Author SHA1 Message Date
Cameron CordesandClaude Opus 5.5 e754e149d7 parity(#143): post-migration span capture + diff vs #137 baseline
Captured from feature/tracing-migration f510940 (rebased on master 8284509),
same Jaeger / request set / DB snapshot procedure as pre-migration. Result:
names + semantic attributes preserved, traceparent intact, no orphaned spans,
async/streaming paths now single traces. See post-migration/README.md.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-29 17:29:31 -04:00
cameron 73523c6796 baseline(#137): pre-migration OTel span capture from da3901c
Raw Jaeger trace dumps (with and without incoming traceparent) plus a
derived span inventory and README describing the pre-migration span shape.
Captured from master da3901c release build against a local Jaeger; see
docs/tracing-baseline/pre-migration/README.md for the procedure and the
single span-neutral deviation (aux listen port 8088->18088).

Artifact branch only; /docs/* is gitignored, files force-added deliberately.
2026-09-29 13:57:05 -04:00
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# Post-migration span capture + parity diff (ticket #143, map #135)
The "after" counterpart of `../pre-migration/` (#137). It is captured the same
way, against the same local Jaeger, with the same request set, and diffed
against `../pre-migration/span-inventory.json`.
## What was run
- **Revision:** `feature/tracing-migration` @ `f510940`, rebased onto master
`8284509` (dev/e2e server). Release build. No source patch was needed:
master's `LOCAL_BIND_URL=` disables the secondary `:8088` listener.
- **Exporter:** the same local Jaeger all-in-one (OTLP/gRPC `:14317`). Traces
were filtered by capture start time, because the container still holds the
baseline traces.
- **DB:** a fresh `.backup` of the live `auth.db` (21,298 `image_exif` rows,
4 libraries, max job id 379, so the agentic job is again **380**). Output
dirs point at temp. `REEL_PREGEN_ENABLED=0`, `REEL_CACHE_SWEEP_ENABLED=0`.
- **LLM:** the live local stack (`LLM_BACKEND=llamacpp`,
`qwen3.8-27b-abliterated`).
- **Requests:** the baseline table, replayed by `replay.sh`: photos, memories,
agentic (202, polled to `completed`), chat stream (87 deltas + `done`), and
the `traceparent: 00-1111…-2222…-01` probe.
Two captures were taken. Run 1 found two gaps, which are fixed in `f510940`
(see "Gaps found and fixed"). Run 2, the files here, is the capture of record.
## Parity result
| Check | Before (#137) | After | Verdict |
|---|---|---|---|
| Operation names | — | every baseline op present (`find_relevant_events_hybrid` is a model-chosen tool; run 1 hit it, run 2 didn't) | ✅ preserved |
| Attribute keys (semantic) | per `pre-migration/span-inventory.json` | **identical** for every common op (`list_photos`' ~27 request attrs, `ai.insight.generate_agentic`, `ai.rag.*`, `generate_video_thumbnail`, `db.*`, `llm.request`) | ✅ preserved |
| `llm.request` | kind=client; `llm.model` / `llm.provider` / `llm.operation` / `llm.tokens.*` / `http.status_code` | same, on all 12 LLM spans | ✅ |
| `llm.backend` | absent from every baseline span (it lives on the async-turn path, which neither capture exercises) | same | ✅ no loss |
| Incoming `traceparent` | `list_photos` CHILD_OF remote `2222…` in trace `1111…` | the `GET /photos` root span is CHILD_OF remote `2222…`, with `list_photos` + DB spans under it, all in trace `1111…` | ✅ intact |
| DB span nesting | most DB spans were single-span traces | **no DB span is a root**; each nests under its request / feature / job span | ✅ fixed |
| Agentic 202 → background | two traces (`948d2756…` / `9b520713…`) | one 52-span trace: `POST …/agentic` → `http.insights.generate_agentic` → `ai.insight.generate_agentic` → `ai.agentic.loop` → `llm.request` / `ai.rag.*` / DB | ✅ fixed |
| Streaming chat | fragmented, no handler span | one trace: `POST /insights/chat/stream` → `ai.chat.turn.stream` → `llm.request (chat_stream)` + DB | ✅ fixed |
| Thumbnail sweep | 222 `generate_video_thumbnail` in 1 trace | 414 in 1 trace, all with one parent (the `creating thumbnails` root, still open when capture stopped) | ✅ |
**Roots in the after capture:** only request roots (`GET /photos`,
`GET /memories`, `POST …/agentic`, `POST /insights/chat/stream`,
`GET /insights/generation/status`) and the background root
`watcher.initial_probe`. **No orphans.**
## Intentional changes (vs baseline)
- **New per-request root spans** (`GET /photos`, …) from `tracing-actix-web`
(#139). Operation spans (`list_photos`, …) now sit one level under them.
- **New spans:** `ai.chat.turn.stream` (#140), `watcher.initial_probe` and the
other job roots (#142); `db.query.get_job_by_id` shows up because the
replay now polls job status.
- **DB tracer scope:** `db` → `image-server`. DB spans come from the
subscriber's tracer (#141). The span names and `db.*` attributes are unchanged.
- **Extra per-span metadata** from tracing-opentelemetry, excluded from the key
diff above: `code.file.path` / `code.line.number` / `code.module.name`,
`thread.id` / `thread.name`, `target`, `busy_ns` / `idle_ns`.
- **Removed:** the zero-length `file write` span in `upload_image` (#141). It
wasn't exercised by either capture.
## Gaps found and fixed (run 1 → `f510940`)
1. **Agentic background still split off.** Both insight handlers run the
generation in a nested `tokio::task::spawn` (for panic isolation) that
wasn't instrumented, so `ai.insight.generate_agentic` was a root.
2. **Watcher boot probe.** `count_for_library` ran before the first tick span,
leaving 4 root DB spans. It now runs under `watcher.initial_probe`.
## Files
- `traces.json` — Jaeger `/api/traces` dump for run 2.
- `span-inventory.json` — the baseline's schema, plus `parents` / `root_count`.
- `diff-report.txt` — the full `analyze.py` output (before/after diff, roots,
ancestry chains, traceparent chain, per-`llm.request` attributes).
- `analyze.py`, `replay.sh` — reproduce with
`python3 analyze.py <dir-with traces-after.json + inventory-before.json>`.
## Full suite on `f510940`
`cargo build` ✅, `cargo clippy --all-targets` 0 warnings ✅, `cargo fmt --check` ✅,
`cargo test` ✅ (690 lib + 775 integration + 5 OTel regression + 4 doc).
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"""#143 parity analysis: after-capture Jaeger dump vs the #137 baseline.
Writes span-inventory.json (baseline schema + nesting columns) and prints a
before/after diff plus targeted nesting / propagation checks.
"""
import json
import sys
from collections import defaultdict
W = sys.argv[1]
after = json.load(open(f"{W}/traces-after.json"))["data"]
before_inv = {r["operation"]: r for r in json.load(open(f"{W}/inventory-before.json"))}
# Attributes tracing-opentelemetry adds to every span (location / thread /
# timing metadata). Reported separately so the diff shows semantic changes.
TRACING_EXTRAS = {
"busy_ns", "idle_ns", "target", "thread.id", "thread.name",
"code.file.path", "code.line.number", "code.module.name",
}
# Spans produced by my auth probes, not by the baseline request set.
PROBE_NOISE = set()
spans = {}
by_trace = defaultdict(list)
for t in after:
for s in t["spans"]:
s["_tags"] = {kv["key"]: kv["value"] for kv in s["tags"]}
spans[s["spanID"]] = s
by_trace[s["traceID"]].append(s)
def parent(s):
for r in s.get("references", []):
if r["refType"] == "CHILD_OF":
return r["spanID"], r["traceID"]
return None, None
def op(sid):
return spans[sid]["operationName"] if sid in spans else None
# Inventory in the baseline's schema, plus nesting columns.
inv = defaultdict(lambda: {"span_count": 0, "traces": set(), "kinds": set(), "scopes": set(),
"statuses": set(), "keys": set(), "parents": defaultdict(int),
"orphans": 0})
for s in spans.values():
r = inv[s["operationName"]]
r["span_count"] += 1
r["traces"].add(s["traceID"])
r["kinds"].add(s["_tags"].get("span.kind", "internal"))
r["scopes"].add(s["_tags"].get("otel.scope.name", "?"))
r["statuses"].add(s["_tags"].get("otel.status_code", "(none)"))
r["keys"].update(s["_tags"])
pid, _ = parent(s)
if pid is None:
r["orphans"] += 1
else:
r["parents"][op(pid) or "(remote)"] += 1
inventory = []
for name, r in sorted(inv.items(), key=lambda kv: -kv[1]["span_count"]):
inventory.append({
"operation": name,
"span_count": r["span_count"],
"trace_count": len(r["traces"]),
"kind": "/".join(sorted(r["kinds"])),
"scope": "/".join(sorted(r["scopes"])),
"status": "/".join(sorted(r["statuses"])),
"attribute_keys": sorted(r["keys"] - TRACING_EXTRAS),
"parents": dict(r["parents"]),
"root_count": r["orphans"],
})
json.dump(inventory, open(f"{W}/span-inventory.json", "w"), indent=2)
print("== Operations: before -> after ==")
before_ops, after_ops = set(before_inv), set(inv)
print("only before:", sorted(before_ops - after_ops))
print("only after: ", sorted(after_ops - before_ops))
print()
print("== Common operations: kind / scope / attribute-key changes ==")
for name in sorted(before_ops & after_ops):
b, a = before_inv[name], next(x for x in inventory if x["operation"] == name)
bk, ak = set(b["attribute_keys"]), set(a["attribute_keys"])
changes = []
if b["kind"] != a["kind"]:
changes.append(f"kind {b['kind']}->{a['kind']}")
if b["scope"] != a["scope"]:
changes.append(f"scope {b['scope']}->{a['scope']}")
if bk - ak:
changes.append(f"LOST {sorted(bk - ak)}")
if ak - bk:
changes.append(f"added {sorted(ak - bk)}")
nest = f"traces {b['trace_count']}/{b['span_count']} -> {a['trace_count']}/{a['span_count']}, roots={a['root_count']}"
print(f"{name}: {'; '.join(changes) or 'same'} | {nest}")
print()
print("== Roots in the after capture (span with no parent) ==")
for s in spans.values():
if parent(s)[0] is None:
print(f" {s['operationName']} trace={s['traceID'][:8]} spans_in_trace={len(by_trace[s['traceID']])}")
def chain(s):
out = [s["operationName"]]
pid, _ = parent(s)
while pid:
if pid not in spans:
out.append(f"(remote {pid})")
break
out.append(spans[pid]["operationName"])
pid, _ = parent(spans[pid])
return " <- ".join(out)
print()
print("== Ancestry of key spans ==")
seen = set()
for s in spans.values():
n = s["operationName"]
key = (n, s["_tags"].get("llm.operation"))
if n in ("llm.request", "ai.agentic.loop", "ai.insight.generate_agentic",
"db.insert.store_insight", "db.update.update_training_messages",
"ai.chat.turn.stream", "list_photos", "list_memories",
"generate_video_thumbnail") and key not in seen:
seen.add(key)
extra = f" [llm.operation={key[1]}]" if key[1] else ""
print(f" {chain(s)}{extra}")
print()
print("== traceparent probe ==")
probe = [s for s in spans.values() if s["traceID"].startswith("11111111")]
for s in sorted(probe, key=lambda s: s["startTime"]):
print(f" {chain(s)} trace={s['traceID']}")
print()
print("== llm.request attribute presence ==")
for s in spans.values():
if s["operationName"] == "llm.request":
t = s["_tags"]
print(f" op={t.get('llm.operation')} model={t.get('llm.model')} provider={t.get('llm.provider')} "
f"status={t.get('http.status_code')} tokens_in={t.get('llm.tokens.input')} "
f"parent={op(parent(s)[0])}")
print()
print("== turn / insight spans: llm.backend + llm.model ==")
for s in spans.values():
if s["operationName"] in ("ai.chat.turn.stream", "ai.insight.generate_agentic"):
t = s["_tags"]
print(f" {s['operationName']}: llm.backend={t.get('llm.backend')} llm.model={t.get('llm.model')} backend={t.get('backend')} model={t.get('model')}")
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== Operations: before -> after ==
only before: ['db.query.find_relevant_events_hybrid']
only after: ['GET /insights/generation/status', 'GET /memories', 'GET /photos', 'POST /insights/chat/stream', 'POST /insights/generate/agentic', 'ai.chat.turn.stream', 'db.query.get_job_by_id', 'watcher.initial_probe']
== Common operations: kind / scope / attribute-key changes ==
ai.agentic.loop: same | traces 1/1 -> 1/1, roots=0
ai.insight.generate_agentic: same | traces 1/1 -> 1/1, roots=0
ai.rag.search_daily_summaries: same | traces 1/1 -> 1/2, roots=0
db.insert.create_job: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.insert.store_insight: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.insert.upsert_entity: scope db->image-server | traces 1/2 -> 1/3, roots=0
db.insert.upsert_fact: scope db->image-server | traces 1/1 -> 1/2, roots=0
db.insert.upsert_photo_link: scope db->image-server | traces 1/1 -> 1/2, roots=0
db.query.count_for_library: scope db->image-server | traces 4/4 -> 1/4, roots=0
db.query.faces_for_hash: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.query.find_similar_summaries_with_time_weight: scope db->image-server | traces 1/1 -> 1/2, roots=0
db.query.get_active_job: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.query.get_current_insight_for_library: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.query.get_event_count: scope db->image-server | traces 2/2 -> 2/2, roots=0
db.query.get_exif: scope db->image-server | traces 2/2 -> 1/3, roots=0
db.query.get_links_for_photo: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.query.get_location_count: scope db->image-server | traces 2/2 -> 2/2, roots=0
db.query.get_memories_in_window: scope db->image-server | traces 1/4 -> 1/4, roots=0
db.query.get_persona: scope db->image-server | traces 4/4 -> 2/4, roots=0
db.query.get_prefs: scope db->image-server | traces 4/4 -> 3/4, roots=0
db.query.get_tag_counts_batch: scope db->db/image-server | traces 1/1 -> 2/4, roots=0
db.query.get_tags_for_path: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.query.has_any_faces: scope db->image-server | traces 2/2 -> 2/2, roots=0
db.query.has_any_summaries: scope db->image-server | traces 2/2 -> 2/2, roots=0
db.query.list_entities: scope db->image-server | traces 1/2 -> 1/4, roots=0
db.query.list_rel_paths_for_libraries: scope db->db/image-server | traces 1/1 -> 2/4, roots=0
db.query.resolve_content_hash: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.update.cancel_active_jobs: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.update.complete_job: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.update.update_facts_insight_id: scope db->image-server | traces 1/1 -> 1/1, roots=0
db.update.update_training_messages: scope db->image-server | traces 1/1 -> 1/1, roots=0
generate_video_thumbnail: same | traces 1/222 -> 1/414, roots=0
http.insights.generate_agentic: same | traces 1/1 -> 1/1, roots=0
list_memories: same | traces 1/1 -> 1/1, roots=0
list_photos: same | traces 1/1 -> 2/4, roots=0
llm.request: same | traces 3/8 -> 2/12, roots=0
== Roots in the after capture (span with no parent) ==
GET /insights/generation/status trace=4e4c40ef spans_in_trace=2
GET /insights/generation/status trace=9b6f5cad spans_in_trace=2
GET /insights/generation/status trace=92fe175c spans_in_trace=2
GET /insights/generation/status trace=a1c2c449 spans_in_trace=2
GET /insights/generation/status trace=73ad5d54 spans_in_trace=2
GET /insights/generation/status trace=96ba44fa spans_in_trace=2
GET /insights/generation/status trace=63be2acf spans_in_trace=2
POST /insights/chat/stream trace=119b1ad6 spans_in_trace=11
GET /insights/generation/status trace=d0f13d49 spans_in_trace=2
GET /insights/generation/status trace=01e0824c spans_in_trace=2
watcher.initial_probe trace=09884c56 spans_in_trace=5
GET /insights/generation/status trace=4a47ba01 spans_in_trace=2
POST /insights/generate/agentic trace=881c56c0 spans_in_trace=52
GET /insights/generation/status trace=87857a0b spans_in_trace=2
GET /insights/generation/status trace=e1cf97cb spans_in_trace=2
GET /insights/generation/status trace=5f02a109 spans_in_trace=2
GET /insights/generation/status trace=6fb52a67 spans_in_trace=2
GET /insights/generation/status trace=2512bbae spans_in_trace=2
GET /photos trace=4cd7207a spans_in_trace=4
GET /memories trace=0c26f842 spans_in_trace=7
GET /insights/generation/status trace=6844193f spans_in_trace=2
== Ancestry of key spans ==
list_photos <- (remote 2222222222222222)
llm.request <- ai.chat.turn.stream <- POST /insights/chat/stream [llm.operation=chat_stream]
db.update.update_training_messages <- ai.chat.turn.stream <- POST /insights/chat/stream
ai.chat.turn.stream <- POST /insights/chat/stream
llm.request <- ai.rag.search_daily_summaries <- ai.agentic.loop <- ai.insight.generate_agentic <- http.insights.generate_agentic <- POST /insights/generate/agentic [llm.operation=embeddings]
llm.request <- ai.agentic.loop <- ai.insight.generate_agentic <- http.insights.generate_agentic <- POST /insights/generate/agentic [llm.operation=chat]
ai.agentic.loop <- ai.insight.generate_agentic <- http.insights.generate_agentic <- POST /insights/generate/agentic
db.insert.store_insight <- ai.insight.generate_agentic <- http.insights.generate_agentic <- POST /insights/generate/agentic
ai.insight.generate_agentic <- http.insights.generate_agentic <- POST /insights/generate/agentic
list_memories <- GET /memories
generate_video_thumbnail <- (remote 4b78d96000f31655)
== traceparent probe ==
list_photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.list_rel_paths_for_libraries <- list_photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.get_tag_counts_batch <- list_photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.list_rel_paths_for_libraries <- list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.get_tag_counts_batch <- list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.list_rel_paths_for_libraries <- list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
db.query.get_tag_counts_batch <- list_photos <- GET /photos <- (remote 2222222222222222) trace=11111111111111111111111111111111
== llm.request attribute presence ==
op=chat_stream model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=11148 parent=ai.chat.turn.stream
op=embeddings model=embed provider=llamacpp status=200 tokens_in=None parent=ai.rag.search_daily_summaries
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=10289 parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=10480 parent=ai.agentic.loop
op=embeddings model=embed provider=llamacpp status=200 tokens_in=None parent=ai.agentic.loop
op=embeddings model=embed provider=llamacpp status=200 tokens_in=None parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=5089 parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=10672 parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=10911 parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=10340 parent=ai.agentic.loop
op=chat model=qwen3.8-27b-abliterated provider=llamacpp status=200 tokens_in=9858 parent=ai.agentic.loop
op=embeddings model=embed provider=llamacpp status=200 tokens_in=None parent=ai.rag.search_daily_summaries
== turn / insight spans: llm.backend + llm.model ==
ai.chat.turn.stream: llm.backend=None llm.model=None backend=None model=None
ai.insight.generate_agentic: llm.backend=None llm.model=None backend=local model=qwen3.8-27b-abliterated
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#!/bin/bash
# Replays the #137 baseline request set against the after-capture server.
set -u
W=$(dirname "$0"); B=http://127.0.0.1:18080
T=$(python3 $W/mint_jwt.py); H="Authorization: Bearer $T"
echo "1) photos"; curl -s -o /dev/null -w "%{http_code}\n" -H "$H" "$B/photos?path=Colleen&recursive=true&limit=20"
echo "2) memories"; curl -s -o /dev/null -w "%{http_code}\n" -H "$H" "$B/memories?path=.&recursive=true"
echo "3) agentic"; R=$(curl -s -H "$H" -H 'Content-Type: application/json' -d '{"file_path":"Photo06172345.jpg","backend":"local"}' "$B/insights/generate/agentic"); echo "$R"
JOB=$(echo "$R" | jq -r '.job_id // empty')
if [ -n "$JOB" ]; then
for i in $(seq 1 120); do S=$(curl -s -H "$H" "$B/insights/generation/status?job_id=$JOB" | jq -r .status); [ "$S" != "running" ] && [ "$S" != "pending" ] && break; sleep 5; done
echo " job $JOB -> $S"
fi
echo "4) chat stream"; curl -sN -H "$H" -H 'Content-Type: application/json' -d '{"file_path":"Photo06172345.jpg","user_message":"What was I wearing in this photo?","backend":"local"}' "$B/insights/chat/stream" > $W/chat.sse; echo " deltas=$(grep -c '^event: text' $W/chat.sse) done=$(grep -c '^event: done' $W/chat.sse) errors=$(grep -c '^event: error' $W/chat.sse)"
echo "5) traceparent probe"; curl -s -o /dev/null -w "%{http_code}\n" -H "$H" -H 'traceparent: 00-11111111111111111111111111111111-2222222222222222-01' "$B/photos?path=Colleen&recursive=true&limit=5"
@@ -0,0 +1,918 @@
[
{
"operation": "generate_video_thumbnail",
"span_count": 414,
"trace_count": 1,
"kind": "internal",
"scope": "image-server",
"status": "(none)",
"attribute_keys": [
"file-name",
"library",
"otel.scope.name",
"span.kind",
"type"
],
"parents": {
"(remote)": 414
},
"root_count": 0
},
{
"operation": "db.query.get_job_by_id",
"span_count": 16,
"trace_count": 16,
"kind": "internal",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
],
"parents": {
"GET /insights/generation/status": 16
},
"root_count": 0
},
{
"operation": "GET /insights/generation/status",
"span_count": 16,
"trace_count": 16,
"kind": "server",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"http.client_ip",
"http.flavor",
"http.host",
"http.method",
"http.route",
"http.scheme",
"http.status_code",
"http.target",
"http.user_agent",
"otel.scope.name",
"otel.status_code",
"request_id",
"span.kind",
"trace_id"
],
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@@ -0,0 +1 @@
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/insights/generation/status","references":[],"startTime":1790716648578868,"duration":219,"tags":[{"key":"busy_ns","type":"int64","value":157935},{"key":"code.file.path","type":"string","value":"/home/cameron/.cargo/registry/src/index.crates.io-1949cf8c6b5b557f/tracing-actix-web-0.7.25/src/root_span_builder.rs"},{"key":"code.line.number","type":"int64","value":44},{"key":"code.module.name","type":"string","value":"tracing_actix_web::root_span_builder"},{"key":"http.client_ip","type":"string","value":"127.0.0.1"},{"key":"http.flavor","type":"string","valLine truncated
@@ -0,0 +1,129 @@
# Pre-migration span baseline (ticket #137, map #135)
Captured from **master @ `da3901c`** ("before" the tracing migration) so the
post-migration output can be diffed for parity. See map #135 for the
migration's destination.
## What was run
- **Revision:** `da3901c` (merge of "Prefs: owner defaults"), the last
master commit before `feature/tracing-migration`.
- **Build:** `cargo build --release` — release is required; the pre-migration
OTel init is behind `#[cfg(not(debug_assertions))]`, so debug builds are a
no-op (no global tracer provider, no spans).
- **Exporter:** local Jaeger all-in-one (`jaegertracing/all-in-one:latest`),
OTLP/gRPC on host `:14317` (container `:4317`), UI `:16686`. Prod SigNoz
(`OTLP_OTLS_ENDPOINT=http://192.168.10.50:4317`) was overridden deliberately.
- **DB:** a private `.backup` copy of the live `auth.db` (21,298 `image_exif`
rows, 4 NAS-backed libraries). The live deployment (`image-rs.service`) was
left running and untouched; all output dirs (thumbs/gifs/video/reels) point
at a temp dir.
- **LLM backend:** the live local stack — `LLM_BACKEND=llamacpp`,
`LLAMA_SWAP_URL=http://192.168.10.50:9292/v1`, model
`qwen3.8-27b-abliterated`.
### Deviation from pristine `da3901c`
The binary was built from `da3901c` with **one span-neutral change**: the
hardcoded secondary listener `.bind("localhost:8088")` was moved to
`.bind("localhost:18088")` because the live `image-rs.service` owns `:8088`.
The listen port cannot affect span production. Everything else is unmodified.
### Requests exercised (the representative set)
All with `Authorization: Bearer <JWT>` (minted with the live `SECRET_KEY`,
`sub=2`).
| # | Request | Span trace(s) |
|---|---------|---------------|
| 1 | `GET /photos?path=Colleen&recursive=true&limit=20` | `cb07eeec…` (3 spans) |
| 2 | `GET /memories?path=.&recursive=true` | `44b3b67d…` (6 spans) |
| 3 | `POST /insights/generate/agentic` `{file_path:"Photo06172345.jpg",backend:"local"}` → **202 job_id=380** (async) | `948d2756…` (HTTP span) **and** `9b520713…` (background, 22 spans) |
| 4 | `POST /insights/chat/stream` `{file_path:"Photo06172345.jpg",user_message:"What was I wearing in this photo?",backend:"local"}` (SSE, 88 text deltas, `done`) | fragmented — see below |
| 5 | `GET /photos?path=Colleen&recursive=true&limit=5` **with** `traceparent: 00-1111…1111-2222…2222-01` | `11111111…` (3 spans) |
## Span shape (the "before")
**Service:** `image-server` (resource `service.name`), version from
`CARGO_PKG_VERSION`. No per-request HTTP server span exists — the migration's
`tracing-actix-web` middleware (#139) adds one.
**Span names**
- Operation / "root" spans (created manually in handlers): `list_photos`,
`list_memories`, `http.insights.generate_agentic`, `ai.insight.generate_agentic`,
`ai.agentic.loop`, `ai.rag.search_daily_summaries`, `generate_video_thumbnail`.
- DB spans: `db.{query_type}.{operation}` — `query_type ∈ {query, insert, update}`,
`operation` = snake_case DAO method (`get_exif`, `store_insight`, …).
Tracer scope (`otel.scope.name`) is `db`.
- LLM spans: `llm.request`, tracer scope `image-server`.
**`span.kind`:** `internal` for every operation/DB span; `client` for
`llm.request`.
**Key attributes**
- Every span: `otel.scope.name` (`image-server` or `db`), `otel.status_code`
(`OK` / unset), `span.kind`.
- DB (`db.*`): `db.query_type`, `db.operation`.
- LLM (`llm.request`): `llm.model` (`qwen3.8-27b-abliterated`),
`llm.provider` (`llamacpp`), `llm.operation` (`chat` for tool calls,
`chat_stream` for the SSE turn), `llm.tokens.input`, `llm.tokens.output`,
`http.status_code`.
- `list_photos`: rich request shape — `path`, `recursive`, `sort`, `library`,
`media_type`, `pagination.limit/offset/enabled`, `file_count`,
`returned_count`, `total_count`, `optimization.batch_tags`,
`optimization.db_sort`, `tag_filter_mode`, plus empty camera/gps/date fields.
- `ai.insight.generate_agentic`: `backend`, `file_path`, `images_inline`,
`max_iterations`, `model`. `ai.agentic.loop`: `iterations_used`.
- `generate_video_thumbnail`: `file-name`, `library`, `type`.
- `ai.rag.search_daily_summaries`: `query`, `date`, `limit`, `results_count`,
`time_weighted`.
**Nesting — the headline finding.** Parent/child threading is *inconsistent*:
1. **No HTTP root span.** Handlers open an operation-named span as a root.
2. **Most DB spans are orphaned into their own single-span trace** (see
`span-inventory.json`: `trace_count == span_count` for most ops).
`db.query.get_prefs`, `db.query.count_for_library`, `db.insert.store_insight`,
`db.update.*`, etc. each form a separate trace.
3. **Threading works in pockets.** `list_photos` (→ 2 DB children),
`list_memories` (→ `get_prefs` + 4× `get_memories_in_window`), and the
agentic loop (`ai.insight.generate_agentic` → `ai.agentic.loop` →
`llm.request` + DB spans) nest correctly.
4. **Async work loses the trace.** `POST /insights/generate/agentic` returns
**202** with `http.insights.generate_agentic` in one trace; the background
generation is a *different root trace* (`ai.insight.generate_agentic`).
The streaming chat path is likewise fragmented — its DB calls and
`llm.request` land as separate single-span traces, with **no handler span
at all**.
5. **One 222-span trace** (`b94440d1…`) holds the startup thumbnail sweep —
all `generate_video_thumbnail` spans share one trace.
**Incoming propagation WORKS.** With a caller-supplied W3C `traceparent`, the
`list_photos` span is created in the caller's trace-id and references the
remote span-id as `CHILD_OF` — i.e. the request joins the upstream trace
correctly. This is the behavior the migration must preserve.
## Files
- `traces-no-traceparent.json` — all 33 traces from requests 1–4 (Jaeger
`/api/traces` dump; requests made without an incoming traceparent).
- `traces-with-traceparent.json` — includes the propagation test (request 5).
- `span-inventory.json` — per-operation summary: span count, trace count,
kind, scope, status, attribute keys. The direct input for a before/after
shape diff.
## Re-capturing
1. Build `da3901c` release (or the branch under test for the "after").
2. `docker run -d --name jaeger -p 16686:16686 -p 14317:4317 jaegertracing/all-in-one:latest`.
3. Run the server against a **copy** of the DB with
`OTLP_OTLS_ENDPOINT=http://localhost:14317` and a temp `BIND_URL`; remember
the hardcoded secondary `localhost:8088` bind collides with the live
service (patch it, or stop the service).
4. Mint a JWT (`HS256`, `{sub, exp}`, `SECRET_KEY`) and replay the request set
in the table above.
5. `curl 'http://localhost:16686/api/traces?service=image-server&limit=600'`
→ regenerate `span-inventory.json` and diff operation names, kinds,
attribute keys, and nesting.
@@ -0,0 +1,590 @@
[
{
"operation": "generate_video_thumbnail",
"span_count": 222,
"trace_count": 1,
"kind": "internal",
"scope": "image-server",
"status": "(none)",
"attribute_keys": [
"file-name",
"library",
"otel.scope.name",
"span.kind",
"type"
]
},
{
"operation": "llm.request",
"span_count": 8,
"trace_count": 3,
"kind": "client",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"http.status_code",
"llm.model",
"llm.operation",
"llm.provider",
"llm.tokens.input",
"llm.tokens.output",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.count_for_library",
"span_count": 4,
"trace_count": 4,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_memories_in_window",
"span_count": 4,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_persona",
"span_count": 4,
"trace_count": 4,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_prefs",
"span_count": 4,
"trace_count": 4,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.insert.upsert_entity",
"span_count": 2,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_event_count",
"span_count": 2,
"trace_count": 2,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_exif",
"span_count": 2,
"trace_count": 2,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_location_count",
"span_count": 2,
"trace_count": 2,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.has_any_faces",
"span_count": 2,
"trace_count": 2,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.has_any_summaries",
"span_count": 2,
"trace_count": 2,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.list_entities",
"span_count": 2,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "ai.agentic.loop",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"iterations_used",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "ai.insight.generate_agentic",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"backend",
"file_path",
"images_inline",
"max_iterations",
"model",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "ai.rag.search_daily_summaries",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "image-server",
"status": "OK",
"attribute_keys": [
"date",
"limit",
"otel.scope.name",
"otel.status_code",
"query",
"results_count",
"span.kind",
"time_weighted"
]
},
{
"operation": "db.insert.create_job",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.insert.store_insight",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.insert.upsert_fact",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.insert.upsert_photo_link",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.faces_for_hash",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"content_hash",
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.find_relevant_events_hybrid",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.find_similar_summaries_with_time_weight",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_active_job",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_current_insight_for_library",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_links_for_photo",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_tag_counts_batch",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"file_count",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.get_tags_for_path",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"path",
"span.kind"
]
},
{
"operation": "db.query.list_rel_paths_for_libraries",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.query.resolve_content_hash",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.update.cancel_active_jobs",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.update.complete_job",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
"operation": "db.update.update_facts_insight_id",
"span_count": 1,
"trace_count": 1,
"kind": "internal",
"scope": "db",
"status": "OK",
"attribute_keys": [
"db.operation",
"db.query_type",
"otel.scope.name",
"otel.status_code",
"span.kind"
]
},
{
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