Tracing: LLM clients + streaming spans on tracing, drop cx threading (#140)

LlmClient methods no longer take an OpenTelemetry Context. llm.request is
now a tracing span (otel.kind=client, llm.provider/operation/model) that
parents on the caller's ambient span; traceparent injection reads the
span's OTel context via OpenTelemetrySpanExt.

The src/ai feature spans (handlers, insight generation, chat, persona
chat, daily summaries, TTS) move to #[instrument] / info_span!, and every
LLM-bearing tokio::spawn carries its parent span with .instrument(): the
streaming chat turn (chat_turn_stream_inner), async chat / persona turns,
background insight jobs and TTS jobs. Sub-spans in the agentic loops
(ai.chat.loop, ai.agentic.loop) instrument each LLM / tool await.

DAO calls keep their explicit Context (derived from the tracing span)
until the DAO migration (#141).

tests/otel_llm_spans.rs pins nesting + traceparent for the blocking and
streaming paths across a spawn on a multi-thread runtime.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

src/ai/mod.rs

@@ -115,26 +115,24 @@ fn embed_prefix(key: &str) -> String {
 /// `Instruct: <task>\nQuery: `. Must pair with the document prefix the
 /// corpus was embedded with or similarity degrades.
 pub async fn embed_query(
-    cx: &opentelemetry::Context,
     ollama: &OllamaClient,
     llamacpp: Option<&LlamaCppClient>,
     text: &str,
 ) -> anyhow::Result<Vec<f32>> {
     let prefixed = format!("{}{}", embed_prefix("EMBED_QUERY_PREFIX"), text);
-    embed_one(cx, ollama, llamacpp, &prefixed).await
+    embed_one(ollama, llamacpp, &prefixed).await
 }
 
 /// Embed corpus text (the stored side of retrieval). Applies
 /// `EMBED_DOCUMENT_PREFIX` (default empty; nomic v1.5 wants
 /// `search_document: `, Qwen3-Embedding wants none).
 pub async fn embed_document(
-    cx: &opentelemetry::Context,
     ollama: &OllamaClient,
     llamacpp: Option<&LlamaCppClient>,
     text: &str,
 ) -> anyhow::Result<Vec<f32>> {
     let prefixed = format!("{}{}", embed_prefix("EMBED_DOCUMENT_PREFIX"), text);
-    embed_one(cx, ollama, llamacpp, &prefixed).await
+    embed_one(ollama, llamacpp, &prefixed).await
 }
 
 /// Embed a batch of strings via the configured local backend. Routes
@@ -142,32 +140,30 @@ pub async fn embed_document(
 /// configured), else Ollama. See [`local_backend_is_llamacpp`] for the
 /// rationale on consistency.
 pub async fn embed_many(
-    cx: &opentelemetry::Context,
     ollama: &OllamaClient,
     llamacpp: Option<&LlamaCppClient>,
     texts: &[&str],
 ) -> anyhow::Result<Vec<Vec<f32>>> {
     if local_backend_is_llamacpp() {
         if let Some(lc) = llamacpp {
-            return <LlamaCppClient as LlmClient>::generate_embeddings(lc, cx, texts).await;
+            return <LlamaCppClient as LlmClient>::generate_embeddings(lc, texts).await;
         }
         anyhow::bail!(
             "LLM_BACKEND=llamacpp but LlamaCppClient is unconfigured — \
              set LLAMA_SWAP_URL or switch to LLM_BACKEND=ollama"
         );
     }
-    ollama.generate_embeddings(cx, texts).await
+    ollama.generate_embeddings(texts).await
 }
 
 /// Embed one string via the configured local backend. Single-text
 /// convenience over [`embed_many`].
 pub async fn embed_one(
-    cx: &opentelemetry::Context,
     ollama: &OllamaClient,
     llamacpp: Option<&LlamaCppClient>,
     text: &str,
 ) -> anyhow::Result<Vec<f32>> {
-    let mut vecs = embed_many(cx, ollama, llamacpp, &[text]).await?;
+    let mut vecs = embed_many(ollama, llamacpp, &[text]).await?;
     vecs.pop()
         .ok_or_else(|| anyhow::anyhow!("embedding backend returned no embeddings"))
 }