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harness_loop/
telemetry.rs

1//! `TelemetryHook` — maps the agent's lifecycle [`Event`] stream onto
2//! structured `tracing` spans and events, so a run becomes observable in any
3//! `tracing` subscriber.
4//!
5//! Why `tracing` and not a hard OpenTelemetry dependency? Because `tracing` is
6//! the idiomatic Rust instrumentation seam: the library emits spans + events,
7//! and the *binary* chooses the exporter. Attach
8//! [`tracing-opentelemetry`](https://docs.rs/tracing-opentelemetry) with an
9//! OTLP pipeline and every span below is exported to Jaeger / Tempo / any OTLP
10//! backend with **zero changes here**; attach `tracing_subscriber::fmt().json()`
11//! and you get newline-delimited JSON for log pipelines. One instrumentation,
12//! many backends.
13//!
14//! Field names follow the OpenTelemetry **GenAI semantic conventions**
15//! (`gen_ai.*`), so any OTel-aware backend — Logfire, SigNoz, Langfuse via OTLP,
16//! Grafana — recognizes token counts, model, and finish reason automatically and
17//! computes cost/latency with zero mapping. The pre-convention flat names
18//! (`input_tokens`, `tool`, …) are kept alongside as aliases for existing
19//! consumers.
20//!
21//! Span/event shape (target `harness.telemetry`):
22//!
23//! ```text
24//! agent_run (span, fields: source, gen_ai.operation.name=invoke_agent)
25//!   ├─ run.start
26//!   ├─ iter            (iter)
27//!   ├─ model.complete  (gen_ai.operation.name=chat,
28//!   │                   gen_ai.usage.input_tokens, gen_ai.usage.output_tokens,
29//!   │                   gen_ai.usage.cached_input_tokens,
30//!   │                   gen_ai.response.finish_reasons
31//!   │                   + aliases: input_tokens, output_tokens,
32//!   │                     cached_input_tokens, tool_calls, stop)
33//!   ├─ tool.call       (gen_ai.operation.name=execute_tool, gen_ai.tool.name,
34//!   │                   ok, duration_ms + alias: tool)
35//!   ├─ sensor          (sensor, signals)
36//!   ├─ compact         (stage, tokens_before, tokens_after, tokens_saved)
37//!   ├─ budget.warning  (ratio)
38//!   └─ run.end         (gen_ai.usage.*, total_tokens, model_calls, tool_calls,
39//!                       tool_failures, compactions, tokens_saved, duration_ms)
40//! ```
41//!
42//! To export over OTLP, enable the crate's `otel` feature and call
43//! [`crate::otel::init_tracing_with_otlp`] from your binary; see that module.
44//!
45//! Wire it like any hook:
46//! ```ignore
47//! let loop_ = AgentLoop::new(model).with_hook(std::sync::Arc::new(TelemetryHook::new()));
48//! ```
49
50use harness_core::{Event, Hook, HookOutcome, World};
51use std::collections::HashMap;
52use std::sync::Mutex;
53use std::time::Instant;
54
55/// Emits a span per run and a structured event per model call, tool call,
56/// sensor, compaction, and budget warning. See the module docs for the OTLP
57/// bridge.
58pub struct TelemetryHook {
59    /// The current run's span. Events are recorded inside it so an OTLP exporter
60    /// nests them under one trace.
61    run: Mutex<Option<tracing::Span>>,
62    /// `call_id -> dispatch start`, so `tool.call` can report a duration.
63    tool_starts: Mutex<HashMap<String, Instant>>,
64    /// When the current model call was handed off, so the run summary can say
65    /// how much of the wall clock was spent waiting on the provider.
66    model_start: Mutex<Option<Instant>>,
67    /// True until the current streamed call produces its first fragment — the
68    /// latency a person actually experiences, as distinct from how long the
69    /// whole answer took.
70    awaiting_first_token: Mutex<bool>,
71    /// Running totals for the whole run, so `run.end` can answer "what did this
72    /// cost?" without the reader summing per-turn lines by hand.
73    totals: Mutex<RunTotals>,
74}
75
76/// What a run added up to, accumulated across its turns.
77#[derive(Default)]
78struct RunTotals {
79    started: Option<Instant>,
80    input_tokens: u64,
81    output_tokens: u64,
82    cached_input_tokens: u64,
83    cache_write_input_tokens: u64,
84    model_calls: u64,
85    tool_calls: u64,
86    tool_failures: u64,
87    compactions: u64,
88    tokens_saved: u64,
89    /// Wall-clock spent inside model calls, and the summed duration of tool
90    /// calls. Tools dispatched in parallel overlap, so `tool_ms` can exceed the
91    /// wall clock it occupied — it is a cost, not a span.
92    model_ms: u64,
93    tool_ms: u64,
94    /// Read-only calls that exactly repeated an earlier one — wasted rounds the
95    /// stuck-detector cannot see, because they are not consecutive.
96    repeats: u64,
97    /// Time to the first streamed fragment of the run's first model call: what
98    /// the person watching waited before anything appeared. Zero when the run
99    /// did not stream.
100    first_token_ms: u64,
101}
102
103impl TelemetryHook {
104    pub fn new() -> Self {
105        Self {
106            run: Mutex::new(None),
107            tool_starts: Mutex::new(HashMap::new()),
108            model_start: Mutex::new(None),
109            awaiting_first_token: Mutex::new(false),
110            totals: Mutex::new(RunTotals::default()),
111        }
112    }
113
114    /// Run `f` inside the current run span (if any), so its events attach to the
115    /// run's trace. Falls back to the ambient subscriber if no run is active.
116    fn in_run<F: FnOnce()>(&self, f: F) {
117        let guard = self.run.lock().unwrap();
118        match &*guard {
119            Some(span) => span.in_scope(f),
120            None => f(),
121        }
122    }
123}
124
125impl Default for TelemetryHook {
126    fn default() -> Self {
127        Self::new()
128    }
129}
130
131impl Hook for TelemetryHook {
132    fn name(&self) -> &str {
133        "telemetry"
134    }
135    fn matches(&self, _ev: &Event<'_>) -> bool {
136        true
137    }
138
139    fn fire(&self, ev: &Event<'_>, _world: &mut World) -> HookOutcome {
140        match ev {
141            Event::SessionStart { source } => {
142                let span = tracing::info_span!(
143                    target: "harness.telemetry",
144                    "agent_run",
145                    "gen_ai.operation.name" = "invoke_agent",
146                    source = format!("{source:?}")
147                );
148                span.in_scope(|| {
149                    tracing::info!(target: "harness.telemetry", event = "run.start");
150                });
151                *self.run.lock().unwrap() = Some(span);
152                *self.totals.lock().unwrap() = RunTotals {
153                    started: Some(Instant::now()),
154                    ..Default::default()
155                };
156            }
157            Event::PreModel { .. } => {
158                *self.model_start.lock().unwrap() = Some(Instant::now());
159                *self.awaiting_first_token.lock().unwrap() = true;
160            }
161            Event::ModelTokenDelta { .. } => {
162                // Only the first fragment of each call; the rest are noise.
163                let mut awaiting = self.awaiting_first_token.lock().unwrap();
164                if !*awaiting {
165                    return HookOutcome::Allow;
166                }
167                *awaiting = false;
168                drop(awaiting);
169                let ttft = self
170                    .model_start
171                    .lock()
172                    .unwrap()
173                    .map(|s| s.elapsed().as_millis() as u64)
174                    .unwrap_or(0);
175                {
176                    let mut t = self.totals.lock().unwrap();
177                    // The first call's figure is the one a person felt; later
178                    // calls are the agent thinking, not the answer starting.
179                    if t.first_token_ms == 0 {
180                        t.first_token_ms = ttft;
181                    }
182                }
183                self.in_run(|| {
184                    tracing::info!(
185                        target: "harness.telemetry",
186                        event = "model.first_token",
187                        ttft_ms = ttft,
188                    );
189                });
190            }
191            Event::Heartbeat { iter } => self.in_run(|| {
192                tracing::info!(target: "harness.telemetry", event = "iter", iter = *iter);
193            }),
194            Event::PostModel { out } => self.in_run(|| {
195                let waited = self
196                    .model_start
197                    .lock()
198                    .unwrap()
199                    .take()
200                    .map(|s| s.elapsed().as_millis() as u64)
201                    .unwrap_or(0);
202                {
203                    let mut t = self.totals.lock().unwrap();
204                    t.model_calls += 1;
205                    t.model_ms += waited;
206                    t.input_tokens += out.usage.input_tokens as u64;
207                    t.output_tokens += out.usage.output_tokens as u64;
208                    t.cached_input_tokens += out.usage.cached_input_tokens as u64;
209                    t.cache_write_input_tokens += out.usage.cache_write_input_tokens as u64;
210                }
211                let stop = format!("{:?}", out.stop_reason);
212                tracing::info!(
213                    target: "harness.telemetry",
214                    event = "model.complete",
215                    // OTel GenAI semantic conventions:
216                    "gen_ai.operation.name" = "chat",
217                    "gen_ai.usage.input_tokens" = out.usage.input_tokens,
218                    "gen_ai.usage.output_tokens" = out.usage.output_tokens,
219                    "gen_ai.usage.cached_input_tokens" = out.usage.cached_input_tokens,
220                    "gen_ai.usage.cache_write_input_tokens" = out.usage.cache_write_input_tokens,
221                    "gen_ai.response.finish_reasons" = %stop,
222                    // pre-convention aliases:
223                    input_tokens = out.usage.input_tokens,
224                    output_tokens = out.usage.output_tokens,
225                    cached_input_tokens = out.usage.cached_input_tokens,
226                    cache_write_input_tokens = out.usage.cache_write_input_tokens,
227                    tool_calls = out.tool_calls.len(),
228                    stop = %stop,
229                    duration_ms = waited,
230                );
231            }),
232            Event::PreToolUse { action } => {
233                self.tool_starts
234                    .lock()
235                    .unwrap()
236                    .insert(action.call_id.clone(), Instant::now());
237            }
238            Event::PostToolUse { action, result } => {
239                let duration_ms = self
240                    .tool_starts
241                    .lock()
242                    .unwrap()
243                    .remove(&action.call_id)
244                    .map(|s| s.elapsed().as_millis() as u64)
245                    .unwrap_or(0);
246                let repeat = result
247                    .content
248                    .get("repeat_of_earlier_call")
249                    .and_then(|v| v.as_bool())
250                    .unwrap_or(false);
251                {
252                    let mut t = self.totals.lock().unwrap();
253                    t.tool_calls += 1;
254                    t.tool_ms += duration_ms;
255                    if repeat {
256                        t.repeats += 1;
257                    }
258                    if !result.ok {
259                        t.tool_failures += 1;
260                    }
261                }
262                self.in_run(|| {
263                    tracing::info!(
264                        target: "harness.telemetry",
265                        event = "tool.call",
266                        "gen_ai.operation.name" = "execute_tool",
267                        "gen_ai.tool.name" = %action.tool,
268                        ok = result.ok,
269                        duration_ms,
270                        tool = %action.tool, // alias
271                    );
272                });
273            }
274            Event::PostSensor { sensor, signals } => self.in_run(|| {
275                tracing::debug!(
276                    target: "harness.telemetry",
277                    event = "sensor",
278                    sensor = %sensor,
279                    signals = signals.len(),
280                );
281            }),
282            Event::PostCompact {
283                stage,
284                before,
285                after,
286            } => self.in_run(|| {
287                let saved = before.saturating_sub(*after);
288                {
289                    let mut t = self.totals.lock().unwrap();
290                    t.compactions += 1;
291                    t.tokens_saved += saved as u64;
292                }
293                // At info, not debug: compaction is what keeps a long run
294                // affordable, and "it ran" without "it saved 12k" is not an
295                // observation anyone can act on.
296                tracing::info!(
297                    target: "harness.telemetry",
298                    event = "compact",
299                    stage = format!("{stage:?}"),
300                    tokens_before = *before,
301                    tokens_after = *after,
302                    tokens_saved = saved,
303                );
304            }),
305            Event::BudgetWarning { ratio } => self.in_run(|| {
306                tracing::warn!(
307                    target: "harness.telemetry",
308                    event = "budget.warning",
309                    ratio = *ratio,
310                );
311            }),
312            Event::SessionEnd => {
313                let t = std::mem::take(&mut *self.totals.lock().unwrap());
314                self.in_run(|| {
315                    // One line with the whole bill. Per-turn events answer "what
316                    // happened"; this answers "what did it cost", which is the
317                    // question asked after every run and previously required
318                    // adding the turns up by hand.
319                    tracing::info!(
320                        target: "harness.telemetry",
321                        event = "run.end",
322                        "gen_ai.usage.input_tokens" = t.input_tokens,
323                        "gen_ai.usage.output_tokens" = t.output_tokens,
324                        "gen_ai.usage.cached_input_tokens" = t.cached_input_tokens,
325                        "gen_ai.usage.cache_write_input_tokens" = t.cache_write_input_tokens,
326                        total_tokens = t.input_tokens + t.output_tokens,
327                        model_calls = t.model_calls,
328                        tool_calls = t.tool_calls,
329                        tool_failures = t.tool_failures,
330                        compactions = t.compactions,
331                        tokens_saved = t.tokens_saved,
332                        model_ms = t.model_ms,
333                        tool_ms = t.tool_ms,
334                        repeat_calls = t.repeats,
335                        first_token_ms = t.first_token_ms,
336                        duration_ms = t.started.map(|s| s.elapsed().as_millis() as u64).unwrap_or(0),
337                    );
338                });
339                *self.run.lock().unwrap() = None;
340            }
341            _ => {}
342        }
343        HookOutcome::Allow
344    }
345}