ConfigureConcurrency() set each adapter pool's target to the sum of
max_concurrent over its sources (108 on this deployment) and `created` only
ever went UP: once a Lua state was booted it was parked forever, so a
long-running gateway's resident state count was a high-water mark of all
traffic it had ever seen, never of what it currently needs.
Pools are now sized from three live inputs:
* the adapter's MAX CONCURRENCY (sum of max_concurrent) is a ceiling, not a
preallocation, and it sets the growth step:
growStep = clamp(ceil(maxW/8), 1, 8). A 64-wide adapter warms 8 states at
once on a spike; an 8-wide one creeps up one at a time.
* the LIVE CONNECTION COUNT (inUse, i.e. checked-out states) sets the shrink
step: shrinkStep = clamp(ceil(excess/(1+inUse)), 1, excess). With no
connections the slack collapses in a single round; a busy adapter gives up
one state per round so the hot path keeps its warm states.
* how many states already exist (created / len(idle)) decides how much room
is left to grow and how much can be reclaimed.
Batch prewarm only fires on genuine contention (a miss while every existing
state is checked out), so a single sequential caller keeps reusing one state
rather than burning a whole grow step on a cold start. A single VM-level
janitor goroutine (not one per adapter) reclaims idle states every 30s, and
shrinkGraceRounds=2 plus idleHeadroom=1 keep a gap between requests from being
mistaken for the end of a load period; any checkout resets the grace counter.
`created` now decrements on reclaim and on shutdown, and release() closes a
state outright when the ceiling was lowered underneath it, so shrinking
max_concurrent in the config gives memory back immediately instead of parking
orphans until restart.
PoolStats() exposes created/idle/in_use/waiting/max/resident/grow_step/
shrink_step/peak_in_use for the status API.
Measured on the test instance (single mock source, max_concurrent=64):
idle created=1; 50 concurrent requests -> created=10 (peak_in_use=5, ceiling
respected); after 95s of silence -> created=1. On production after deploy: 13
adapters, 1 resident Lua state total with ceilings up to 76.
Live testing across the zen pool showed models report
prompt_tokens_details.cached_tokens even when the hit count is 0 (e.g.
nemotron-3-ultra-free returns cached_tokens:0, audio_tokens:0,
cache_write_tokens:0). The previous >0 guard dropped those objects, so a
cache-enabled upstream looked identical to one without cache support.
- types: PromptTokensDetails.CachedTokens always emitted (drop inner
omitempty) so clients see cached_tokens:0 explicitly; dsh reads it as
a 0% hit instead of 'no data'
- adapters (9): forward prompt_tokens_details whenever the upstream
provides it (presence check instead of >0)
- Req: add cache_reported flag set when usage carried cache accounting;
WebUI shows an amber 0% tag for reported-but-missed rows and keeps
the em-dash only for sources that never report cache data
Live testing proved both sensenova and zen DO return cache fields:
- zen laguna-s-2.1-free: usage.prompt_tokens_details.cached_tokens = 32
(real hit), plus cache_write_tokens/audio_tokens
- sensenova glm-5.2: prompt_tokens_details.cached_tokens present (0 on
short prompts)
The previous round only patched deepseek/openai/anthropic/gemini.lua;
sensenova/opencode (localzen!) and the other adapters still dropped them.
- sensenova/opencode/groq/mistral/github/kimicode: stream + response
cache passthrough (same pattern as openai.lua)
- agentrouter: response passthrough + NEW stream usage forwarding (it
previously dropped the terminal usage-only chunk entirely)
- ollama skipped intentionally: its native API has no cache fields
Verified end-to-end through the gateway: localzen/laguna-s-2.1-free now
returns prompt_tokens_details.cached_tokens=32 to clients, and the request
record carries cache_hit_tokens (both chat and stream paths).
dsh displays cache-hit %, but llmsproxy dropped every upstream's cache
fields — deepseek prompt_cache_hit_tokens, OpenAI prompt_tokens_details.
cached_tokens, anthropic cache_read_input_tokens, gemini cachedContentTokenCount.
Changes:
- TokenUsage: add PromptTokensDetails (with CachedTokens) + PromptCacheHit/Miss
- MarshalJSON: emit prompt_tokens_details.cached_tokens (OpenAI v2 standard)
and prompt_cache_hit/miss_tokens (DeepSeek legacy) — dsh reads the former
first, falls back to the latter
- mergeUsage: preserve cache fields across stream chunks
- standardSSEChunk: parse the upstream raw prompt_tokens_details too
- deepseek.lua: forward prompt_cache_hit/miss_tokens + create
prompt_tokens_details from them
- openai.lua: forward prompt_tokens_details.cached_tokens and legacy
prompt_cache_hit/miss_tokens; normalize legacy hits into the standard
object so dsh sees them regardless of upstream format
- anthropic.lua: map cache_read_input_tokens → prompt_tokens_details
- gemini.lua: map cachedContentTokenCount → prompt_tokens_details
Every upstream formats errors differently, which is adapter territory:
the protocol gains an optional transform_error(status, body) hook and all
built-in adapters implement their own envelope parsing (zen free-pool
labels, anthropic/gemini/ollama/mistral shapes, sensenova quota notes,
agentrouter WAF pages). The core keeps a single uniform fallback: when no
hook yields a reason clients get "api error <status>: unknown error" and
the raw body goes to server logs only.
The gateway hardcoded "stop" on every terminating stream chunk, so
tool-call rounds reported finish_reason=stop and length caps were
invisible to clients. UnifiedChunk now carries finish_reason; adapters
emit it (with empty-string finish reasons like sensenova treated as
non-terminal), standardSSEChunk passes it through for un-adapted
upstreams, [DONE] no longer emits a duplicate reason-less done chunk,
and both streaming paths emit the real reason with "stop" as fallback.
Also vendor sensenova/agentrouter adapters into the repo: they were
WebUI-only uploads and a deploy sync silently removed them while live
AUTO-chain slots still referenced them.
zen fingerprints clients via UA + x-opencode-client/session/request/project
headers; requests without them are routed as anonymous and fail with a
single-chunk network_error stream (tools+stream) or 503 Endpoint is
unavailable (non-stream), which the adapter laundered into empty-but-valid
replies. Derive per-request session/request ids from build_headers meta
(sandbox has no os/math), bump UA to the real client format, map zen
reasoning field to reasoning_content, and set stream_options.include_usage.
The prior usage-passthrough fix only covered openai/opencode; the same
empty-choices+usage drop bug remained in the 5 sibling OpenAI-compatible
adapters, and non-OpenAI providers (anthropic/gemini/ollama) never surfaced
streaming usage at all.
- deepseek/github/groq/kimicode/mistral: preserve usage on empty-choices
chunks and attach it to normal chunks (same pattern as openai.lua)
- anthropic: emit usage from message_start (prompt) and message_delta
(completion); gateway merges split usage additively
- gemini: read usageMetadata in the stream path
- ollama: fix non-streaming key (usage -> token_usage, matches
UnifiedResponse json tag) and read prompt_eval_count/eval_count;
surface counts from the done stream chunk
- gateway: mergeUsage combines usage across chunks (non-zero fields win,
total recomputed from prompt+completion) so split usage doesn't lose
the prompt half; single-chunk case (OpenAI) preserved exactly
- usage-only chunks: done=false (no redundant terminal stop), matching
the Go fallback standardSSEChunk
Streaming responses now carry the upstream's real token usage instead of
gateway estimates:
- UnifiedChunk gains an optional Usage field; adapters (opencode, openai)
extract usage from upstream stream chunks (including the final chunk with
empty choices) and pass it through.
- standardSSEChunk preserves usage for passthrough adapters.
- Gateway emits the exact usage in the final stream chunk when available,
falling back to estimates only when the upstream provided none.
Non-streaming usage was already fixed to emit OpenAI-standard keys.
- adapters/opencode.lua: opencode.ai zen free pool adapter — sends the
opencode client User-Agent (zen fingerprints clients by UA; non-official
clients hit FreeUsageLimitError); pairs with api_key: public
- config: no config file ships in the repo; first run generates a default
config at the -config path with a random admin key, loopback listen and a
keyless zen source (config.EnsureDefault); remove config.example.yaml
- lua: seed bundled adapters from the embedded FS instead of a hardcoded
name list
- ui: widen model kind select (chat was clipped to 'cha')
- phase 5 bugfixes: stats ms/s bucket mixing, cleanScopes nil, ctx.Err
guards, direct-path ModelAvailable, empty stream body failure,
bestImageModel rewrite, transform failure recording, Core.mu, timer,
effective model for tool-calls
