Enable deployment_affinity, responses_api_deployment_check, and session_affinity to be configured per model group via router_settings.model_group_affinity_config, falling back to global settings for unconfigured groups.
- Add model_group_affinity_config parameter to Router and DeploymentAffinityCheck
- Add _get_effective_flags helper to resolve flags per model group
- Update async_filter_deployments and async_pre_call_deployment_hook to use per-group config
- Add 4 comprehensive tests covering per-group config, fallback, and override scenarios
This allows fine-grained control of affinity behavior across model groups, e.g., enabling stickiness only for cross-provider deployments while leaving other groups free to load-balance.
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Previously the test called common_processing_pre_call_logic in isolation,
making generate_polling_id.assert_not_called() vacuously true. Now the test
calls responses_api() end-to-end so it actually verifies that a rate-limited
request never receives a polling ID.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Guard logging_obj for None when skip_pre_call_logic=True: raise ValueError
if litellm_logging_obj not in data, preventing AttributeError downstream
- Add model=None to common_processing_pre_call_logic call in endpoints.py
to match style of other call sites
- Add test verifying rate-limited request never receives polling ID
Move pre-call checks (rate limits, guardrails, budget) to run BEFORE
polling ID creation in the background streaming flow. This prevents the
edge case where a rate-limited request receives a polling ID that
immediately fails.
Changes:
- Add skip_pre_call_logic parameter to base_process_llm_request to allow
skipping pre-call checks (avoiding double-counting of RPM/parallel requests)
- Run common_processing_pre_call_logic before generating polling ID in the
responses API endpoint. If rate limits/guardrails fail, return error
immediately without creating a polling ID
- Background streaming task passes skip_pre_call_logic=True to avoid re-running
pre-call checks that were already done before polling ID creation
- Add tests verifying skip_pre_call_logic parameter works correctly
Fixes the edge case where polling_via_cache would return a polling ID
for a request that immediately fails due to rate limiting.
- Change chunk["id"] to chunk.get("id") for compatibility with MiniMax
- ModelResponseStream auto-generates id when None is passed
- Add regression test test_chunk_parser_without_id_field
Replace bare _get_deployment_default_tpm/rpm_limit calls in the
async_log_success_event condition with get_key_model_tpm/rpm_limit
(model_name=model_group). The higher-level getters short-circuit on
key/team metadata hits before ever reaching the router, so requests
that don't use deployment defaults incur no extra router lookup. Remove
the now-unused bare helper imports.
Also fix invalid `int = None` type hints in test helper signatures
to `Optional[int] = None`.
Co-Authored-By: Claude (claude-sonnet-4-6) <noreply@anthropic.com>
- Use min() across all matching deployments instead of first-wins when
resolving default_api_key_tpm/rpm_limit for a model group, so
load-balanced setups with different per-deployment limits always apply
the most conservative value
- Replace the global SensitiveDataMasker non_sensitive_overrides change
with a targeted excluded_keys set at the remove_sensitive_info_from_deployment
call site, avoiding unintended suppression of other fields
- Update the v1 parallel request limiter to pass model_name to
get_key_model_tpm/rpm_limit so deployment defaults apply there too
- Add 4 tests covering multi-deployment min semantics
Co-Authored-By: Claude (claude-sonnet-4-6) <noreply@anthropic.com>
Adds `default_api_key_tpm_limit` and `default_api_key_rpm_limit` to
`GenericLiteLLMParams` so operators can set per-deployment rate limit
defaults in config.yaml. When a key has no model-specific tpm/rpm limit
configured, the proxy falls back to these deployment defaults (Case 2 in
spec). Key-level limits always take priority (Case 1).
- Extends `get_key_model_tpm_limit` / `get_key_model_rpm_limit` with a
`model_name` param and a priority-4 deployment-default fallback
- Passes `model_name=requested_model` in the parallel request limiter so
the fallback is triggered at enforcement time
- Adds `"limit"` to `SensitiveDataMasker` non-sensitive overrides so
`*_limit` fields are not masked in `/model/info` responses
- Adds 17 unit tests covering both spec cases and the `/model/info` path
Co-Authored-By: Claude (claude-sonnet-4-6) <noreply@anthropic.com>
- Only remove wildcard path from openai_routes when the route entry has
type="subpath", avoiding accidental removal when two endpoints share
the same base path but differ in include_subpath
- Clean up _registered_pass_through_routes in the test finally block to
prevent stale entries from polluting subsequent tests on failure
- Add dedup guard for base path registration (prevents unbounded list
growth on config reload)
- Clean up base path and wildcard path from openai_routes when an
endpoint is removed via remove_endpoint_routes
- Rewrite test to exercise initialize_pass_through_endpoints directly,
covering registration, dedup on reload, and cleanup on removal
When a pass-through endpoint has both auth=true and include_subpath=true,
non-admin users got 401 errors on subpath requests because only the base
path was registered in openai_routes. Now the wildcard path is also
registered so the auth check recognizes subpath requests as LLM API routes.
Also fixes pre-existing pyright error where logging_obj was possibly
unbound in the except block.
Add support for {"location": "tool_config"} in cache_control_injection_points,
which appends a cachePoint block to the Bedrock Converse toolConfig.tools array.
This enables prompt caching of tool definitions on Bedrock Claude models.
Also update the cache control hook to pass through non-message injection points
to provider-specific handling instead of silently dropping them.
Fixes#21969
OpenAI strict mode requires both additionalProperties:false AND all
property keys in required. Without required, OpenAI rejects the schema
even with additionalProperties:false set.
Enables Gemini 3+ models to combine built-in tools (Google Search, etc.)
with custom functions via `include_server_side_tool_invocations=True`.
Server-side invocations are surfaced in provider_specific_fields and
automatically re-injected on subsequent turns for multi-turn coherence.
Closes#24047
When translating Anthropic output_format to OpenAI response_format,
the adapter sets strict: true but didn't add additionalProperties: false,
which OpenAI requires at every object nesting level. This caused
BadRequestError for structured output requests routed to OpenAI models.
Fixes#20997
The check `content.get("thinking", None) is not None` incorrectly
drops thinking blocks when the `thinking` key is explicitly null or
absent. Changed to `content.get("type") == "thinking"` to match
the fix already applied in the experimental pass-through path (PR #15501).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Deduplicate: update_key_fn now delegates to _get_and_validate_existing_key()
instead of inlining its own copy of the lookup logic
- Use _hash_token_if_needed (already imported at module level) instead of
inline `from proxy_server import hash_token` + manual conditional
- Fix stale docstring: _get_and_validate_existing_key raises ProxyException,
not HTTPException
- Add unit test: test_update_key_nonexistent_key_returns_404
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Accept theirs for UI test file conflicts (not related to our changes).
Our key_management_endpoints.py merged cleanly.
Co-authored-by: yuneng-jiang <yuneng-jiang@users.noreply.github.com>
Incorporate new _check_key_admin_access() calls from the base branch
into block_key/unblock_key alongside our existence-check fix.
Update test mocks: replace references to removed get_key_object and
_cache_key_object with _delete_cache_key_object in both the shared
_setup_block_unblock_mocks helper and individual test functions.
Co-authored-by: yuneng-jiang <yuneng-jiang@users.noreply.github.com>
* feat(xai): add grok-4.20 beta 2 models with pricing (#23900)
Add three grok-4.20 beta 2 model variants from xAI:
- grok-4.20-multi-agent-beta-0309 (reasoning + multi-agent)
- grok-4.20-beta-0309-reasoning (reasoning)
- grok-4.20-beta-0309-non-reasoning
Pricing (from https://docs.x.ai/docs/models):
- Input: $2.00/1M tokens ($0.20/1M cached)
- Output: $6.00/1M tokens
- Context: 2M tokens
All variants support vision, function calling, tool choice, and web search.
Closes LIT-2171
* docs: add Quick Install section for litellm --setup wizard (#23905)
* docs: add Quick Install section for litellm --setup wizard
* docs: clarify setup wizard is for local/beginner use
* feat(setup): interactive setup wizard + install.sh (#23644)
* feat(setup): add interactive setup wizard + install.sh
Adds `litellm --setup` — a Claude Code-style TUI onboarding wizard that
guides users through provider selection, API key entry, and proxy config
generation, then optionally starts the proxy immediately.
- litellm/setup_wizard.py: wizard with ASCII art, numbered provider menu
(OpenAI, Anthropic, Azure, Gemini, Bedrock, Ollama), API key prompts,
port/master-key config, and litellm_config.yaml generation
- litellm/proxy/proxy_cli.py: adds --setup flag that invokes the wizard
- scripts/install.sh: curl-installable script (detect OS/Python, pip
install litellm[proxy], launch wizard)
Usage:
curl -fsSL https://raw.githubusercontent.com/BerriAI/litellm/main/scripts/install.sh | sh
litellm --setup
* fix(install.sh): remove orange color, add LITELLM_BRANCH env var for branch installs
* fix(install.sh): install from git branch so --setup is available for QA
* fix(install.sh): remove stale LITELLM_BRANCH reference that caused unbound variable error
* fix(install.sh): force-reinstall from git to bypass cached PyPI version
* fix(install.sh): show pip progress bar during install
* fix(install.sh): always launch wizard via $PYTHON_BIN -m litellm, not PATH binary
* fix(install.sh): use litellm.proxy.proxy_cli module (no __main__.py exists)
* fix(install.sh): suppress RuntimeWarning from module invocation
* fix(install.sh): use Python bin-dir litellm binary to avoid CWD sys.path shadowing
* fix(install.sh): use sysconfig.get_path('scripts') to find pip-installed litellm binary
* fix(install.sh): redirect stdin from /dev/tty on exec so wizard gets terminal, not exhausted pipe
* fix(install.sh): warn about git clone duration, drop --no-cache-dir so re-runs are faster
* feat(setup_wizard): arrow-key selector, updated model names
* fix(setup_wizard): use sysconfig binary to start proxy, not python -m litellm
* feat(setup_wizard): credential validation after key entry + clear next-steps after proxy start
* style(install.sh): show git clone warning in blue
* refactor(setup_wizard): class with static methods, use check_valid_key from litellm.utils
* address greptile review: fix yaml escaping, port validation, display name collisions, tests
- setup_wizard.py: add _yaml_escape() for safe YAML embedding of API keys
- setup_wizard.py: add _styled_input() with readline ANSI ignore markers
- setup_wizard.py: change DIVIDER to _divider() fn to avoid import-time color capture
- setup_wizard.py: validate port range 1-65535, initialize before loop
- setup_wizard.py: qualify azure display names (azure-gpt-4o) to avoid collision with openai
- setup_wizard.py: work on env_copy in _build_config to avoid mutating caller's dict
- setup_wizard.py: skip model_list entries for providers with no credentials
- setup_wizard.py: prompt for azure deployment name
- setup_wizard.py: wrap os.execlp in try/except with friendly fallback
- setup_wizard.py: wrap config write in try/except OSError
- setup_wizard.py: fix _validate_and_report to use two print lines (no \r overwrite)
- setup_wizard.py: add .gitignore tip next to key storage notice
- setup_wizard.py: fix run_setup_wizard() return type annotation to None
- scripts/install.sh: drop pipefail (not supported by dash on Ubuntu when invoked as sh)
- scripts/install.sh: use litellm[proxy] from PyPI (not hardcoded dev branch)
- scripts/install.sh: guard /dev/tty read with -r check for Docker/CI compat
- scripts/install.sh: remove --force-reinstall to avoid downgrading dependencies
- tests/test_litellm/test_setup_wizard.py: 13 unit tests for _build_config and _yaml_escape
* style: black format setup_wizard.py
* fix: address remaining greptile issues - Windows compat, YAML quoting, credential flow
- guard termios/tty imports with try/except ImportError for Windows compat
- quote master_key as YAML double-quoted scalar (same as env vars)
- remove unused port param from _build_config signature
- _validate_and_report now returns the final key so re-entered creds are stored
- add test for master_key YAML quoting
* fix: add --port to suggested command, guard /dev/tty exec in install.sh
* fix: quote api_base in YAML, skip azure if no deployment, only redraw on state change
* fix: address greptile review comments
- _yaml_escape: add control character escaping (\n, \r, \t)
- test: fix tautological assertion in test_build_config_azure_no_deployment_skipped
- test: add tests for control character escaping in _yaml_escape
* feat(ui): remove Chat UI page link and banner from sidebar and playground (#23908)
* feat(guardrails): MCPJWTSigner - built-in guardrail for zero trust MCP auth (#23897)
* Allow pre_mcp_call guardrail hooks to mutate outbound MCP headers
* Enhance MCPServerManager to support hook-modified arguments and extra headers. Update tests to validate argument mutation and header injection behavior, including warnings for OpenAPI-backed servers when headers are present.
* Refactor MCPServerManager to raise HTTPException for extra headers in OpenAPI-backed servers. Update tests to reflect this change, ensuring proper exception handling instead of logging warnings.
* Allow pre_mcp_call guardrail hooks to mutate outbound MCP headers
* Enhance MCPServerManager to support hook-modified arguments and extra headers. Update tests to validate argument mutation and header injection behavior, including warnings for OpenAPI-backed servers when headers are present.
* Refactor MCPServerManager to raise HTTPException for extra headers in OpenAPI-backed servers. Update tests to reflect this change, ensuring proper exception handling instead of logging warnings.
* feat(guardrails): add MCPJWTSigner built-in guardrail for zero trust MCP auth
Signs outbound MCP tool calls with a LiteLLM-issued RS256 JWT so MCP servers
can trust a single signing authority instead of every upstream IdP.
Enable in config.yaml:
guardrails:
- guardrail_name: mcp-jwt-signer
litellm_params:
guardrail: mcp_jwt_signer
mode: pre_mcp_call
default_on: true
JWT carries sub (user_id), act.sub (team_id, RFC 8693), tool-level scope, iss,
aud, iat/exp/nbf. RSA-2048 keypair auto-generated at startup unless
MCP_JWT_SIGNING_KEY env var is set.
Adds /.well-known/jwks.json endpoint and jwks_uri to /.well-known/openid-configuration
so MCP servers can verify LiteLLM-issued tokens via OIDC discovery.
* Update MCPServerManager to raise HTTPException with status code 400 for extra headers in OpenAPI-backed servers. Adjust tests to verify the correct status code and exception message.
* fix: address P1 issues in MCPJWTSigner
- OpenAPI servers: warn + skip header injection instead of 500
- JWKS Cache-Control: 5min for auto-generated keys, 1h for persistent
- sub claim: fallback to apikey:{token_hash} for anonymous callers
- ttl_seconds: validate > 0 at init time
* docs: add MCP zero trust auth guide with architecture diagram
* docs: add FastMCP JWT verification guide to zero trust doc
* fix: address remaining Greptile review issues (round 2)
- mcp_server_manager: warn when hook Authorization overwrites existing header
- __init__: remove _mcp_jwt_signer_instance from __all__ (private internal)
- discoverable_endpoints: copy dict instead of mutating in-place on OIDC augmentation
- test docstring: reflect warn-and-continue behavior for OpenAPI servers
- test: update scope assertions for least-privilege (no mcp:tools/list on tool-call JWTs)
* fix: address Greptile round 3 feedback
- initialize_guardrail: validate mode='pre_mcp_call' at init time — misconfigured
mode silently bypasses JWT injection, which is a zero-trust bypass
- _build_claims: remove duplicate inline 'import re' (module-level import already present)
- _types.py: add TODO comment explaining jwt_claims is forward-compat plumbing
for a follow-up PR that will forward upstream IdP claims into outbound MCP JWTs
* feat(mcp_jwt_signer): add verify+re-sign, claim ops, two-token model, configurable scopes
Addresses all missing pieces from the scoping doc review:
FR-5 (Verify + re-sign): MCPJWTSigner now accepts access_token_discovery_uri
and token_introspection_endpoint. When set, the incoming Bearer token is
extracted from raw_headers (threaded through pre_call_tool_check), verified
against the IdP's JWKS (JWT) or introspected (opaque), and only re-signed if
valid. Falls back to user_api_key_dict.jwt_claims for LiteLLM JWT-auth mode.
FR-12 (Configurable end-user identity mapping): end_user_claim_sources
ordered list drives sub resolution — sources: token:<claim>, litellm:user_id,
litellm:email, litellm:end_user_id, litellm:team_id.
FR-13 (Claim operations): add_claims (insert-if-absent), set_claims (always
override), remove_claims (delete) applied in that order.
FR-14 (Two-token model): channel_token_audience + channel_token_ttl issue a
second JWT injected as x-mcp-channel-token: Bearer <token>.
FR-15 (Incoming claim validation): required_claims raises HTTP 403 when any
listed claim is absent; optional_claims passes listed claims from verified
token into the outbound JWT.
FR-9 (Debug headers): debug_headers: true emits x-litellm-mcp-debug with kid,
sub, iss, exp, scope.
FR-10 (Configurable scopes): allowed_scopes replaces auto-generation. Also
fixed: tool-call JWTs no longer grant mcp:tools/list (overpermission).
P1 fixes:
- proxy/utils.py: _convert_mcp_hook_response_to_kwargs merges rather than
replaces extra_headers, preserving headers from prior guardrails.
- mcp_server_manager.py: warns when hook injects Authorization alongside a
server-configured authentication_token (previously silent).
- mcp_server_manager.py: pre_call_tool_check now accepts raw_headers and
extracts incoming_bearer_token so FR-5 verification has the raw token.
- proxy/utils.py: remove stray inline import inspect inside loop (pre-existing
lint error, now cleaned up).
Tests: 43 passing (28 new tests covering all FR flags + P1 fixes).
* feat(mcp_jwt_signer): add verify+re-sign, claim ops, two-token model, configurable scopes (core)
Remaining files from the FR implementation:
mcp_jwt_signer.py — full rewrite with all new params:
FR-5: access_token_discovery_uri, token_introspection_endpoint,
verify_issuer, verify_audience + _verify_incoming_jwt(),
_introspect_opaque_token()
FR-12: end_user_claim_sources ordered resolution chain
FR-13: add_claims, set_claims, remove_claims
FR-14: channel_token_audience, channel_token_ttl → x-mcp-channel-token
FR-15: required_claims (raises 403), optional_claims (passthrough)
FR-9: debug_headers → x-litellm-mcp-debug
FR-10: allowed_scopes; tool-call JWTs no longer over-grant tools/list
mcp_server_manager.py:
- pre_call_tool_check gains raw_headers param to extract incoming_bearer_token
- Silent Authorization override warning fixed: now fires when server has
authentication_token AND hook injects Authorization
tests/test_mcp_jwt_signer.py:
28 new tests covering all FR flags + P1 fixes (43 total, all passing)
* fix(mcp_jwt_signer): address pre-landing review issues
- Remove stale TODO comment on UserAPIKeyAuth.jwt_claims — the field is
already populated and consumed by MCPJWTSigner in the same PR
- Fix _get_oidc_discovery to only cache the OIDC discovery doc when
jwks_uri is present; a malformed/empty doc now retries on the next
request instead of being permanently cached until proxy restart
- Add FR-5 test coverage for _fetch_jwks (cache hit/miss),
_get_oidc_discovery (cache/no-cache on bad doc), _verify_incoming_jwt
(valid token, expired token), _introspect_opaque_token (active,
inactive, no endpoint), and the end-to-end 401 hook path — 53 tests
total, all passing
* docs(mcp_zero_trust): rewrite as use-case guide covering all new JWT signer features
Add scenario-driven sections for each new config area:
- Verify+re-sign with Okta/Azure AD (access_token_discovery_uri,
end_user_claim_sources, token_introspection_endpoint)
- Enforcing caller attributes with required_claims / optional_claims
- Adding metadata via add_claims / set_claims / remove_claims
- Two-token model for AWS Bedrock AgentCore Gateway
(channel_token_audience / channel_token_ttl)
- Controlling scopes with allowed_scopes
- Debugging JWT rejections with debug_headers
Update JWT claims table to reflect configurable sub (end_user_claim_sources)
* fix(mcp_jwt_signer): wire all config.yaml params through initialize_guardrail
The factory was only passing issuer/audience/ttl_seconds to MCPJWTSigner.
All FR-5/9/10/12/13/14/15 params (access_token_discovery_uri,
end_user_claim_sources, add/set/remove_claims, channel_token_audience,
required/optional_claims, debug_headers, allowed_scopes, etc.) were
silently dropped, making every advertised advanced feature non-functional
when loaded from config.yaml.
Add regression test that asserts every param is wired through correctly.
* docs(mcp_zero_trust): add hero image
* docs(mcp_zero_trust): apply Linear-style edits
- Lead with the problem (unsigned direct calls bypass access controls)
- Shorter statement section headers instead of question-form headers
- Move diagram/OIDC discovery block after the reader is bought in
- Add 'read further only if you need to' callout after basic setup
- Two-token section now opens from the user problem not product jargon
- Add concrete 403 error response example in required_claims section
- Debug section opens from the symptom (MCP server returning 401)
- Lowercase claims reference header for consistency
* fix(mcp_jwt_signer): fix algorithm confusion attack + add OIDC discovery 24h TTL
- Remove alg from unverified JWT header; use signing_jwk.algorithm_name from JWKS key instead.
Reading alg from attacker-controlled headers enables alg:none / HS256 confusion attacks.
- Add _oidc_discovery_fetched_at timestamp and _OIDC_DISCOVERY_TTL = 86400 (24h).
Without a TTL the cached discovery doc never refreshes, so IdP key rotation is invisible.
---------
Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com>
* fix(ci): stabilize CI - formatting, type errors, test polling, security CVEs, router bug, batch resolution
Fix 1: Run Black formatter on 35 files
Fix 2: Fix MyPy type errors:
- setup_wizard.py: add type annotation for 'selected' set variable
- user_api_key_auth.py: remove redundant type annotation on jwt_claims reassignment
Fix 3: Fix spend accuracy test burst 2 polling to wait for expected total
spend instead of just 'any increase' from burst 2
Fix 4: Bump Next.js 16.1.6 -> 16.1.7 to fix CVE-2026-27978, CVE-2026-27979,
CVE-2026-27980, CVE-2026-29057
Fix 5: Fix router _pre_call_checks model variable being overwritten inside
loop, causing wrong model lookups on subsequent deployments. Use local
_deployment_model variable instead.
Fix 6: Add missing resolve_output_file_ids_to_unified call in batch retrieve
non-terminal-to-terminal path (matching the terminal path behavior)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* chore: regenerate poetry.lock to sync with pyproject.toml
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix: format merged files from main and regenerate poetry.lock
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(mypy): annotate jwt_claims as Optional[dict] to fix type incompatibility
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(ci): update router region test to use gpt-4.1-mini (fix flaky model lookup)
Replace deprecated gpt-3.5-turbo-1106 with gpt-4.1-mini + mock_response in
test_router_region_pre_call_check, following the same pattern used in commit
717d37cc5b for test_router_context_window_check_pre_call_check_out_group.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* ci: retry flaky logging_testing (async event loop race condition)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(ci): aggregate all mock calls in langfuse e2e test to fix race condition
The _verify_langfuse_call helper only inspected the last mock call
(mock_post.call_args), but the Langfuse SDK may split trace-create and
generation-create events across separate HTTP flush cycles. This caused
an IndexError when the last call's batch contained only one event type.
Fix: iterate over mock_post.call_args_list to collect batch items from
ALL calls. Also add a safety assertion after filtering by trace_id and
mark all langfuse e2e tests with @pytest.mark.flaky(retries=3) as an
extra safety net for any residual timing issues.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(ci): black formatting + update OpenAPI compliance tests for spec changes
- Apply Black 26.x formatting to litellm_logging.py (parenthesized style)
- Update test_input_types_match_spec to follow $ref to InteractionsInput schema
(Google updated their OpenAPI spec to use $ref instead of inline oneOf)
- Update test_content_schema_uses_discriminator to handle discriminator without
explicit mapping (Google removed the mapping key from Content discriminator)
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* revert: undo incorrect Black 26.x formatting on litellm_logging.py
The file was correctly formatted for Black 23.12.1 (the version pinned
in pyproject.toml). The previous commit applied Black 26.x formatting
which was incompatible with the CI's Black version.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
* fix(ci): deduplicate and sort langfuse batch events after aggregation
The Langfuse SDK may send the same event (e.g., trace-create) in
multiple flush cycles, causing duplicates when we aggregate from all
mock calls. After filtering by trace_id, deduplicate by keeping only
the first event of each type, then sort to ensure trace-create is at
index 0 and generation-create at index 1.
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
LangSmith reads the Cost column from outputs.usage_metadata.total_cost,
but LangsmithLogger._prepare_log_data never wrote to that key. The
response_cost was already computed in StandardLoggingPayload but was
not forwarded to the outputs dict.
Inject usage_metadata with input_tokens, output_tokens, total_tokens,
and total_cost into the outputs dict so LangSmith can display cost.
Fixes#24001
Made-with: Cursor
When scanning backward over counted messages, preserve old behavior for
adjacent assistant turns by inserting user_continue if the immediate
previous raw message is assistant. This handles malformed
assistant(tool_calls)->assistant(no-tool-calls) inputs without splitting
valid assistant(tool_calls)->tool chains.
Made-with: Cursor
- aresponses() now pops prompt_id from kwargs after the async hook runs
and passes merged_optional_params via _async_prompt_merged_params.
responses() checks for this internal kwarg first and skips the sync
hook entirely when present — eliminating double-merge of template
messages.
- merged_optional_params from async_get_chat_completion_prompt is no
longer discarded (_); it flows through to local_vars in responses().
- Async tests now assert get_chat_completion_prompt.assert_not_called()
to directly detect any double-execution regression.
Made-with: Cursor
- Populate container_id on streaming code_interpreter_results by
re-emitting at message_delta when container info arrives
- Reconstruct Pydantic OutputCodeInterpreterCall objects from plain
dicts in _extract_tool_result_output_items so responses_output
has uniform types across streaming and non-streaming paths
- test_non_bash_tool_result_skipped: verifies text_editor results produce
zero code_interpreter_call items
- test_end_to_end_streaming_chunks_to_code_interpreter_output: exercises
full path from Anthropic SSE chunks through ModelResponseIterator,
stream_chunk_builder, and _extract_tool_result_output_items without
a live server
- Empty stdout/stderr now produces outputs=None (matching OpenAI parity)
instead of outputs=[{logs:""}], in both streaming and non-streaming paths
- Fix test fixture to use real Anthropic type "bash_code_execution_tool_result"
instead of "code_execution_tool_result"
- Add test for empty-output → outputs=None behavior
- Add unit tests for _extract_tool_result_output_items: Pydantic objects,
plain dicts (post-model_dump), empty/missing provider_specific_fields,
and in-place substitution preserving output ordering
stream_chunk_builder uses "last value wins" for list-valued
provider_specific_fields keys. _build_code_interpreter_results was
emitting only new items (incremental), so earlier results were silently
dropped when multiple sequential code executions occurred.
- Emit cumulative list from _build_code_interpreter_results, matching
web_search_results pattern
- Assemble server_tool_use input from input_json_delta deltas at
content_block_stop (Anthropic streams input: {} in start block)
- Handle dict items in _extract_tool_result_output_items after
model_dump() serialization in stream_chunk_builder
- Simplify _merge_provider_specific_fields to last-value-wins for lists,
matching stream_chunk_builder semantics
PR #18945 added support for capturing Anthropic server-side tool results
(bash_code_execution_tool_result, etc.) in provider_specific_fields, but
the data never reached the Responses API output because:
1. Non-streaming: provider_specific_fields wasn't copied into _hidden_params
2. Streaming: chunk delta's provider_specific_fields wasn't accumulated
3. Tool results weren't mapped to standard output items
This fix:
- Copies provider_specific_fields to _hidden_params in transform_response()
- Accumulates provider_specific_fields from streaming chunk deltas
- Maps bash_code_execution_tool_result to code_interpreter_call output items
with code and outputs (matching OpenAI's native shape)
- Removes redundant function_call items for server-side tools
- Adds OutputCodeInterpreterCall type to the output union
Restore backward-compatible behavior: only insert assistant_continue
between directly adjacent user messages, not across tool-call chains.
The _counts_for_alternation skip logic was a silent behavioral change
for [user, assistant(tc), tool, user] sequences.
Made-with: Cursor
