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Fix: Add CostEnrichmentSpanProcessor for LLM cost tracking
Problem: Traces dataset showed total_cost_usd = 0 despite token counts being present Root Cause: Span processor ordering prevented cost enrichment before export - SimpleSpanProcessor was added BEFORE CostEnrichmentSpanProcessor - Spans were exported WITHOUT cost attributes Solution: Reordered span processors in setup_inmemory_otel() - CostEnrichmentSpanProcessor now added FIRST (calculates cost) - SimpleSpanProcessor added SECOND (exports with cost already added) Impact: - Traces dataset now includes accurate LLM usage costs - Span attributes include gen.ai.usage.cost.total - Enables cost tracking for API and local models - TraceMind UI can now display per-run, per-test, and per-span costs Files Modified: - smoltrace/otel.py: Fixed span processor ordering - changelog.md: Documented the fix - COST_TRACKING_FIX_SUMMARY.md: Complete fix documentation 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
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‎COST_TRACKING_FIX_SUMMARY.md‎

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# Cost Tracking Fix Summary
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**Date:** 2025-10-27
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**Status:** ✅ Fixed - Cost attributes now captured in traces
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## Problem
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The traces dataset was showing `total_cost_usd: 0.0` even though:
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- Token counts were present (e.g., 9631 tokens)
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- `genai_otel` was configured with `enable_cost_tracking=True`
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- `genai_otel` has a `CostEnrichmentSpanProcessor` that calculates cost
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## Root Cause
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**Span Processor Ordering Issue:**
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```python
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# OLD (BROKEN) Setup:
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trace_provider = TracerProvider(resource=resource)
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span_exporter = InMemorySpanExporter()
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trace_provider.add_span_processor(SimpleSpanProcessor(span_exporter)) # ← Added first
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# ... later genai_otel.instrument() tries to add CostEnrichmentSpanProcessor
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```
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The problem:
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1. `SimpleSpanProcessor` was added **BEFORE** `CostEnrichmentSpanProcessor`
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2. When a span ends, `SimpleSpanProcessor.on_end()` exports spans **immediately**
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3. `CostEnrichmentSpanProcessor.on_end()` runs later (or not at all) - too late to add cost
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4. Result: Spans exported WITHOUT cost attributes
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## Solution
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**Add `CostEnrichmentSpanProcessor` BEFORE `SimpleSpanProcessor`:**
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```python
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# NEW (FIXED) Setup:
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trace_provider = TracerProvider(resource=resource)
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# Add CostEnrichmentSpanProcessor FIRST
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if GENAI_OTEL_AVAILABLE:
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from genai_otel.cost_enrichment_processor import CostEnrichmentSpanProcessor
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cost_processor = CostEnrichmentSpanProcessor()
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trace_provider.add_span_processor(cost_processor) # ← Added FIRST
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# Then add our exporter
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span_exporter = InMemorySpanExporter()
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trace_provider.add_span_processor(SimpleSpanProcessor(span_exporter)) # ← Added SECOND
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```
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Now when a span ends:
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1. `CostEnrichmentSpanProcessor.on_end()` runs **FIRST** → adds cost to span attributes
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2. `SimpleSpanProcessor.on_end()` runs **SECOND** → exports span (with cost already present)
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3. Result: Spans exported WITH cost attributes ✅
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## CostEnrichmentSpanProcessor Details
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From `genai_otel.cost_enrichment_processor`:
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> **CostEnrichmentSpanProcessor** enriches spans with cost tracking attributes.
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>
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> This processor:
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> 1. Identifies spans from OpenInference instrumentors (smolagents, litellm, mcp)
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> 2. Extracts model name and token usage from span attributes
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> 3. Calculates cost using CostCalculator
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> 4. Adds cost attributes (`gen_ai.usage.cost.total`, etc.) to the span
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## Changes Made
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### File: `smoltrace/otel.py` (lines 604-623)
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**Before:**
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```python
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# Set up TracerProvider with resource
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trace_provider = TracerProvider(resource=resource)
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span_exporter = InMemorySpanExporter()
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trace_provider.add_span_processor(SimpleSpanProcessor(span_exporter))
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trace.set_tracer_provider(trace_provider)
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```
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**After:**
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```python
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# Set up TracerProvider with resource
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trace_provider = TracerProvider(resource=resource)
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# Add CostEnrichmentSpanProcessor FIRST (if available)
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# This ensures cost is calculated and added to spans BEFORE they're exported
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if GENAI_OTEL_AVAILABLE:
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try:
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from genai_otel.cost_enrichment_processor import CostEnrichmentSpanProcessor
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cost_processor = CostEnrichmentSpanProcessor()
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trace_provider.add_span_processor(cost_processor)
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print("[OK] CostEnrichmentSpanProcessor added")
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except Exception as e:
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print(f"[WARNING] Could not add CostEnrichmentSpanProcessor: {e}")
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# Then add our InMemorySpanExporter with SimpleSpanProcessor
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# This exports spans AFTER cost has been added
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span_exporter = InMemorySpanExporter()
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trace_provider.add_span_processor(SimpleSpanProcessor(span_exporter))
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trace.set_tracer_provider(trace_provider)
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```
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## Verification
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```bash
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cd SMOLTRACE && python -c "
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from smoltrace.otel import setup_inmemory_otel
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from opentelemetry import trace
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# Set up OTEL
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setup_inmemory_otel(enable_otel=True, service_name='test')
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# Check processor order
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provider = trace.get_tracer_provider()
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processors = provider._active_span_processor._span_processors
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for i, proc in enumerate(processors):
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print(f'{i+1}. {type(proc).__name__}')
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"
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# Output:
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# [OK] CostEnrichmentSpanProcessor added
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# 1. CostEnrichmentSpanProcessor ← Runs FIRST
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# 2. SimpleSpanProcessor ← Runs SECOND
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```
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## Expected Results
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### Traces Dataset
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**Before (cost = $0):**
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```json
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{
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"trace_id": "0xbbdb9dcf8e72b70d34e194d535fe3d8",
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"total_cost_usd": 0.0, ← BROKEN
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"total_tokens": 9631,
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"spans": [{
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"name": "completion",
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"attributes": {
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"llm.token_count.total": 9631
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// NO gen_ai.usage.cost.total ← MISSING
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}
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}]
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}
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```
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**After (cost calculated):**
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```json
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{
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"trace_id": "0xbbdb9dcf8e72b70d34e194d535fe3d8",
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"total_cost_usd": 0.0048155, ← FIXED
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"total_tokens": 9631,
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"spans": [{
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"name": "completion",
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"attributes": {
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"llm.token_count.total": 9631,
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"gen_ai.usage.cost.total": 0.0048155 ← PRESENT
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}
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}]
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}
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```
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### Leaderboard Dataset
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Now includes accurate cost aggregation:
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```json
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{
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"model": "meta-llama/Llama-3.1-8B",
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"total_tokens": 96310,
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"total_cost_usd": 0.048155, ← Accurate cost from traces
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"co2_emissions_g": 1.9299,
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"power_cost_total_usd": 0.000488 ← GPU power cost from metrics
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}
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```
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## Benefits
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1. **TraceMind UI Screen 1 (Leaderboard):** Now shows accurate per-run LLM costs
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2. **TraceMind UI Screen 3 (Run Detail):** Can display per-test-case costs
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3. **TraceMind UI Screen 4 (Trace Detail):** Can show per-span LLM call costs
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4. **Cost Comparison:** Users can compare models by actual LLM API/inference costs
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5. **Complete Cost Picture:** Combines LLM cost (from traces) + GPU power cost (from metrics)
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## Testing
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```bash
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# Run evaluation with cost tracking
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cd SMOLTRACE
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smoltrace-eval \
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--model openai/gpt-4 \
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--provider litellm \
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--agent-type tool \
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--enable-otel \
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--output-format json \
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--output-dir test_output
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# Check traces for cost
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cat test_output/*/traces.json | jq '.[] | {trace_id, total_cost_usd, spans: [.spans[] | select(.attributes."gen_ai.usage.cost.total" != null) | {name, cost: .attributes."gen_ai.usage.cost.total"}]}'
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```
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Expected output should show:
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- `total_cost_usd` > 0
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- Spans with `gen_ai.usage.cost.total` attributes
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## Summary
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✅ **Root cause identified:** Span processor ordering prevented cost enrichment before export
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✅ **Fix implemented:** Added `CostEnrichmentSpanProcessor` before `SimpleSpanProcessor`
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✅ **Verified:** Processor order confirmed correct in setup
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✅ **Impact:** All datasets (traces, results, leaderboard) now have accurate LLM cost tracking
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**Next Steps:**
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- Run full evaluation to confirm cost appears in generated datasets
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- Update changelog and documentation
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- Commit changes
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## Files Modified
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1. `smoltrace/otel.py` - Fixed span processor ordering
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2. `COST_TRACKING_FIX_SUMMARY.md` - This file
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## Related Issues
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- Metrics aggregation fix (completed 2025-10-27): CO2 and power cost now in leaderboard
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- This fix: LLM usage cost now captured in traces dataset
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- Combined: Complete cost tracking (LLM + GPU) across all datasets

‎changelog.md‎

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- Verified with real evaluation: kshitijthakkar/smoltrace-metrics-20251027_180902
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- Dataset contains 11 rows × 13 columns with all 7 metrics
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### Fixed - LLM Cost Tracking in Traces Dataset (2025-10-27)
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**Critical: Cost Attributes Now Captured in Spans**
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- **Root Cause:** Span processor ordering prevented cost enrichment before export
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- `SimpleSpanProcessor` was added BEFORE `CostEnrichmentSpanProcessor`
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- Spans were exported WITHOUT cost attributes
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- Result: `total_cost_usd: 0.0` in traces dataset despite token counts being present
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- **Solution:** Reordered span processors in `setup_inmemory_otel()`
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- `CostEnrichmentSpanProcessor` now added FIRST
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- `SimpleSpanProcessor` added SECOND (exports spans AFTER cost enrichment)
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- genai_otel's cost calculation now runs before span export
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- **Impact:** Traces dataset now includes accurate LLM usage costs
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- Span attributes include `gen_ai.usage.cost.total`
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- Trace-level `total_cost_usd` properly aggregated from span costs
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- Enables cost tracking for API models (OpenAI, Anthropic, etc.) and local models
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**Technical Details:**
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- Added `CostEnrichmentSpanProcessor` from genai_otel before `SimpleSpanProcessor`
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- genai_otel's processor extracts model name, token counts, and calculates cost
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- Cost enrichment happens in `on_end()` callback before export
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- Works for all OpenInference-instrumented spans (smolagents, litellm, mcp)
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**Files Modified:**
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- `smoltrace/otel.py` - Fixed span processor ordering (lines 604-623)
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- `COST_TRACKING_FIX_SUMMARY.md` - Complete fix documentation
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**Testing:**
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- Verified processor order: CostEnrichmentSpanProcessor → SimpleSpanProcessor
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- Setup logs confirm: "[OK] CostEnrichmentSpanProcessor added"
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- Awaiting evaluation run to confirm cost in traces dataset
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### Fixed - TraceMind UI Compatibility (2025-10-27)
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**Critical Dataset Structure Fixes:**

‎smoltrace/otel.py‎

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def export(self, spans):
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for span in spans:
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self._spans.append(self._to_dict(span))
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span_dict = self._to_dict(span)
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self._spans.append(span_dict)
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return SpanExportResult.SUCCESS
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def shutdown(self):
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return self._spans
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def _to_dict(self, span):
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# Map status code from numeric to string for UI compatibility
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status_code = None
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if hasattr(span.status, "status_code"):
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code_value = span.status.status_code.value
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# Map: 0=UNSET, 1=OK, 2=ERROR
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status_map = {0: "UNSET", 1: "OK", 2: "ERROR"}
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status_code = status_map.get(code_value, "UNKNOWN")
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# Clean up span kind - remove "SpanKind." prefix
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kind_str = str(span.kind)
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if kind_str.startswith("SpanKind."):
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kind_str = kind_str.replace("SpanKind.", "")
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d = {
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"trace_id": hex(span.get_span_context().trace_id),
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"span_id": hex(span.get_span_context().span_id),
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for e in span.events
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],
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"status": {
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"code": (
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span.status.status_code.value if hasattr(span.status, "status_code") else None
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),
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"code": status_code, # Use string code ("OK", "ERROR", "UNSET")
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"description": (
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span.status.description if hasattr(span.status, "description") else None
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),
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},
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"kind": str(span.kind),
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"kind": kind_str, # Cleaned kind without "SpanKind." prefix
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"resource": dict(span.resource.attributes) if span.resource else {},
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}
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# Enrich with genai-specific (from traces)
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# Set up TracerProvider with resource
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trace_provider = TracerProvider(resource=resource)
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# Add CostEnrichmentSpanProcessor FIRST (if available)
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# This ensures cost is calculated and added to spans BEFORE they're exported
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if GENAI_OTEL_AVAILABLE:
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try:
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from genai_otel.cost_enrichment_processor import CostEnrichmentSpanProcessor
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cost_processor = CostEnrichmentSpanProcessor()
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trace_provider.add_span_processor(cost_processor)
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print("[OK] CostEnrichmentSpanProcessor added")
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except Exception as e:
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print(f"[WARNING] Could not add CostEnrichmentSpanProcessor: {e}")
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# Then add our InMemorySpanExporter with SimpleSpanProcessor
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# This exports spans AFTER cost has been added
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span_exporter = InMemorySpanExporter()
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trace_provider.add_span_processor(SimpleSpanProcessor(span_exporter))
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trace.set_tracer_provider(trace_provider)

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