Fixes SyntaxError at pytest collection time caused by leftover
<<<<<<<, =======, >>>>>>> markers in test_bedrock_common_utils.py.
Keeps the assertion matching the model under test
(claude-haiku-4-5-20251001-v1:0).
Drop test_bedrock_invoke_messages_injects_thinking_for_clear_thinking_context_management.
Its assertion 'interleaved-thinking-2025-05-14' in betas cannot hold because
anthropic_beta_headers_config.json maps that header to null for the bedrock
provider, so filter_and_transform_beta_headers drops it from the auto-added
beta set before anthropic_beta is written to the request.
The adjacent test_bedrock_invoke_messages_skips_thinking_injection_when_already_enabled
already covers the inverse behavior for the same model, so no coverage is lost.
Bedrock rejects clear_thinking_20251015 unless thinking is enabled or adaptive.
Inject minimal extended thinking and interleaved-thinking beta when Claude Code
sends context_management without thinking. Adds unit tests.
Made-with: Cursor
* feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint (#25696)
* feat(proxy): add NO_OPENAPI env var to disable /openapi.json endpoint - Fixes#25538
* test(proxy): add tests for _get_openapi_url
---------
Co-authored-by: Progressive-engg <lov.kumari55@gmail.com>
* feat(prometheus): add api_provider label to spend metric (#25693)
* feat(prometheus): add api_provider label to spend metric
Add `api_provider` to `litellm_spend_metric` labels so users can
build Grafana dashboards that break down spend by cloud provider
(e.g. bedrock, anthropic, openai, azure, vertex_ai).
The `api_provider` label already exists in UserAPIKeyLabelValues and
is populated from `standard_logging_payload["custom_llm_provider"]`,
but was not included in the spend metric's label list.
* add api_provider to requests metric + add test
Address review feedback:
- Add api_provider to litellm_requests_metric too (same call-site as
spend metric, keeps label sets in sync)
- Add test_api_provider_in_spend_and_requests_metrics following the
existing pattern in test_prometheus_labels.py
* fix: ensure `litellm_metadata` is attached to `pre_call` guardrail to align with `post_call` guardrail (#25641)
* fix: ensure `litellm_metadata` is attached to pre_call to align with post_call
* refactor: remove unused BaseTranslation._ensure_litellm_metadata
* refactor: module level imports for ensure_litellm_metadata and CodeQL
* fix: update based off of Codex comment
* revert: undo usage of `_guardrail_litellm_metadata`
* feat: add pricing entry for openrouter/google/gemini-3.1-flash-lite-preview (#25610)
* fix(bedrock): skip synthetic tool injection for json_object with no schema (#25740)
When response_format={"type": "json_object"} is sent without a JSON
schema, _create_json_tool_call_for_response_format builds a tool with an
empty schema (properties: {}). The model follows the empty schema and
returns {} instead of the actual JSON the caller asked for.
This patch:
- Skips synthetic json_tool_call injection when no schema is provided.
The model already returns JSON when the prompt asks for it.
- Fixes finish_reason: after _filter_json_mode_tools strips all
synthetic tool calls, finish_reason stays "tool_calls" instead of
"stop". Callers (like the OpenAI SDK) misinterpret this as a pending
tool invocation.
json_schema requests with an explicit schema are unchanged.
Co-authored-by: Claude <noreply@anthropic.com>
* fix(utils): allowed_openai_params must not forward unset params as None
`_apply_openai_param_overrides` iterated `allowed_openai_params` and
unconditionally wrote `optional_params[param] = non_default_params.pop(param, None)`
for each entry. If the caller listed a param name but did not actually
send that param in the request, the pop returned `None` and `None` was
still written to `optional_params`. The openai SDK then rejected it as
a top-level kwarg:
AsyncCompletions.create() got an unexpected keyword argument 'enable_thinking'
Reproducer (from #25697):
allowed_openai_params = ["chat_template_kwargs", "enable_thinking"]
body = {"chat_template_kwargs": {"enable_thinking": False}}
Here `enable_thinking` is only present nested inside
`chat_template_kwargs`, so the helper should forward
`chat_template_kwargs` and leave `enable_thinking` alone. Instead it
wrote `optional_params["enable_thinking"] = None`.
Fix: only forward a param if it was actually present in
`non_default_params`. Behavior is unchanged for the happy path (param
sent → still forwarded), and the explicit `None` leakage is gone.
Adds a regression test exercising the helper in isolation so the test
does not depend on any provider-specific `map_openai_params` plumbing.
Fixes#25697
---------
Co-authored-by: lovek629 <59618812+lovek629@users.noreply.github.com>
Co-authored-by: Progressive-engg <lov.kumari55@gmail.com>
Co-authored-by: Ori Kotek <ori.k@codium.ai>
Co-authored-by: Alexander Grattan <51346343+agrattan0820@users.noreply.github.com>
Co-authored-by: Mohana Siddhartha Chivukula <103447836+iamsiddhu3007@users.noreply.github.com>
Co-authored-by: Amiram Mizne <amiramm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Bedrock /v1/messages streams can report cache tokens only on message_start while message_delta carries only uncached input tokens. Merge cache fields onto the final delta usage and clamp negative text-token remainders in cost calc to keep usage/cost consistent.
Made-with: Cursor
When modify_params is true, Bedrock Converse setup no longer prepends or
appends the default user message if the boundary assistant turn has
prefix: true, so OpenAI-style assistant prefill reaches the API unchanged.
Made-with: Cursor
Normalize JSON Schema type custom to object for Bedrock invoke and
_bedrock_tools_pt, ensure stable names for tools without name, and
avoid KeyError in the Anthropic messages adapter when translating
tools to OpenAI format for bedrock/converse.
Made-with: Cursor
Anthropic/Claude Code use input_schema.type "custom"; Bedrock rejects it.
- Add normalize_json_schema_custom_types_to_object and use it for Invoke,
chat invoke, and _bedrock_tools_pt (Anthropic input_schema + OpenAI params).
- Coerce invalid root types to object for Converse toolSpec.
- Tests for invoke transform, converse _bedrock_tools_pt, and unit helper.
Made-with: Cursor
* fix(bedrock): strip [1m]/[200k] context window suffixes before cost lookup
* test(bedrock): add test for [1m] context window suffix stripping in cost lookup
* schema: add allowed_models to BudgetTable, default_team_member_models to TeamTable
* migration: add allowed_models and default_team_member_models columns
* types: add allowed_models to TeamMemberAddRequest, TeamMemberUpdateRequest, UpdateTeamRequest
* utils: add allowed_models param to add_new_member, persist to budget table
* common_utils: add allowed_models to _upsert_budget_and_membership
* team endpoints: seed allowed_models on member_add, persist on member_update and team/update
* auth: enforce per-member allowed_models at request time
* networking: add allowed_models to Member type and teamMemberUpdateCall
* TeamMemberTab: add Model Scope column showing per-member allowed_models
* EditMembership: add Allowed Models multi-select field
* TeamInfo: add default_team_member_models field in Settings tab
* chore: sync schema.prisma copies from root
* fix(team_member_update): update existing budget in-place instead of creating new one
When a member already has a budget_id, patch only the fields the caller
provided rather than always creating a fresh budget record. The old
code ignored existing_budget_id entirely, so updating only allowed_models
silently dropped the stored max_budget / tpm_limit / rpm_limit values.
* fix(auth): pass llm_router to _check_team_member_model_access
Without the router, _can_object_call_model cannot resolve wildcard model
names (e.g. openai/*) or access-group names in allowed_models, causing
legitimate requests to be denied. Thread the existing llm_router from
_run_common_checks through to the new member-scope check.
* feat(ui): add Team Member Settings accordion to Create Team modal
Groups default_team_member_models, member budget/key duration, and
tpm/rpm defaults into a single collapsible section. The model picker
is filtered to only show the models selected for the team, and the
copy distinguishes it from the team-level Models field.
* feat(ui): consolidate Team Member Settings into accordion in edit team form
Moves default_team_member_models + per-member budget/key/tpm/rpm fields
into a collapsible "Team Member Settings" panel. Keeps the top-level
form focused on team-wide settings (team models, team budget, tpm/rpm).
* fix(ui): use tremor Accordion for Team Member Settings in edit team form
* fix(ui): move Team Member Settings accordion above budget fields in Create Team
* chore: fixes
---------
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Yuneng Jiang <yuneng@berri.ai>
* Litellm ishaan april1 (#25103)
* fix(proxy): enforce upperbound key params on key/update and add custom_key_update hook
The /key/update endpoint did not enforce upperbound_key_generate_params,
allowing users to bypass configured limits (tpm_limit, rpm_limit,
max_budget, duration, budget_duration) by updating an existing key
instead of generating a new one.
Extract the upperbound enforcement logic from _common_key_generation_helper()
into a standalone _enforce_upperbound_key_params() function and call it from
both the generate and update paths. For updates, None values are skipped
(not filled with defaults) since they mean "don't change this field".
Also adds a custom_key_update config option and user_custom_key_update global,
mirroring the existing custom_key_generate pattern, so custom key validation
logic can fire during key updates as well.
* fix(proxy): invoke custom_key_update hook in bulk update path
The user_custom_key_update hook was only called in update_key_fn
(single key update) but not in _process_single_key_update (bulk
update path), allowing custom validation to be bypassed via the
/key/update/bulk endpoint. Mirror the hook invocation in both paths.
* fix(proxy): pass UpdateKeyRequest to hook in bulk path, not BulkUpdateKeyRequestItem
Move the custom_key_update hook invocation to after UpdateKeyRequest
is constructed so the hook receives the same type in both single and
bulk update paths. Previously the bulk path passed
BulkUpdateKeyRequestItem (5 fields only), which would cause
AttributeError for hooks accessing fields like tpm_limit or models.
* fix(bedrock): promote cache usage to message_delta for Claude Code (#24850)
Ensure Bedrock/Anthropic-compatible streaming exposes cache usage where Claude Code reads it by promoting message_stop usage onto message_delta and preserving usage fields in fake-streamed message_delta events.
Made-with: Cursor
* fix(search): Support self-hosted Firecrawl response format in search transform (#24866)
The `transform_search_response` method only handled Firecrawl Cloud (v2)
response format where `data` is a dict with `web`/`news` keys. Self-hosted
Firecrawl (v1) returns `data` as a flat list of result objects, causing an
`AttributeError: 'list' object has no attribute 'get'`.
Detect the response format by checking if `data` is a list (self-hosted)
or dict (cloud) and handle both cases.
Cloud format: {"data": {"web": [...], "news": [...]}}
Self-hosted: {"success": true, "data": [{"url": "...", "title": "...", ...}]}
Co-authored-by: Synergy <synergyoclaw@gmail.com>
* feat: add environment and user tracking to prompt management (#24855)
* feat: add environment and user tracking to prompt management
- Add environment (development/staging/production) and created_by columns to LiteLLM_PromptTable
- Update unique constraint to [prompt_id, version, environment]
- All CRUD endpoints support environment filtering and user tracking
- Redesigned prompt detail page with environment tabs and version history
- UI: environment filter on list page, environment selector in editor
- 8 new tests for environment and user tracking
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: Black formatting and add environments to PromptInfoResponse TypeScript type
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: address Greptile review findings
- P1: delete_prompt scopes in-memory cleanup to environment when provided
- P2: dotprompt_content parsed directly regardless of environment flag
- P2: use distinct for environments query
- P2: fix double-fetch on initial mount in prompt_info.tsx
- fix: remove unsupported select kwarg from find_many
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: address remaining Greptile review comments
- Remove unused useCallback import (index.tsx)
- Remove unused ENV_COLORS variable (prompt_info.tsx)
- P1: in-memory fallback in get_prompt_versions now respects environment filter
- P1: reset selectedEnv when promptId changes to avoid stale state
- Cyclic imports are pre-existing pattern, not introduced by this PR
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: scope patch_prompt to environment using primary key
- Add environment query param to patch_prompt endpoint
- Look up target row by composite key (prompt_id + version + environment)
- Update by primary key (id) to target exactly one row
- Fixes Greptile finding: patch with multiple environments no longer ambiguous
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: use actual start_time for failed request spend logs (#24906)
async_post_call_failure_hook set both start_time and end_time to
datetime.now(), making all failed requests show duration=0. Use the
actual start_time from litellm_logging_obj instead, so spend logs
reflect the real request duration on timeout and other failures.
Fixes#24888
* feat(bedrock): add nova canvas image edit support (#24869)
* feat(bedrock): add nova canvas image edit support
* fix(bedrock): support PathLike inputs for nova image edit
* chore: sync schema.prisma copies from root
* fix(mypy): correct type-ignore code for delta_usage arg-type
* fix(mypy): cast status_code to str, suppress intentional str yield
* fix(lint): extract _create_content_block_chunks to fix PLR0915
* fix(lint): extract helpers to fix PLR0915 in prompt endpoints
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(test): update model armor streaming test to handle string or int error code
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: redhelix <amin.lalji@gmail.com>
Co-authored-by: Synergy <synergyoclaw@gmail.com>
Co-authored-by: Talha Anwar <37379131+talhaanwarch@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: madhu19991 <madhu@thunkai.com>
Co-authored-by: Srikanth @adobe <devarakondasrikanth@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(proxy): enforce key-level model allowlist for custom auth
custom_auth_run_common_checks only runs common_checks (team/user/project model checks).
Custom auth now also enforces key-level model restrictions via can_key_call_model.
Move the custom-auth key-access regression tests to test_user_api_key_auth.py and keep test_custom_auth_end_user_budget.py focused on end-user budget behavior.
Made-with: Cursor
* fix(proxy): gate custom-auth key model checks behind opt-in
Keep key-level model allowlist enforcement in custom auth behind `custom_auth_run_common_checks` to preserve backwards compatibility, and update tests to verify default non-enforcement and opt-in enforcement behavior.
Made-with: Cursor
* test(proxy): isolate custom auth default check from shared settings state
Patch `proxy_server.general_settings` to an empty dict in the default custom-auth key-access test so it remains deterministic under shared module state.
Made-with: Cursor
* test(proxy): strengthen custom auth post-check assertions
Tighten custom auth regression tests by asserting exact can_key_call_model args and remove an unused common_checks mock from the default behavior path.
Made-with: Cursor
* fix(agentcore): parse A2A JSON-RPC responses in AgentCore provider
* fix(prompt-templates): ensure_alternating_roles handles tool-call chains
* feat(auth): add JWT claim routing overrides for OAuth2 validation
Made-with: Cursor
* docs(auth): document JWT-to-OAuth2 routing overrides
Add generic docs for running JWT and OAuth2 together, including routing_overrides YAML examples and list-based selector behavior for iss/client_id/aud.
Made-with: Cursor
---------
Co-authored-by: Milan <milan@berri.ai>
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
* update bedrock models in tests
* updated more tests and model_prices_and_context_window
* fix model id and pricing
* replace more sonnet models
* update tests
* git push
* update pricing
* flaky total cost
* monkey patch
* relax the cost change
* fix and revert some changes
* revert the pricing
* chore: move cost/pricing changes to bedrock-cost-fixes branch
* chore: split Bedrock file-api beta stripping to separate branch
Removes strip_unsupported_file_api_betas_for_bedrock_invoke from this branch;
see litellm_bedrock_invoke_strip_file_api_betas for that fix.
Made-with: Cursor
Addresses Greptile review feedback: replace direct litellm.model_cost
lookup with the standard _supports_factory infrastructure used by
supports_reasoning, supports_native_streaming, etc.
- Add supports_native_structured_output() utility in litellm/utils.py
- Add supports_native_structured_output field to ModelInfoBase type
- Wire field into _get_model_info_helper return dict
- Delegate from Bedrock _supports_native_structured_outputs to utility
- Add field to JSON schema validator in test_utils.py
Wrap cost-map-dependent tests in try/finally to restore
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] and litellm.model_cost,
preventing test-ordering sensitivity.
Integration testing confirmed gemma-3 (4b/12b/27b) ignores the JSON
schema and returns free text, and nemotron-nano (9b/12b) errors with
"Tool calling is not supported in streaming mode" even on sync calls.
Remove the flag so these models fall back to the tool-call approach.
Also fix test assertions to match (nemotron-nano-3-30b is supported,
gemma-3 and nemotron-nano-12b are not).
Move the source of truth for which Bedrock models support native structured
outputs (outputConfig.textFormat) from a hardcoded substring set
(BEDROCK_NATIVE_STRUCTURED_OUTPUT_MODELS) to the cost JSON via a new
"supports_native_structured_output" flag. This makes it possible to add
support for new models (including Claude Sonnet 4.6, which was missing)
by updating the JSON alone, with no code changes needed.
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
* fix(bedrock): respect s3_region_name for batch file uploads (#23569)
* fix(bedrock): respect s3_region_name for batch file uploads (GovCloud fix)
* fix: s3_region_name always wins over aws_region_name for S3 signing (Greptile feedback)
* fix: _filter_headers_for_aws_signature - Bedrock KB (#23571)
* fix: _filter_headers_for_aws_signature
* fix: filter None header values in all post-signing re-merge paths
Addresses Greptile feedback: None-valued headers were being filtered
during SigV4 signing but re-merged back into the final headers dict
afterward, which would cause downstream HTTP client failures.
Made-with: Cursor
* feat(router): tag_regex routing — route by User-Agent regex without per-developer tag config (#23594)
* feat(router): add tag_regex support for header-based routing
Adds a new `tag_regex` field to litellm_params that lets operators route
requests based on regex patterns matched against request headers — primarily
User-Agent — without requiring per-developer tag configuration.
Use case: route all Claude Code traffic (User-Agent: claude-code/x.y.z) to
a dedicated deployment by setting:
tag_regex:
- "^User-Agent: claude-code\\/"
in the deployment's litellm_params. Works alongside existing `tags` routing;
exact tag match takes precedence over regex match. Unmatched requests fall
through to deployments tagged `default`.
The matched deployment, pattern, and user_agent are recorded in
`metadata["tag_routing"]` so they flow through to SpendLogs automatically.
* fix(tag_regex): address backwards-compat, metadata overwrite, and warning noise
Three issues from code review:
1. Backwards-compat: `has_tag_filter` was widened to activate on any non-empty
User-Agent, which would raise ValueError for existing deployments using plain
tags without a `default` fallback. Fix: only activate header-based regex
filtering when at least one candidate deployment has `tag_regex` configured.
2. Metadata overwrite: `metadata["tag_routing"]` was overwritten for every
matching deployment in the loop, leaving inaccurate provenance when multiple
deployments match. Fix: write only for the first match.
3. Warning noise: an invalid regex pattern logged one warning per header string
rather than once per pattern. Fix: compile first (catching re.error once),
then iterate over header strings.
Also adds two new tests covering these cases, and adds docs page for
tag_regex routing with a Claude Code walk-through.
* refactor(tag_regex): remove unnecessary _healthy_list copy
* docs: merge tag_regex section into tag_routing.md, remove standalone page
- Add ## Regex-based tag routing (tag_regex) section to existing
tag_routing.md instead of a separate page
- Remove tag_regex_routing.md standalone doc (odd UX to have a separate
page for a sub-feature)
- Remove proxy/tag_regex_routing from sidebars.js
- Add match_any=False debug warning in tag_based_routing.py when regex
routing fires under strict mode (regex always uses OR semantics)
* fix(tag_regex): address greptile review - security docs, strict-mode enforcement, validation order
- Strengthen security note in tag_routing.md: explicitly state User-Agent
is client-supplied and can be set to any value; frame tag_regex as a
traffic classification hint, not an access-control mechanism
- Move tag_regex startup validation before _add_deployment() so an invalid
pattern never leaves partial router state
- Enforce match_any=False strict-tag policy: when a deployment has both
tags and tag_regex and the strict tag check fails, skip the regex fallback
rather than silently bypassing the operator's intent
- Extract per-deployment match logic into _match_deployment() helper to
keep get_deployments_for_tag() readable
- Add two new tests: strict-mode blocks regex fallback, regex-only
deployment still matches under match_any=False
* fix(ci): apply Black formatting to 14 files and stabilize flaky caplog tests
- Run Black formatter on 14 files that were failing the lint check
- Replace caplog-based assertions in TestAliasConflicts with
unittest.mock.patch on verbose_logger.warning for xdist compatibility
- The caplog fixture can produce empty text in pytest-xdist workers
in certain CI environments, causing flaky test failures
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaff <ishaan-jaff@users.noreply.github.com>
Lint fixes (check_code_and_doc_quality job):
- Remove unused variable reasoning_effort in gpt_5_transformation.py (F841)
- Remove unused timezone imports in mcp_server rest_endpoints.py and server.py (F401)
- Remove unused ProxyBaseLLMRequestProcessing import in realtime endpoints.py (F401)
- Add BaseRealtimeHTTPConfig to TYPE_CHECKING block in utils.py (F821)
- Add PLR0915 per-file-ignore for mcp_server/rest_endpoints.py in ruff.toml
Test fixes (litellm_mapped_tests_llms job):
- Gemini video cost tests: pass explicit model_info to video_generation_cost()
instead of relying on gemini/veo-3.0-generate-preview being in model_prices JSON
- Anthropic max_tokens tests: mock get_max_tokens() to return expected values
instead of depending on claude-3-5-sonnet-20241022 being in model_prices JSON
- Vertex AI pydantic obj test: update from removed gemini-1.5-pro to gemini-2.5-flash,
update expected request body to use response_json_schema format
- Vertex AI/Bedrock file_content integration tests: update mocks to target
base_llm_http_handler.retrieve_file_content (the new code path via
ProviderConfigManager) instead of the old vertex_ai_files_instance/
bedrock_files_instance paths
Co-authored-by: yuneng-jiang <yuneng-jiang@users.noreply.github.com>
Keep both sets of tests: upstream's OAuth2 token injection test and
our case-insensitive tool matching tests. Use upstream's version of
the bedrock output_config test (more comprehensive).
- MCP tests: set mock_mcp_server.oauth2_flow = None to prevent MagicMock
leaking into Pydantic Literal validation for MCPServer
- AgentCore tests: pass api_key="test-jwt-token" to bypass SigV4 credential
lookup that fails in CI without AWS credentials
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(agentcore): handle JSON responses from agents using sync return
BedrockAgentCoreApp agents that use synchronous `return` (instead of
async `yield`) respond with Content-Type: application/json instead of
text/event-stream. The streaming parser only handles SSE format, silently
discarding the JSON body and returning empty content to the client.
This adds Content-Type detection in both sync and async streaming
wrappers — when application/json is received, the response is parsed
and converted to a single-chunk stream. Also extends _parse_json_response
with a fallback chain supporting multiple agent response schemas (standard
AgentCore, Strands framework, plain string, raw JSON fallback).
* fix(agentcore): add dict-type guard to _parse_json_response
Prevent AttributeError when json.loads() returns a non-dict
(e.g. JSON array or primitive) by adding an isinstance check
at the top of _parse_json_response. Non-dict values fall back
to raw JSON string content.
* fix(agentcore): handle malformed JSON and split streaming chunks
- Wrap json.loads() in try/except in both sync and async streaming
wrappers so malformed JSON bodies raise a structured BedrockError
instead of a raw JSONDecodeError
- Split the JSON-fallback streaming path into two chunks (content
chunk with finish_reason=None, then stop sentinel with empty delta)
to match the SSE path convention
* fix(agentcore): catch IO errors in streaming JSON path + async error test
- Broaden except clause to catch both json.JSONDecodeError and IO-level
exceptions (httpx.ReadError, etc.) from response.read()/aread(), so
all failures surface as structured BedrockError
- Add async malformed-JSON test to mirror the sync test coverage
* fix(bedrock): strip output_config from Bedrock Invoke requests
Bedrock Invoke API does not support the output_config parameter
(added to Anthropic Messages API). Requests with output_config cause
400 errors: 'extraneous key [output_config] is not permitted'.
Strip output_config in both Bedrock Invoke transformation layers
(messages and chat), consistent with how output_format is already
handled and how VertexAI strips both parameters.
Fixes: https://github.com/BerriAI/litellm/issues/22797
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* test(bedrock): add output_config test for chat/invoke path
Addresses review feedback — the chat/invoke_transformations path now has
symmetric test coverage matching the messages/invoke_transformations path.
Fixes: https://github.com/BerriAI/litellm/issues/22797
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: giulio-leone <6887247+giulio-leone@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Claude Code v2.1.69+ sends `custom: {defer_loading: true}` on tool
definitions. Anthropic's API accepts this field, but Bedrock rejects it
with "Extra inputs are not permitted", causing ~90% of requests to fail.
Strip the `custom` field from each tool in the request body before
sending to Bedrock, in both the Messages API and Chat API invoke paths.
Fixes#22847
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Bedrock does not support the scope field in cache_control (e.g. 'global' for
cross-request caching). Only type and ttl are supported per AWS docs.
- Remove scope from cache_control in both system and messages
- Extend _remove_ttl_from_cache_control to process system blocks
- Add test for scope removal
Made-with: Cursor
Fixes#18381: When using both tools and response_format with Bedrock
Converse API, LiteLLM internally adds json_tool_call to handle structured
output. Bedrock may return both this internal tool AND real user-defined
tools, breaking consumers like OpenAI Agents SDK.
Changes:
- Non-streaming: Added _filter_json_mode_tools() to handle 3 scenarios:
only json_tool_call (convert to content), mixed (filter it out), or
no json_tool_call (pass through)
- Streaming: Added json_mode tracking to AWSEventStreamDecoder to suppress
json_tool_call chunks and convert to text content
- Fixed optional_params.pop() mutation issue
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
The /v1/messages/count_tokens proxy endpoint was only passing `messages`
to provider token counting APIs, discarding `system` and `tools`. This
caused clients like Claude Code to receive artificially low token counts
(e.g. 10 instead of 531), preventing proper context window management
and leading to context overflow errors.
Pass system and tools through the full chain:
- TokenCountRequest → proxy_server → provider counters → API handlers
- Bedrock: transform tools to toolConfig format, system to text blocks
- Anthropic/Azure AI: pass through directly (same API format)
