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/daily_summary_job.rs

@@ -360,11 +360,17 @@ async fn generate_and_store_daily_summary(
     span.set_attribute(KeyValue::new("date", date.to_string()));
     span.set_attribute(KeyValue::new("contact", contact.to_string()));
     span.set_attribute(KeyValue::new("message_count", messages.len() as i64));
+    // Parent context for the child llm.request spans; the span itself stays
+    // borrowed here for the attribute updates below.
+    let llm_cx =
+        opentelemetry::Context::new().with_remote_span_context(span.span_context().clone());
 
     let (prompt, system_prompt) = build_daily_summary_prompt(contact, date, messages);
 
     // Generate summary with LLM
-    let summary = ollama.generate(&prompt, Some(system_prompt)).await?;
+    let summary = ollama
+        .generate(&llm_cx, &prompt, Some(system_prompt))
+        .await?;
 
     log::debug!(
         "Generated summary for {}: {}",
@@ -382,7 +388,9 @@ async fn generate_and_store_daily_summary(
     );
 
     // Embed the stripped summary (store original summary in DB)
-    let embedding = ollama.generate_embedding(&stripped_summary).await?;
+    let embedding = ollama
+        .generate_embedding(&llm_cx, &stripped_summary)
+        .await?;
 
     span.set_attribute(KeyValue::new(
         "embedding_dimensions",