5ed7ec8511
* fix(lens): price agent traces by joining gen_ai.response.id to spend logs Trace spend now joins each model call to spend_logs on one key: the span's response id (gen_ai.response.id or the id the normalizers read from OpenInference/LangChain output) against spend_logs.response_id or the upstream id embedded in a managed resp_ id. The litellm.call_id and traceparent transport join paths and the per-row ownership gate are removed; the spend SQL still restricts rows to what the reader can see. A run with some unpriced calls now reports the sum of its priced calls plus priced_calls, instead of an unknown total. * test(lens): cover response id spend join and partial trace totals * chore(lens): regenerate trace types for priced_calls * feat(lens): show partial run cost as a lower bound with priced call count * fix(lens): treat litellm.call_id as the same assigned call id for spend joins The id LiteLLM assigned to a call is either the response id it returned (gen_ai.response.id -> spend_logs.response_id) or its gateway call id (litellm.call_id -> spend_logs.litellm_call_id). Both are exact ids the gateway mints and logs, so the join stays one rule. Transport span matching and the ownership gate stay removed. * test(lens): cover litellm.call_id spend joins and restore captured totals * feat(lens): link each priced model call to its spend log Spans gain spend_log_request_id, the spend_logs.request_id the call was priced from, and spend_match, which says whether a model call matched or why not (no assigned id on the span, no spend log with that id, or an ambiguous match). A model call span is priced from the same ids as the run total, so its cost and the total agree. * test(lens): cover spend log links on model call spans * chore(lens): regenerate trace types for spend log links * feat(lens): open the matched spend log from an LLM step An LLM step's header now shows a Spend log chip with the matched request id and cost; clicking it opens the request log drawer over the run, fetched by the exact spend_logs.request_id instead of the span's own response id. Unpriced steps say why (no assigned id on the span, or no spend log with it). Tree rows show each model call's cost, and a partial run cost shows its priced call count inline. * test(lens): cover the spend log link and unmatched cost reasons * feat(lens): show the spend log link as a bordered LiteLLM Spend Log button * feat(lens): add a back link from the spend log drawer to the agent trace * feat(lens): label the spend log back link Back to Lens trace with the Lens icon * fix(lens): ignore assigned ids that name no spend log when pricing a call An id that names no row no longer vetoes the call, so a span carrying both a response id and a call id still prices from a spend row logged before litellm_call_id existed. An id naming two or more rows makes the call ambiguous, and the match reason comes from the same per-id result, so a single matched row with no cost is reported as matched. * fix(lens): price a trace only from spend logs in its own team A reader with several teams could see the same assigned id in another team's spend log; only rows from the trace's team now price it. The user and key ownership gate stays removed. * perf(lens): resolve each model call's spend once per trace Model call matches are computed once when the trace is resolved and looked up by span index, instead of scanning the model call list for every span and walking the graph again for spans, agents and the run total. * fix(lens): hide a step's Cost fact only when its spend log link shows the cost * chore(lens): drop narrative doc comments from the spend join * fix(lens): price a model call only when its ids agree on one spend log per span * fix(lens): keep pricing spend logs written before litellm_call_id by their request id * fix(lens): price every attempt a model call's ids name when they agree |
||
|---|---|---|
| .. | ||
| schemas | ||
| templates | ||
| config.json | ||
| README.md | ||
Run uv run scripts/generate_trace_types.py from the repository root to export Rust schemas and regenerate the Python trace contracts. Run uv run scripts/generate_trace_types.py --check to compare fresh output with the committed schemas and Python files
The script pins datamodel-code-generator in its inline dependency metadata. Rust uses the workspace's locked Schemars version through each owning crate's optional schema feature. Neither tool is a Python runtime dependency
The litellm-traces Rust request types own the generated request models in litellm/rust_bridge/trace/generated/requests.py. The GET routes bind their query parameters directly to the generated models. GET request types allow unknown fields because existing clients' unknown query parameters are ignored. The SQL body model forbids extra fields
Each crate exports its own roots using JSON Schema 2020-12. Request parameters use Schemars' deserialization contract and carry only explicitly declared constraints. Their schemas skip the integer-bounds transform because it would add i64 bounds to start_ms and end_ms, narrowing what Python accepts, and replace page_size's explicit 1..500 range with 0..65535. Trace views and query help use the serialization contract. Lens rows use their ClickHouse deserialization schemas, including quoted numbers and numeric boolean flags
The templates preserve tuple conversion, immutable tuple defaults, and bounded ReadOnly TypedDict fields. Pydantic models use the generator's frozen-model option and each schema's extra-field policy. ClickHouse numeric schemas select bounded, normalized Python scalar types through schema metadata consumed by the model template
Changing the public request contract requires a separate behavior-change PR
Edit the owning Rust contract, schema annotation, or generation configuration, then regenerate. Never edit litellm/rust_bridge/trace/generated/ manually. responses.py holds the generated SQL response, and queries.py keeps the ClickHouse envelope as an internal validator