Otel: llm.request client spans + traceparent on LLM calls (#130)

Add OpenTelemetry tracing to every LLM client call so an insight/chat
turn is a single trace from HTTP entry to each downstream inference.

- LlmClient trait: thread a &opentelemetry::Context through all 5
  methods (generate, chat_with_tools, chat_with_tools_stream,
  generate_embeddings, describe_image), matching the DAO convention of
  explicit context threading rather than ambient Context::current().
- otel::start_llm_request_span: single shared helper that every
  provider (openrouter / llamacpp / ollama) funnels through, so the
  span shape is identical: name llm.request, SpanKind::Client,
  llm.provider / llm.operation / llm.model.
- Per-method spans in all three clients with the spec's operation enum
  (chat | chat_stream | embeddings | describe_image | generate); stream
  spans are owned and moved into the async_stream generator so they end
  when the response drains, not when headers arrive.
- llm.tokens.input / llm.tokens.output recorded on non-stream and
  stream completion; llm.cost_usd from usage.cost (OpenRouter);
  http.status_code + error status on failure.
- W3C traceparent injected on outgoing LLM HTTP requests (llama-swap,
  Ollama, OpenRouter) gated on span_context.is_valid() so debug
  no-op-tracer builds don't send an all-zero parent.
- Turn-level spans (ai.chat.turn.execute, ai.persona_chat.turn.execute)
  now carry llm.backend + llm.model; with_entry streaming paths thread
  the turn context (turn_cx) to child describe_image / agentic-loop
  calls instead of the ambient context.

clippy clean; 690 lib + 775 integration + 4 doc tests green.

src/ai/persona_chat.rs

@@ -26,7 +26,7 @@ use actix_web::{HttpRequest, HttpResponse, Responder, delete, get, post, web};
 use anyhow::{Context, Result, anyhow, bail};
 use chrono::Utc;
 use opentelemetry::KeyValue;
-use opentelemetry::trace::{Span, Status, Tracer};
+use opentelemetry::trace::{Span, Status, TraceContextExt, Tracer};
 use serde::{Deserialize, Serialize};
 use std::collections::HashMap;
 use std::sync::{Arc, Mutex as StdMutex};
@@ -685,6 +685,7 @@ impl PersonaChatSession {
                     entry_clone.clone(),
                     user_id,
                     library_id,
+                    &mut span,
                 )
                 .await;
             match result {
@@ -721,6 +722,7 @@ impl PersonaChatSession {
         entry: Arc<TurnEntry>,
         user_id: i32,
         _library_id: i32,
+        turn_span: &mut opentelemetry::global::BoxedSpan,
     ) -> Result<()> {
         // Per-conversation mutex — serializes this turn against a
         // concurrent rewind or branch switch on the same transcript.
@@ -808,6 +810,12 @@ impl PersonaChatSession {
             .resolve_backend(backend_kind, &overrides)
             .await?;
         let model_used = backend.model().to_string();
+        // llm.* attributes on the turn-level span (issue #130), plus the
+        // parent context for the child llm.request spans.
+        turn_span.set_attribute(KeyValue::new("llm.backend", backend.kind.as_str()));
+        turn_span.set_attribute(KeyValue::new("llm.model", model_used.clone()));
+        let turn_cx = opentelemetry::Context::new()
+            .with_remote_span_context(turn_span.span_context().clone());
 
         // Build a no-photo tool catalog. `current_gate_opts_for_persona`
         // already probes each tool's backing table for presence and
@@ -874,6 +882,7 @@ impl PersonaChatSession {
             &persona.persona_id,
             max_iterations,
             &entry,
+            &turn_cx,
         )
         .await
         .map_err(|e| anyhow!("persona chat loop failed: {e:?}"))?;
@@ -942,7 +951,7 @@ impl PersonaChatSession {
         // list falls back to the persona name while the title is empty.
         if needs_title {
             let title = self
-                .generate_title(&backend, &messages)
+                .generate_title(&backend, &messages, &turn_cx)
                 .await
                 .unwrap_or_else(|| fallback_title(&messages));
             if !title.is_empty() {
@@ -1047,6 +1056,7 @@ impl PersonaChatSession {
         &self,
         backend: &crate::ai::backend::ResolvedBackend,
         messages: &[ChatMessage],
+        cx: &opentelemetry::Context,
     ) -> Option<String> {
         let user_message = messages.iter().find(|m| m.role == "user")?;
         // The last assistant message with actual prose — earlier ones may be
@@ -1057,7 +1067,7 @@ impl PersonaChatSession {
             .find(|m| m.role == "assistant" && !m.content.trim().is_empty())?;
 
         let prompt = title_prompt(&user_message.content, &reply.content);
-        match backend.chat().generate(&prompt, None, None).await {
+        match backend.chat().generate(cx, &prompt, None, None).await {
             Ok(raw) => {
                 let title = sanitize_title(&crate::ai::llm_client::strip_think_blocks(&raw));
                 if title.is_empty() { None } else { Some(title) }