Files
llama-swap/proxy/metrics_monitor.go
Benson Wong e250e71e59 Include metrics from upstream chat requests (#361)
* proxy: refactor metrics recording

- remove metrics_middleware.go as this wrapper is no longer needed. This
  also eliminiates double body parsing for the modelID
- move metrics parsing to be part of MetricsMonitor
- refactor how metrics are recording in ProxyManager
- add MetricsMonitor tests
- improve mem efficiency of processStreamingResponse
- add benchmarks for MetricsMonitor.addMetrics
- proxy: refactor MetricsMonitor to be more safe handling errors
2025-10-25 17:38:18 -07:00

268 lines
7.3 KiB
Go

package proxy
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"sync"
"time"
"github.com/gin-gonic/gin"
"github.com/mostlygeek/llama-swap/event"
"github.com/tidwall/gjson"
)
// TokenMetrics represents parsed token statistics from llama-server logs
type TokenMetrics struct {
ID int `json:"id"`
Timestamp time.Time `json:"timestamp"`
Model string `json:"model"`
CachedTokens int `json:"cache_tokens"`
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
PromptPerSecond float64 `json:"prompt_per_second"`
TokensPerSecond float64 `json:"tokens_per_second"`
DurationMs int `json:"duration_ms"`
}
// TokenMetricsEvent represents a token metrics event
type TokenMetricsEvent struct {
Metrics TokenMetrics
}
func (e TokenMetricsEvent) Type() uint32 {
return TokenMetricsEventID // defined in events.go
}
// metricsMonitor parses llama-server output for token statistics
type metricsMonitor struct {
mu sync.RWMutex
metrics []TokenMetrics
maxMetrics int
nextID int
logger *LogMonitor
}
func newMetricsMonitor(logger *LogMonitor, maxMetrics int) *metricsMonitor {
mp := &metricsMonitor{
logger: logger,
maxMetrics: maxMetrics,
}
return mp
}
// addMetrics adds a new metric to the collection and publishes an event
func (mp *metricsMonitor) addMetrics(metric TokenMetrics) {
mp.mu.Lock()
defer mp.mu.Unlock()
metric.ID = mp.nextID
mp.nextID++
mp.metrics = append(mp.metrics, metric)
if len(mp.metrics) > mp.maxMetrics {
mp.metrics = mp.metrics[len(mp.metrics)-mp.maxMetrics:]
}
event.Emit(TokenMetricsEvent{Metrics: metric})
}
// getMetrics returns a copy of the current metrics
func (mp *metricsMonitor) getMetrics() []TokenMetrics {
mp.mu.RLock()
defer mp.mu.RUnlock()
result := make([]TokenMetrics, len(mp.metrics))
copy(result, mp.metrics)
return result
}
// getMetricsJSON returns metrics as JSON
func (mp *metricsMonitor) getMetricsJSON() ([]byte, error) {
mp.mu.RLock()
defer mp.mu.RUnlock()
return json.Marshal(mp.metrics)
}
// wrapHandler wraps the proxy handler to extract token metrics
// if wrapHandler returns an error it is safe to assume that no
// data was sent to the client
func (mp *metricsMonitor) wrapHandler(
modelID string,
writer gin.ResponseWriter,
request *http.Request,
next func(modelID string, w http.ResponseWriter, r *http.Request) error,
) error {
recorder := newBodyCopier(writer)
if err := next(modelID, recorder, request); err != nil {
return err
}
// after this point we have to assume that data was sent to the client
// and we can only log errors but not send them to clients
if recorder.Status() != http.StatusOK {
mp.logger.Warnf("metrics skipped, HTTP status=%d, path=%s", recorder.Status(), request.URL.Path)
return nil
}
body := recorder.body.Bytes()
if len(body) == 0 {
mp.logger.Warn("metrics skipped, empty body")
return nil
}
if strings.Contains(recorder.Header().Get("Content-Type"), "text/event-stream") {
if tm, err := processStreamingResponse(modelID, recorder.StartTime(), body); err != nil {
mp.logger.Warnf("error processing streaming response: %v, path=%s", err, request.URL.Path)
} else {
mp.addMetrics(tm)
}
} else {
if gjson.ValidBytes(body) {
if tm, err := parseMetrics(modelID, recorder.StartTime(), gjson.ParseBytes(body)); err != nil {
mp.logger.Warnf("error parsing metrics: %v, path=%s", err, request.URL.Path)
} else {
mp.addMetrics(tm)
}
} else {
mp.logger.Warnf("metrics skipped, invalid JSON in response body path=%s", request.URL.Path)
}
}
return nil
}
func processStreamingResponse(modelID string, start time.Time, body []byte) (TokenMetrics, error) {
// Iterate **backwards** through the body looking for the data payload with
// usage data. This avoids allocating a slice of all lines via bytes.Split.
// Start from the end of the body and scan backwards for newlines
pos := len(body)
for pos > 0 {
// Find the previous newline (or start of body)
lineStart := bytes.LastIndexByte(body[:pos], '\n')
if lineStart == -1 {
lineStart = 0
} else {
lineStart++ // Move past the newline
}
line := bytes.TrimSpace(body[lineStart:pos])
pos = lineStart - 1 // Move position before the newline for next iteration
if len(line) == 0 {
continue
}
// SSE payload always follows "data:"
prefix := []byte("data:")
if !bytes.HasPrefix(line, prefix) {
continue
}
data := bytes.TrimSpace(line[len(prefix):])
if len(data) == 0 {
continue
}
if bytes.Equal(data, []byte("[DONE]")) {
// [DONE] line itself contains nothing of interest.
continue
}
if gjson.ValidBytes(data) {
return parseMetrics(modelID, start, gjson.ParseBytes(data))
}
}
return TokenMetrics{}, fmt.Errorf("no valid JSON data found in stream")
}
func parseMetrics(modelID string, start time.Time, jsonData gjson.Result) (TokenMetrics, error) {
usage := jsonData.Get("usage")
timings := jsonData.Get("timings")
if !usage.Exists() && !timings.Exists() {
return TokenMetrics{}, fmt.Errorf("no usage or timings data found")
}
// default values
cachedTokens := -1 // unknown or missing data
outputTokens := 0
inputTokens := 0
// timings data
tokensPerSecond := -1.0
promptPerSecond := -1.0
durationMs := int(time.Since(start).Milliseconds())
if usage.Exists() {
outputTokens = int(jsonData.Get("usage.completion_tokens").Int())
inputTokens = int(jsonData.Get("usage.prompt_tokens").Int())
}
// use llama-server's timing data for tok/sec and duration as it is more accurate
if timings.Exists() {
inputTokens = int(jsonData.Get("timings.prompt_n").Int())
outputTokens = int(jsonData.Get("timings.predicted_n").Int())
promptPerSecond = jsonData.Get("timings.prompt_per_second").Float()
tokensPerSecond = jsonData.Get("timings.predicted_per_second").Float()
durationMs = int(jsonData.Get("timings.prompt_ms").Float() + jsonData.Get("timings.predicted_ms").Float())
if cachedValue := jsonData.Get("timings.cache_n"); cachedValue.Exists() {
cachedTokens = int(cachedValue.Int())
}
}
return TokenMetrics{
Timestamp: time.Now(),
Model: modelID,
CachedTokens: cachedTokens,
InputTokens: inputTokens,
OutputTokens: outputTokens,
PromptPerSecond: promptPerSecond,
TokensPerSecond: tokensPerSecond,
DurationMs: durationMs,
}, nil
}
// responseBodyCopier records the response body and writes to the original response writer
// while also capturing it in a buffer for later processing
type responseBodyCopier struct {
gin.ResponseWriter
body *bytes.Buffer
tee io.Writer
start time.Time
}
func newBodyCopier(w gin.ResponseWriter) *responseBodyCopier {
bodyBuffer := &bytes.Buffer{}
return &responseBodyCopier{
ResponseWriter: w,
body: bodyBuffer,
tee: io.MultiWriter(w, bodyBuffer),
}
}
func (w *responseBodyCopier) Write(b []byte) (int, error) {
if w.start.IsZero() {
w.start = time.Now()
}
// Single write operation that writes to both the response and buffer
return w.tee.Write(b)
}
func (w *responseBodyCopier) WriteHeader(statusCode int) {
w.ResponseWriter.WriteHeader(statusCode)
}
func (w *responseBodyCopier) Header() http.Header {
return w.ResponseWriter.Header()
}
func (w *responseBodyCopier) StartTime() time.Time {
return w.start
}