 5 | //! plus a few neutral types, with two implementations: |
| 6 | //! |
| 7 | //! - `LocalBackend` runs on-device through the `onde` crate (`ChatEngine`). |
| 8 | //! - `OpenAiBackend` talks to any OpenAI-compatible HTTP endpoint, configured by |
| 9 | //! `base_url`, `api_key`, and `model`. |
| 10 | //! |
| 11 | //! The trait exposes neither `onde` nor OpenAI types, so the loop does not depend |
| 12 | //! on a specific backend. |
| 13 | //! |
| 14 | //! The seam is consumed by both surfaces: the interactive client (`#[cfg(unix)]`, |
| 15 | //! see `run_interactive` in `main.rs` and `mod tui` in `chat.rs`) and the ACP |
| 16 | //! server's prompt loop. Some items are still reached only through the |
| 17 | //! Unix-only interactive paths, so the dead-code lint stays suppressed on |
| 18 | //! non-Unix targets only — Unix builds keep full coverage. |
| 19 | #![cfg_attr(not(unix), allow(dead_code))] |
| 20 | |
| 21 | use std::sync::Arc; |
| 22 | |
| 23 | use async_trait::async_trait; |
| 24 | use onde::inference::{ChatEngine, ChatMessage, ChatRole, ToolDefinition}; |
| 25 | use serde::Deserialize; |
| 26 | use tokio::sync::Mutex; |
| 27 | |
| 28 | // ── Neutral types ─────────────────────────────────────────────────────────────── |
| 29 | |
| 30 | /// A tool the model may call, in a provider-neutral form. `parameters_schema` is |
| 31 | /// a JSON Schema encoded as a string (matching how siGit already declares tools). |
| 32 | #[derive(Debug, Clone)] |
| 33 | pub struct ToolSpec { |
| 34 | pub name: String, |
| 35 | pub description: String, |
| 36 | pub parameters_schema: String, |
| 37 | } |
| 38 | |
| 39 | /// A tool call requested by the model. |
| 40 | #[derive(Debug, Clone)] |
| 41 | pub struct ToolCall { |
| 42 | pub id: String, |
| 43 | pub name: String, |
| 44 | /// Arguments as a JSON-encoded string. |
| 45 | pub arguments: String, |
| 46 | } |
| 47 | |
| 48 | /// The output of executing one tool call, fed back to the model. |
| 49 | #[derive(Debug, Clone)] |
| 50 | pub struct ToolResult { |
| 51 | pub tool_call_id: String, |
| 52 | pub content: String, |
| 53 | } |
| 54 | |
| 55 | /// The result of one assistant turn: free text and/or tool calls. |
| 56 | #[derive(Debug, Clone, Default)] |
| 57 | pub struct TurnResult { |
| 58 | pub text: String, |
| 59 | pub tool_calls: Vec<ToolCall>, |
| 60 | } |
| 61 | |
| 62 | /// Backend errors are plain strings. Callers map them to ACP errors. |
| 63 | pub type BackendError = String; |
| 64 | |
| 65 | /// Rough context budget for a conversation, in estimated tokens (see |
| 66 | /// [`estimate_tokens`]). When a snapshot exceeds this, the agent loops compact |
| 67 | /// history before the next tool round. |
| 68 | pub const DEFAULT_CONTEXT_TOKEN_BUDGET: usize = 24_000; |
| 69 | |
| 70 | /// How many trailing messages survive a compaction verbatim (the rest are |
| 71 | /// folded into the summary). |
| 72 | pub const COMPACT_KEEP_LAST: usize = 6; |
| 73 | |
| 74 | /// The summarization request sent to the model when compacting history. |
| 75 | const SUMMARIZE_PROMPT: &str = "Summarize this coding session so far: decisions made, \ |
| 76 | files touched, current state, open items. Be concise and factual."; |
| 77 | |
| 78 | /// Crude token estimate for a history snapshot: serialized characters / 4. |
| 79 | /// Deliberately model-agnostic — it only needs to be in the right ballpark to |
| 80 | /// decide when compaction is worth an extra inference round. |
| 81 | pub fn estimate_tokens(history: &[serde_json::Value]) -> usize { |
| 82 | let chars: usize = history |
| 83 | .iter() |
| 84 | .map(|message| message.to_string().chars().count()) |
| 85 | .sum(); |
| 86 | chars / 4 |
| 87 | } |
| 88 | |
| 89 | /// A sink for streaming assistant text deltas to the UI as they are produced. |
| 90 | /// |
| 91 | /// When a caller passes `Some(sink)`, a streaming-capable backend forwards each |
| 92 | /// text fragment through it as the model emits it; the returned [`TurnResult`] |
| 93 | /// still carries the fully assembled text (and any tool calls). When the sink is |
| 94 | /// `None`, the backend runs in non-streaming mode. Unbounded so the inference |
| 95 | /// task never blocks on a slow consumer. |
| 96 | pub type TokenSink = tokio::sync::mpsc::UnboundedSender<String>; |
| 97 | |
| 98 | // ── The trait ─────────────────────────────────────────────────────────────────── |
| 99 | |
| 100 | /// A swappable inference backend driving siGit Code's agent loop. |
| 101 | #[async_trait] |
| 102 | pub trait InferenceBackend: Send + Sync { |
| 103 | /// Start an assistant turn from a new user message, offering `tools`. |
| 104 | /// |
| 105 | /// If `sink` is `Some`, text is streamed through it as it is generated. A |
| 106 | /// backend may decline to stream a given round (for example, on-device |
| 107 | /// inference cannot stream while it is still deciding whether to call a |
| 108 | /// tool); in that case the text is delivered only via the returned result. |
| 109 | async fn send_message_with_tools( |
| 110 | &self, |
| 111 | text: &str, |
| 112 | tools: &[ToolSpec], |
| 113 | sink: Option<&TokenSink>, |
| 114 | ) -> Result<TurnResult, BackendError>; |
| 115 | |
| 116 | /// Continue the turn by returning tool results. `tools` may be `None` on the |
| 117 | /// final round to force a text answer. `sink` streams that text when set. |
| 118 | async fn send_tool_results( |
| 119 | &self, |
| 120 | results: Vec<ToolResult>, |
| 121 | tools: Option<&[ToolSpec]>, |
| 122 | sink: Option<&TokenSink>, |
| 123 | ) -> Result<TurnResult, BackendError>; |
| 124 | |
| 125 | /// Record tool results in the conversation history *without* asking the |
| 126 | /// model to continue the turn. Used when a turn is abandoned mid-round |
| 127 | /// (the user cancelled at the permission gate): by then the assistant |
| 128 | /// message carrying the tool calls is already in history, and leaving them |
| 129 | /// unanswered makes strict OpenAI-compatible endpoints reject every later |
| 130 | /// request in the session. |
| 131 | async fn record_cancelled_tool_results(&self, results: Vec<ToolResult>); |
| 132 | |
| 133 | /// Whether inference runs over the network (a configured provider) rather |
| 134 | /// than on-device. Drives UI labelling so the displayed model can't claim a |
| 135 | /// local model while requests actually go to the cloud. |
| 136 | fn is_remote(&self) -> bool; |
| 137 | |
| 138 | /// A serializable snapshot of the conversation history, one JSON object per |
| 139 | /// message (`{"role": ..., "content": ...}` at minimum). The snapshot is |
| 140 | /// what the session store persists; it includes any seeded system message |
| 141 | /// so [`InferenceBackend::restore_history`] can replace state wholesale. |
| 142 | async fn history_snapshot(&self) -> Vec<serde_json::Value>; |
| 143 | |
| 144 | /// Replace the conversation history with a previously saved snapshot. |
| 145 | /// Backends that cannot represent every entry (e.g. on-device history has |
| 146 | /// no tool-call structure) flatten what they can and drop the rest. |
| 147 | async fn restore_history(&self, history: Vec<serde_json::Value>); |
| 148 | |
| 149 | /// Shrink the conversation history: summarize everything so far with one |
| 150 | /// extra (non-streaming) inference round, then rebuild history as |
| 151 | /// `[system message, summary, last keep_last non-system messages]`. On |
| 152 | /// error the original history is left in place. |
| 153 | async fn compact_history(&self, keep_last: usize) -> Result<(), BackendError>; |
| 154 | } |
| 155 | |
| 156 | // ── Local backend (onde ChatEngine) ────────────────────────────────────────────── |
| 157 | |
| 158 | /// On-device inference. A thin adapter over `onde::ChatEngine`. |
| 159 | pub struct LocalBackend { |
| 160 | engine: Arc<ChatEngine>, |
| 161 | } |
| 162 | |
| 163 | impl LocalBackend { |
| 164 | pub fn new(engine: Arc<ChatEngine>) -> Self { |
| 165 | Self { engine } |
| 166 | } |
| 167 | } |
| 168 | |
| 169 | fn to_onde_tools(tools: &[ToolSpec]) -> Vec<ToolDefinition> { |
| 170 | tools |
| 171 | .iter() |
| 172 | .map(|tool| ToolDefinition { |
| 173 | name: tool.name.clone(), |
| 174 | description: tool.description.clone(), |
| 175 | parameters_schema: tool.parameters_schema.clone(), |
| 176 | }) |
| 177 | .collect() |
| 178 | } |
| 179 | |
| 180 | #[async_trait] |
| 181 | impl InferenceBackend for LocalBackend { |
| 182 | async fn send_message_with_tools( |
| 183 | &self, |
| 184 | text: &str, |
| 185 | tools: &[ToolSpec], |
| 186 | sink: Option<&TokenSink>, |
| 187 | ) -> Result<TurnResult, BackendError> { |
| 188 | // onde's tool-aware path is non-streaming: it has to buffer the whole |
| 189 | // reply to detect tool calls. We can only stream when no tools are on |
| 190 | // offer (a plain answer), which is exactly the tools-disabled case. |
| 191 | if let Some(sink) = sink |
| 192 | && tools.is_empty() |
| 193 | { |
| 194 | let rx = self |
| 195 | .engine |
| 196 | .stream_message(text) |
| 197 | .await |
| 198 | .map_err(|error| error.to_string())?; |
| 199 | return drain_onde_stream(rx, sink).await; |
| 200 | } |
| 201 | |
| 202 | let onde_tools = to_onde_tools(tools); |
| 203 | let result = self |
| 204 | .engine |
| 205 | .send_message_with_tools(text, &onde_tools) |
| 206 | .await |
| 207 | .map_err(|error| error.to_string())?; |
| 208 | Ok(onde_result_to_turn(result)) |
| 209 | } |
| 210 | |
| 211 | async fn send_tool_results( |
| 212 | &self, |
| 213 | results: Vec<ToolResult>, |
| 214 | tools: Option<&[ToolSpec]>, |
| 215 | sink: Option<&TokenSink>, |
| 216 | ) -> Result<TurnResult, BackendError> { |
| 217 | let onde_results: Vec<onde::inference::ToolResult> = results |
| 218 | .into_iter() |
| 219 | .map(|result| onde::inference::ToolResult { |
| 220 | tool_call_id: result.tool_call_id, |
| 221 | content: result.content, |
| 222 | }) |
| 223 | .collect(); |
| 224 | |
| 225 | // The final round passes `tools = None` to force a text answer; that's |
| 226 | // the only round onde can stream, since no further tool calls are parsed. |
| 227 | if let Some(sink) = sink |
| 228 | && tools.is_none() |
| 229 | { |
| 230 | let rx = self |
| 231 | .engine |
| 232 | .stream_tool_results(onde_results, None) |
| 233 | .await |
| 234 | .map_err(|error| error.to_string())?; |
| 235 | return drain_onde_stream(rx, sink).await; |
| 236 | } |
| 237 | |
| 238 | let onde_tools = tools.map(to_onde_tools); |
| 239 | let result = self |
| 240 | .engine |
| 241 | .send_tool_results(onde_results, onde_tools.as_deref()) |
| 242 | .await |
| 243 | .map_err(|error| error.to_string())?; |
| 244 | Ok(onde_result_to_turn(result)) |
| 245 | } |
| 246 | |
| 247 | async fn record_cancelled_tool_results(&self, _results: Vec<ToolResult>) { |
| 248 | // onde's public API cannot append tool-result history entries without |
| 249 | // running another inference round, so the dangling tool call stays in |
| 250 | // its history. The chat template replays it as-is, which local models |
| 251 | // tolerate — worst case the model re-issues the call next turn. |
| 252 | } |
| 253 | |
| 254 | fn is_remote(&self) -> bool { |
| 255 | false |
| 256 | } |
| 257 | |
| 258 | async fn history_snapshot(&self) -> Vec<serde_json::Value> { |
| 259 | // onde's `history()` already flattens tool entries: assistant tool |
| 260 | // calls become plain assistant text and tool results are omitted, so |
| 261 | // the snapshot is lossy for tool-heavy turns (acceptable in this MVP). |
| 262 | self.engine |
| 263 | .history() |
| 264 | .await |
| 265 | .iter() |
| 266 | .map(|message| { |
| 267 | serde_json::json!({ |
| 268 | "role": message.role.to_string(), |
| 269 | "content": message.content, |
| 270 | }) |
| 271 | }) |
| 272 | .collect() |
| 273 | } |
| 274 | |
| 275 | async fn restore_history(&self, history: Vec<serde_json::Value>) { |
| 276 | self.engine.clear_history().await; |
| 277 | for entry in history { |
| 278 | let role = entry["role"].as_str().unwrap_or(""); |
| 279 | let content = entry["content"].as_str().unwrap_or("").to_string(); |
| 280 | // Tool-call-only assistant entries and empty tool results carry no |
| 281 | // text a plain chat history can replay; drop them. |
| 282 | if content.is_empty() && role != "user" && role != "system" { |
| 283 | continue; |
| 284 | } |
| 285 | let message = match role { |
| 286 | "system" => ChatMessage::system(content), |
| 287 | "user" => ChatMessage::user(content), |
| 288 | "assistant" => ChatMessage::assistant(content), |
| 289 | // Tool results flatten to plain text (MVP; acceptable loss). |
| 290 | "tool" => ChatMessage::user(format!("[tool result]\n{content}")), |
| 291 | _ => continue, |
| 292 | }; |
| 293 | self.engine.push_history(message).await; |
| 294 | } |
| 295 | } |
| 296 | |
| 297 | async fn compact_history(&self, keep_last: usize) -> Result<(), BackendError> { |
| 298 | let snapshot = self.engine.history().await; |
| 299 | // One plain (tool-free) inference round produces the summary. On error |
| 300 | // history is untouched — send_message only mutates it on success, and |
| 301 | // whatever it appended is wiped by the clear below anyway. |
| 302 | let result = self |
| 303 | .engine |
| 304 | .send_message(SUMMARIZE_PROMPT) |
| 305 | .await |
| 306 | .map_err(|error| error.to_string())?; |
| 307 | // Local models may reason in <think> blocks; keep only the visible part. |
| 308 | let (_think, summary) = crate::chat::strip_think_blocks(&result.text); |
| 309 | |
| 310 | self.engine.clear_history().await; |
| 311 | // Leading system messages carry the session context; keep them all. |
| 312 | for message in snapshot |
| 313 | .iter() |
| 314 | .take_while(|message| message.role == ChatRole::System) |
| 315 | { |
| 316 | self.engine.push_history(message.clone()).await; |
| 317 | } |
| 318 | self.engine |
| 319 | .push_history(ChatMessage::user(format!( |
| 320 | "[Conversation summary]\n{summary}" |
| 321 | ))) |
| 322 | .await; |
| 323 | let non_system: Vec<&ChatMessage> = snapshot |
| 324 | .iter() |
| 325 | .filter(|message| message.role != ChatRole::System) |
| 326 | .collect(); |
| 327 | let tail_start = non_system.len().saturating_sub(keep_last); |
| 328 | for message in &non_system[tail_start..] { |
| 329 | self.engine.push_history((*message).clone()).await; |
| 330 | } |
| 331 | Ok(()) |
| 332 | } |
| 333 | } |
| 334 | |
| 335 | /// Drain an onde streaming receiver, forwarding each token to `sink` and |
| 336 | /// assembling the full text. onde reports stream failures as a final chunk whose |
| 337 | /// `finish_reason` is `"error: …"`; surface those as a backend error. |
| 338 | async fn drain_onde_stream( |
| 339 | mut rx: tokio::sync::mpsc::Receiver<onde::inference::StreamChunk>, |
| 340 | sink: &TokenSink, |
| 341 | ) -> Result<TurnResult, BackendError> { |
| 342 | let mut text = String::new(); |
| 343 | while let Some(chunk) = rx.recv().await { |
| 344 | if !chunk.delta.is_empty() { |
| 345 | text.push_str(&chunk.delta); |
| 346 | // The receiver is the UI; if it's gone the turn is being cancelled, |
| 347 | // so stop assembling rather than spinning the model to completion. |
| 348 | if sink.send(chunk.delta).is_err() { |
| 349 | break; |
| 350 | } |
| 351 | } |
| 352 | if chunk.done { |
| 353 | if let Some(reason) = chunk.finish_reason |
| 354 | && let Some(message) = reason.strip_prefix("error: ") |
| 355 | { |
| 356 | return Err(message.to_string()); |
| 357 | } |
| 358 | break; |
| 359 | } |
| 360 | } |
| 361 | Ok(TurnResult { |
| 362 | text, |
| 363 | tool_calls: Vec::new(), |
| 364 | }) |
| 365 | } |
| 366 | |
| 367 | /// Convert an `onde` tool-aware result into the neutral [`TurnResult`]. |
| 368 | fn onde_result_to_turn(result: onde::inference::ToolAwareResult) -> TurnResult { |
| 369 | TurnResult { |
| 370 | text: result.text, |
| 371 | tool_calls: result |
| 372 | .tool_calls |
| 373 | .into_iter() |
| 374 | .map(|call| ToolCall { |
| 375 | id: call.id, |
| 376 | name: call.function_name, |
| 377 | arguments: call.arguments, |
| 378 | }) |
| 379 | .collect(), |
| 380 | } |
| 381 | } |
| 382 | |
| 383 | // ── OpenAI-compatible backend ───────────────────────────────────────────────────── |
| 384 | |
| 385 | /// Inference against any OpenAI-compatible Chat Completions endpoint. |
| 386 | /// |
| 387 | /// Conversation state is held client-side and replayed on every request, so the |
| 388 | /// endpoint can be stateless. Standard OpenAI function-calling is used end to |
| 389 | /// end (`tools`, `choices[].message.tool_calls`, `role: "tool"` follow-ups). |
| 390 | pub struct OpenAiBackend { |
| 391 | base_url: String, |
| 392 | api_key: String, |
| 393 | model: String, |
| 394 | http: reqwest::Client, |
| 395 | /// The full message list sent on each request (system + turns + tool results). |
| 396 | history: Mutex<Vec<serde_json::Value>>, |
| 397 | } |
| 398 | |
| 399 | impl OpenAiBackend { |
| 400 | /// Build a backend for `{base_url, api_key, model}`, seeding the optional |
| 401 | /// system prompt. `base_url` should include the API root (e.g. ending in |
| 402 | /// `/v1`); the chat path is appended. |
| 403 | pub fn new( |
| 404 | base_url: impl Into<String>, |
| 405 | api_key: impl Into<String>, |
| 406 | model: impl Into<String>, |
| 407 | system_prompt: Option<String>, |
| 408 | ) -> Self { |
| 409 | let mut history = Vec::new(); |
| 410 | if let Some(prompt) = system_prompt { |
| 411 | history.push(serde_json::json!({ "role": "system", "content": prompt })); |
| 412 | } |
| 413 | Self { |
| 414 | base_url: base_url.into(), |
| 415 | api_key: api_key.into(), |
| 416 | model: model.into(), |
| 417 | http: reqwest::Client::new(), |
| 418 | history: Mutex::new(history), |
| 419 | } |
| 420 | } |
| 421 | |
| 422 | fn tools_json(tools: &[ToolSpec]) -> Vec<serde_json::Value> { |
| 423 | tools |
| 424 | .iter() |
| 425 | .map(|tool| { |
| 426 | // parameters_schema is a JSON string; parse it, defaulting to an |
| 427 | // empty object schema if malformed. |
| 428 | let parameters: serde_json::Value = serde_json::from_str(&tool.parameters_schema) |
| 429 | .unwrap_or_else(|_| serde_json::json!({ "type": "object", "properties": {} })); |
| 430 | serde_json::json!({ |
| 431 | "type": "function", |
| 432 | "function": { |
| 433 | "name": tool.name, |
| 434 | "description": tool.description, |
| 435 | "parameters": parameters, |
| 436 | } |
| 437 | }) |
| 438 | }) |
| 439 | .collect() |
| 440 | } |
| 441 | |
| 442 | /// POST the current history (plus `tools`) and apply the assistant reply to |
| 443 | /// history, returning the neutral turn result. Streams via SSE when `sink` |
| 444 | /// is set; otherwise reads a single JSON response. |
| 445 | async fn complete( |
| 446 | &self, |
| 447 | tools: Option<&[ToolSpec]>, |
| 448 | sink: Option<&TokenSink>, |
| 449 | ) -> Result<TurnResult, BackendError> { |
| 450 | let url = format!("{}/chat/completions", self.base_url.trim_end_matches('/')); |
| 451 | let streaming = sink.is_some(); |
| 452 | |
| 453 | let mut body = serde_json::json!({ |
| 454 | "model": self.model, |
| 455 | "messages": *self.history.lock().await, |
| 456 | "stream": streaming, |
| 457 | }); |
| 458 | if let Some(tools) = tools |
| 459 | && !tools.is_empty() |
| 460 | { |
| 461 | body["tools"] = serde_json::Value::Array(Self::tools_json(tools)); |
| 462 | // OpenAI specifies `auto` as the default when tools are present, |
| 463 | // but not every OpenAI-compatible gateway implements that default. |
| 464 | // Sending it explicitly is important for the cloud path: otherwise |
| 465 | // a model can describe the action it intends to take as text and |
| 466 | // end the turn without returning a tool call at all. |
| 467 | body["tool_choice"] = serde_json::Value::String("auto".to_string()); |
| 468 | } |
| 469 | |
| 470 | let response = self |
| 471 | .http |
| 472 | .post(&url) |
| 473 | .bearer_auth(&self.api_key) |
| 474 | .json(&body) |
| 475 | .send() |
| 476 | .await |
| 477 | .map_err(|error| format!("request to {url} failed: {error}"))?; |
| 478 | |
| 479 | if !response.status().is_success() { |
| 480 | let status = response.status(); |
| 481 | let detail = response.text().await.unwrap_or_default(); |
| 482 | return Err(format!("endpoint returned {status}: {detail}")); |
| 483 | } |
| 484 | |
| 485 | if let Some(sink) = sink { |
| 486 | self.consume_stream(response, sink).await |
| 487 | } else { |
| 488 | self.consume_json(response).await |
| 489 | } |
| 490 | } |
| 491 | |
| 492 | /// Parse a single non-streaming chat-completion response. |
| 493 | async fn consume_json(&self, response: reqwest::Response) -> Result<TurnResult, BackendError> { |
| 494 | let parsed: ChatCompletion = response |
| 495 | .json() |
| 496 | .await |
| 497 | .map_err(|error| format!("response parse error: {error}"))?; |
| 498 | |
| 499 | let message = parsed |
| 500 | .choices |
| 501 | .into_iter() |
| 502 | .next() |
| 503 | .map(|choice| choice.message) |
| 504 | .ok_or_else(|| "endpoint returned no choices".to_string())?; |
| 505 | |
| 506 | let text = message.content.clone().unwrap_or_default(); |
| 507 | let tool_calls: Vec<ToolCall> = message |
| 508 | .tool_calls |
| 509 | .iter() |
| 510 | .flatten() |
| 511 | .map(|call| ToolCall { |
| 512 | id: call.id.clone(), |
| 513 | name: call.function.name.clone(), |
| 514 | arguments: call.function.arguments.clone(), |
| 515 | }) |
| 516 | .collect(); |
| 517 | |
| 518 | // Record the assistant turn so later tool results have context. |
| 519 | self.history.lock().await.push(message.into_history_value()); |
| 520 | |
| 521 | Ok(TurnResult { text, tool_calls }) |
| 522 | } |
| 523 | |
| 524 | /// Consume an OpenAI Server-Sent Events stream, forwarding content deltas to |
| 525 | /// `sink` and reassembling any tool calls (which arrive fragmented across |
| 526 | /// chunks, keyed by `index`). |
| 527 | async fn consume_stream( |
| 528 | &self, |
| 529 | response: reqwest::Response, |
| 530 | sink: &TokenSink, |
| 531 | ) -> Result<TurnResult, BackendError> { |
| 532 | use futures::StreamExt; |
| 533 | |
| 534 | let mut stream = response.bytes_stream(); |
| 535 | // Newlines are ASCII, so splitting raw bytes on `\n` never bisects a |
| 536 | // multibyte UTF-8 sequence; we only lossily decode whole lines. |
| 537 | let mut buffer: Vec<u8> = Vec::new(); |
| 538 | let mut text = String::new(); |
| 539 | let mut tool_accum: Vec<StreamingToolCall> = Vec::new(); |
| 540 | let mut done = false; |
| 541 | |
| 542 | while let Some(item) = stream.next().await { |
| 543 | let bytes = item.map_err(|error| format!("stream read error: {error}"))?; |
| 544 | buffer.extend_from_slice(&bytes); |
| 545 | |
| 546 | while let Some(pos) = buffer.iter().position(|&b| b == b'\n') { |
| 547 | let line: Vec<u8> = buffer.drain(..=pos).collect(); |
| 548 | let line = String::from_utf8_lossy(&line); |
| 549 | let line = line.trim(); |
| 550 | |
| 551 | let Some(data) = line.strip_prefix("data:") else { |
| 552 | continue; |
| 553 | }; |
| 554 | let data = data.trim(); |
| 555 | if data == "[DONE]" { |
| 556 | done = true; |
| 557 | break; |
| 558 | } |
| 559 | if data.is_empty() { |
| 560 | continue; |
| 561 | } |
| 562 | |
| 563 | let chunk: StreamCompletion = match serde_json::from_str(data) { |
| 564 | Ok(chunk) => chunk, |
| 565 | // Skip keep-alive comments and anything we can't parse rather |
| 566 | // than aborting a turn over one malformed frame. |
| 567 | Err(_) => continue, |
| 568 | }; |
| 569 | |
| 570 | let Some(choice) = chunk.choices.into_iter().next() else { |
| 571 | continue; |
| 572 | }; |
| 573 | if let Some(content) = choice.delta.content |
| 574 | && !content.is_empty() |
| 575 | { |
| 576 | text.push_str(&content); |
| 577 | if sink.send(content).is_err() { |
| 578 | // Consumer dropped (turn cancelled) — stop reading. |
| 579 | done = true; |
| 580 | break; |
| 581 | } |
| 582 | } |
| 583 | for delta in choice.delta.tool_calls.into_iter().flatten() { |
| 584 | let index = delta.index.unwrap_or(0) as usize; |
| 585 | if tool_accum.len() <= index { |
| 586 | tool_accum.resize_with(index + 1, StreamingToolCall::default); |
| 587 | } |
| 588 | let slot = &mut tool_accum[index]; |
| 589 | if let Some(id) = delta.id { |
| 590 | slot.id = id; |
| 591 | } |
| 592 | if let Some(function) = delta.function { |
| 593 | if let Some(name) = function.name { |
| 594 | slot.name = name; |
| 595 | } |
| 596 | if let Some(arguments) = function.arguments { |
| 597 | slot.arguments.push_str(&arguments); |
| 598 | } |
| 599 | } |
| 600 | } |
| 601 | } |
| 602 | |
| 603 | if done { |
| 604 | break; |
| 605 | } |
| 606 | } |
| 607 | |
| 608 | let tool_calls: Vec<ToolCall> = tool_accum |
| 609 | .iter() |
| 610 | .filter(|call| !call.name.is_empty()) |
| 611 | .enumerate() |
| 612 | .map(|(index, call)| ToolCall { |
| 613 | id: if call.id.is_empty() { |
| 614 | format!("call_{index}") |
| 615 | } else { |
| 616 | call.id.clone() |
| 617 | }, |
| 618 | name: call.name.clone(), |
| 619 | arguments: call.arguments.clone(), |
| 620 | }) |
| 621 | .collect(); |
| 622 | |
| 623 | // Record the assistant turn so later tool results have context. |
| 624 | self.history |
| 625 | .lock() |
| 626 | .await |
| 627 | .push(streamed_assistant_history(&text, &tool_calls)); |
| 628 | |
| 629 | Ok(TurnResult { text, tool_calls }) |
| 630 | } |
| 631 | } |
| 632 | |
| 633 | /// One tool call being reassembled from streamed deltas. |
| 634 | #[derive(Default)] |
| 635 | struct StreamingToolCall { |
| 636 | id: String, |
| 637 | name: String, |
| 638 | arguments: String, |
| 639 | } |
| 640 | |
| 641 | /// Rebuild the assistant message for replay in history after a streamed turn, |
| 642 | /// preserving any tool calls so the follow-up request is well-formed. Mirrors |
| 643 | /// [`ResponseMessage::into_history_value`] for the non-streaming path. |
| 644 | fn streamed_assistant_history(text: &str, tool_calls: &[ToolCall]) -> serde_json::Value { |
| 645 | let mut message = serde_json::json!({ "role": "assistant" }); |
| 646 | message["content"] = if text.is_empty() { |
| 647 | serde_json::Value::Null |
| 648 | } else { |
| 649 | serde_json::Value::String(text.to_string()) |
| 650 | }; |
| 651 | if !tool_calls.is_empty() { |
| 652 | message["tool_calls"] = serde_json::json!( |
| 653 | tool_calls |
| 654 | .iter() |
| 655 | .map(|call| serde_json::json!({ |
| 656 | "id": call.id, |
| 657 | "type": "function", |
| 658 | "function": { |
| 659 | "name": call.name, |
| 660 | "arguments": call.arguments, |
| 661 | } |
| 662 | })) |
| 663 | .collect::<Vec<_>>() |
| 664 | ); |
| 665 | } |
| 666 | message |
| 667 | } |
| 668 | |
| 669 | #[async_trait] |
| 670 | impl InferenceBackend for OpenAiBackend { |
| 671 | async fn send_message_with_tools( |
| 672 | &self, |
| 673 | text: &str, |
| 674 | tools: &[ToolSpec], |
| 675 | sink: Option<&TokenSink>, |
| 676 | ) -> Result<TurnResult, BackendError> { |
| 677 | self.history |
| 678 | .lock() |
| 679 | .await |
| 680 | .push(serde_json::json!({ "role": "user", "content": text })); |
| 681 | self.complete(Some(tools), sink).await |
| 682 | } |
| 683 | |
| 684 | async fn send_tool_results( |
| 685 | &self, |
| 686 | results: Vec<ToolResult>, |
| 687 | tools: Option<&[ToolSpec]>, |
| 688 | sink: Option<&TokenSink>, |
| 689 | ) -> Result<TurnResult, BackendError> { |
| 690 | { |
| 691 | let mut history = self.history.lock().await; |
| 692 | for result in results { |
| 693 | history.push(serde_json::json!({ |
| 694 | "role": "tool", |
| 695 | "tool_call_id": result.tool_call_id, |
| 696 | "content": result.content, |
| 697 | })); |
| 698 | } |
| 699 | } |
| 700 | self.complete(tools, sink).await |
| 701 | } |
| 702 | |
| 703 | async fn record_cancelled_tool_results(&self, results: Vec<ToolResult>) { |
| 704 | let mut history = self.history.lock().await; |
| 705 | for result in results { |
| 706 | history.push(serde_json::json!({ |
| 707 | "role": "tool", |
| 708 | "tool_call_id": result.tool_call_id, |
| 709 | "content": result.content, |
| 710 | })); |
| 711 | } |
| 712 | } |
| 713 | |
| 714 | fn is_remote(&self) -> bool { |
| 715 | true |
| 716 | } |
| 717 | |
| 718 | async fn history_snapshot(&self) -> Vec<serde_json::Value> { |
| 719 | self.history.lock().await.clone() |
| 720 | } |
| 721 | |
| 722 | async fn restore_history(&self, history: Vec<serde_json::Value>) { |
| 723 | // The snapshot includes the seeded system message, so a wholesale |
| 724 | // replacement restores exactly what was saved. |
| 725 | *self.history.lock().await = history; |
| 726 | } |
| 727 | |
| 728 | async fn compact_history(&self, keep_last: usize) -> Result<(), BackendError> { |
| 729 | let snapshot: Vec<serde_json::Value> = self.history.lock().await.clone(); |
| 730 | |
| 731 | // Ask the endpoint for a summary of the conversation so far, through |
| 732 | // the ordinary completion machinery (non-streaming). |
| 733 | self.history |
| 734 | .lock() |
| 735 | .await |
| 736 | .push(serde_json::json!({ "role": "user", "content": SUMMARIZE_PROMPT })); |
| 737 | let summary = match self.complete(None, None).await { |
| 738 | Ok(result) => result.text, |
| 739 | Err(error) => { |
| 740 | // Roll back the summarization request; the turn never happened. |
| 741 | *self.history.lock().await = snapshot; |
| 742 | return Err(error); |
| 743 | } |
| 744 | }; |
| 745 | |
| 746 | let system = snapshot |
| 747 | .first() |
| 748 | .filter(|message| message["role"] == "system") |
| 749 | .cloned(); |
| 750 | let non_system: Vec<serde_json::Value> = snapshot |
| 751 | .iter() |
| 752 | .filter(|message| message["role"] != "system") |
| 753 | .cloned() |
| 754 | .collect(); |
| 755 | let tail_start = non_system.len().saturating_sub(keep_last); |
| 756 | let mut tail = non_system[tail_start..].to_vec(); |
| 757 | // Drop leading tool results whose assistant tool-call message was |
| 758 | // summarized away — strict endpoints reject orphaned `role: "tool"` |
| 759 | // entries on the very next request. |
| 760 | while tail |
| 761 | .first() |
| 762 | .is_some_and(|message| message["role"] == "tool") |
| 763 | { |
| 764 | tail.remove(0); |
| 765 | } |
| 766 | |
| 767 | let mut rebuilt = Vec::new(); |
| 768 | if let Some(system) = system { |
| 769 | rebuilt.push(system); |
| 770 | } |
| 771 | rebuilt.push(serde_json::json!({ |
| 772 | "role": "user", |
| 773 | "content": format!("[Conversation summary]\n{summary}"), |
| 774 | })); |
| 775 | rebuilt.extend(tail); |
| 776 | *self.history.lock().await = rebuilt; |
| 777 | Ok(()) |
| 778 | } |
| 779 | } |
| 780 | |
| 781 | // ── OpenAI response shapes ──────────────────────────────────────────────────────── |
| 782 | |
| 783 | #[derive(Debug, Deserialize)] |
| 784 | struct ChatCompletion { |
| 785 | #[serde(default)] |
| 786 | choices: Vec<CompletionChoice>, |
| 787 | } |
| 788 | |
| 789 | #[derive(Debug, Deserialize)] |
| 790 | struct CompletionChoice { |
| 791 | message: ResponseMessage, |
| 792 | } |
| 793 | |
| 794 | #[derive(Debug, Deserialize)] |
| 795 | struct ResponseMessage { |
| 796 | #[serde(default)] |
| 797 | content: Option<String>, |
| 798 | #[serde(default)] |
| 799 | tool_calls: Option<Vec<ResponseToolCall>>, |
| 800 | } |
| 801 | |
| 802 | impl ResponseMessage { |
| 803 | /// Reconstruct the assistant message for replay in history, preserving any |
| 804 | /// tool calls so the follow-up request is well-formed. |
| 805 | fn into_history_value(self) -> serde_json::Value { |
| 806 | let mut message = serde_json::json!({ "role": "assistant" }); |
| 807 | message["content"] = match self.content { |
| 808 | Some(text) => serde_json::Value::String(text), |
| 809 | None => serde_json::Value::Null, |
| 810 | }; |
| 811 | if let Some(tool_calls) = self.tool_calls { |
| 812 | message["tool_calls"] = serde_json::json!( |
| 813 | tool_calls |
| 814 | .into_iter() |
| 815 | .map(|call| serde_json::json!({ |
| 816 | "id": call.id, |
| 817 | "type": "function", |
| 818 | "function": { |
| 819 | "name": call.function.name, |
| 820 | "arguments": call.function.arguments, |
| 821 | } |
| 822 | })) |
| 823 | .collect::<Vec<_>>() |
| 824 | ); |
| 825 | } |
| 826 | message |
| 827 | } |
| 828 | } |
| 829 | |
| 830 | #[derive(Debug, Deserialize)] |
| 831 | struct ResponseToolCall { |
| 832 | id: String, |
| 833 | function: ResponseFunction, |
| 834 | } |
| 835 | |
| 836 | #[derive(Debug, Deserialize)] |
| 837 | struct ResponseFunction { |
| 838 | name: String, |
| 839 | #[serde(default)] |
| 840 | arguments: String, |
| 841 | } |
| 842 | |
| 843 | // ── OpenAI streaming (SSE) chunk shapes ───────────────────────────────────────── |
| 844 | |
| 845 | #[derive(Debug, Deserialize)] |
| 846 | struct StreamCompletion { |
| 847 | #[serde(default)] |
| 848 | choices: Vec<StreamChoice>, |
| 849 | } |
| 850 | |
| 851 | #[derive(Debug, Deserialize)] |
| 852 | struct StreamChoice { |
| 853 | #[serde(default)] |
| 854 | delta: StreamDelta, |
| 855 | } |
| 856 | |
| 857 | #[derive(Debug, Default, Deserialize)] |
| 858 | struct StreamDelta { |
| 859 | #[serde(default)] |
| 860 | content: Option<String>, |
| 861 | #[serde(default)] |
| 862 | tool_calls: Option<Vec<StreamToolCallDelta>>, |
| 863 | } |
| 864 | |
| 865 | #[derive(Debug, Deserialize)] |
| 866 | struct StreamToolCallDelta { |
| 867 | #[serde(default)] |
| 868 | index: Option<u32>, |
| 869 | #[serde(default)] |
| 870 | id: Option<String>, |
| 871 | #[serde(default)] |
| 872 | function: Option<StreamFunctionDelta>, |
| 873 | } |
| 874 | |
| 875 | #[derive(Debug, Deserialize)] |
| 876 | struct StreamFunctionDelta { |
| 877 | #[serde(default)] |
| 878 | name: Option<String>, |
| 879 | #[serde(default)] |
| 880 | arguments: Option<String>, |
| 881 | } |
| 882 | |
| 883 | // ── Carrying a conversation across a model switch ──────────────────────────── |
| 884 | |
| 885 | /// The part of a history snapshot that survives a model switch: every |
| 886 | /// non-system message, with half-finished tool plumbing repaired. |
| 887 | /// |
| 888 | /// System messages are dropped because the backend being switched *to* seeds |
| 889 | /// its own — a different model's prompt, or a freshly pushed session-context |
| 890 | /// message. A switch can land mid-turn, after the assistant asked for a tool |
| 891 | /// but before the results came back; a tool call with no matching result (or a |
| 892 | /// result with no matching call) makes strict OpenAI-compatible endpoints |
| 893 | /// reject every later request in the session, so those halves are stripped |
| 894 | /// instead of carried. |
| 895 | pub fn carryover_history(snapshot: Vec<serde_json::Value>) -> Vec<serde_json::Value> { |
| 896 | let answered: std::collections::HashSet<String> = snapshot |
| 897 | .iter() |
| 898 | .filter(|message| message["role"] == "tool") |
| 899 | .filter_map(|message| message["tool_call_id"].as_str().map(str::to_string)) |
| 900 | .collect(); |
| 901 | |
| 902 | let mut carried: Vec<serde_json::Value> = Vec::with_capacity(snapshot.len()); |
| 903 | let mut called: std::collections::HashSet<String> = std::collections::HashSet::new(); |
| 904 | |
| 905 | for mut message in snapshot { |
| 906 | match message["role"].as_str().unwrap_or_default() { |
| 907 | "system" => continue, |
| 908 | "assistant" => { |
| 909 | if let Some(calls) = message["tool_calls"].as_array() { |
| 910 | let kept: Vec<serde_json::Value> = calls |
| 911 | .iter() |
| 912 | .filter(|call| call["id"].as_str().is_some_and(|id| answered.contains(id))) |
| 913 | .cloned() |
| 914 | .collect(); |
| 915 | if kept.is_empty() { |
| 916 | // Only unanswered requests: keep whatever text came |
| 917 | // with them, drop the message if there was none. |
| 918 | if let Some(object) = message.as_object_mut() { |
| 919 | object.remove("tool_calls"); |
| 920 | } |
| 921 | if message["content"].as_str().unwrap_or_default().is_empty() { |
| 922 | continue; |
| 923 | } |
| 924 | } else { |
| 925 | for call in &kept { |
| 926 | called.insert(call["id"].as_str().unwrap_or_default().to_string()); |
| 927 | } |
| 928 | message["tool_calls"] = serde_json::Value::Array(kept); |
| 929 | } |
| 930 | } |
| 931 | carried.push(message); |
| 932 | } |
| 933 | "tool" => { |
| 934 | let answers_a_kept_call = message["tool_call_id"] |
| 935 | .as_str() |
| 936 | .is_some_and(|id| called.contains(id)); |
| 937 | if answers_a_kept_call { |
| 938 | carried.push(message); |
| 939 | } |
| 940 | } |
| 941 | _ => carried.push(message), |
| 942 | } |
| 943 | } |
| 944 | |
| 945 | carried |
| 946 | } |
| 947 | |
| 948 | /// Replay `carried` (from [`carryover_history`]) into `backend`, on top of the |
| 949 | /// system messages `backend` seeded for itself. Used when a model switch |
| 950 | /// installs a new backend — or reloads the on-device engine, which wipes its |
| 951 | /// history — so the thread continues under the new model instead of restarting. |
| 952 | pub async fn adopt_carryover(backend: &dyn InferenceBackend, carried: Vec<serde_json::Value>) { |
| 953 | if carried.is_empty() { |
| 954 | return; |
| 955 | } |
| 956 | let mut rebuilt: Vec<serde_json::Value> = backend |
| 957 | .history_snapshot() |
| 958 | .await |
| 959 | .into_iter() |
| 960 | .take_while(|message| message["role"] == "system") |
| 961 | .collect(); |
| 962 | rebuilt.extend(carried); |
| 963 | backend.restore_history(rebuilt).await; |
| 964 | } |
| 965 | |
| 966 | #[cfg(test)] |
| 967 | mod tests { |
| 968 | use super::*; |
| 969 | |
| 970 | #[test] |
| 971 | fn tools_json_wraps_function_schema() { |
| 972 | let tools = vec![ToolSpec { |
| 973 | name: "read_file".to_string(), |
| 974 | description: "Read a file".to_string(), |
| 975 | parameters_schema: r#"{"type":"object","properties":{"path":{"type":"string"}}}"# |
| 976 | .to_string(), |
| 977 | }]; |
| 978 | let json = OpenAiBackend::tools_json(&tools); |
| 979 | assert_eq!(json[0]["type"], "function"); |
| 980 | assert_eq!(json[0]["function"]["name"], "read_file"); |
| 981 | assert_eq!( |
| 982 | json[0]["function"]["parameters"]["properties"]["path"]["type"], |
| 983 | "string" |
| 984 | ); |
| 985 | } |
| 986 | |
| 987 | #[test] |
| 988 | fn malformed_schema_falls_back_to_empty_object() { |
| 989 | let tools = vec![ToolSpec { |
| 990 | name: "x".to_string(), |
| 991 | description: String::new(), |
| 992 | parameters_schema: "not json".to_string(), |
| 993 | }]; |
| 994 | let json = OpenAiBackend::tools_json(&tools); |
| 995 | assert_eq!(json[0]["function"]["parameters"]["type"], "object"); |
| 996 | } |
| 997 | |
| 998 | #[test] |
| 999 | fn streamed_assistant_history_omits_empty_tool_calls() { |
| 1000 | let value = streamed_assistant_history("hello", &[]); |
| 1001 | assert_eq!(value["role"], "assistant"); |
| 1002 | assert_eq!(value["content"], "hello"); |
| 1003 | assert!(value.get("tool_calls").is_none()); |
| 1004 | } |
| 1005 | |
| 1006 | #[test] |
| 1007 | fn streamed_assistant_history_preserves_tool_calls() { |
| 1008 | let calls = vec![ToolCall { |
| 1009 | id: "call_0".to_string(), |
| 1010 | name: "read_file".to_string(), |
| 1011 | arguments: r#"{"path":"a.rs"}"#.to_string(), |
| 1012 | }]; |
| 1013 | let value = streamed_assistant_history("", &calls); |
| 1014 | assert!(value["content"].is_null()); |
| 1015 | assert_eq!(value["tool_calls"][0]["id"], "call_0"); |
| 1016 | assert_eq!(value["tool_calls"][0]["type"], "function"); |
| 1017 | assert_eq!(value["tool_calls"][0]["function"]["name"], "read_file"); |
| 1018 | assert_eq!( |
| 1019 | value["tool_calls"][0]["function"]["arguments"], |
| 1020 | r#"{"path":"a.rs"}"# |
| 1021 | ); |
| 1022 | } |
| 1023 | |
| 1024 | #[tokio::test] |
| 1025 | async fn cancelled_tool_results_close_out_history() { |
| 1026 | let backend = OpenAiBackend::new("http://localhost", "", "test-model", None); |
| 1027 | backend |
| 1028 | .history |
| 1029 | .lock() |
| 1030 | .await |
| 1031 | .push(streamed_assistant_history( |
| 1032 | "", |
| 1033 | &[ToolCall { |
| 1034 | id: "call_9".to_string(), |
| 1035 | name: "run_command".to_string(), |
| 1036 | arguments: r#"{"command":"ls"}"#.to_string(), |
| 1037 | }], |
| 1038 | )); |
| 1039 | |
| 1040 | backend |
| 1041 | .record_cancelled_tool_results(vec![ToolResult { |
| 1042 | tool_call_id: "call_9".to_string(), |
| 1043 | content: "cancelled by the user".to_string(), |
| 1044 | }]) |
| 1045 | .await; |
| 1046 | |
| 1047 | let history = backend.history.lock().await; |
| 1048 | let last = history.last().unwrap(); |
| 1049 | assert_eq!(last["role"], "tool"); |
| 1050 | assert_eq!(last["tool_call_id"], "call_9"); |
| 1051 | assert_eq!(last["content"], "cancelled by the user"); |
| 1052 | } |
| 1053 | |
| 1054 | #[test] |
| 1055 | fn carryover_drops_system_messages_and_keeps_the_turns() { |
| 1056 | let snapshot = vec![ |
| 1057 | serde_json::json!({ "role": "system", "content": "old prompt" }), |
| 1058 | serde_json::json!({ "role": "user", "content": "hello" }), |
| 1059 | serde_json::json!({ "role": "assistant", "content": "hi" }), |
| 1060 | ]; |
| 1061 | |
| 1062 | let carried = carryover_history(snapshot); |
| 1063 | |
| 1064 | assert_eq!(carried.len(), 2); |
| 1065 | assert_eq!(carried[0]["role"], "user"); |
| 1066 | assert_eq!(carried[1]["content"], "hi"); |
| 1067 | } |
| 1068 | |
| 1069 | #[test] |
| 1070 | fn carryover_strips_a_tool_call_that_never_got_a_result() { |
| 1071 | // Switching mid-turn: the assistant asked for a tool, nothing answered. |
| 1072 | let snapshot = vec![ |
| 1073 | serde_json::json!({ "role": "user", "content": "read a.rs" }), |
| 1074 | streamed_assistant_history( |
| 1075 | "on it", |
| 1076 | &[ToolCall { |
| 1077 | id: "call_1".to_string(), |
| 1078 | name: "read_file".to_string(), |
| 1079 | arguments: "{}".to_string(), |
| 1080 | }], |
| 1081 | ), |
| 1082 | ]; |
| 1083 | |
| 1084 | let carried = carryover_history(snapshot); |
| 1085 | |
| 1086 | assert_eq!(carried.len(), 2); |
| 1087 | assert_eq!(carried[1]["content"], "on it"); |
| 1088 | assert!( |
| 1089 | carried[1].get("tool_calls").is_none(), |
| 1090 | "an unanswered tool call must not survive the switch" |
| 1091 | ); |
| 1092 | } |
| 1093 | |
| 1094 | #[test] |
| 1095 | fn carryover_drops_a_textless_unanswered_tool_call_and_its_late_result() { |
| 1096 | let snapshot = vec![ |
| 1097 | streamed_assistant_history( |
| 1098 | "", |
| 1099 | &[ToolCall { |
| 1100 | id: "call_1".to_string(), |
| 1101 | name: "read_file".to_string(), |
| 1102 | arguments: "{}".to_string(), |
| 1103 | }], |
| 1104 | ), |
| 1105 | // An orphan: its assistant message is gone with the line above. |
| 1106 | serde_json::json!({ |
| 1107 | "role": "tool", |
| 1108 | "tool_call_id": "call_other", |
| 1109 | "content": "file contents", |
| 1110 | }), |
| 1111 | ]; |
| 1112 | |
| 1113 | assert!(carryover_history(snapshot).is_empty()); |
| 1114 | } |
| 1115 | |
| 1116 | #[test] |
| 1117 | fn carryover_keeps_an_answered_tool_call_paired_with_its_result() { |
| 1118 | let snapshot = vec![ |
| 1119 | streamed_assistant_history( |
| 1120 | "", |
| 1121 | &[ToolCall { |
| 1122 | id: "call_1".to_string(), |
| 1123 | name: "read_file".to_string(), |
| 1124 | arguments: "{}".to_string(), |
| 1125 | }], |
| 1126 | ), |
| 1127 | serde_json::json!({ |
| 1128 | "role": "tool", |
| 1129 | "tool_call_id": "call_1", |
| 1130 | "content": "file contents", |
| 1131 | }), |
| 1132 | ]; |
| 1133 | |
| 1134 | let carried = carryover_history(snapshot); |
| 1135 | |
| 1136 | assert_eq!(carried.len(), 2); |
| 1137 | assert_eq!(carried[0]["tool_calls"][0]["id"], "call_1"); |
| 1138 | assert_eq!(carried[1]["tool_call_id"], "call_1"); |
| 1139 | } |
| 1140 | |
| 1141 | #[tokio::test] |
| 1142 | async fn adopt_carryover_replays_the_thread_under_the_new_system_prompt() { |
| 1143 | let new_backend = |
| 1144 | OpenAiBackend::new("http://localhost", "", "m", Some("new prompt".into())); |
| 1145 | |
| 1146 | let carried = carryover_history(vec![ |
| 1147 | serde_json::json!({ "role": "system", "content": "old prompt" }), |
| 1148 | serde_json::json!({ "role": "user", "content": "hello" }), |
| 1149 | serde_json::json!({ "role": "assistant", "content": "hi" }), |
| 1150 | ]); |
| 1151 | adopt_carryover(&new_backend, carried).await; |
| 1152 | |
| 1153 | let history = new_backend.history_snapshot().await; |
| 1154 | assert_eq!(history.len(), 3); |
| 1155 | assert_eq!(history[0]["role"], "system"); |
| 1156 | assert_eq!(history[0]["content"], "new prompt"); |
| 1157 | assert_eq!(history[1]["content"], "hello"); |
| 1158 | assert_eq!(history[2]["content"], "hi"); |
| 1159 | } |
| 1160 | |
| 1161 | #[tokio::test] |
| 1162 | async fn adopt_carryover_leaves_a_fresh_backend_alone() { |
| 1163 | let new_backend = |
| 1164 | OpenAiBackend::new("http://localhost", "", "m", Some("new prompt".into())); |
| 1165 | |
| 1166 | adopt_carryover(&new_backend, Vec::new()).await; |
| 1167 | |
| 1168 | let history = new_backend.history_snapshot().await; |
| 1169 | assert_eq!(history.len(), 1); |
| 1170 | assert_eq!(history[0]["content"], "new prompt"); |
| 1171 | } |
| 1172 | |
| 1173 | #[test] |
| 1174 | fn estimate_tokens_scales_with_serialized_size() { |
| 1175 | assert_eq!(estimate_tokens(&[]), 0); |
| 1176 | |
| 1177 | let short = vec![serde_json::json!({ "role": "user", "content": "hi" })]; |
| 1178 | let long = vec![serde_json::json!({ "role": "user", "content": "x".repeat(4_000) })]; |
| 1179 | let short_estimate = estimate_tokens(&short); |
| 1180 | let long_estimate = estimate_tokens(&long); |
| 1181 | |
| 1182 | assert!(short_estimate > 0, "non-empty history estimates > 0 tokens"); |
| 1183 | assert!(long_estimate > short_estimate, "longer history costs more"); |
| 1184 | // 4,000 content chars / 4 ≈ 1,000 tokens, plus a little JSON framing. |
| 1185 | assert!((1_000..1_100).contains(&long_estimate), "{long_estimate}"); |
| 1186 | } |
| 1187 | |
| 1188 | #[tokio::test] |
| 1189 | async fn openai_snapshot_restore_round_trips_exactly() { |
| 1190 | let backend = OpenAiBackend::new("http://localhost", "", "m", Some("be helpful".into())); |
| 1191 | { |
| 1192 | let mut history = backend.history.lock().await; |
| 1193 | history.push(serde_json::json!({ "role": "user", "content": "hello" })); |
| 1194 | history.push(streamed_assistant_history( |
| 1195 | "", |
| 1196 | &[ToolCall { |
| 1197 | id: "call_1".to_string(), |
| 1198 | name: "read_file".to_string(), |
| 1199 | arguments: r#"{"path":"a.rs"}"#.to_string(), |
| 1200 | }], |
| 1201 | )); |
| 1202 | history.push(serde_json::json!({ |
| 1203 | "role": "tool", "tool_call_id": "call_1", "content": "fn main() {}", |
| 1204 | })); |
| 1205 | history.push(serde_json::json!({ "role": "assistant", "content": "done" })); |
| 1206 | } |
| 1207 | let snapshot = backend.history_snapshot().await; |
| 1208 | assert_eq!( |
| 1209 | snapshot[0]["role"], "system", |
| 1210 | "snapshot keeps the system message" |
| 1211 | ); |
| 1212 | |
| 1213 | // Restoring into a backend seeded with a *different* system prompt must |
| 1214 | // replace everything, including that seed. |
| 1215 | let restored = OpenAiBackend::new("http://localhost", "", "m", Some("other seed".into())); |
| 1216 | restored.restore_history(snapshot.clone()).await; |
| 1217 | assert_eq!(restored.history_snapshot().await, snapshot); |
| 1218 | } |
| 1219 | |
| 1220 | /// Minimal scripted OpenAI-compatible endpoint: accepts one HTTP request on |
| 1221 | /// a std listener and answers with a fixed non-streaming completion. |
| 1222 | fn spawn_completion_stub(summary: &str) -> std::net::SocketAddr { |
| 1223 | use std::io::{Read, Write}; |
| 1224 | |
| 1225 | let listener = std::net::TcpListener::bind("127.0.0.1:0").unwrap(); |
| 1226 | let addr = listener.local_addr().unwrap(); |
| 1227 | let body = serde_json::json!({ |
| 1228 | "choices": [{ "message": { "role": "assistant", "content": summary } }] |
| 1229 | }) |
| 1230 | .to_string(); |
| 1231 | std::thread::spawn(move || { |
| 1232 | let (mut stream, _) = listener.accept().unwrap(); |
| 1233 | // Read until the full request (headers + content-length body) is in. |
| 1234 | let mut request = Vec::new(); |
| 1235 | let mut chunk = [0u8; 4096]; |
| 1236 | loop { |
| 1237 | let n = stream.read(&mut chunk).unwrap_or(0); |
| 1238 | if n == 0 { |
| 1239 | break; |
| 1240 | } |
| 1241 | request.extend_from_slice(&chunk[..n]); |
| 1242 | if let Some(headers_end) = |
| 1243 | request.windows(4).position(|window| window == b"\r\n\r\n") |
| 1244 | { |
| 1245 | let headers = String::from_utf8_lossy(&request[..headers_end]); |
| 1246 | let content_length = headers |
| 1247 | .lines() |
| 1248 | .find_map(|line| { |
| 1249 | line.to_ascii_lowercase() |
| 1250 | .strip_prefix("content-length:") |
| 1251 | .map(|value| value.trim().parse::<usize>().unwrap_or(0)) |
| 1252 | }) |
| 1253 | .unwrap_or(0); |
| 1254 | if request.len() >= headers_end + 4 + content_length { |
| 1255 | break; |
| 1256 | } |
| 1257 | } |
| 1258 | } |
| 1259 | let response = format!( |
| 1260 | "HTTP/1.1 200 OK\r\ncontent-type: application/json\r\n\ |
| 1261 | content-length: {}\r\nconnection: close\r\n\r\n{}", |
| 1262 | body.len(), |
| 1263 | body |
| 1264 | ); |
| 1265 | let _ = stream.write_all(response.as_bytes()); |
| 1266 | }); |
| 1267 | addr |
| 1268 | } |
| 1269 | |
| 1270 | #[tokio::test] |
| 1271 | async fn compact_history_rebuilds_system_summary_and_tail() { |
| 1272 | let addr = spawn_completion_stub("We refactored backend.rs; tests pass."); |
| 1273 | let backend = OpenAiBackend::new( |
| 1274 | format!("http://{addr}/v1"), |
| 1275 | "test-key", |
| 1276 | "test-model", |
| 1277 | Some("be helpful".into()), |
| 1278 | ); |
| 1279 | { |
| 1280 | let mut history = backend.history.lock().await; |
| 1281 | for i in 0..5 { |
| 1282 | let role = if i % 2 == 0 { "user" } else { "assistant" }; |
| 1283 | history.push(serde_json::json!({ |
| 1284 | "role": role, "content": format!("message {i}"), |
| 1285 | })); |
| 1286 | } |
| 1287 | } |
| 1288 | |
| 1289 | backend.compact_history(2).await.unwrap(); |
| 1290 | |
| 1291 | let history = backend.history_snapshot().await; |
| 1292 | assert_eq!(history.len(), 4, "system + summary + last 2: {history:?}"); |
| 1293 | assert_eq!(history[0]["role"], "system"); |
| 1294 | assert_eq!(history[0]["content"], "be helpful"); |
| 1295 | assert_eq!(history[1]["role"], "user"); |
| 1296 | let summary_text = history[1]["content"].as_str().unwrap(); |
| 1297 | assert!(summary_text.starts_with("[Conversation summary]\n")); |
| 1298 | assert!(summary_text.contains("We refactored backend.rs; tests pass.")); |
| 1299 | assert_eq!( |
| 1300 | history[2], |
| 1301 | serde_json::json!({ "role": "assistant", "content": "message 3" }) |
| 1302 | ); |
| 1303 | assert_eq!( |
| 1304 | history[3], |
| 1305 | serde_json::json!({ "role": "user", "content": "message 4" }) |
| 1306 | ); |
| 1307 | } |
| 1308 | |
| 1309 | #[tokio::test] |
| 1310 | async fn compact_history_failure_leaves_history_intact() { |
| 1311 | // No listener at this address: the summarization request fails, and |
| 1312 | // history must roll back to exactly what it was. |
| 1313 | let backend = |
| 1314 | OpenAiBackend::new("http://127.0.0.1:9", "", "test-model", Some("sys".into())); |
| 1315 | backend |
| 1316 | .history |
| 1317 | .lock() |
| 1318 | .await |
| 1319 | .push(serde_json::json!({ "role": "user", "content": "hello" })); |
| 1320 | let before = backend.history_snapshot().await; |
| 1321 | |
| 1322 | assert!(backend.compact_history(2).await.is_err()); |
| 1323 | assert_eq!(backend.history_snapshot().await, before); |
| 1324 | } |
| 1325 | |
| 1326 | #[test] |
| 1327 | fn assistant_message_with_tool_calls_round_trips() { |
| 1328 | let message = ResponseMessage { |
| 1329 | content: None, |
| 1330 | tool_calls: Some(vec![ResponseToolCall { |
| 1331 | id: "call_1".to_string(), |
| 1332 | function: ResponseFunction { |
| 1333 | name: "read_file".to_string(), |
| 1334 | arguments: r#"{"path":"a.rs"}"#.to_string(), |
| 1335 | }, |
| 1336 | }]), |
| 1337 | }; |
| 1338 | let value = message.into_history_value(); |
| 1339 | assert_eq!(value["role"], "assistant"); |
| 1340 | assert!(value["content"].is_null()); |
| 1341 | assert_eq!(value["tool_calls"][0]["id"], "call_1"); |
| 1342 | assert_eq!(value["tool_calls"][0]["type"], "function"); |
| 1343 | assert_eq!(value["tool_calls"][0]["function"]["name"], "read_file"); |
| 1344 | } |
| 1345 | } |