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.
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@@ -220,7 +220,9 @@ async fn main() -> Result<()> {
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println!("Generating summary...");
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let summary = ollama.generate(&prompt, Some(system_prompt)).await?;
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let summary = ollama
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.generate(&opentelemetry::Context::new(), &prompt, Some(system_prompt))
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.await?;
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println!("\n📝 GENERATED SUMMARY:");
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println!("─────────────────────────────────────────");
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@@ -236,7 +238,9 @@ async fn main() -> Result<()> {
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);
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println!("\nGenerating embedding...");
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let embedding = ollama.generate_embedding(&stripped).await?;
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let embedding = ollama
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.generate_embedding(&opentelemetry::Context::new(), &stripped)
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.await?;
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println!("✓ Embedding generated ({} dimensions)", embedding.len());
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println!("Saving to database...");
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