fix(mistral): drop eager response serialization, use allowlist metadata pass-through#604
Merged
Abhijeet Prasad (AbhiPrasad) merged 1 commit intoJul 21, 2026
Conversation
…ta pass-through Align the Mistral integration with `.agents/skills/sdk-integrations/SKILL.md` following the same pattern as #594 (litellm) and #583 (anthropic): - **Response finalizers** no longer call `_normalized_mistral_dict(response)` to full-`model_dump` the response just to read a few fields. Read `choices` / `outputs` / `pages` / `usage` / `id` / `model` directly via the existing `_get_value` helper (dict-or-pydantic aware, handles Mistral's `Unset` sentinel). `bt_safe_deep_copy` in `logger.log_internal` already `model_dump`s pydantic values at log time. - **`_build_request_metadata`** stops walk-and-dumping every metadata value (`temperature`, `top_p`, `tools`, `response_format`, `stop`, …). These don't carry attachments; pass through and let bt_json handle it. - **Streaming aggregators** stop pre-dumping `usage` / `segments` into the intermediate dict; `_parse_usage_metrics` already accepts pydantic and the log-time deep-copy handles the output. - **Tool-span walkers** (`_completion_tool_calls`, `_conversation_tool_outputs`, `_log_completion_tool_spans`, `_log_conversation_tool_spans`) switched to `_get_value` so they work on raw pydantic responses. The multimodal walker is retained where attachment materialization matters: the `_start_span` input path, `_append_delta_content` / `_merge_tool_calls` streaming assembly, and per-field accumulators for conversation outputs. Metadata is still allowlist-per-surface — no changes there. Test updates (no new mocks, no cassette re-recording): - `test_wrappers_ignore_usage_when_response_normalization_fails` → `test_wrappers_read_usage_from_plain_python_responses`. The old test asserted metrics were dropped for plain-Python responses — that was a side-effect of `.model_dump()` failing on non-pydantic objects. The new behavior correctly reads usage via `getattr`; assert the positive. - `test_aggregate_completion_events_merges_tool_calls_and_content`: `aggregated["usage"]` is now the raw pydantic `UsageInfo` (dumps at log time, not in the aggregator); switched to `getattr(..., "total_tokens")`. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Abhijeet Prasad (AbhiPrasad)
approved these changes
Jul 21, 2026
Abhijeet Prasad (AbhiPrasad)
enabled auto-merge (squash)
July 21, 2026 00:19
Abhijeet Prasad (AbhiPrasad)
deleted the
fix/mistral-drop-eager-serialization
branch
July 21, 2026 00:25
This was referenced Jul 21, 2026
Abhijeet Prasad (AbhiPrasad)
pushed a commit
that referenced
this pull request
Jul 21, 2026
…ation (#608) ## Summary Aligns the OpenRouter integration with `.agents/skills/sdk-integrations/SKILL.md`, following #604 (mistral), #603 (livekit_agents), #594 (litellm), #593 (langchain), and #585 (claude_agent_sdk). Audit found two issues: - **Excess serialization.** `sanitize_openrouter_logged_value` called `bt_safe_deep_copy` on every span input, every kwargs dict, every response (for both output and metadata extraction), and every usage dict. Braintrust already runs `bt_safe_deep_copy` at log time in `Span.log_internal` (`logger.py:4699`), so every one of those was a duplicate walk. Dropped the wrapper; reads now go through a small `_get_field(obj, key)` helper (dict-or-attribute) and pydantic responses flow straight to `span.log(...)`. - **Denylist metadata → per-surface allowlist.** `_OMITTED_KEYS` was a small denylist (`execute`, `render`, `nextTurnParams`, `requireApproval`); the old `_build_openrouter_metadata` then dumped every *other* kwarg — including `messages`, `api_key`, `extra_headers`, and unknown kwargs — into `metadata`. Replaced with three request allowlists (`_CHAT_REQUEST_KEYS`, `_EMBEDDINGS_REQUEST_KEYS`, `_RESPONSES_REQUEST_KEYS`) and three response allowlists (`_CHAT_RESPONSE_KEYS`, `_EMBEDDINGS_RESPONSE_KEYS`, `_RESPONSES_RESPONSE_KEYS`), mirroring `litellm/_SAFE_METADATA_KEYS` and mistral's `_*_METADATA_KEYS` family. `is_byok` is still extracted from `usage` (it's still nested there). Also collapsed the three near-identical `_finalize_*_response` functions into one parameterized `_finalize_response(..., *, output, response_keys)`, and factored the shared model/provider stamping (`_stamp_model_and_provider`) used by both request and response metadata builders. Net: 1 file changed, +262 / −178 (net −0 after adding the allowlist tuples, but the tracing surface itself shrank meaningfully). ## Test plan - [x] **No new mocks/fakes.** All coverage stays on the existing `@pytest.mark.vcr` cassette-backed tests in `integrations/openrouter/test_openrouter.py` (chat sync/stream/async, embeddings, responses sync + async-stream, `setup_*_creates_spans`, `setup_*_is_idempotent`, auto_instrument subprocess). - [x] **No cassette re-recording.** HTTP behavior is unchanged; only in-process span shaping was touched. - [x] `cd py && nox -s "test_openrouter(latest)"` — 9/9 passed. - [x] `cd py && nox -s "test_openrouter(0.6.0)"` — 9/9 passed. - [x] `ruff check` + `ruff format --check` — clean. 🤖 Generated with [Claude Code](https://claude.com/claude-code) <!-- sfk:created-approved-by --> Created by abhijeet <!-- sfk:slack-thread --> [Slack thread](https://starfolkai.slack.com/archives/C0AQDETAVT3/p1784653510318699?thread_ts=1784653510.318699&cid=C0AQDETAVT3) Co-authored-by: Starfolk <noreply@starfolk.ai> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Abhijeet Prasad (AbhiPrasad)
pushed a commit
that referenced
this pull request
Jul 21, 2026
…ialization (#606) ## Summary Aligns the OpenAI integration with `.agents/skills/sdk-integrations/SKILL.md`, following the same pattern as #604 (mistral), #594 (litellm), #603 (livekit), and #583 (anthropic). Audit turned up two issues: - **Denylist metadata pass-through (real leak vector).** Every `_parse_params` copy (`ChatCompletionWrapper`, `ResponseWrapper`, `BaseWrapper` for Embedding/Moderation/Speech, `_AudioFileWrapper`, `_ImageBaseWrapper`) did `metadata: {**params, "provider": "openai"}` — every non-input request kwarg landed in span metadata. `ResponseWrapper._parse_event_from_result` did the same on the response side (`{k: v for k, v in result.items() if k not in ["output", "usage"]}`). That flowed `extra_headers`, `extra_query`, `extra_body`, user-provided Responses `metadata`, `user`, `safety_identifier`, `prompt_cache_key`, and anything OpenAI adds in future SDK versions straight into telemetry. Three tests actively ratified the header leak. Replaced with per-surface allowlist tuples plus a shared `_filter_metadata` helper that drops `NOT_GIVEN`/`Omit` sentinels and serializes `response_format` inline. Mirrors Anthropic's `METADATA_PARAMS`. - **Eager response serialization.** `_try_to_dict(raw_response)` was full-dumping every non-streaming Chat/Response API response just to read `usage` + `choices`/`output` — `bt_safe_deep_copy` already dumps at log time. Same fix pattern the mistral/litellm/anthropic PRs used: reads via `getattr` through a small `_get_attr` helper, plus a narrow `_choices_output` that dumps only `choices` (needed for the audio-attachment walker in `_process_attachments_in_chat_output`). `_parse_event_from_result` and `_extract_moderation_metadata` were made dict-or-object aware. Streaming paths still pre-dump chunks via `_try_to_dict(item)` because the aggregator reads deeply nested delta fields — that's not the "over-serialize" case the SKILL warns about. ## Note on `moderation` Added to both chat + responses request allowlists and the responses result allowlist. It's a Braintrust-proxy request parameter (`{"model": "omni-moderation-latest"}`) that deep-merges with the response's `moderation` object (`{"input": ..., "output": ...}`) at log time via `merge_dicts`. The two existing `*_inline_moderation_metadata` tests rely on this merge to see `logged_moderation["model"]`. ## Test plan - [x] **No new mocks/fakes.** All provider-behavior coverage stays on the existing `@pytest.mark.vcr` cassette-backed tests. - [x] **No cassette re-recording.** HTTP behavior unchanged; only in-process span shaping was touched. - [x] `nox -s "test_openai(latest)"` — 76/76 pass across `test_openai.py` (70), `test_openai_ddtrace.py` (3), `test_openai_openrouter_gateway.py` (3) - [x] `nox -s "test_openai(1.92.0)"`, `test_openai(1.77.0)`, `test_openai(1.71.0)` — all green - [x] `nox -s "test_openai_http2_streaming(latest)"` — 3/3 - [x] `nox -s "test_btx_openai(latest)"` — 5/5 - [x] `nox -s "test_openai_agents(latest)"` — 7/7 - [x] `ruff check` + `ruff format --check` on touched files — clean Three tests updated: assertions that expected `metadata["extra_headers"]["X-Stainless-Helper-Method"] == "chat.completions.stream"` flipped to `"extra_headers" not in span["metadata"]` — pins the specific leak vector the fix closes. 🤖 Generated with [Claude Code](https://claude.com/claude-code) <!-- sfk:created-approved-by --> Created by abhijeet <!-- sfk:slack-thread --> [Slack thread](https://starfolkai.slack.com/archives/C0AQDETAVT3/p1784593895623669?thread_ts=1784593895.623669&cid=C0AQDETAVT3) --------- Co-authored-by: Starfolk <noreply@starfolk.ai> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This was referenced Jul 21, 2026
Abhijeet Prasad (AbhiPrasad)
pushed a commit
that referenced
this pull request
Jul 21, 2026
…reads (#612) ## Summary Aligns the Strands integration with `.agents/skills/sdk-integrations/SKILL.md`, following the pattern of #606 (openai), #604 (mistral), #603 (livekit), #594 (litellm), #583 (anthropic). Audit turned up several issues: - **Missing span_origin instrumentation name.** Every other integration has `_INSTRUMENTATION = "<provider>-auto"` + a module-level `start_span` wrapper; strands was the only one whose spans lacked `context.span_origin.instrumentation.name`. Added the standard wrapper and pass `internal={"instrumentation": _INSTRUMENTATION}` explicitly through the nested `parent.start_span(...)` path, which doesn't route through the module wrapper. - **Denylist metrics extraction (real leak vector).** `_end_model_invoke_span_wrapper` was doing `{k: v for k, v in metrics.items() if _is_supported_metric_value(v)}` — every numeric key strands emits (present + future) flowed into the span's top-level `metrics` bag. Replaced with an explicit allowlist (`latencyMs`, `timeToFirstByteMs`). Since neither key is spec-listed, they land under `metadata.strands_metrics` rather than top-level `metrics`. - **Silently-broken agent metadata extraction.** `_agent_metrics_and_metadata` did `metrics = getattr(result, "metrics"); if not isinstance(metrics, dict): return {}, {}` — but `AgentResult.metrics` is an `EventLoopMetrics` **dataclass**, so the guard discarded everything. Renamed to `_agent_metadata_from_result` and read `cycle_count` / `accumulated_usage` / `accumulated_metrics` off the dataclass through a single `_pick_numeric(source, keys)` allowlist helper. Moved `cycles` from `metrics` to `metadata` (not a spec metric key). - **Positional-arg reads.** `_start_agent_span_wrapper` / `_start_model_invoke_span_wrapper` were `kwargs.get("tools")` / `kwargs.get("system_prompt")` etc. Strands' signatures put those at fixed positional slots — switched to `_arg(args, kwargs, N, name)` so positional callers work. - **Simplifications (via `/simplify`):** collapsed twin allowlist helpers into `_pick_numeric`; collapsed the parent-vs-module `if/else` in `_start_span_for_otel`; replaced the `_bt_parent_otel_span` metadata back-channel with a direct `parent_otel_span=` kwarg; dropped the now-orphan `metrics=` parameter from `_end_span_for_otel`; trimmed the verbose `wrap_strands_tracer` and `_InvalidOtelSpanKey` docstrings. ## Known SKILL gaps NOT fixed here Each deserves its own PR/discussion — flagging so they don't get lost: 1. **`metadata.provider` on LLM spans.** Strands' `Tracer` only receives `model_id`, not the model class — provider inference would require brittle id-pattern matching. 2. **Tokens under `metadata.strands_usage` rather than `metrics.tokens` / `prompt_tokens` / `completion_tokens`.** Fixing correctly means deciding whether model-invoke should stay typed `llm` at all — Strands' `OpenAIModel` / `AnthropicModel` delegate to the underlying provider SDK, which per the SKILL's "framework llm-like spans that delegate" rule should NOT be typed `llm`. 3. **No `test_auto_strands.py` subprocess auto-instrument test.** Strands is wired into `auto.py` but lacks the subprocess parity test other integrations have. ## Test plan - [x] **No new mocks/fakes.** Existing cassette-backed VCR test (`test_strands_openai_agent_traces_native_otel_lifecycle`) covers the behavior; added a `span_origin.instrumentation.name == "strands-auto"` assertion on every emitted span. - [x] **No cassette re-recording.** HTTP behavior is unchanged; only in-process span shaping was touched. - [x] `cd py && nox -s "test_strands(latest)"` — 2/2 pass - [x] `cd py && nox -s "test_strands(1.20.0)"` — 2/2 pass - [x] `ruff check` + `ruff format --check` on touched files — clean - [x] `nox -s pylint` — clean 🤖 Generated with [Claude Code](https://claude.com/claude-code) <!-- sfk:created-approved-by --> Created by abhijeet <!-- sfk:slack-thread --> [Slack thread](https://starfolkai.slack.com/archives/C0AQDETAVT3/p1784659948425149?thread_ts=1784659948.425149&cid=C0AQDETAVT3) Co-authored-by: Starfolk <noreply@starfolk.ai> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Abhijeet Prasad (AbhiPrasad)
pushed a commit
that referenced
this pull request
Jul 21, 2026
…eshape (#610) ## Summary Aligns the pydantic_ai integration with `.agents/skills/sdk-integrations/SKILL.md`, following the same pattern as #606 (openai), #608 (openrouter), and #604/#603/#594 (anthropic/livekit/litellm/mistral). Audit turned up two issues: - **Denylist metadata pass-through (real leak vector).** `_build_agent_input_and_metadata` and `_build_direct_model_input_and_metadata` did `for key, value in kwargs.items(): if key not in [...]: input_data[key] = value` — every non-`deps` / non-`{model,messages}` kwarg landed in span input. That flowed `usage` (a mutable counter), `event_stream_handler` (a callable), `infer_name`, `instrument`, and anything pydantic_ai adds in future SDK versions straight into telemetry. `deps` (user's app-level container — commonly holds API keys / DB connections) was the sole excluded key on the agent path; on the direct-model path there was no exclusion at all. Replaced with per-surface allowlist tuples (`_AGENT_INPUT_ALLOWLIST`, `_DIRECT_MODEL_INPUT_ALLOWLIST`) covering the known kwargs across `Agent.run` / `run_sync` / `run_stream` / `run_stream_events` / `to_cli_sync` and `direct.model_request*`. Explicitly excludes `deps`, `usage`, `event_stream_handler`, `infer_name`, `instrument`. - **Eager message reshaping dropping fields.** `_shape_message` / `_shape_content_part` / `_shape_model_response` reshaped every message into shallow dicts via a hard-coded field allowlist (`_MESSAGE_FIELDS`, `_PART_FIELDS`, `_RESPONSE_FIELDS`) even when no binary content needed materialization. That dropped real pydantic_ai v2 fields — `instructions`, `run_id`, `conversation_id`, `metadata`, `state`, `provider_details`, `outcome`, ... — and burned CPU rebuilding dicts that `bt_safe_deep_copy` (which already handles dataclasses + Pydantic models) would produce anyway at log time. Added `_has_binary_leaf` walker; the four shape helpers now short-circuit to the raw object when no binary is present. Reshape (and its field allowlist) only runs when a binary attachment actually needs materialization. Also: - Extracted `_shape_toolset(ts)` from a nested 20-line block inside `_build_agent_input_and_metadata`. - Trimmed docstrings/comments that just restated the helper name. Kept the ones explaining non-obvious *why* (portal-thread context propagation, wrapper-vs-leaf token ownership, 1.78.0 ToolManager alias, `_system_prompts` private-API access). - Hoisted `import inspect` from inside `_shape_type` to module top. ## Test plan - [x] **No new mocks/fakes.** All provider-behavior coverage stays on the existing `@pytest.mark.vcr` cassette-backed tests. - [x] **No cassette re-recording.** HTTP behavior unchanged; only in-process input/shape logic was touched. - [x] `nox -s "test_pydantic_ai_integration(latest)"` — 68/68 pass (`pydantic-ai==2.13.0`) - [x] `nox -s "test_pydantic_ai_integration(1.10.0)"` — 68/68 pass (min-supported matrix version) - [x] `nox -s "test_pydantic_ai_wrap_openai(latest)"` — green - [x] `nox -s "test_pydantic_ai_logfire(latest)"` — 1/1 pass Two new tests pin the security invariant: - `test_agent_input_kwargs_are_allowlisted` — asserts `deps` / `usage` / `event_stream_handler` / `infer_name` never land in span input; allowlisted kwargs (`instructions`, `usage_limits`, `retries`, `conversation_id`, `metadata`) do. - `test_direct_model_request_kwargs_are_allowlisted` — asserts `instrument` never leaks; `model_settings` / `model_request_parameters` do. One existing test replaced: `test_v2_message_and_response_fields_are_shaped` → `test_shape_message_and_response_pass_through_when_no_binary` — the old test was locking in the reshape that was losing v2 fields. 🤖 Generated with [Claude Code](https://claude.com/claude-code) <!-- sfk:created-approved-by --> Created by abhijeet <!-- sfk:slack-thread --> [Slack thread](https://starfolkai.slack.com/archives/C0AQDETAVT3/p1784659060950489?thread_ts=1784659060.950489&cid=C0AQDETAVT3) --------- Co-authored-by: Starfolk <noreply@starfolk.ai> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
Aligns the Mistral integration with
.agents/skills/sdk-integrations/SKILL.md, following the same pattern as #594 (litellm) and #583 (anthropic). Audit turned up two issues:Excess serialization.
_normalize_mistral_multimodal_value(which recursively callsvalue.model_dump(mode="python", by_alias=True)) was invoked 25 times acrosstracing.py. Two sites did real waste:_finalize_completion_response,_finalize_conversation_response,_finalize_ocr_response,_finalize_embeddings_response) full-dumped the response just to read a handful of fields (id,model,choices/outputs/pages,usage)._build_request_metadatawalk-and-dumped every metadata value (temperature,top_p,tools,response_format,stop, …) — none of which carry attachments.Both are redundant:
bt_safe_deep_copyinlogger.log_internalalreadymodel_dumps pydantic values at log time. Replaced with attribute reads through the existing_get_valuehelper (already dict-or-pydantic aware and handles Mistral'sUnsetsentinel — no new helper needed).Aggregators.
_aggregate_completion_events/_aggregate_conversation_events/_aggregate_transcription_events/_aggregate_speech_eventspre-dumpedusage/segmentsinto the intermediate dict._parse_usage_metricsalready accepts pydantic, andbt_safe_deep_copyhandles the output. Dropped.Tool-span walkers.
_completion_tool_calls,_conversation_tool_outputs,_log_completion_tool_spans,_log_conversation_tool_spansswitched to_get_valueso they walk raw pydantic responses instead of assuming pre-dumped dict shape.Multimodal walker retained where attachment materialization matters (
_start_spaninput path,_append_delta_content/_merge_tool_callsstreaming assembly, per-field conversation-output accumulators).Metadata is still allowlist-per-surface — no changes to what fields we capture. Comments were not excessive; nothing to trim.
Net: −36 LOC in
tracing.py, one dead helper file removed (_response_data_to_metadata,_conversation_response_data_to_metadata,_conversation_outputs_data,_ocr_output_datacollapsed into the pydantic-aware equivalents).Test plan
_PlainResponsefor the plain-Python usage path, and lambda fail-injectors for error-propagation tests) fall under the SKILL's "narrow error injection / provider-independent helpers" carve-out. All provider-behavior coverage stays on the 30+@pytest.mark.vcrcassette-backed tests.cd py && nox -s "test_mistral(latest)"— 45/45 passed.cd py && nox -s "test_mistral(1.12.4)"— 43/43 passed (2 pre-existing skips for speech API which doesn't exist on 1.12.4).ruff check+ruff format --checkon touched files — clean.Two existing unit tests were updated because their assertions hinged on the old eager-serialization behavior:
test_wrappers_ignore_usage_when_response_normalization_fails→test_wrappers_read_usage_from_plain_python_responses. The old test asserted metrics were dropped for plain-Python responses — that only happened because.model_dump()failed on non-pydantic objects and we bailed out. The new code correctly readsusageviagetattr; assertion is now positive (metrics are present).test_aggregate_completion_events_merges_tool_calls_and_content:aggregated["usage"]is now the raw pydanticUsageInfo(dumps at log time, not in the aggregator); switched togetattr(..., "total_tokens").🤖 Generated with Claude Code
Created by abhijeet
Slack thread