observability/ai-trace-explorer

1---2title: AI Trace Explorer3emoji: 🔎4colorFrom: blue5colorTo: indigo6sdk: static7pinned: false8---9 10# AI Trace Explorer11 12### Explore end-to-end traces across modern AI systems13 14**AI Trace Explorer** is an interactive Hugging Face Space for understanding how traces connect models, retrieval, tools, agents, memory, verification and infrastructure into one observable execution path.15 16> **A trace turns a complex AI workflow into a sequence you can inspect, correlate and debug.**17 18---19 20# What Is an AI Trace?21 22An **AI trace** is an end-to-end record of what happened during one request or workflow.23 24A trace may include:25 26- user request27- routing decision28- model call29- retrieval30- reranking31- tool use32- agent step33- memory read34- memory write35- verifier call36- fallback37- human approval38- final response39 40Example:41 42```text43User Request44   ↓45Router46   ↓47Reasoning Model48   ↓49Retriever50   ↓51Tool Call52   ↓53Agent Step54   ↓55Verifier56   ↓57Final Response58```59 60---61 62# Why Traces Matter63 64Modern AI systems often distribute work across many components.65 66Without a trace, operators may know that a request failed but not:67 68- where it failed69- why it failed70- which model was used71- which tool was called72- which context was retrieved73- whether verification ran74- whether a fallback occurred75- how much each stage cost76 77Traces make these questions answerable.78 79---80 81# Trace Anatomy82 83A trace usually contains multiple spans.84 85```text86TRACE87 ├── Span: Request88 ├── Span: Router89 ├── Span: Model90 ├── Span: Retrieval91 ├── Span: Tool92 ├── Span: Verification93 └── Span: Response94```95 96Each span may contain:97 98- `trace_id`99- `span_id`100- `parent_span_id`101- start time102- end time103- duration104- component105- status106- input107- output108- error109- metadata110- token usage111- cost112 113---114 115# Correlation116 117The core purpose of tracing is correlation.118 119Example:120 121```text122trace_id = abc123123 124request125  ↓126model_call127  ↓128retrieval129  ↓130tool_call131  ↓132verification133  ↓134response135```136 137Every stage belongs to the same execution context.138 139---140 141# Trace Types142 143## LLM Trace144 145Tracks:146 147- prompt148- model149- provider150- output151- latency152- tokens153- cost154 155## RAG Trace156 157Tracks:158 159- query160- retrieval161- candidates162- reranking163- context164- generation165 166## Agent Trace167 168Tracks:169 170- goal171- plan172- steps173- tools174- memory175- retries176- verification177 178## Multi-Agent Trace179 180Tracks:181 182- agent identity183- delegation184- messages185- shared state186- synthesis187 188## Inference Trace189 190Tracks:191 192- queue time193- model load194- batch195- compute196- token streaming197- latency198 199---200 201# End-to-End Trace Example202 203```text204User Request205  ↓206Intent Classification207  ↓208Model Router209  ↓210Reasoning Model211  ↓212Knowledge Retrieval213  ↓214Reranker215  ↓216Tool Selection217  ↓218Tool Execution219  ↓220Verifier221  ↓222Response223```224 225A trace explorer should make this path visible.226 227---228 229# Trace Fields230 231Useful trace fields include:232 233```text234trace_id235span_id236parent_span_id237timestamp238component239operation240status241duration242model243provider244agent245tool246input_tokens247output_tokens248cost249error250evaluation251verification252metadata253```254 255---256 257# Span Relationships258 259Spans may be:260 261- sequential262- nested263- parallel264- retried265- branched266- merged267 268Example:269 270```text271Request272 ├── Retrieval273 │    ├── Search274 │    └── Rerank275 ├── Model276 └── Verification277```278 279---280 281# Parallel Spans282 283Parallel execution is common in:284 285- multi-agent systems286- ensemble verification287- parallel retrieval288- speculative execution289- model comparison290 291```text292        ┌→ Agent A293Request ├→ Agent B294        └→ Agent C295             ↓296          Merge297```298 299Trace visualization helps show concurrency and timing.300 301---302 303# Retry Tracing304 305Retries should be explicit.306 307```text308Tool Call309  ↓310Failure311  ↓312Retry 1313  ↓314Failure315  ↓316Fallback Tool317  ↓318Success319```320 321Useful fields:322 323- retry count324- retry reason325- backoff326- alternate route327- final outcome328 329---330 331# Error Tracing332 333Error traces should answer:334 335- which component failed336- what input caused it337- what error occurred338- whether the system recovered339- whether the user was affected340 341---342 343# Cost Tracing344 345A single trace may include cost from:346 347- model calls348- embeddings349- retrieval350- reranking351- tools352- verification353- retries354 355Example:356 357```text358Trace Cost359  ├── Model         $...360  ├── Retrieval     $...361  ├── Tool          $...362  ├── Verification  $...363  └── Retry         $...364```365 366---367 368# Latency Tracing369 370Latency can be decomposed into:371 372```text373Total Latency374  ├── Queue375  ├── Model376  ├── Retrieval377  ├── Tool378  ├── Verification379  └── Network380```381 382This helps identify bottlenecks.383 384---385 386# Trace + Evaluation387 388Traces become more useful when quality signals are attached.389 390Example:391 392```text393trace_id: abc123394task_success: true395quality_score: 0.91396verification: pass397cost: ...398latency: ...399```400 401This enables analysis such as:402 403> Which execution patterns correlate with high-quality results?404 405---406 407# Trace + Validation408 409Validation can be linked to specific spans.410 411For example:412 413- structured output validation414- schema validation415- tool-result validation416- policy validation417- final response validation418 419---420 421# Trace + Verification422 423Verification should be observable as its own span.424 425```text426Output427  ↓428Verifier Span429  ↓430Pass / Fail431  ↓432Continue / Retry433```434 435---436 437# Trace + Human Approval438 439Human approval can be represented as an event or span.440 441Useful fields:442 443- approval request444- risk level445- approver446- decision447- wait time448- resulting action449 450---451 452# Trace Sampling453 454High-volume systems may sample traces.455 456Possible strategies:457 458- random sampling459- error-biased sampling460- latency-biased sampling461- high-cost sampling462- low-quality sampling463- policy-event sampling464 465Sampling should avoid hiding rare but important failures.466 467---468 469# Trace Privacy470 471Traces may contain sensitive data.472 473Potentially sensitive fields:474 475- prompts476- user input477- model output478- retrieved documents479- credentials480- tool arguments481- personal information482 483Useful controls include:484 485- redaction486- masking487- selective capture488- retention limits489- access control490- encryption491 492---493 494# Trace Retention495 496Not every trace needs to be stored forever.497 498Retention may depend on:499 500- risk501- incident relevance502- regulatory requirements503- cost504- debugging needs505- privacy requirements506 507---508 509# Trace Search510 511Useful trace search dimensions include:512 513- trace ID514- model515- agent516- tool517- error518- latency519- cost520- verifier result521- user522- workflow version523- time range524 525---526 527# Trace Comparison528 529Comparing traces helps diagnose regressions.530 531Example:532 533```text534Trace A535  model = X536  latency = 2.1s537  quality = 0.92538 539Trace B540  model = Y541  latency = 1.1s542  quality = 0.81543```544 545---546 547# Trace Diffing548 549A trace diff can compare:550 551- model versions552- prompt versions553- routing decisions554- tool paths555- retrieval context556- number of steps557- total cost558- outcome559 560---561 562# Interactive Explorer563 564The included `index.html` lets users explore trace patterns for:565 566- LLM calls567- RAG568- agents569- multi-agent systems570- tool retries571- verification572- cost573- latency574- human approval575- failure recovery576 577Each pattern includes:578 579- execution flow580- important fields581- debugging value582- operational risks583 584---585 586# SEO & GEO Topic Map587 588This Space is structured around:589 590- AI Trace Explorer591- AI tracing592- LLM tracing593- agent tracing594- AI trace visualization595- AI span tracing596- RAG tracing597- tool tracing598- AI observability599- AI telemetry600- AI debugging601- trace correlation602- trace sampling603- trace cost604- trace latency605- agent runtime tracing606- multi-agent tracing607- verification tracing608- AI trace analysis609 610---611 612# GEO Entity Relationships613 614```text615AI Trace616  CONTAINS → Spans617  CONNECTS → Models618  CONNECTS → Agents619  CONNECTS → Tools620  CONNECTS → Retrieval621  CONNECTS → Memory622  CONNECTS → Verification623  TRACKS → Latency624  TRACKS → Cost625  TRACKS → Errors626  SUPPORTS → Debugging627  SUPPORTS → Evaluation628  SUPPORTS → Validation629  SUPPORTS → Reliability630```631 632---633 634# Collaboration & Partnerships635 636**AI Trace Explorer** is open to collaboration with companies, research teams, universities and open-source projects working on AI tracing, telemetry and observability.637 638Relevant areas include:639 640- tracing641- spans642- telemetry643- LLM observability644- agent observability645- tool tracing646- RAG tracing647- cost tracing648- latency analysis649- evaluation650- verification651- OpenTelemetry652- production AI systems653 654Possible collaboration formats include:655 656- joint Hugging Face Spaces657- trace visualization demos658- framework integrations659- technical showcases660- benchmark projects661- open-source integrations662- clearly disclosed partnerships and sponsorships663 664## Collaboration Contact665 666**agenten@magenta.de**667 668---669 670# Independence671 672**AI Trace Explorer** is an independent Hugging Face Space.673 674It is not an official project of Hugging Face, OpenTelemetry, any AI laboratory, observability vendor, model provider or technology company.675 676---677 678# Long-Term Vision679 680The goal is to make complex AI execution paths understandable at a glance.681 682> **One request. Many components. One trace.**683 684### Trace. Correlate. Diagnose. Improve.685