{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm-traceloop-instrumentation-llamaindex","slug":"traceloop-instrumentation-llamaindex","name":"@traceloop/instrumentation-llamaindex","type":"framework","url":"https://github.com/traceloop/openllmetry-js/tree/main/packages/instrumentation-llamaindex","page_url":"https://unfragile.ai/traceloop-instrumentation-llamaindex","categories":["frameworks-sdks"],"tags":["opentelemetry","nodejs","tracing","llamaindex"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm-traceloop-instrumentation-llamaindex__cap_0","uri":"capability://automation.workflow.automatic.llamaindex.operation.tracing","name":"automatic-llamaindex-operation-tracing","description":"Automatically instruments LlamaIndex operations (indexing, querying, embedding, LLM calls) by hooking into LlamaIndex's internal event system and converting them to OpenTelemetry spans. 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Automatically detects operation failures (embedding errors, LLM API failures, vector search timeouts) and attaches error context including exception type, message, and stack trace to spans for root cause analysis.","intents":["I want to see which LlamaIndex operations are failing and why without parsing logs","I need to correlate embedding failures with specific models or vector database issues","I want to track error rates per LlamaIndex component (indexing vs querying) in my trace backend"],"best_for":["SREs and observability engineers debugging production failures in LlamaIndex-based RAG systems","developers building resilient RAG pipelines who need detailed error context from LlamaIndex operations","teams using trace backends with error tracking and alerting capabilities (Datadog, New Relic, Sentry integration)"],"limitations":["Error capture depends on LlamaIndex's exception handling; some internal errors may not propagate to the instrumentation layer","Stack traces are captured but may be truncated or sanitized by OpenTelemetry exporters depending on backend limits","Sensitive error data (API keys, user data in error messages) may be exposed in spans; requires careful configuration of span processors or exporters","Error attribution is limited to the LlamaIndex operation level; root cause in external services (LLM API, vector DB) may require additional instrumentation"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","OpenTelemetry API and SDK","LlamaIndex 0.9.0 or compatible","trace backend with error tracking and alerting (optional but recommended)"],"input_types":["exceptions and errors thrown by LlamaIndex operations","operation context and metadata at time of failure"],"output_types":["OpenTelemetry span events with error type and message","span status set to ERROR with exception details","structured error data queryable in trace backends"],"categories":["safety-moderation","observability"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-traceloop-instrumentation-llamaindex__cap_4","uri":"capability://data.processing.analysis.llamaindex.operation.latency.measurement","name":"llamaindex-operation-latency-measurement","description":"Measures and records the duration of LlamaIndex operations (indexing, querying, embedding, LLM calls) as OpenTelemetry span durations with nanosecond precision. Automatically captures start and end times for each instrumented operation, enabling latency analysis, percentile tracking, and performance bottleneck identification across the RAG pipeline.","intents":["I want to identify which LlamaIndex operations are slowest in my RAG pipeline (indexing vs querying vs embedding)","I need to track p50, p95, p99 latencies for embedding calls and vector searches to detect performance degradation","I want to correlate latency spikes with specific LlamaIndex components or external service changes"],"best_for":["performance engineers optimizing LlamaIndex-based RAG systems for latency-sensitive applications","teams using APM platforms (Datadog, New Relic) with latency dashboarding and alerting","developers profiling LlamaIndex operations to identify optimization opportunities"],"limitations":["Latency measurement includes instrumentation overhead (~1-5ms per operation depending on exporter configuration)","High-frequency operations (millions of embeddings) may create excessive span volume, impacting trace backend storage and query performance","Latency attribution is limited to LlamaIndex operation boundaries; does not measure time spent in external services (LLM API, vector DB) separately unless those services are also instrumented","Clock skew or system time adjustments may affect latency accuracy; relies on system clock precision"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","OpenTelemetry API and SDK with timer support","LlamaIndex 0.9.0 or compatible","trace backend with latency aggregation and percentile calculation (optional but recommended)"],"input_types":["LlamaIndex operation start and end events","operation context and metadata"],"output_types":["OpenTelemetry span duration in nanoseconds","latency metrics aggregatable by operation type, model, or backend","time-series data for latency trending and alerting"],"categories":["data-processing-analysis","observability"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-traceloop-instrumentation-llamaindex__cap_5","uri":"capability://automation.workflow.llamaindex.context.propagation.across.operations","name":"llamaindex-context-propagation-across-operations","description":"Propagates OpenTelemetry trace context (trace ID, span ID, baggage) across LlamaIndex operations and between LlamaIndex and external service calls (LLM APIs, vector databases). Ensures that all operations within a single RAG query or indexing job share the same trace ID, enabling end-to-end tracing of request flows through the entire system.","intents":["I want to trace a single user query through the entire LlamaIndex pipeline (retrieval, ranking, LLM call) with a single trace ID","I need to correlate LlamaIndex operations with external service calls (OpenAI API, Pinecone) in a unified trace","I want to propagate trace context to downstream services so that a single request is traceable across my entire system"],"best_for":["distributed systems teams building microservices around LlamaIndex where end-to-end tracing is critical","teams integrating LlamaIndex with external LLM and vector database APIs and needing unified trace visibility","organizations using trace correlation for debugging complex multi-service failures"],"limitations":["Context propagation requires compatible instrumentation in external services; if LLM APIs or vector DBs are not instrumented, trace context will not propagate beyond LlamaIndex","Baggage propagation adds overhead and may expose sensitive data if not carefully configured; requires filtering of sensitive attributes","Context propagation format depends on OpenTelemetry's W3C Trace Context standard; older systems may not support it","Trace context is lost if LlamaIndex operations spawn background tasks or async operations without explicit context passing"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","OpenTelemetry API and SDK with context propagation support","LlamaIndex 0.9.0 or compatible","compatible instrumentation in external services (LLM APIs, vector DBs) for full end-to-end tracing (optional)"],"input_types":["OpenTelemetry trace context from incoming requests","LlamaIndex operation context","external service call context"],"output_types":["propagated trace ID and span ID across LlamaIndex operations","W3C Trace Context headers for external service calls","unified trace view in trace backends showing all operations with same trace ID"],"categories":["automation-workflow","observability"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-traceloop-instrumentation-llamaindex__cap_6","uri":"capability://automation.workflow.llamaindex.instrumentation.configuration.and.control","name":"llamaindex-instrumentation-configuration-and-control","description":"Provides configuration options to enable/disable instrumentation, control span sampling, filter which LlamaIndex operations are traced, and customize span naming and attribute mapping. Uses environment variables and programmatic configuration to allow fine-grained control over instrumentation behavior without code changes to LlamaIndex-using applications.","intents":["I want to disable tracing for specific LlamaIndex operations (e.g., skip embedding traces) to reduce overhead","I need to sample only 10% of LlamaIndex queries in production to manage trace volume","I want to customize span names or attributes to match my organization's naming conventions"],"best_for":["teams managing high-volume LlamaIndex applications who need to control trace volume and costs","organizations with custom observability standards requiring span naming or attribute customization","developers tuning instrumentation overhead in performance-sensitive applications"],"limitations":["Configuration is external to the instrumentation package; requires separate OpenTelemetry SDK configuration","Sampling configuration at the instrumentation level may conflict with SDK-level sampling; requires careful coordination","Custom span naming or attribute mapping requires code changes to configuration, not just environment variables","No built-in UI for configuration; requires manual editing of configuration files or environment variables"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","OpenTelemetry SDK with configuration support","LlamaIndex 0.9.0 or compatible"],"input_types":["environment variables or configuration objects","instrumentation enable/disable flags","sampling rate configuration","operation filter lists"],"output_types":["configured instrumentation behavior","filtered or sampled spans based on configuration","customized span names and attributes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-traceloop-instrumentation-llamaindex__cap_7","uri":"capability://automation.workflow.llamaindex.version.compatibility.detection","name":"llamaindex-version-compatibility-detection","description":"Automatically detects the installed LlamaIndex version and adapts instrumentation behavior to match the version's API and event system. Handles breaking changes across LlamaIndex versions by conditionally enabling/disabling instrumentation features based on detected version, ensuring compatibility without requiring manual version-specific configuration.","intents":["I want to upgrade LlamaIndex without worrying about breaking my instrumentation","I need to support multiple LlamaIndex versions in my application without manual configuration","I want to know if my instrumentation is compatible with my installed LlamaIndex version"],"best_for":["teams managing LlamaIndex upgrades and needing instrumentation compatibility assurance","monorepos or multi-service environments using different LlamaIndex versions","developers building LlamaIndex-based libraries that need to support multiple versions"],"limitations":["Version detection is performed at runtime; incompatibilities are discovered after instrumentation initialization","Instrumentation may gracefully degrade for unsupported versions, losing some tracing capabilities without explicit warning","Version compatibility matrix is maintained by the instrumentation package maintainers; lag between LlamaIndex releases and instrumentation updates is possible","No built-in migration guide or warnings for deprecated LlamaIndex APIs; developers must consult LlamaIndex changelog separately"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","LlamaIndex 0.9.0 or compatible (specific version range depends on instrumentation version)"],"input_types":["installed LlamaIndex package version"],"output_types":["instrumentation behavior adapted to detected version","compatibility status (compatible, degraded, incompatible)","warnings or errors if version is unsupported"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-traceloop-instrumentation-llamaindex__cap_8","uri":"capability://tool.use.integration.opentelemetry.sdk.integration.and.initialization","name":"opentelemetry-sdk-integration-and-initialization","description":"Integrates with OpenTelemetry SDK initialization patterns, providing a standardized way to register LlamaIndex instrumentation alongside other Node.js instrumentation (HTTP, database, etc.). Follows OpenTelemetry's instrumentation registration conventions, allowing LlamaIndex tracing to be enabled via a single SDK initialization call.","intents":["I want to enable LlamaIndex tracing as part of my standard OpenTelemetry SDK setup without special configuration","I need to register LlamaIndex instrumentation alongside other Node.js instrumentation (HTTP, database)","I want to use OpenTelemetry's standard instrumentation patterns for consistency across my application"],"best_for":["Node.js teams already using OpenTelemetry and wanting to add LlamaIndex tracing","organizations standardizing on OpenTelemetry instrumentation across all services","developers building observability infrastructure for Node.js applications"],"limitations":["Requires understanding of OpenTelemetry SDK initialization and configuration; not suitable for teams unfamiliar with OpenTelemetry","Integration is limited to Node.js; no support for browser or other JavaScript runtimes","SDK initialization must occur before LlamaIndex is imported; incorrect initialization order may result in missed traces","Instrumentation registration is global; cannot selectively enable/disable per LlamaIndex instance"],"requires":["Node.js 14+","@traceloop/instrumentation-llamaindex package","OpenTelemetry API (@opentelemetry/api)","OpenTelemetry SDK (@opentelemetry/sdk-node)","OpenTelemetry exporter (e.g., @opentelemetry/exporter-trace-otlp-http)"],"input_types":["OpenTelemetry SDK configuration","instrumentation registration calls"],"output_types":["initialized OpenTelemetry SDK with LlamaIndex instrumentation registered","active tracer provider ready to capture LlamaIndex spans"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Node.js 14+","@traceloop/instrumentation-llamaindex npm package","OpenTelemetry API and SDK (@opentelemetry/api, @opentelemetry/sdk-node)","LlamaIndex 0.9.0 or compatible version","OpenTelemetry exporter (e.g., @opentelemetry/exporter-trace-otlp-http for OTLP, or vendor-specific exporters)","@traceloop/instrumentation-llamaindex package","OpenTelemetry API and SDK","LlamaIndex 0.9.0 or compatible","trace backend supporting attribute-based querying (optional but recommended)","OpenTelemetry SDK (@opentelemetry/sdk-node)"],"failure_modes":["Only instruments LlamaIndex operations; 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