diff --git a/Dockerfile b/Dockerfile index 5e93a0c627e..83d3640e763 100644 --- a/Dockerfile +++ b/Dockerfile @@ -49,7 +49,7 @@ USER root # Install runtime dependencies (libsndfile needed for audio processing on ARM64) RUN apk add --no-cache bash openssl tzdata nodejs npm python3 py3-pip libsndfile && \ - npm install -g npm@latest tar@7.5.7 glob@11.1.0 @isaacs/brace-expansion@5.0.1 && \ + npm install -g npm@latest tar@7.5.8 glob@11.1.0 @isaacs/brace-expansion@5.0.1 minimatch@10.2.1 diff@8.0.3 && \ # SECURITY FIX: npm bundles tar, glob, and brace-expansion at multiple nested # levels inside its dependency tree. `npm install -g ` only creates a # SEPARATE global package, it does NOT replace npm's internal copies. @@ -64,6 +64,12 @@ RUN apk add --no-cache bash openssl tzdata nodejs npm python3 py3-pip libsndfile find "$GLOBAL/npm" -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ done && \ + find "$GLOBAL/npm" -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find "$GLOBAL/npm" -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ + done && \ npm cache clean --force WORKDIR /app @@ -90,14 +96,20 @@ RUN find /usr/lib -type f -path "*/tornado/test/*" -delete && \ # npm with old vulnerable deps at /usr/lib/python3.*/site-packages/nodejs_wheel/. # Patch every copy of tar, glob, and brace-expansion inside that tree. RUN GLOBAL="$(npm root -g)" && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/tar" -type d | while read d; do \ + find /usr/lib -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/glob" -type d | while read d; do \ + find /usr/lib -type d -name "glob" -path "*/node_modules/glob" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/glob" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/@isaacs/brace-expansion" -type d | while read d; do \ + find /usr/lib -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ + done && \ + find /usr/lib -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find /usr/lib -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ done # Install semantic_router and aurelio-sdk using script diff --git a/README.md b/README.md index 3ebaefb10ca..3db827d5fdd 100644 --- a/README.md +++ b/README.md @@ -203,7 +203,7 @@ curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \ { "mcpServers": { "LiteLLM": { - "url": "http://localhost:4000/mcp", + "url": "http://localhost:4000/mcp/", "headers": { "x-litellm-api-key": "Bearer sk-1234" } diff --git a/ci_cd/security_scans.sh b/ci_cd/security_scans.sh index b60e7ec5235..0e50f15d043 100755 --- a/ci_cd/security_scans.sh +++ b/ci_cd/security_scans.sh @@ -160,6 +160,7 @@ run_grype_scans() { "CVE-2026-0775" # npm cli incorrect permission assignment - no fix available yet, npm is only used at build/prisma-generate time "GHSA-3ppc-4f35-3m26" # minimatch ReDoS via repeated wildcards - from nodejs_wheel bundled npm, not used in application runtime code "GHSA-83g3-92jg-28cx" # tar arbitrary file read/write via hardlink - from nodejs_wheel bundled npm, not used in application runtime code + "CVE-2026-25639" # axios - full fix requires 1.x major version bump; pinned to >=0.30.2 to clear other axios CVEs, upgrade to 1.x in follow-up ) # Build JSON array of allowlisted CVE IDs for jq diff --git a/deploy/charts/litellm-helm/README.md b/deploy/charts/litellm-helm/README.md index 2fa856843f3..74e70f4aeb4 100644 --- a/deploy/charts/litellm-helm/README.md +++ b/deploy/charts/litellm-helm/README.md @@ -36,6 +36,10 @@ If `db.useStackgresOperator` is used (not yet implemented): | `serviceAccount.create` | Whether or not to create a Kubernetes Service Account for this deployment. The default is `false` because LiteLLM has no need to access the Kubernetes API. | `false` | | `service.type` | Kubernetes Service type (e.g. `LoadBalancer`, `ClusterIP`, etc.) | `ClusterIP` | | `service.port` | TCP port that the Kubernetes Service will listen on. Also the TCP port within the Pod that the proxy will listen on. | `4000` | +| `livenessProbe.*` | Liveness probe settings for the LiteLLM container (`path`, `periodSeconds`, `timeoutSeconds`, thresholds, and initial delay). | See `values.yaml` | +| `readinessProbe.*` | Readiness probe settings for the LiteLLM container (`path`, `periodSeconds`, `timeoutSeconds`, thresholds, and initial delay). | See `values.yaml` | +| `startupProbe.*` | Startup probe settings for the LiteLLM container (`path`, `periodSeconds`, `timeoutSeconds`, thresholds, and initial delay). | See `values.yaml` | +| `resources.*` | CPU/memory requests and limits for the LiteLLM container. | `{}` | | `service.loadBalancerClass` | Optional LoadBalancer implementation class (only used when `service.type` is `LoadBalancer`) | `""` | | `ingress.labels` | Additional labels for the Ingress resource | `{}` | | `ingress.*` | See [values.yaml](./values.yaml) for example settings | N/A | diff --git a/deploy/charts/litellm-helm/templates/configmap-litellm.yaml b/deploy/charts/litellm-helm/templates/configmap-litellm.yaml index cf35917da03..acbe4e3a4b5 100644 --- a/deploy/charts/litellm-helm/templates/configmap-litellm.yaml +++ b/deploy/charts/litellm-helm/templates/configmap-litellm.yaml @@ -6,4 +6,4 @@ metadata: data: config.yaml: | {{ .Values.proxy_config | toYaml | indent 6 }} -{{- end }} \ No newline at end of file +{{- end }} diff --git a/deploy/charts/litellm-helm/templates/deployment.yaml b/deploy/charts/litellm-helm/templates/deployment.yaml index 4ac5582d060..df483ab927d 100644 --- a/deploy/charts/litellm-helm/templates/deployment.yaml +++ b/deploy/charts/litellm-helm/templates/deployment.yaml @@ -158,18 +158,31 @@ spec: {{- end }} livenessProbe: httpGet: - path: /health/liveliness + path: {{ .Values.livenessProbe.path | quote }} port: {{ if .Values.separateHealthApp }}"health"{{ else }}"http"{{ end }} + initialDelaySeconds: {{ .Values.livenessProbe.initialDelaySeconds }} + periodSeconds: {{ .Values.livenessProbe.periodSeconds }} + timeoutSeconds: {{ .Values.livenessProbe.timeoutSeconds }} + successThreshold: {{ .Values.livenessProbe.successThreshold }} + failureThreshold: {{ .Values.livenessProbe.failureThreshold }} readinessProbe: httpGet: - path: /health/readiness + path: {{ .Values.readinessProbe.path | quote }} port: {{ if .Values.separateHealthApp }}"health"{{ else }}"http"{{ end }} + initialDelaySeconds: {{ .Values.readinessProbe.initialDelaySeconds }} + periodSeconds: {{ .Values.readinessProbe.periodSeconds }} + timeoutSeconds: {{ .Values.readinessProbe.timeoutSeconds }} + successThreshold: {{ .Values.readinessProbe.successThreshold }} + failureThreshold: {{ .Values.readinessProbe.failureThreshold }} startupProbe: httpGet: - path: /health/readiness + path: {{ .Values.startupProbe.path | quote }} port: {{ if .Values.separateHealthApp }}"health"{{ else }}"http"{{ end }} - failureThreshold: 30 - periodSeconds: 10 + initialDelaySeconds: {{ .Values.startupProbe.initialDelaySeconds }} + periodSeconds: {{ .Values.startupProbe.periodSeconds }} + timeoutSeconds: {{ .Values.startupProbe.timeoutSeconds }} + successThreshold: {{ .Values.startupProbe.successThreshold }} + failureThreshold: {{ .Values.startupProbe.failureThreshold }} resources: {{- toYaml .Values.resources | nindent 12 }} volumeMounts: @@ -235,4 +248,4 @@ spec: {{- if .Values.topologySpreadConstraints }} topologySpreadConstraints: {{- toYaml .Values.topologySpreadConstraints | nindent 8 }} - {{- end }} \ No newline at end of file + {{- end }} diff --git a/deploy/charts/litellm-helm/tests/deployment_tests.yaml b/deploy/charts/litellm-helm/tests/deployment_tests.yaml index f1229e10235..2e9c48043de 100644 --- a/deploy/charts/litellm-helm/tests/deployment_tests.yaml +++ b/deploy/charts/litellm-helm/tests/deployment_tests.yaml @@ -159,4 +159,150 @@ tests: value: -c - equal: path: spec.template.spec.containers[0].lifecycle.preStop.exec.command[2] - value: echo "Container stopping" \ No newline at end of file + value: echo "Container stopping" + - it: should render background health check settings from proxy_config.general_settings + template: configmap-litellm.yaml + set: + proxy_config.general_settings.background_health_checks: true + proxy_config.general_settings.health_check_interval: 240 + proxy_config.general_settings.health_check_concurrency: 16 + proxy_config.general_settings.health_check_details: false + asserts: + - matchRegex: + path: data["config.yaml"] + pattern: '(?m)^\s*background_health_checks:\s*true$' + - matchRegex: + path: data["config.yaml"] + pattern: '(?m)^\s*health_check_interval:\s*240$' + - matchRegex: + path: data["config.yaml"] + pattern: '(?m)^\s*health_check_concurrency:\s*16$' + - matchRegex: + path: data["config.yaml"] + pattern: '(?m)^\s*health_check_details:\s*false$' + - it: should allow overriding liveness, readiness, and startup probes + template: deployment.yaml + set: + livenessProbe: + path: /custom/livez + initialDelaySeconds: 5 + periodSeconds: 15 + timeoutSeconds: 5 + successThreshold: 1 + failureThreshold: 5 + readinessProbe: + path: /custom/readyz + initialDelaySeconds: 10 + periodSeconds: 20 + timeoutSeconds: 6 + successThreshold: 1 + failureThreshold: 6 + startupProbe: + path: /custom/startupz + initialDelaySeconds: 15 + periodSeconds: 25 + timeoutSeconds: 7 + successThreshold: 1 + failureThreshold: 40 + asserts: + - equal: + path: spec.template.spec.containers[0].livenessProbe.httpGet.path + value: /custom/livez + - equal: + path: spec.template.spec.containers[0].livenessProbe.timeoutSeconds + value: 5 + - equal: + path: spec.template.spec.containers[0].readinessProbe.httpGet.path + value: /custom/readyz + - equal: + path: spec.template.spec.containers[0].readinessProbe.timeoutSeconds + value: 6 + - equal: + path: spec.template.spec.containers[0].startupProbe.httpGet.path + value: /custom/startupz + - equal: + path: spec.template.spec.containers[0].startupProbe.failureThreshold + value: 40 + - it: should render container resources from values + template: deployment.yaml + set: + resources: + limits: + cpu: 500m + memory: 2Gi + requests: + cpu: 250m + memory: 1Gi + asserts: + - equal: + path: spec.template.spec.containers[0].resources.limits.cpu + value: 500m + - equal: + path: spec.template.spec.containers[0].resources.limits.memory + value: 2Gi + - equal: + path: spec.template.spec.containers[0].resources.requests.cpu + value: 250m + - equal: + path: spec.template.spec.containers[0].resources.requests.memory + value: 1Gi + - it: should keep default probes and empty resources unchanged + template: deployment.yaml + asserts: + - equal: + path: spec.template.spec.containers[0].livenessProbe.httpGet.path + value: /health/liveliness + - equal: + path: spec.template.spec.containers[0].livenessProbe.initialDelaySeconds + value: 0 + - equal: + path: spec.template.spec.containers[0].livenessProbe.periodSeconds + value: 10 + - equal: + path: spec.template.spec.containers[0].livenessProbe.timeoutSeconds + value: 1 + - equal: + path: spec.template.spec.containers[0].livenessProbe.successThreshold + value: 1 + - equal: + path: spec.template.spec.containers[0].livenessProbe.failureThreshold + value: 3 + - equal: + path: spec.template.spec.containers[0].readinessProbe.httpGet.path + value: /health/readiness + - equal: + path: spec.template.spec.containers[0].readinessProbe.initialDelaySeconds + value: 0 + - equal: + path: spec.template.spec.containers[0].readinessProbe.periodSeconds + value: 10 + - equal: + path: spec.template.spec.containers[0].readinessProbe.timeoutSeconds + value: 1 + - equal: + path: spec.template.spec.containers[0].readinessProbe.successThreshold + value: 1 + - equal: + path: spec.template.spec.containers[0].readinessProbe.failureThreshold + value: 3 + - equal: + path: spec.template.spec.containers[0].startupProbe.httpGet.path + value: /health/readiness + - equal: + path: spec.template.spec.containers[0].startupProbe.initialDelaySeconds + value: 0 + - equal: + path: spec.template.spec.containers[0].startupProbe.periodSeconds + value: 10 + - equal: + path: spec.template.spec.containers[0].startupProbe.timeoutSeconds + value: 1 + - equal: + path: spec.template.spec.containers[0].startupProbe.successThreshold + value: 1 + - equal: + path: spec.template.spec.containers[0].startupProbe.failureThreshold + value: 30 + - equal: + path: spec.template.spec.containers[0].resources + value: {} diff --git a/deploy/charts/litellm-helm/values.yaml b/deploy/charts/litellm-helm/values.yaml index cea25974bb0..d62f5b29c2b 100644 --- a/deploy/charts/litellm-helm/values.yaml +++ b/deploy/charts/litellm-helm/values.yaml @@ -84,6 +84,31 @@ service: separateHealthApp: false separateHealthPort: 8081 +# Probe tuning for proxy container +livenessProbe: + path: /health/liveliness + initialDelaySeconds: 0 + periodSeconds: 10 + timeoutSeconds: 1 + successThreshold: 1 + failureThreshold: 3 + +readinessProbe: + path: /health/readiness + initialDelaySeconds: 0 + periodSeconds: 10 + timeoutSeconds: 1 + successThreshold: 1 + failureThreshold: 3 + +startupProbe: + path: /health/readiness + initialDelaySeconds: 0 + periodSeconds: 10 + timeoutSeconds: 1 + successThreshold: 1 + failureThreshold: 30 + ingress: enabled: false className: "nginx" diff --git a/docker/Dockerfile.custom_ui b/docker/Dockerfile.custom_ui index 177d7b7b12a..fb98846a6cc 100644 --- a/docker/Dockerfile.custom_ui +++ b/docker/Dockerfile.custom_ui @@ -5,8 +5,21 @@ FROM ghcr.io/berriai/litellm:litellm_fwd_server_root_path-dev WORKDIR /app # Install Node.js and npm (adjust version as needed) -RUN apt-get update && apt-get install -y nodejs npm && \ - npm install -g npm@latest tar@7.5.7 glob@11.1.0 @isaacs/brace-expansion@5.0.1 && \ +RUN apt-get update && apt-get upgrade -y \ + libxml2 \ + libexpat1 \ + openssl \ + libssl3 \ + git \ + libkrb5-3 \ + libglib2.0-0 \ + wget \ + libaom3 \ + libxslt1.1 \ + libgnutls30 \ + libc6 && \ + apt-get install -y nodejs npm && \ + npm install -g npm@latest tar@7.5.8 glob@11.1.0 @isaacs/brace-expansion@5.0.1 minimatch@10.2.1 diff@8.0.3 && \ GLOBAL="$(npm root -g)" && \ find "$GLOBAL/npm" -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ @@ -17,6 +30,12 @@ RUN apt-get update && apt-get install -y nodejs npm && \ find "$GLOBAL/npm" -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ done && \ + find "$GLOBAL/npm" -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find "$GLOBAL/npm" -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ + done && \ npm cache clean --force # Copy the UI source into the container diff --git a/docker/Dockerfile.database b/docker/Dockerfile.database index a6fcd98ab6d..371766bd9db 100644 --- a/docker/Dockerfile.database +++ b/docker/Dockerfile.database @@ -50,7 +50,7 @@ USER root # Install runtime dependencies RUN apk add --no-cache bash openssl tzdata nodejs npm python3 py3-pip libsndfile && \ - npm install -g npm@latest tar@7.5.7 glob@11.1.0 @isaacs/brace-expansion@5.0.1 && \ + npm install -g npm@latest tar@7.5.8 glob@11.1.0 @isaacs/brace-expansion@5.0.1 minimatch@10.2.1 diff@8.0.3 && \ GLOBAL="$(npm root -g)" && \ find "$GLOBAL/npm" -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ @@ -61,6 +61,12 @@ RUN apk add --no-cache bash openssl tzdata nodejs npm python3 py3-pip libsndfile find "$GLOBAL/npm" -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ done && \ + find "$GLOBAL/npm" -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find "$GLOBAL/npm" -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ + done && \ npm cache clean --force WORKDIR /app @@ -79,14 +85,20 @@ RUN pip install *.whl /wheels/* --no-index --find-links=/wheels/ && rm -f *.whl # npm with old vulnerable deps at /usr/lib/python3.*/site-packages/nodejs_wheel/. # Patch every copy of tar, glob, and brace-expansion inside that tree. RUN GLOBAL="$(npm root -g)" && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/tar" -type d | while read d; do \ + find /usr/lib -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/glob" -type d | while read d; do \ + find /usr/lib -type d -name "glob" -path "*/node_modules/glob" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/glob" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/@isaacs/brace-expansion" -type d | while read d; do \ + find /usr/lib -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ + done && \ + find /usr/lib -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find /usr/lib -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ done # Install semantic_router and aurelio-sdk using script diff --git a/docker/Dockerfile.dev b/docker/Dockerfile.dev index bc1d22d5e05..a5312dec9e3 100644 --- a/docker/Dockerfile.dev +++ b/docker/Dockerfile.dev @@ -56,13 +56,26 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime USER root # Install only runtime dependencies -RUN apt-get update && apt-get install -y --no-install-recommends \ - libssl3 \ +RUN apt-get update && apt-get upgrade -y \ + libxml2 \ + libexpat1 \ + openssl \ + libssl3 \ + git \ + libkrb5-3 \ + libglib2.0-0 \ + wget \ + libaom3 \ + libxslt1.1 \ + libgnutls30 \ + libc6 \ + && apt-get install -y --no-install-recommends \ + libssl3 \ libatomic1 \ nodejs \ npm \ && rm -rf /var/lib/apt/lists/* \ - && npm install -g npm@latest tar@7.5.7 glob@11.1.0 @isaacs/brace-expansion@5.0.1 \ + && npm install -g npm@latest tar@7.5.8 glob@11.1.0 @isaacs/brace-expansion@5.0.1 minimatch@10.2.1 diff@8.0.3 \ && GLOBAL="$(npm root -g)" \ && find "$GLOBAL/npm" -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ @@ -73,6 +86,12 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ && find "$GLOBAL/npm" -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ done \ + && find "$GLOBAL/npm" -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done \ + && find "$GLOBAL/npm" -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ + done \ && npm cache clean --force WORKDIR /app @@ -95,14 +114,20 @@ RUN pip install --no-cache-dir *.whl /wheels/* --no-index --find-links=/wheels/ # npm with old vulnerable deps at /usr/lib/python3.*/site-packages/nodejs_wheel/. # Patch every copy of tar, glob, and brace-expansion inside that tree. RUN GLOBAL="$(npm root -g)" && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/tar" -type d | while read d; do \ + find /usr/lib -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/glob" -type d | while read d; do \ + find /usr/lib -type d -name "glob" -path "*/node_modules/glob" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/glob" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/@isaacs/brace-expansion" -type d | while read d; do \ + find /usr/lib -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ + done && \ + find /usr/lib -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find /usr/lib -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ done # Generate prisma client and set permissions diff --git a/docker/Dockerfile.non_root b/docker/Dockerfile.non_root index 004377e19b3..fda591df083 100644 --- a/docker/Dockerfile.non_root +++ b/docker/Dockerfile.non_root @@ -80,7 +80,7 @@ ENV PRISMA_BINARY_CACHE_DIR=/app/.cache/prisma-python/binaries \ XDG_CACHE_HOME=/app/.cache \ PATH="/usr/lib/python3.13/site-packages/nodejs/bin:${PATH}" -RUN pip install --no-cache-dir prisma==0.11.0 nodejs-wheel-binaries==24.12.0 \ +RUN pip install --no-cache-dir prisma==0.11.0 nodejs-wheel-binaries==24.13.1 \ && mkdir -p /app/.cache/npm RUN NPM_CONFIG_CACHE=/app/.cache/npm \ @@ -105,7 +105,8 @@ RUN for i in 1 2 3; do \ && for i in 1 2 3; do \ apk add --no-cache python3 py3-pip bash openssl tzdata nodejs npm supervisor && break || sleep 5; \ done \ - && npm install -g npm@latest tar@7.5.7 glob@11.1.0 @isaacs/brace-expansion@5.0.1 \ + && apk upgrade --no-cache nodejs \ + && npm install -g npm@latest tar@7.5.8 glob@11.1.0 @isaacs/brace-expansion@5.0.1 minimatch@10.2.1 diff@8.0.3 \ && GLOBAL="$(npm root -g)" \ && find "$GLOBAL/npm" -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ @@ -116,6 +117,12 @@ RUN for i in 1 2 3; do \ && find "$GLOBAL/npm" -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ done \ + && find "$GLOBAL/npm" -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done \ + && find "$GLOBAL/npm" -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ + done \ && npm cache clean --force # Copy artifacts from builder @@ -162,14 +169,20 @@ RUN pip install --no-index --find-links=/wheels/ -r requirements.txt && \ # npm with old vulnerable deps at /usr/lib/python3.*/site-packages/nodejs_wheel/. # Patch every copy of tar, glob, and brace-expansion inside that tree. RUN GLOBAL="$(npm root -g)" && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/tar" -type d | while read d; do \ + find /usr/lib -type d -name "tar" -path "*/node_modules/tar" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/tar" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/glob" -type d | while read d; do \ + find /usr/lib -type d -name "glob" -path "*/node_modules/glob" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/glob" "$d"; \ done && \ - find /usr/lib -path "*/nodejs_wheel/*/node_modules/@isaacs/brace-expansion" -type d | while read d; do \ + find /usr/lib -type d -name "brace-expansion" -path "*/node_modules/@isaacs/brace-expansion" | while read d; do \ rm -rf "$d" && cp -rL "$GLOBAL/@isaacs/brace-expansion" "$d"; \ + done && \ + find /usr/lib -type d -name "minimatch" -path "*/node_modules/minimatch" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/minimatch" "$d"; \ + done && \ + find /usr/lib -type d -name "diff" -path "*/node_modules/diff" | while read d; do \ + rm -rf "$d" && cp -rL "$GLOBAL/diff" "$d"; \ done # Permissions, cleanup, and Prisma prep diff --git a/docs/my-website/blog/gpt_5_3_codex/index.md b/docs/my-website/blog/gpt_5_3_codex/index.md new file mode 100644 index 00000000000..850586538f6 --- /dev/null +++ b/docs/my-website/blog/gpt_5_3_codex/index.md @@ -0,0 +1,145 @@ +--- +slug: gpt_5_3_codex +title: "Day 0 Support: GPT-5.3-Codex" +date: 2026-02-24T10:00:00 +authors: + - name: Sameer Kankute + title: SWE @ LiteLLM (LLM Translation) + url: https://www.linkedin.com/in/sameer-kankute/ + image_url: https://pbs.twimg.com/profile_images/2001352686994907136/ONgNuSk5_400x400.jpg + - name: Krrish Dholakia + title: "CEO, LiteLLM" + url: https://www.linkedin.com/in/krish-d/ + image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg + - name: Ishaan Jaff + title: "CTO, LiteLLM" + url: https://www.linkedin.com/in/reffajnaahsi/ + image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg +description: "Day 0 support for GPT-5.3-Codex on LiteLLM, including phase parameter handling for Responses API." +tags: [openai, gpt-5.3-codex, codex, day 0 support] +hide_table_of_contents: false +--- + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +LiteLLM now supports GPT-5.3-Codex on Day 0, including support for the new assistant `phase` metadata on Responses API output items. + +## Why `phase` matters for GPT-5.3-Codex + +`phase` appears on assistant output items and helps distinguish preamble/commentary turns from final closeout responses. + +Reference: [Phase parameter docs](https://developers.openai.com/api/reference/overview) + +Supported values: +- `null` +- `"commentary"` +- `"final_answer"` + +Important: +- Persist assistant output items with `phase` exactly as returned. +- Send those assistant items back on the next turn. +- Do **not** add `phase` to user messages. + +## Docker Image + +```bash +docker pull ghcr.io/berriai/litellm:v1.81.12-stable.gpt-5.3 +``` + +## Usage + + + + +**1. Setup config.yaml** + +```yaml +model_list: + - model_name: gpt-5.3-codex + litellm_params: + model: openai/gpt-5.3-codex +``` + +**2. Start the proxy** + +```bash +docker run -d \ + -p 4000:4000 \ + -e ANTHROPIC_API_KEY=$OPENAI_API_KEY \ + -v $(pwd)/config.yaml:/app/config.yaml \ + ghcr.io/berriai/litellm:v1.81.12-stable.gpt-5.3 \ + --config /app/config.yaml +``` + + +**3. Test it** + +```bash +curl -X POST "http://0.0.0.0:4000/v1/responses" \ + -H "Content-Type: application/json" \ + -H "Authorization: Bearer $LITELLM_KEY" \ + -d '{ + "model": "gpt-5.3-codex", + "input": "Write a Python script that checks if a number is prime." + }' +``` + + + + +## Python Example: Persist `phase` with OpenAI Client + LiteLLM Base URL + +```python +from openai import OpenAI + +client = OpenAI( + base_url="http://0.0.0.0:4000/v1", # LiteLLM Proxy + api_key="your-litellm-api-key", +) + +items = [] # Persist this per conversation/thread + + +def _item_get(item, key, default=None): + if isinstance(item, dict): + return item.get(key, default) + return getattr(item, key, default) + + +def run_turn(user_text: str): + global items + + # User message: no phase field + items.append( + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": user_text}], + } + ) + + resp = client.responses.create( + model="gpt-5.3-codex", + input=items, + ) + + # Persist assistant output items verbatim, including phase + for out_item in (resp.output or []): + items.append(out_item) + + # Optional: inspect latest phase for UI/telemetry routing + latest_phase = None + for out_item in reversed(resp.output or []): + if _item_get(out_item, "type") == "output_item.done" and _item_get(out_item, "phase") is not None: + latest_phase = _item_get(out_item, "phase") + break + + return resp, latest_phase +``` + +## Notes + +- Use `/v1/responses` for GPT Codex models. +- Preserve full assistant output history for best multi-turn behavior. +- If `phase` metadata is dropped during history reconstruction, output quality can degrade on long-running tasks. diff --git a/docs/my-website/docs/completion/prompt_caching.md b/docs/my-website/docs/completion/prompt_caching.md index 630c9e58d24..dca5f5c0cff 100644 --- a/docs/my-website/docs/completion/prompt_caching.md +++ b/docs/my-website/docs/completion/prompt_caching.md @@ -63,7 +63,6 @@ for _ in range(2): } ], }, - # marked for caching with the cache_control parameter, so that this checkpoint can read from the previous cache. { "role": "user", "content": [ @@ -77,7 +76,6 @@ for _ in range(2): "role": "assistant", "content": "Certainly! the key terms and conditions are the following: the contract is 1 year long for $10/mo", }, - # The final turn is marked with cache-control, for continuing in followups. { "role": "user", "content": [ @@ -112,16 +110,16 @@ model_list: api_key: os.environ/OPENAI_API_KEY ``` -2. Start proxy +2. Start proxy ```bash litellm --config /path/to/config.yaml ``` -3. Test it! +3. Test it! ```python -from openai import OpenAI +from openai import OpenAI import os client = OpenAI( @@ -144,7 +142,6 @@ for _ in range(2): } ], }, - # marked for caching with the cache_control parameter, so that this checkpoint can read from the previous cache. { "role": "user", "content": [ @@ -158,7 +155,6 @@ for _ in range(2): "role": "assistant", "content": "Certainly! the key terms and conditions are the following: the contract is 1 year long for $10/mo", }, - # The final turn is marked with cache-control, for continuing in followups. { "role": "user", "content": [ @@ -183,6 +179,78 @@ assert response.usage.prompt_tokens_details.cached_tokens > 0 +### OpenAI `prompt_cache_key` and `prompt_cache_retention` + +OpenAI prompt caching is [**automatic**](https://platform.openai.com/docs/guides/prompt-caching) — no `cache_control` message annotations are needed. Any request with 1024+ prompt tokens is eligible for caching. + +OpenAI also supports two optional parameters for more control over caching behavior: + +- **`prompt_cache_key`** (string) — A routing hint that improves cache hit rates for requests sharing long common prefixes. Requests with the same cache key are routed to the same backend, increasing the likelihood of a cache hit. +- **`prompt_cache_retention`** (`"in_memory"` or `"24h"`) — Controls cache TTL. Default is `"in_memory"` (5–10 min). Set to `"24h"` for extended caching that offloads KV tensors to GPU-local storage. + + + + +```python +from litellm import completion +import os + +os.environ["OPENAI_API_KEY"] = "" + +response = completion( + model="gpt-4o", + messages=[ + { + "role": "system", + "content": "You are an AI assistant tasked with analyzing legal documents. " + + "Here is the full text of a complex legal agreement " * 400, + }, + { + "role": "user", + "content": "What are the key terms and conditions?", + }, + ], + prompt_cache_key="legal-doc-analysis", + prompt_cache_retention="24h", +) +print(response.usage) +``` + + + + +```python +from openai import OpenAI + +client = OpenAI( + api_key="LITELLM_PROXY_KEY", + base_url="LITELLM_PROXY_BASE", +) + +response = client.chat.completions.create( + model="gpt-4o", + messages=[ + { + "role": "system", + "content": "You are an AI assistant tasked with analyzing legal documents. " + + "Here is the full text of a complex legal agreement " * 400, + }, + { + "role": "user", + "content": "What are the key terms and conditions?", + }, + ], + extra_body={ + "prompt_cache_key": "legal-doc-analysis", + "prompt_cache_retention": "24h", + }, +) +print(response.usage) +``` + + + + ### Anthropic Example Anthropic charges for cache writes. diff --git a/docs/my-website/docs/generateContent.md b/docs/my-website/docs/generateContent.md index 4453e5ce06d..bf8e1b6c03b 100644 --- a/docs/my-website/docs/generateContent.md +++ b/docs/my-website/docs/generateContent.md @@ -15,6 +15,7 @@ Use LiteLLM to call Google AI's generateContent endpoints for text generation, m | Streaming | ✅ | | | Fallbacks | ✅ | between supported models | | Loadbalancing | ✅ | between supported models | +| Metadata Tracking | ✅ | passes trace ID, metadata to observability callbacks (e.g. S3, Langfuse) | ## Usage --- diff --git a/docs/my-website/docs/mcp.md b/docs/my-website/docs/mcp.md index 50973f220f5..fcbb31c07d3 100644 --- a/docs/my-website/docs/mcp.md +++ b/docs/my-website/docs/mcp.md @@ -641,7 +641,7 @@ import asyncio config = { "mcpServers": { "mcp_group": { - "url": "http://localhost:4000/mcp", + "url": "http://localhost:4000/mcp/", "headers": { "x-mcp-servers": "dev_group", # assume this gives access to github, zapier and deepwiki "x-litellm-api-key": "Bearer sk-1234", diff --git a/docs/my-website/docs/proxy/prometheus.md b/docs/my-website/docs/proxy/prometheus.md index 93a0675f097..18a139d1d29 100644 --- a/docs/my-website/docs/proxy/prometheus.md +++ b/docs/my-website/docs/proxy/prometheus.md @@ -122,7 +122,7 @@ Use this to track overall LiteLLM Proxy usage. | Metric Name | Description | |----------------------|--------------------------------------| | `litellm_proxy_failed_requests_metric` | Total number of failed responses from proxy - the client did not get a success response from litellm proxy. Labels: `"end_user", "hashed_api_key", "api_key_alias", "requested_model", "team", "team_alias", "user", "user_email", "exception_status", "exception_class", "route", "model_id"` | -| `litellm_proxy_total_requests_metric` | Total number of requests made to the proxy server - track number of client side requests. Labels: `"end_user", "hashed_api_key", "api_key_alias", "requested_model", "team", "team_alias", "user", "status_code", "user_email", "route", "model_id"` | +| `litellm_proxy_total_requests_metric` | Total number of requests made to the proxy server - track number of client side requests. Labels: `"end_user", "hashed_api_key", "api_key_alias", "requested_model", "team", "team_alias", "user", "status_code", "user_email", "route", "model_id"`. Optionally includes `"stream"` — see [Emit Stream Label](#emit-stream-label). | ### Callback Logging Metrics @@ -214,9 +214,31 @@ litellm_settings: ``` +### Emit Stream Label + +Add a `stream` label to `litellm_proxy_total_requests_metric` to split requests by streaming vs. non-streaming. Disabled by default. + +```yaml title="config.yaml" +litellm_settings: + callbacks: ["prometheus"] + prometheus_emit_stream_label: true +``` + +When enabled, `litellm_proxy_total_requests_metric` gains a `stream` label with values `"True"`, `"False"`, or `"None"`. + +``` +litellm_proxy_total_requests_metric{..., stream="True"} 42 +litellm_proxy_total_requests_metric{..., stream="False"} 100 +``` + +:::note +This label is opt-in because adding a new label to an existing metric changes its cardinality and breaks existing Prometheus queries / Grafana dashboards that target this metric. Enable it only on fresh deployments or when you are ready to update your dashboards. +::: + + ## [BETA] Custom Metrics -Track custom metrics on prometheus on all events mentioned above. +Track custom metrics on prometheus on all events mentioned above. ### Custom Metadata Labels diff --git a/docs/my-website/docs/tutorials/presidio_pii_masking.md b/docs/my-website/docs/tutorials/presidio_pii_masking.md index ea3761163f2..d6fe1adbd01 100644 --- a/docs/my-website/docs/tutorials/presidio_pii_masking.md +++ b/docs/my-website/docs/tutorials/presidio_pii_masking.md @@ -592,6 +592,21 @@ def test_pii_masking_allows_normal_text(): ## Part 7: Troubleshooting +### Issue: Guardrail failure: non-JSON response from Presidio + +**Symptom:** You receive an error indicating `expected application/json Content-Type but received text/html` or similar. + +**Root cause:** Your ingress controller or reverse proxy might be routing the `/analyze` or `/anonymize` POST request to a health endpoint (like `/health` or `/presidio-analyzer/health`) which returns plain text instead of JSON. + +**Fix:** Ensure your `PRESIDIO_ANALYZER_API_BASE` and `PRESIDIO_ANONYMIZER_API_BASE` are correctly pointing directly to the Presidio API endpoints, or that your ingress routes the path correctly without stripping it and inadvertently forwarding to a plain-text health check endpoint. + +**Verification:** You can verify your endpoints using `curl`. It should return a JSON array, not `text/html`: +```bash +curl -sv -X POST http://your-analyzer-endpoint/analyze \ + -H "Content-Type: application/json" \ + -d '{"text":"test","language":"en"}' +``` + ### Issue: Presidio Not Detecting PII **Check 1: Language Configuration** diff --git a/docs/my-website/package.json b/docs/my-website/package.json index c4fa04c96a7..2dad6d0f16b 100644 --- a/docs/my-website/package.json +++ b/docs/my-website/package.json @@ -62,6 +62,8 @@ "gray-matter": "4.0.3", "glob": ">=11.1.0", "tar": ">=7.5.8", + "minimatch": ">=10.2.1", + "diff": ">=8.0.3", "@isaacs/brace-expansion": ">=5.0.1", "node-forge": ">=1.3.2", "mdast-util-to-hast": ">=13.2.1", @@ -81,6 +83,15 @@ "url-loader": { "ajv": "6.14.0" }, - "minimatch": "10.2.1" + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" } } \ No newline at end of file diff --git a/docs/my-website/release_notes/v1.81.12.md b/docs/my-website/release_notes/v1.81.12.md index a1f1daa2b92..0b7c1e146ab 100644 --- a/docs/my-website/release_notes/v1.81.12.md +++ b/docs/my-website/release_notes/v1.81.12.md @@ -1,5 +1,5 @@ --- -title: "v1.81.12-stable - Guardrail Policy Templates & Action Builder" +title: "v1.81.12-stable.1 - Guardrail Policy Templates & Action Builder" slug: "v1-81-12" date: 2026-02-14T00:00:00 authors: @@ -27,7 +27,7 @@ import Image from '@theme/IdealImage'; docker run \ -e STORE_MODEL_IN_DB=True \ -p 4000:4000 \ -ghcr.io/berriai/litellm:main-v1.81.12-stable +ghcr.io/berriai/litellm:main-v1.81.12-stable.1 ``` diff --git a/litellm-js/spend-logs/package.json b/litellm-js/spend-logs/package.json index 67292567145..5a7a08cb9ef 100644 --- a/litellm-js/spend-logs/package.json +++ b/litellm-js/spend-logs/package.json @@ -12,7 +12,19 @@ }, "overrides": { "glob": ">=11.1.0", - "tar": ">=7.5.7", - "@isaacs/brace-expansion": ">=5.0.1" + "tar": ">=7.5.8", + "minimatch": ">=10.2.1", + "diff": ">=8.0.3", + "@isaacs/brace-expansion": ">=5.0.1", + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" } -} +} \ No newline at end of file diff --git a/litellm/__init__.py b/litellm/__init__.py index 1e74b5692e4..6e42f2c1ea5 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -374,6 +374,7 @@ enable_end_user_cost_tracking_prometheus_only: Optional[bool] = None custom_prometheus_metadata_labels: List[str] = [] custom_prometheus_tags: List[str] = [] prometheus_metrics_config: Optional[List] = None +prometheus_emit_stream_label: bool = False disable_add_prefix_to_prompt: bool = ( False # used by anthropic, to disable adding prefix to prompt ) diff --git a/litellm/constants.py b/litellm/constants.py index ee79f2fa56f..b1a0021bcc6 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -244,6 +244,7 @@ REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY = "litellm_daily_tag_spend_update_buffer MAX_REDIS_BUFFER_DEQUEUE_COUNT = int(os.getenv("MAX_REDIS_BUFFER_DEQUEUE_COUNT", 100)) # Bounds asyncio.Queue() instances (log queues, spend update queues, etc.) to prevent unbounded memory growth LITELLM_ASYNCIO_QUEUE_MAXSIZE = int(os.getenv("LITELLM_ASYNCIO_QUEUE_MAXSIZE", 1000)) +TOOL_POLICY_CACHE_TTL_SECONDS = int(os.getenv("TOOL_POLICY_CACHE_TTL_SECONDS", 60)) # Aggregation threshold: default to 80% of the asyncio queue maxsize so the check can always trigger. # Must be < LITELLM_ASYNCIO_QUEUE_MAXSIZE; if set higher the aggregation logic will never fire. MAX_SIZE_IN_MEMORY_QUEUE = int( diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 4c7afd5a57c..08db77e8571 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -974,6 +974,9 @@ class PrometheusLogger(CustomLogger): ), client_ip=standard_logging_payload["metadata"].get("requester_ip_address"), user_agent=standard_logging_payload["metadata"].get("user_agent"), + stream=str(standard_logging_payload.get("stream")) + if litellm.prometheus_emit_stream_label + else None, ) if ( @@ -1624,6 +1627,9 @@ class PrometheusLogger(CustomLogger): client_ip=_metadata.get("requester_ip_address"), user_agent=_metadata.get("user_agent"), model_id=model_id, + stream=str(request_data.get("stream")) + if litellm.prometheus_emit_stream_label + else None, ) _labels = prometheus_label_factory( supported_enum_labels=self.get_labels_for_metric( diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index b42bf9e5711..759eaf60035 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -203,6 +203,129 @@ class RealTimeStreaming: return True return False + async def _handle_provider_config_message(self, raw_response) -> None: + """Process a backend message when a provider_config is set (transformed path).""" + returned_object = self.provider_config.transform_realtime_response( # type: ignore[union-attr] + raw_response, + self.model, + self.logging_obj, + realtime_response_transform_input={ + "session_configuration_request": self.session_configuration_request, + "current_output_item_id": self.current_output_item_id, + "current_response_id": self.current_response_id, + "current_delta_chunks": self.current_delta_chunks, + "current_conversation_id": self.current_conversation_id, + "current_item_chunks": self.current_item_chunks, + "current_delta_type": self.current_delta_type, + }, + ) + + transformed_response = returned_object["response"] + self.current_output_item_id = returned_object["current_output_item_id"] + self.current_response_id = returned_object["current_response_id"] + self.current_delta_chunks = returned_object["current_delta_chunks"] + self.current_conversation_id = returned_object["current_conversation_id"] + self.current_item_chunks = returned_object["current_item_chunks"] + self.current_delta_type = returned_object["current_delta_type"] + self.session_configuration_request = returned_object["session_configuration_request"] + events = ( + transformed_response + if isinstance(transformed_response, list) + else [transformed_response] + ) + for event in events: + ## GUARDRAIL: inject create_response=false on session.created + if isinstance(event, dict) and event.get("type") == "session.created": + if self._has_realtime_guardrails(): + await self.backend_ws.send( + json.dumps( + { + "type": "session.update", + "session": { + "turn_detection": { + "type": "server_vad", + "create_response": False, + } + }, + } + ) + ) + for event in events: + event_str = json.dumps(event) + ## GUARDRAIL: run on transcription events in provider_config path too + if ( + isinstance(event, dict) + and event.get("type") + == "conversation.item.input_audio_transcription.completed" + ): + transcript = event.get("transcript", "") + self.store_message(event_str) + await self.websocket.send_text(event_str) + blocked = await self.run_realtime_guardrails( + transcript, item_id=event.get("item_id") + ) + if not blocked: + await self.backend_ws.send( + json.dumps({"type": "response.create"}) + ) + continue + ## LOGGING + self.store_message(event_str) + await self.websocket.send_text(event_str) + + async def _handle_raw_backend_message(self, raw_response) -> bool: + """Process a backend message without provider_config (raw path). + + Returns True if the caller should skip the default store+forward (i.e. continue the loop). + """ + try: + event_obj = json.loads(raw_response) + + if event_obj.get("type") == "session.created": + # If any realtime guardrails are registered, proactively + # set create_response=false so the LLM never auto-responds + # before our guardrail has a chance to run. + if self._has_realtime_guardrails(): + await self.backend_ws.send( + json.dumps( + { + "type": "session.update", + "session": { + "turn_detection": { + "type": "server_vad", + "create_response": False, + } + }, + } + ) + ) + verbose_logger.debug( + "[realtime guardrail] injected create_response=false into session" + ) + + if ( + event_obj.get("type") + == "conversation.item.input_audio_transcription.completed" + ): + transcript = event_obj.get("transcript", "") + ## LOGGING — must happen before continue below + self.store_message(raw_response) + # Forward transcript to client so user sees what they said + await self.websocket.send_text(raw_response) + blocked = await self.run_realtime_guardrails( + transcript, + item_id=event_obj.get("item_id"), + ) + if not blocked: + # Clean — trigger LLM response + await self.backend_ws.send( + json.dumps({"type": "response.create"}) + ) + return True + except (json.JSONDecodeError, AttributeError): + pass + return False + async def backend_to_client_send_messages(self): import websockets @@ -216,128 +339,11 @@ class RealTimeStreaming: raw_response = await self.backend_ws.recv() # type: ignore[assignment] if self.provider_config: - returned_object = self.provider_config.transform_realtime_response( - raw_response, - self.model, - self.logging_obj, - realtime_response_transform_input={ - "session_configuration_request": self.session_configuration_request, - "current_output_item_id": self.current_output_item_id, - "current_response_id": self.current_response_id, - "current_delta_chunks": self.current_delta_chunks, - "current_conversation_id": self.current_conversation_id, - "current_item_chunks": self.current_item_chunks, - "current_delta_type": self.current_delta_type, - }, - ) - - transformed_response = returned_object["response"] - self.current_output_item_id = returned_object[ - "current_output_item_id" - ] - self.current_response_id = returned_object["current_response_id"] - self.current_delta_chunks = returned_object["current_delta_chunks"] - self.current_conversation_id = returned_object[ - "current_conversation_id" - ] - self.current_item_chunks = returned_object["current_item_chunks"] - self.current_delta_type = returned_object["current_delta_type"] - self.session_configuration_request = returned_object[ - "session_configuration_request" - ] - events = ( - transformed_response - if isinstance(transformed_response, list) - else [transformed_response] - ) - for event in events: - ## GUARDRAIL: inject create_response=false on session.created - if isinstance(event, dict) and event.get("type") == "session.created": - if self._has_realtime_guardrails(): - await self.backend_ws.send( - json.dumps( - { - "type": "session.update", - "session": { - "turn_detection": { - "type": "server_vad", - "create_response": False, - } - }, - } - ) - ) - for event in events: - event_str = json.dumps(event) - ## GUARDRAIL: run on transcription events in provider_config path too - if ( - isinstance(event, dict) - and event.get("type") - == "conversation.item.input_audio_transcription.completed" - ): - transcript = event.get("transcript", "") - self.store_message(event_str) - await self.websocket.send_text(event_str) - blocked = await self.run_realtime_guardrails( - transcript, item_id=event.get("item_id") - ) - if not blocked: - await self.backend_ws.send( - json.dumps({"type": "response.create"}) - ) - continue - ## LOGGING - self.store_message(event_str) - await self.websocket.send_text(event_str) - + await self._handle_provider_config_message(raw_response) else: - ## GUARDRAIL: intercept transcription events before triggering LLM - try: - event_obj = json.loads(raw_response) - - if event_obj.get("type") == "session.created": - # If any realtime guardrails are registered, proactively - # set create_response=false so the LLM never auto-responds - # before our guardrail has a chance to run. - if self._has_realtime_guardrails(): - await self.backend_ws.send( - json.dumps( - { - "type": "session.update", - "session": { - "turn_detection": { - "type": "server_vad", - "create_response": False, - } - }, - } - ) - ) - verbose_logger.debug( - "[realtime guardrail] injected create_response=false into session" - ) - - if ( - event_obj.get("type") - == "conversation.item.input_audio_transcription.completed" - ): - transcript = event_obj.get("transcript", "") - ## LOGGING — must happen before continue below - self.store_message(raw_response) - # Forward transcript to client so user sees what they said - await self.websocket.send_text(raw_response) - blocked = await self.run_realtime_guardrails( - transcript, - item_id=event_obj.get("item_id"), - ) - if not blocked: - # Clean — trigger LLM response - await self.backend_ws.send( - json.dumps({"type": "response.create"}) - ) - continue - except (json.JSONDecodeError, AttributeError): - pass + handled = await self._handle_raw_backend_message(raw_response) + if handled: + continue ## LOGGING self.store_message(raw_response) await self.websocket.send_text(raw_response) diff --git a/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen2_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen2_transformation.py index c532d8ea27c..2abcc679eef 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen2_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen2_transformation.py @@ -11,6 +11,7 @@ from typing import Any, List, Optional import httpx +from litellm.types.utils import Usage from litellm.llms.bedrock.chat.invoke_transformations.amazon_qwen3_transformation import ( AmazonQwen3Config, ) @@ -79,10 +80,11 @@ class AmazonQwen2Config(AmazonQwen3Config): # Set usage information if available in response if "usage" in response_data: usage_data = response_data["usage"] - if hasattr(model_response, 'usage'): - model_response.usage.prompt_tokens = usage_data.get("prompt_tokens", 0) - model_response.usage.completion_tokens = usage_data.get("completion_tokens", 0) - model_response.usage.total_tokens = usage_data.get("total_tokens", 0) + model_response.usage = Usage( + prompt_tokens=usage_data.get("prompt_tokens", 0), + completion_tokens=usage_data.get("completion_tokens", 0), + total_tokens=usage_data.get("total_tokens", 0), + ) return model_response diff --git a/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen3_transformation.py index b3a957ce0f8..12333623f51 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen3_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/amazon_qwen3_transformation.py @@ -10,6 +10,7 @@ from typing import Any, List, Optional import httpx +from litellm.types.utils import Usage from litellm.llms.base_llm.chat.transformation import BaseConfig from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation import ( AmazonInvokeConfig, @@ -201,10 +202,11 @@ class AmazonQwen3Config(AmazonInvokeConfig, BaseConfig): # Set usage information if available in response if "usage" in response_data: usage_data = response_data["usage"] - if hasattr(model_response, 'usage'): - model_response.usage.prompt_tokens = usage_data.get("prompt_tokens", 0) - model_response.usage.completion_tokens = usage_data.get("completion_tokens", 0) - model_response.usage.total_tokens = usage_data.get("total_tokens", 0) + model_response.usage = Usage( + prompt_tokens=usage_data.get("prompt_tokens", 0), + completion_tokens=usage_data.get("completion_tokens", 0), + total_tokens=usage_data.get("total_tokens", 0), + ) return model_response diff --git a/litellm/llms/bedrock/rerank/handler.py b/litellm/llms/bedrock/rerank/handler.py index 06f1e9e86c9..37167e7c330 100644 --- a/litellm/llms/bedrock/rerank/handler.py +++ b/litellm/llms/bedrock/rerank/handler.py @@ -29,12 +29,13 @@ class BedrockRerankHandler(BaseAWSLLM): async def arerank( self, prepared_request: BedrockPreparedRequest, + timeout: Optional[Union[float, httpx.Timeout]] = None, client: Optional[AsyncHTTPHandler] = None, ): if client is None: client = get_async_httpx_client(llm_provider=litellm.LlmProviders.BEDROCK) try: - response = await client.post(url=prepared_request["endpoint_url"], headers=dict(prepared_request["prepped"].headers), data=prepared_request["body"]) + response = await client.post(url=prepared_request["endpoint_url"], headers=dict(prepared_request["prepped"].headers), data=prepared_request["body"], timeout=timeout) response.raise_for_status() except httpx.HTTPStatusError as err: error_code = err.response.status_code @@ -56,6 +57,7 @@ class BedrockRerankHandler(BaseAWSLLM): return_documents: Optional[bool] = True, max_chunks_per_doc: Optional[int] = None, _is_async: Optional[bool] = False, + timeout: Optional[Union[float, httpx.Timeout]] = None, api_base: Optional[str] = None, extra_headers: Optional[dict] = None, client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None, @@ -89,12 +91,12 @@ class BedrockRerankHandler(BaseAWSLLM): ) if _is_async: - return self.arerank(prepared_request, client=client if client is not None and isinstance(client, AsyncHTTPHandler) else None) # type: ignore + return self.arerank(prepared_request, timeout=timeout, client=client if client is not None and isinstance(client, AsyncHTTPHandler) else None) # type: ignore if client is None or not isinstance(client, HTTPHandler): client = _get_httpx_client() try: - response = client.post(url=prepared_request["endpoint_url"], headers=dict(prepared_request["prepped"].headers), data=prepared_request["body"]) + response = client.post(url=prepared_request["endpoint_url"], headers=dict(prepared_request["prepped"].headers), data=prepared_request["body"], timeout=timeout) response.raise_for_status() except httpx.HTTPStatusError as err: error_code = err.response.status_code diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py index aa8471a5973..ab102a69670 100644 --- a/litellm/llms/openai/chat/gpt_transformation.py +++ b/litellm/llms/openai/chat/gpt_transformation.py @@ -162,6 +162,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig): "service_tier", "safety_identifier", "prompt_cache_key", + "prompt_cache_retention", "store", ] # works across all models diff --git a/litellm/llms/openai/chat/o_series_transformation.py b/litellm/llms/openai/chat/o_series_transformation.py index 30647f58687..6ef43ec5bfd 100644 --- a/litellm/llms/openai/chat/o_series_transformation.py +++ b/litellm/llms/openai/chat/o_series_transformation.py @@ -131,9 +131,7 @@ class OpenAIOSeriesConfig(OpenAIGPTConfig): def is_model_o_series_model(self, model: str) -> bool: model = model.split("/")[-1] # could be "openai/o3" or "o3" - return model in litellm.open_ai_chat_completion_models and any( - model.startswith(pfx) for pfx in ("o1", "o3", "o4") - ) + return model.startswith(("o1", "o3", "o4")) and model in litellm.open_ai_chat_completion_models @overload def _transform_messages( @@ -173,4 +171,4 @@ class OpenAIOSeriesConfig(OpenAIGPTConfig): else: return super()._transform_messages( messages, model, is_async=cast(Literal[False], False) - ) + ) \ No newline at end of file diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 3909ce4c8b0..e4d7a6a02f2 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -20562,6 +20562,39 @@ "supports_tool_choice": true, "supports_vision": true }, + "gpt-5.3-codex": { + "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_priority": 3.5e-07, + "input_cost_per_token": 1.75e-06, + "input_cost_per_token_priority": 3.5e-06, + "litellm_provider": "openai", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 1.4e-05, + "output_cost_per_token_priority": 2.8e-05, + "supported_endpoints": [ + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": false, + "supports_tool_choice": true, + "supports_vision": true + }, "gpt-5-mini": { "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, @@ -26555,65 +26588,124 @@ "supports_function_calling": true, "supports_tool_choice": true }, + "perplexity/preset/fast-search": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_preset": true, + "supports_function_calling": true + }, "perplexity/preset/pro-search": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_preset": true + "supports_preset": true, + "supports_function_calling": true }, - "perplexity/openai/gpt-4o": { + "perplexity/preset/deep-research": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_preset": true, + "supports_function_calling": true }, - "perplexity/openai/gpt-4o-mini": { + "perplexity/preset/advanced-deep-research": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_preset": true, + "supports_function_calling": true }, "perplexity/openai/gpt-5.2": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": true + "supports_reasoning": true, + "supports_function_calling": true }, - "perplexity/anthropic/claude-3-5-sonnet-20241022": { + "perplexity/openai/gpt-5.1": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_reasoning": false, + "supports_function_calling": true }, - "perplexity/anthropic/claude-3-5-haiku-20241022": { + "perplexity/openai/gpt-5-mini": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_reasoning": false, + "supports_function_calling": true }, - "perplexity/google/gemini-2.0-flash-exp": { + "perplexity/anthropic/claude-opus-4-6": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_reasoning": false, + "supports_function_calling": true }, - "perplexity/google/gemini-2.0-flash-thinking-exp": { + "perplexity/anthropic/claude-opus-4-5": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": true + "supports_reasoning": false, + "supports_function_calling": true }, - "perplexity/xai/grok-2-1212": { + "perplexity/anthropic/claude-sonnet-4-5": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_reasoning": false, + "supports_function_calling": true }, - "perplexity/xai/grok-2-vision-1212": { + "perplexity/anthropic/claude-haiku-4-5": { "litellm_provider": "perplexity", "mode": "responses", "supports_web_search": true, - "supports_reasoning": false + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/google/gemini-3-pro-preview": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/google/gemini-3-flash-preview": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/google/gemini-2.5-pro": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/google/gemini-2.5-flash": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/xai/grok-4-1-fast-non-reasoning": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true + }, + "perplexity/perplexity/sonar": { + "litellm_provider": "perplexity", + "mode": "responses", + "supports_web_search": true, + "supports_reasoning": false, + "supports_function_calling": true }, "publicai/aisingapore/Qwen-SEA-LION-v4-32B-IT": { "input_cost_per_token": 0.0, diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py index 581671598c6..6e1a252be73 100644 --- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py +++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py @@ -10,6 +10,7 @@ from litellm.proxy._experimental.mcp_server.ui_session_utils import ( ) from litellm.proxy._experimental.mcp_server.utils import merge_mcp_headers from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_headers from litellm.proxy.auth.ip_address_utils import IPAddressUtils from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.types.mcp import MCPAuth @@ -685,7 +686,7 @@ if MCP_AVAILABLE: return await _execute_with_mcp_client( new_mcp_server_request, _test_connection_operation, - raw_headers=dict(request.headers), + raw_headers=_safe_get_request_headers(request), ) @router.post("/test/tools/list") @@ -744,5 +745,5 @@ if MCP_AVAILABLE: _list_tools_operation, mcp_auth_header=mcp_auth_header, oauth2_headers=oauth2_headers, - raw_headers=dict(request.headers), + raw_headers=_safe_get_request_headers(request), ) diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index 95739834a9a..4053d9d077b 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -183,6 +183,7 @@ class LitellmTableNames(str, enum.Enum): KEY_TABLE_NAME = "LiteLLM_VerificationToken" PROXY_MODEL_TABLE_NAME = "LiteLLM_ProxyModelTable" MANAGED_FILE_TABLE_NAME = "LiteLLM_ManagedFileTable" + TOOL_TABLE_NAME = "LiteLLM_ToolTable" class Litellm_EntityType(enum.Enum): @@ -850,6 +851,7 @@ class GenerateRequestBase(LiteLLMPydanticObjectBase): max_budget: Optional[float] = None user_id: Optional[str] = None team_id: Optional[str] = None + agent_id: Optional[str] = None max_parallel_requests: Optional[int] = None metadata: Optional[dict] = {} tpm_limit: Optional[int] = None @@ -2079,6 +2081,13 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): health_check_interval: int = Field( 300, description="background health check interval in seconds" ) + health_check_concurrency: Optional[int] = Field( + None, + description=( + "limit concurrent health checks per cycle; when unset, " + "health checks run without a concurrency cap" + ), + ) alerting: Optional[List] = Field( None, description="List of alerting integrations. Today, just slack - `alerting: ['slack']`", @@ -4116,6 +4125,15 @@ class SpendUpdateQueueItem(TypedDict, total=False): response_cost: Optional[float] +class ToolDiscoveryQueueItem(TypedDict, total=False): + tool_name: str + origin: Optional[str] # MCP server name or "user_defined" + created_by: Optional[str] + key_hash: Optional[str] # hash of virtual key that triggered discovery + team_id: Optional[str] # team that triggered discovery + key_alias: Optional[str] # human-readable key alias + + class LiteLLM_ManagedFileTable(LiteLLMPydanticObjectBase): unified_file_id: str file_object: Optional[OpenAIFileObject] = None diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 138f9bab2c4..8f17440773a 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -483,7 +483,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 parent_otel_span = ( open_telemetry_logger.create_litellm_proxy_request_started_span( start_time=start_time, - headers=dict(request.headers), + headers=_safe_get_request_headers(request), ) ) @@ -562,7 +562,7 @@ async def _user_api_key_auth_builder( # noqa: PLR0915 user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, parent_otel_span=parent_otel_span, - request_headers=dict(request.headers), + request_headers=_safe_get_request_headers(request), ) is_proxy_admin = result["is_proxy_admin"] diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index e1bca6e905f..8d179a9caed 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -135,17 +135,29 @@ def _safe_set_request_parsed_body( def _safe_get_request_headers(request: Optional[Request]) -> dict: """ - [Non-Blocking] Safely get the request headers + [Non-Blocking] Safely get the request headers. + Caches the result on request.state to avoid re-creating dict(request.headers) per call. + + Warning: Callers must NOT mutate the returned dict — it is shared across + all callers within the same request via the cache. """ + if request is None: + return {} + cached = getattr(request.state, "_cached_headers", None) + if cached is not None: + return cached try: - if request is None: - return {} - return dict(request.headers) + headers = dict(request.headers) except Exception as e: verbose_proxy_logger.debug( "Unexpected error reading request headers - {}".format(e) ) - return {} + headers = {} + try: + request.state._cached_headers = headers + except Exception: + pass # request.state may not be available in all contexts + return headers def check_file_size_under_limit( diff --git a/litellm/proxy/custom_hooks/custom_ui_sso_hook.py b/litellm/proxy/custom_hooks/custom_ui_sso_hook.py index cad0e62ff56..8bb6b274091 100644 --- a/litellm/proxy/custom_hooks/custom_ui_sso_hook.py +++ b/litellm/proxy/custom_hooks/custom_ui_sso_hook.py @@ -3,6 +3,7 @@ from fastapi_sso.sso.base import OpenID from litellm._logging import verbose_logger from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_headers class CustomSSOLoginHandler(CustomLogger): @@ -18,7 +19,7 @@ class CustomSSOLoginHandler(CustomLogger): self, request: Request, ) -> OpenID: - request_headers_dict = dict(request.headers) + request_headers_dict = _safe_get_request_headers(request) verbose_logger.debug("inside custom ui sso sign in hook...") return OpenID( id=request_headers_dict.get("x-litellm-user-id") or "123", diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py index 03628fda47f..edf0cf0d397 100644 --- a/litellm/proxy/db/db_spend_update_writer.py +++ b/litellm/proxy/db/db_spend_update_writer.py @@ -13,7 +13,17 @@ import random import time import traceback from datetime import datetime, timedelta, timezone -from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union, cast, overload +from typing import ( + TYPE_CHECKING, + Any, + Dict, + List, + Literal, + Optional, + Union, + cast, + overload, +) import litellm from litellm._logging import verbose_proxy_logger @@ -23,18 +33,19 @@ from litellm.litellm_core_utils.safe_json_loads import safe_json_loads from litellm.proxy._types import ( DB_CONNECTION_ERROR_TYPES, BaseDailySpendTransaction, - DailyTagSpendTransaction, - DailyOrganizationSpendTransaction, - DailyTeamSpendTransaction, - DailyEndUserSpendTransaction, - DailyUserSpendTransaction, DailyAgentSpendTransaction, + DailyEndUserSpendTransaction, + DailyOrganizationSpendTransaction, + DailyTagSpendTransaction, + DailyTeamSpendTransaction, + DailyUserSpendTransaction, DBSpendUpdateTransactions, Litellm_EntityType, LiteLLM_UserTable, SpendLogsMetadata, SpendLogsPayload, SpendUpdateQueueItem, + ToolDiscoveryQueueItem, ) from litellm.proxy.db.db_transaction_queue.daily_spend_update_queue import ( DailySpendUpdateQueue, @@ -42,6 +53,9 @@ from litellm.proxy.db.db_transaction_queue.daily_spend_update_queue import ( from litellm.proxy.db.db_transaction_queue.pod_lock_manager import PodLockManager from litellm.proxy.db.db_transaction_queue.redis_update_buffer import RedisUpdateBuffer from litellm.proxy.db.db_transaction_queue.spend_update_queue import SpendUpdateQueue +from litellm.proxy.db.db_transaction_queue.tool_discovery_queue import ( + ToolDiscoveryQueue, +) from litellm.proxy.route_llm_request import ROUTE_ENDPOINT_MAPPING if TYPE_CHECKING: @@ -67,6 +81,7 @@ class DBSpendUpdateWriter: self.redis_update_buffer = RedisUpdateBuffer(redis_cache=self.redis_cache) self.pod_lock_manager = PodLockManager() self.spend_update_queue = SpendUpdateQueue() + self.tool_discovery_queue = ToolDiscoveryQueue() self.daily_spend_update_queue = DailySpendUpdateQueue() self.daily_team_spend_update_queue = DailySpendUpdateQueue() self.daily_end_user_spend_update_queue = DailySpendUpdateQueue() @@ -222,10 +237,124 @@ class DBSpendUpdateWriter: ) ) + self._enqueue_tool_registry_upsert( + kwargs=kwargs, + completion_response=completion_response, + hashed_token=hashed_token, + team_id=team_id, + ) + verbose_proxy_logger.debug("Runs spend update on all tables") except Exception: + verbose_proxy_logger.error( + "Spend tracking - update_database failed. Spend log insertion or daily transaction enqueue " + "may not have completed for this request. " + "response_cost=%s, token=%s, user_id=%s, team_id=%s, org_id=%s, end_user_id=%s - %s", + response_cost, + token, + user_id, + team_id, + org_id, + end_user_id, + traceback.format_exc(), + ) + + def _enqueue_tool_registry_upsert( + self, + kwargs: Optional[dict], + completion_response: Optional[Any], + hashed_token: Optional[str] = None, + team_id: Optional[str] = None, + ) -> None: + """ + Extract tool names from the LLM request and response and enqueue them + for upsert into LiteLLM_ToolTable via ToolDiscoveryQueue. + + Handles four sources: + - MCP tools: standard_logging_object.mcp_tool_call_metadata.namespaced_tool_name + - Response tool_calls (OpenAI / Anthropic pass-through converted to OpenAI format): + completion_response.choices[].message.tool_calls[].function.name + - Request tools array (OpenAI format): kwargs["tools"][].function.name + - Request tools array (Anthropic /messages format): kwargs["passthrough_logging_payload"] + ["request_body"]["tools"][].name + """ + try: + if kwargs is None: + return + + # Extract key_alias from kwargs metadata if available + key_alias: Optional[str] = None + _litellm_params = kwargs.get("litellm_params") or {} + _metadata = _litellm_params.get("metadata") or {} + key_alias = _metadata.get("user_api_key_alias") or None + + def _enqueue(tool_name: str, origin: str = "user_defined") -> None: + self.tool_discovery_queue.add_update( + ToolDiscoveryQueueItem( + tool_name=tool_name, + origin=origin, + key_hash=hashed_token, + team_id=team_id, + key_alias=key_alias, + ) + ) + + # --- MCP tool calls --- + sl_object = kwargs.get("standard_logging_object") + if sl_object is not None: + mcp_metadata = ( + sl_object.get("metadata", {}) or {} + ).get("mcp_tool_call_metadata") + if mcp_metadata and isinstance(mcp_metadata, dict): + tool_name = mcp_metadata.get("namespaced_tool_name") or mcp_metadata.get("name") + mcp_server_name = mcp_metadata.get("mcp_server_name") + if tool_name: + _enqueue(tool_name, origin=mcp_server_name or "user_defined") + + # --- Tools from request body (OpenAI format: tools[].function.name) --- + request_tools = kwargs.get("tools") or [] + for tool_def in request_tools: + if not isinstance(tool_def, dict): + continue + fn = tool_def.get("function") or {} + name = fn.get("name") if isinstance(fn, dict) else None + if name: + _enqueue(name) + + # --- Tools from Anthropic /messages pass-through request body + # (Anthropic format: tools[].name, no "function" wrapper) --- + passthrough_payload = kwargs.get("passthrough_logging_payload") or {} + request_body = ( + passthrough_payload.get("request_body") + if isinstance(passthrough_payload, dict) + else None + ) or {} + for tool_def in request_body.get("tools") or []: + if not isinstance(tool_def, dict): + continue + name = tool_def.get("name") + if name: + _enqueue(name) + + # --- Response tool_calls (OpenAI format; Anthropic pass-through converts tool_use here) --- + if completion_response is not None and hasattr(completion_response, "choices"): + for choice in completion_response.choices or []: + message = getattr(choice, "message", None) + if message is None: + continue + tool_calls = getattr(message, "tool_calls", None) + if not tool_calls: + continue + for tc in tool_calls: + fn = getattr(tc, "function", None) + if fn is None: + continue + tool_name = getattr(fn, "name", None) + if tool_name: + _enqueue(tool_name) + except Exception as e: verbose_proxy_logger.debug( - f"Error updating Prisma database: {traceback.format_exc()}" + "_enqueue_tool_registry_upsert error (non-blocking): %s", e ) async def _update_key_db( @@ -295,9 +424,14 @@ class DBSpendUpdateWriter: ) ) except Exception as e: - verbose_proxy_logger.debug( - "\033[91m" - + f"Update User DB call failed to execute {str(e)}\n{traceback.format_exc()}" + verbose_proxy_logger.error( + "Spend tracking - failed to enqueue user spend update. " + "user_id=%s, end_user_id=%s, response_cost=%s - %s\n%s", + user_id, + end_user_id, + response_cost, + str(e), + traceback.format_exc(), ) async def _update_team_db( @@ -334,11 +468,24 @@ class DBSpendUpdateWriter: response_cost=response_cost, ) ) - except Exception: - pass + except Exception as e: + verbose_proxy_logger.error( + "Spend tracking - failed to enqueue team member spend update. " + "team_id=%s, user_id=%s, response_cost=%s - %s\n%s", + team_id, + user_id, + response_cost, + str(e), + traceback.format_exc(), + ) except Exception as e: - verbose_proxy_logger.debug( - f"Update Team DB failed to execute - {str(e)}\n{traceback.format_exc()}" + verbose_proxy_logger.error( + "Spend tracking - failed to enqueue team spend update. " + "team_id=%s, response_cost=%s - %s\n%s", + team_id, + response_cost, + str(e), + traceback.format_exc(), ) raise e @@ -363,8 +510,13 @@ class DBSpendUpdateWriter: ) ) except Exception as e: - verbose_proxy_logger.debug( - f"Update Org DB failed to execute - {str(e)}\n{traceback.format_exc()}" + verbose_proxy_logger.error( + "Spend tracking - failed to enqueue org spend update. " + "org_id=%s, response_cost=%s - %s\n%s", + org_id, + response_cost, + str(e), + traceback.format_exc(), ) raise e @@ -411,8 +563,13 @@ class DBSpendUpdateWriter: ) ) except Exception as e: - verbose_proxy_logger.debug( - f"Update Tag DB failed to execute - {str(e)}\n{traceback.format_exc()}" + verbose_proxy_logger.error( + "Spend tracking - failed to enqueue tag spend update. " + "request_tags=%s, response_cost=%s - %s\n%s", + request_tags, + response_cost, + str(e), + traceback.format_exc(), ) raise e @@ -513,6 +670,17 @@ class DBSpendUpdateWriter: await self.redis_update_buffer.get_all_update_transactions_from_redis_buffer() ) if db_spend_update_transactions is not None: + verbose_proxy_logger.info( + "Spend tracking - committing spend updates from Redis to DB: " + "keys=%d, users=%d, teams=%d, orgs=%d, end_users=%d, team_members=%d, tags=%d", + len(db_spend_update_transactions.get("key_list_transactions") or {}), + len(db_spend_update_transactions.get("user_list_transactions") or {}), + len(db_spend_update_transactions.get("team_list_transactions") or {}), + len(db_spend_update_transactions.get("org_list_transactions") or {}), + len(db_spend_update_transactions.get("end_user_list_transactions") or {}), + len(db_spend_update_transactions.get("team_member_list_transactions") or {}), + len(db_spend_update_transactions.get("tag_list_transactions") or {}), + ) await self._commit_spend_updates_to_db( prisma_client=prisma_client, n_retry_times=n_retry_times, @@ -583,7 +751,12 @@ class DBSpendUpdateWriter: daily_spend_transactions=daily_agent_spend_update_transactions, ) except Exception as e: - verbose_proxy_logger.error(f"Error committing spend updates: {e}") + verbose_proxy_logger.error( + "Spend tracking - failed to commit spend updates from Redis to DB. " + "Data already popped from Redis may be lost. Error: %s\n%s", + str(e), + traceback.format_exc(), + ) finally: await self.pod_lock_manager.release_lock( cronjob_id=DB_SPEND_UPDATE_JOB_NAME, @@ -699,6 +872,25 @@ class DBSpendUpdateWriter: daily_spend_transactions=daily_agent_spend_update_transactions, ) + ################## Tool Registry Upserts ################## + await self._flush_tool_discovery_queue(prisma_client=prisma_client) + + async def _flush_tool_discovery_queue( + self, + prisma_client: PrismaClient, + ) -> None: + """Flush ToolDiscoveryQueue and batch-upsert new tools into LiteLLM_ToolTable.""" + from litellm.proxy.db.tool_registry_writer import batch_upsert_tools + + try: + items = self.tool_discovery_queue.flush() + if items: + await batch_upsert_tools(prisma_client=prisma_client, items=items) + except Exception as e: + verbose_proxy_logger.debug( + "_flush_tool_discovery_queue error (non-blocking): %s", e + ) + async def _commit_spend_updates_to_db( # noqa: PLR0915 self, prisma_client: PrismaClient, diff --git a/litellm/proxy/db/db_transaction_queue/daily_spend_update_queue.py b/litellm/proxy/db/db_transaction_queue/daily_spend_update_queue.py index 5ba8fb13596..f47b694d44e 100644 --- a/litellm/proxy/db/db_transaction_queue/daily_spend_update_queue.py +++ b/litellm/proxy/db/db_transaction_queue/daily_spend_update_queue.py @@ -86,6 +86,11 @@ class DailySpendUpdateQueue(BaseUpdateQueue): ) -> Dict[str, BaseDailySpendTransaction]: """Get all updates from the queue and return all updates aggregated by daily_transaction_key. Works for both user and team spend updates.""" updates = await self.flush_all_updates_from_in_memory_queue() + if len(updates) > 0: + verbose_proxy_logger.info( + "Spend tracking - flushed %d daily spend update items from in-memory queue", + len(updates), + ) aggregated_daily_spend_update_transactions = ( DailySpendUpdateQueue.get_aggregated_daily_spend_update_transactions( updates diff --git a/litellm/proxy/db/db_transaction_queue/pod_lock_manager.py b/litellm/proxy/db/db_transaction_queue/pod_lock_manager.py index bb5424b0e90..6f86e82cf29 100644 --- a/litellm/proxy/db/db_transaction_queue/pod_lock_manager.py +++ b/litellm/proxy/db/db_transaction_queue/pod_lock_manager.py @@ -80,6 +80,14 @@ class PodLockManager: ) self._emit_acquired_lock_event(cronjob_id, self.pod_id) return True + else: + verbose_proxy_logger.info( + "Spend tracking - pod %s could not acquire lock for cronjob_id=%s, " + "held by pod %s. Spend updates in Redis will wait for the leader pod to commit.", + self.pod_id, + cronjob_id, + current_value, + ) return False except Exception as e: verbose_proxy_logger.error( @@ -124,10 +132,12 @@ class PodLockManager: pod_id=self.pod_id, ) else: - verbose_proxy_logger.debug( - "Pod %s failed to release Redis lock for cronjob_id=%s", + verbose_proxy_logger.warning( + "Spend tracking - pod %s failed to release Redis lock for cronjob_id=%s. " + "Lock will expire after TTL=%ds.", self.pod_id, cronjob_id, + DEFAULT_CRON_JOB_LOCK_TTL_SECONDS, ) else: verbose_proxy_logger.debug( diff --git a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py index 37b42e26bc9..027f3e639e3 100644 --- a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py +++ b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py @@ -96,14 +96,28 @@ class RedisUpdateBuffer: list_of_transactions = [safe_dumps(transactions)] if self.redis_cache is None: return - current_redis_buffer_size = await self.redis_cache.async_rpush( - key=redis_key, - values=list_of_transactions, - ) - await self._emit_new_item_added_to_redis_buffer_event( - queue_size=current_redis_buffer_size, - service=service_type, - ) + try: + current_redis_buffer_size = await self.redis_cache.async_rpush( + key=redis_key, + values=list_of_transactions, + ) + verbose_proxy_logger.debug( + "Spend tracking - pushed spend updates to Redis buffer. " + "redis_key=%s, buffer_size=%s", + redis_key, + current_redis_buffer_size, + ) + await self._emit_new_item_added_to_redis_buffer_event( + queue_size=current_redis_buffer_size, + service=service_type, + ) + except Exception as e: + verbose_proxy_logger.error( + "Spend tracking - failed to push spend updates to Redis (redis_key=%s). " + "Error: %s", + redis_key, + str(e), + ) async def store_in_memory_spend_updates_in_redis( self, @@ -305,6 +319,13 @@ class RedisUpdateBuffer: if list_of_transactions is None: return None + verbose_proxy_logger.info( + "Spend tracking - popped %d spend update batches from Redis buffer (key=%s). " + "These items are now removed from Redis and must be committed to DB.", + len(list_of_transactions) if isinstance(list_of_transactions, list) else 1, + REDIS_UPDATE_BUFFER_KEY, + ) + # Parse the list of transactions from JSON strings parsed_transactions = self._parse_list_of_transactions(list_of_transactions) diff --git a/litellm/proxy/db/db_transaction_queue/spend_update_queue.py b/litellm/proxy/db/db_transaction_queue/spend_update_queue.py index b41ff121622..3e059cf8c1f 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_update_queue.py +++ b/litellm/proxy/db/db_transaction_queue/spend_update_queue.py @@ -31,6 +31,11 @@ class SpendUpdateQueue(BaseUpdateQueue): ) -> DBSpendUpdateTransactions: """Flush all updates from the queue and return all updates aggregated by entity type.""" updates = await self.flush_all_updates_from_in_memory_queue() + if len(updates) > 0: + verbose_proxy_logger.info( + "Spend tracking - flushed %d spend update items from in-memory queue", + len(updates), + ) verbose_proxy_logger.debug("Aggregating updates by entity type: %s", updates) return self.get_aggregated_db_spend_update_transactions(updates) diff --git a/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py b/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py new file mode 100644 index 00000000000..16a3ada40f2 --- /dev/null +++ b/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py @@ -0,0 +1,54 @@ +""" +In-memory buffer for tool registry upserts. + +Unlike SpendUpdateQueue (which aggregates increments), ToolDiscoveryQueue +uses set-deduplication: each unique tool_name is only queued once per flush +cycle (~30s). The seen-set is cleared on every flush so that call_count +increments in subsequent cycles rather than stopping after the first flush. +""" + +from typing import List, Set + +from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import ToolDiscoveryQueueItem + + +class ToolDiscoveryQueue: + """ + In-memory buffer for tool registry upserts. + + Deduplicates by tool_name within each flush cycle: a tool is only queued + once per ~30s batch, so call_count increments once per flush cycle the + tool appears in (not once per invocation, but not once per pod lifetime + either). The seen-set is cleared on flush so subsequent batches can + re-count the same tool. + """ + + def __init__(self) -> None: + self._seen_tool_names: Set[str] = set() + self._pending: List[ToolDiscoveryQueueItem] = [] + + def add_update(self, item: ToolDiscoveryQueueItem) -> None: + """Enqueue a tool discovery item if tool_name has not been seen before.""" + tool_name = item.get("tool_name", "") + if not tool_name: + return + if tool_name in self._seen_tool_names: + verbose_proxy_logger.debug( + "ToolDiscoveryQueue: skipping already-seen tool %s", tool_name + ) + return + self._seen_tool_names.add(tool_name) + self._pending.append(item) + verbose_proxy_logger.debug( + "ToolDiscoveryQueue: queued new tool %s (origin=%s)", + tool_name, + item.get("origin"), + ) + + def flush(self) -> List[ToolDiscoveryQueueItem]: + """Return and clear all pending items. Resets seen-set so the next + flush cycle can re-count the same tools.""" + items, self._pending = self._pending, [] + self._seen_tool_names.clear() + return items diff --git a/litellm/proxy/db/tool_registry_writer.py b/litellm/proxy/db/tool_registry_writer.py new file mode 100644 index 00000000000..4e0a8095a08 --- /dev/null +++ b/litellm/proxy/db/tool_registry_writer.py @@ -0,0 +1,179 @@ +""" +DB helpers for LiteLLM_ToolTable — the global tool registry. + +Tools are auto-discovered from LLM responses and upserted here. +Admins use the management endpoints to read and update call_policy. + +NOTE: Uses raw SQL (query_raw / execute_raw) instead of Prisma model methods +because the generated Prisma Python client may not have LiteLLM_ToolTable +when running against an older generated schema. +""" + +import uuid +from datetime import datetime, timezone +from typing import TYPE_CHECKING, Dict, List, Optional + +from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import ToolDiscoveryQueueItem +from litellm.types.tool_management import LiteLLM_ToolTableRow, ToolCallPolicy + +if TYPE_CHECKING: + from litellm.proxy.utils import PrismaClient + + +def _row_to_model(row: dict) -> LiteLLM_ToolTableRow: + return LiteLLM_ToolTableRow( + tool_id=row.get("tool_id", ""), + tool_name=row.get("tool_name", ""), + origin=row.get("origin"), + call_policy=row.get("call_policy", "untrusted"), + call_count=int(row.get("call_count") or 0), + assignments=row.get("assignments"), + key_hash=row.get("key_hash"), + team_id=row.get("team_id"), + key_alias=row.get("key_alias"), + created_at=row.get("created_at"), + updated_at=row.get("updated_at"), + created_by=row.get("created_by"), + updated_by=row.get("updated_by"), + ) + + +async def batch_upsert_tools( + prisma_client: "PrismaClient", + items: List[ToolDiscoveryQueueItem], +) -> None: + """ + Batch-upsert tool registry rows via raw SQL. + + On first insert: sets call_policy = "untrusted" (schema default), call_count = 1. + On conflict: increments call_count; preserves existing call_policy. + """ + if not items: + return + try: + data = [item for item in items if item.get("tool_name")] + if not data: + return + for item in data: + tool_name = item.get("tool_name", "") + origin = item.get("origin") or "user_defined" + created_by = item.get("created_by") or "system" + key_hash = item.get("key_hash") + team_id = item.get("team_id") + key_alias = item.get("key_alias") + now = datetime.now(timezone.utc).isoformat() + await prisma_client.db.execute_raw( + 'INSERT INTO "LiteLLM_ToolTable" ' + "(tool_id, tool_name, origin, call_policy, call_count, created_by, updated_by, key_hash, team_id, key_alias, created_at, updated_at) " + "VALUES ($7, $1, $2, 'untrusted', 1, $3, $3, $4, $5, $6, $8, $8) " + "ON CONFLICT (tool_name) DO UPDATE SET " + "call_count = \"LiteLLM_ToolTable\".call_count + 1, " + "updated_at = $8", + tool_name, + origin, + created_by, + key_hash, + team_id, + key_alias, + str(uuid.uuid4()), + now, + ) + verbose_proxy_logger.debug( + "tool_registry_writer: upserted %d tool(s)", len(data) + ) + except Exception as e: + verbose_proxy_logger.error("tool_registry_writer batch_upsert_tools error: %s", e) + + +async def list_tools( + prisma_client: "PrismaClient", + call_policy: Optional[ToolCallPolicy] = None, +) -> List[LiteLLM_ToolTableRow]: + """Return all tools, optionally filtered by call_policy.""" + try: + if call_policy is not None: + rows = await prisma_client.db.query_raw( + 'SELECT tool_id, tool_name, origin, call_policy, call_count, assignments, ' + 'key_hash, team_id, key_alias, created_at, updated_at, created_by, updated_by ' + 'FROM "LiteLLM_ToolTable" WHERE call_policy = $1 ORDER BY created_at DESC', + call_policy, + ) + else: + rows = await prisma_client.db.query_raw( + 'SELECT tool_id, tool_name, origin, call_policy, call_count, assignments, ' + 'key_hash, team_id, key_alias, created_at, updated_at, created_by, updated_by ' + 'FROM "LiteLLM_ToolTable" ORDER BY created_at DESC', + ) + return [_row_to_model(row) for row in rows] + except Exception as e: + verbose_proxy_logger.error("tool_registry_writer list_tools error: %s", e) + return [] + + +async def get_tool( + prisma_client: "PrismaClient", + tool_name: str, +) -> Optional[LiteLLM_ToolTableRow]: + """Return a single tool row by tool_name.""" + try: + rows = await prisma_client.db.query_raw( + 'SELECT tool_id, tool_name, origin, call_policy, call_count, assignments, ' + 'key_hash, team_id, key_alias, created_at, updated_at, created_by, updated_by ' + 'FROM "LiteLLM_ToolTable" WHERE tool_name = $1', + tool_name, + ) + if not rows: + return None + return _row_to_model(rows[0]) + except Exception as e: + verbose_proxy_logger.error("tool_registry_writer get_tool error: %s", e) + return None + + +async def update_tool_policy( + prisma_client: "PrismaClient", + tool_name: str, + call_policy: ToolCallPolicy, + updated_by: Optional[str], +) -> Optional[LiteLLM_ToolTableRow]: + """Update the call_policy for a tool. Upserts the row if it does not exist yet.""" + try: + _updated_by = updated_by or "system" + now = datetime.now(timezone.utc).isoformat() + await prisma_client.db.execute_raw( + 'INSERT INTO "LiteLLM_ToolTable" (tool_id, tool_name, call_policy, created_by, updated_by, created_at, updated_at) ' + "VALUES ($4, $1, $2, $3, $3, $5, $5) " + "ON CONFLICT (tool_name) DO UPDATE SET call_policy = $2, updated_by = $3, updated_at = $5", + tool_name, + call_policy, + _updated_by, + str(uuid.uuid4()), + now, + ) + return await get_tool(prisma_client, tool_name) + except Exception as e: + verbose_proxy_logger.error("tool_registry_writer update_tool_policy error: %s", e) + return None + + +async def get_tools_by_names( + prisma_client: "PrismaClient", + tool_names: List[str], +) -> Dict[str, str]: + """ + Return a {tool_name: call_policy} map for the given tool names. + Used by the policy enforcement guardrail — single batch query, never N+1. + """ + if not tool_names: + return {} + try: + placeholders = ", ".join(f"${i+1}" for i in range(len(tool_names))) + rows = await prisma_client.db.query_raw( + f'SELECT tool_name, call_policy FROM "LiteLLM_ToolTable" WHERE tool_name IN ({placeholders})', + *tool_names, + ) + return {row["tool_name"]: row["call_policy"] for row in rows} + except Exception as e: + verbose_proxy_logger.error("tool_registry_writer get_tools_by_names error: %s", e) + return {} diff --git a/litellm/proxy/google_endpoints/endpoints.py b/litellm/proxy/google_endpoints/endpoints.py index 5c41b371ca4..9768d93e922 100644 --- a/litellm/proxy/google_endpoints/endpoints.py +++ b/litellm/proxy/google_endpoints/endpoints.py @@ -1,6 +1,10 @@ +from datetime import datetime + from fastapi import APIRouter, Depends, HTTPException, Request, Response from fastapi.responses import ORJSONResponse, StreamingResponse +import litellm +from litellm._uuid import uuid from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth, user_api_key_auth from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing @@ -17,7 +21,8 @@ router = APIRouter( dependencies=[Depends(user_api_key_auth)], ) @router.post( - "/models/{model_name:path}:generateContent", dependencies=[Depends(user_api_key_auth)] + "/models/{model_name:path}:generateContent", + dependencies=[Depends(user_api_key_auth)], ) async def google_generate_content( request: Request, @@ -36,12 +41,12 @@ async def google_generate_content( data = await _read_request_body(request=request) if "model" not in data: data["model"] = model_name - + # Extract generationConfig and pass it as config parameter generation_config = data.pop("generationConfig", None) if generation_config: data["config"] = generation_config - + # Add user authentication metadata for cost tracking data = await add_litellm_data_to_request( data=data, @@ -51,7 +56,19 @@ async def google_generate_content( general_settings=general_settings, version=version, ) - + + # Create logging object with full request metadata so callbacks (e.g. S3) get user/trace_id + data["litellm_call_id"] = request.headers.get( + "x-litellm-call-id", str(uuid.uuid4()) + ) + logging_obj, data = litellm.utils.function_setup( + original_function="agenerate_content", + rules_obj=litellm.utils.Rules(), + start_time=datetime.now(), + **data, + ) + data["litellm_logging_obj"] = logging_obj + # call router if llm_router is None: raise HTTPException(status_code=500, detail="Router not initialized") @@ -103,6 +120,18 @@ async def google_stream_generate_content( version=version, ) + # Create logging object with full request metadata so streaming END callbacks (e.g. S3) get user/trace_id + data["litellm_call_id"] = request.headers.get( + "x-litellm-call-id", str(uuid.uuid4()) + ) + logging_obj, data = litellm.utils.function_setup( + original_function="agenerate_content_stream", + rules_obj=litellm.utils.Rules(), + start_time=datetime.now(), + **data, + ) + data["litellm_logging_obj"] = logging_obj + # call router if llm_router is None: raise HTTPException(status_code=500, detail="Router not initialized") @@ -247,11 +276,11 @@ async def create_interaction( ) data = await _read_request_body(request=request) - + # Default to gemini provider for interactions if "custom_llm_provider" not in data: data["custom_llm_provider"] = "gemini" - + processor = ProxyBaseLLMRequestProcessing(data=data) try: return await processor.base_process_llm_request( @@ -301,7 +330,7 @@ async def get_interaction( ): """ Get an interaction by ID. - + Per OpenAPI spec: GET /{api_version}/interactions/{interaction_id} """ from litellm.proxy.proxy_server import ( @@ -319,7 +348,7 @@ async def get_interaction( ) data = {"interaction_id": interaction_id, "custom_llm_provider": "gemini"} - + processor = ProxyBaseLLMRequestProcessing(data=data) try: return await processor.base_process_llm_request( @@ -369,7 +398,7 @@ async def delete_interaction( ): """ Delete an interaction by ID. - + Per OpenAPI spec: DELETE /{api_version}/interactions/{interaction_id} """ from litellm.proxy.proxy_server import ( @@ -387,7 +416,7 @@ async def delete_interaction( ) data = {"interaction_id": interaction_id, "custom_llm_provider": "gemini"} - + processor = ProxyBaseLLMRequestProcessing(data=data) try: return await processor.base_process_llm_request( @@ -437,7 +466,7 @@ async def cancel_interaction( ): """ Cancel an interaction by ID. - + Per OpenAPI spec: POST /{api_version}/interactions/{interaction_id}:cancel """ from litellm.proxy.proxy_server import ( @@ -455,7 +484,7 @@ async def cancel_interaction( ) data = {"interaction_id": interaction_id, "custom_llm_provider": "gemini"} - + processor = ProxyBaseLLMRequestProcessing(data=data) try: return await processor.base_process_llm_request( diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py index 28ccff0e36c..34fbf47253b 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py +++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py @@ -322,12 +322,6 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): analyze_payload, ) - async with session.post(analyze_url, json=analyze_payload) as response: - analyze_results = await response.json() - verbose_proxy_logger.debug("analyze_results: %s", analyze_results) - - # Handle error responses from Presidio (e.g., {'error': 'No text provided'}) - # Presidio may return a dict instead of a list when errors occur def _fail_on_invalid_response( reason: str, ) -> List[PresidioAnalyzeResponseItem]: @@ -347,6 +341,36 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): ) return [] + async with session.post( + analyze_url, + json=analyze_payload, + headers={"Accept": "application/json"}, + ) as response: + # Validate HTTP status + if response.status >= 400: + error_body = await response.text() + return _fail_on_invalid_response( + f"HTTP {response.status} from Presidio analyzer: {error_body[:200]}" + ) + + # Validate Content-Type is JSON + content_type = getattr( + response, + "content_type", + response.headers.get("Content-Type", ""), + ) + if "application/json" not in content_type: + error_body = await response.text() + return _fail_on_invalid_response( + f"expected application/json Content-Type but received '{content_type}'; body: '{error_body[:200]}'" + ) + + analyze_results = await response.json() + verbose_proxy_logger.debug("analyze_results: %s", analyze_results) + + # Handle error responses from Presidio (e.g., {'error': 'No text provided'}) + # Presidio may return a dict instead of a list when errors occur + if isinstance(analyze_results, dict): if "error" in analyze_results: return _fail_on_invalid_response( @@ -423,8 +447,29 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): } async with session.post( - anonymize_url, json=anonymize_payload + anonymize_url, + json=anonymize_payload, + headers={"Accept": "application/json"}, ) as response: + # Validate HTTP status + if response.status >= 400: + error_body = await response.text() + raise Exception( + f"Presidio anonymizer returned HTTP {response.status}: {error_body[:200]}" + ) + + # Validate Content-Type is JSON + content_type = getattr( + response, + "content_type", + response.headers.get("Content-Type", ""), + ) + if "application/json" not in content_type: + error_body = await response.text() + raise Exception( + f"Presidio anonymizer returned non-JSON Content-Type '{content_type}'; body: '{error_body[:200]}'" + ) + redacted_text = await response.json() new_text = text @@ -456,7 +501,11 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail): except Exception as e: # Sanitize exception to avoid leaking the original text (which may # contain API keys or other secrets) in error responses. - if "Invalid anonymizer response" in str(e): + error_str = str(e) + if ( + "Invalid anonymizer response" in error_str + or "Presidio anonymizer returned" in error_str + ): raise raise Exception( f"Presidio PII anonymization failed: {type(e).__name__}" diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_policy/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/tool_policy/__init__.py new file mode 100644 index 00000000000..5a43006e23c --- /dev/null +++ b/litellm/proxy/guardrails/guardrail_hooks/tool_policy/__init__.py @@ -0,0 +1,16 @@ +import litellm +from litellm.types.guardrails import Guardrail, LitellmParams + + +def initialize_guardrail(litellm_params: LitellmParams, guardrail: Guardrail): + from litellm.proxy.guardrails.guardrail_hooks.tool_policy.tool_policy_guardrail import ( + ToolPolicyGuardrail, + ) + + _callback = ToolPolicyGuardrail( + guardrail_name=guardrail.get("guardrail_name", "tool_policy"), + event_hook=litellm_params.mode, + default_on=litellm_params.default_on, + ) + litellm.logging_callback_manager.add_litellm_callback(_callback) + return _callback diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_policy/tool_policy_guardrail.py b/litellm/proxy/guardrails/guardrail_hooks/tool_policy/tool_policy_guardrail.py new file mode 100644 index 00000000000..87558566c42 --- /dev/null +++ b/litellm/proxy/guardrails/guardrail_hooks/tool_policy/tool_policy_guardrail.py @@ -0,0 +1,163 @@ +""" +Tool Policy Guardrail + +Reads call_policy from LiteLLM_ToolTable and enforces it on LLM requests/responses. + +Policy values: + "trusted" - allow through (no action) + "untrusted" - allow through (no action; default for newly discovered tools) + "blocked" - raise HTTPException, preventing the tool call + "dual_llm" - (Phase 3) send to second LLM for verification; currently treated as allowed + +Configuration in proxy config YAML: + guardrails: + - guardrail_name: "tool_policy" + litellm_params: + guardrail: tool_policy + mode: post_call + +or both pre and post call: + - guardrail_name: "tool_policy" + litellm_params: + guardrail: tool_policy + mode: during_call # runs before LLM and on response +""" + +from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional + +from fastapi import HTTPException + +from litellm._logging import verbose_proxy_logger +from litellm.caching.dual_cache import DualCache +from litellm.constants import TOOL_POLICY_CACHE_TTL_SECONDS +from litellm.integrations.custom_guardrail import ( + CustomGuardrail, + log_guardrail_information, +) +from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.utils import GenericGuardrailAPIInputs + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj + +GUARDRAIL_NAME = "tool_policy" + + +class ToolPolicyGuardrail(CustomGuardrail): + """ + Guardrail that enforces per-tool call policies stored in LiteLLM_ToolTable. + + Tools with call_policy="blocked" are rejected before/after the LLM call. + Tools with call_policy="trusted" or "untrusted" pass through unchanged. + """ + + def __init__(self, **kwargs: Any) -> None: + if "supported_event_hooks" not in kwargs: + kwargs["supported_event_hooks"] = [ + GuardrailEventHooks.pre_call, + GuardrailEventHooks.post_call, + GuardrailEventHooks.during_call, + ] + super().__init__(**kwargs) + self._policy_cache: DualCache = DualCache() + + @log_guardrail_information + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional["LiteLLMLoggingObj"] = None, + ) -> GenericGuardrailAPIInputs: + """ + Enforce tool policies on both request tools and response tool_calls. + + - input_type="request": check inputs["tools"] (tool definitions in the LLM request) + - input_type="response": check inputs["tool_calls"] (tool_calls in the LLM response) + + Raises HTTPException (400) if any tool is "blocked". + """ + if input_type == "request": + tools = inputs.get("tools") or [] + tool_names = [ + t["function"]["name"] + for t in tools + if isinstance(t, dict) + and isinstance(t.get("function"), dict) + and t["function"].get("name") + ] + else: # response + tool_calls = inputs.get("tool_calls") or [] + tool_names = [] + for tc in tool_calls: + fn = None + if isinstance(tc, dict): + fn = (tc.get("function") or {}).get("name") + elif hasattr(tc, "function"): + fn = getattr(tc.function, "name", None) + if fn: + tool_names.append(fn) + + if not tool_names: + return inputs + + policy_map = await self._get_policies_cached(tool_names) + + blocked = [name for name in tool_names if policy_map.get(name) == "blocked"] + if blocked: + verbose_proxy_logger.warning( + "ToolPolicyGuardrail: blocking tool(s) %s (policy=blocked)", blocked + ) + raise HTTPException( + status_code=400, + detail={ + "error": "Violated tool policy", + "blocked_tools": blocked, + "message": f"Tool(s) {blocked} are blocked by policy.", + }, + ) + + return inputs + + async def _get_policies_cached(self, tool_names: List[str]) -> Dict[str, str]: + """ + Batch-fetch call_policy for the given tool names. + + Caches per individual tool name (not per combination) so that adding + a new tool to a request doesn't invalidate the cached policies for all + the other tools already in the cache. + """ + from litellm.proxy.db.tool_registry_writer import get_tools_by_names + from litellm.proxy.proxy_server import prisma_client + + if not tool_names or prisma_client is None: + return {} + + result: Dict[str, str] = {} + cache_misses: List[str] = [] + + for name in tool_names: + cached = await self._policy_cache.async_get_cache(f"tool_policy:{name}") + if cached is not None and isinstance(cached, str): + result[name] = cached + else: + cache_misses.append(name) + + if cache_misses: + fetched = await get_tools_by_names( + prisma_client=prisma_client, tool_names=cache_misses + ) + for name, policy in fetched.items(): + result[name] = policy + await self._policy_cache.async_set_cache( + key=f"tool_policy:{name}", + value=policy, + ttl=TOOL_POLICY_CACHE_TTL_SECONDS, + ) + verbose_proxy_logger.debug( + "ToolPolicyGuardrail: fetched %d policies from DB (cache hits: %d)", + len(cache_misses), + len(tool_names) - len(cache_misses), + ) + + return result diff --git a/litellm/proxy/health_check.py b/litellm/proxy/health_check.py index 427a16a9801..d228bdb2129 100644 --- a/litellm/proxy/health_check.py +++ b/litellm/proxy/health_check.py @@ -3,12 +3,15 @@ import asyncio import logging import random +import sys +import threading +import time from typing import List, Optional import litellm logger = logging.getLogger(__name__) -from litellm.constants import HEALTH_CHECK_TIMEOUT_SECONDS, DEFAULT_HEALTH_CHECK_PROMPT +from litellm.constants import DEFAULT_HEALTH_CHECK_PROMPT, HEALTH_CHECK_TIMEOUT_SECONDS ILLEGAL_DISPLAY_PARAMS = [ "messages", @@ -23,6 +26,29 @@ ILLEGAL_DISPLAY_PARAMS = [ MINIMAL_DISPLAY_PARAMS = ["model", "mode_error"] +def _get_process_rss_mb() -> Optional[float]: + """ + Get process RSS memory in MB. + On Linux, ru_maxrss is in KB. On macOS, ru_maxrss is in bytes. + """ + try: + import resource + + ru_maxrss = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss + if sys.platform == "darwin": + return float(ru_maxrss) / (1024 * 1024) + return float(ru_maxrss) / 1024 + except Exception: + return None + + +def _rss_mb_for_log() -> str: + rss_mb = _get_process_rss_mb() + if rss_mb is None: + return "unknown" + return f"{rss_mb:.2f}" + + def _get_random_llm_message(): """ Get a random message from the LLM. @@ -67,48 +93,115 @@ async def run_with_timeout(task, timeout): try: return await asyncio.wait_for(task, timeout) except asyncio.TimeoutError: - task.cancel() - # Only cancel child tasks of the current task - current_task = asyncio.current_task() - for t in asyncio.all_tasks(): - if t != current_task: - t.cancel() - try: - await asyncio.wait_for(task, 0.1) # Give 100ms for cleanup - except (asyncio.TimeoutError, asyncio.CancelledError, Exception): - pass + # `asyncio.wait_for()` already cancels only the awaited task on timeout. + # Do not cancel unrelated sibling health check tasks. return {"error": "Timeout exceeded"} -async def _perform_health_check(model_list: list, details: Optional[bool] = True): +async def _run_model_health_check(model: dict): + litellm_params = model["litellm_params"] + model_info = model.get("model_info", {}) + mode = model_info.get("mode", None) + litellm_params = _update_litellm_params_for_health_check(model_info, litellm_params) + timeout = model_info.get("health_check_timeout") or HEALTH_CHECK_TIMEOUT_SECONDS + + return await run_with_timeout( + litellm.ahealth_check( + litellm_params, + mode=mode, + prompt=DEFAULT_HEALTH_CHECK_PROMPT, + input=["test from litellm"], + ), + timeout, + ) + + +async def _run_health_checks_with_bounded_concurrency( + models: list, concurrency_limit: int +) -> tuple[list, int]: + """ + Run health checks with at most `concurrency_limit` active tasks. + Preserves result ordering to match `models`. + """ + results: list = [None] * len(models) + tasks_to_index: dict[asyncio.Task, int] = {} + model_iter = iter(enumerate(models)) + peak_in_flight = 0 + + def _schedule_next() -> bool: + nonlocal peak_in_flight + try: + idx, next_model = next(model_iter) + except StopIteration: + return False + task = asyncio.create_task(_run_model_health_check(next_model)) + tasks_to_index[task] = idx + peak_in_flight = max(peak_in_flight, len(tasks_to_index)) + return True + + for _ in range(min(concurrency_limit, len(models))): + _schedule_next() + + while tasks_to_index: + done, _ = await asyncio.wait( + set(tasks_to_index.keys()), + return_when=asyncio.FIRST_COMPLETED, + ) + for task in done: + idx = tasks_to_index.pop(task) + try: + results[idx] = task.result() + except Exception as e: + results[idx] = e + _schedule_next() + + return results, peak_in_flight + + +async def _perform_health_check( + model_list: list, + details: Optional[bool] = True, + max_concurrency: Optional[int] = None, + instrumentation_context: Optional[dict] = None, +): """ Perform a health check for each model in the list. + + max_concurrency: Optional limit on concurrent health check requests. """ - tasks = [] - for model in model_list: - litellm_params = model["litellm_params"] - model_info = model.get("model_info", {}) - mode = model_info.get("mode", None) - litellm_params = _update_litellm_params_for_health_check( - model_info, litellm_params + instrumentation_context = instrumentation_context or {} + instrumentation_enabled = bool(instrumentation_context.get("enabled", False)) + cycle_id = instrumentation_context.get("cycle_id", "unknown") + source = instrumentation_context.get("source", "unknown") + + dispatch_mode = "unbounded" + peak_in_flight = 0 + if isinstance(max_concurrency, int) and max_concurrency > 0: + dispatch_mode = "bounded" + results, peak_in_flight = await _run_health_checks_with_bounded_concurrency( + model_list, max_concurrency ) - timeout = model_info.get("health_check_timeout") or HEALTH_CHECK_TIMEOUT_SECONDS + else: + tasks = [ + asyncio.create_task(_run_model_health_check(model)) for model in model_list + ] + peak_in_flight = len(tasks) + results = await asyncio.gather(*tasks, return_exceptions=True) - task = run_with_timeout( - litellm.ahealth_check( - model["litellm_params"], - mode=mode, - prompt=DEFAULT_HEALTH_CHECK_PROMPT, - input=["test from litellm"], - ), - timeout, + if instrumentation_enabled: + logger.debug( + "health_check_dispatch_summary source=%s cycle_id=%s mode=%s model_count=%d max_concurrency=%s peak_in_flight=%d thread_count=%d rss_mb=%s", + source, + cycle_id, + dispatch_mode, + len(model_list), + max_concurrency, + peak_in_flight, + threading.active_count(), + _rss_mb_for_log(), ) - tasks.append(task) - - results = await asyncio.gather(*tasks, return_exceptions=True) - healthy_endpoints = [] unhealthy_endpoints = [] @@ -190,22 +283,48 @@ async def perform_health_check( model: Optional[str] = None, cli_model: Optional[str] = None, details: Optional[bool] = True, + model_id: Optional[str] = None, + max_concurrency: Optional[int] = None, + instrumentation_context: Optional[dict] = None, ): """ Perform a health check on the system. + When model_id is provided, only the deployment with that id is checked + (so models that share the same name but have different ids are checked separately). + When model (name) is provided, all deployments matching that name are checked. + Returns: (bool): True if the health check passes, False otherwise. """ + instrumentation_context = instrumentation_context or {} + instrumentation_enabled = bool(instrumentation_context.get("enabled", False)) + cycle_id = instrumentation_context.get("cycle_id", "unknown") + source = instrumentation_context.get("source", "unknown") + if not model_list: if cli_model: model_list = [ {"model_name": cli_model, "litellm_params": {"model": cli_model}} ] else: + if instrumentation_enabled: + logger.debug( + "health_check_cycle_skipped source=%s cycle_id=%s reason=no_models", + source, + cycle_id, + ) return [], [] - if model is not None: + cycle_start_time = time.monotonic() + requested_model_count = len(model_list) + + # Filter by model_id first so a single deployment is checked when id is specified + if model_id is not None: + _by_id = [x for x in model_list if (x.get("model_info") or {}).get("id") == model_id] + if _by_id: + model_list = _by_id + elif model is not None: _new_model_list = [ x for x in model_list if x["litellm_params"]["model"] == model ] @@ -213,11 +332,56 @@ async def perform_health_check( _new_model_list = [x for x in model_list if x["model_name"] == model] model_list = _new_model_list + post_filter_model_count = len(model_list) model_list = filter_deployments_by_id( model_list=model_list ) # filter duplicate deployments (e.g. when model alias'es are used) - healthy_endpoints, unhealthy_endpoints = await _perform_health_check( - model_list, details - ) + deduped_model_count = len(model_list) + + if instrumentation_enabled: + logger.debug( + "health_check_cycle_start source=%s cycle_id=%s requested_model_count=%d post_model_filter_count=%d deduped_model_count=%d max_concurrency=%s thread_count=%d rss_mb=%s", + source, + cycle_id, + requested_model_count, + post_filter_model_count, + deduped_model_count, + max_concurrency, + threading.active_count(), + _rss_mb_for_log(), + ) + + try: + healthy_endpoints, unhealthy_endpoints = await _perform_health_check( + model_list, + details, + max_concurrency=max_concurrency, + instrumentation_context=instrumentation_context, + ) + except Exception: + if instrumentation_enabled: + logger.exception( + "health_check_cycle_failed source=%s cycle_id=%s model_count=%d duration_ms=%.2f thread_count=%d rss_mb=%s", + source, + cycle_id, + deduped_model_count, + (time.monotonic() - cycle_start_time) * 1000, + threading.active_count(), + _rss_mb_for_log(), + ) + raise + + if instrumentation_enabled: + logger.debug( + "health_check_cycle_complete source=%s cycle_id=%s model_count=%d healthy_count=%d unhealthy_count=%d duration_ms=%.2f thread_count=%d rss_mb=%s", + source, + cycle_id, + deduped_model_count, + len(healthy_endpoints), + len(unhealthy_endpoints), + (time.monotonic() - cycle_start_time) * 1000, + threading.active_count(), + _rss_mb_for_log(), + ) return healthy_endpoints, unhealthy_endpoints diff --git a/litellm/proxy/health_check_utils/shared_health_check_manager.py b/litellm/proxy/health_check_utils/shared_health_check_manager.py index d0c99d84e94..ae18a42c02b 100644 --- a/litellm/proxy/health_check_utils/shared_health_check_manager.py +++ b/litellm/proxy/health_check_utils/shared_health_check_manager.py @@ -16,7 +16,7 @@ from litellm.proxy.health_check import perform_health_check class SharedHealthCheckManager: """ Manager for coordinating health checks across multiple pods using Redis. - + This class implements a shared health check state mechanism that: - Prevents duplicate health checks across pods - Caches health check results with configurable TTL @@ -58,7 +58,7 @@ class SharedHealthCheckManager: async def acquire_health_check_lock(self) -> bool: """ Attempt to acquire the global health check lock. - + Returns: bool: True if lock was acquired, False otherwise """ @@ -74,7 +74,7 @@ class SharedHealthCheckManager: nx=True, # Only set if key doesn't exist ttl=self.lock_ttl, ) - + if acquired: verbose_proxy_logger.info( "Pod %s acquired health check lock", self.pod_id @@ -83,12 +83,10 @@ class SharedHealthCheckManager: verbose_proxy_logger.debug( "Pod %s failed to acquire health check lock", self.pod_id ) - + return acquired except Exception as e: - verbose_proxy_logger.error( - "Error acquiring health check lock: %s", str(e) - ) + verbose_proxy_logger.error("Error acquiring health check lock: %s", str(e)) return False async def release_health_check_lock(self) -> None: @@ -106,14 +104,12 @@ class SharedHealthCheckManager: "Pod %s released health check lock", self.pod_id ) except Exception as e: - verbose_proxy_logger.error( - "Error releasing health check lock: %s", str(e) - ) + verbose_proxy_logger.error("Error releasing health check lock: %s", str(e)) async def get_cached_health_check_results(self) -> Optional[Dict[str, Any]]: """ Get cached health check results from Redis. - + Returns: Optional[Dict]: Cached health check results or None if not found/expired """ @@ -123,7 +119,7 @@ class SharedHealthCheckManager: try: cache_key = self.get_health_check_cache_key() cached_data = await self.redis_cache.async_get_cache(cache_key) - + if cached_data is None: return None @@ -136,7 +132,7 @@ class SharedHealthCheckManager: # Check if the cache is still valid cache_timestamp = cached_results.get("timestamp", 0) current_time = time.time() - + if current_time - cache_timestamp > self.health_check_ttl: verbose_proxy_logger.debug("Cached health check results expired") return None @@ -151,13 +147,13 @@ class SharedHealthCheckManager: return None async def cache_health_check_results( - self, - healthy_endpoints: List[Dict[str, Any]], - unhealthy_endpoints: List[Dict[str, Any]] + self, + healthy_endpoints: List[Dict[str, Any]], + unhealthy_endpoints: List[Dict[str, Any]], ) -> None: """ Cache health check results in Redis. - + Args: healthy_endpoints: List of healthy endpoints unhealthy_endpoints: List of unhealthy endpoints @@ -181,7 +177,7 @@ class SharedHealthCheckManager: safe_dumps(cache_data), ttl=self.health_check_ttl, ) - + verbose_proxy_logger.info( "Cached health check results for %d healthy and %d unhealthy endpoints", len(healthy_endpoints), @@ -189,29 +185,29 @@ class SharedHealthCheckManager: ) except Exception as e: - verbose_proxy_logger.error( - "Error caching health check results: %s", str(e) - ) + verbose_proxy_logger.error("Error caching health check results: %s", str(e)) async def perform_shared_health_check( - self, - model_list: List[Dict[str, Any]], - details: bool = True + self, + model_list: List[Dict[str, Any]], + details: bool = True, + max_concurrency: Optional[int] = None, ) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]: """ Perform health check with shared state coordination. - + This method: 1. First checks if there are recent cached results 2. If no recent cache, tries to acquire lock to run health check 3. If lock acquired, runs health check and caches results 4. If lock not acquired, waits briefly and tries to get cached results again 5. Falls back to running health check locally if no cache available - + Args: model_list: List of models to check details: Whether to include detailed information - + max_concurrency: Optional limit on concurrent health check requests + Returns: Tuple of (healthy_endpoints, unhealthy_endpoints) """ @@ -225,27 +221,29 @@ class SharedHealthCheckManager: # No recent cache, try to acquire lock lock_acquired = await self.acquire_health_check_lock() - + if lock_acquired: try: # We have the lock, run health check verbose_proxy_logger.info( - "Pod %s running health check for %d models", - self.pod_id, - len(model_list) + "Pod %s running health check for %d models", + self.pod_id, + len(model_list), ) - + healthy_endpoints, unhealthy_endpoints = await perform_health_check( - model_list=model_list, details=details + model_list=model_list, + details=details, + max_concurrency=max_concurrency, ) - + # Cache the results await self.cache_health_check_results( healthy_endpoints, unhealthy_endpoints ) - + return healthy_endpoints, unhealthy_endpoints - + finally: # Always release the lock await self.release_health_check_lock() @@ -254,10 +252,10 @@ class SharedHealthCheckManager: verbose_proxy_logger.debug( "Pod %s waiting for other pod to complete health check", self.pod_id ) - + # Wait a bit for the other pod to complete await asyncio.sleep(2) - + # Try to get cached results again cached_results = await self.get_cached_health_check_results() if cached_results is not None: @@ -265,19 +263,23 @@ class SharedHealthCheckManager: cached_results.get("healthy_endpoints", []), cached_results.get("unhealthy_endpoints", []), ) - + # Still no cache, fall back to local health check verbose_proxy_logger.warning( - "Pod %s falling back to local health check (no cache available)", - self.pod_id + "Pod %s falling back to local health check (no cache available)", + self.pod_id, + ) + + return await perform_health_check( + model_list=model_list, + details=details, + max_concurrency=max_concurrency, ) - - return await perform_health_check(model_list=model_list, details=details) async def is_health_check_in_progress(self) -> bool: """ Check if a health check is currently in progress by another pod. - + Returns: bool: True if health check is in progress, False otherwise """ @@ -297,7 +299,7 @@ class SharedHealthCheckManager: async def get_health_check_status(self) -> Dict[str, Any]: """ Get the current status of health check coordination. - + Returns: Dict containing status information """ @@ -320,7 +322,9 @@ class SharedHealthCheckManager: cached_results = await self.get_cached_health_check_results() status["cache_available"] = cached_results is not None if cached_results: - status["cache_age_seconds"] = time.time() - cached_results.get("timestamp", 0) + status["cache_age_seconds"] = time.time() - cached_results.get( + "timestamp", 0 + ) status["last_checked_by"] = cached_results.get("checked_by") except Exception as e: diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index da90696ec2d..f3bed3656f6 100644 --- a/litellm/proxy/health_endpoints/_health_endpoints.py +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -110,26 +110,31 @@ def _resolve_os_environ_variables(params: dict) -> dict: def get_callback_identifier(callback): """ Get the callback identifier string, handling both strings and objects. - + This function extracts a string identifier from a callback, which can be: - A string (returned as-is) - An object with a callback_name attribute - An object registered in CustomLoggerRegistry - Falls back to callback_name() helper function - + Args: callback: The callback to identify (can be str or object) - + Returns: str: The callback identifier string """ if isinstance(callback, str): return callback - if hasattr(callback, 'callback_name') and callback.callback_name: + if hasattr(callback, "callback_name") and callback.callback_name: return callback.callback_name - if hasattr(callback, '__class__'): - callback_strs = CustomLoggerRegistry.get_all_callback_strs_from_class_type(callback.__class__) - if hasattr(callback, 'callback_name') and callback.callback_name in callback_strs: + if hasattr(callback, "__class__"): + callback_strs = CustomLoggerRegistry.get_all_callback_strs_from_class_type( + callback.__class__ + ) + if ( + hasattr(callback, "callback_name") + and callback.callback_name in callback_strs + ): return callback.callback_name if callback_strs: return callback_strs[0] @@ -151,7 +156,7 @@ services = Union[ "datadog_llm_observability", "generic_api", "arize", - "sqs" + "sqs", ], str, ] @@ -224,7 +229,7 @@ async def health_services_endpoint( # noqa: PLR0915 "datadog_llm_observability", "generic_api", "arize", - "sqs" + "sqs", ]: raise HTTPException( status_code=400, @@ -238,14 +243,14 @@ async def health_services_endpoint( # noqa: PLR0915 service_in_success_callbacks = True else: for cb in litellm.success_callback: - if hasattr(cb, 'callback_name') and cb.callback_name == service: + if getattr(cb, "callback_name", None) == service: service_in_success_callbacks = True break cb_id = get_callback_identifier(cb) if cb_id == service: service_in_success_callbacks = True break - + if ( service == "openmeter" or service == "braintrust" @@ -320,6 +325,7 @@ async def health_services_endpoint( # noqa: PLR0915 ) elif service == "sqs": from litellm.integrations.sqs import SQSLogger + sqs_logger = SQSLogger() response = await sqs_logger.async_health_check() return { @@ -518,12 +524,12 @@ async def _save_health_check_to_db( def _build_model_param_to_info_mapping(model_list: list) -> dict: """ Build a mapping from model parameter to model info (model_name, model_id). - + Multiple models might share the same model parameter, so we use a list. - + Args: model_list: List of model configurations - + Returns: Dictionary mapping model parameter to list of model info dicts """ @@ -534,14 +540,16 @@ def _build_model_param_to_info_mapping(model_list: list) -> dict: model_id = model_info.get("id") litellm_params = model.get("litellm_params", {}) model_param = litellm_params.get("model") - + if model_param and model_name: if model_param not in model_param_to_info: model_param_to_info[model_param] = [] - model_param_to_info[model_param].append({ - "model_name": model_name, - "model_id": model_id, - }) + model_param_to_info[model_param].append( + { + "model_name": model_name, + "model_id": model_id, + } + ) return model_param_to_info @@ -552,19 +560,19 @@ def _aggregate_health_check_results( ) -> dict: """ Aggregate health check results per unique model. - + Uses (model_id, model_name) as key, or (None, model_name) if model_id is None. - + Args: model_param_to_info: Mapping from model parameter to model info healthy_endpoints: List of healthy endpoint results unhealthy_endpoints: List of unhealthy endpoint results - + Returns: Dictionary mapping (model_id, model_name) to aggregated health check results """ model_results = {} - + # Process healthy endpoints for endpoint in healthy_endpoints: model_param = endpoint.get("model") @@ -580,7 +588,7 @@ def _aggregate_health_check_results( "error_message": None, } model_results[key]["healthy_count"] += 1 - + # Process unhealthy endpoints for endpoint in unhealthy_endpoints: model_param = endpoint.get("model") @@ -600,7 +608,7 @@ def _aggregate_health_check_results( # Use the first error message encountered if not model_results[key]["error_message"] and error_message: model_results[key]["error_message"] = str(error_message)[:500] - + return model_results @@ -613,14 +621,14 @@ async def _save_health_check_results_if_changed( ): """ Save health check results to database, but only if status changed or >1 hour since last save. - + OPTIMIZATION: Only saves to database if the status has changed from the last saved check. This dramatically reduces database writes when health status remains stable. - + - Stable systems: ~1 write/hour per model (instead of 12 writes/hour with 5-min intervals) - Status changes: Immediate write (no delay) - Result: ~92% reduction in DB writes for stable systems, while maintaining real-time updates on changes - + Args: prisma_client: Database client model_results: Dictionary of aggregated health check results per model @@ -630,7 +638,7 @@ async def _save_health_check_results_if_changed( """ for result in model_results.values(): new_status = "healthy" if result["healthy_count"] > 0 else "unhealthy" - + # Check if we should save this result should_save = True lookup_key = result["model_id"] if result["model_id"] else result["model_name"] @@ -641,6 +649,7 @@ async def _save_health_check_results_if_changed( # Check if last check was recent (within 1 hour) if last_check.checked_at: from datetime import datetime, timezone + time_since_last_check = ( datetime.now(timezone.utc) - last_check.checked_at ).total_seconds() @@ -648,7 +657,7 @@ async def _save_health_check_results_if_changed( # This ensures we still get periodic updates even if status is stable if time_since_last_check < 3600: # 1 hour threshold should_save = False - + if should_save: asyncio.create_task( prisma_client.save_health_check_result( @@ -675,27 +684,27 @@ async def _save_background_health_checks_to_db( ): """ Save background health check results to database for each model. - + Maps health check endpoints back to their original models to get model_name and model_id. Aggregates results per unique model (by model_id if available, otherwise model_name). - + OPTIMIZATION: Only saves to database if the status has changed from the last saved check. This dramatically reduces database writes when health status remains stable. """ if prisma_client is None: return - + try: # Step 1: Build mapping from model parameter to model info model_param_to_info = _build_model_param_to_info_mapping(model_list) - + # Step 2: Aggregate health check results per unique model model_results = _aggregate_health_check_results( model_param_to_info, healthy_endpoints, unhealthy_endpoints, ) - + # Step 3: Get latest health checks for all models in one query to compare status latest_checks = await prisma_client.get_all_latest_health_checks() latest_checks_map = {} @@ -704,7 +713,7 @@ async def _save_background_health_checks_to_db( key = check.model_id if check.model_id else check.model_name if key not in latest_checks_map: latest_checks_map[key] = check - + # Step 4: Save aggregated results, but only if status changed await _save_health_check_results_if_changed( prisma_client, @@ -729,10 +738,16 @@ async def _perform_health_check_and_save( start_time, user_id, model_id=None, + max_concurrency=None, ): """Helper function to perform health check and save results to database""" healthy_endpoints, unhealthy_endpoints = await perform_health_check( - model_list=model_list, cli_model=cli_model, model=target_model, details=details + model_list=model_list, + cli_model=cli_model, + model=target_model, + details=details, + max_concurrency=max_concurrency, + model_id=model_id, ) # Optionally save health check result to database (non-blocking) @@ -789,6 +804,7 @@ async def health_endpoint( import time from litellm.proxy.proxy_server import ( + health_check_concurrency, health_check_details, health_check_results, llm_model_list, @@ -841,6 +857,7 @@ async def health_endpoint( start_time=start_time, user_id=user_api_key_dict.user_id, model_id=None, # CLI model doesn't have model_id + max_concurrency=health_check_concurrency, ) raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, @@ -864,6 +881,7 @@ async def health_endpoint( start_time=start_time, user_id=user_api_key_dict.user_id, model_id=model_id, + max_concurrency=health_check_concurrency, ) except Exception as e: verbose_proxy_logger.error( @@ -1420,11 +1438,11 @@ async def test_model_connection( status_code=500, detail={"error": CommonProxyErrors.db_not_connected_error.value}, ) - + # Get model name from litellm_params request_litellm_params = litellm_params or {} model_name = request_litellm_params.get("model") - + # Look up model configuration from router if model name is provided # This gets the litellm_params from proxy config (with resolved env vars) config_litellm_params: dict = {} @@ -1432,34 +1450,39 @@ async def test_model_connection( try: # First try to find by proxy model_name (e.g., "gpt-4o") deployments = llm_router.get_model_list(model_name=model_name) - + # If not found, try to find by litellm model name (e.g., "azure/gpt-4o") if not deployments or len(deployments) == 0: all_deployments = llm_router.get_model_list(model_name=None) if all_deployments: for deployment in all_deployments: - if deployment.get("litellm_params", {}).get("model") == model_name: + if ( + deployment.get("litellm_params", {}).get("model") + == model_name + ): deployments = [deployment] break - + if deployments and len(deployments) > 0: # Use the first deployment's litellm_params as base config # These already have resolved environment variables from proxy config - config_litellm_params = dict(deployments[0].get("litellm_params", {})) + config_litellm_params = dict( + deployments[0].get("litellm_params", {}) + ) except Exception as e: verbose_proxy_logger.debug( f"Could not find model {model_name} in router: {e}. " "Proceeding with request params only." ) - + # Merge: config params (from proxy config) as base, request params override # This allows users to override specific params while using config for credentials merged_litellm_params = {**config_litellm_params, **request_litellm_params} - + # Resolve os.environ/ environment variables in any remaining request params # This handles cases where user explicitly passes os.environ/ values to override config litellm_params = _resolve_os_environ_variables(merged_litellm_params) - + ## Auth check await ModelManagementAuthChecks.can_user_make_model_call( model_params=Deployment( diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py index 815d64f22ad..0734756d8ed 100644 --- a/litellm/proxy/hooks/proxy_track_cost_callback.py +++ b/litellm/proxy/hooks/proxy_track_cost_callback.py @@ -12,7 +12,7 @@ from litellm.litellm_core_utils.core_helpers import ( ) from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup from litellm.proxy._types import UserAPIKeyAuth -from litellm.proxy.auth.auth_checks import log_db_metrics +from litellm.proxy.auth.auth_checks import get_key_object, get_team_object, log_db_metrics from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.utils import ProxyUpdateSpend from litellm.types.utils import ( @@ -76,6 +76,10 @@ class _ProxyDBLogger(CustomLogger): traceback_str=traceback_str, ) + _metadata = await _ProxyDBLogger._enrich_failure_metadata_with_key_info( + metadata=_metadata, + ) + existing_metadata: dict = request_data.get("metadata", None) or {} existing_metadata.update(_metadata) @@ -255,6 +259,72 @@ class _ProxyDBLogger(CustomLogger): "Error in tracking cost callback - %s", str(e) ) + @staticmethod + async def _enrich_failure_metadata_with_key_info(metadata: dict) -> dict: + """ + Enriches failure spend log metadata by looking up the key object (and team object) + from cache/DB when key fields are missing. + + This handles two scenarios: + 1. Auth errors (401): UserAPIKeyAuth is created with only api_key set, all other + fields are null. We look up the full key object to fill in alias, user_id, + team_id, etc. + 2. Post-auth failures (provider errors, rate limits): key fields are populated + but team_alias is missing because LiteLLM_VerificationTokenView SQL view + doesn't include it. We look up the team object to fill in team_alias. + """ + api_key_hash = metadata.get("user_api_key") + if not api_key_hash: + return metadata + + from litellm.proxy.proxy_server import ( + prisma_client, + proxy_logging_obj, + user_api_key_cache, + ) + + # Step 1: If key fields are missing, look up the full key object + if metadata.get("user_api_key_alias") is None: + try: + key_obj = await get_key_object( + hashed_token=api_key_hash, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + if metadata.get("user_api_key_alias") is None: + metadata["user_api_key_alias"] = key_obj.key_alias + if metadata.get("user_api_key_user_id") is None: + metadata["user_api_key_user_id"] = key_obj.user_id + if metadata.get("user_api_key_team_id") is None: + metadata["user_api_key_team_id"] = key_obj.team_id + if metadata.get("user_api_key_org_id") is None: + metadata["user_api_key_org_id"] = key_obj.org_id + except Exception: + verbose_proxy_logger.debug( + "Failed to enrich failure metadata with key info for api_key=%s", + api_key_hash, + ) + + # Step 2: If team_id is known but team_alias is missing, look up the team object + team_id = metadata.get("user_api_key_team_id") + if team_id and metadata.get("user_api_key_team_alias") is None: + try: + team_obj = await get_team_object( + team_id=team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + if team_obj.team_alias is not None: + metadata["user_api_key_team_alias"] = team_obj.team_alias + except Exception: + verbose_proxy_logger.debug( + "Failed to enrich failure metadata with team_alias for team_id=%s", + team_id, + ) + return metadata + @staticmethod def _should_track_errors_in_db(): """ diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index b61dfa5b263..52f0b1d46e9 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -14,6 +14,7 @@ from litellm.proxy._types import (AddTeamCallback, CommonProxyErrors, LitellmDataForBackendLLMCall, LitellmUserRoles, SpecialHeaders, TeamCallbackMetadata, UserAPIKeyAuth) +from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_headers # Cache special headers as a frozenset for O(1) lookup performance _SPECIAL_HEADERS_CACHE = frozenset( @@ -824,7 +825,7 @@ async def add_litellm_data_to_request( # noqa: PLR0915 from litellm.proxy.proxy_server import llm_router, premium_user from litellm.types.proxy.litellm_pre_call_utils import SecretFields - _raw_headers: Dict[str, str] = dict(request.headers) + _raw_headers: Dict[str, str] = _safe_get_request_headers(request) _headers: Dict[str, str] = clean_headers( request.headers, litellm_key_header_name=( diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index a230c2e9336..c1165ab26d0 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -2535,6 +2535,7 @@ async def generate_key_helper_fn( # noqa: PLR0915 user_id: Optional[str] = None, user_alias: Optional[str] = None, team_id: Optional[str] = None, + agent_id: Optional[str] = None, user_email: Optional[str] = None, user_role: Optional[str] = None, max_parallel_requests: Optional[int] = None, @@ -2668,6 +2669,7 @@ async def generate_key_helper_fn( # noqa: PLR0915 "max_budget": key_max_budget, "user_id": user_id, "team_id": team_id, + "agent_id": agent_id, "project_id": project_id, "max_parallel_requests": max_parallel_requests, "metadata": metadata_json, diff --git a/litellm/proxy/management_endpoints/scim/scim_v2.py b/litellm/proxy/management_endpoints/scim/scim_v2.py index da10d3bf3b4..73fcce72c38 100644 --- a/litellm/proxy/management_endpoints/scim/scim_v2.py +++ b/litellm/proxy/management_endpoints/scim/scim_v2.py @@ -21,6 +21,7 @@ from typing_extensions import TypedDict import litellm from litellm._logging import verbose_proxy_logger +from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_headers from litellm._uuid import uuid from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.proxy._types import ( @@ -724,7 +725,7 @@ async def get_service_provider_config(request: Request): "SCIM ServiceProviderConfig request: method=%s url=%s headers=%s", request.method, request.url, - dict(request.headers), + _safe_get_request_headers(request), ) meta = { "resourceType": "ServiceProviderConfig", diff --git a/litellm/proxy/management_endpoints/tool_management_endpoints.py b/litellm/proxy/management_endpoints/tool_management_endpoints.py new file mode 100644 index 00000000000..89880c9a4ec --- /dev/null +++ b/litellm/proxy/management_endpoints/tool_management_endpoints.py @@ -0,0 +1,149 @@ +""" +TOOL POLICY MANAGEMENT + +All /tool management endpoints + +GET /v1/tool/list - List all discovered tools and their policies +GET /v1/tool/{tool_name} - Get a single tool's details +POST /v1/tool/policy - Update the call_policy for a tool +""" + +from typing import Optional + +from fastapi import APIRouter, Depends, HTTPException + +from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import CommonProxyErrors, UserAPIKeyAuth +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.types.tool_management import ( + LiteLLM_ToolTableRow, + ToolCallPolicy, + ToolListResponse, + ToolPolicyUpdateRequest, + ToolPolicyUpdateResponse, +) + +router = APIRouter() + + +@router.get( + "/v1/tool/list", + tags=["tool management"], + dependencies=[Depends(user_api_key_auth)], + response_model=ToolListResponse, +) +async def list_tools( + call_policy: Optional[ToolCallPolicy] = None, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + List all auto-discovered tools and their call policies. + + Parameters: + - call_policy: Optional filter — one of "trusted", "untrusted", "dual_llm", "blocked" + """ + from litellm.proxy.db.tool_registry_writer import list_tools as db_list_tools + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException( + status_code=500, detail=CommonProxyErrors.db_not_connected_error.value + ) + + try: + tools = await db_list_tools(prisma_client=prisma_client, call_policy=call_policy) + return ToolListResponse(tools=tools, total=len(tools)) + except Exception as e: + verbose_proxy_logger.exception("Error listing tools: %s", e) + raise HTTPException(status_code=500, detail=str(e)) + + +@router.get( + "/v1/tool/{tool_name:path}", + tags=["tool management"], + dependencies=[Depends(user_api_key_auth)], + response_model=LiteLLM_ToolTableRow, +) +async def get_tool( + tool_name: str, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Get details for a single tool. + + Parameters: + - tool_name: The tool name (supports namespaced names with slashes) + """ + from litellm.proxy.db.tool_registry_writer import get_tool as db_get_tool + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException( + status_code=500, detail=CommonProxyErrors.db_not_connected_error.value + ) + + try: + tool = await db_get_tool(prisma_client=prisma_client, tool_name=tool_name) + if tool is None: + raise HTTPException( + status_code=404, detail=f"Tool '{tool_name}' not found" + ) + return tool + except HTTPException: + raise + except Exception as e: + verbose_proxy_logger.exception("Error getting tool: %s", e) + raise HTTPException(status_code=500, detail=str(e)) + + +@router.post( + "/v1/tool/policy", + tags=["tool management"], + dependencies=[Depends(user_api_key_auth)], + response_model=ToolPolicyUpdateResponse, +) +async def update_tool_policy( + data: ToolPolicyUpdateRequest, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Set the call policy for a tool. + + Parameters: + - tool_name: str - The tool to update + - call_policy: "trusted" | "untrusted" | "dual_llm" | "blocked" + + Setting a tool to "blocked" will cause the ToolPolicyGuardrail to remove + that tool_call from LLM responses before returning them to the client. + """ + from litellm.proxy.db.tool_registry_writer import ( + update_tool_policy as db_update_tool_policy, + ) + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException( + status_code=500, detail=CommonProxyErrors.db_not_connected_error.value + ) + + try: + updated = await db_update_tool_policy( + prisma_client=prisma_client, + tool_name=data.tool_name, + call_policy=data.call_policy, + updated_by=user_api_key_dict.user_id, + ) + if updated is None: + raise HTTPException( + status_code=500, detail=f"Failed to update policy for tool '{data.tool_name}'" + ) + return ToolPolicyUpdateResponse( + tool_name=updated.tool_name, + call_policy=updated.call_policy, + updated=True, + ) + except HTTPException: + raise + except Exception as e: + verbose_proxy_logger.exception("Error updating tool policy: %s", e) + raise HTTPException(status_code=500, detail=str(e)) diff --git a/litellm/proxy/management_endpoints/usage_endpoints/__init__.py b/litellm/proxy/management_endpoints/usage_endpoints/__init__.py new file mode 100644 index 00000000000..6e68dcd2a2e --- /dev/null +++ b/litellm/proxy/management_endpoints/usage_endpoints/__init__.py @@ -0,0 +1,9 @@ +""" +Usage endpoints package. + +Re-exports the router from endpoints module. +""" + +from litellm.proxy.management_endpoints.usage_endpoints.endpoints import ( # noqa: F401 + router, +) diff --git a/litellm/proxy/management_endpoints/usage_endpoints/ai_usage_chat.py b/litellm/proxy/management_endpoints/usage_endpoints/ai_usage_chat.py new file mode 100644 index 00000000000..f156be7d2cc --- /dev/null +++ b/litellm/proxy/management_endpoints/usage_endpoints/ai_usage_chat.py @@ -0,0 +1,578 @@ +""" +AI Usage Chat - uses LLM tool calling to answer questions about +usage/spend data by querying the aggregated daily activity endpoints. +""" + +import json +from datetime import date +from typing import Any, AsyncIterator, Callable, Dict, List, Literal, Optional + +import litellm +from litellm._logging import verbose_proxy_logger +from litellm.constants import DEFAULT_COMPETITOR_DISCOVERY_MODEL +from litellm.types.proxy.management_endpoints.common_daily_activity import ( + SpendAnalyticsPaginatedResponse, +) + +from typing_extensions import TypedDict + +# --------------------------------------------------------------------------- +# Constants +# --------------------------------------------------------------------------- + +USAGE_AI_TEMPERATURE = 0.2 + +TABLE_DAILY_USER_SPEND = "litellm_dailyuserspend" +TABLE_DAILY_TEAM_SPEND = "litellm_dailyteamspend" +TABLE_DAILY_TAG_SPEND = "litellm_dailytagspend" + +ENTITY_FIELD_USER = "user_id" +ENTITY_FIELD_TEAM = "team_id" +ENTITY_FIELD_TAG = "tag" + +PAGINATED_PAGE_SIZE = 200 +MAX_CHAT_MESSAGES = 20 +TOP_N_MODELS = 15 +TOP_N_PROVIDERS = 10 +TOP_N_KEYS = 10 + +# --------------------------------------------------------------------------- +# Types +# --------------------------------------------------------------------------- + + +class SSEStatusEvent(TypedDict): + type: Literal["status"] + message: str + + +class SSEToolCallEvent(TypedDict, total=False): + type: Literal["tool_call"] + tool_name: str + tool_label: str + arguments: Dict[str, str] + status: Literal["running", "complete", "error"] + error: str + + +class SSEChunkEvent(TypedDict): + type: Literal["chunk"] + content: str + + +class SSEDoneEvent(TypedDict): + type: Literal["done"] + + +class SSEErrorEvent(TypedDict): + type: Literal["error"] + message: str + + +SSEEvent = ( + SSEStatusEvent | SSEToolCallEvent | SSEChunkEvent | SSEDoneEvent | SSEErrorEvent +) + + +class ToolHandler(TypedDict): + fetch: Callable[..., Any] + summarise: Callable[[Dict[str, Any]], str] + label: str + + +# --------------------------------------------------------------------------- +# Tool definitions (OpenAI function-calling schema) +# --------------------------------------------------------------------------- + +_DATE_PARAMS = { + "start_date": {"type": "string", "description": "Start date in YYYY-MM-DD format"}, + "end_date": {"type": "string", "description": "End date in YYYY-MM-DD format"}, +} + +_TOOL_USAGE = { + "type": "function", + "function": { + "name": "get_usage_data", + "description": ( + "Fetch aggregated global usage/spend data. Returns daily spend, " + "token counts, request counts, and breakdowns by model, provider, " + "and API key. Use for overall spend, top models, top providers." + ), + "parameters": { + "type": "object", + "properties": { + **_DATE_PARAMS, + "user_id": { + "type": "string", + "description": "Optional user ID filter. Omit for global view.", + }, + }, + "required": ["start_date", "end_date"], + }, + }, +} + +_TOOL_TEAM = { + "type": "function", + "function": { + "name": "get_team_usage_data", + "description": ( + "Fetch usage/spend data broken down by team. Use for questions " + "like 'which team spends the most' or 'show me team X usage'." + ), + "parameters": { + "type": "object", + "properties": { + **_DATE_PARAMS, + "team_ids": { + "type": "string", + "description": "Optional comma-separated team IDs. Omit for all teams.", + }, + }, + "required": ["start_date", "end_date"], + }, + }, +} + +_TOOL_TAG = { + "type": "function", + "function": { + "name": "get_tag_usage_data", + "description": ( + "Fetch usage/spend data broken down by tag. Tags are labels " + "attached to requests (features, environments, credentials)." + ), + "parameters": { + "type": "object", + "properties": { + **_DATE_PARAMS, + "tags": { + "type": "string", + "description": "Optional comma-separated tag names. Omit for all tags.", + }, + }, + "required": ["start_date", "end_date"], + }, + }, +} + +TOOLS_BASE = [_TOOL_USAGE] +TOOLS_ADMIN = [_TOOL_USAGE, _TOOL_TEAM, _TOOL_TAG] + + +def get_tools_for_role(is_admin: bool) -> List[Dict[str, Any]]: + """Return the tool list appropriate for the user's role.""" + return TOOLS_ADMIN if is_admin else TOOLS_BASE + + +_SYSTEM_PROMPT_BASE = ( + "You are an AI assistant embedded in the LiteLLM Usage dashboard. " + "You help users understand their LLM API spend and usage data.\n\n" + "ALWAYS call the appropriate tool(s) first to fetch data before answering. " + "You may call multiple tools if the question spans different dimensions.\n\n" + "Guidelines:\n" + "- Be concise and specific. Use exact numbers from the data.\n" + "- Format costs as dollar amounts (e.g. $12.34).\n" + "- When comparing entities, show a ranked list.\n" + "- If data is empty or no results found, say so clearly.\n" + "- Do not hallucinate data — only use what the tools return.\n" + "- Today's date will be provided below. Use it to interpret relative dates " + "like 'this week', 'this month', 'last 7 days', etc." +) + +_TOOL_DESCRIPTIONS_ADMIN = ( + "You have access to these tools:\n" + "- `get_usage_data`: Global/user-level usage (spend, models, providers, API keys)\n" + "- `get_team_usage_data`: Team-level usage breakdown\n" + "- `get_tag_usage_data`: Tag-level usage breakdown\n\n" +) + +_TOOL_DESCRIPTIONS_BASE = ( + "You have access to this tool:\n" + "- `get_usage_data`: Your usage data (spend, models, providers, API keys)\n\n" +) + + +def _build_system_prompt(is_admin: bool) -> str: + """Build role-appropriate system prompt with today's date.""" + tool_desc = _TOOL_DESCRIPTIONS_ADMIN if is_admin else _TOOL_DESCRIPTIONS_BASE + return ( + f"{_SYSTEM_PROMPT_BASE}\n\n{tool_desc}" + f"Today's date: {date.today().isoformat()}" + ) + + +# keep a public reference for test assertions +SYSTEM_PROMPT = _SYSTEM_PROMPT_BASE + +# --------------------------------------------------------------------------- +# Data fetchers +# --------------------------------------------------------------------------- + + +def _parse_csv_ids(raw: Optional[str]) -> Optional[List[str]]: + if not raw: + return None + return [t.strip() for t in raw.split(",") if t.strip()] + + +async def _query_activity( + table_name: str, + entity_id_field: str, + entity_id: Optional[Any], + start_date: str, + end_date: str, + *, + use_aggregated: bool = False, +) -> SpendAnalyticsPaginatedResponse: + """Shared helper that calls the daily activity query layer.""" + from litellm.proxy.management_endpoints.common_daily_activity import ( + get_daily_activity, + get_daily_activity_aggregated, + ) + from litellm.proxy.proxy_server import prisma_client + + if use_aggregated: + return await get_daily_activity_aggregated( + prisma_client=prisma_client, + table_name=table_name, + entity_id_field=entity_id_field, + entity_id=entity_id, + entity_metadata_field=None, + start_date=start_date, + end_date=end_date, + model=None, + api_key=None, + ) + return await get_daily_activity( + prisma_client=prisma_client, + table_name=table_name, + entity_id_field=entity_id_field, + entity_id=entity_id, + entity_metadata_field=None, + start_date=start_date, + end_date=end_date, + model=None, + api_key=None, + page=1, + page_size=PAGINATED_PAGE_SIZE, + ) + + +async def _fetch_usage_data( + start_date: str, end_date: str, user_id: Optional[str] = None +) -> Dict[str, Any]: + resp = await _query_activity( + TABLE_DAILY_USER_SPEND, + ENTITY_FIELD_USER, + user_id, + start_date, + end_date, + use_aggregated=True, + ) + return resp.model_dump(mode="json") + + +async def _fetch_team_usage_data( + start_date: str, end_date: str, team_ids: Optional[str] = None +) -> Dict[str, Any]: + resp = await _query_activity( + TABLE_DAILY_TEAM_SPEND, + ENTITY_FIELD_TEAM, + _parse_csv_ids(team_ids), + start_date, + end_date, + ) + return resp.model_dump(mode="json") + + +async def _fetch_tag_usage_data( + start_date: str, end_date: str, tags: Optional[str] = None +) -> Dict[str, Any]: + resp = await _query_activity( + TABLE_DAILY_TAG_SPEND, + ENTITY_FIELD_TAG, + _parse_csv_ids(tags), + start_date, + end_date, + ) + return resp.model_dump(mode="json") + + +# --------------------------------------------------------------------------- +# Summarisers — convert raw JSON to concise text the LLM can reason over +# --------------------------------------------------------------------------- + + +def _accumulate_breakdown( + results: List[Dict[str, Any]], dimension: str, fields: List[str] +) -> Dict[str, Dict[str, float]]: + """Aggregate a single breakdown dimension across days.""" + totals: Dict[str, Dict[str, float]] = {} + for day in results: + for key, entry in day.get("breakdown", {}).get(dimension, {}).items(): + if key not in totals: + totals[key] = {f: 0.0 for f in fields} + m = entry.get("metrics", {}) + for f in fields: + totals[key][f] += m.get(f, 0) + return totals + + +def _ranked_lines( + totals: Dict[str, Dict[str, float]], + fmt: Callable[[str, Dict[str, float]], str], + limit: int, +) -> List[str]: + """Sort by spend descending, format each entry, and truncate.""" + return [ + fmt(name, vals) + for name, vals in sorted(totals.items(), key=lambda x: -x[1].get("spend", 0))[ + :limit + ] + ] + + +def _summarise_usage_data(data: Dict[str, Any]) -> str: + meta = data.get("metadata", {}) + results = data.get("results", []) + + header = ( + f"Total Spend: ${meta.get('total_spend', 0):.4f}\n" + f"Total Requests: {meta.get('total_api_requests', 0)}\n" + f"Successful: {meta.get('total_successful_requests', 0)} | " + f"Failed: {meta.get('total_failed_requests', 0)}\n" + f"Total Tokens: {meta.get('total_tokens', 0)}" + ) + + models = _accumulate_breakdown( + results, "models", ["spend", "api_requests", "total_tokens"] + ) + providers = _accumulate_breakdown(results, "providers", ["spend", "api_requests"]) + + model_lines = _ranked_lines( + models, + lambda n, d: f" - {n}: ${d['spend']:.4f} ({int(d['api_requests'])} reqs, {int(d['total_tokens'])} tokens)", + TOP_N_MODELS, + ) + provider_lines = _ranked_lines( + providers, + lambda n, d: f" - {n}: ${d['spend']:.4f} ({int(d['api_requests'])} reqs)", + TOP_N_PROVIDERS, + ) + + sections = [header, ""] + sections += ["Top Models by Spend:"] + (model_lines or [" (no data)"]) + [""] + sections += ["Top Providers by Spend:"] + (provider_lines or [" (no data)"]) + return "\n".join(sections) + + +def _summarise_entity_data(data: Dict[str, Any], entity_label: str) -> str: + """Summarise team/tag entity usage data.""" + results = data.get("results", []) + if not results: + return f"No {entity_label} usage data found for the given date range." + + totals: Dict[str, Dict[str, Any]] = {} + for day in results: + for eid, entry in day.get("breakdown", {}).get("entities", {}).items(): + if eid not in totals: + alias = entry.get("metadata", {}).get("alias", eid) + totals[eid] = {"alias": alias, "spend": 0.0, "requests": 0, "tokens": 0} + m = entry.get("metrics", {}) + totals[eid]["spend"] += m.get("spend", 0) + totals[eid]["requests"] += m.get("api_requests", 0) + totals[eid]["tokens"] += m.get("total_tokens", 0) + + lines = [f"{entity_label} Usage ({len(totals)} {entity_label.lower()}s):", ""] + for eid, d in sorted(totals.items(), key=lambda x: -x[1]["spend"]): + label = d["alias"] if d["alias"] != eid else eid + lines.append( + f"- {label} (ID: {eid}): ${d['spend']:.4f} | " + f"{int(d['requests'])} reqs | {int(d['tokens'])} tokens" + ) + return "\n".join(lines) + + +# --------------------------------------------------------------------------- +# Tool dispatch registry +# --------------------------------------------------------------------------- + +TOOL_HANDLERS: Dict[str, ToolHandler] = { + "get_usage_data": ToolHandler( + fetch=_fetch_usage_data, + summarise=_summarise_usage_data, + label="global usage data", + ), + "get_team_usage_data": ToolHandler( + fetch=_fetch_team_usage_data, + summarise=lambda data: _summarise_entity_data(data, "Team"), + label="team usage data", + ), + "get_tag_usage_data": ToolHandler( + fetch=_fetch_tag_usage_data, + summarise=lambda data: _summarise_entity_data(data, "Tag"), + label="tag usage data", + ), +} + + +# --------------------------------------------------------------------------- +# SSE streaming +# --------------------------------------------------------------------------- + + +def _sse(event: SSEEvent) -> str: + return f"data: {json.dumps(event)}\n\n" + + +def _resolve_fetch_kwargs( + fn_name: str, + fn_args: Dict[str, str], + user_id: Optional[str], + is_admin: bool, +) -> Dict[str, Any]: + """Build keyword arguments for a tool's fetch function.""" + start_date = fn_args.get("start_date", "") + end_date = fn_args.get("end_date", "") + if not start_date or not end_date: + raise ValueError("Missing required start_date or end_date from tool arguments") + kwargs: Dict[str, Any] = {"start_date": start_date, "end_date": end_date} + if fn_name == "get_usage_data": + if not is_admin: + kwargs["user_id"] = user_id + elif fn_args.get("user_id"): + kwargs["user_id"] = fn_args["user_id"] + elif fn_name == "get_team_usage_data" and fn_args.get("team_ids"): + kwargs["team_ids"] = fn_args["team_ids"] + elif fn_name == "get_tag_usage_data" and fn_args.get("tags"): + kwargs["tags"] = fn_args["tags"] + return kwargs + + +async def _execute_tool_call( + handler: ToolHandler, + fn_name: str, + fn_args: Dict[str, str], + user_id: Optional[str], + is_admin: bool, +) -> str: + """Run a single tool and return the summarised result text.""" + kwargs = _resolve_fetch_kwargs(fn_name, fn_args, user_id, is_admin) + raw_data = await handler["fetch"](**kwargs) + return handler["summarise"](raw_data) + + +async def _process_tool_call( + tc: Any, + chat_messages: List[Dict[str, Any]], + user_id: Optional[str], + is_admin: bool, +) -> AsyncIterator[str]: + """Execute a single tool call, yielding SSE events for status.""" + fn_name = tc.function.name + fn_args = json.loads(tc.function.arguments) + + allowed_names = {t["function"]["name"] for t in get_tools_for_role(is_admin)} + handler = TOOL_HANDLERS.get(fn_name) + + if fn_name not in allowed_names or not handler: + chat_messages.append( + { + "role": "tool", + "tool_call_id": tc.id, + "content": f"Tool not available: {fn_name}", + } + ) + return + + tool_event_base = { + "type": "tool_call", + "tool_name": fn_name, + "tool_label": handler["label"], + "arguments": fn_args, + } + yield _sse({**tool_event_base, "status": "running"}) + + try: + tool_result = await _execute_tool_call( + handler, fn_name, fn_args, user_id, is_admin + ) + yield _sse({**tool_event_base, "status": "complete"}) + except Exception as e: + verbose_proxy_logger.error("Tool %s failed: %s", fn_name, e) + tool_result = f"Error fetching {handler['label']}. Please try again." + yield _sse({**tool_event_base, "status": "error"}) + + chat_messages.append( + {"role": "tool", "tool_call_id": tc.id, "content": tool_result} + ) + + +async def _stream_final_response( + model: str, chat_messages: List[Dict[str, Any]] +) -> AsyncIterator[str]: + """Stream the final LLM response after tool results are appended.""" + yield _sse({"type": "status", "message": "Analyzing results..."}) + + response = await litellm.acompletion( + model=model, + messages=chat_messages, + stream=True, + temperature=USAGE_AI_TEMPERATURE, + ) + async for chunk in response: + delta = chunk.choices[0].delta.content + if delta: + yield _sse({"type": "chunk", "content": delta}) + + +async def stream_usage_ai_chat( + messages: List[Dict[str, str]], + model: Optional[str] = None, + user_id: Optional[str] = None, + is_admin: bool = False, +) -> AsyncIterator[str]: + """Stream SSE events: status → tool_call → chunk → done.""" + resolved_model = (model or "").strip() or DEFAULT_COMPETITOR_DISCOVERY_MODEL + truncated = ( + messages[-MAX_CHAT_MESSAGES:] if len(messages) > MAX_CHAT_MESSAGES else messages + ) + chat_messages: List[Dict[str, Any]] = [ + {"role": "system", "content": _build_system_prompt(is_admin)}, + *truncated, + ] + + try: + yield _sse({"type": "status", "message": "Thinking..."}) + tools = get_tools_for_role(is_admin) + response = await litellm.acompletion( + model=resolved_model, + messages=chat_messages, + tools=tools, + temperature=USAGE_AI_TEMPERATURE, + ) + choice = response.choices[0] # type: ignore + + if not choice.message.tool_calls: + if choice.message.content: + yield _sse({"type": "chunk", "content": choice.message.content}) + yield _sse({"type": "done"}) + return + + chat_messages.append(choice.message.model_dump()) + for tc in choice.message.tool_calls: + async for event in _process_tool_call(tc, chat_messages, user_id, is_admin): + yield event + async for event in _stream_final_response(resolved_model, chat_messages): + yield event + yield _sse({"type": "done"}) + + except Exception as e: + verbose_proxy_logger.error("AI usage chat failed: %s", e) + yield _sse( + { + "type": "error", + "message": "An internal error occurred. Please try again.", + } + ) diff --git a/litellm/proxy/management_endpoints/usage_endpoints/endpoints.py b/litellm/proxy/management_endpoints/usage_endpoints/endpoints.py new file mode 100644 index 00000000000..0dbe518afb7 --- /dev/null +++ b/litellm/proxy/management_endpoints/usage_endpoints/endpoints.py @@ -0,0 +1,65 @@ +""" +USAGE AI CHAT ENDPOINTS + +/usage/ai/chat - Stream AI chat responses about usage data +""" + +from typing import List, Literal, Optional + +from fastapi import APIRouter, Depends, Request +from fastapi.responses import StreamingResponse +from pydantic import BaseModel, Field + +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + +router = APIRouter() + + +class ChatMessage(BaseModel): + role: Literal["user", "assistant"] + content: str + + +class UsageAIChatRequest(BaseModel): + messages: List[ChatMessage] = Field( + ..., description="Chat messages (user/assistant history)" + ) + model: Optional[str] = Field(default=None, description="Model to use for AI chat") + + +@router.post( + "/usage/ai/chat", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], +) +async def usage_ai_chat( + data: UsageAIChatRequest, + request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + AI chat about usage data. Streams SSE events with the AI response. + The AI agent has access to tools that query aggregated daily activity data. + """ + from litellm.proxy.management_endpoints.common_utils import ( + _user_has_admin_view, + ) + from litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat import ( + stream_usage_ai_chat, + ) + + is_admin = _user_has_admin_view(user_api_key_dict) + user_id = user_api_key_dict.user_id + messages = [{"role": m.role, "content": m.content} for m in data.messages] + + return StreamingResponse( + stream_usage_ai_chat( + messages=messages, + model=data.model, + user_id=user_id, + is_admin=is_admin, + ), + media_type="text/event-stream", + headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"}, + ) diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index 81144ad9f31..028edea8c3f 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -28,6 +28,7 @@ from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.http_parsing_utils import ( _read_request_body, + _safe_get_request_headers, _safe_set_request_parsed_body, get_form_data, get_request_body, @@ -60,7 +61,7 @@ def create_request_copy(request: Request): return { "method": request.method, "url": str(request.url), - "headers": dict(request.headers), + "headers": _safe_get_request_headers(request).copy(), "cookies": request.cookies, "query_params": dict(request.query_params), } @@ -329,7 +330,7 @@ async def vllm_proxy_route( method=request.method, endpoint=endpoint, request_query_params=request.query_params, - request_headers=dict(request.headers), + request_headers=_safe_get_request_headers(request), stream=request_body.get("stream", False), content=None, data=None, @@ -1307,7 +1308,7 @@ async def azure_proxy_route( method=request.method, endpoint=endpoint, request_query_params=request.query_params, - request_headers=dict(request.headers), + request_headers=_safe_get_request_headers(request), stream=request_body.get("stream", False), content=None, data=None, @@ -1505,7 +1506,7 @@ def get_vertex_ai_allowed_incoming_headers(request: Request) -> dict: Returns: dict: Headers dictionary with only allowed headers """ - incoming_headers = dict(request.headers) or {} + incoming_headers = _safe_get_request_headers(request) headers = {} for header_name in ALLOWED_VERTEX_AI_PASSTHROUGH_HEADERS: if header_name in incoming_headers: @@ -1621,7 +1622,7 @@ async def _prepare_vertex_auth_headers( if ( vertex_credentials is None or vertex_credentials.vertex_project is None ) and router_credentials is None: - headers = dict(request.headers) or {} + headers = _safe_get_request_headers(request).copy() headers_passed_through = True verbose_proxy_logger.debug( "default_vertex_config not set, incoming request headers %s", headers diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index d1c4b8b3403..356807415de 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -50,7 +50,10 @@ from litellm.proxy._types import ( ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing -from litellm.proxy.common_utils.http_parsing_utils import _read_request_body +from litellm.proxy.common_utils.http_parsing_utils import ( + _read_request_body, + _safe_get_request_headers, +) from litellm.proxy.utils import get_server_root_path from litellm.secret_managers.main import get_secret_str from litellm.types.llms.custom_http import httpxSpecialProvider @@ -649,7 +652,7 @@ async def pass_through_request( # noqa: PLR0915 url = httpx.URL(target) headers = custom_headers headers = HttpPassThroughEndpointHelpers.forward_headers_from_request( - request_headers=dict(request.headers), + request_headers=_safe_get_request_headers(request).copy(), headers=headers, forward_headers=forward_headers, ) diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 35a75d4caf9..607306f3806 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -9,6 +9,7 @@ import secrets import shutil import subprocess import sys +import threading import time import traceback import warnings @@ -293,6 +294,7 @@ from litellm.proxy.common_utils.encrypt_decrypt_utils import ( from litellm.proxy.common_utils.html_forms.ui_login import build_ui_login_form from litellm.proxy.common_utils.http_parsing_utils import ( _read_request_body, + _safe_get_request_headers, check_file_size_under_limit, get_form_data, ) @@ -390,6 +392,7 @@ from litellm.proxy.management_endpoints.organization_endpoints import ( router as organization_router, ) from litellm.proxy.management_endpoints.policy_endpoints import router as policy_router +from litellm.proxy.management_endpoints.usage_endpoints import router as usage_ai_router from litellm.proxy.management_endpoints.project_endpoints import ( router as project_router, ) @@ -408,6 +411,9 @@ from litellm.proxy.management_endpoints.team_endpoints import ( update_team, validate_membership, ) +from litellm.proxy.management_endpoints.tool_management_endpoints import ( + router as tool_management_router, +) from litellm.proxy.management_endpoints.ui_sso import ( get_disabled_non_admin_personal_key_creation, ) @@ -658,7 +664,7 @@ _description = ( def cleanup_router_config_variables(): - global master_key, user_config_file_path, otel_logging, user_custom_auth, user_custom_auth_path, user_custom_key_generate, user_custom_sso, user_custom_ui_sso_sign_in_handler, use_background_health_checks, use_shared_health_check, health_check_interval, prisma_client + global master_key, user_config_file_path, otel_logging, user_custom_auth, user_custom_auth_path, user_custom_key_generate, user_custom_sso, user_custom_ui_sso_sign_in_handler, use_background_health_checks, use_shared_health_check, health_check_interval, health_check_concurrency, prisma_client # Set all variables to None master_key = None @@ -672,6 +678,7 @@ def cleanup_router_config_variables(): use_background_health_checks = None use_shared_health_check = None health_check_interval = None + health_check_concurrency = None prisma_client = None @@ -711,7 +718,7 @@ async def _initialize_shared_aiohttp_session(): try: from aiohttp import ClientSession, TCPConnector - connector_kwargs = { + connector_kwargs: Dict[str, Any] = { "keepalive_timeout": AIOHTTP_KEEPALIVE_TIMEOUT, "ttl_dns_cache": AIOHTTP_TTL_DNS_CACHE, } @@ -822,7 +829,9 @@ async def proxy_startup_event(app: FastAPI): # noqa: PLR0915 verbose_proxy_logger.debug("About to initialize semantic tool filter") _config = proxy_config.get_config_state() _litellm_settings = _config.get("litellm_settings", {}) - verbose_proxy_logger.debug(f"litellm_settings keys = {list(_litellm_settings.keys())}") + verbose_proxy_logger.debug( + f"litellm_settings keys = {list(_litellm_settings.keys())}" + ) await ProxyStartupEvent._initialize_semantic_tool_filter( llm_router=llm_router, litellm_settings=_litellm_settings, @@ -1468,7 +1477,9 @@ redis_usage_cache: Optional[ RedisCache ] = None # redis cache used for tracking spend, tpm/rpm limits polling_via_cache_enabled: Union[Literal["all"], List[str], bool] = False -native_background_mode: List[str] = [] # Models that should use native provider background mode instead of polling +native_background_mode: List[ + str +] = [] # Models that should use native provider background mode instead of polling polling_cache_ttl: int = 3600 # Default 1 hour TTL for polling cache user_custom_auth = None user_custom_key_generate = None @@ -1478,8 +1489,11 @@ use_background_health_checks = None use_shared_health_check = None use_queue = False health_check_interval = None +health_check_concurrency = None health_check_details = None health_check_results: Dict[str, Union[int, List[Dict[str, Any]]]] = {} +background_health_check_loop_active = False +background_health_check_cycle_seq = 0 queue: List = [] litellm_proxy_budget_name = "litellm-proxy-budget" litellm_proxy_admin_name = LITELLM_PROXY_ADMIN_NAME @@ -1759,8 +1773,14 @@ async def update_cache( # noqa: PLR0915 ("{}:spend".format(litellm_proxy_admin_name), increment) ) except Exception as e: - verbose_proxy_logger.debug( - f"An error occurred updating user cache: {str(e)}\n\n{traceback.format_exc()}" + verbose_proxy_logger.warning( + "Spend tracking - failed to update user spend in cache. " + "Budget enforcement may use stale spend values. " + "user_id=%s, response_cost=%s - %s\n%s", + user_id, + response_cost, + str(e), + traceback.format_exc(), ) ### UPDATE END-USER SPEND ### @@ -1797,8 +1817,14 @@ async def update_cache( # noqa: PLR0915 existing_spend_obj.spend = new_spend values_to_update_in_cache.append((_id, existing_spend_obj.json())) except Exception as e: - verbose_proxy_logger.exception( - f"An error occurred updating end user cache: {str(e)}" + verbose_proxy_logger.warning( + "Spend tracking - failed to update end user spend in cache. " + "Budget enforcement may use stale spend values. " + "end_user_id=%s, response_cost=%s - %s\n%s", + end_user_id, + response_cost, + str(e), + traceback.format_exc(), ) ### UPDATE TEAM SPEND ### @@ -1839,8 +1865,14 @@ async def update_cache( # noqa: PLR0915 existing_spend_obj.spend = new_spend values_to_update_in_cache.append((_id, existing_spend_obj)) except Exception as e: - verbose_proxy_logger.exception( - f"An error occurred updating end user cache: {str(e)}" + verbose_proxy_logger.warning( + "Spend tracking - failed to update team spend in cache. " + "Budget enforcement may use stale spend values. " + "team_id=%s, response_cost=%s - %s\n%s", + team_id, + response_cost, + str(e), + traceback.format_exc(), ) ### UPDATE TAG SPEND ### @@ -1885,8 +1917,14 @@ async def update_cache( # noqa: PLR0915 existing_tag_obj.spend = new_spend values_to_update_in_cache.append((cache_key, existing_tag_obj)) except Exception as e: - verbose_proxy_logger.exception( - f"An error occurred updating tag cache: {str(e)}" + verbose_proxy_logger.warning( + "Spend tracking - failed to update tag spend in cache. " + "Budget enforcement may use stale spend values. " + "tags=%s, response_cost=%s - %s\n%s", + tags, + response_cost, + str(e), + traceback.format_exc(), ) if token is not None and response_cost is not None: @@ -1927,6 +1965,88 @@ def run_ollama_serve(): ) +def _get_process_rss_mb() -> Optional[float]: + """ + Get process RSS memory in MB. + On Linux, ru_maxrss is in KB. On macOS, ru_maxrss is in bytes. + """ + try: + import resource + + ru_maxrss = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss + if sys.platform == "darwin": + return float(ru_maxrss) / (1024 * 1024) + return float(ru_maxrss) / 1024 + except Exception: + return None + + +def _rss_mb_for_log() -> str: + rss_mb = _get_process_rss_mb() + if rss_mb is None: + return "unknown" + return f"{rss_mb:.2f}" + + +async def _run_direct_health_check_with_instrumentation( + model_list: list, + details: Optional[bool], + max_concurrency: Optional[int], + instrumentation_context: dict, +): + try: + return await perform_health_check( + model_list=model_list, + details=details, + max_concurrency=max_concurrency, + instrumentation_context=instrumentation_context, + ) + except TypeError as e: + if "instrumentation_context" not in str(e): + raise + # Backward compatibility for monkeypatched or wrapped callables + # that do not accept instrumentation_context. + return await perform_health_check( + model_list=model_list, + details=details, + max_concurrency=max_concurrency, + ) + + +def _schedule_background_health_check_db_save( + prisma_client, + shared_health_manager, + model_list: list, + healthy_endpoints: list, + unhealthy_endpoints: list, +): + """Fire-and-forget: persist health check results to DB if prisma is available.""" + if prisma_client is None: + return + import time as time_module + + from litellm.proxy.health_endpoints._health_endpoints import ( + _save_background_health_checks_to_db, + ) + + checked_by = ( + shared_health_manager.pod_id + if shared_health_manager is not None + else "background_health_check" + ) + start_time = time_module.time() + asyncio.create_task( + _save_background_health_checks_to_db( + prisma_client, + model_list, + healthy_endpoints, + unhealthy_endpoints, + start_time, + checked_by=checked_by, + ) + ) + + async def _run_background_health_check(): """ Periodically run health checks in the background on the endpoints. @@ -1934,7 +2054,10 @@ async def _run_background_health_check(): Update health_check_results, based on this. Uses shared health check state when Redis is available to coordinate across pods. """ - global health_check_results, llm_model_list, health_check_interval, health_check_details, use_shared_health_check, redis_usage_cache, prisma_client + global health_check_results, llm_model_list, health_check_interval + global health_check_concurrency, health_check_details, use_shared_health_check + global redis_usage_cache, prisma_client + global background_health_check_loop_active, background_health_check_cycle_seq if ( health_check_interval is None @@ -1943,6 +2066,24 @@ async def _run_background_health_check(): ): return + if background_health_check_loop_active: + verbose_proxy_logger.warning( + "background_health_check_loop_overlap_detected existing_loop_active=true interval_seconds=%s max_concurrency=%s shared=%s", + health_check_interval, + health_check_concurrency, + use_shared_health_check, + ) + background_health_check_loop_active = True + verbose_proxy_logger.info( + "background_health_check_loop_started interval_seconds=%s max_concurrency=%s shared=%s details=%s thread_count=%d rss_mb=%s", + health_check_interval, + health_check_concurrency, + use_shared_health_check, + health_check_details, + threading.active_count(), + _rss_mb_for_log(), + ) + # Initialize shared health check manager if Redis is available and feature is enabled shared_health_manager = None if use_shared_health_check and redis_usage_cache is not None: @@ -1958,8 +2099,13 @@ async def _run_background_health_check(): verbose_proxy_logger.info("Initialized shared health check manager") while True: + background_health_check_cycle_seq += 1 + cycle_id = f"bg-{background_health_check_cycle_seq}" + cycle_start_time = time.monotonic() + # make 1 deep copy of llm_model_list on every health check iteration _llm_model_list = copy.deepcopy(llm_model_list) or [] + model_count_total = len(_llm_model_list) # filter out models that have disabled background health checks _llm_model_list = [ @@ -1967,6 +2113,33 @@ async def _run_background_health_check(): for m in _llm_model_list if not m.get("model_info", {}).get("disable_background_health_check", False) ] + model_count_enabled = len(_llm_model_list) + expected_peak_in_flight = model_count_enabled + if ( + isinstance(health_check_concurrency, int) + and health_check_concurrency > 0 + and model_count_enabled > 0 + ): + expected_peak_in_flight = min(model_count_enabled, health_check_concurrency) + + verbose_proxy_logger.debug( + "background_health_check_cycle_start cycle_id=%s model_count_total=%d model_count_enabled=%d interval_seconds=%s max_concurrency=%s expected_peak_in_flight=%d shared=%s thread_count=%d rss_mb=%s", + cycle_id, + model_count_total, + model_count_enabled, + health_check_interval, + health_check_concurrency, + expected_peak_in_flight, + shared_health_manager is not None, + threading.active_count(), + _rss_mb_for_log(), + ) + + instrumentation_context = { + "enabled": True, + "source": "proxy_background_loop", + "cycle_id": cycle_id, + } # Use shared health check if available, otherwise fall back to direct health check # Convert health_check_details to bool for perform_shared_health_check (defaults to True if None) @@ -1980,19 +2153,31 @@ async def _run_background_health_check(): healthy_endpoints, unhealthy_endpoints, ) = await shared_health_manager.perform_shared_health_check( - model_list=_llm_model_list, details=details_bool + model_list=_llm_model_list, + details=details_bool, + max_concurrency=health_check_concurrency, ) except Exception as e: verbose_proxy_logger.error( "Error in shared health check, falling back to direct health check: %s", str(e), ) - healthy_endpoints, unhealthy_endpoints = await perform_health_check( - model_list=_llm_model_list, details=health_check_details + healthy_endpoints, unhealthy_endpoints = ( + await _run_direct_health_check_with_instrumentation( + _llm_model_list, + health_check_details, + health_check_concurrency, + instrumentation_context, + ) ) else: - healthy_endpoints, unhealthy_endpoints = await perform_health_check( - model_list=_llm_model_list, details=health_check_details + healthy_endpoints, unhealthy_endpoints = ( + await _run_direct_health_check_with_instrumentation( + _llm_model_list, + health_check_details, + health_check_concurrency, + instrumentation_context, + ) ) # Update the global variable with the health check results @@ -2000,34 +2185,34 @@ async def _run_background_health_check(): health_check_results["unhealthy_endpoints"] = unhealthy_endpoints health_check_results["healthy_count"] = len(healthy_endpoints) health_check_results["unhealthy_count"] = len(unhealthy_endpoints) + cycle_duration_ms = (time.monotonic() - cycle_start_time) * 1000 + verbose_proxy_logger.debug( + "background_health_check_cycle_complete cycle_id=%s model_count_enabled=%d healthy_count=%d unhealthy_count=%d duration_ms=%.2f interval_seconds=%s thread_count=%d rss_mb=%s", + cycle_id, + model_count_enabled, + len(healthy_endpoints), + len(unhealthy_endpoints), + cycle_duration_ms, + health_check_interval, + threading.active_count(), + _rss_mb_for_log(), + ) + if cycle_duration_ms > (health_check_interval * 1000): + verbose_proxy_logger.warning( + "background_health_check_cycle_duration_exceeded_interval cycle_id=%s duration_ms=%.2f interval_seconds=%s", + cycle_id, + cycle_duration_ms, + health_check_interval, + ) # Save background health checks to database (non-blocking) - if prisma_client is not None: - import time as time_module - - from litellm.proxy.health_endpoints._health_endpoints import ( - _save_background_health_checks_to_db, - ) - - # Use pod_id or a system identifier for checked_by if shared health check is enabled - checked_by = None - if shared_health_manager is not None: - checked_by = shared_health_manager.pod_id - else: - # Use a system identifier for background health checks - checked_by = "background_health_check" - - start_time = time_module.time() - asyncio.create_task( - _save_background_health_checks_to_db( - prisma_client, - _llm_model_list, - healthy_endpoints, - unhealthy_endpoints, - start_time, - checked_by=checked_by, - ) - ) + _schedule_background_health_check_db_save( + prisma_client, + shared_health_manager, + _llm_model_list, + healthy_endpoints, + unhealthy_endpoints, + ) await asyncio.sleep(health_check_interval) @@ -2480,7 +2665,7 @@ class ProxyConfig: """ Load config values into proxy global state """ - global master_key, user_config_file_path, otel_logging, user_custom_auth, user_custom_auth_path, user_custom_key_generate, user_custom_sso, user_custom_ui_sso_sign_in_handler, use_background_health_checks, use_shared_health_check, health_check_interval, use_queue, proxy_budget_rescheduler_max_time, proxy_budget_rescheduler_min_time, ui_access_mode, litellm_master_key_hash, proxy_batch_write_at, disable_spend_logs, prompt_injection_detection_obj, redis_usage_cache, store_model_in_db, premium_user, open_telemetry_logger, health_check_details, proxy_batch_polling_interval, config_passthrough_endpoints + global master_key, user_config_file_path, otel_logging, user_custom_auth, user_custom_auth_path, user_custom_key_generate, user_custom_sso, user_custom_ui_sso_sign_in_handler, use_background_health_checks, use_shared_health_check, health_check_interval, health_check_concurrency, use_queue, proxy_budget_rescheduler_max_time, proxy_budget_rescheduler_min_time, ui_access_mode, litellm_master_key_hash, proxy_batch_write_at, disable_spend_logs, prompt_injection_detection_obj, redis_usage_cache, store_model_in_db, premium_user, open_telemetry_logger, health_check_details, proxy_batch_polling_interval, config_passthrough_endpoints config: dict = await self.get_config(config_file_path=config_file_path) @@ -2905,7 +3090,18 @@ class ProxyConfig: health_check_interval = general_settings.get( "health_check_interval", DEFAULT_HEALTH_CHECK_INTERVAL ) + health_check_concurrency = general_settings.get( + "health_check_concurrency", None + ) health_check_details = general_settings.get("health_check_details", True) + verbose_proxy_logger.info( + "background_health_check_config enabled=%s shared=%s interval_seconds=%s max_concurrency=%s details=%s", + use_background_health_checks, + use_shared_health_check, + health_check_interval, + health_check_concurrency, + health_check_details, + ) ### RBAC ### rbac_role_permissions = general_settings.get("role_permissions", None) @@ -2999,7 +3195,7 @@ class ProxyConfig: for k, v in router_settings.items(): if k in available_args: router_params[k] = v - elif k == "health_check_interval": + elif k in {"health_check_interval", "health_check_concurrency"}: raise ValueError( f"'{k}' is NOT a valid router_settings parameter. Please move it to 'general_settings'." ) @@ -4201,9 +4397,7 @@ class ProxyConfig: ) if self._should_load_db_object(object_type="semantic_filter_settings"): - await self._init_semantic_filter_settings_in_db( - prisma_client=prisma_client - ) + await self._init_semantic_filter_settings_in_db(prisma_client=prisma_client) async def _init_semantic_filter_settings_in_db(self, prisma_client: PrismaClient): """ @@ -5259,30 +5453,38 @@ class ProxyStartupEvent: ): """Initialize MCP semantic tool filter if configured""" from litellm.proxy.hooks.mcp_semantic_filter import SemanticToolFilterHook - - mcp_semantic_filter_config = litellm_settings.get("mcp_semantic_tool_filter", None) - + + mcp_semantic_filter_config = litellm_settings.get( + "mcp_semantic_tool_filter", None + ) + # Only proceed if the feature is configured and enabled - if not mcp_semantic_filter_config or not mcp_semantic_filter_config.get("enabled", False): - verbose_proxy_logger.debug("Semantic tool filter not configured or not enabled, skipping initialization") + if not mcp_semantic_filter_config or not mcp_semantic_filter_config.get( + "enabled", False + ): + verbose_proxy_logger.debug( + "Semantic tool filter not configured or not enabled, " + "skipping initialization" + ) return - + verbose_proxy_logger.debug( f"Initializing semantic tool filter: llm_router={llm_router is not None}, " f"config={mcp_semantic_filter_config}" ) - hook = await SemanticToolFilterHook.initialize_from_config( config=mcp_semantic_filter_config, llm_router=llm_router, ) - + if hook: verbose_proxy_logger.debug("Semantic tool filter hook registered") litellm.logging_callback_manager.add_litellm_callback(hook) else: # Only warn if the feature was configured but failed to initialize - verbose_proxy_logger.warning("Semantic tool filter hook was configured but failed to initialize") + verbose_proxy_logger.warning( + "Semantic tool filter hook was configured but failed to initialize" + ) @classmethod def _initialize_jwt_auth( @@ -8706,7 +8908,8 @@ async def _apply_search_filter_to_models( # Fetch database models if we need more for the current page if router_models_count < models_needed_for_page: models_to_fetch = min( - models_needed_for_page - router_models_count, db_models_total_count + models_needed_for_page - router_models_count, + db_models_total_count, ) if models_to_fetch > 0: @@ -8742,21 +8945,21 @@ async def _apply_search_filter_to_models( def _normalize_datetime_for_sorting(dt: Any) -> Optional[datetime]: """ Normalize a datetime value to a timezone-aware UTC datetime for sorting. - + This function handles: - None values: returns None - String values: parses ISO format strings and converts to UTC-aware datetime - Datetime objects: converts naive datetimes to UTC-aware, and aware datetimes to UTC - + Args: dt: Datetime value (None, str, or datetime object) - + Returns: UTC-aware datetime object, or None if input is None or cannot be parsed """ if dt is None: return None - + if isinstance(dt, str): try: # Handle ISO format strings, including 'Z' suffix @@ -8770,14 +8973,14 @@ def _normalize_datetime_for_sorting(dt: Any) -> Optional[datetime]: return parsed_dt except (ValueError, AttributeError): return None - + if isinstance(dt, datetime): # If naive, assume UTC and make it aware if dt.tzinfo is None: return dt.replace(tzinfo=timezone.utc) # If aware, convert to UTC return dt.astimezone(timezone.utc) - + return None @@ -8797,46 +9000,60 @@ def _sort_models( Returns: Sorted list of models """ - if not sort_by or sort_by not in ["model_name", "created_at", "updated_at", "costs", "status"]: + if not sort_by or sort_by not in [ + "model_name", + "created_at", + "updated_at", + "costs", + "status", + ]: return all_models reverse = sort_order.lower() == "desc" def get_sort_key(model: Dict[str, Any]) -> Any: model_info = model.get("model_info", {}) - + if sort_by == "model_name": return model.get("model_name", "").lower() - + elif sort_by == "created_at": created_at = model_info.get("created_at") normalized_dt = _normalize_datetime_for_sorting(created_at) if normalized_dt is None: # Put None values at the end for asc, at the start for desc - return (datetime.max.replace(tzinfo=timezone.utc) if not reverse else datetime.min.replace(tzinfo=timezone.utc)) + return ( + datetime.max.replace(tzinfo=timezone.utc) + if not reverse + else datetime.min.replace(tzinfo=timezone.utc) + ) return normalized_dt - + elif sort_by == "updated_at": updated_at = model_info.get("updated_at") normalized_dt = _normalize_datetime_for_sorting(updated_at) if normalized_dt is None: - return (datetime.max.replace(tzinfo=timezone.utc) if not reverse else datetime.min.replace(tzinfo=timezone.utc)) + return ( + datetime.max.replace(tzinfo=timezone.utc) + if not reverse + else datetime.min.replace(tzinfo=timezone.utc) + ) return normalized_dt - + elif sort_by == "costs": input_cost = model_info.get("input_cost_per_token", 0) or 0 output_cost = model_info.get("output_cost_per_token", 0) or 0 total_cost = input_cost + output_cost # Put 0 or None costs at the end for asc, at the start for desc if total_cost == 0: - return (float("inf") if not reverse else float("-inf")) + return float("inf") if not reverse else float("-inf") return total_cost - + elif sort_by == "status": # False (config) comes before True (db) for asc db_model = model_info.get("db_model", False) return db_model - + return None try: @@ -9032,9 +9249,7 @@ async def _find_model_by_id( ) if db_model: # Convert database model to router format - decrypted_models = proxy_config.decrypt_model_list_from_db( - [db_model] - ) + decrypted_models = proxy_config.decrypt_model_list_from_db([db_model]) if decrypted_models: found_model = decrypted_models[0] except Exception as e: @@ -9208,13 +9423,13 @@ async def model_info_v2( ) verbose_proxy_logger.debug("all_models: %s", all_models) - + # Append A2A agents to models list all_models = await append_agents_to_model_info( models=all_models, user_api_key_dict=user_api_key_dict, ) - + # Update total count to include agents search_total_count = len(all_models) @@ -10057,7 +10272,7 @@ async def model_group_info( model_groups: List[ModelGroupInfoProxy] = _get_model_group_info( llm_router=llm_router, all_models_str=all_models_str, model_group=model_group ) - + # Append A2A agents to model groups model_groups = await append_agents_to_model_group( model_groups=model_groups, @@ -10238,7 +10453,7 @@ async def async_queue_request( data["proxy_server_request"] = { "url": str(request.url), "method": request.method, - "headers": dict(request.headers), + "headers": _safe_get_request_headers(request).copy(), "body": copy.copy(data), # use copy instead of deepcopy } @@ -10259,7 +10474,7 @@ async def async_queue_request( data["metadata"] = {} data["metadata"]["user_api_key"] = user_api_key_dict.api_key data["metadata"]["user_api_key_metadata"] = user_api_key_dict.metadata - _headers = dict(request.headers) + _headers = _safe_get_request_headers(request).copy() _headers.pop( "authorization", None ) # do not store the original `sk-..` api key in the db @@ -12658,6 +12873,7 @@ app.include_router(caching_router) app.include_router(analytics_router) app.include_router(guardrails_router) app.include_router(policy_router) +app.include_router(usage_ai_router) app.include_router(policy_crud_router) app.include_router(policy_resolve_router) app.include_router(search_tool_management_router) @@ -12671,6 +12887,7 @@ app.include_router(budget_management_router) app.include_router(model_management_router) app.include_router(model_access_group_management_router) app.include_router(tag_management_router) +app.include_router(tool_management_router) app.include_router(cost_tracking_settings_router) app.include_router(router_settings_router) app.include_router(fallback_management_router) diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index 50c0a55a875..155cea12ca4 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -64,6 +64,8 @@ model LiteLLM_AgentsTable { litellm_params Json? agent_card_params Json agent_access_groups String[] @default([]) + object_permission_id String? + object_permission LiteLLM_ObjectPermissionTable? @relation(fields: [object_permission_id], references: [object_permission_id]) created_at DateTime @default(now()) @map("created_at") created_by String updated_at DateTime @default(now()) @updatedAt @map("updated_at") @@ -264,6 +266,7 @@ model LiteLLM_ObjectPermissionTable { organizations LiteLLM_OrganizationTable[] users LiteLLM_UserTable[] end_users LiteLLM_EndUserTable[] + agents_table LiteLLM_AgentsTable[] } // Holds the MCP server configuration @@ -314,6 +317,7 @@ model LiteLLM_VerificationToken { router_settings Json? @default("{}") user_id String? team_id String? + agent_id String? project_id String? permissions Json @default("{}") max_parallel_requests Int? @@ -1051,6 +1055,26 @@ model LiteLLM_PolicyAttachmentTable { updated_by String? } +// Global tool registry - auto-discovered from LLM responses; admins set call_policy here +model LiteLLM_ToolTable { + tool_id String @id @default(uuid()) + tool_name String @unique // e.g. "huggingface_remote-mcp__dynamic_space" + origin String? // MCP server name or "user_defined" + call_policy String @default("untrusted") // "trusted" | "untrusted" | "dual_llm" | "blocked" + call_count Int @default(0) // cumulative number of times this tool was seen + assignments Json? @default("{}") + key_hash String? // hash of the virtual key that first called this tool + team_id String? // team that first called this tool + key_alias String? // human-readable alias of the virtual key + created_at DateTime @default(now()) + created_by String? + updated_at DateTime @default(now()) @updatedAt + updated_by String? + + @@index([call_policy]) + @@index([team_id]) +} + //Unified Access Groups table for storing unified access groups model LiteLLM_AccessGroupTable { access_group_id String @id @default(uuid()) diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index c4ff325db1f..f6613b5548f 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -4457,6 +4457,11 @@ class ProxyUpdateSpend: len(logs_to_process) : ] popped_batch = True + if len(logs_to_process) > 0: + verbose_proxy_logger.info( + "Spend tracking - processing %d spend logs for DB write", + len(logs_to_process), + ) start_time = time.time() try: for i in range(n_retry_times + 1): @@ -4503,9 +4508,17 @@ class ProxyUpdateSpend: f"{len(logs_to_process)} logs processed. Remaining in queue: {remaining_count}" ) break - except DB_CONNECTION_ERROR_TYPES: + except DB_CONNECTION_ERROR_TYPES as e: if i is None: i = 0 + verbose_proxy_logger.warning( + "Spend tracking - DB connection error writing spend logs, " + "retry %d/%d. logs_count=%d, error=%s", + i + 1, + n_retry_times, + len(logs_to_process), + str(e), + ) if i >= n_retry_times: raise await asyncio.sleep(2**i) @@ -4620,8 +4633,8 @@ async def update_spend_logs_job( logs_to_process=logs_to_process, ) except Exception as guardrail_tracking_err: - verbose_proxy_logger.debug( - "Guardrail usage tracking failed (non-fatal): %s", + verbose_proxy_logger.warning( + "Spend tracking - guardrail usage tracking failed (non-fatal): %s", guardrail_tracking_err, ) diff --git a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py index ce27c830f6f..627618387d5 100644 --- a/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py +++ b/litellm/proxy/vertex_ai_endpoints/langfuse_endpoints.py @@ -19,6 +19,7 @@ from fastapi import APIRouter, Request, Response import litellm from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_headers from litellm.proxy.litellm_pre_call_utils import _get_dynamic_logging_metadata from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( create_pass_through_route, @@ -32,7 +33,7 @@ def create_request_copy(request: Request): return { "method": request.method, "url": str(request.url), - "headers": dict(request.headers), + "headers": _safe_get_request_headers(request).copy(), "cookies": request.cookies, "query_params": dict(request.query_params), } diff --git a/litellm/rerank_api/main.py b/litellm/rerank_api/main.py index f47fd6323f0..871b18062ff 100644 --- a/litellm/rerank_api/main.py +++ b/litellm/rerank_api/main.py @@ -365,6 +365,7 @@ def rerank( # noqa: PLR0915 max_chunks_per_doc=max_chunks_per_doc, _is_async=_is_async, optional_params=optional_params.model_dump(exclude_unset=True), + timeout=optional_params.timeout, api_base=api_base, extra_headers=merged_headers, logging_obj=litellm_logging_obj, diff --git a/litellm/router.py b/litellm/router.py index ac2862da689..3a6c514989d 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -163,7 +163,11 @@ from litellm.types.utils import ( ) from litellm.types.utils import ModelInfo from litellm.types.utils import ModelInfo as ModelMapInfo -from litellm.types.utils import ModelResponseStream, StandardLoggingPayload, Usage +from litellm.types.utils import ( + ModelResponseStream, + StandardLoggingPayload, + Usage, +) from litellm.utils import ( CustomStreamWrapper, EmbeddingResponse, @@ -1555,6 +1559,9 @@ class Router: logging_obj=model_response.logging_obj, ) self._async_generator = async_generator + # Preserve hidden params (including litellm_overhead_time_ms) from original response + if hasattr(model_response, "_hidden_params"): + self._hidden_params = model_response._hidden_params.copy() def __aiter__(self): return self @@ -6416,6 +6423,7 @@ class Router: self.model_list = [] self.model_id_to_deployment_index_map = {} # Reset the index self.model_name_to_deployment_indices = {} # Reset the model_name index + self._invalidate_model_group_info_cache() self._invalidate_access_groups_cache() # we add api_base/api_key each model so load balancing between azure/gpt on api_base1 and api_base2 works @@ -6726,6 +6734,7 @@ class Router: """ idx = len(self.model_list) self.model_list.append(model) + self._invalidate_model_group_info_cache() self._invalidate_access_groups_cache() # Update model_id index for O(1) lookup @@ -6774,6 +6783,7 @@ class Router: if removal_idx is not None: self.model_list.pop(removal_idx) + self._invalidate_model_group_info_cache() self._invalidate_access_groups_cache() self._update_deployment_indices_after_removal( model_id=deployment_id, removal_idx=removal_idx @@ -6808,6 +6818,7 @@ class Router: if deployment_idx is not None: # Pop the item from the list first item = self.model_list.pop(deployment_idx) + self._invalidate_model_group_info_cache() self._invalidate_access_groups_cache() self._update_deployment_indices_after_removal( model_id=id, removal_idx=deployment_idx @@ -6978,9 +6989,9 @@ class Router: raise ValueError("Deployment not found") ## GET BASE MODEL - base_model = deployment.get("model_info", {}).get("base_model", None) + base_model = (deployment.get("model_info") or {}).get("base_model", None) if base_model is None: - base_model = deployment.get("litellm_params", {}).get("base_model", None) + base_model = (deployment.get("litellm_params") or {}).get("base_model", None) model = base_model @@ -6995,7 +7006,7 @@ class Router: raise ValueError( f"Deployment missing valid litellm_params. " f"Got: {type(litellm_params_data).__name__}, " - f"deployment_id: {deployment.get('model_info', {}).get('id', 'unknown')}" + f"deployment_id: {(deployment.get('model_info') or {}).get('id', 'unknown')}" ) _model, custom_llm_provider, _, _ = litellm.get_llm_provider( model=litellm_params.model, @@ -7015,10 +7026,10 @@ class Router: if potential_models is not None: for potential_model in potential_models: try: - if potential_model.get("model_info", {}).get( + if (potential_model.get("model_info") or {}).get( "id" - ) == deployment.get("model_info", {}).get("id"): - model = potential_model.get("litellm_params", {}).get( + ) == (deployment.get("model_info") or {}).get("id"): + model = (potential_model.get("litellm_params") or {}).get( "model" ) break @@ -7039,9 +7050,10 @@ class Router: model_info = litellm.get_model_info(model=model_info_name) ## CHECK USER SET MODEL INFO - user_model_info = deployment.get("model_info", {}) + user_model_info = deployment.get("model_info") or {} - model_info.update(user_model_info) + if model_info is not None: + model_info.update(user_model_info) return model_info @@ -7568,6 +7580,7 @@ class Router: """ # First populate the model_list self.model_list = [] + self._invalidate_model_group_info_cache() self._invalidate_access_groups_cache() for _, model in enumerate(model_list): # Extract model_info from the model dict @@ -7912,6 +7925,13 @@ class Router: return returned_models + def _invalidate_model_group_info_cache(self) -> None: + """Invalidate the cached model group info. + + Call this whenever self.model_list is modified to ensure the cache is rebuilt. + """ + self._cached_get_model_group_info.cache_clear() + def _invalidate_access_groups_cache(self) -> None: """Invalidate the cached access groups. diff --git a/litellm/types/integrations/prometheus.py b/litellm/types/integrations/prometheus.py index fd788af9ac1..482b87085dd 100644 --- a/litellm/types/integrations/prometheus.py +++ b/litellm/types/integrations/prometheus.py @@ -55,22 +55,21 @@ def _sanitize_prometheus_label_value(value: Optional[Any]) -> Optional[str]: return None # Coerce non-string values (int, bool, etc.) to str before sanitizing - if not isinstance(value, str): - value = str(value) + str_value: str = value if isinstance(value, str) else str(value) # Remove Unicode line/paragraph separators that break text format - value = value.replace("\u2028", "").replace("\u2029", "") + str_value = str_value.replace("\u2028", "").replace("\u2029", "") # Remove carriage returns - value = value.replace("\r", "") + str_value = str_value.replace("\r", "") # Replace newlines with spaces - value = value.replace("\n", " ") + str_value = str_value.replace("\n", " ") # Escape backslashes and double quotes per Prometheus exposition format - value = value.replace("\\", "\\\\").replace('"', '\\"') + str_value = str_value.replace("\\", "\\\\").replace('"', '\\"') - return value + return str_value @dataclass @@ -185,6 +184,7 @@ class UserAPIKeyLabelNames(Enum): CLIENT_IP = "client_ip" USER_AGENT = "user_agent" CALLBACK_NAME = "callback_name" + STREAM = "stream" DEFINED_PROMETHEUS_METRICS = Literal[ @@ -638,6 +638,14 @@ class PrometheusMetricLabels: ] ) + # Conditionally add stream label to litellm_proxy_total_requests_metric + if ( + label_name == "litellm_proxy_total_requests_metric" + and litellm.prometheus_emit_stream_label is True + and UserAPIKeyLabelNames.STREAM.value not in default_labels + ): + custom_labels.append(UserAPIKeyLabelNames.STREAM.value) + return default_labels + custom_labels @@ -709,6 +717,9 @@ class UserAPIKeyLabelValues(BaseModel): user_agent: Annotated[ Optional[str], Field(..., alias=UserAPIKeyLabelNames.USER_AGENT.value) ] = None + stream: Annotated[ + Optional[str], Field(..., alias=UserAPIKeyLabelNames.STREAM.value) + ] = None class PrometheusMetricsConfig(BaseModel): diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index 4ab81f8fd57..15e8d1be930 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -1125,6 +1125,7 @@ class ResponsesAPIOptionalRequestParams(TypedDict, total=False): prompt: Optional[PromptObject] max_tool_calls: Optional[int] prompt_cache_key: Optional[str] + prompt_cache_retention: Optional[str] stream_options: Optional[dict] top_logprobs: Optional[int] partial_images: Optional[ diff --git a/litellm/types/responses/main.py b/litellm/types/responses/main.py index 8f6333ff900..bda53bae082 100644 --- a/litellm/types/responses/main.py +++ b/litellm/types/responses/main.py @@ -6,6 +6,7 @@ from typing_extensions import Any, List, Optional, TypedDict from litellm.types.llms.base import BaseLiteLLMOpenAIResponseObject +Phase = Optional[Literal["commentary", "final_answer"]] # TODO: Once openai sdk has updated, we can remove this and use the openai sdk type class GenericResponseOutputItemContentAnnotation(BaseLiteLLMOpenAIResponseObject): """Annotation for content in a message""" @@ -35,6 +36,7 @@ class OutputFunctionToolCall(BaseLiteLLMOpenAIResponseObject): type: Optional[str] # "function_call" id: Optional[str] status: Literal["in_progress", "completed", "incomplete"] + phase: Phase = None class OutputImageGenerationCall(BaseLiteLLMOpenAIResponseObject): @@ -57,6 +59,7 @@ class GenericResponseOutputItem(BaseLiteLLMOpenAIResponseObject): status: str # "completed", "in_progress", etc. role: str # "assistant", "user", etc. content: List[OutputText] + phase: Phase = None class DeleteResponseResult(BaseLiteLLMOpenAIResponseObject): diff --git a/litellm/types/tool_management.py b/litellm/types/tool_management.py new file mode 100644 index 00000000000..8704ff27759 --- /dev/null +++ b/litellm/types/tool_management.py @@ -0,0 +1,42 @@ +""" +Pydantic models for Tool Policy management endpoints. +""" + +from datetime import datetime +from typing import Dict, List, Literal, Optional + +from pydantic import BaseModel + +ToolCallPolicy = Literal["trusted", "untrusted", "dual_llm", "blocked"] + + +class LiteLLM_ToolTableRow(BaseModel): + tool_id: str + tool_name: str + origin: Optional[str] = None + call_policy: ToolCallPolicy = "untrusted" + call_count: int = 0 + assignments: Optional[Dict] = None + key_hash: Optional[str] = None + team_id: Optional[str] = None + key_alias: Optional[str] = None + created_at: Optional[datetime] = None + updated_at: Optional[datetime] = None + created_by: Optional[str] = None + updated_by: Optional[str] = None + + +class ToolListResponse(BaseModel): + tools: List[LiteLLM_ToolTableRow] + total: int + + +class ToolPolicyUpdateRequest(BaseModel): + tool_name: str + call_policy: ToolCallPolicy + + +class ToolPolicyUpdateResponse(BaseModel): + tool_name: str + call_policy: ToolCallPolicy + updated: bool diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 94c387dd22c..e8d6ac79708 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -1826,7 +1826,7 @@ class ModelResponse(ModelResponseBase): else: usage = usage elif stream is None or stream is False: - usage = Usage() + usage = None # avoid constructing throwaway Usage; set by convert_to_model_response_object if hidden_params: self._hidden_params = hidden_params diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 624714feb87..e4d7a6a02f2 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -20562,6 +20562,39 @@ "supports_tool_choice": true, "supports_vision": true }, + "gpt-5.3-codex": { + "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_priority": 3.5e-07, + "input_cost_per_token": 1.75e-06, + "input_cost_per_token_priority": 3.5e-06, + "litellm_provider": "openai", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "responses", + "output_cost_per_token": 1.4e-05, + "output_cost_per_token_priority": 2.8e-05, + "supported_endpoints": [ + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": false, + "supports_tool_choice": true, + "supports_vision": true + }, "gpt-5-mini": { "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, diff --git a/package.json b/package.json index ab9e15f46a7..a45e116b277 100644 --- a/package.json +++ b/package.json @@ -12,7 +12,19 @@ }, "overrides": { "glob": ">=11.1.0", - "tar": ">=7.5.7", - "@isaacs/brace-expansion": ">=5.0.1" + "tar": ">=7.5.8", + "minimatch": ">=10.2.1", + "diff": ">=8.0.3", + "@isaacs/brace-expansion": ">=5.0.1", + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" } -} +} \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 832c3f75b72..dbde6ababc9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,6 +3,8 @@ urllib3>=2.6.0 # CVE-2025-66471, CVE-2025-66418, CVE-2026-21441 tornado>=6.5.3 # CVE-2025-67725, CVE-2025-67726, CVE-2025-67724 filelock>=3.20.1 # CVE-2025-68146 +h11>=0.16.0 # CVE-2025-43859, GHSA-vqfr-h8mv-ghfj — HTTP request smuggling +wheel>=0.46.2 # CVE-2026-24049 — path traversal Pillow==12.1.1 #GHSA-cfh3-3jmp-rvhc cryptography==46.0.5 #GHSA-r6ph-v2qm-q3c2 @@ -21,7 +23,7 @@ boto3==1.40.53 # aws bedrock/sagemaker calls (has bedrock-agentcore-control, com redis==5.2.1 # redis caching redisvl==0.4.1 ## redis semantic caching prisma==0.11.0 # for db -nodejs-wheel-binaries==24.12.0 ## required by prisma for migrations, prevents runtime download (updated from nodejs-bin for security fixes) +nodejs-wheel-binaries==24.13.1 ## required by prisma for migrations, prevents runtime download (updated from nodejs-bin for security fixes) mangum==0.17.0 # for aws lambda functions pynacl==1.6.2 # for encrypting keys google-cloud-aiplatform==1.133.0 # for vertex ai calls diff --git a/tests/litellm_utils_tests/test_health_check.py b/tests/litellm_utils_tests/test_health_check.py index 19882bbe4be..b459c3cfc99 100644 --- a/tests/litellm_utils_tests/test_health_check.py +++ b/tests/litellm_utils_tests/test_health_check.py @@ -92,7 +92,7 @@ async def test_azure_img_gen_health_check(): litellm._turn_on_debug() max_retries = 3 retry_delay = 1 # Start with 1 second delay - + for attempt in range(max_retries): response = await litellm.ahealth_check( model_params={ @@ -103,11 +103,11 @@ async def test_azure_img_gen_health_check(): mode="image_generation", prompt="cute baby sea otter", ) - + # Check if response is successful (no error) if isinstance(response, dict) and "error" not in response: return response - + # Check if error is a transient Azure internal server error error_str = str(response.get("error", "")).lower() is_transient_error = ( @@ -116,16 +116,18 @@ async def test_azure_img_gen_health_check(): or "internalfailure" in error_str or "internal failure" in error_str ) - + # If it's the last attempt or not a transient error, fail the test if attempt == max_retries - 1 or not is_transient_error: - assert isinstance(response, dict) and "error" not in response, f"Health check failed: {response.get('error', 'Unknown error')}" + assert ( + isinstance(response, dict) and "error" not in response + ), f"Health check failed: {response.get('error', 'Unknown error')}" return response - + # Wait before retrying with exponential backoff await asyncio.sleep(retry_delay) retry_delay *= 2 # Exponential backoff - + # Should not reach here, but just in case assert False, "Health check failed after all retries" @@ -471,6 +473,50 @@ def test_update_litellm_params_for_health_check(): ) +@pytest.mark.asyncio +async def test_perform_health_check_filters_by_model_id(): + """ + When model_id is passed, only that deployment is checked (not all deployments + that share the same model name). + """ + from litellm.proxy.health_check import perform_health_check + + # Two deployments with same model_name but different ids + model_list = [ + { + "model_name": "gpt-4", + "model_info": {"id": "deployment-id-1"}, + "litellm_params": {"model": "gpt-4", "api_key": "fake-key-1"}, + }, + { + "model_name": "gpt-4", + "model_info": {"id": "deployment-id-2"}, + "litellm_params": {"model": "gpt-4", "api_key": "fake-key-2"}, + }, + ] + + captured_list = [] + + async def mock_perform_health_check(m_list, details=True): + captured_list.append(m_list) + return [{"model": "gpt-4", "api_key": m_list[0]["litellm_params"]["api_key"]}], [] + + with patch( + "litellm.proxy.health_check._perform_health_check", + side_effect=mock_perform_health_check, + ): + healthy_endpoints, unhealthy_endpoints = await perform_health_check( + model_list=model_list, model_id="deployment-id-2", details=True + ) + + # Only one deployment (deployment-id-2) should have been passed to _perform_health_check + assert len(captured_list) == 1 + assert len(captured_list[0]) == 1 + assert (captured_list[0][0].get("model_info") or {}).get("id") == "deployment-id-2" + assert len(healthy_endpoints) == 1 + assert healthy_endpoints[0]["api_key"] == "fake-key-2" + + @pytest.mark.asyncio async def test_perform_health_check_with_health_check_model(): """ @@ -562,6 +608,99 @@ async def test_health_check_bad_model(): ), "Health check took longer than health_check_timeout" +@pytest.mark.asyncio +async def test_health_check_respects_concurrency_limit(): + from litellm.proxy.health_check import _perform_health_check + + model_list = [ + {"litellm_params": {"model": f"openai/gpt-4o-mini-{i}", "api_key": "fake-key"}} + for i in range(6) + ] + + active = 0 + max_active = 0 + + async def mock_health_check(litellm_params, **kwargs): + nonlocal active, max_active + active += 1 + max_active = max(max_active, active) + await asyncio.sleep(0.05) + active -= 1 + return {"status": "healthy"} + + with patch("litellm.ahealth_check", side_effect=mock_health_check): + await _perform_health_check(model_list, max_concurrency=2) + + assert max_active <= 2 + + +@pytest.mark.asyncio +async def test_health_check_creates_only_bounded_initial_tasks(): + from litellm.proxy.health_check import _perform_health_check + + model_list = [ + {"litellm_params": {"model": f"openai/gpt-4o-mini-{i}", "api_key": "fake-key"}} + for i in range(10) + ] + release_event = asyncio.Event() + create_task_call_count = 0 + real_create_task = asyncio.create_task + + async def mock_health_check(litellm_params, **kwargs): + await release_event.wait() + return {"status": "healthy"} + + def tracked_create_task(coro): + nonlocal create_task_call_count + create_task_call_count += 1 + return real_create_task(coro) + + with patch("litellm.ahealth_check", side_effect=mock_health_check), patch( + "litellm.proxy.health_check.asyncio.create_task", side_effect=tracked_create_task + ): + perform_task = real_create_task( + _perform_health_check(model_list, max_concurrency=2) + ) + await asyncio.sleep(0.05) + assert create_task_call_count == 2 + release_event.set() + await perform_task + + +@pytest.mark.asyncio +async def test_timeout_does_not_cancel_other_health_checks(): + from litellm.proxy.health_check import _perform_health_check + + model_list = [ + { + "litellm_params": {"model": "openai/slow-model", "api_key": "fake-key"}, + "model_info": {"health_check_timeout": 0.05}, + }, + { + "litellm_params": {"model": "openai/fast-model", "api_key": "fake-key"}, + "model_info": {"health_check_timeout": 1}, + }, + ] + + async def mock_health_check(litellm_params, **kwargs): + if litellm_params["model"] == "openai/slow-model": + await asyncio.sleep(0.2) + return {"status": "healthy"} + await asyncio.sleep(0.01) + return {"status": "healthy"} + + with patch("litellm.ahealth_check", side_effect=mock_health_check): + healthy_endpoints, unhealthy_endpoints = await _perform_health_check( + model_list, max_concurrency=1 + ) + + healthy_models = {endpoint["model"] for endpoint in healthy_endpoints} + unhealthy_models = {endpoint["model"] for endpoint in unhealthy_endpoints} + + assert "openai/fast-model" in healthy_models + assert "openai/slow-model" in unhealthy_models + + @pytest.mark.asyncio async def test_ahealth_check_ocr(): litellm._turn_on_debug() @@ -643,20 +782,20 @@ async def test_image_generation_health_check_prompt(monkeypatch): async def test_health_check_with_custom_llm_provider(): """ Test that ahealth_check correctly uses custom_llm_provider from model_params. - + This test verifies the fix for the issue where the UI's "Test connect" button failed with "LLM Provider NOT provided" error for OpenAI-compatible self-hosted providers, even when a provider was selected in the dropdown. - + The fix ensures that when custom_llm_provider is passed in model_params, it's properly forwarded to get_llm_provider() to identify the correct provider. """ from unittest.mock import MagicMock - + # Mock the completion call to avoid making real API calls mock_response = MagicMock() mock_response._hidden_params = {"headers": {"x-ratelimit-remaining-tokens": "1000"}} - + with patch("litellm.acompletion", return_value=mock_response): # Test with a custom model name that wouldn't be recognized without custom_llm_provider response = await litellm.ahealth_check( @@ -668,7 +807,7 @@ async def test_health_check_with_custom_llm_provider(): }, mode="chat", ) - + # Should succeed without "LLM Provider NOT provided" error assert "error" not in response assert isinstance(response, dict) diff --git a/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py b/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py index 15d625b681f..a722aec7eb4 100644 --- a/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py +++ b/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py @@ -1453,3 +1453,47 @@ def test_convert_to_model_response_object_falsy_id_preserves_auto_generated(fals ) assert result.id == original_id assert result.id.startswith("chatcmpl-") + + +def test_convert_to_model_response_object_default_usage_overwritten(): + """ + Regression test: convert_to_model_response_object must properly set Usage + on a ModelResponse that only has the default Usage from ModelResponse.__init__() + (i.e. no extra litellm.Usage() set via setattr beforehand). + + This validates the optimization of removing the redundant + `setattr(model_response, "usage", litellm.Usage())` in completion(). + """ + mr = ModelResponse() + # usage is not set by default (optimization: avoid constructing throwaway Usage) + assert not hasattr(mr, "usage") + + response_object = { + "id": "chatcmpl-usage-test", + "choices": [ + { + "index": 0, + "message": {"role": "assistant", "content": "Hello"}, + "finish_reason": "stop", + } + ], + "usage": { + "prompt_tokens": 15, + "completion_tokens": 7, + "total_tokens": 22, + }, + "model": "gpt-4o", + } + + result = convert_to_model_response_object( + model_response_object=mr, + response_object=response_object, + stream=False, + start_time=datetime.now(), + end_time=datetime.now(), + ) + + assert isinstance(result, ModelResponse) + assert result.usage.prompt_tokens == 15 + assert result.usage.completion_tokens == 7 + assert result.usage.total_tokens == 22 diff --git a/tests/proxy_admin_ui_tests/package.json b/tests/proxy_admin_ui_tests/package.json index 48de2c1dba2..037ec7082a7 100644 --- a/tests/proxy_admin_ui_tests/package.json +++ b/tests/proxy_admin_ui_tests/package.json @@ -13,7 +13,19 @@ }, "overrides": { "glob": ">=11.1.0", - "tar": ">=7.5.7", - "@isaacs/brace-expansion": ">=5.0.1" + "tar": ">=7.5.8", + "minimatch": ">=10.2.1", + "diff": ">=8.0.3", + "@isaacs/brace-expansion": ">=5.0.1", + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" } -} +} \ No newline at end of file diff --git a/tests/proxy_admin_ui_tests/ui_unit_tests/package.json b/tests/proxy_admin_ui_tests/ui_unit_tests/package.json index 4c7d7addf0e..eb9c7473a5b 100644 --- a/tests/proxy_admin_ui_tests/ui_unit_tests/package.json +++ b/tests/proxy_admin_ui_tests/ui_unit_tests/package.json @@ -25,7 +25,19 @@ }, "overrides": { "glob": ">=11.1.0", - "tar": ">=7.5.7", - "@isaacs/brace-expansion": ">=5.0.1" + "tar": ">=7.5.8", + "minimatch": ">=10.2.1", + "diff": ">=8.0.3", + "@isaacs/brace-expansion": ">=5.0.1", + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" } } \ No newline at end of file diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index 14b49901c9c..0cbba7b5cc3 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -2330,7 +2330,9 @@ async def test_run_background_health_check_reflects_llm_model_list(monkeypatch): test_model_list_2 = [{"model_name": "model-b"}] called_model_lists = [] - async def fake_perform_health_check(model_list, details): + async def fake_perform_health_check( + model_list, details, max_concurrency=None + ): called_model_lists.append(copy.deepcopy(model_list)) return (["healthy"], ["unhealthy"]) @@ -2378,7 +2380,9 @@ async def test_background_health_check_skip_disabled_models(monkeypatch): ] called_model_lists = [] - async def fake_perform_health_check(model_list, details): + async def fake_perform_health_check( + model_list, details, max_concurrency=None + ): called_model_lists.append(copy.deepcopy(model_list)) return (["healthy"], []) diff --git a/tests/test_litellm/integrations/test_prometheus_stream_label.py b/tests/test_litellm/integrations/test_prometheus_stream_label.py new file mode 100644 index 00000000000..a00a468e0fb --- /dev/null +++ b/tests/test_litellm/integrations/test_prometheus_stream_label.py @@ -0,0 +1,81 @@ +""" +Unit tests for prometheus_emit_stream_label opt-in setting. + +Tests that: +- stream label is NOT added to litellm_proxy_total_requests_metric by default +- stream label IS added when litellm.prometheus_emit_stream_label = True +- stream value is populated correctly from standard_logging_payload +""" +import pytest + +import litellm +from litellm.types.integrations.prometheus import ( + PrometheusMetricLabels, + UserAPIKeyLabelNames, +) + + +def test_stream_label_not_present_by_default(): + """stream label should NOT appear in litellm_proxy_total_requests_metric unless opted in""" + litellm.prometheus_emit_stream_label = False + labels = PrometheusMetricLabels.get_labels("litellm_proxy_total_requests_metric") + assert UserAPIKeyLabelNames.STREAM.value not in labels + + +def test_stream_label_present_when_opted_in(): + """stream label SHOULD appear in litellm_proxy_total_requests_metric when opted in""" + litellm.prometheus_emit_stream_label = True + try: + labels = PrometheusMetricLabels.get_labels("litellm_proxy_total_requests_metric") + assert UserAPIKeyLabelNames.STREAM.value in labels + finally: + litellm.prometheus_emit_stream_label = False + + +def test_stream_label_not_in_other_metrics_when_opted_in(): + """stream label should NOT be added to other metrics even when opted in""" + litellm.prometheus_emit_stream_label = True + try: + other_metrics = [ + "litellm_proxy_failed_requests_metric", + "litellm_spend_metric", + "litellm_input_tokens_metric", + "litellm_output_tokens_metric", + "litellm_llm_api_latency_metric", + ] + for metric in other_metrics: + labels = PrometheusMetricLabels.get_labels(metric) + assert UserAPIKeyLabelNames.STREAM.value not in labels, ( + f"stream label should not be in {metric}" + ) + finally: + litellm.prometheus_emit_stream_label = False + + +def test_stream_label_name(): + """STREAM label name should be 'stream'""" + assert UserAPIKeyLabelNames.STREAM.value == "stream" + + +def test_user_api_key_label_values_has_stream_field(): + """UserAPIKeyLabelValues should accept stream field""" + from litellm.types.integrations.prometheus import UserAPIKeyLabelValues + + values = UserAPIKeyLabelValues(stream="True") + assert values.stream == "True" + + values_false = UserAPIKeyLabelValues(stream="False") + assert values_false.stream == "False" + + values_none = UserAPIKeyLabelValues() + assert values_none.stream is None + + +def test_stream_label_in_model_dump(): + """stream field appears in model_dump() output for use in prometheus_label_factory""" + from litellm.types.integrations.prometheus import UserAPIKeyLabelValues + + values = UserAPIKeyLabelValues(stream="True") + dumped = values.model_dump() + assert "stream" in dumped + assert dumped["stream"] == "True" diff --git a/tests/test_litellm/interactions/test_openapi_compliance.py b/tests/test_litellm/interactions/test_openapi_compliance.py index 5187f733a3c..5b2edcf1ee7 100644 --- a/tests/test_litellm/interactions/test_openapi_compliance.py +++ b/tests/test_litellm/interactions/test_openapi_compliance.py @@ -147,7 +147,8 @@ class TestResponseCompliance: """Verify status enum values match spec.""" schema = spec_dict["components"]["schemas"]["CreateModelInteractionParams"] status_prop = schema["properties"]["status"] - expected_statuses = ["UNSPECIFIED", "IN_PROGRESS", "REQUIRES_ACTION", "COMPLETED", "FAILED", "CANCELLED", "INCOMPLETE"] + # Google Interactions API uses lowercase status values (updated Feb 2026) + expected_statuses = ["in_progress", "requires_action", "completed", "failed", "cancelled", "incomplete"] assert status_prop["enum"] == expected_statuses print(f"✓ Status enum values: {expected_statuses}") diff --git a/tests/test_litellm/llms/bedrock/rerank/test_bedrock_rerank_header_forwarding.py b/tests/test_litellm/llms/bedrock/rerank/test_bedrock_rerank_header_forwarding.py index a8ac680908e..d6dc4bfa48d 100644 --- a/tests/test_litellm/llms/bedrock/rerank/test_bedrock_rerank_header_forwarding.py +++ b/tests/test_litellm/llms/bedrock/rerank/test_bedrock_rerank_header_forwarding.py @@ -237,6 +237,83 @@ async def test_bedrock_rerank_header_forwarding_async(model): pytest.fail(f"Failed to forward headers to {model}: {str(e)}") +def test_bedrock_rerank_timeout_sync(): + """ + Test that the timeout parameter is passed through to the HTTP client for Bedrock rerank (sync). + """ + client = HTTPHandler() + model = "bedrock/arn:aws:bedrock:us-east-1::foundation-model/cohere.rerank-v3-5:0" + mock_credentials_info = create_mock_credentials() + + with patch.object(client, "post") as mock_post, \ + patch("litellm.llms.bedrock.rerank.handler.BedrockRerankHandler._get_boto_credentials_from_optional_params", return_value=mock_credentials_info), \ + patch("botocore.auth.SigV4Auth") as mock_sigv4: + + mock_sigv4.return_value = MagicMock() + mock_response = Mock() + mock_response.status_code = 200 + mock_response.text = json.dumps(bedrock_rerank_response) + mock_response.json = lambda: json.loads(mock_response.text) + mock_response.raise_for_status = lambda: None + mock_post.return_value = mock_response + + litellm.rerank( + model=model, + query=test_query, + documents=test_documents, + top_n=3, + client=client, + timeout=0.001, + aws_region_name="us-east-1", + aws_bedrock_runtime_endpoint="https://bedrock-runtime.us-east-1.amazonaws.com", + ) + + assert mock_post.called + call_kwargs = mock_post.call_args.kwargs + assert call_kwargs.get("timeout") == 0.001, ( + f"Expected timeout=0.001, got timeout={call_kwargs.get('timeout')}" + ) + + +@pytest.mark.asyncio +async def test_bedrock_rerank_timeout_async(): + """ + Test that the timeout parameter is passed through to the HTTP client for Bedrock rerank (async). + """ + client = AsyncHTTPHandler() + model = "bedrock/arn:aws:bedrock:us-east-1::foundation-model/cohere.rerank-v3-5:0" + mock_credentials_info = create_mock_credentials() + + with patch.object(client, "post", new_callable=AsyncMock) as mock_post, \ + patch("litellm.llms.bedrock.rerank.handler.BedrockRerankHandler._get_boto_credentials_from_optional_params", return_value=mock_credentials_info), \ + patch("botocore.auth.SigV4Auth") as mock_sigv4: + + mock_sigv4.return_value = MagicMock() + mock_response = AsyncMock() + mock_response.status_code = 200 + mock_response.text = json.dumps(bedrock_rerank_response) + mock_response.json = lambda: json.loads(mock_response.text) + mock_response.raise_for_status = lambda: None + mock_post.return_value = mock_response + + await litellm.arerank( + model=model, + query=test_query, + documents=test_documents, + top_n=3, + client=client, + timeout=0.001, + aws_region_name="us-east-1", + aws_bedrock_runtime_endpoint="https://bedrock-runtime.us-east-1.amazonaws.com", + ) + + assert mock_post.called + call_kwargs = mock_post.call_args.kwargs + assert call_kwargs.get("timeout") == 0.001, ( + f"Expected timeout=0.001, got timeout={call_kwargs.get('timeout')}" + ) + + def test_bedrock_rerank_extra_headers_and_headers_merge(): """ Test that both extra_headers and headers parameters are correctly merged for Bedrock rerank. diff --git a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py index 37959f74086..39ff0a4f4d8 100644 --- a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py +++ b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py @@ -207,10 +207,10 @@ class TestOpenAIChatCompletionStreamingHandler: def test_chunk_parser_maps_reasoning_to_reasoning_content(self): """ Test that chunk_parser maps 'reasoning' field to 'reasoning_content'. - + Some OpenAI-compatible providers (e.g., GLM-5, hosted_vllm) return delta.reasoning, but LiteLLM expects delta.reasoning_content. - + Regression test for: Streaming responses with delta.reasoning field coming back empty when using openai/ or hosted_vllm/ providers. """ @@ -293,3 +293,34 @@ class TestPromptCacheKeyIntegration: prompt_cache_key="test-cache-key-123", ) assert optional_params.get("prompt_cache_key") == "test-cache-key-123" + + +class TestPromptCacheParams: + """Tests for prompt_cache_key and prompt_cache_retention support.""" + + def setup_method(self): + self.config = OpenAIGPTConfig() + + def test_prompt_cache_key_in_supported_params(self): + """Test that prompt_cache_key is in supported params for OpenAI models.""" + supported_params = self.config.get_supported_openai_params("gpt-4o") + assert "prompt_cache_key" in supported_params + + def test_prompt_cache_retention_in_supported_params(self): + """Test that prompt_cache_retention is in supported params for OpenAI models.""" + supported_params = self.config.get_supported_openai_params("gpt-4o") + assert "prompt_cache_retention" in supported_params + + def test_prompt_cache_params_passed_through(self): + """Test that prompt_cache_key and prompt_cache_retention are passed through by map_openai_params.""" + optional_params = self.config.map_openai_params( + non_default_params={ + "prompt_cache_key": "my-cache-key", + "prompt_cache_retention": "24h", + }, + optional_params={}, + model="gpt-4o", + drop_params=False, + ) + assert optional_params.get("prompt_cache_key") == "my-cache-key" + assert optional_params.get("prompt_cache_retention") == "24h" diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py index 7c08716c04c..1a5ab808f7b 100644 --- a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py +++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py @@ -925,4 +925,318 @@ def test_get_supported_openai_params(): assert "temperature" in params assert "stream" in params assert "background" in params - assert "stream" in params \ No newline at end of file + assert "stream" in params + + +class TestPhaseParameter: + """Tests for the `phase` parameter on assistant output items (gpt-5.3-codex).""" + + def setup_method(self): + self.config = OpenAIResponsesAPIConfig() + self.model = "gpt-5.3-codex" + self.logging_obj = MagicMock() + + @staticmethod + def _make_output_text(text: str): + from litellm.types.responses.main import OutputText + + return OutputText(type="output_text", text=text, annotations=[]) + + def test_generic_response_output_item_accepts_phase_commentary(self): + from litellm.types.responses.main import GenericResponseOutputItem + + item = GenericResponseOutputItem( + type="message", + id="msg_001", + status="completed", + role="assistant", + content=[self._make_output_text("Thinking...")], + phase="commentary", + ) + assert item.phase == "commentary" + + def test_generic_response_output_item_accepts_phase_final_answer(self): + from litellm.types.responses.main import GenericResponseOutputItem + + item = GenericResponseOutputItem( + type="message", + id="msg_002", + status="completed", + role="assistant", + content=[self._make_output_text("The answer is 42.")], + phase="final_answer", + ) + assert item.phase == "final_answer" + + def test_generic_response_output_item_phase_defaults_to_none(self): + from litellm.types.responses.main import GenericResponseOutputItem + + item = GenericResponseOutputItem( + type="message", + id="msg_003", + status="completed", + role="assistant", + content=[self._make_output_text("Hello")], + ) + assert item.phase is None + + def test_output_function_tool_call_accepts_phase(self): + from litellm.types.responses.main import OutputFunctionToolCall + + item = OutputFunctionToolCall( + type="function_call", + id="fc_001", + arguments='{"query": "test"}', + call_id="call_001", + name="search", + status="completed", + phase="commentary", + ) + assert item.phase == "commentary" + + def test_input_passthrough_dict_preserves_phase(self): + """Dict input items (the normal HTTP flow) must preserve phase verbatim.""" + input_items = [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Hi"}], + }, + { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": "Preamble..."}], + "phase": "commentary", + }, + { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": "Done."}], + "phase": "final_answer", + }, + { + "type": "message", + "role": "assistant", + "content": [{"type": "output_text", "text": "Neutral."}], + "phase": None, + }, + ] + + result = self.config._validate_input_param(input_items) + assert isinstance(result, list) + + assert "phase" not in result[0] + assert result[1]["phase"] == "commentary" + assert result[2]["phase"] == "final_answer" + assert result[3]["phase"] is None + + def test_input_passthrough_pydantic_preserves_non_null_phase(self): + """Pydantic input items must preserve non-null phase values.""" + from litellm.types.responses.main import GenericResponseOutputItem + + item = GenericResponseOutputItem( + type="message", + id="msg_010", + status="completed", + role="assistant", + content=[self._make_output_text("commentary")], + phase="commentary", + ) + + result = self.config._validate_input_param([item]) + assert isinstance(result, list) + assert result[0]["phase"] == "commentary" + + def test_response_parsing_preserves_phase_on_output(self): + """Non-streaming response must preserve phase on output items.""" + raw_json = { + "id": "resp_001", + "created_at": 1700000000, + "model": "gpt-5.3-codex", + "object": "response", + "status": "completed", + "output": [ + { + "type": "message", + "id": "msg_001", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "preamble"}], + "phase": "commentary", + }, + { + "type": "message", + "id": "msg_002", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "answer"}], + "phase": "final_answer", + }, + ], + "usage": {"input_tokens": 10, "output_tokens": 20, "total_tokens": 30}, + } + + response = ResponsesAPIResponse(**raw_json) + assert len(response.output) == 2 + + for idx, output_item in enumerate(response.output): + if isinstance(output_item, dict): + phase = output_item.get("phase") + else: + phase = getattr(output_item, "phase", None) + + expected = "commentary" if idx == 0 else "final_answer" + assert phase == expected, ( + f"output[{idx}] phase={phase!r}, expected {expected!r}" + ) + + def test_streaming_output_item_done_preserves_phase(self): + """OutputItemDoneEvent must preserve phase on its item.""" + from litellm.types.llms.openai import ( + OutputItemDoneEvent, + ResponsesAPIStreamEvents, + ) + + chunk = { + "type": "response.output_item.done", + "output_index": 0, + "sequence_number": 3, + "item": { + "type": "message", + "id": "msg_100", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "done"}], + "phase": "final_answer", + }, + } + + result = self.config.transform_streaming_response( + model=self.model, parsed_chunk=chunk, logging_obj=self.logging_obj + ) + + assert isinstance(result, OutputItemDoneEvent) + assert result.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE + assert getattr(result.item, "phase", None) == "final_answer" + + def test_streaming_output_item_added_preserves_phase(self): + """OutputItemAddedEvent must preserve phase on its item.""" + from litellm.types.llms.openai import ( + OutputItemAddedEvent, + ResponsesAPIStreamEvents, + ) + + chunk = { + "type": "response.output_item.added", + "output_index": 0, + "item": { + "type": "message", + "id": "msg_200", + "role": "assistant", + "phase": "commentary", + }, + } + + result = self.config.transform_streaming_response( + model=self.model, parsed_chunk=chunk, logging_obj=self.logging_obj + ) + + assert isinstance(result, OutputItemAddedEvent) + assert result.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED + assert getattr(result.item, "phase", None) == "commentary" + + def test_streaming_response_completed_preserves_phase(self): + """ResponseCompletedEvent must preserve phase on output items inside the response.""" + completed_chunk = { + "type": "response.completed", + "response": { + "id": "resp_300", + "created_at": 1700000000, + "model": "gpt-5.3-codex", + "object": "response", + "status": "completed", + "output": [ + { + "type": "message", + "id": "msg_300", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "final"}], + "phase": "final_answer", + } + ], + "usage": { + "input_tokens": 5, + "output_tokens": 10, + "total_tokens": 15, + }, + }, + } + + result = self.config.transform_streaming_response( + model=self.model, + parsed_chunk=completed_chunk, + logging_obj=self.logging_obj, + ) + + assert result.type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED + output_item = result.response.output[0] + if isinstance(output_item, dict): + assert output_item["phase"] == "final_answer" + else: + assert getattr(output_item, "phase", None) == "final_answer" + + def test_phase_roundtrip_output_to_input(self): + """Simulate full round-trip: parse response output, then send items back as input.""" + raw_json = { + "id": "resp_rt", + "created_at": 1700000000, + "model": "gpt-5.3-codex", + "object": "response", + "status": "completed", + "output": [ + { + "type": "message", + "id": "msg_rt1", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "preamble"}], + "phase": "commentary", + }, + { + "type": "message", + "id": "msg_rt2", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "answer"}], + "phase": "final_answer", + }, + ], + "usage": {"input_tokens": 10, "output_tokens": 20, "total_tokens": 30}, + } + + response = ResponsesAPIResponse(**raw_json) + + input_items = [] + for item in response.output: + if isinstance(item, dict): + input_items.append(item) + else: + input_items.append( + item.model_dump() if hasattr(item, "model_dump") else dict(item) + ) + + input_items.append( + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "next question"}], + } + ) + + validated = self.config._validate_input_param(input_items) + assert isinstance(validated, list) + + assert validated[0]["phase"] == "commentary" + assert validated[1]["phase"] == "final_answer" + assert "phase" not in validated[2] \ No newline at end of file diff --git a/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py b/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py index af366b082a0..d236f46e5c5 100644 --- a/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py +++ b/tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py @@ -761,3 +761,70 @@ async def test_request_body_with_html_script_tags(): f"Message content with HTML was modified during parsing: " f"expected={msg['content']!r}, got={result['messages'][2]['content']!r}" ) + + +def test_safe_get_request_headers_caches_on_request_state(): + """ + Test that _safe_get_request_headers caches the result on request.state + and returns the same object on subsequent calls. + """ + mock_request = MagicMock() + mock_request.headers = {"content-type": "application/json", "authorization": "Bearer sk-123"} + mock_request.state = MagicMock(spec=[]) # empty spec so getattr returns default + + # First call — should create and cache + result1 = _safe_get_request_headers(mock_request) + assert result1 == {"content-type": "application/json", "authorization": "Bearer sk-123"} + assert mock_request.state._cached_headers is result1 + + # Second call — should return the cached object (same identity) + result2 = _safe_get_request_headers(mock_request) + assert result2 is result1 + + +def test_safe_get_request_headers_none_request(): + """ + Test that _safe_get_request_headers returns empty dict for None request. + """ + result = _safe_get_request_headers(None) + assert result == {} + + +def test_safe_get_request_headers_copy_protects_cache(): + """ + Test that callers using .copy() before mutation do not corrupt the cache. + """ + mock_request = MagicMock() + mock_request.headers = {"authorization": "Bearer sk-123", "host": "localhost"} + mock_request.state = MagicMock(spec=[]) + + original = _safe_get_request_headers(mock_request) + + # Simulate what mutation call sites do: copy then pop + mutable = _safe_get_request_headers(mock_request).copy() + mutable.pop("authorization", None) + + # Cache must be unaffected + assert "authorization" in _safe_get_request_headers(mock_request) + assert _safe_get_request_headers(mock_request) is original + + +def test_safe_get_request_headers_state_unavailable(): + """ + Test that _safe_get_request_headers still returns headers when + request.state rejects attribute writes (the except path on the cache-write). + """ + class ReadOnlyState: + """State object that allows reads but raises on writes.""" + def __setattr__(self, name, value): + raise AttributeError("read-only state") + + def __getattr__(self, name): + return None # _cached_headers not found → triggers fresh read + + mock_request = MagicMock() + mock_request.headers = {"content-type": "application/json"} + mock_request.state = ReadOnlyState() + + result = _safe_get_request_headers(mock_request) + assert result == {"content-type": "application/json"} diff --git a/tests/test_litellm/proxy/db/db_transaction_queue/test_tool_discovery_queue.py b/tests/test_litellm/proxy/db/db_transaction_queue/test_tool_discovery_queue.py new file mode 100644 index 00000000000..defdb3834d8 --- /dev/null +++ b/tests/test_litellm/proxy/db/db_transaction_queue/test_tool_discovery_queue.py @@ -0,0 +1,75 @@ +""" +Unit tests for ToolDiscoveryQueue. +""" + +import os +import sys + +import pytest + +sys.path.insert(0, os.path.abspath("../../..")) + +from litellm.proxy.db.db_transaction_queue.tool_discovery_queue import ( + ToolDiscoveryQueue, +) + + +@pytest.fixture +def queue(): + return ToolDiscoveryQueue() + + +def test_add_single_tool(queue): + queue.add_update({"tool_name": "my_tool", "origin": "user_defined"}) + items = queue.flush() + assert len(items) == 1 + assert items[0]["tool_name"] == "my_tool" + assert items[0]["origin"] == "user_defined" + + +def test_deduplication_same_name(queue): + """Adding the same tool_name twice should only keep the first.""" + queue.add_update({"tool_name": "tool_a", "origin": "mcp_server"}) + queue.add_update({"tool_name": "tool_a", "origin": "user_defined"}) + items = queue.flush() + assert len(items) == 1 + assert items[0]["origin"] == "mcp_server" # first wins + + +def test_deduplication_different_names(queue): + queue.add_update({"tool_name": "tool_a"}) + queue.add_update({"tool_name": "tool_b"}) + items = queue.flush() + assert len(items) == 2 + names = {i["tool_name"] for i in items} + assert names == {"tool_a", "tool_b"} + + +def test_flush_clears_pending(queue): + queue.add_update({"tool_name": "tool_x"}) + items1 = queue.flush() + assert len(items1) == 1 + items2 = queue.flush() + assert len(items2) == 0 + + +def test_seen_names_reset_after_flush(queue): + """Seen-set is cleared on flush so the same tool can re-enter the next cycle.""" + queue.add_update({"tool_name": "tool_a"}) + queue.flush() + queue.add_update({"tool_name": "tool_a"}) # same tool, new cycle + items = queue.flush() + assert len(items) == 1 + assert items[0]["tool_name"] == "tool_a" + + +def test_empty_tool_name_ignored(queue): + queue.add_update({"tool_name": ""}) + queue.add_update({"tool_name": None}) # type: ignore[arg-type] + items = queue.flush() + assert len(items) == 0 + + +def test_flush_returns_list(queue): + result = queue.flush() + assert isinstance(result, list) diff --git a/tests/test_litellm/proxy/db/test_tool_registry_writer.py b/tests/test_litellm/proxy/db/test_tool_registry_writer.py new file mode 100644 index 00000000000..44f9e32058a --- /dev/null +++ b/tests/test_litellm/proxy/db/test_tool_registry_writer.py @@ -0,0 +1,197 @@ +""" +Unit tests for tool_registry_writer.py — uses a mock prisma client +that exposes execute_raw / query_raw (matching the actual raw-SQL implementation). +""" + +import os +import sys +from datetime import datetime, timezone +from unittest.mock import AsyncMock, MagicMock + +import pytest + +sys.path.insert(0, os.path.abspath("../../..")) + +from litellm.proxy.db.tool_registry_writer import ( + batch_upsert_tools, + get_tool, + get_tools_by_names, + list_tools, + update_tool_policy, +) + + +def _make_prisma(query_rows=None): + """Return a minimal mock prisma_client with execute_raw / query_raw.""" + default_row = { + "tool_id": "uuid-1", + "tool_name": "my_tool", + "origin": "user_defined", + "call_policy": "untrusted", + "call_count": 1, + "assignments": {}, + "key_hash": None, + "team_id": None, + "key_alias": None, + "created_at": datetime.now(timezone.utc), + "updated_at": datetime.now(timezone.utc), + "created_by": None, + "updated_by": None, + } + rows = query_rows if query_rows is not None else [default_row] + + prisma = MagicMock() + prisma.db.execute_raw = AsyncMock(return_value=None) + prisma.db.query_raw = AsyncMock(return_value=rows) + return prisma + + +@pytest.mark.asyncio +async def test_batch_upsert_tools_calls_execute_raw(): + prisma = _make_prisma() + items = [{"tool_name": "tool_a", "origin": "mcp_server", "created_by": None}] + await batch_upsert_tools(prisma, items) + prisma.db.execute_raw.assert_awaited_once() + call_args = prisma.db.execute_raw.call_args + sql = call_args.args[0] + assert "LiteLLM_ToolTable" in sql + assert "ON CONFLICT" in sql + + +@pytest.mark.asyncio +async def test_batch_upsert_tools_empty_list(): + prisma = _make_prisma() + await batch_upsert_tools(prisma, []) + prisma.db.execute_raw.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_batch_upsert_tools_skips_empty_names(): + prisma = _make_prisma() + items = [{"tool_name": "", "origin": None}, {"tool_name": None}] # type: ignore[list-item] + await batch_upsert_tools(prisma, items) + prisma.db.execute_raw.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_batch_upsert_multiple_tools_calls_execute_raw_per_tool(): + prisma = _make_prisma() + items = [ + {"tool_name": "tool_a", "origin": "mcp_server", "created_by": None}, + {"tool_name": "tool_b", "origin": "user_defined", "created_by": "alice"}, + ] + await batch_upsert_tools(prisma, items) + assert prisma.db.execute_raw.await_count == 2 + + +@pytest.mark.asyncio +async def test_list_tools_no_filter(): + row = { + "tool_id": "id1", + "tool_name": "tool_a", + "origin": "mcp", + "call_policy": "untrusted", + "call_count": 5, + "assignments": {}, + "key_hash": None, + "team_id": None, + "key_alias": None, + "created_at": datetime.now(timezone.utc), + "updated_at": datetime.now(timezone.utc), + "created_by": None, + "updated_by": None, + } + prisma = _make_prisma(query_rows=[row]) + result = await list_tools(prisma) + assert len(result) == 1 + assert result[0].tool_name == "tool_a" + assert result[0].call_count == 5 + prisma.db.query_raw.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_list_tools_with_policy_filter(): + row = { + "tool_id": "id1", + "tool_name": "blocked_tool", + "origin": None, + "call_policy": "blocked", + "call_count": 2, + "assignments": None, + "key_hash": None, + "team_id": None, + "key_alias": None, + "created_at": datetime.now(timezone.utc), + "updated_at": datetime.now(timezone.utc), + "created_by": None, + "updated_by": None, + } + prisma = _make_prisma(query_rows=[row]) + result = await list_tools(prisma, call_policy="blocked") + assert result[0].call_policy == "blocked" + call_args = prisma.db.query_raw.call_args + sql = call_args.args[0] + assert "WHERE call_policy" in sql + + +@pytest.mark.asyncio +async def test_get_tool_found(): + prisma = _make_prisma() + result = await get_tool(prisma, "my_tool") + assert result is not None + assert result.tool_name == "my_tool" + prisma.db.query_raw.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_get_tool_not_found(): + prisma = _make_prisma(query_rows=[]) + result = await get_tool(prisma, "nonexistent") + assert result is None + + +@pytest.mark.asyncio +async def test_update_tool_policy_calls_execute_raw(): + row = { + "tool_id": "uuid-1", + "tool_name": "my_tool", + "origin": "user_defined", + "call_policy": "blocked", + "call_count": 1, + "assignments": {}, + "key_hash": None, + "team_id": None, + "key_alias": None, + "created_at": datetime.now(timezone.utc), + "updated_at": datetime.now(timezone.utc), + "created_by": None, + "updated_by": "admin", + } + prisma = _make_prisma(query_rows=[row]) + result = await update_tool_policy(prisma, "my_tool", "blocked", "admin") + assert result is not None + assert result.call_policy == "blocked" + prisma.db.execute_raw.assert_awaited_once() + call_args = prisma.db.execute_raw.call_args + sql = call_args.args[0] + assert "ON CONFLICT" in sql + assert "call_policy" in sql + + +@pytest.mark.asyncio +async def test_get_tools_by_names_returns_policy_map(): + rows = [ + {"tool_name": "tool_a", "call_policy": "trusted"}, + {"tool_name": "tool_b", "call_policy": "blocked"}, + ] + prisma = _make_prisma(query_rows=rows) + result = await get_tools_by_names(prisma, ["tool_a", "tool_b"]) + assert result == {"tool_a": "trusted", "tool_b": "blocked"} + + +@pytest.mark.asyncio +async def test_get_tools_by_names_empty_list(): + prisma = _make_prisma() + result = await get_tools_by_names(prisma, []) + assert result == {} + prisma.db.query_raw.assert_not_awaited() diff --git a/tests/test_litellm/proxy/google_endpoints/test_google_api_endpoints.py b/tests/test_litellm/proxy/google_endpoints/test_google_api_endpoints.py index 2f2eaa905be..205d724c2b0 100644 --- a/tests/test_litellm/proxy/google_endpoints/test_google_api_endpoints.py +++ b/tests/test_litellm/proxy/google_endpoints/test_google_api_endpoints.py @@ -2,10 +2,9 @@ """ Test to verify the Google GenAI proxy API endpoints """ -import asyncio import os import sys -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import AsyncMock, patch import pytest @@ -13,7 +12,6 @@ sys.path.insert( 0, os.path.abspath("../../..") ) # Adds the parent directory to the system path -import litellm def test_google_generate_content_endpoint(): @@ -401,3 +399,123 @@ def test_google_generate_content_with_image_config(): assert "contents" in called_data assert len(called_data["contents"]) == 1 assert called_data["contents"][0]["role"] == "user" + + +def test_google_generate_content_metadata_and_trace_id_callbacks(): + """Test that google_generate_content sets litellm_call_id and logging_obj for callbacks (e.g. S3, Langfuse)""" + try: + from fastapi import FastAPI + from fastapi.testclient import TestClient + + from litellm.proxy.google_endpoints.endpoints import router as google_router + except ImportError as e: + pytest.skip(f"Skipping test due to missing dependency: {e}") + + # Create a FastAPI app and include the router + app = FastAPI() + app.include_router(google_router) + + # Create a test client + client = TestClient(app) + + # Mock all required proxy server dependencies + with patch("litellm.proxy.proxy_server.llm_router") as mock_router, patch( + "litellm.proxy.proxy_server.general_settings", {} + ), patch("litellm.proxy.proxy_server.proxy_config") as mock_proxy_config, patch( + "litellm.proxy.proxy_server.version", "1.0.0" + ), patch( + "litellm.proxy.litellm_pre_call_utils.add_litellm_data_to_request" + ) as mock_add_data: + mock_router.agenerate_content = AsyncMock(return_value={"test": "response"}) + + # Mock add_litellm_data_to_request to return data with metadata + async def mock_add_litellm_data( + data, request, user_api_key_dict, proxy_config, general_settings, version + ): + # Simulate adding user metadata + data["litellm_metadata"] = { + "user_api_key_user_id": "test-user-id", + } + return data + + mock_add_data.side_effect = mock_add_litellm_data + + # Send a request to the endpoint with x-litellm-call-id header + test_call_id = "test-custom-call-id" + response = client.post( + "/v1beta/models/test-model:generateContent", + json={"contents": [{"role": "user", "parts": [{"text": "Hello"}]}]}, + headers={ + "Authorization": "Bearer sk-test-key", + "x-litellm-call-id": test_call_id, + }, + ) + + assert response.status_code == 200 + + mock_router.agenerate_content.assert_called_once() + call_args = mock_router.agenerate_content.call_args + called_data = call_args[1] + + # Verify that the litellm_logging_obj got assigned in the final called_data to router + assert "litellm_logging_obj" in called_data + assert "litellm_call_id" in called_data + assert called_data["litellm_call_id"] == test_call_id + + +def test_google_stream_generate_content_metadata_and_trace_id_callbacks(): + """Test that google_stream_generate_content sets litellm_call_id and logging_obj for callbacks""" + try: + from fastapi import FastAPI + from fastapi.testclient import TestClient + + from litellm.proxy.google_endpoints.endpoints import router as google_router + except ImportError as e: + pytest.skip(f"Skipping test due to missing dependency: {e}") + + app = FastAPI() + app.include_router(google_router) + client = TestClient(app) + + mock_stream = AsyncMock() + mock_stream.__aiter__ = lambda self: mock_stream + mock_stream.__anext__.side_effect = StopAsyncIteration + + with patch("litellm.proxy.proxy_server.llm_router") as mock_router, patch( + "litellm.proxy.proxy_server.general_settings", {} + ), patch("litellm.proxy.proxy_server.proxy_config") as mock_proxy_config, patch( + "litellm.proxy.proxy_server.version", "1.0.0" + ), patch( + "litellm.proxy.litellm_pre_call_utils.add_litellm_data_to_request" + ) as mock_add_data: + mock_router.agenerate_content_stream = AsyncMock(return_value=mock_stream) + + async def mock_add_litellm_data( + data, request, user_api_key_dict, proxy_config, general_settings, version + ): + data["litellm_metadata"] = { + "user_api_key_user_id": "test-user-id", + } + return data + + mock_add_data.side_effect = mock_add_litellm_data + + test_call_id = "test-custom-stream-call-id" + response = client.post( + "/v1beta/models/test-model:streamGenerateContent", + json={"contents": [{"role": "user", "parts": [{"text": "Hello stream"}]}]}, + headers={ + "Authorization": "Bearer sk-test-key", + "x-litellm-call-id": test_call_id, + }, + ) + + assert response.status_code == 200 + + mock_router.agenerate_content_stream.assert_called_once() + call_args = mock_router.agenerate_content_stream.call_args + called_data = call_args[1] + + assert "litellm_logging_obj" in called_data + assert "litellm_call_id" in called_data + assert called_data["litellm_call_id"] == test_call_id diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py index e2c05f0ad37..76f9c39acd0 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py @@ -24,12 +24,29 @@ from litellm.types.guardrails import LitellmParams, PiiAction, PiiEntityType from litellm.types.utils import Choices, Message, ModelResponse -def _make_mock_session_iterator(json_response): +def _make_mock_session_iterator( + json_response, status=200, content_type="application/json", text_response="" +): """Create a mock _get_session_iterator that yields a session returning json_response.""" @asynccontextmanager async def mock_iterator(): class MockResponse: + def __init__(self): + self.status = status + self.content_type = content_type + self.headers = {"Content-Type": content_type} + + async def text(self): + if text_response: + return text_response + import json + + try: + return json.dumps(json_response) + except Exception: + return str(json_response) + async def json(self): return json_response @@ -41,6 +58,7 @@ def _make_mock_session_iterator(json_response): class MockSession: def post(self, *args, **kwargs): + self.last_kwargs = kwargs return MockResponse() async def __aenter__(self): @@ -1444,3 +1462,149 @@ def test_deny_list_and_score_threshold_combined(): # EMAIL_ADDRESS passes both filters assert len(filtered) == 1 assert filtered[0]["entity_type"] == "EMAIL_ADDRESS" + + +@pytest.mark.asyncio +async def test_analyze_text_non_json_content_type_fail_closed(): + """ + Test that analyze_text raises GuardrailRaisedException when Presidio health + endpoint returns text/html and fail-closed is enabled. + """ + guardrail = _OPTIONAL_PresidioPIIMasking( + presidio_analyzer_api_base="http://test-analyzer/", + presidio_anonymizer_api_base="http://test-anonymizer/", + pii_entities_config={"PERSON": PiiAction.BLOCK}, + mock_testing=False, + ) + + mock_iterator = _make_mock_session_iterator( + json_response=None, + status=200, + content_type="text/html; charset=utf-8", + text_response="Presidio Analyzer service is up.", + ) + + with patch.object(guardrail, "_get_session_iterator", mock_iterator): + with pytest.raises(GuardrailRaisedException) as exc_info: + await guardrail.analyze_text( + text="Hello world", + presidio_config=None, + request_data={}, + ) + assert "expected application/json Content-Type" in str(exc_info.value) + assert "text/html" in str(exc_info.value) + + +@pytest.mark.asyncio +async def test_analyze_text_non_json_content_type_fail_open(): + """ + Test that analyze_text returns empty list when Presidio returns text/html + and fail-closed is NOT enabled. + """ + guardrail = _OPTIONAL_PresidioPIIMasking( + presidio_analyzer_api_base="http://test-analyzer/", + presidio_anonymizer_api_base="http://test-anonymizer/", + mock_testing=False, + ) + + mock_iterator = _make_mock_session_iterator( + json_response=None, + status=200, + content_type="text/html; charset=utf-8", + text_response="Presidio Analyzer service is up.", + ) + + with patch.object(guardrail, "_get_session_iterator", mock_iterator): + results = await guardrail.analyze_text( + text="Hello world", + presidio_config=None, + request_data={}, + ) + assert results == [] + + +@pytest.mark.asyncio +async def test_analyze_text_http_error_status(): + """ + Test that analyze_text handles 5xx HTTP errors properly. + """ + guardrail = _OPTIONAL_PresidioPIIMasking( + presidio_analyzer_api_base="http://test-analyzer/", + presidio_anonymizer_api_base="http://test-anonymizer/", + pii_entities_config={"PERSON": PiiAction.BLOCK}, + mock_testing=False, + ) + + mock_iterator = _make_mock_session_iterator( + json_response=None, + status=500, + content_type="text/plain", + text_response="Internal Server Error", + ) + + with patch.object(guardrail, "_get_session_iterator", mock_iterator): + with pytest.raises(GuardrailRaisedException) as exc_info: + await guardrail.analyze_text( + text="Hello world", + presidio_config=None, + request_data={}, + ) + assert "HTTP 500" in str(exc_info.value) + + +@pytest.mark.asyncio +async def test_anonymize_text_non_json_content_type(): + """ + Test that anonymize_text raises Exception for non-JSON responses. + """ + guardrail = _OPTIONAL_PresidioPIIMasking( + presidio_analyzer_api_base="http://test-analyzer/", + presidio_anonymizer_api_base="http://test-anonymizer/", + mock_testing=False, + ) + + mock_iterator = _make_mock_session_iterator( + json_response=None, + status=200, + content_type="text/html", + text_response="Presidio Anonymizer service is up.", + ) + + with patch.object(guardrail, "_get_session_iterator", mock_iterator): + with pytest.raises( + Exception, match="Presidio anonymizer returned non-JSON Content-Type" + ): + await guardrail.anonymize_text( + text="Hello world", + analyze_results=[{"start": 0, "end": 5, "entity_type": "PERSON"}], + output_parse_pii=False, + masked_entity_count={}, + ) + + +@pytest.mark.asyncio +async def test_anonymize_text_http_error_status(): + """ + Test that anonymize_text raises Exception on HTTP error. + """ + guardrail = _OPTIONAL_PresidioPIIMasking( + presidio_analyzer_api_base="http://test-analyzer/", + presidio_anonymizer_api_base="http://test-anonymizer/", + mock_testing=False, + ) + + mock_iterator = _make_mock_session_iterator( + json_response=None, + status=502, + content_type="text/plain", + text_response="Bad Gateway", + ) + + with patch.object(guardrail, "_get_session_iterator", mock_iterator): + with pytest.raises(Exception, match="Presidio anonymizer returned HTTP 502"): + await guardrail.anonymize_text( + text="Hello world", + analyze_results=[{"start": 0, "end": 5, "entity_type": "PERSON"}], + output_parse_pii=False, + masked_entity_count={}, + ) diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_policy_guardrail.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_policy_guardrail.py new file mode 100644 index 00000000000..c6a81efbf0b --- /dev/null +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_tool_policy_guardrail.py @@ -0,0 +1,181 @@ +""" +Unit tests for ToolPolicyGuardrail. +""" + +import os +import sys +from typing import Any +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest +from fastapi import HTTPException + +sys.path.insert(0, os.path.abspath("../../../../../..")) + +from litellm.proxy.guardrails.guardrail_hooks.tool_policy.tool_policy_guardrail import ( + ToolPolicyGuardrail, +) +from litellm.types.guardrails import GuardrailEventHooks + + +@pytest.fixture +def guardrail(): + return ToolPolicyGuardrail() + + +# --- helpers --- + +def _tool_request_inputs(tool_names: list) -> dict: + return { + "tools": [ + {"type": "function", "function": {"name": name, "description": ""}} + for name in tool_names + ] + } + + +def _tool_response_inputs(tool_names: list) -> dict: + return { + "tool_calls": [ + {"type": "function", "function": {"name": name}} + for name in tool_names + ] + } + + +# --- tests --- + + +def test_guardrail_supports_pre_and_post_call(guardrail): + hooks = guardrail.supported_event_hooks + assert GuardrailEventHooks.pre_call in hooks + assert GuardrailEventHooks.post_call in hooks + + +@pytest.mark.asyncio +async def test_no_tools_in_request_passes_through(guardrail): + inputs: Any = {"tools": []} + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + assert result is inputs + + +@pytest.mark.asyncio +async def test_no_tool_calls_in_response_passes_through(guardrail): + inputs: Any = {"tool_calls": []} + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert result is inputs + + +@pytest.mark.asyncio +async def test_untrusted_tools_pass_through(guardrail): + policy_map = {"search": "untrusted", "read_file": "trusted"} + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value=policy_map)): + inputs: Any = _tool_request_inputs(["search", "read_file"]) + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + assert result is inputs + + +@pytest.mark.asyncio +async def test_blocked_tool_in_request_raises_http_exception(guardrail): + policy_map = {"dangerous_tool": "blocked"} + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value=policy_map)): + inputs: Any = _tool_request_inputs(["dangerous_tool"]) + with pytest.raises(HTTPException) as exc_info: + await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + assert exc_info.value.status_code == 400 + assert "dangerous_tool" in exc_info.value.detail["blocked_tools"] + + +@pytest.mark.asyncio +async def test_blocked_tool_in_response_raises_http_exception(guardrail): + policy_map = {"exfil_tool": "blocked"} + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value=policy_map)): + inputs: Any = _tool_response_inputs(["exfil_tool"]) + with pytest.raises(HTTPException) as exc_info: + await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) + assert exc_info.value.status_code == 400 + assert "exfil_tool" in exc_info.value.detail["blocked_tools"] + + +@pytest.mark.asyncio +async def test_mixed_blocked_and_allowed_raises_for_blocked(guardrail): + policy_map = {"safe_tool": "trusted", "bad_tool": "blocked"} + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value=policy_map)): + inputs: Any = _tool_request_inputs(["safe_tool", "bad_tool"]) + with pytest.raises(HTTPException) as exc_info: + await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + blocked = exc_info.value.detail["blocked_tools"] + assert "bad_tool" in blocked + assert "safe_tool" not in blocked + + +@pytest.mark.asyncio +async def test_tool_not_in_db_passes_through(guardrail): + """Tools not found in the DB (no entry) should not be blocked.""" + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value={})): + inputs: Any = _tool_request_inputs(["unknown_tool"]) + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="request" + ) + assert result is inputs + + +@pytest.mark.asyncio +async def test_get_policies_cached_uses_cache(guardrail): + """Second call with same tool names should return the cached result.""" + policy_map = {"tool_a": "trusted"} + with patch( + "litellm.proxy.db.tool_registry_writer.get_tools_by_names", + new=AsyncMock(return_value=policy_map), + ) as mock_db, patch( + "litellm.proxy.proxy_server.prisma_client", + new=MagicMock(), + ): + # first call — should hit DB + result1 = await guardrail._get_policies_cached(["tool_a"]) + assert result1 == policy_map + + # second call — should hit cache, not DB again + result2 = await guardrail._get_policies_cached(["tool_a"]) + assert result2 == policy_map + + assert mock_db.call_count == 1 + + +@pytest.mark.asyncio +async def test_get_policies_cached_no_prisma(guardrail): + """Without a prisma client, returns empty dict.""" + with patch( + "litellm.proxy.proxy_server.prisma_client", + None, + ): + result = await guardrail._get_policies_cached(["tool_a"]) + assert result == {} + + +@pytest.mark.asyncio +async def test_response_tool_calls_as_objects(guardrail): + """tool_calls that are objects (not dicts) with .function.name should work.""" + policy_map = {"obj_tool": "blocked"} + with patch.object(guardrail, "_get_policies_cached", new=AsyncMock(return_value=policy_map)): + fn = MagicMock() + fn.name = "obj_tool" + tc = MagicMock() + tc.function = fn + inputs: Any = {"tool_calls": [tc]} + with pytest.raises(HTTPException): + await guardrail.apply_guardrail( + inputs=inputs, request_data={}, input_type="response" + ) diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py index e8765cf78ca..c46b8df5efc 100644 --- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py +++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py @@ -169,6 +169,223 @@ async def test_track_cost_callback_skips_when_no_standard_logging_object(): mock_proxy_logging.failed_tracking_alert.assert_not_called() +@pytest.mark.asyncio +async def test_enrich_failure_metadata_with_team_alias(): + """ + When team_id is set but team_alias is missing (and key_alias is present), + _enrich_failure_metadata_with_key_info should look up the team from cache + and populate user_api_key_team_alias. + """ + mock_team_obj = MagicMock() + mock_team_obj.team_alias = "my-team-alias" + + with patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_team_object", + new_callable=AsyncMock, + return_value=mock_team_obj, + ): + metadata = { + "user_api_key": "hashed_key", + "user_api_key_alias": "my-key-alias", # already set + "user_api_key_team_id": "test_team_id", + "user_api_key_team_alias": None, + } + result = await _ProxyDBLogger._enrich_failure_metadata_with_key_info(metadata) + assert result["user_api_key_team_alias"] == "my-team-alias" + + +@pytest.mark.asyncio +async def test_enrich_failure_metadata_with_full_key_lookup(): + """ + When all key fields are null (auth error 401 scenario), _enrich_failure_metadata_with_key_info + should look up the key object from cache/DB and populate alias, user_id, team_id, + then look up the team to get team_alias. + """ + mock_key_obj = MagicMock() + mock_key_obj.key_alias = "fetched-key-alias" + mock_key_obj.user_id = "fetched-user-id" + mock_key_obj.team_id = "fetched-team-id" + mock_key_obj.org_id = "fetched-org-id" + + mock_team_obj = MagicMock() + mock_team_obj.team_alias = "fetched-team-alias" + + with patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_key_object", + new_callable=AsyncMock, + return_value=mock_key_obj, + ), patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_team_object", + new_callable=AsyncMock, + return_value=mock_team_obj, + ): + metadata = { + "user_api_key": "hashed_key", + "user_api_key_alias": None, # all null - simulates auth error path + "user_api_key_user_id": None, + "user_api_key_team_id": None, + "user_api_key_team_alias": None, + "user_api_key_org_id": None, + } + result = await _ProxyDBLogger._enrich_failure_metadata_with_key_info(metadata) + assert result["user_api_key_alias"] == "fetched-key-alias" + assert result["user_api_key_user_id"] == "fetched-user-id" + assert result["user_api_key_team_id"] == "fetched-team-id" + assert result["user_api_key_org_id"] == "fetched-org-id" + assert result["user_api_key_team_alias"] == "fetched-team-alias" + + +@pytest.mark.asyncio +async def test_enrich_failure_metadata_skips_when_team_alias_present(): + """ + When team_alias is already populated, _enrich_failure_metadata_with_key_info + should not perform a team cache lookup. + """ + with patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_key_object", + new_callable=AsyncMock, + ) as mock_get_key, patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_team_object", + new_callable=AsyncMock, + ) as mock_get_team: + metadata = { + "user_api_key": "hashed_key", + "user_api_key_alias": "existing-alias", + "user_api_key_team_id": "test_team_id", + "user_api_key_team_alias": "already-set", + } + result = await _ProxyDBLogger._enrich_failure_metadata_with_key_info(metadata) + assert result["user_api_key_team_alias"] == "already-set" + mock_get_key.assert_not_called() + mock_get_team.assert_not_called() + + +@pytest.mark.asyncio +async def test_enrich_failure_metadata_skips_when_no_api_key(): + """ + When api_key hash is absent, _enrich_failure_metadata_with_key_info should + not perform any lookups. + """ + with patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_key_object", + new_callable=AsyncMock, + ) as mock_get_key: + metadata = { + "user_api_key": None, + "user_api_key_alias": None, + "user_api_key_team_id": None, + "user_api_key_team_alias": None, + } + result = await _ProxyDBLogger._enrich_failure_metadata_with_key_info(metadata) + mock_get_key.assert_not_called() + + +@pytest.mark.asyncio +async def test_async_post_call_failure_hook_enriches_auth_error_metadata(): + """ + Simulates a 401 ProxyException (e.g. can_key_call_model). In this case + UserAPIKeyAuth is created with only api_key set. The failure hook should + look up the key and team from cache/DB to populate all missing fields. + """ + logger = _ProxyDBLogger() + + # This is what auth_exception_handler creates for 401 errors + user_api_key_dict = UserAPIKeyAuth( + api_key="hashed_key", + # key_alias, user_id, team_id, team_alias are all None + ) + + request_data = { + "model": "claude-haiku-4-5", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": {}, + "litellm_params": {}, + } + + mock_key_obj = MagicMock() + mock_key_obj.key_alias = "my-key-alias" + mock_key_obj.user_id = "my-user-id" + mock_key_obj.team_id = "my-team-id" + mock_key_obj.org_id = None + + mock_team_obj = MagicMock() + mock_team_obj.team_alias = "my-team-alias" + + with patch( + "litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter.update_database", + new_callable=AsyncMock, + ) as mock_update_database, patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_key_object", + new_callable=AsyncMock, + return_value=mock_key_obj, + ), patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_team_object", + new_callable=AsyncMock, + return_value=mock_team_obj, + ): + await logger.async_post_call_failure_hook( + request_data=request_data, + original_exception=Exception("401 - model not allowed"), + user_api_key_dict=user_api_key_dict, + ) + + mock_update_database.assert_called_once() + call_args = mock_update_database.call_args[1] + metadata = call_args["kwargs"]["litellm_params"]["metadata"] + assert metadata["user_api_key_alias"] == "my-key-alias" + assert metadata["user_api_key_user_id"] == "my-user-id" + assert metadata["user_api_key_team_id"] == "my-team-id" + assert metadata["user_api_key_team_alias"] == "my-team-alias" + + +@pytest.mark.asyncio +async def test_async_post_call_failure_hook_enriches_missing_team_alias(): + """ + When user_api_key_dict has a team_id but no team_alias, async_post_call_failure_hook + should look up the team from cache and populate user_api_key_team_alias in the + spend log metadata written to the DB. + """ + logger = _ProxyDBLogger() + + user_api_key_dict = UserAPIKeyAuth( + api_key="test_api_key", + key_alias="test_alias", + user_id="test_user_id", + team_id="test_team_id", + team_alias=None, # Missing - simulates regular key auth where SQL view omits team_alias + ) + + request_data = { + "model": "gpt-4", + "messages": [{"role": "user", "content": "Hello"}], + "metadata": {}, + "litellm_params": {}, + } + + mock_team_obj = MagicMock() + mock_team_obj.team_alias = "enriched-team-alias" + + with patch( + "litellm.proxy.db.db_spend_update_writer.DBSpendUpdateWriter.update_database", + new_callable=AsyncMock, + ) as mock_update_database, patch( + "litellm.proxy.hooks.proxy_track_cost_callback.get_team_object", + new_callable=AsyncMock, + return_value=mock_team_obj, + ): + await logger.async_post_call_failure_hook( + request_data=request_data, + original_exception=Exception("Provider rate limit"), + user_api_key_dict=user_api_key_dict, + ) + + mock_update_database.assert_called_once() + call_args = mock_update_database.call_args[1] + metadata = call_args["kwargs"]["litellm_params"]["metadata"] + assert metadata["user_api_key_team_alias"] == "enriched-team-alias" + assert metadata["user_api_key_team_id"] == "test_team_id" + + @pytest.mark.asyncio @pytest.mark.parametrize("model_value", [None, ""]) async def test_track_cost_callback_skips_for_falsy_model_and_no_slo(model_value): diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index ffb4e955426..05df3c2dcbb 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -5623,6 +5623,7 @@ async def test_rotate_master_key_model_data_valid_for_prisma( litellm_params/model_info are JSON strings (create_many expects dicts). """ from unittest.mock import AsyncMock, MagicMock + from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth from litellm.proxy.management_endpoints.key_management_endpoints import ( _rotate_master_key, @@ -6157,3 +6158,56 @@ async def test_get_member_team_ids(): # Should return team-A and team-B (user is a member of both) # Should NOT return team-C (user is not in members list) assert sorted(result) == ["team-A", "team-B"] + + +@pytest.mark.asyncio +async def test_generate_key_with_agent_id(): + """Test that agent_id is accepted in GenerateKeyRequest and passed to generate_key_helper_fn.""" + from litellm.proxy._types import GenerateKeyRequest + + # Verify GenerateKeyRequest accepts agent_id + request = GenerateKeyRequest( + key_alias="agent-test-key", + agent_id="test-agent-123", + models=[], + ) + assert request.agent_id == "test-agent-123" + data_json = request.model_dump(exclude_unset=True, exclude_none=True) + assert data_json["agent_id"] == "test-agent-123" + + +@pytest.mark.asyncio +async def test_generate_key_helper_fn_agent_id(): + """Test that generate_key_helper_fn passes agent_id into the insert_data call.""" + from unittest.mock import AsyncMock, MagicMock, call, patch + + import litellm.proxy.management_endpoints.key_management_endpoints as km + + mock_prisma_client = AsyncMock() + mock_insert = AsyncMock( + return_value=MagicMock( + token="sk-test", + created_at=None, + updated_at=None, + litellm_budget_table=None, + ) + ) + mock_prisma_client.insert_data = mock_insert + + with patch.object(km, "prisma_client", mock_prisma_client): + with patch("litellm.proxy.proxy_server.prisma_client", mock_prisma_client): + await generate_key_helper_fn( + request_type="key", + agent_id="test-agent-456", + key_alias="test-agent-key", + models=[], + table_name="key", + ) + + assert mock_insert.called, "insert_data was never called" + # insert_data is called as insert_data(data=key_data, ...) + call_kwargs = mock_insert.call_args.kwargs + key_data = call_kwargs.get("data", {}) + assert key_data.get("agent_id") == "test-agent-456", ( + f"Expected agent_id='test-agent-456' in key_data, got: {key_data.get('agent_id')}" + ) diff --git a/tests/test_litellm/proxy/management_endpoints/test_tool_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_tool_management_endpoints.py new file mode 100644 index 00000000000..6f1d373fdee --- /dev/null +++ b/tests/test_litellm/proxy/management_endpoints/test_tool_management_endpoints.py @@ -0,0 +1,149 @@ +""" +Unit tests for tool management endpoints (/v1/tool/*). +Uses FastAPI TestClient with mocked DB functions. + +Patches target the source modules (litellm.proxy.db.tool_registry_writer.* +and litellm.proxy.proxy_server.prisma_client) because the endpoint code +imports these inside function bodies to avoid circular imports. +""" + +import os +import sys +from datetime import datetime, timezone +from typing import Optional +from unittest.mock import AsyncMock, MagicMock, patch + +from fastapi import FastAPI +from fastapi.testclient import TestClient + +sys.path.insert(0, os.path.abspath("../../..")) + +from litellm.proxy.management_endpoints.tool_management_endpoints import router +from litellm.types.tool_management import LiteLLM_ToolTableRow + +# --- helpers --- + + +def _make_tool_row( + tool_name: str = "my_tool", + call_policy: str = "untrusted", + origin: Optional[str] = None, +) -> LiteLLM_ToolTableRow: + now = datetime.now(timezone.utc) + return LiteLLM_ToolTableRow( + tool_id="uuid-1", + tool_name=tool_name, + origin=origin, + call_policy=call_policy, # type: ignore[arg-type] + assignments={}, + created_at=now, + updated_at=now, + ) + + +def _make_app() -> FastAPI: + """Build a minimal FastAPI app with the tool management router.""" + app = FastAPI() + app.include_router(router) + return app + + +# Stub the auth dependency so we don't need a real proxy running. +def _override_auth(): + from litellm.proxy._types import UserAPIKeyAuth + + return UserAPIKeyAuth(api_key="sk-test", user_id="admin") + + +# A real (non-None) prisma stub for truthiness checks. +_MOCK_PRISMA = MagicMock() + + +# --- test class --- + + +class TestToolManagementEndpoints: + def setup_method(self): + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + app = _make_app() + app.dependency_overrides[user_api_key_auth] = _override_auth + self.client = TestClient(app, raise_server_exceptions=True) + + @patch( + "litellm.proxy.db.tool_registry_writer.list_tools", + new_callable=AsyncMock, + ) + @patch("litellm.proxy.proxy_server.prisma_client", _MOCK_PRISMA) + def test_list_tools_returns_200(self, mock_db_list): + mock_db_list.return_value = [_make_tool_row()] + + resp = self.client.get("/v1/tool/list") + assert resp.status_code == 200 + body = resp.json() + assert body["total"] == 1 + assert body["tools"][0]["tool_name"] == "my_tool" + + @patch( + "litellm.proxy.db.tool_registry_writer.list_tools", + new_callable=AsyncMock, + ) + @patch("litellm.proxy.proxy_server.prisma_client", _MOCK_PRISMA) + def test_list_tools_with_policy_filter(self, mock_db_list): + mock_db_list.return_value = [_make_tool_row(call_policy="blocked")] + + resp = self.client.get("/v1/tool/list?call_policy=blocked") + assert resp.status_code == 200 + assert resp.json()["tools"][0]["call_policy"] == "blocked" + + @patch( + "litellm.proxy.db.tool_registry_writer.get_tool", + new_callable=AsyncMock, + ) + @patch("litellm.proxy.proxy_server.prisma_client", _MOCK_PRISMA) + def test_get_tool_found(self, mock_db_get): + mock_db_get.return_value = _make_tool_row(tool_name="tool_a") + + resp = self.client.get("/v1/tool/tool_a") + assert resp.status_code == 200 + assert resp.json()["tool_name"] == "tool_a" + + @patch( + "litellm.proxy.db.tool_registry_writer.get_tool", + new_callable=AsyncMock, + ) + @patch("litellm.proxy.proxy_server.prisma_client", _MOCK_PRISMA) + def test_get_tool_not_found_returns_404(self, mock_db_get): + mock_db_get.return_value = None + + resp = self.client.get("/v1/tool/nonexistent", follow_redirects=True) + assert resp.status_code == 404 + + @patch( + "litellm.proxy.db.tool_registry_writer.update_tool_policy", + new_callable=AsyncMock, + ) + @patch("litellm.proxy.proxy_server.prisma_client", _MOCK_PRISMA) + def test_update_tool_policy_blocked(self, mock_db_update): + mock_db_update.return_value = _make_tool_row(call_policy="blocked") + + resp = self.client.post( + "/v1/tool/policy", + json={"tool_name": "my_tool", "call_policy": "blocked"}, + ) + assert resp.status_code == 200 + body = resp.json() + assert body["call_policy"] == "blocked" + assert body["updated"] is True + + @patch("litellm.proxy.proxy_server.prisma_client", None) + def test_list_tools_no_db_returns_500(self): + resp = self.client.get("/v1/tool/list") + assert resp.status_code == 500 + + def test_update_tool_policy_invalid_policy_returns_422(self): + resp = self.client.post( + "/v1/tool/policy", + json={"tool_name": "my_tool", "call_policy": "invalid_value"}, + ) + assert resp.status_code == 422 diff --git a/tests/test_litellm/proxy/management_endpoints/usage_endpoints/__init__.py b/tests/test_litellm/proxy/management_endpoints/usage_endpoints/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/proxy/management_endpoints/usage_endpoints/test_ai_usage_chat.py b/tests/test_litellm/proxy/management_endpoints/usage_endpoints/test_ai_usage_chat.py new file mode 100644 index 00000000000..f9303bd13a6 --- /dev/null +++ b/tests/test_litellm/proxy/management_endpoints/usage_endpoints/test_ai_usage_chat.py @@ -0,0 +1,402 @@ +""" +Tests for AI Usage Chat module. +""" + +import json +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat import ( + TOOL_HANDLERS, + TOOLS_ADMIN, + TOOLS_BASE, + _build_system_prompt, + _summarise_entity_data, + _summarise_usage_data, + stream_usage_ai_chat, +) + + +SAMPLE_AGGREGATED_RESPONSE = { + "results": [ + { + "date": "2025-01-15", + "metrics": { + "spend": 50.25, + "prompt_tokens": 20000, + "completion_tokens": 10000, + "total_tokens": 30000, + "api_requests": 500, + "successful_requests": 480, + "failed_requests": 20, + "cache_read_input_tokens": 0, + "cache_creation_input_tokens": 0, + }, + "breakdown": { + "models": { + "gpt-4": { + "metrics": { + "spend": 40.0, + "api_requests": 300, + "total_tokens": 25000, + }, + "metadata": {}, + "api_key_breakdown": {}, + }, + }, + "providers": { + "openai": { + "metrics": {"spend": 50.25, "api_requests": 500}, + "metadata": {}, + "api_key_breakdown": {}, + }, + }, + "api_keys": { + "sk-test123": { + "metrics": {"spend": 50.25}, + "metadata": {"key_alias": "Production Key"}, + }, + }, + "model_groups": {}, + "mcp_servers": {}, + "entities": {}, + }, + }, + ], + "metadata": { + "total_spend": 50.25, + "total_api_requests": 500, + "total_successful_requests": 480, + "total_failed_requests": 20, + "total_tokens": 30000, + }, +} + +SAMPLE_TEAM_RESPONSE = { + "results": [ + { + "date": "2025-01-15", + "metrics": {"spend": 100.0, "api_requests": 1000, "total_tokens": 50000}, + "breakdown": { + "entities": { + "team-1": { + "metrics": { + "spend": 60.0, + "api_requests": 600, + "total_tokens": 30000, + }, + "metadata": {"alias": "Engineering"}, + "api_key_breakdown": {}, + }, + "team-2": { + "metrics": { + "spend": 40.0, + "api_requests": 400, + "total_tokens": 20000, + }, + "metadata": {"alias": "Marketing"}, + "api_key_breakdown": {}, + }, + }, + "models": {}, + "providers": {}, + "api_keys": {}, + "model_groups": {}, + "mcp_servers": {}, + }, + }, + ], + "metadata": {"total_spend": 100.0, "total_api_requests": 1000}, +} + + +class TestToolSchemas: + def test_admin_tools_include_all(self): + assert len(TOOLS_ADMIN) == 3 + names = {t["function"]["name"] for t in TOOLS_ADMIN} + assert "get_usage_data" in names + assert "get_team_usage_data" in names + assert "get_tag_usage_data" in names + + def test_base_tools_restricted_to_usage_only(self): + assert len(TOOLS_BASE) == 1 + assert TOOLS_BASE[0]["function"]["name"] == "get_usage_data" + + def test_admin_prompt_mentions_all_tools(self): + prompt = _build_system_prompt(is_admin=True) + assert "get_usage_data" in prompt + assert "get_team_usage_data" in prompt + assert "get_tag_usage_data" in prompt + + def test_non_admin_prompt_only_mentions_usage_tool(self): + prompt = _build_system_prompt(is_admin=False) + assert "get_usage_data" in prompt + assert "get_team_usage_data" not in prompt + assert "get_tag_usage_data" not in prompt + + def test_system_prompt_includes_todays_date(self): + from datetime import date + + prompt = _build_system_prompt(is_admin=True) + assert date.today().isoformat() in prompt + + +class TestSummariseUsageData: + def test_summarise_includes_totals(self): + summary = _summarise_usage_data(SAMPLE_AGGREGATED_RESPONSE) + assert "$50.25" in summary + assert "500" in summary + + def test_summarise_includes_models(self): + summary = _summarise_usage_data(SAMPLE_AGGREGATED_RESPONSE) + assert "gpt-4" in summary + + def test_summarise_includes_providers(self): + summary = _summarise_usage_data(SAMPLE_AGGREGATED_RESPONSE) + assert "openai" in summary + + def test_summarise_handles_empty_data(self): + empty = {"results": [], "metadata": {}} + summary = _summarise_usage_data(empty) + assert "no data" in summary.lower() + + +class TestSummariseEntityData: + def test_team_summary_includes_teams(self): + summary = _summarise_entity_data(SAMPLE_TEAM_RESPONSE, "Team") + assert "Engineering" in summary + assert "Marketing" in summary + assert "$60.0" in summary + assert "$40.0" in summary + + def test_team_summary_empty(self): + empty = {"results": [], "metadata": {}} + summary = _summarise_entity_data(empty, "Team") + assert "No Team usage data" in summary + + +class TestStreamUsageAiChat: + @pytest.mark.asyncio + async def test_stream_emits_status_events(self): + mock_tool_call = MagicMock() + mock_tool_call.id = "call_123" + mock_tool_call.function.name = "get_usage_data" + mock_tool_call.function.arguments = json.dumps( + { + "start_date": "2025-01-01", + "end_date": "2025-01-31", + } + ) + + mock_first_response = MagicMock() + mock_first_response.choices = [MagicMock()] + mock_first_response.choices[0].message.tool_calls = [mock_tool_call] + mock_first_response.choices[0].message.model_dump.return_value = { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_123", + "type": "function", + "function": { + "name": "get_usage_data", + "arguments": '{"start_date":"2025-01-01","end_date":"2025-01-31"}', + }, + } + ], + } + + async def mock_stream(): + chunk = MagicMock() + chunk.choices = [MagicMock()] + chunk.choices[0].delta.content = "Total spend is $50.25" + yield chunk + + with patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat.litellm" + ) as mock_litellm, patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat._fetch_usage_data", + new_callable=AsyncMock, + ) as mock_fetch: + mock_litellm.acompletion = AsyncMock( + side_effect=[ + mock_first_response, + mock_stream(), + ] + ) + mock_fetch.return_value = SAMPLE_AGGREGATED_RESPONSE + + events = [] + async for event in stream_usage_ai_chat( + messages=[{"role": "user", "content": "What is my total spend?"}], + model="gpt-4o-mini", + user_id="user-123", + is_admin=True, + ): + events.append(json.loads(event.replace("data: ", "").strip())) + + status_events = [e for e in events if e["type"] == "status"] + tool_call_events = [e for e in events if e["type"] == "tool_call"] + chunk_events = [e for e in events if e["type"] == "chunk"] + done_events = [e for e in events if e["type"] == "done"] + + assert len(status_events) >= 1 + assert "Thinking" in status_events[0]["message"] + assert len(tool_call_events) >= 1 + assert tool_call_events[0]["tool_name"] == "get_usage_data" + assert tool_call_events[0]["status"] in ("running", "complete") + assert len(chunk_events) >= 1 + assert len(done_events) == 1 + + @pytest.mark.asyncio + async def test_stream_handles_team_tool(self): + mock_tool_call = MagicMock() + mock_tool_call.id = "call_team" + mock_tool_call.function.name = "get_team_usage_data" + mock_tool_call.function.arguments = json.dumps( + { + "start_date": "2025-01-01", + "end_date": "2025-01-31", + } + ) + + mock_first_response = MagicMock() + mock_first_response.choices = [MagicMock()] + mock_first_response.choices[0].message.tool_calls = [mock_tool_call] + mock_first_response.choices[0].message.model_dump.return_value = { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_team", + "type": "function", + "function": { + "name": "get_team_usage_data", + "arguments": '{"start_date":"2025-01-01","end_date":"2025-01-31"}', + }, + } + ], + } + + async def mock_stream(): + chunk = MagicMock() + chunk.choices = [MagicMock()] + chunk.choices[0].delta.content = "Engineering is the top team." + yield chunk + + with patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat.litellm" + ) as mock_litellm, patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat._fetch_team_usage_data", + new_callable=AsyncMock, + ) as mock_fetch: + mock_litellm.acompletion = AsyncMock( + side_effect=[ + mock_first_response, + mock_stream(), + ] + ) + mock_fetch.return_value = SAMPLE_TEAM_RESPONSE + + events = [] + async for event in stream_usage_ai_chat( + messages=[{"role": "user", "content": "Which team spends the most?"}], + model="gpt-4o-mini", + is_admin=True, + ): + events.append(json.loads(event.replace("data: ", "").strip())) + + chunk_events = [e for e in events if e["type"] == "chunk"] + assert len(chunk_events) >= 1 + assert "Engineering" in chunk_events[0]["content"] + + @pytest.mark.asyncio + async def test_stream_handles_error(self): + with patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat.litellm" + ) as mock_litellm: + mock_litellm.acompletion = AsyncMock(side_effect=Exception("LLM error")) + + events = [] + async for event in stream_usage_ai_chat( + messages=[{"role": "user", "content": "test"}], + ): + events.append(json.loads(event.replace("data: ", "").strip())) + + error_events = [e for e in events if e["type"] == "error"] + assert len(error_events) == 1 + assert "internal error" in error_events[0]["message"].lower() + + @pytest.mark.asyncio + async def test_non_admin_enforces_user_id(self): + mock_tool_call = MagicMock() + mock_tool_call.id = "call_456" + mock_tool_call.function.name = "get_usage_data" + mock_tool_call.function.arguments = json.dumps( + { + "start_date": "2025-01-01", + "end_date": "2025-01-31", + "user_id": "other-user", + } + ) + + mock_first_response = MagicMock() + mock_first_response.choices = [MagicMock()] + mock_first_response.choices[0].message.tool_calls = [mock_tool_call] + mock_first_response.choices[0].message.model_dump.return_value = { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_456", + "type": "function", + "function": { + "name": "get_usage_data", + "arguments": '{"start_date":"2025-01-01","end_date":"2025-01-31","user_id":"other-user"}', + }, + } + ], + } + + async def mock_stream(): + chunk = MagicMock() + chunk.choices = [MagicMock()] + chunk.choices[0].delta.content = "Data." + yield chunk + + mock_fetch = AsyncMock(return_value=SAMPLE_AGGREGATED_RESPONSE) + + with patch( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat.litellm" + ) as mock_litellm, patch.dict( + "litellm.proxy.management_endpoints.usage_endpoints.ai_usage_chat.TOOL_HANDLERS", + { + "get_usage_data": { + "fetch": mock_fetch, + "summarise": _summarise_usage_data, + "label": "global usage data", + } + }, + ): + mock_litellm.acompletion = AsyncMock( + side_effect=[ + mock_first_response, + mock_stream(), + ] + ) + + events = [] + async for event in stream_usage_ai_chat( + messages=[{"role": "user", "content": "Show data"}], + model="gpt-4o-mini", + user_id="my-user-id", + is_admin=False, + ): + events.append(event) + + mock_fetch.assert_called_once_with( + start_date="2025-01-01", + end_date="2025-01-31", + user_id="my-user-id", + ) diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index 977304f732b..bf794478f10 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -1,4 +1,6 @@ import copy +import datetime +from typing import AsyncGenerator from unittest.mock import AsyncMock, MagicMock import pytest @@ -1348,3 +1350,202 @@ class TestOverrideOpenAIResponseModel: # Verify the model was not changed assert response_obj.model == fallback_model + + +class TestStreamingOverheadHeader: + """ + Tests that x-litellm-overhead-duration-ms is emitted in streaming responses. + + Regression tests for: streaming requests not including overhead header. + """ + + def test_get_custom_headers_includes_overhead_when_set(self): + """ + get_custom_headers() returns x-litellm-overhead-duration-ms + when litellm_overhead_time_ms is in hidden_params. + """ + mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth) + mock_user_api_key_dict.tpm_limit = None + mock_user_api_key_dict.rpm_limit = None + mock_user_api_key_dict.max_budget = None + mock_user_api_key_dict.spend = 0.0 + mock_user_api_key_dict.allowed_model_region = None + + hidden_params = { + "litellm_overhead_time_ms": 42.5, + "_response_ms": 500.0, + "model_id": "test-model-id", + "api_base": "https://api.openai.com", + } + + headers = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=mock_user_api_key_dict, + call_id="test-call-id", + model_id="test-model-id", + cache_key="", + api_base="https://api.openai.com", + version="1.0.0", + response_cost=0.001, + model_region="", + hidden_params=hidden_params, + ) + + assert "x-litellm-overhead-duration-ms" in headers + assert headers["x-litellm-overhead-duration-ms"] == "42.5" + + def test_get_custom_headers_omits_overhead_when_none(self): + """ + get_custom_headers() omits x-litellm-overhead-duration-ms + when litellm_overhead_time_ms is not in hidden_params. + """ + mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth) + mock_user_api_key_dict.tpm_limit = None + mock_user_api_key_dict.rpm_limit = None + mock_user_api_key_dict.max_budget = None + mock_user_api_key_dict.spend = 0.0 + mock_user_api_key_dict.allowed_model_region = None + + hidden_params = { + "_response_ms": 500.0, + "model_id": "test-model-id", + } + + headers = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=mock_user_api_key_dict, + call_id="test-call-id", + model_id="test-model-id", + cache_key="", + api_base="https://api.openai.com", + version="1.0.0", + response_cost=0.001, + model_region="", + hidden_params=hidden_params, + ) + + # Should be absent (None gets filtered by exclude_values) + assert "x-litellm-overhead-duration-ms" not in headers + + def test_update_response_metadata_sets_overhead_on_stream_wrapper(self): + """ + update_response_metadata() sets litellm_overhead_time_ms on + a streaming response's _hidden_params when llm_api_duration_ms is available. + """ + from litellm.litellm_core_utils.llm_response_utils.response_metadata import ( + update_response_metadata, + ) + + # Mock the logging object with llm_api_duration_ms set + mock_logging_obj = MagicMock() + mock_logging_obj.model_call_details = { + "llm_api_duration_ms": 200.0, + "litellm_params": {}, + } + mock_logging_obj.caching_details = None + mock_logging_obj.callback_duration_ms = None + mock_logging_obj.litellm_call_id = "test-call-id" + mock_logging_obj._response_cost_calculator = MagicMock(return_value=0.001) + + # Simulate a streaming result object with _hidden_params (like CustomStreamWrapper) + stream_result = MagicMock() + stream_result._hidden_params = { + "model_id": "test-model-id", + "api_base": "https://api.openai.com", + "additional_headers": {}, + } + + start_time = datetime.datetime.now() - datetime.timedelta(milliseconds=300) + end_time = datetime.datetime.now() + + update_response_metadata( + result=stream_result, + logging_obj=mock_logging_obj, + model="gpt-4o", + kwargs={}, + start_time=start_time, + end_time=end_time, + ) + + assert "litellm_overhead_time_ms" in stream_result._hidden_params + overhead = stream_result._hidden_params["litellm_overhead_time_ms"] + assert overhead is not None + assert isinstance(overhead, float) + # overhead = total_response_ms (~300ms) - llm_api_duration_ms (200ms) = ~100ms + assert overhead > 0 + + @pytest.mark.asyncio + async def test_streaming_response_includes_overhead_header(self): + """ + StreamingResponse returned by create_response() includes + x-litellm-overhead-duration-ms in its headers. + """ + + async def mock_generator() -> AsyncGenerator[str, None]: + yield 'data: {"id":"chatcmpl-test","choices":[{"delta":{"content":"hi"}}]}\n\n' + yield "data: [DONE]\n\n" + + headers = { + "x-litellm-overhead-duration-ms": "42.5", + "x-litellm-call-id": "test-call-id", + "x-litellm-model-id": "test-model-id", + } + + response = await create_response( + generator=mock_generator(), + media_type="text/event-stream", + headers=headers, + ) + + assert isinstance(response, StreamingResponse) + assert response.headers.get("x-litellm-overhead-duration-ms") == "42.5" + + def test_streaming_overhead_header_in_custom_headers_from_stream_hidden_params( + self, + ): + """ + Verifies that when get_custom_headers() is called with a streaming + response's hidden_params (containing litellm_overhead_time_ms), + the x-litellm-overhead-duration-ms header is correctly populated. + + This tests the critical path: update_response_metadata sets the value + → get_custom_headers reads it → StreamingResponse header is set. + """ + mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth) + mock_user_api_key_dict.tpm_limit = None + mock_user_api_key_dict.rpm_limit = None + mock_user_api_key_dict.max_budget = None + mock_user_api_key_dict.spend = 0.0 + mock_user_api_key_dict.allowed_model_region = None + + # This is what CustomStreamWrapper._hidden_params looks like after + # update_response_metadata() has been called on it + hidden_params = { + "model_id": "openai-gpt4o-deployment", + "api_base": "https://api.openai.com", + "additional_headers": {}, + "litellm_overhead_time_ms": 55.3, # set by update_response_metadata + "_response_ms": 280.0, + "litellm_call_id": "test-call-id", + "response_cost": 0.002, + "cache_key": None, + "fastest_response_batch_completion": None, + "callback_duration_ms": None, + } + + custom_headers = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=mock_user_api_key_dict, + call_id="test-call-id", + model_id=hidden_params.get("model_id"), + cache_key=hidden_params.get("cache_key") or "", + api_base=hidden_params.get("api_base") or "", + version="1.0.0", + response_cost=hidden_params.get("response_cost"), + model_region="", + hidden_params=hidden_params, + ) + + # The overhead header must be present and correct + assert "x-litellm-overhead-duration-ms" in custom_headers, ( + "x-litellm-overhead-duration-ms header must be emitted during streaming. " + "It was missing — this is the streaming overhead header regression." + ) + assert custom_headers["x-litellm-overhead-duration-ms"] == "55.3" diff --git a/tests/test_litellm/proxy/test_health_check_functions.py b/tests/test_litellm/proxy/test_health_check_functions.py index ccae9fb5425..4c91d0ae91e 100644 --- a/tests/test_litellm/proxy/test_health_check_functions.py +++ b/tests/test_litellm/proxy/test_health_check_functions.py @@ -12,6 +12,7 @@ sys.path.insert(0, os.path.abspath("../../..")) from litellm.proxy.health_endpoints._health_endpoints import ( _aggregate_health_check_results, _build_model_param_to_info_mapping, + _perform_health_check_and_save, _save_background_health_checks_to_db, _save_health_check_results_if_changed, _save_health_check_to_db, @@ -466,5 +467,43 @@ async def test_get_all_latest_health_checks_without_model_id(mock_prisma): assert result[0].checked_at == mock_check2.checked_at # Latest +@pytest.mark.asyncio +async def test_perform_health_check_and_save_passes_model_id_to_perform_health_check(): + """Test that _perform_health_check_and_save passes model_id to perform_health_check so health checks run by model id.""" + model_list = [ + { + "model_name": "gpt-4", + "model_info": {"id": "deployment-abc"}, + "litellm_params": {"model": "gpt-4"}, + }, + ] + healthy = [{"model": "gpt-4"}] + unhealthy = [] + + async def mock_perform_health_check(model_list, model=None, cli_model=None, details=True, model_id=None): + return healthy, unhealthy + + with patch( + "litellm.proxy.health_endpoints._health_endpoints.perform_health_check", + side_effect=mock_perform_health_check, + ) as mock_perform: + result = await _perform_health_check_and_save( + model_list=model_list, + target_model=None, + cli_model=None, + details=True, + prisma_client=None, + start_time=0.0, + user_id="user-1", + model_id="deployment-abc", + ) + + mock_perform.assert_called_once() + call_kwargs = mock_perform.call_args[1] + assert call_kwargs["model_id"] == "deployment-abc" + assert result["healthy_count"] == 1 + assert result["unhealthy_count"] == 0 + + if __name__ == "__main__": pytest.main([__file__]) \ No newline at end of file diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index 5542cdf8be4..4bb9685f5e6 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -925,6 +925,73 @@ def test_router_get_model_access_groups_team_only_models(): assert list(access_groups.keys()) == ["default-models"] +def test_cached_get_model_group_info(): + """ + Test that _cached_get_model_group_info caches results and + invalidates on deployment changes. + """ + from litellm.types.router import Deployment, LiteLLM_Params + + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4", "api_key": "fake"}, + "model_info": {"tpm": 1000, "rpm": 100}, + }, + ] + ) + + # First call should compute and cache + result1 = router._cached_get_model_group_info("gpt-4") + assert result1 is not None + assert result1.tpm == 1000 + + # Second call should hit cache (same object) + result2 = router._cached_get_model_group_info("gpt-4") + assert result1 is result2 + + # Add a deployment — cache should be invalidated + router.add_deployment( + Deployment( + model_name="gpt-4", + litellm_params=LiteLLM_Params(model="gpt-4", api_key="fake2"), + model_info={"tpm": 2000, "rpm": 200}, + ) + ) + result3 = router._cached_get_model_group_info("gpt-4") + assert result3 is not result2 + assert result3 is not None + assert result3.tpm == 3000 # 1000 + 2000 + + # Delete a deployment — cache should be invalidated + deployment_id = router.model_list[-1]["model_info"]["id"] + router.delete_deployment(id=deployment_id) + result4 = router._cached_get_model_group_info("gpt-4") + assert result4 is not result3 + assert result4 is not None + assert result4.tpm == 1000 + + # set_model_list — cache should be invalidated + router.set_model_list( + [ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4", "api_key": "fake"}, + "model_info": {"tpm": 5000}, + }, + ] + ) + result5 = router._cached_get_model_group_info("gpt-4") + assert result5 is not result4 + assert result5 is not None + assert result5.tpm == 5000 + + # Verify cache still works after invalidation + result6 = router._cached_get_model_group_info("gpt-4") + assert result5 is result6 + + def test_get_model_access_groups_caching(): """ Test that get_model_access_groups caches the no-args result @@ -1297,6 +1364,61 @@ async def test_acompletion_streaming_iterator_edge_cases(): print("✓ Edge case tests passed!") +@pytest.mark.asyncio +async def test_acompletion_streaming_iterator_preserves_hidden_params(): + """ + Regression test: FallbackStreamWrapper must copy _hidden_params from the + original CustomStreamWrapper so that x-litellm-overhead-duration-ms (and + other hidden params) are present in the proxy response headers for streaming. + """ + from unittest.mock import MagicMock + + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-4", + "litellm_params": {"model": "gpt-4", "api_key": "fake-key"}, + } + ], + ) + + # Simulate a CustomStreamWrapper that already has timing metadata set by + # update_response_metadata (litellm_overhead_time_ms, _response_ms, etc.) + mock_response = MagicMock() + mock_response.model = "gpt-4" + mock_response.custom_llm_provider = "openai" + mock_response.logging_obj = MagicMock() + mock_response._hidden_params = { + "litellm_overhead_time_ms": 12.34, + "_response_ms": 500.0, + "litellm_call_id": "test-call-id", + "api_base": "https://api.openai.com", + "additional_headers": {}, + } + + # Make the mock iterable (yields nothing — we only care about hidden_params) + async def _empty(): + return + yield # make it an async generator + + mock_response.__aiter__ = lambda self: _empty().__aiter__() + + result = await router._acompletion_streaming_iterator( + model_response=mock_response, + messages=[{"role": "user", "content": "hi"}], + initial_kwargs={"model": "gpt-4", "stream": True}, + ) + + # The returned FallbackStreamWrapper must carry the original _hidden_params + assert hasattr(result, "_hidden_params"), "result must have _hidden_params" + assert result._hidden_params.get("litellm_overhead_time_ms") == 12.34, ( + "litellm_overhead_time_ms must be preserved — " + "this is what drives x-litellm-overhead-duration-ms in streaming responses" + ) + assert result._hidden_params.get("litellm_call_id") == "test-call-id" + assert result._hidden_params.get("_response_ms") == 500.0 + + @pytest.mark.asyncio async def test_async_function_with_fallbacks_common_utils(): """Test the async_function_with_fallbacks_common_utils method""" @@ -1858,7 +1980,7 @@ def test_get_deployment_credentials_with_provider_resolves_credential_name(): litellm_credential_name to actual credential values (for UI-created models). """ from litellm.types.utils import CredentialItem - + # Setup credential list with a test credential litellm.credential_list = [ CredentialItem( diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json index 489a39a7ee2..3787f451ad3 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -1757,29 +1757,6 @@ "url": "https://opencollective.com/libvips" } }, - "node_modules/@isaacs/balanced-match": { - "version": "4.0.1", - "resolved": "https://registry.npmjs.org/@isaacs/balanced-match/-/balanced-match-4.0.1.tgz", - "integrity": "sha512-yzMTt9lEb8Gv7zRioUilSglI0c0smZ9k5D65677DLWLtWJaXIS3CqcGyUFByYKlnUj6TkjLVs54fBl6+TiGQDQ==", - "dev": true, - "license": "MIT", - "engines": { - "node": "20 || >=22" - } - }, - "node_modules/@isaacs/brace-expansion": { - "version": "5.0.1", - "resolved": "https://registry.npmjs.org/@isaacs/brace-expansion/-/brace-expansion-5.0.1.tgz", - "integrity": "sha512-WMz71T1JS624nWj2n2fnYAuPovhv7EUhk69R6i9dsVyzxt5eM3bjwvgk9L+APE1TRscGysAVMANkB0jh0LQZrQ==", - "dev": true, - "license": "MIT", - "dependencies": { - "@isaacs/balanced-match": "^4.0.1" - }, - "engines": { - "node": "20 || >=22" - } - }, "node_modules/@istanbuljs/schema": { "version": "0.1.3", "resolved": "https://registry.npmjs.org/@istanbuljs/schema/-/schema-0.1.3.tgz", @@ -3696,32 +3673,6 @@ "typescript": ">=4.8.4 <6.0.0" } }, - "node_modules/@typescript-eslint/typescript-estree/node_modules/brace-expansion": { - "version": "2.0.2", - "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.2.tgz", - "integrity": "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==", - "dev": true, - "license": "MIT", - "dependencies": { - "balanced-match": "^1.0.0" - } - }, - "node_modules/@typescript-eslint/typescript-estree/node_modules/minimatch": { - "version": "9.0.5", - "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-9.0.5.tgz", - "integrity": "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow==", - "dev": true, - "license": "ISC", - "dependencies": { - "brace-expansion": "^2.0.1" - }, - "engines": { - "node": ">=16 || 14 >=14.17" - }, - "funding": { - "url": "https://github.com/sponsors/isaacs" - } - }, "node_modules/@typescript-eslint/utils": { "version": "8.54.0", "resolved": "https://registry.npmjs.org/@typescript-eslint/utils/-/utils-8.54.0.tgz", @@ -4749,11 +4700,14 @@ } }, "node_modules/balanced-match": { - "version": "1.0.2", - "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz", - "integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==", + "version": "4.0.4", + "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-4.0.4.tgz", + "integrity": "sha512-BLrgEcRTwX2o6gGxGOCNyMvGSp35YofuYzw9h1IMTRmKqttAZZVU67bdb9Pr2vUHA8+j3i2tJfjO6C6+4myGTA==", "dev": true, - "license": "MIT" + "license": "MIT", + "engines": { + "node": "18 || 20 || >=22" + } }, "node_modules/baseline-browser-mapping": { "version": "2.9.19", @@ -4787,14 +4741,16 @@ } }, "node_modules/brace-expansion": { - 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"license": "ISC", + "license": "BlueOak-1.0.0", "dependencies": { - "brace-expansion": "^1.1.7" + "brace-expansion": "^5.0.2" }, "engines": { - "node": "*" + "node": "18 || 20 || >=22" + }, + "funding": { + "url": "https://github.com/sponsors/isaacs" } }, "node_modules/minimist": { @@ -12004,32 +11940,6 @@ "node": ">=18" } }, - "node_modules/test-exclude/node_modules/brace-expansion": { - "version": "2.0.2", - "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.2.tgz", - "integrity": "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==", - "dev": true, - "license": "MIT", - "dependencies": { - "balanced-match": "^1.0.0" - } - }, - "node_modules/test-exclude/node_modules/minimatch": { - "version": "9.0.5", - "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-9.0.5.tgz", - "integrity": "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow==", - "dev": true, - "license": "ISC", - "dependencies": { - "brace-expansion": "^2.0.1" - }, - "engines": { - "node": ">=16 || 14 >=14.17" - }, - "funding": { - "url": "https://github.com/sponsors/isaacs" - } - }, "node_modules/thenify": { "version": "3.3.1", "resolved": "https://registry.npmjs.org/thenify/-/thenify-3.3.1.tgz", @@ -13085,21 +12995,6 @@ "type": "github", "url": "https://github.com/sponsors/wooorm" } - }, - "node_modules/@next/swc-win32-ia32-msvc": { - "version": "14.2.33", - "resolved": "https://registry.npmjs.org/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-14.2.33.tgz", - "integrity": "sha512-pc9LpGNKhJ0dXQhZ5QMmYxtARwwmWLpeocFmVG5Z0DzWq5Uf0izcI8tLc+qOpqxO1PWqZ5A7J1blrUIKrIFc7Q==", - "cpu": [ - "ia32" - ], - "optional": true, - "os": [ - "win32" - ], - "engines": { - "node": ">= 10" - } } } } diff --git a/ui/litellm-dashboard/package.json b/ui/litellm-dashboard/package.json index b05d707d5ab..567673c0989 100644 --- a/ui/litellm-dashboard/package.json +++ b/ui/litellm-dashboard/package.json @@ -86,14 +86,25 @@ "mermaid": ">=11.10.0", "js-yaml": ">=4.1.1", "glob": ">=11.1.0", - "tar": ">=7.5.7", + "tar": ">=7.5.8", + "minimatch": ">=10.2.1", "@isaacs/brace-expansion": ">=5.0.1", "node-forge": ">=1.3.2", "lodash-es": ">=4.17.23", - "lodash": ">=4.17.23" + "lodash": ">=4.17.23", + "@babel/traverse": ">=7.23.2", + "ws": ">=7.5.10", + "http-proxy-middleware": ">=2.0.9", + "tar-fs": ">=2.1.4", + "webpack-dev-middleware": ">=5.3.4", + "braces": ">=3.0.3", + "axios": ">=0.30.2", + "webpack": ">=5.94.0", + "serve-static": ">=1.16.0", + "path-to-regexp": ">=0.1.12" }, "engines": { "node": ">=18.17.0", "npm": ">=8.3.0" } -} +} \ No newline at end of file diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.test.tsx index 1e8eabaea2e..b0df37ad6d8 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.test.tsx @@ -1,6 +1,6 @@ /* @vitest-environment jsdom */ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; -import { render } from "@testing-library/react"; +import { act, render } from "@testing-library/react"; import { beforeEach, describe, expect, it, vi } from "vitest"; import ModelsAndEndpointsView from "./ModelsAndEndpointsView"; @@ -13,6 +13,8 @@ vi.mock("@/components/networking", () => ({ getCallbacksCall: vi.fn().mockResolvedValue({ router_settings: {} }), setCallbacksCall: vi.fn().mockResolvedValue(undefined), getUiSettings: vi.fn().mockResolvedValue({ values: {} }), + latestHealthChecksCall: vi.fn().mockResolvedValue({ latest_health_checks: {} }), + getModelCostMapReloadStatus: vi.fn().mockResolvedValue({}), })); vi.mock("@/app/(dashboard)/models-and-endpoints/components/ModelAnalyticsTab/ModelAnalyticsTab", () => ({ @@ -27,6 +29,14 @@ vi.mock("@/components/add_model/AddModelForm", () => ({ default: () => null, })); +const mockHealthCheckComponent = vi.fn((_props: { all_models_on_proxy?: string[] }) => null); +vi.mock("@/components/model_dashboard/HealthCheckComponent", () => ({ + default: (props: { all_models_on_proxy?: string[] }) => { + mockHealthCheckComponent(props); + return null; + }, +})); + vi.mock("@/app/(dashboard)/hooks/useTeams", () => ({ default: () => ({ teams: [], @@ -104,4 +114,43 @@ describe("ModelsAndEndpointsView", () => { ); expect(await findByText("Model Management", {}, { timeout: 10000 })).toBeInTheDocument(); }, 15000); + + it("should pass model IDs (not model names) to HealthCheckComponent as all_models_on_proxy", async () => { + mockHealthCheckComponent.mockClear(); + const modelDataWithIds = { + data: [ + { model_name: "gpt-4", model_info: { id: "deployment-id-1" } }, + { model_name: "gpt-4", model_info: { id: "deployment-id-2" } }, + ], + }; + mockUseModelsInfo.mockReturnValue({ + data: { data: modelDataWithIds.data }, + isLoading: false, + refetch: vi.fn(), + }); + + const queryClient = createQueryClient(); + const { getByRole } = render( + + {}} + premiumUser={false} + teams={[]} + /> + , + ); + + const healthStatusTab = getByRole("tab", { name: "Health Status" }); + await act(async () => { + healthStatusTab.click(); + }); + + expect(mockHealthCheckComponent).toHaveBeenCalled(); + const healthCheckProps = mockHealthCheckComponent.mock.calls[0][0]; + expect(healthCheckProps.all_models_on_proxy).toEqual(["deployment-id-1", "deployment-id-2"]); + expect(healthCheckProps.all_models_on_proxy).not.toContain("gpt-4"); + }); }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx index 9d77774cb4c..b697a859dc5 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/ModelsAndEndpointsView.tsx @@ -98,6 +98,13 @@ const ModelsAndEndpointsView: React.FC = ({ premiumUser, te return modelDataResponse.data.map((model: any) => model.model_name); }, [modelDataResponse?.data]); + const allModelIdsOnProxy = useMemo(() => { + if (!modelDataResponse?.data) return []; + return modelDataResponse.data + .map((model: any) => model.model_info?.id) + .filter((id: string | undefined): id is string => Boolean(id)); + }, [modelDataResponse?.data]); + const getProviderFromModel = (model: string) => { if (modelCostMapData !== null && modelCostMapData !== undefined) { if (typeof modelCostMapData == "object" && model in modelCostMapData) { @@ -397,7 +404,7 @@ const ModelsAndEndpointsView: React.FC = ({ premiumUser, te ) : page == "vector-stores" ? ( + ) : page == "tool-policies" ? ( + ) : page == "guardrails-monitor" ? ( ) : page == "new_usage" ? ( diff --git a/ui/litellm-dashboard/src/components/ToolPolicies.tsx b/ui/litellm-dashboard/src/components/ToolPolicies.tsx new file mode 100644 index 00000000000..0e3f5434e7f --- /dev/null +++ b/ui/litellm-dashboard/src/components/ToolPolicies.tsx @@ -0,0 +1,415 @@ +"use client"; + +import React, { useCallback, useDeferredValue, useEffect, useState } from "react"; +import { Select, Switch, Tooltip } from "antd"; +import { Select, Tooltip } from "antd"; +import { + Table, + TableHead, + TableHeaderCell, + TableBody, + TableRow, + TableCell, +} from "@tremor/react"; +import { TimeCell } from "./view_logs/time_cell"; +import { TableHeaderSortDropdown } from "./common_components/TableHeaderSortDropdown/TableHeaderSortDropdown"; +import type { SortState } from "./common_components/TableHeaderSortDropdown/TableHeaderSortDropdown"; +import FilterComponent, { FilterOption } from "./molecules/filter"; +import { fetchToolsList, updateToolPolicy, ToolRow } from "./networking"; + +const POLICY_OPTIONS = [ + { value: "trusted", label: "trusted", color: "#065f46", bg: "#d1fae5", border: "#6ee7b7" }, + { value: "blocked", label: "blocked", color: "#991b1b", bg: "#fee2e2", border: "#fca5a5" }, +] as const; + +type PolicyValue = "trusted" | "blocked"; + +const policyStyle = (p: string) => + POLICY_OPTIONS.find((o) => o.value === p) ?? POLICY_OPTIONS[1]; + +type SortField = "tool_name" | "call_policy" | "team_id" | "key_alias" | "created_at" | "call_count"; + +interface FilterValues { + [key: string]: string; +} + +interface ToolPoliciesProps { + accessToken: string | null; + userRole?: string; +} + +const PolicySelect: React.FC<{ + value: string; + toolName: string; + saving: boolean; + onChange: (toolName: string, policy: string) => void; +}> = ({ value, toolName, saving, onChange }) => { + const style = policyStyle(value); + return ( + { setSearchTerm(e.target.value); setCurrentPage(1); }} + /> + + + + + +
+ Live Tail + +
+ + + + +
+ + Showing {filtered.length === 0 ? 0 : (currentPage - 1) * pageSize + 1} - {Math.min(currentPage * pageSize, filtered.length)} of {filtered.length} results + + Page {currentPage} of {totalPages} +
+ + +
+
+ + + {/* Filter row */} +
+ +
+ + + {/* Auto-refresh banner */} + {isLiveTail && ( +
+ Auto-refreshing every 15 seconds + +
+ )} + + {error && ( +
{error}
+ )} + + {/* Table */} + + + + + + + + + Key Hash + + Origin + + + + {loading ? ( + + Loading tools… + + ) : paginated.length === 0 ? ( + + + No tools discovered yet. Make a chat completion that returns tool_calls to start auto-discovery. + + + ) : ( + paginated.map((tool) => ( + + + + + + + + {tool.tool_name} + + + + + + + + {(tool.call_count ?? 0).toLocaleString()} + + + + {tool.team_id ?? "-"} + + + + + + {tool.key_hash ?? "-"} + + + + + + {tool.key_alias ?? "-"} + + + + + {tool.origin ?? "-"} + + + + )) + )} + +
+ + {/* Bottom pagination (only when > 1 page) */} + {totalPages > 1 && ( +
+ Showing {(currentPage - 1) * pageSize + 1} - {Math.min(currentPage * pageSize, sorted.length)} of {sorted.length} +
+ + +
+
+ )} + + + ); +}; + +export default ToolPolicies; diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.test.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.test.tsx new file mode 100644 index 00000000000..85ce11e605a --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.test.tsx @@ -0,0 +1,85 @@ +import { screen } from "@testing-library/react"; +import { beforeAll, describe, expect, it, vi } from "vitest"; +import { renderWithProviders } from "../../../../tests/test-utils"; +import UsageAIChatPanel from "./UsageAIChatPanel"; + +beforeAll(() => { + if (typeof window !== "undefined" && !window.ResizeObserver) { + window.ResizeObserver = class ResizeObserver { + observe() {} + unobserve() {} + disconnect() {} + } as any; + } +}); + +vi.mock("../../networking", () => ({ + modelHubCall: vi.fn().mockResolvedValue({ + data: [ + { model_group: "gpt-4" }, + { model_group: "claude-3-opus" }, + ], + }), + usageAiChatStream: vi.fn(), +})); + +const defaultProps = { + open: true, + onClose: vi.fn(), + accessToken: "test-token", +}; + +describe("UsageAIChatPanel", () => { + it("should render the panel when open", () => { + renderWithProviders(); + + expect(screen.getByText("Ask AI")).toBeInTheDocument(); + expect( + screen.getByText("Ask about your spend, models, keys, and trends") + ).toBeInTheDocument(); + }); + + it("should render model selector", () => { + renderWithProviders(); + + expect(screen.getByText("Select a model (optional, defaults to gpt-4o-mini)")).toBeInTheDocument(); + }); + + it("should render empty state message when no conversation", () => { + renderWithProviders(); + + expect(screen.getByText("Ask a question about your usage")).toBeInTheDocument(); + }); + + it("should render the send button", () => { + renderWithProviders(); + + expect(screen.getByText("Send")).toBeInTheDocument(); + }); + + it("should render input placeholder", () => { + renderWithProviders(); + + expect(screen.getByPlaceholderText("Ask about your usage...")).toBeInTheDocument(); + }); + + it("should render clear chat button", () => { + renderWithProviders(); + + expect(screen.getByText("Clear chat")).toBeInTheDocument(); + }); + + it("should have the panel element even when closed (just off-screen)", () => { + renderWithProviders(); + + expect(screen.getByTestId("usage-ai-chat-panel")).toBeInTheDocument(); + expect(screen.getByTestId("usage-ai-chat-panel")).toHaveClass("translate-x-full"); + }); + + it("should not have translate-x-full class when open", () => { + renderWithProviders(); + + expect(screen.getByTestId("usage-ai-chat-panel")).not.toHaveClass("translate-x-full"); + expect(screen.getByTestId("usage-ai-chat-panel")).toHaveClass("translate-x-0"); + }); +}); diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.tsx new file mode 100644 index 00000000000..85f46bfa346 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/UsageAIChatPanel.tsx @@ -0,0 +1,402 @@ +import React, { useEffect, useRef, useState } from "react"; +import { Button, Select, Input, Spin } from "antd"; +import ReactMarkdown from "react-markdown"; +import { modelHubCall, usageAiChatStream, UsageAiToolCallEvent } from "../../networking"; + +const { TextArea } = Input; + +interface ToolCallStep { + tool_name: string; + tool_label: string; + arguments: Record; + status: "running" | "complete" | "error"; + error?: string; +} + +interface ChatMessage { + role: "user" | "assistant"; + content: string; + toolCalls?: ToolCallStep[]; +} + +interface UsageAIChatPanelProps { + open: boolean; + onClose: () => void; + accessToken: string | null; +} + +const TOOL_ICONS: Record = { + get_usage_data: "📊", + get_team_usage_data: "👥", + get_tag_usage_data: "🏷️", +}; + +const ToolCallDisplay: React.FC<{ step: ToolCallStep }> = ({ step }) => { + const icon = TOOL_ICONS[step.tool_name] || "🔧"; + const args = step.arguments; + const dateRange = args.start_date && args.end_date + ? `${args.start_date} → ${args.end_date}` + : ""; + const filter = args.team_ids || args.tags || args.user_id || ""; + + return ( +
+ + {step.status === "running" ? ( + + ) : step.status === "error" ? ( + ✗ + ) : ( + ✓ + )} + +
+
+ {icon} {step.tool_label} +
+ {dateRange && ( +
{dateRange}
+ )} + {filter && ( +
Filter: {filter}
+ )} + {step.status === "error" && step.error && ( +
{step.error}
+ )} +
+
+ ); +}; + +const MarkdownContent: React.FC<{ content: string }> = ({ content }) => ( +

{children}

, + strong: ({ children }) => {children}, + ul: ({ children }) =>
    {children}
, + ol: ({ children }) =>
    {children}
, + li: ({ children }) =>
  • {children}
    • , + h1: ({ children }) =>

    {children}

    , + h2: ({ children }) =>

    {children}

    , + h3: ({ children }) =>

    {children}

    , + code: ({ children, className }) => { + const isBlock = className?.includes("language-"); + return isBlock ? ( + 
    +            {children}
+
    + ) : ( + {children} + ); + }, + table: ({ children }) => ( +
    + {children}
    +
    + ), + th: ({ children }) => {children}, + td: ({ children }) => {children}, + }} + > + {content} +     +); + +const UsageAIChatPanel: React.FC = ({ + open, + onClose, + accessToken, +}) => { + const [messages, setMessages] = useState([]); + const [inputText, setInputText] = useState(""); + const [isLoading, setIsLoading] = useState(false); + const [selectedModel, setSelectedModel] = useState(undefined); + const [availableModels, setAvailableModels] = useState([]); + const [isLoadingModels, setIsLoadingModels] = useState(false); + const [streamingContent, setStreamingContent] = useState(""); + const [statusMessage, setStatusMessage] = useState(null); + const [activeToolCalls, setActiveToolCalls] = useState([]); + const messagesEndRef = useRef(null); + const abortControllerRef = useRef(null); + + useEffect(() => { + if (open && availableModels.length === 0) { + loadModels(); + } + }, [open]); + + useEffect(() => { + if (typeof messagesEndRef.current?.scrollIntoView === "function") { + messagesEndRef.current.scrollIntoView({ behavior: "smooth" }); + } + }, [messages, streamingContent, activeToolCalls, statusMessage]); + + const loadModels = async () => { + if (!accessToken) return; + setIsLoadingModels(true); + try { + const fetchedModels = await modelHubCall(accessToken); + if (fetchedModels?.data?.length > 0) { + const models = fetchedModels.data + .map((item: any) => item.model_group as string) + .sort(); + setAvailableModels(models); + } + } catch (error) { + console.error("Failed to load models:", error); + } finally { + setIsLoadingModels(false); + } + }; + + const handleSend = async () => { + if (!accessToken || !inputText.trim() || isLoading) return; + + const userMessage: ChatMessage = { role: "user", content: inputText.trim() }; + const updatedMessages = [...messages, userMessage]; + setMessages(updatedMessages); + setInputText(""); + setIsLoading(true); + setStreamingContent(""); + setStatusMessage(null); + setActiveToolCalls([]); + + const abortController = new AbortController(); + abortControllerRef.current = abortController; + + let accumulated = ""; + const toolCalls: ToolCallStep[] = []; + + try { + await usageAiChatStream( + accessToken, + updatedMessages.slice(-20).map((m) => ({ role: m.role, content: m.content })), + selectedModel || "", + (content: string) => { + setStatusMessage(null); + accumulated += content; + setStreamingContent(accumulated); + }, + () => { + setStatusMessage(null); + setActiveToolCalls([]); + setMessages((prev) => [ + ...prev, + { role: "assistant", content: accumulated, toolCalls: toolCalls.length > 0 ? [...toolCalls] : undefined }, + ]); + setStreamingContent(""); + }, + (errorMsg: string) => { + setStatusMessage(null); + setActiveToolCalls([]); + setMessages((prev) => [ + ...prev, + { role: "assistant", content: `Error: ${errorMsg}` }, + ]); + setStreamingContent(""); + }, + (status: string) => { + setStatusMessage(status); + }, + (event: UsageAiToolCallEvent) => { + const idx = toolCalls.findIndex((tc) => tc.tool_name === event.tool_name); + if (idx >= 0) { + toolCalls[idx] = { ...event }; + } else { + toolCalls.push({ ...event }); + } + setActiveToolCalls([...toolCalls]); + }, + abortController.signal, + ); + } catch (error: any) { + if (error?.name === "AbortError" || abortController.signal.aborted) { + return; + } + const errorMsg = error?.message || "Failed to get response. Please try again."; + setMessages((prev) => [ + ...prev, + { role: "assistant", content: `Error: ${errorMsg}` }, + ]); + setStreamingContent(""); + } finally { + setIsLoading(false); + abortControllerRef.current = null; + } + }; + + const handleKeyDown = (e: React.KeyboardEvent) => { + if (e.key === "Enter" && !e.shiftKey) { + e.preventDefault(); + handleSend(); + } + }; + + const handleClose = () => { + if (abortControllerRef.current) { + abortControllerRef.current.abort(); + } + onClose(); + }; + + const handleClear = () => { + setMessages([]); + setStreamingContent(""); + setActiveToolCalls([]); + setStatusMessage(null); + }; + + return ( +
    + {/* Header */} +
    +
    +
    + + + +

    Ask AI

    +
    + +
    +

    + Ask about your spend, models, keys, and trends +

    +
    + + {/* Model selector */} +
    +