diff --git a/.circleci/config.yml b/.circleci/config.yml
index 0ebf9127033..6dd1177f79c 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -24,6 +24,39 @@ commands:
cd enterprise
python -m pip install -e .
cd ..
+ setup_litellm_test_deps:
+ steps:
+ - checkout
+ - setup_google_dns
+ - restore_cache:
+ keys:
+ - v2-litellm-deps-{{ checksum "requirements.txt" }}-{{ checksum ".circleci/config.yml" }}
+ - v2-litellm-deps-
+ - run:
+ name: Install Dependencies
+ command: |
+ python -m pip install --upgrade pip
+ python -m pip install -r requirements.txt
+ pip install "pytest-mock==3.12.0"
+ pip install "pytest==7.3.1"
+ pip install "pytest-retry==1.6.3"
+ pip install "pytest-cov==5.0.0"
+ pip install "pytest-asyncio==0.21.1"
+ pip install "respx==0.22.0"
+ pip install "hypercorn==0.17.3"
+ pip install "pydantic==2.10.2"
+ pip install "mcp==1.10.1"
+ pip install "requests-mock>=1.12.1"
+ pip install "responses==0.25.7"
+ pip install "pytest-xdist==3.6.1"
+ pip install "pytest-timeout==2.2.0"
+ pip install "semantic_router==0.1.10"
+ pip install "fastapi-offline==1.7.3"
+ - setup_litellm_enterprise_pip
+ - save_cache:
+ paths:
+ - ~/.cache/pip
+ key: v2-litellm-deps-{{ checksum "requirements.txt" }}-{{ checksum ".circleci/config.yml" }}
jobs:
# Add Windows testing job
@@ -668,13 +701,16 @@ jobs:
paths:
- litellm_security_tests_coverage.xml
- litellm_security_tests_coverage
- litellm_proxy_unit_testing: # Runs all tests with the "proxy", "key", "jwt" filenames
+ # Split proxy unit tests into 3 jobs for faster execution and better debugging
+ # test_key_generate_prisma runs separately without parallel execution to avoid event loop issues with logging worker
+ litellm_proxy_unit_testing_key_generation:
docker:
- image: cimg/python:3.11
auth:
username: ${DOCKERHUB_USERNAME}
password: ${DOCKERHUB_PASSWORD}
working_directory: ~/project
+ resource_class: large
steps:
- checkout
- setup_google_dns
@@ -699,6 +735,114 @@ jobs:
pip install "pytest-retry==1.6.3"
pip install "pytest-asyncio==0.21.1"
pip install "pytest-cov==5.0.0"
+ pip install "pytest-timeout==2.2.0"
+ pip install "pytest-forked==1.6.0"
+ pip install "mypy==1.18.2"
+ pip install "google-generativeai==0.3.2"
+ pip install "google-cloud-aiplatform==1.43.0"
+ pip install "google-genai==1.22.0"
+ pip install pyarrow
+ pip install "boto3==1.36.0"
+ pip install "aioboto3==13.4.0"
+ pip install langchain
+ pip install lunary==0.2.5
+ pip install "azure-identity==1.16.1"
+ pip install "langfuse==2.59.7"
+ pip install "logfire==0.29.0"
+ pip install numpydoc
+ pip install traceloop-sdk==0.21.1
+ pip install opentelemetry-api==1.25.0
+ pip install opentelemetry-sdk==1.25.0
+ pip install opentelemetry-exporter-otlp==1.25.0
+ pip install openai==1.100.1
+ pip install prisma==0.11.0
+ pip install "detect_secrets==1.5.0"
+ pip install "httpx==0.24.1"
+ pip install "respx==0.22.0"
+ pip install fastapi
+ pip install "gunicorn==21.2.0"
+ pip install "anyio==4.2.0"
+ pip install "aiodynamo==23.10.1"
+ pip install "asyncio==3.4.3"
+ pip install "apscheduler==3.10.4"
+ pip install "PyGithub==1.59.1"
+ pip install argon2-cffi
+ pip install "pytest-mock==3.12.0"
+ pip install python-multipart
+ pip install google-cloud-aiplatform
+ pip install prometheus-client==0.20.0
+ pip install "pydantic==2.10.2"
+ pip install "diskcache==5.6.1"
+ pip install "Pillow==10.3.0"
+ pip install "jsonschema==4.22.0"
+ pip install "pytest-postgresql==7.0.1"
+ pip install "fakeredis==2.28.1"
+ - setup_litellm_enterprise_pip
+ - save_cache:
+ paths:
+ - ./venv
+ key: v1-dependencies-{{ checksum ".circleci/requirements.txt" }}
+ - run:
+ name: Run prisma ./docker/entrypoint.sh
+ command: |
+ set +e
+ chmod +x docker/entrypoint.sh
+ ./docker/entrypoint.sh
+ set -e
+ - run:
+ name: Run key generation tests (no parallel execution to avoid event loop issues)
+ command: |
+ pwd
+ ls
+ # Run without -n flag to avoid pytest-xdist event loop conflicts with logging worker
+ python -m pytest tests/proxy_unit_tests/test_key_generate_prisma.py --cov=litellm --cov-report=xml --junitxml=test-results/junit-key-generation.xml --durations=10 --timeout=300 -vv --log-cli-level=INFO
+ no_output_timeout: 120m
+ - run:
+ name: Rename the coverage files
+ command: |
+ mv coverage.xml litellm_proxy_unit_tests_key_generation_coverage.xml
+ mv .coverage litellm_proxy_unit_tests_key_generation_coverage
+ - store_test_results:
+ path: test-results
+ - persist_to_workspace:
+ root: .
+ paths:
+ - litellm_proxy_unit_tests_key_generation_coverage.xml
+ - litellm_proxy_unit_tests_key_generation_coverage
+ litellm_proxy_unit_testing_part1:
+ docker:
+ - image: cimg/python:3.11
+ auth:
+ username: ${DOCKERHUB_USERNAME}
+ password: ${DOCKERHUB_PASSWORD}
+ working_directory: ~/project
+ resource_class: large
+ steps:
+ - checkout
+ - setup_google_dns
+ - run:
+ name: Show git commit hash
+ command: |
+ echo "Git commit hash: $CIRCLE_SHA1"
+ - run:
+ name: Install PostgreSQL
+ command: |
+ sudo apt-get update
+ sudo apt-get install -y postgresql-14 postgresql-contrib-14
+ - restore_cache:
+ keys:
+ - v1-dependencies-{{ checksum ".circleci/requirements.txt" }}
+ - run:
+ name: Install Dependencies
+ command: |
+ python -m pip install --upgrade pip
+ python -m pip install -r .circleci/requirements.txt
+ pip install "pytest==7.3.1"
+ pip install "pytest-retry==1.6.3"
+ pip install "pytest-asyncio==0.21.1"
+ pip install "pytest-cov==5.0.0"
+ pip install "pytest-timeout==2.2.0"
+ pip install "pytest-forked==1.6.0"
pip install "mypy==1.18.2"
pip install "google-generativeai==0.3.2"
pip install "google-cloud-aiplatform==1.43.0"
@@ -752,28 +896,132 @@ jobs:
chmod +x docker/entrypoint.sh
./docker/entrypoint.sh
set -e
- # Run pytest and generate JUnit XML report
- run:
- name: Run tests
+ name: Run proxy unit tests (part 1 - auth checks only, key generation in separate job)
command: |
pwd
ls
- python -m pytest tests/proxy_unit_tests --cov=litellm --cov-report=xml -vv -x -v --junitxml=test-results/junit.xml --durations=5 -n 4
+ # Run auth tests with parallel execution (test_key_generate_prisma moved to separate job to avoid event loop issues)
+ python -m pytest tests/proxy_unit_tests/test_auth_checks.py tests/proxy_unit_tests/test_user_api_key_auth.py --cov=litellm --cov-report=xml --junitxml=test-results/junit-part1.xml --durations=10 -n 8 --timeout=300 -vv --log-cli-level=INFO
no_output_timeout: 120m
- run:
name: Rename the coverage files
command: |
- mv coverage.xml litellm_proxy_unit_tests_coverage.xml
- mv .coverage litellm_proxy_unit_tests_coverage
- # Store test results
+ mv coverage.xml litellm_proxy_unit_tests_part1_coverage.xml
+ mv .coverage litellm_proxy_unit_tests_part1_coverage
- store_test_results:
path: test-results
-
- persist_to_workspace:
root: .
paths:
- - litellm_proxy_unit_tests_coverage.xml
- - litellm_proxy_unit_tests_coverage
+ - litellm_proxy_unit_tests_part1_coverage.xml
+ - litellm_proxy_unit_tests_part1_coverage
+ litellm_proxy_unit_testing_part2:
+ docker:
+ - image: cimg/python:3.11
+ auth:
+ username: ${DOCKERHUB_USERNAME}
+ password: ${DOCKERHUB_PASSWORD}
+ working_directory: ~/project
+ resource_class: large
+ steps:
+ - checkout
+ - setup_google_dns
+ - run:
+ name: Show git commit hash
+ command: |
+ echo "Git commit hash: $CIRCLE_SHA1"
+ - run:
+ name: Install PostgreSQL
+ command: |
+ sudo apt-get update
+ sudo apt-get install -y postgresql-14 postgresql-contrib-14
+ - restore_cache:
+ keys:
+ - v1-dependencies-{{ checksum ".circleci/requirements.txt" }}
+ - run:
+ name: Install Dependencies
+ command: |
+ python -m pip install --upgrade pip
+ python -m pip install -r .circleci/requirements.txt
+ pip install "pytest==7.3.1"
+ pip install "pytest-retry==1.6.3"
+ pip install "pytest-asyncio==0.21.1"
+ pip install "pytest-cov==5.0.0"
+ pip install "pytest-timeout==2.2.0"
+ pip install "pytest-forked==1.6.0"
+ pip install "mypy==1.18.2"
+ pip install "google-generativeai==0.3.2"
+ pip install "google-cloud-aiplatform==1.43.0"
+ pip install "google-genai==1.22.0"
+ pip install pyarrow
+ pip install "boto3==1.36.0"
+ pip install "aioboto3==13.4.0"
+ pip install langchain
+ pip install lunary==0.2.5
+ pip install "azure-identity==1.16.1"
+ pip install "langfuse==2.59.7"
+ pip install "logfire==0.29.0"
+ pip install numpydoc
+ pip install traceloop-sdk==0.21.1
+ pip install opentelemetry-api==1.25.0
+ pip install opentelemetry-sdk==1.25.0
+ pip install opentelemetry-exporter-otlp==1.25.0
+ pip install openai==1.100.1
+ pip install prisma==0.11.0
+ pip install "detect_secrets==1.5.0"
+ pip install "httpx==0.24.1"
+ pip install "respx==0.22.0"
+ pip install fastapi
+ pip install "gunicorn==21.2.0"
+ pip install "anyio==4.2.0"
+ pip install "aiodynamo==23.10.1"
+ pip install "asyncio==3.4.3"
+ pip install "apscheduler==3.10.4"
+ pip install "PyGithub==1.59.1"
+ pip install argon2-cffi
+ pip install "pytest-mock==3.12.0"
+ pip install python-multipart
+ pip install google-cloud-aiplatform
+ pip install prometheus-client==0.20.0
+ pip install "pydantic==2.10.2"
+ pip install "diskcache==5.6.1"
+ pip install "Pillow==10.3.0"
+ pip install "jsonschema==4.22.0"
+ pip install "pytest-postgresql==7.0.1"
+ pip install "fakeredis==2.28.1"
+ pip install "pytest-xdist==3.6.1"
+ - setup_litellm_enterprise_pip
+ - save_cache:
+ paths:
+ - ./venv
+ key: v1-dependencies-{{ checksum ".circleci/requirements.txt" }}
+ - run:
+ name: Run prisma ./docker/entrypoint.sh
+ command: |
+ set +e
+ chmod +x docker/entrypoint.sh
+ ./docker/entrypoint.sh
+ set -e
+ - run:
+ name: Run proxy unit tests (part 2 - remaining tests)
+ command: |
+ pwd
+ ls
+ python -m pytest tests/proxy_unit_tests --ignore=tests/proxy_unit_tests/test_key_generate_prisma.py --ignore=tests/proxy_unit_tests/test_auth_checks.py --ignore=tests/proxy_unit_tests/test_user_api_key_auth.py --cov=litellm --cov-report=xml --junitxml=test-results/junit-part2.xml --durations=10 -n 8 --timeout=300 -vv --log-cli-level=INFO
+ no_output_timeout: 120m
+ - run:
+ name: Rename the coverage files
+ command: |
+ mv coverage.xml litellm_proxy_unit_tests_part2_coverage.xml
+ mv .coverage litellm_proxy_unit_tests_part2_coverage
+ - store_test_results:
+ path: test-results
+ - persist_to_workspace:
+ root: .
+ paths:
+ - litellm_proxy_unit_tests_part2_coverage.xml
+ - litellm_proxy_unit_tests_part2_coverage
litellm_assistants_api_testing: # Runs all tests with the "assistants" keyword
docker:
- image: cimg/python:3.13.1
@@ -1128,59 +1376,88 @@ jobs:
paths:
- search_coverage.xml
- search_coverage
- litellm_mapped_tests:
+ # Split litellm_mapped_tests into 3 parallel jobs for 3x faster execution
+ litellm_mapped_tests_proxy:
docker:
- image: cimg/python:3.11
auth:
username: ${DOCKERHUB_USERNAME}
password: ${DOCKERHUB_PASSWORD}
working_directory: ~/project
-
+ resource_class: xlarge
steps:
- - checkout
- - setup_google_dns
+ - setup_litellm_test_deps
- run:
- name: Install Dependencies
+ name: Run proxy tests
command: |
- python -m pip install --upgrade pip
- python -m pip install -r requirements.txt
- pip install "pytest-mock==3.12.0"
- pip install "pytest==7.3.1"
- pip install "pytest-retry==1.6.3"
- pip install "pytest-cov==5.0.0"
- pip install "pytest-asyncio==0.21.1"
- pip install "respx==0.22.0"
- pip install "hypercorn==0.17.3"
- pip install "pydantic==2.10.2"
- pip install "mcp==1.10.1"
- pip install "requests-mock>=1.12.1"
- pip install "responses==0.25.7"
- pip install "pytest-xdist==3.6.1"
- pip install "semantic_router==0.1.10"
- pip install "fastapi-offline==1.7.3"
- - setup_litellm_enterprise_pip
- # Run pytest and generate JUnit XML report
- - run:
- name: Run litellm tests
- command: |
- pwd
- ls
- python -m pytest -vv tests/test_litellm --cov=litellm --cov-report=xml -v --junitxml=test-results/junit-litellm.xml --durations=10 -n 8
+ python -m pytest tests/test_litellm/proxy --cov=litellm --cov-report=xml --junitxml=test-results/junit-proxy.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING
no_output_timeout: 120m
- run:
name: Rename the coverage files
command: |
- mv coverage.xml litellm_mapped_tests_coverage.xml
- mv .coverage litellm_mapped_tests_coverage
-
- # Store test results
+ mv coverage.xml litellm_proxy_tests_coverage.xml
+ mv .coverage litellm_proxy_tests_coverage
- store_test_results:
path: test-results
- persist_to_workspace:
root: .
paths:
- - litellm_mapped_tests_coverage.xml
- - litellm_mapped_tests_coverage
+ - litellm_proxy_tests_coverage.xml
+ - litellm_proxy_tests_coverage
+ litellm_mapped_tests_llms:
+ docker:
+ - image: cimg/python:3.11
+ auth:
+ username: ${DOCKERHUB_USERNAME}
+ password: ${DOCKERHUB_PASSWORD}
+ working_directory: ~/project
+ resource_class: xlarge
+ steps:
+ - setup_litellm_test_deps
+ - run:
+ name: Run LLM provider tests
+ command: |
+ python -m pytest tests/test_litellm/llms --cov=litellm --cov-report=xml --junitxml=test-results/junit-llms.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING
+ no_output_timeout: 120m
+ - run:
+ name: Rename the coverage files
+ command: |
+ mv coverage.xml litellm_llms_tests_coverage.xml
+ mv .coverage litellm_llms_tests_coverage
+ - store_test_results:
+ path: test-results
+ - persist_to_workspace:
+ root: .
+ paths:
+ - litellm_llms_tests_coverage.xml
+ - litellm_llms_tests_coverage
+ litellm_mapped_tests_core:
+ docker:
+ - image: cimg/python:3.11
+ auth:
+ username: ${DOCKERHUB_USERNAME}
+ password: ${DOCKERHUB_PASSWORD}
+ working_directory: ~/project
+ resource_class: xlarge
+ steps:
+ - setup_litellm_test_deps
+ - run:
+ name: Run core tests
+ command: |
+ python -m pytest tests/test_litellm --ignore=tests/test_litellm/proxy --ignore=tests/test_litellm/llms --cov=litellm --cov-report=xml --junitxml=test-results/junit-core.xml --durations=10 -n 16 --maxfail=5 --timeout=300 -vv --log-cli-level=WARNING
+ no_output_timeout: 120m
+ - run:
+ name: Rename the coverage files
+ command: |
+ mv coverage.xml litellm_core_tests_coverage.xml
+ mv .coverage litellm_core_tests_coverage
+ - store_test_results:
+ path: test-results
+ - persist_to_workspace:
+ root: .
+ paths:
+ - litellm_core_tests_coverage.xml
+ - litellm_core_tests_coverage
litellm_mapped_enterprise_tests:
docker:
- image: cimg/python:3.11
@@ -1447,7 +1724,7 @@ jobs:
command: |
pwd
ls
- python -m pytest -vv tests/logging_callback_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5
+ python -m pytest -vv tests/logging_callback_tests --cov=litellm --cov-report=xml -s -v --junitxml=test-results/junit.xml --durations=5
no_output_timeout: 120m
- run:
name: Rename the coverage files
@@ -1914,14 +2191,14 @@ jobs:
sudo usermod -aG docker $USER
docker version
- run:
- name: Install Python 3.9
+ name: Install Python 3.10
command: |
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh --output miniconda.sh
bash miniconda.sh -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
conda init bash
source ~/.bashrc
- conda create -n myenv python=3.9 -y
+ conda create -n myenv python=3.10 -y
conda activate myenv
python --version
- run:
@@ -2695,19 +2972,22 @@ jobs:
sudo usermod -aG docker $USER
docker version
- run:
- name: Install Python 3.9
+ name: Install Python 3.10
command: |
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh --output miniconda.sh
bash miniconda.sh -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
conda init bash
source ~/.bashrc
- conda create -n myenv python=3.9 -y
+ conda create -n myenv python=3.10 -y
conda activate myenv
python --version
- run:
name: Install Dependencies
command: |
+ export PATH="$HOME/miniconda/bin:$PATH"
+ source $HOME/miniconda/etc/profile.d/conda.sh
+ conda activate myenv
pip install "pytest==7.3.1"
pip install "pytest-retry==1.6.3"
pip install "pytest-asyncio==0.21.1"
@@ -2736,6 +3016,8 @@ jobs:
pip install "langchain_mcp_adapters==0.0.5"
pip install "langchain_openai==0.2.1"
pip install "langgraph==0.3.18"
+ pip install "fastuuid==0.13.5"
+ pip install -r requirements.txt
- run:
name: Install dockerize
command: |
@@ -2848,6 +3130,9 @@ jobs:
- run:
name: Run tests
command: |
+ export PATH="$HOME/miniconda/bin:$PATH"
+ source $HOME/miniconda/etc/profile.d/conda.sh
+ conda activate myenv
pwd
ls
python -m pytest -vv tests/pass_through_tests/ -x --junitxml=test-results/junit.xml --durations=5
@@ -2878,7 +3163,7 @@ jobs:
python -m venv venv
. venv/bin/activate
pip install coverage
- coverage combine llm_translation_coverage llm_responses_api_coverage ocr_coverage search_coverage mcp_coverage logging_coverage audio_coverage litellm_router_coverage local_testing_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_coverage image_gen_coverage pass_through_unit_tests_coverage batches_coverage litellm_security_tests_coverage guardrails_coverage
+ coverage combine llm_translation_coverage llm_responses_api_coverage ocr_coverage search_coverage mcp_coverage logging_coverage audio_coverage litellm_router_coverage local_testing_coverage litellm_assistants_api_coverage auth_ui_unit_tests_coverage langfuse_coverage caching_coverage litellm_proxy_unit_tests_part1_coverage litellm_proxy_unit_tests_part2_coverage image_gen_coverage pass_through_unit_tests_coverage batches_coverage litellm_security_tests_coverage guardrails_coverage litellm_mapped_tests_coverage
coverage xml
- codecov/upload:
file: ./coverage.xml
@@ -3054,7 +3339,7 @@ jobs:
python -m build
twine upload --verbose dist/*
- e2e_ui_testing:
+ ui_build:
machine:
image: ubuntu-2204:2023.10.1
resource_class: xlarge
@@ -3081,6 +3366,48 @@ jobs:
# Now source the build script
source ./build_ui.sh
+ - persist_to_workspace:
+ root: .
+ paths:
+ - litellm/proxy/_experimental/out
+
+ ui_unit_tests:
+ machine:
+ image: ubuntu-2204:2023.10.1
+ resource_class: xlarge
+ working_directory: ~/project
+ steps:
+ - checkout
+ - setup_google_dns
+ - run:
+ name: Run UI unit tests (Vitest)
+ command: |
+ # Use Node 20 (several deps require >=20)
+ export NVM_DIR="/opt/circleci/.nvm"
+ source "$NVM_DIR/nvm.sh"
+ nvm install 20
+ nvm use 20
+
+ cd ui/litellm-dashboard
+ npm ci || npm install
+
+ # CI run, with both LCOV (Codecov) and HTML (artifact you can click)
+ CI=true npm run test -- --run --coverage \
+ --coverage.provider=v8 \
+ --coverage.reporter=lcov \
+ --coverage.reporter=html \
+ --coverage.reportsDirectory=coverage/html
+
+ e2e_ui_testing:
+ machine:
+ image: ubuntu-2204:2023.10.1
+ resource_class: xlarge
+ working_directory: ~/project
+ steps:
+ - checkout
+ - setup_google_dns
+ - attach_workspace:
+ at: ~/project
- run:
name: Upgrade Docker to v24.x (API 1.44+)
command: |
@@ -3126,24 +3453,6 @@ jobs:
name: Install Playwright Browsers
command: |
npx playwright install
- - run:
- name: Run UI unit tests (Vitest)
- command: |
- # Use Node 20 (several deps require >=20)
- export NVM_DIR="/opt/circleci/.nvm"
- source "$NVM_DIR/nvm.sh"
- nvm install 20
- nvm use 20
-
- cd ui/litellm-dashboard
- npm ci || npm install
-
- # CI run, with both LCOV (Codecov) and HTML (artifact you can click)
- CI=true npm run test -- --run --coverage \
- --coverage.provider=v8 \
- --coverage.reporter=lcov \
- --coverage.reporter=html \
- --coverage.reportsDirectory=coverage/html
- run:
name: Build Docker image
@@ -3300,7 +3609,19 @@ workflows:
only:
- main
- /litellm_.*/
- - litellm_proxy_unit_testing:
+ - litellm_proxy_unit_testing_key_generation:
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
+ - litellm_proxy_unit_testing_part1:
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
+ - litellm_proxy_unit_testing_part2:
filters:
branches:
only:
@@ -3336,6 +3657,20 @@ workflows:
only:
- main
- /litellm_.*/
+ - ui_build:
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
+ - ui_unit_tests:
+ requires:
+ - ui_build
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
- auth_ui_unit_tests:
filters:
branches:
@@ -3343,6 +3678,8 @@ workflows:
- main
- /litellm_.*/
- e2e_ui_testing:
+ requires:
+ - ui_build
filters:
branches:
only:
@@ -3444,7 +3781,19 @@ workflows:
only:
- main
- /litellm_.*/
- - litellm_mapped_tests:
+ - litellm_mapped_tests_proxy:
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
+ - litellm_mapped_tests_llms:
+ filters:
+ branches:
+ only:
+ - main
+ - /litellm_.*/
+ - litellm_mapped_tests_core:
filters:
branches:
only:
@@ -3495,7 +3844,9 @@ workflows:
- llm_responses_api_testing
- ocr_testing
- search_testing
- - litellm_mapped_tests
+ - litellm_mapped_tests_proxy
+ - litellm_mapped_tests_llms
+ - litellm_mapped_tests_core
- litellm_mapped_enterprise_tests
- batches_testing
- litellm_utils_testing
@@ -3506,7 +3857,9 @@ workflows:
- litellm_router_testing
- litellm_router_unit_testing
- caching_unit_tests
- - litellm_proxy_unit_testing
+ - litellm_proxy_unit_testing_key_generation
+ - litellm_proxy_unit_testing_part1
+ - litellm_proxy_unit_testing_part2
- litellm_security_tests
- langfuse_logging_unit_tests
- local_testing
@@ -3560,7 +3913,9 @@ workflows:
- llm_responses_api_testing
- ocr_testing
- search_testing
- - litellm_mapped_tests
+ - litellm_mapped_tests_proxy
+ - litellm_mapped_tests_llms
+ - litellm_mapped_tests_core
- litellm_mapped_enterprise_tests
- batches_testing
- litellm_utils_testing
@@ -3576,7 +3931,9 @@ workflows:
- auth_ui_unit_tests
- db_migration_disable_update_check
- e2e_ui_testing
- - litellm_proxy_unit_testing
+ - litellm_proxy_unit_testing_key_generation
+ - litellm_proxy_unit_testing_part1
+ - litellm_proxy_unit_testing_part2
- litellm_security_tests
- installing_litellm_on_python
- installing_litellm_on_python_3_13
diff --git a/AGENTS.md b/AGENTS.md
index 8e7b5f2bd2e..d72b00f7e14 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -94,6 +94,10 @@ LiteLLM supports MCP for agent workflows:
- Support for external MCP servers (Zapier, Jira, Linear, etc.)
- See `litellm/experimental_mcp_client/` and `litellm/proxy/_experimental/mcp_server/`
+## RUNNING SCRIPTS
+
+Use `poetry run python script.py` to run Python scripts in the project environment (for non-test files).
+
## TESTING CONSIDERATIONS
1. **Provider Tests**: Test against real provider APIs when possible
diff --git a/CLAUDE.md b/CLAUDE.md
index 50bed6e43e2..15984323394 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -25,6 +25,9 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
- `poetry run pytest tests/path/to/test_file.py -v` - Run specific test file
- `poetry run pytest tests/path/to/test_file.py::test_function -v` - Run specific test
+### Running Scripts
+- `poetry run python script.py` - Run Python scripts (use for non-test files)
+
## Architecture Overview
LiteLLM is a unified interface for 100+ LLM providers with two main components:
diff --git a/Makefile b/Makefile
index a79a397f945..1614a58fc7d 100644
--- a/Makefile
+++ b/Makefile
@@ -34,13 +34,13 @@ install-proxy-dev:
# CI-compatible installations (matches GitHub workflows exactly)
install-dev-ci:
- pip install openai==1.99.5
+ pip install openai==2.8.0
poetry install --with dev
- pip install openai==1.99.5
+ pip install openai==2.8.0
install-proxy-dev-ci:
poetry install --with dev,proxy-dev --extras proxy
- pip install openai==1.99.5
+ pip install openai==2.8.0
install-test-deps: install-proxy-dev
poetry run pip install "pytest-retry==1.6.3"
diff --git a/VERTEX_ENV_SETUP.md b/VERTEX_ENV_SETUP.md
deleted file mode 100644
index 93a631c82f1..00000000000
--- a/VERTEX_ENV_SETUP.md
+++ /dev/null
@@ -1,261 +0,0 @@
-# Vertex AI Environment Variables Setup Guide
-
-## Overview
-
-LiteLLM can load Vertex AI credentials from environment variables instead of storing them in config files. This is more secure and easier to manage for local development.
-
-## Environment Variables
-
-LiteLLM looks for these environment variables (in order of precedence):
-
-### 1. **DEFAULT_VERTEXAI_PROJECT** (Required)
-Your GCP project ID that has Vertex AI enabled.
-
-```bash
-export DEFAULT_VERTEXAI_PROJECT="my-gcp-project-id"
-```
-
-### 2. **DEFAULT_VERTEXAI_LOCATION** (Required)
-The region/location for Vertex AI services.
-
-```bash
-export DEFAULT_VERTEXAI_LOCATION="global"
-# or
-export DEFAULT_VERTEXAI_LOCATION="us-central1"
-```
-
-Common locations:
-- `global` - For Discovery Engine and global services
-- `us-central1` - US Central region
-- `us-east1` - US East region
-- `europe-west1` - Europe West region
-- `asia-southeast1` - Asia Southeast region
-
-### 3. **DEFAULT_GOOGLE_APPLICATION_CREDENTIALS** (Required)
-Path to your service account JSON key file.
-
-```bash
-export DEFAULT_GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"
-```
-
-### 4. **GOOGLE_APPLICATION_CREDENTIALS** (Fallback)
-Standard Google Cloud environment variable (used as fallback).
-
-```bash
-export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"
-```
-
-## Quick Setup
-
-### Option 1: Interactive Script
-
-```bash
-chmod +x setup_vertex_env.sh
-source setup_vertex_env.sh
-```
-
-### Option 2: Manual Setup
-
-1. **Set environment variables** (for current session):
-
-```bash
-export DEFAULT_VERTEXAI_PROJECT="your-project-id"
-export DEFAULT_VERTEXAI_LOCATION="global"
-export DEFAULT_GOOGLE_APPLICATION_CREDENTIALS="$HOME/.gcp/service-account.json"
-export GOOGLE_APPLICATION_CREDENTIALS="$HOME/.gcp/service-account.json"
-```
-
-2. **Make them persistent** (add to `~/.zshrc` or `~/.bashrc`):
-
-```bash
-echo 'export DEFAULT_VERTEXAI_PROJECT="your-project-id"' >> ~/.zshrc
-echo 'export DEFAULT_VERTEXAI_LOCATION="global"' >> ~/.zshrc
-echo 'export DEFAULT_GOOGLE_APPLICATION_CREDENTIALS="$HOME/.gcp/service-account.json"' >> ~/.zshrc
-echo 'export GOOGLE_APPLICATION_CREDENTIALS="$HOME/.gcp/service-account.json"' >> ~/.zshrc
-```
-
-3. **Reload your shell**:
-
-```bash
-source ~/.zshrc
-```
-
-## Service Account Setup
-
-### 1. Create a Service Account
-
-```bash
-gcloud iam service-accounts create litellm-vertex-sa \
- --display-name="LiteLLM Vertex AI Service Account"
-```
-
-### 2. Grant Necessary Permissions
-
-For Discovery Engine (vector stores):
-```bash
-gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
- --member="serviceAccount:litellm-vertex-sa@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
- --role="roles/discoveryengine.viewer"
-
-gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
- --member="serviceAccount:litellm-vertex-sa@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
- --role="roles/discoveryengine.dataStoreEditor"
-```
-
-For general Vertex AI:
-```bash
-gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
- --member="serviceAccount:litellm-vertex-sa@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
- --role="roles/aiplatform.user"
-```
-
-### 3. Create and Download Key
-
-```bash
-gcloud iam service-accounts keys create ~/service-account-key.json \
- --iam-account=litellm-vertex-sa@YOUR_PROJECT_ID.iam.gserviceaccount.com
-```
-
-## Verify Setup
-
-### Check Environment Variables
-
-```bash
-python3 << 'EOF'
-import os
-print("✓ Environment Variables:")
-print(f" DEFAULT_VERTEXAI_PROJECT: {os.getenv('DEFAULT_VERTEXAI_PROJECT')}")
-print(f" DEFAULT_VERTEXAI_LOCATION: {os.getenv('DEFAULT_VERTEXAI_LOCATION')}")
-print(f" DEFAULT_GOOGLE_APPLICATION_CREDENTIALS: {os.getenv('DEFAULT_GOOGLE_APPLICATION_CREDENTIALS')}")
-print(f" GOOGLE_APPLICATION_CREDENTIALS: {os.getenv('GOOGLE_APPLICATION_CREDENTIALS')}")
-
-# Check if credentials file exists
-creds_path = os.getenv('DEFAULT_GOOGLE_APPLICATION_CREDENTIALS')
-if creds_path and os.path.exists(creds_path):
- print(f"\n✅ Credentials file found at: {creds_path}")
-else:
- print(f"\n❌ Credentials file NOT found at: {creds_path}")
-EOF
-```
-
-### Test Authentication
-
-```bash
-python3 << 'EOF'
-import os
-import json
-from google.oauth2 import service_account
-from google.auth.transport.requests import Request
-
-creds_path = os.getenv('DEFAULT_GOOGLE_APPLICATION_CREDENTIALS')
-project = os.getenv('DEFAULT_VERTEXAI_PROJECT')
-
-try:
- # Load credentials
- credentials = service_account.Credentials.from_service_account_file(
- creds_path,
- scopes=['https://www.googleapis.com/auth/cloud-platform']
- )
-
- # Get access token
- credentials.refresh(Request())
-
- print("✅ Authentication successful!")
- print(f" Project: {project}")
- print(f" Service Account: {credentials.service_account_email}")
- print(f" Token expiry: {credentials.expiry}")
-
-except Exception as e:
- print(f"❌ Authentication failed: {e}")
-EOF
-```
-
-## Using with Vector Store Passthrough
-
-Once your environment is set up, the vector store passthrough will work in two ways:
-
-### 1. **With Vector Store Config** (Priority 1)
-If you have a vector store configured with its own credentials in `litellm_params`, those will be used first:
-
-```yaml
-vector_stores:
- - vector_store_id: test-store-123
- custom_llm_provider: vertex_ai
- litellm_params:
- vertex_project: "specific-project"
- vertex_location: "us-central1"
- vertex_credentials: "{...}" # Inline credentials
-```
-
-### 2. **Environment Variables Fallback** (Priority 2)
-If the vector store doesn't have explicit credentials, it falls back to your environment variables:
-
-```yaml
-vector_stores:
- - vector_store_id: test-store-123
- custom_llm_provider: vertex_ai
- # No litellm_params - will use DEFAULT_VERTEXAI_PROJECT, DEFAULT_VERTEXAI_LOCATION, etc.
-```
-
-### 3. **Model Config Fallback** (Priority 3)
-If neither above work, it looks for credentials in your model configuration.
-
-## Troubleshooting
-
-### "No credentials found"
-
-Check that all environment variables are set:
-```bash
-env | grep -E "(DEFAULT_VERTEXAI|GOOGLE_APPLICATION_CREDENTIALS)"
-```
-
-### "Authentication failed"
-
-Verify your service account key is valid:
-```bash
-cat $DEFAULT_GOOGLE_APPLICATION_CREDENTIALS | python3 -m json.tool
-```
-
-### "Permission denied"
-
-Ensure your service account has the necessary roles:
-```bash
-gcloud projects get-iam-policy YOUR_PROJECT_ID \
- --flatten="bindings[].members" \
- --filter="bindings.members:serviceAccount:litellm-vertex-sa@*"
-```
-
-### Different Credentials for Different Projects
-
-If you need to use different credentials for different vector stores, configure them explicitly in the vector store config rather than relying on environment variables.
-
-## Start LiteLLM Proxy
-
-Once your environment is configured:
-
-```bash
-# Start the proxy (it will automatically load env vars)
-litellm --config proxy_server_config.yaml
-
-# Or with debug logging
-export LITELLM_LOG=DEBUG
-litellm --config proxy_server_config.yaml
-```
-
-You should see logs like:
-```
-Vertex: Loading vertex credentials from /path/to/service-account.json
-Found credentials for vertex_ai_default
-```
-
-## Test the Endpoint
-
-```bash
-curl -X POST http://0.0.0.0:4000/vertex_ai/discovery/v1/projects/fake-project/locations/global/dataStores/test-store-123/servingConfigs/default_config:search \
- -H 'Authorization: Bearer YOUR_LITELLM_API_KEY' \
- -H 'Content-Type: application/json' \
- -d '{"query": "test query"}'
-```
-
-The proxy will use your environment credentials to make the request to Vertex AI!
-
diff --git a/cookbook/LiteLLM_CometAPI.ipynb b/cookbook/LiteLLM_CometAPI.ipynb
index bdd916c5bfe..0a7ab581ae3 100644
--- a/cookbook/LiteLLM_CometAPI.ipynb
+++ b/cookbook/LiteLLM_CometAPI.ipynb
@@ -28,7 +28,7 @@
"Requirement already satisfied: importlib-metadata>=6.8.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (8.6.1)\n",
"Requirement already satisfied: jinja2<4.0.0,>=3.1.2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (3.1.6)\n",
"Requirement already satisfied: jsonschema<5.0.0,>=4.22.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (4.25.1)\n",
- "Requirement already satisfied: openai>=1.99.5 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (1.109.1)\n",
+ "Requirement already satisfied: openai>=2.8.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (1.109.1)\n",
"Requirement already satisfied: pydantic<3.0.0,>=2.5.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (2.11.10)\n",
"Requirement already satisfied: python-dotenv>=0.2.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (1.1.1)\n",
"Requirement already satisfied: tiktoken>=0.7.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from litellm) (0.12.0)\n",
@@ -50,11 +50,11 @@
"Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (2025.9.1)\n",
"Requirement already satisfied: referencing>=0.28.4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (0.36.2)\n",
"Requirement already satisfied: rpds-py>=0.7.1 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from jsonschema<5.0.0,>=4.22.0->litellm) (0.27.1)\n",
- "Requirement already satisfied: distro<2,>=1.7.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=1.99.5->litellm) (1.9.0)\n",
- "Requirement already satisfied: jiter<1,>=0.4.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=1.99.5->litellm) (0.11.0)\n",
- "Requirement already satisfied: sniffio in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=1.99.5->litellm) (1.3.1)\n",
- "Requirement already satisfied: tqdm>4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=1.99.5->litellm) (4.67.1)\n",
- "Requirement already satisfied: typing-extensions<5,>=4.11 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=1.99.5->litellm) (4.15.0)\n",
+ "Requirement already satisfied: distro<2,>=1.7.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (1.9.0)\n",
+ "Requirement already satisfied: jiter<1,>=0.4.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (0.11.0)\n",
+ "Requirement already satisfied: sniffio in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (1.3.1)\n",
+ "Requirement already satisfied: tqdm>4 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (4.67.1)\n",
+ "Requirement already satisfied: typing-extensions<5,>=4.11 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from openai>=2.8.0->litellm) (4.15.0)\n",
"Requirement already satisfied: annotated-types>=0.6.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (0.7.0)\n",
"Requirement already satisfied: pydantic-core==2.33.2 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (2.33.2)\n",
"Requirement already satisfied: typing-inspection>=0.4.0 in /Users/xmx/.miniforge3/lib/python3.12/site-packages (from pydantic<3.0.0,>=2.5.0->litellm) (0.4.2)\n",
diff --git a/cookbook/misc/update_json_caching.py b/cookbook/misc/update_json_caching.py
index 8202d7033fd..2601cb452bb 100644
--- a/cookbook/misc/update_json_caching.py
+++ b/cookbook/misc/update_json_caching.py
@@ -10,7 +10,6 @@ models_to_update = [
"gpt-4o-2024-05-13",
"text-embedding-3-small",
"text-embedding-3-large",
- "text-embedding-ada-002-v2",
"ft:gpt-4o-2024-08-06",
"ft:gpt-4o-mini-2024-07-18",
"ft:gpt-3.5-turbo",
diff --git a/deploy/charts/litellm-helm/Chart.yaml b/deploy/charts/litellm-helm/Chart.yaml
index aa81e4efecc..eedadebaa8e 100644
--- a/deploy/charts/litellm-helm/Chart.yaml
+++ b/deploy/charts/litellm-helm/Chart.yaml
@@ -18,7 +18,7 @@ type: application
# This is the chart version. This version number should be incremented each time you make changes
# to the chart and its templates, including the app version.
# Versions are expected to follow Semantic Versioning (https://semver.org/)
-version: 0.4.7
+version: 0.4.8
# This is the version number of the application being deployed. This version number should be
# incremented each time you make changes to the application. Versions are not expected to
diff --git a/deploy/charts/litellm-helm/templates/migrations-job.yaml b/deploy/charts/litellm-helm/templates/migrations-job.yaml
index 243a4ba7d48..f8893a47afe 100644
--- a/deploy/charts/litellm-helm/templates/migrations-job.yaml
+++ b/deploy/charts/litellm-helm/templates/migrations-job.yaml
@@ -22,6 +22,9 @@ spec:
metadata:
labels:
{{- include "litellm.labels" . | nindent 8 }}
+ {{- with .Values.podLabels }}
+ {{- toYaml . | nindent 8 }}
+ {{- end }}
annotations:
{{- with .Values.migrationJob.annotations }}
{{- toYaml . | nindent 8 }}
diff --git a/docs/my-website/.trivyignore b/docs/my-website/.trivyignore
new file mode 100644
index 00000000000..977504f2670
--- /dev/null
+++ b/docs/my-website/.trivyignore
@@ -0,0 +1,7 @@
+# js-yaml CVE-2025-64718
+# This vulnerability is not applicable because we've forced js-yaml to version 4.1.1
+# via npm overrides in package.json. Trivy incorrectly reports this based on
+# dependency requirements in the lockfile, but the actual installed version is 4.1.1.
+# Verified with: npm list js-yaml
+CVE-2025-64718
+
diff --git a/docs/my-website/blog/authors.yml b/docs/my-website/blog/authors.yml
new file mode 100644
index 00000000000..2a49a736333
--- /dev/null
+++ b/docs/my-website/blog/authors.yml
@@ -0,0 +1,24 @@
+litellm:
+ name: LiteLLM Team
+ title: LiteLLM Core Team
+ url: https://github.com/BerriAI/litellm
+ image_url: https://github.com/BerriAI.png
+
+krrish:
+ name: Krrish Dholakia
+ title: CEO, LiteLLM
+ url: https://www.linkedin.com/in/krish-d/
+ image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
+
+ishaan:
+ name: Ishaan Jaffer
+ title: CTO, LiteLLM
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
+
+# Alias for typo in name
+ishaan-alt:
+ name: Ishaan Jaff
+ title: CTO, LiteLLM
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
diff --git a/docs/my-website/blog/gemini_3/index.md b/docs/my-website/blog/gemini_3/index.md
new file mode 100644
index 00000000000..2f4cc5bb0f8
--- /dev/null
+++ b/docs/my-website/blog/gemini_3/index.md
@@ -0,0 +1,700 @@
+---
+slug: gemini_3
+title: "DAY 0 Support: Gemini 3 on LiteLLM"
+date: 2025-11-19T10:00:00
+authors:
+ - name: Sameer Kankute
+ title: "SWE @ LiteLLM (LLM Translation)"
+ url: https://in.linkedin.com/in/sameer-kankute
+ image_url: https://media.licdn.com/dms/image/v2/D4D03AQHB_loQYd5gjg/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1719137160975?e=1765411200&v=beta&t=c8396f--_lH6Fb_pVvx_jGholPfcl0bvwmNynbNdnII
+ - name: Krrish Dholakia
+ title: "CEO, LiteLLM"
+ url: https://www.linkedin.com/in/krish-d/
+ image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
+ - name: Ishaan Jaff
+ title: "CTO, LiteLLM"
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
+tags: [gemini, day 0 support, llms]
+hide_table_of_contents: false
+---
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+:::info
+
+This guide covers common questions and best practices for using `gemini-3-pro-preview` with LiteLLM Proxy and SDK.
+
+:::
+
+## Quick Start
+
+
+
+
+```python
+from litellm import completion
+import os
+
+os.environ["GEMINI_API_KEY"] = "your-api-key"
+
+response = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=[{"role": "user", "content": "Hello!"}],
+ reasoning_effort="low"
+)
+
+print(response.choices[0].message.content)
+```
+
+
+
+
+**1. Add to config.yaml:**
+
+```yaml
+model_list:
+ - model_name: gemini-3-pro-preview
+ litellm_params:
+ model: gemini/gemini-3-pro-preview
+ api_key: os.environ/GEMINI_API_KEY
+```
+
+**2. Start proxy:**
+
+```bash
+litellm --config /path/to/config.yaml
+```
+
+**3. Make request:**
+
+```bash
+curl http://0.0.0.0:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [{"role": "user", "content": "Hello!"}],
+ "reasoning_effort": "low"
+ }'
+```
+
+
+
+
+## Supported Endpoints
+
+LiteLLM provides **full end-to-end support** for Gemini 3 Pro Preview on:
+
+- ✅ `/v1/chat/completions` - OpenAI-compatible chat completions endpoint
+- ✅ [`/v1/messages`](../../docs/anthropic_unified) - Anthropic-compatible messages endpoint
+
+Both endpoints support:
+- Streaming and non-streaming responses
+- Function calling with thought signatures
+- Multi-turn conversations
+- All Gemini 3-specific features
+
+## Thought Signatures
+
+#### What are Thought Signatures?
+
+Thought signatures are encrypted representations of the model's internal reasoning process. They're essential for maintaining context across multi-turn conversations, especially with function calling.
+
+#### How Thought Signatures Work
+
+1. **Automatic Extraction**: When Gemini 3 returns a function call, LiteLLM automatically extracts the `thought_signature` from the response
+2. **Storage**: Thought signatures are stored in `provider_specific_fields.thought_signature` of tool calls
+3. **Automatic Preservation**: When you include the assistant's message in conversation history, LiteLLM automatically preserves and returns thought signatures to Gemini
+
+## Example: Multi-Turn Function Calling
+
+#### Streaming with Thought Signatures
+
+When using streaming mode with `stream_chunk_builder()`, thought signatures are now automatically preserved:
+
+
+
+
+```python
+import os
+import litellm
+from litellm import completion
+
+os.environ["GEMINI_API_KEY"] = "your-api-key"
+
+MODEL = "gemini/gemini-3-pro-preview"
+
+messages = [
+ {"role": "system", "content": "You are a helpful assistant. Use the calculate tool."},
+ {"role": "user", "content": "What is 2+2?"},
+]
+
+tools = [{
+ "type": "function",
+ "function": {
+ "name": "calculate",
+ "description": "Calculate a mathematical expression",
+ "parameters": {
+ "type": "object",
+ "properties": {"expression": {"type": "string"}},
+ "required": ["expression"],
+ },
+ },
+}]
+
+print("Step 1: Sending request with stream=True...")
+response = completion(
+ model=MODEL,
+ messages=messages,
+ stream=True,
+ tools=tools,
+ reasoning_effort="low"
+)
+
+# Collect all chunks
+chunks = []
+for part in response:
+ chunks.append(part)
+
+# Reconstruct message using stream_chunk_builder
+# Thought signatures are now preserved automatically!
+full_response = litellm.stream_chunk_builder(chunks, messages=messages)
+print(f"Full response: {full_response}")
+
+assistant_msg = full_response.choices[0].message
+
+# ✅ Thought signature is now preserved in provider_specific_fields
+if assistant_msg.tool_calls and assistant_msg.tool_calls[0].provider_specific_fields:
+ thought_sig = assistant_msg.tool_calls[0].provider_specific_fields.get("thought_signature")
+ print(f"Thought signature preserved: {thought_sig is not None}")
+
+# Append assistant message (includes thought signatures automatically)
+messages.append(assistant_msg)
+
+# Mock tool execution
+messages.append({
+ "role": "tool",
+ "content": "4",
+ "tool_call_id": assistant_msg.tool_calls[0].id
+})
+
+print("\nStep 2: Sending tool result back to model...")
+response_2 = completion(
+ model=MODEL,
+ messages=messages,
+ stream=True,
+ tools=tools,
+ reasoning_effort="low"
+)
+
+for part in response_2:
+ if part.choices[0].delta.content:
+ print(part.choices[0].delta.content, end="")
+print() # New line
+```
+
+**Key Points:**
+- ✅ `stream_chunk_builder()` now preserves `provider_specific_fields` including thought signatures
+- ✅ Thought signatures are automatically included when appending `assistant_msg` to conversation history
+- ✅ Multi-turn conversations work seamlessly with streaming
+
+
+
+
+```python
+from openai import OpenAI
+import json
+
+client = OpenAI(api_key="sk-1234", base_url="http://localhost:4000")
+
+# Define tools
+tools = [
+ {
+ "type": "function",
+ "function": {
+ "name": "get_weather",
+ "description": "Get the current weather",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "location": {"type": "string"}
+ },
+ "required": ["location"]
+ }
+ }
+ }
+]
+
+# Step 1: Initial request
+messages = [{"role": "user", "content": "What's the weather in Tokyo?"}]
+
+response = client.chat.completions.create(
+ model="gemini-3-pro-preview",
+ messages=messages,
+ tools=tools,
+ reasoning_effort="low"
+)
+
+# Step 2: Append assistant message (thought signatures automatically preserved)
+messages.append(response.choices[0].message)
+
+# Step 3: Execute tool and append result
+for tool_call in response.choices[0].message.tool_calls:
+ if tool_call.function.name == "get_weather":
+ result = {"temperature": 30, "unit": "celsius"}
+ messages.append({
+ "role": "tool",
+ "content": json.dumps(result),
+ "tool_call_id": tool_call.id
+ })
+
+# Step 4: Follow-up request (thought signatures automatically included)
+response2 = client.chat.completions.create(
+ model="gemini-3-pro-preview",
+ messages=messages,
+ tools=tools,
+ reasoning_effort="low"
+)
+
+print(response2.choices[0].message.content)
+```
+
+**Key Points:**
+- ✅ Thought signatures are automatically extracted from `response.choices[0].message.tool_calls[].provider_specific_fields.thought_signature`
+- ✅ When you append `response.choices[0].message` to your conversation history, thought signatures are automatically preserved
+- ✅ You don't need to manually extract or manage thought signatures
+
+
+
+
+```bash
+# Step 1: Initial request
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [
+ {"role": "user", "content": "What'\''s the weather in Tokyo?"}
+ ],
+ "tools": [
+ {
+ "type": "function",
+ "function": {
+ "name": "get_weather",
+ "description": "Get the current weather",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "location": {"type": "string"}
+ },
+ "required": ["location"]
+ }
+ }
+ }
+ ],
+ "reasoning_effort": "low"
+ }'
+```
+
+**Response includes thought signature:**
+
+```json
+{
+ "choices": [{
+ "message": {
+ "role": "assistant",
+ "tool_calls": [{
+ "id": "call_abc123",
+ "type": "function",
+ "function": {
+ "name": "get_weather",
+ "arguments": "{\"location\": \"Tokyo\"}"
+ },
+ "provider_specific_fields": {
+ "thought_signature": "CpcHAdHtim9+q4rstcbvQC0ic4x1/vqQlCJWgE+UZ6dTLYGHMMBkF/AxqL5UmP6SY46uYC8t4BTFiXG5zkw6EMJ..."
+ }
+ }]
+ }
+ }]
+}
+```
+
+```bash
+# Step 2: Follow-up request (include assistant message with thought signature)
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [
+ {"role": "user", "content": "What'\''s the weather in Tokyo?"},
+ {
+ "role": "assistant",
+ "content": null,
+ "tool_calls": [{
+ "id": "call_abc123",
+ "type": "function",
+ "function": {
+ "name": "get_weather",
+ "arguments": "{\"location\": \"Tokyo\"}"
+ },
+ "provider_specific_fields": {
+ "thought_signature": "CpcHAdHtim9+q4rstcbvQC0ic4x1/vqQlCJWgE+UZ6dTLYGHMMBkF/AxqL5UmP6SY46uYC8t4BTFiXG5zkw6EMJ..."
+ }
+ }]
+ },
+ {
+ "role": "tool",
+ "content": "{\"temperature\": 30, \"unit\": \"celsius\"}",
+ "tool_call_id": "call_abc123"
+ }
+ ],
+ "tools": [...],
+ "reasoning_effort": "low"
+ }'
+```
+
+
+
+
+#### Important Notes on Thought Signatures
+
+1. **Automatic Handling**: LiteLLM automatically extracts and preserves thought signatures. You don't need to manually manage them.
+
+2. **Parallel Function Calls**: When the model makes parallel function calls, only the **first function call** has a thought signature.
+
+3. **Sequential Function Calls**: In multi-step function calling, each step's first function call has its own thought signature that must be preserved.
+
+4. **Required for Context**: Thought signatures are essential for maintaining reasoning context. Without them, the model may lose context of its previous reasoning.
+
+## Conversation History: Switching from Non-Gemini-3 Models
+
+#### Common Question: Will switching from a non-Gemini-3 model to Gemini-3 break conversation history?
+
+**Answer: No!** LiteLLM automatically handles this by adding dummy thought signatures when needed.
+
+#### How It Works
+
+When you switch from a model that doesn't use thought signatures (e.g., `gemini-2.5-flash`) to Gemini 3, LiteLLM:
+
+1. **Detects missing signatures**: Identifies assistant messages with tool calls that lack thought signatures
+2. **Adds dummy signature**: Automatically injects a dummy thought signature (`skip_thought_signature_validator`) for compatibility
+3. **Maintains conversation flow**: Your conversation history continues to work seamlessly
+
+#### Example: Switching Models Mid-Conversation
+
+
+
+
+```python
+from openai import OpenAI
+
+client = OpenAI(api_key="sk-1234", base_url="http://localhost:4000")
+
+# Step 1: Start with gemini-2.5-flash (no thought signatures)
+messages = [{"role": "user", "content": "What's the weather?"}]
+
+response1 = client.chat.completions.create(
+ model="gemini-2.5-flash",
+ messages=messages,
+ tools=[...],
+ reasoning_effort="low"
+)
+
+# Append assistant message (no tool call thought signature from gemini-2.5-flash)
+messages.append(response1.choices[0].message)
+
+# Step 2: Switch to gemini-3-pro-preview
+# LiteLLM automatically adds dummy thought signature to the previous assistant message
+response2 = client.chat.completions.create(
+ model="gemini-3-pro-preview", # 👈 Switched model
+ messages=messages, # 👈 Same conversation history
+ tools=[...],
+ reasoning_effort="low"
+)
+
+# ✅ Works seamlessly! No errors, no breaking changes
+print(response2.choices[0].message.content)
+```
+
+
+
+
+```bash
+# Step 1: Start with gemini-2.5-flash
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-2.5-flash",
+ "messages": [{"role": "user", "content": "What'\''s the weather?"}],
+ "tools": [...],
+ "reasoning_effort": "low"
+ }'
+
+# Step 2: Switch to gemini-3-pro-preview with same conversation history
+# LiteLLM automatically handles the missing thought signature
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview", # 👈 Switched model
+ "messages": [
+ {"role": "user", "content": "What'\''s the weather?"},
+ {
+ "role": "assistant",
+ "tool_calls": [...] # 👈 No thought_signature from gemini-2.5-flash
+ }
+ ],
+ "tools": [...],
+ "reasoning_effort": "low"
+ }'
+# ✅ Works! LiteLLM adds dummy signature automatically
+```
+
+
+
+
+#### Dummy Signature Details
+
+The dummy signature used is: `base64("skip_thought_signature_validator")`
+
+This is the recommended approach by Google for handling conversation history from models that don't support thought signatures. It allows Gemini 3 to:
+- Accept the conversation history without validation errors
+- Continue the conversation seamlessly
+- Maintain context across model switches
+
+## Thinking Level Parameter
+
+#### How `reasoning_effort` Maps to `thinking_level`
+
+For Gemini 3 Pro Preview, LiteLLM automatically maps `reasoning_effort` to the new `thinking_level` parameter:
+
+| `reasoning_effort` | `thinking_level` | Notes |
+|-------------------|------------------|-------|
+| `"minimal"` | `"low"` | Maps to low thinking level |
+| `"low"` | `"low"` | Default for most use cases |
+| `"medium"` | `"high"` | Medium not available yet, maps to high |
+| `"high"` | `"high"` | Maximum reasoning depth |
+| `"disable"` | `"low"` | Gemini 3 cannot fully disable thinking |
+| `"none"` | `"low"` | Gemini 3 cannot fully disable thinking |
+
+#### Default Behavior
+
+If you don't specify `reasoning_effort`, LiteLLM automatically sets `thinking_level="low"` for Gemini 3 models, to avoid high costs.
+
+### Example Usage
+
+
+
+
+```python
+from litellm import completion
+
+# Low thinking level (faster, lower cost)
+response = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=[{"role": "user", "content": "What's the weather?"}],
+ reasoning_effort="low" # Maps to thinking_level="low"
+)
+
+# High thinking level (deeper reasoning, higher cost)
+response = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=[{"role": "user", "content": "Solve this complex math problem step by step."}],
+ reasoning_effort="high" # Maps to thinking_level="high"
+)
+```
+
+
+
+
+```bash
+# Low thinking level
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [{"role": "user", "content": "What'\''s the weather?"}],
+ "reasoning_effort": "low"
+ }'
+
+# High thinking level
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [{"role": "user", "content": "Solve this complex problem."}],
+ "reasoning_effort": "high"
+ }'
+```
+
+
+
+
+## Important Notes
+
+1. **Gemini 3 Cannot Disable Thinking**: Unlike Gemini 2.5 models, Gemini 3 cannot fully disable thinking. Even when you set `reasoning_effort="none"` or `"disable"`, it maps to `thinking_level="low"`.
+
+2. **Temperature Recommendation**: For Gemini 3 models, LiteLLM defaults `temperature` to `1.0` and strongly recommends keeping it at this default. Setting `temperature < 1.0` can cause:
+ - Infinite loops
+ - Degraded reasoning performance
+ - Failure on complex tasks
+
+3. **Automatic Defaults**: If you don't specify `reasoning_effort`, LiteLLM automatically sets `thinking_level="low"` for optimal performance.
+
+## Using with Claude Code CLI
+
+You can use `gemini-3-pro-preview` with **Claude Code CLI** - Anthropic's command-line interface. This allows you to use Gemini 3 Pro Preview with Claude Code's native syntax and workflows.
+
+### Setup
+
+**1. Add Gemini 3 Pro Preview to your `config.yaml`:**
+
+```yaml
+model_list:
+ - model_name: gemini-3-pro-preview
+ litellm_params:
+ model: gemini/gemini-3-pro-preview
+ api_key: os.environ/GEMINI_API_KEY
+
+litellm_settings:
+ master_key: os.environ/LITELLM_MASTER_KEY
+```
+
+**2. Set environment variables:**
+
+```bash
+export GEMINI_API_KEY="your-gemini-api-key"
+export LITELLM_MASTER_KEY="sk-1234567890" # Generate a secure key
+```
+
+**3. Start LiteLLM Proxy:**
+
+```bash
+litellm --config /path/to/config.yaml
+
+# RUNNING on http://0.0.0.0:4000
+```
+
+**4. Configure Claude Code to use LiteLLM Proxy:**
+
+```bash
+export ANTHROPIC_BASE_URL="http://0.0.0.0:4000"
+export ANTHROPIC_AUTH_TOKEN="$LITELLM_MASTER_KEY"
+```
+
+**5. Use Gemini 3 Pro Preview with Claude Code:**
+
+```bash
+# Claude Code will use gemini-3-pro-preview from your LiteLLM proxy
+claude --model gemini-3-pro-preview
+
+```
+
+### Example Usage
+
+Once configured, you can interact with Gemini 3 Pro Preview using Claude Code's native interface:
+
+```bash
+$ claude --model gemini-3-pro-preview
+> Explain how thought signatures work in multi-turn conversations.
+
+# Gemini 3 Pro Preview responds through Claude Code interface
+```
+
+### Benefits
+
+- ✅ **Native Claude Code Experience**: Use Gemini 3 Pro Preview with Claude Code's familiar CLI interface
+- ✅ **Unified Authentication**: Single API key for all models through LiteLLM proxy
+- ✅ **Cost Tracking**: All usage tracked through LiteLLM's centralized logging
+- ✅ **Seamless Model Switching**: Easily switch between Claude and Gemini models
+- ✅ **Full Feature Support**: All Gemini 3 features (thought signatures, function calling, etc.) work through Claude Code
+
+### Troubleshooting
+
+**Claude Code not finding the model:**
+- Ensure the model name in Claude Code matches exactly: `gemini-3-pro-preview`
+- Verify your proxy is running: `curl http://0.0.0.0:4000/health`
+- Check that `ANTHROPIC_BASE_URL` points to your LiteLLM proxy
+
+**Authentication errors:**
+- Verify `ANTHROPIC_AUTH_TOKEN` matches your LiteLLM master key
+- Ensure `GEMINI_API_KEY` is set correctly
+- Check LiteLLM proxy logs for detailed error messages
+
+## Best Practices
+
+#### 1. Always Include Thought Signatures in Conversation History
+
+When building multi-turn conversations with function calling:
+
+✅ **Do:**
+```python
+# Append the full assistant message (includes thought signatures)
+messages.append(response.choices[0].message)
+```
+
+❌ **Don't:**
+```python
+# Don't manually construct assistant messages without thought signatures
+messages.append({
+ "role": "assistant",
+ "tool_calls": [...] # Missing thought signatures!
+})
+```
+
+#### 2. Use Appropriate Thinking Levels
+
+- **`reasoning_effort="low"`**: For simple queries, quick responses, cost optimization
+- **`reasoning_effort="high"`**: For complex problems requiring deep reasoning
+
+#### 3. Keep Temperature at Default
+
+For Gemini 3 models, always use `temperature=1.0` (default). Lower temperatures can cause issues.
+
+#### 4. Handle Model Switches Gracefully
+
+When switching from non-Gemini-3 to Gemini-3:
+- ✅ LiteLLM automatically handles missing thought signatures
+- ✅ No manual intervention needed
+- ✅ Conversation history continues seamlessly
+
+## Troubleshooting
+
+#### Issue: Missing Thought Signatures
+
+**Symptom**: Error when including assistant messages in conversation history
+
+**Solution**: Ensure you're appending the full assistant message from the response:
+```python
+messages.append(response.choices[0].message) # ✅ Includes thought signatures
+```
+
+#### Issue: Conversation Breaks When Switching Models
+
+**Symptom**: Errors when switching from gemini-2.5-flash to gemini-3-pro-preview
+
+**Solution**: This should work automatically! LiteLLM adds dummy signatures. If you see errors, ensure you're using the latest LiteLLM version.
+
+#### Issue: Infinite Loops or Poor Performance
+
+**Symptom**: Model gets stuck or produces poor results
+
+**Solution**:
+- Ensure `temperature=1.0` (default for Gemini 3)
+- Check that `reasoning_effort` is set appropriately
+- Verify you're using the correct model name: `gemini/gemini-3-pro-preview`
+
+## Additional Resources
+
+- [Gemini Provider Documentation](../gemini.md)
+- [Thought Signatures Guide](../gemini.md#thought-signatures)
+- [Reasoning Content Documentation](../../reasoning_content.md)
+- [Function Calling Guide](../../function_calling.md)
+
diff --git a/docs/my-website/docs/adding_provider/simple_guardrail_tutorial.md b/docs/my-website/docs/adding_provider/simple_guardrail_tutorial.md
index 2722a4a024c..9c654cd1560 100644
--- a/docs/my-website/docs/adding_provider/simple_guardrail_tutorial.md
+++ b/docs/my-website/docs/adding_provider/simple_guardrail_tutorial.md
@@ -37,57 +37,7 @@ Two files: `my_guardrail.py` (main class) and `__init__.py` (initialization).
`my_guardrail.py`:
-```python
-import os
-from typing import Optional, List
-from fastapi import HTTPException
-
-from litellm.integrations.custom_guardrail import CustomGuardrail
-from litellm.types.guardrails import PiiEntityType
-from litellm._logging import verbose_proxy_logger
-from litellm.llms.custom_httpx.http_handler import (
- get_async_httpx_client,
- httpxSpecialProvider,
-)
-
-class MyGuardrail(CustomGuardrail):
- def __init__(self, api_key: Optional[str] = None, api_base: Optional[str] = None, **kwargs):
- self.api_key = api_key or os.getenv("MY_GUARDRAIL_API_KEY")
- self.api_base = api_base or os.getenv("MY_GUARDRAIL_API_BASE", "https://api.myguardrail.com")
- super().__init__(default_on=True)
-
- async def apply_guardrail(
- self,
- text: str,
- language: Optional[str] = None,
- entities: Optional[List[PiiEntityType]] = None,
- request_data: Optional[dict] = None,
- ) -> str:
- result = await self._check_with_api(text, request_data)
-
- if result.get("action") == "BLOCK":
- raise Exception(f"Content blocked: {result.get('reason', 'Policy violation')}")
-
- return text
-
- async def _check_with_api(self, text: str, request_data: Optional[dict]) -> dict:
- async_client = get_async_httpx_client(llm_provider=httpxSpecialProvider.LoggingCallback)
-
- headers = {
- "Content-Type": "application/json",
- "Authorization": f"Bearer {self.api_key}",
- }
-
- response = await async_client.post(
- f"{self.api_base}/check",
- headers=headers,
- json={"text": text},
- timeout=5,
- )
-
- response.raise_for_status()
- return response.json()
-```
+Follow from [Custom Guardrail](../proxy/guardrails/custom_guardrail#custom-guardrail) tutorial.
### Create the Init File
diff --git a/docs/my-website/docs/benchmarks.md b/docs/my-website/docs/benchmarks.md
index f00732450d1..4e4234949f8 100644
--- a/docs/my-website/docs/benchmarks.md
+++ b/docs/my-website/docs/benchmarks.md
@@ -125,18 +125,23 @@ class MyUser(HttpUser):
## LiteLLM vs Portkey Performance Comparison
**Test Configuration**: 4 CPUs, 8 GB RAM per instance | Load: 1k concurrent users, 500 ramp-up
+**Versions:** Portkey **v1.14.0** | LiteLLM **v1.79.1-stable**
+**Test Duration:** 5 minutes
### Multi-Instance (4×) Performance
-| Metric | Portkey (no DB) | LiteLLM (with DB) |
-| ------------------- | --------------- | ----------------- |
-| **Total Requests** | 293,796 | 312,405 |
-| **Failed Requests** | 0 | 0 |
-| **Median Latency** | 100 ms | 100 ms |
-| **p95 Latency** | 230 ms | 150 ms |
-| **p99 Latency** | 500 ms | 240 ms |
-| **Average Latency** | 123 ms | 111 ms |
-| **Current RPS** | 1,170.9 | 1,170 |
+| Metric | Portkey (no DB) | LiteLLM (with DB) | Comment |
+| ------------------- | --------------- | ----------------- | -------------- |
+| **Total Requests** | 293,796 | 312,405 | LiteLLM higher |
+| **Failed Requests** | 0 | 0 | Same |
+| **Median Latency** | 100 ms | 100 ms | Same |
+| **p95 Latency** | 230 ms | 150 ms | LiteLLM lower |
+| **p99 Latency** | 500 ms | 240 ms | LiteLLM lower |
+| **Average Latency** | 123 ms | 111 ms | LiteLLM lower |
+| **Current RPS** | 1,170.9 | 1,170 | Same |
+
+
+*Lower is better for latency metrics; higher is better for requests and RPS.*
### Technical Insights
diff --git a/docs/my-website/docs/embedding/supported_embedding.md b/docs/my-website/docs/embedding/supported_embedding.md
index e63d9403665..3019b723685 100644
--- a/docs/my-website/docs/embedding/supported_embedding.md
+++ b/docs/my-website/docs/embedding/supported_embedding.md
@@ -196,7 +196,7 @@ input=["good morning from litellm"]
]
}
],
- "model": "text-embedding-ada-002-v2",
+ "model": "text-embedding-ada-002",
"usage": {
"prompt_tokens": 10,
"total_tokens": 10
diff --git a/docs/my-website/docs/enterprise.md b/docs/my-website/docs/enterprise.md
index cc3466fc103..2eed0f53e59 100644
--- a/docs/my-website/docs/enterprise.md
+++ b/docs/my-website/docs/enterprise.md
@@ -3,7 +3,8 @@ import Image from '@theme/IdealImage';
# Enterprise
:::info
-✨ SSO is free for up to 5 users. After that, an enterprise license is required. [Get Started with Enterprise here](https://www.litellm.ai/enterprise)
+- ✨ SSO is free for up to 5 users. After that, an enterprise license is required. [Get Started with Enterprise here](https://www.litellm.ai/enterprise)
+- Who is Enterprise for? Companies giving access to 100+ users **OR** 10+ AI use-cases. If you're not sure, [get in touch with us](https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat) to discuss your needs.
:::
For companies that need SSO, user management and professional support for LiteLLM Proxy
@@ -16,7 +17,7 @@ Get free 7-day trial key [here](https://www.litellm.ai/enterprise#trial)
Includes all enterprise features.
-
+
[**Procurement available via AWS / Azure Marketplace**](./data_security.md#legalcompliance-faqs)
@@ -40,7 +41,7 @@ Self-Managed Enterprise deployments require our team to understand your exact ne
### How does deployment with Enterprise License work?
-You just deploy [our docker image](https://docs.litellm.ai/docs/proxy/deploy) and get an enterprise license key to add to your environment to unlock additional functionality (SSO, Prometheus metrics, etc.).
+You just deploy [our docker image](https://docs.litellm.ai/docs/proxy/deploy) and get an enterprise license key to add to your environment to unlock additional functionality (SSO, etc.).
```env
LITELLM_LICENSE="eyJ..."
diff --git a/docs/my-website/docs/extras/contributing_code.md b/docs/my-website/docs/extras/contributing_code.md
index f3a8271b14b..930a47eec7e 100644
--- a/docs/my-website/docs/extras/contributing_code.md
+++ b/docs/my-website/docs/extras/contributing_code.md
@@ -107,3 +107,18 @@ docker run \
litellm_test_image \
--config /app/config.yaml --detailed_debug
```
+### Running LiteLLM Proxy Locally
+
+1. cd into the `proxy/` directory
+
+```
+cd litellm/litellm/proxy
+```
+
+2. Run the proxy
+
+```shell
+python3 proxy_cli.py --config /path/to/config.yaml
+
+# RUNNING on http://0.0.0.0:4000
+```
\ No newline at end of file
diff --git a/docs/my-website/docs/image_edits.md b/docs/my-website/docs/image_edits.md
index 9a53da510f7..5a108aabf3a 100644
--- a/docs/my-website/docs/image_edits.md
+++ b/docs/my-website/docs/image_edits.md
@@ -16,7 +16,7 @@ LiteLLM provides image editing functionality that maps to OpenAI's `/images/edit
| Supported operations | Create image edits | Single and multiple images supported |
| Supported LiteLLM SDK Versions | 1.63.8+ | Gemini support requires 1.79.3+ |
| Supported LiteLLM Proxy Versions | 1.71.1+ | Gemini support requires 1.79.3+ |
-| Supported LLM providers | **OpenAI**, **Gemini (Google AI Studio)** | Gemini supports the new `gemini-2.5-flash-image` family |
+| Supported LLM providers | **OpenAI**, **Gemini (Google AI Studio)**, **Vertex AI** | Gemini supports the new `gemini-2.5-flash-image` family. Vertex AI supports both Gemini and Imagen models. |
#### ⚡️See all supported models and providers at [models.litellm.ai](https://models.litellm.ai/)
@@ -197,6 +197,53 @@ for idx, image_obj in enumerate(response.data):
f.write(base64.b64decode(image_obj.b64_json))
```
+
+
+
+
+#### Basic Image Edit (Gemini)
+```python showLineNumbers title="Vertex AI Gemini Image Edit"
+import os
+import litellm
+
+# Set Vertex AI credentials
+os.environ["VERTEXAI_PROJECT"] = "your-gcp-project-id"
+os.environ["VERTEXAI_LOCATION"] = "us-central1"
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/service-account.json"
+
+response = litellm.image_edit(
+ model="vertex_ai/gemini-2.5-flash",
+ image=open("original_image.png", "rb"),
+ prompt="Add neon lights in the background",
+ size="1024x1024",
+)
+
+print(response)
+```
+
+#### Image Edit with Imagen (Supports Masks)
+```python showLineNumbers title="Vertex AI Imagen Image Edit"
+import os
+import litellm
+
+# Set Vertex AI credentials
+os.environ["VERTEXAI_PROJECT"] = "your-gcp-project-id"
+os.environ["VERTEXAI_LOCATION"] = "us-central1"
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/path/to/service-account.json"
+
+# Imagen supports mask for inpainting
+response = litellm.image_edit(
+ model="vertex_ai/imagen-3.0-capability-001",
+ image=open("original_image.png", "rb"),
+ mask=open("mask_image.png", "rb"), # Optional: for inpainting
+ prompt="Turn this into watercolor style scenery",
+ n=2, # Number of variations
+ size="1024x1024",
+)
+
+print(response)
+```
+
@@ -302,6 +349,55 @@ curl -X POST "http://0.0.0.0:4000/v1/images/edits" \
-F "size=1024x1024"
```
+
+
+
+
+1. Add Vertex AI image edit models to your `config.yaml`:
+```yaml showLineNumbers title="Vertex AI Proxy Configuration"
+model_list:
+ - model_name: vertex-gemini-image-edit
+ litellm_params:
+ model: vertex_ai/gemini-2.5-flash
+ vertex_project: os.environ/VERTEXAI_PROJECT
+ vertex_location: os.environ/VERTEXAI_LOCATION
+ vertex_credentials: os.environ/GOOGLE_APPLICATION_CREDENTIALS
+
+ - model_name: vertex-imagen-image-edit
+ litellm_params:
+ model: vertex_ai/imagen-3.0-capability-001
+ vertex_project: os.environ/VERTEXAI_PROJECT
+ vertex_location: os.environ/VERTEXAI_LOCATION
+ vertex_credentials: os.environ/GOOGLE_APPLICATION_CREDENTIALS
+```
+
+2. Start the LiteLLM proxy server:
+```bash showLineNumbers title="Start LiteLLM Proxy Server"
+litellm --config /path/to/config.yaml
+```
+
+3. Make an image edit request:
+```bash showLineNumbers title="Vertex AI Gemini Proxy Image Edit"
+curl -X POST "http://0.0.0.0:4000/v1/images/edits" \
+ -H "Authorization: Bearer " \
+ -F "model=vertex-gemini-image-edit" \
+ -F "image=@original_image.png" \
+ -F "prompt=Add neon lights in the background" \
+ -F "size=1024x1024"
+```
+
+4. Imagen image edit with mask:
+```bash showLineNumbers title="Vertex AI Imagen Proxy Image Edit with Mask"
+curl -X POST "http://0.0.0.0:4000/v1/images/edits" \
+ -H "Authorization: Bearer " \
+ -F "model=vertex-imagen-image-edit" \
+ -F "image=@original_image.png" \
+ -F "mask=@mask_image.png" \
+ -F "prompt=Turn this into watercolor style scenery" \
+ -F "n=2" \
+ -F "size=1024x1024"
+```
+
diff --git a/docs/my-website/docs/mcp.md b/docs/my-website/docs/mcp.md
index c735b8ecdd9..408560e5c0a 100644
--- a/docs/my-website/docs/mcp.md
+++ b/docs/my-website/docs/mcp.md
@@ -211,11 +211,12 @@ mcp_servers:
oauth2_example:
url: "https://my-mcp-server.com/mcp"
auth_type: "oauth2" # 👈 KEY CHANGE
- authorization_url: "https://my-mcp-server.com/oauth/authorize" # optional for client-credentials
- token_url: "https://my-mcp-server.com/oauth/token" # required
+ authorization_url: "https://my-mcp-server.com/oauth/authorize" # optional override
+ token_url: "https://my-mcp-server.com/oauth/token" # optional override
+ registration_url: "https://my-mcp-server.com/oauth/register" # optional override
client_id: os.environ/OAUTH_CLIENT_ID
client_secret: os.environ/OAUTH_CLIENT_SECRET
- scopes: ["tool.read", "tool.write"] # optional
+ scopes: ["tool.read", "tool.write"] # optional override
bearer_example:
url: "https://my-mcp-server.com/mcp"
@@ -325,6 +326,10 @@ mcp_servers:
| `spec_path` | Yes | Path or URL to your OpenAPI specification file (JSON or YAML) |
| `auth_type` | No | Authentication type: `none`, `api_key`, `bearer_token`, `basic`, `authorization` |
| `auth_value` | No | Authentication value (required if `auth_type` is set) |
+| `authorization_url` | No | For `auth_type: oauth2`. Optional override; if omitted LiteLLM auto-discovers it. |
+| `token_url` | No | For `auth_type: oauth2`. Optional override; if omitted LiteLLM auto-discovers it. |
+| `registration_url` | No | For `auth_type: oauth2`. Optional override; if omitted LiteLLM auto-discovers it. |
+| `scopes` | No | For `auth_type: oauth2`. Optional override; if omitted LiteLLM uses the scopes advertised by the server. |
| `description` | No | Optional description for the MCP server |
| `allowed_tools` | No | List of specific tools to allow (see [MCP Tool Filtering](#mcp-tool-filtering)) |
| `disallowed_tools` | No | List of specific tools to block (see [MCP Tool Filtering](#mcp-tool-filtering)) |
@@ -1216,7 +1221,6 @@ curl --location 'http://localhost:4000/github_mcp/mcp' \
LiteLLM v 1.77.6 added support for OAuth 2.0 Client Credentials for MCP servers.
-
This configuration is currently available on the config.yaml, with UI support coming soon.
```yaml
@@ -1224,19 +1228,77 @@ mcp_servers:
github_mcp:
url: "https://api.githubcopilot.com/mcp"
auth_type: oauth2
- authorization_url: https://github.com/login/oauth/authorize
- token_url: https://github.com/login/oauth/access_token
client_id: os.environ/GITHUB_OAUTH_CLIENT_ID
client_secret: os.environ/GITHUB_OAUTH_CLIENT_SECRET
- scopes: ["public_repo", "user:email"]
```
-**Note**
-In the future, users will only need to specify the `url` of the MCP server.
-LiteLLM will automatically resolve the corresponding `authorization_url`, `token_url`, and `registration_url` based on the MCP server metadata (e.g., `.well-known/oauth-authorization-server` or `oauth-protected-resource`).
-
[**See Claude Code Tutorial**](./tutorials/claude_responses_api#connecting-mcp-servers)
+### How It Works
+
+```mermaid
+sequenceDiagram
+ participant Browser as User-Agent (Browser)
+ participant Client as Client
+ participant LiteLLM as LiteLLM Proxy
+ participant MCP as MCP Server (Resource Server)
+ participant Auth as Authorization Server
+
+ Note over Client,LiteLLM: Step 1 – Resource discovery
+ Client->>LiteLLM: GET /.well-known/oauth-protected-resource/{mcp_server_name}/mcp
+ LiteLLM->>Client: Return resource metadata
+
+ Note over Client,LiteLLM: Step 2 – Authorization server discovery
+ Client->>LiteLLM: GET /.well-known/oauth-authorization-server/{mcp_server_name}
+ LiteLLM->>Client: Return authorization server metadata
+
+ Note over Client,Auth: Step 3 – Dynamic client registration
+ Client->>LiteLLM: POST /{mcp_server_name}/register
+ LiteLLM->>Auth: Forward registration request
+ Auth->>LiteLLM: Issue client credentials
+ LiteLLM->>Client: Return client credentials
+
+ Note over Client,Browser: Step 4 – User authorization (PKCE)
+ Client->>Browser: Open authorization URL + code_challenge + resource
+ Browser->>Auth: Authorization request
+ Note over Auth: User authorizes
+ Auth->>Browser: Redirect with authorization code
+ Browser->>LiteLLM: Callback to LiteLLM with code
+ LiteLLM->>Browser: Redirect back with authorization code
+ Browser->>Client: Callback with authorization code
+
+ Note over Client,Auth: Step 5 – Token exchange
+ Client->>LiteLLM: Token request + code_verifier + resource
+ LiteLLM->>Auth: Forward token request
+ Auth->>LiteLLM: Access (and refresh) token
+ LiteLLM->>Client: Return tokens
+
+ Note over Client,MCP: Step 6 – Authenticated MCP call
+ Client->>LiteLLM: MCP request with access token + LiteLLM API key
+ LiteLLM->>MCP: MCP request with Bearer token
+ MCP-->>LiteLLM: MCP response
+ LiteLLM-->>Client: Return MCP response
+```
+
+**Participants**
+
+- **Client** – The MCP-capable AI agent (e.g., Claude Code, Cursor, or another IDE/agent) that initiates OAuth discovery, authorization, and tool invocations on behalf of the user.
+- **LiteLLM Proxy** – Mediates all OAuth discovery, registration, token exchange, and MCP traffic while protecting stored credentials.
+- **Authorization Server** – Issues OAuth 2.0 tokens via dynamic client registration, PKCE authorization, and token endpoints.
+- **MCP Server (Resource Server)** – The protected MCP endpoint that receives LiteLLM’s authenticated JSON-RPC requests.
+- **User-Agent (Browser)** – Temporarily involved so the end user can grant consent during the authorization step.
+
+**Flow Steps**
+
+1. **Resource Discovery**: The client fetches MCP resource metadata from LiteLLM’s `.well-known/oauth-protected-resource` endpoint to understand scopes and capabilities.
+2. **Authorization Server Discovery**: The client retrieves the OAuth server metadata (token endpoint, authorization endpoint, supported PKCE methods) through LiteLLM’s `.well-known/oauth-authorization-server` endpoint.
+3. **Dynamic Client Registration**: The client registers through LiteLLM, which forwards the request to the authorization server (RFC 7591). If the provider doesn’t support dynamic registration, you can pre-store `client_id`/`client_secret` in LiteLLM (e.g., GitHub MCP) and the flow proceeds the same way.
+4. **User Authorization**: The client launches a browser session (with code challenge and resource hints). The user approves access, the authorization server sends the code through LiteLLM back to the client.
+5. **Token Exchange**: The client calls LiteLLM with the authorization code, code verifier, and resource. LiteLLM exchanges them with the authorization server and returns the issued access/refresh tokens.
+6. **MCP Invocation**: With a valid token, the client sends the MCP JSON-RPC request (plus LiteLLM API key) to LiteLLM, which forwards it to the MCP server and relays the tool response.
+
+See the official [MCP Authorization Flow](https://modelcontextprotocol.io/specification/2025-06-18/basic/authorization#authorization-flow-steps) for additional reference.
+
## Using your MCP with client side credentials
Use this if you want to pass a client side authentication token to LiteLLM to then pass to your MCP to auth to your MCP.
@@ -1887,4 +1949,4 @@ async with stdio_client(server_params) as (read, write):
```
-
\ No newline at end of file
+
diff --git a/docs/my-website/docs/providers/anthropic.md b/docs/my-website/docs/providers/anthropic.md
index 0ea042e5d98..afcb6a34d9c 100644
--- a/docs/my-website/docs/providers/anthropic.md
+++ b/docs/my-website/docs/providers/anthropic.md
@@ -953,6 +953,30 @@ except Exception as e:
s/o @[Shekhar Patnaik](https://www.linkedin.com/in/patnaikshekhar) for requesting this!
+### Context Management (Beta)
+
+Anthropic’s [context editing](https://docs.claude.com/en/docs/build-with-claude/context-editing) API lets you automatically clear older tool results or thinking blocks. LiteLLM now forwards the native `context_management` payload when you call Anthropic models, and automatically attaches the required `context-management-2025-06-27` beta header.
+
+```python
+from litellm import completion
+
+response = completion(
+ model="anthropic/claude-sonnet-4-20250514",
+ messages=[{"role": "user", "content": "Summarize the latest tool results"}],
+ context_management={
+ "edits": [
+ {
+ "type": "clear_tool_uses_20250919",
+ "trigger": {"type": "input_tokens", "value": 30000},
+ "keep": {"type": "tool_uses", "value": 3},
+ "clear_at_least": {"type": "input_tokens", "value": 5000},
+ "exclude_tools": ["web_search"],
+ }
+ ]
+ },
+)
+```
+
### Anthropic Hosted Tools (Computer, Text Editor, Web Search, Memory)
diff --git a/docs/my-website/docs/providers/azure_ai_speech.md b/docs/my-website/docs/providers/azure_ai_speech.md
index 434a796a2fb..22db98cfac5 100644
--- a/docs/my-website/docs/providers/azure_ai_speech.md
+++ b/docs/my-website/docs/providers/azure_ai_speech.md
@@ -136,6 +136,89 @@ response = speech(
| `wav` | riff-24khz-16bit-mono-pcm | 24kHz |
| `pcm` | raw-24khz-16bit-mono-pcm | 24kHz |
+## Passing Raw SSML
+
+LiteLLM automatically detects when your `input` contains SSML (by checking for `` tags) and passes it through to Azure without any transformation. This gives you complete control over speech synthesis.
+
+**When to use raw SSML:**
+- Using the `` element with multilingual voices to translate text (e.g., English text → Spanish speech)
+- Complex SSML structures with multiple voices or prosody changes
+- Fine-grained control over pronunciation, breaks, emphasis, and other speech features
+
+### LiteLLM SDK
+
+```python showLineNumbers title="Raw SSML for Multilingual Translation"
+from litellm import speech
+
+# Use element to convert English text to Spanish speech
+# The element forces the output language regardless of input text language
+language_code = "es-ES"
+text = "Hello, how are you today?" # English text
+voice = "en-US-AvaMultilingualNeural"
+
+ssml = f"""
+
+ {text}
+
+"""
+
+response = speech(
+ model="azure/speech/azure-tts",
+ voice=voice,
+ input=ssml, # LiteLLM auto-detects SSML and sends as-is
+ api_base="https://eastus.tts.speech.microsoft.com",
+ api_key=os.environ["AZURE_TTS_API_KEY"],
+)
+response.stream_to_file("speech.mp3")
+```
+
+```python showLineNumbers title="Raw SSML with Complex Features"
+from litellm import speech
+
+# Complex SSML with multiple prosody adjustments
+ssml = """
+
+
+
+ Welcome to our service!
+
+
+
+
+ How can I help you today?
+
+
+"""
+
+response = speech(
+ model="azure/speech/azure-tts",
+ voice="en-US-JennyNeural",
+ input=ssml, # LiteLLM detects and passes through unchanged
+ api_base="https://eastus.tts.speech.microsoft.com",
+ api_key=os.environ["AZURE_TTS_API_KEY"],
+)
+response.stream_to_file("speech.mp3")
+```
+
+### LiteLLM Proxy
+
+```bash
+curl http://0.0.0.0:4000/v1/audio/speech \
+ -H "Authorization: Bearer sk-1234" \
+ -H "Content-Type: application/json" \
+ -d '{
+ "model": "azure-speech",
+ "voice": "en-US-AvaMultilingualNeural",
+ "input": "Hello, how are you today?"
+ }' \
+ --output speech.mp3
+```
+
+
## Sending Azure-Specific Params
Azure AI Speech supports advanced SSML features through optional parameters:
diff --git a/docs/my-website/docs/providers/fal_ai.md b/docs/my-website/docs/providers/fal_ai.md
index e50ef919da0..da0fd19123b 100644
--- a/docs/my-website/docs/providers/fal_ai.md
+++ b/docs/my-website/docs/providers/fal_ai.md
@@ -31,10 +31,14 @@ Get your API key from [fal.ai](https://fal.ai/).
| Model Name | Description | Documentation |
|------------|-------------|---------------|
+| `fal_ai/fal-ai/flux-pro/v1.1` | FLUX Pro v1.1 - Balanced speed and quality | [Docs ↗](https://fal.ai/models/fal-ai/flux-pro/v1.1) |
| `fal_ai/flux/schnell` | Flux Schnell - Low-latency generation with `image_size` support | [Docs ↗](https://fal.ai/models/fal-ai/flux/schnell) |
+| `fal_ai/fal-ai/bytedance/seedream/v3/text-to-image` | ByteDance Seedream v3 - Text-to-image with `image_size` control | [Docs ↗](https://fal.ai/models/fal-ai/bytedance/seedream/v3/text-to-image) |
+| `fal_ai/fal-ai/bytedance/dreamina/v3.1/text-to-image` | ByteDance Dreamina v3.1 - Text-to-image with `image_size` control | [Docs ↗](https://fal.ai/models/fal-ai/bytedance/dreamina/v3.1/text-to-image) |
| `fal_ai/fal-ai/flux-pro/v1.1-ultra` | FLUX Pro v1.1 Ultra - High-quality image generation | [Docs ↗](https://fal.ai/models/fal-ai/flux-pro/v1.1-ultra) |
| `fal_ai/fal-ai/imagen4/preview` | Google's Imagen 4 - Highest quality model | [Docs ↗](https://fal.ai/models/fal-ai/imagen4/preview) |
| `fal_ai/fal-ai/recraft/v3/text-to-image` | Recraft v3 - Multiple style options | [Docs ↗](https://fal.ai/models/fal-ai/recraft/v3/text-to-image) |
+| `fal_ai/fal-ai/ideogram/v3` | Ideogram v3 - Lettering-first creative model (Balanced: $0.06/image) | [Docs ↗](https://fal.ai/models/fal-ai/ideogram/v3) |
| `fal_ai/fal-ai/stable-diffusion-v35-medium` | Stable Diffusion v3.5 Medium | [Docs ↗](https://fal.ai/models/fal-ai/stable-diffusion-v35-medium) |
| `fal_ai/bria/text-to-image/3.2` | Bria 3.2 - Commercial-grade generation | [Docs ↗](https://fal.ai/models/bria/text-to-image/3.2) |
diff --git a/docs/my-website/docs/providers/gemini.md b/docs/my-website/docs/providers/gemini.md
index c5014fc2ff3..fd20e907d3b 100644
--- a/docs/my-website/docs/providers/gemini.md
+++ b/docs/my-website/docs/providers/gemini.md
@@ -70,7 +70,11 @@ LiteLLM translates OpenAI's `reasoning_effort` to Gemini's `thinking` parameter.
Note: Reasoning cannot be turned off on Gemini 2.5 Pro models.
:::
-**Mapping**
+:::tip Gemini 3 Models
+For **Gemini 3+ models** (e.g., `gemini-3-pro-preview`), LiteLLM automatically maps `reasoning_effort` to the new `thinking_level` parameter instead of `thinking_budget`. The `thinking_level` parameter uses `"low"` or `"high"` values for better control over reasoning depth.
+:::
+
+**Mapping for Gemini 2.5 and earlier models**
| reasoning_effort | thinking | Notes |
| ---------------- | -------- | ----- |
@@ -80,6 +84,17 @@ Note: Reasoning cannot be turned off on Gemini 2.5 Pro models.
| "medium" | "budget_tokens": 2048 | |
| "high" | "budget_tokens": 4096 | |
+**Mapping for Gemini 3+ models**
+
+| reasoning_effort | thinking_level | Notes |
+| ---------------- | -------------- | ----- |
+| "minimal" | "low" | Minimizes latency and cost |
+| "low" | "low" | Best for simple instruction following or chat |
+| "medium" | "high" | Maps to high (medium not yet available) |
+| "high" | "high" | Maximizes reasoning depth |
+| "disable" | "low" | Cannot fully disable thinking in Gemini 3 |
+| "none" | "low" | Cannot fully disable thinking in Gemini 3 |
+
@@ -137,6 +152,59 @@ curl http://0.0.0.0:4000/v1/chat/completions \
+### Gemini 3+ Models - `thinking_level` Parameter
+
+For Gemini 3+ models (e.g., `gemini-3-pro-preview`), you can use the new `thinking_level` parameter directly:
+
+
+
+
+```python
+from litellm import completion
+
+# Use thinking_level for Gemini 3 models
+resp = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=[{"role": "user", "content": "Solve this complex math problem step by step."}],
+ reasoning_effort="high", # Options: "low" or "high"
+)
+
+# Low thinking level for faster, simpler tasks
+resp = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=[{"role": "user", "content": "What is the weather today?"}],
+ reasoning_effort="low", # Minimizes latency and cost
+)
+```
+
+
+
+
+
+```bash
+curl http://0.0.0.0:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer " \
+ -d '{
+ "model": "gemini-3-pro-preview",
+ "messages": [{"role": "user", "content": "Solve this complex problem."}],
+ "reasoning_effort": "high"
+ }'
+```
+
+
+
+
+:::warning
+**Temperature Recommendation for Gemini 3 Models**
+
+For Gemini 3 models, LiteLLM defaults `temperature` to `1.0` and strongly recommends keeping it at this default. Setting `temperature < 1.0` can cause:
+- Infinite loops
+- Degraded reasoning performance
+- Failure on complex tasks
+
+LiteLLM will automatically set `temperature=1.0` if not specified for Gemini 3+ models.
+:::
**Expected Response**
@@ -951,6 +1019,295 @@ curl -X POST 'http://0.0.0.0:4000/chat/completions' \
+## Thought Signatures
+
+Thought signatures are encrypted representations of the model's internal reasoning process for a given turn in a conversation. By passing thought signatures back to the model in subsequent requests, you provide it with the context of its previous thoughts, allowing it to build upon its reasoning and maintain a coherent line of inquiry.
+
+Thought signatures are particularly important for multi-turn function calling scenarios where the model needs to maintain context across multiple tool invocations.
+
+### How Thought Signatures Work
+
+- **Function calls with signatures**: When Gemini returns a function call, it includes a `thought_signature` in the response
+- **Preservation**: LiteLLM automatically extracts and stores thought signatures in `provider_specific_fields` of tool calls
+- **Return in conversation history**: When you include the assistant's message with tool calls in subsequent requests, LiteLLM automatically preserves and returns the thought signatures to Gemini
+- **Parallel function calls**: Only the first function call in a parallel set has a thought signature
+- **Sequential function calls**: Each function call in a multi-step sequence has its own signature
+
+### Enabling Thought Signatures
+
+To enable thought signatures, you need to enable thinking/reasoning:
+
+
+
+
+```python
+from litellm import completion
+
+response = completion(
+ model="gemini/gemini-2.5-flash",
+ messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
+ tools=[...],
+ reasoning_effort="low", # Enable thinking to get thought signatures
+)
+```
+
+
+
+
+```bash
+curl http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gemini-2.5-flash",
+ "messages": [{"role": "user", "content": "What'\''s the weather in Tokyo?"}],
+ "tools": [...],
+ "reasoning_effort": "low"
+ }'
+```
+
+
+
+
+### Multi-Turn Function Calling with Thought Signatures
+
+When building conversation history for multi-turn function calling, you must include the thought signatures from previous responses. LiteLLM handles this automatically when you append the full assistant message to your conversation history.
+
+
+
+
+```python
+from openai import OpenAI
+import json
+
+client = OpenAI(api_key="sk-1234", base_url="http://localhost:4000")
+
+def get_current_temperature(location: str) -> dict:
+ """Gets the current weather temperature for a given location."""
+ return {"temperature": 30, "unit": "celsius"}
+
+def set_thermostat_temperature(temperature: int) -> dict:
+ """Sets the thermostat to a desired temperature."""
+ return {"status": "success"}
+
+get_weather_declaration = {
+ "name": "get_current_temperature",
+ "description": "Gets the current weather temperature for a given location.",
+ "parameters": {
+ "type": "object",
+ "properties": {"location": {"type": "string"}},
+ "required": ["location"],
+ },
+}
+
+set_thermostat_declaration = {
+ "name": "set_thermostat_temperature",
+ "description": "Sets the thermostat to a desired temperature.",
+ "parameters": {
+ "type": "object",
+ "properties": {"temperature": {"type": "integer"}},
+ "required": ["temperature"],
+ },
+}
+
+# Initial request
+messages = [
+ {"role": "user", "content": "If it's too hot or too cold in London, set the thermostat to a comfortable level."}
+]
+
+response = client.chat.completions.create(
+ model="gemini-2.5-flash",
+ messages=messages,
+ tools=[get_weather_declaration, set_thermostat_declaration],
+ reasoning_effort="low"
+)
+
+# Append the assistant's message (includes thought signatures automatically)
+messages.append(response.choices[0].message)
+
+# Execute tool calls and append results
+for tool_call in response.choices[0].message.tool_calls:
+ if tool_call.function.name == "get_current_temperature":
+ result = get_current_temperature(**json.loads(tool_call.function.arguments))
+ messages.append({
+ "role": "tool",
+ "content": json.dumps(result),
+ "tool_call_id": tool_call.id
+ })
+
+# Second request - thought signatures are automatically preserved
+response2 = client.chat.completions.create(
+ model="gemini-2.5-flash",
+ messages=messages,
+ tools=[get_weather_declaration, set_thermostat_declaration],
+ reasoning_effort="low"
+)
+
+print(response2.choices[0].message.content)
+```
+
+
+
+
+```bash
+# Step 1: Initial request
+curl --location 'http://localhost:4000/v1/chat/completions' \
+ --header 'Content-Type: application/json' \
+ --header 'Authorization: Bearer sk-1234' \
+ --data '{
+ "model": "gemini-2.5-flash",
+ "messages": [
+ {
+ "role": "user",
+ "content": "If it'\''s too hot or too cold in London, set the thermostat to a comfortable level."
+ }
+ ],
+ "tools": [
+ {
+ "type": "function",
+ "function": {
+ "name": "get_current_temperature",
+ "description": "Gets the current weather temperature for a given location.",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "location": {"type": "string"}
+ },
+ "required": ["location"]
+ }
+ }
+ },
+ {
+ "type": "function",
+ "function": {
+ "name": "set_thermostat_temperature",
+ "description": "Sets the thermostat to a desired temperature.",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "temperature": {"type": "integer"}
+ },
+ "required": ["temperature"]
+ }
+ }
+ }
+ ],
+ "tool_choice": "auto",
+ "reasoning_effort": "low"
+ }'
+```
+
+The response will include tool calls with thought signatures in `provider_specific_fields`:
+
+```json
+{
+ "choices": [{
+ "message": {
+ "role": "assistant",
+ "tool_calls": [{
+ "id": "call_abc123",
+ "type": "function",
+ "function": {
+ "name": "get_current_temperature",
+ "arguments": "{\"location\": \"London\"}"
+ },
+ "index": 0,
+ "provider_specific_fields": {
+ "thought_signature": "CpcHAdHtim9+q4rstcbvQC0ic4x1/vqQlCJWgE+UZ6dTLYGHMMBkF/AxqL5UmP6SY46uYC8t4BTFiXG5zkw6EMJ...=="
+ }
+ }]
+ }
+ }]
+}
+```
+
+```bash
+# Step 2: Follow-up request with tool response
+# Include the assistant message from Step 1 (with thought signatures in provider_specific_fields)
+curl --location 'http://localhost:4000/v1/chat/completions' \
+ --header 'Content-Type: application/json' \
+ --header 'Authorization: Bearer sk-1234' \
+ --data '{
+ "model": "gemini-2.5-flash",
+ "messages": [
+ {
+ "role": "user",
+ "content": "If it'\''s too hot or too cold in London, set the thermostat to a comfortable level."
+ },
+ {
+ "role": "assistant",
+ "content": null,
+ "tool_calls": [
+ {
+ "id": "call_c130b9f8c2c042e9b65e39a88245",
+ "type": "function",
+ "function": {
+ "name": "get_current_temperature",
+ "arguments": "{\"location\": \"London\"}"
+ },
+ "index": 0,
+ "provider_specific_fields": {
+ "thought_signature": "CpcHAdHtim9+q4rstcbvQC0ic4x1/vqQlCJWgE+UZ6dTLYGHMMBkF/AxqL5UmP6SY46uYC8t4BTFiXG5zkw6EMJ...=="
+ }
+ }
+ ]
+ },
+ {
+ "role": "tool",
+ "content": "{\"temperature\": 30, \"unit\": \"celsius\"}",
+ "tool_call_id": "call_c130b9f8c2c042e9b65e39a88245"
+ }
+ ],
+ "tools": [
+ {
+ "type": "function",
+ "function": {
+ "name": "get_current_temperature",
+ "description": "Gets the current weather temperature for a given location.",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "location": {"type": "string"}
+ },
+ "required": ["location"]
+ }
+ }
+ },
+ {
+ "type": "function",
+ "function": {
+ "name": "set_thermostat_temperature",
+ "description": "Sets the thermostat to a desired temperature.",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "temperature": {"type": "integer"}
+ },
+ "required": ["temperature"]
+ }
+ }
+ }
+ ],
+ "tool_choice": "auto",
+ "reasoning_effort": "low"
+ }'
+```
+
+
+
+
+### Important Notes
+
+1. **Automatic Handling**: LiteLLM automatically extracts thought signatures from Gemini responses and preserves them when you include assistant messages in conversation history. You don't need to manually extract or manage them.
+
+2. **Parallel Function Calls**: When the model makes parallel function calls, only the first function call will have a thought signature. Subsequent parallel calls won't have signatures.
+
+3. **Sequential Function Calls**: In multi-step function calling scenarios, each step's first function call will have its own thought signature that must be preserved.
+
+4. **Required for Context**: Thought signatures are essential for maintaining reasoning context across multi-turn conversations with function calling. Without them, the model may lose context of its previous reasoning.
+
+5. **Format**: Thought signatures are stored in `provider_specific_fields.thought_signature` of tool calls in the response, and are automatically included when you append the assistant message to your conversation history.
+
## JSON Mode
@@ -1022,6 +1379,56 @@ LiteLLM Supports the following image types passed in `url`
- Images with direct links - https://storage.googleapis.com/github-repo/img/gemini/intro/landmark3.jpg
- Image in local storage - ./localimage.jpeg
+## Image Resolution Control (Gemini 3+)
+
+For Gemini 3+ models, LiteLLM supports per-part media resolution control using OpenAI's `detail` parameter. This allows you to specify different resolution levels for individual images in your request.
+
+**Supported `detail` values:**
+- `"low"` - Maps to `media_resolution: "low"` (280 tokens for images, 70 tokens per frame for videos)
+- `"high"` - Maps to `media_resolution: "high"` (1120 tokens for images)
+- `"auto"` or `None` - Model decides optimal resolution (no `media_resolution` set)
+
+**Usage Example:**
+
+```python
+from litellm import completion
+
+messages = [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image_url",
+ "image_url": {
+ "url": "https://example.com/chart.png",
+ "detail": "high" # High resolution for detailed chart analysis
+ }
+ },
+ {
+ "type": "text",
+ "text": "Analyze this chart"
+ },
+ {
+ "type": "image_url",
+ "image_url": {
+ "url": "https://example.com/icon.png",
+ "detail": "low" # Low resolution for simple icon
+ }
+ }
+ ]
+ }
+]
+
+response = completion(
+ model="gemini/gemini-3-pro-preview",
+ messages=messages,
+)
+```
+
+:::info
+**Per-Part Resolution:** Each image in your request can have its own `detail` setting, allowing mixed-resolution requests (e.g., a high-res chart alongside a low-res icon). This feature is only available for Gemini 3+ models.
+:::
+
## Sample Usage
```python
import os
diff --git a/docs/my-website/docs/providers/oci.md b/docs/my-website/docs/providers/oci.md
index cea5d6824a0..ce6fe18dd6f 100644
--- a/docs/my-website/docs/providers/oci.md
+++ b/docs/my-website/docs/providers/oci.md
@@ -58,12 +58,11 @@ This method is an alternative when using the LiteLLM SDK on Oracle Cloud Infrast
## Usage
-
+
Input the parameters obtained from the OCI signing key creation process into the `completion` function:
```python
-import os
from litellm import completion
messages = [{"role": "user", "content": "Hey! how's it going?"}]
@@ -86,7 +85,7 @@ print(response)
```
-
+
Use the OCI SDK `Signer` for authentication:
@@ -153,7 +152,6 @@ For applications running on OCI compute instances:
from litellm import completion
from oci.auth.signers import InstancePrincipalsSecurityTokenSigner
-oci.auth.signers.get_oke_workload_identity_resource_principal_signer()
# Use instance principal authentication
signer = InstancePrincipalsSecurityTokenSigner()
@@ -168,7 +166,7 @@ response = completion(
print(response)
```
-**Use workload identity authentication**
+**Workload Identity Authentication**
For applications running in Oracle Kubernetes Engine (OKE):
@@ -176,7 +174,7 @@ For applications running in Oracle Kubernetes Engine (OKE):
from litellm import completion
from oci.auth.signers import get_oke_workload_identity_resource_principal_signer
-# Use instance principal authentication
+# Use workload identity authentication
signer = get_oke_workload_identity_resource_principal_signer()
messages = [{"role": "user", "content": "Hey! how's it going?"}]
@@ -196,10 +194,9 @@ print(response)
Just set `stream=True` when calling completion.
-
+
```python
-import os
from litellm import completion
messages = [{"role": "user", "content": "Hey! how's it going?"}]
@@ -224,7 +221,7 @@ for chunk in response:
```
-
+
```python
from litellm import completion
@@ -258,7 +255,27 @@ for chunk in response:
### Using Cohere Models
-
+
+
+```python
+from litellm import completion
+
+messages = [{"role": "user", "content": "Explain quantum computing"}]
+response = completion(
+ model="oci/cohere.command-latest",
+ messages=messages,
+ oci_region="us-chicago-1",
+ oci_user=,
+ oci_fingerprint=,
+ oci_tenancy=,
+ oci_key=,
+ oci_compartment_id=,
+)
+print(response)
+```
+
+
+
```python
from litellm import completion
@@ -283,19 +300,28 @@ print(response)
```
-
+
+
+## Using Dedicated Endpoints
+
+OCI supports dedicated endpoints for hosting models. Use the `oci_serving_mode="DEDICATED"` parameter along with `oci_endpoint_id` to specify the endpoint ID.
+
+
+
```python
from litellm import completion
-messages = [{"role": "user", "content": "Explain quantum computing"}]
+messages = [{"role": "user", "content": "Hey! how's it going?"}]
response = completion(
- model="oci/cohere.command-latest",
+ model="oci/xai.grok-4", # Must match the model type hosted on the endpoint
messages=messages,
- oci_region="us-chicago-1",
+ oci_region=,
oci_user=,
oci_fingerprint=,
oci_tenancy=,
+ oci_serving_mode="DEDICATED",
+ oci_endpoint_id="ocid1.generativeaiendpoint.oc1...", # Your dedicated endpoint OCID
oci_key=,
oci_compartment_id=,
)
@@ -303,4 +329,69 @@ print(response)
```
-
\ No newline at end of file
+
+
+```python
+from litellm import completion
+from oci.signer import Signer
+
+signer = Signer(
+ tenancy="ocid1.tenancy.oc1..",
+ user="ocid1.user.oc1..",
+ fingerprint="xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx:xx",
+ private_key_file_location="~/.oci/key.pem",
+)
+
+messages = [{"role": "user", "content": "Hey! how's it going?"}]
+response = completion(
+ model="oci/xai.grok-4", # Must match the model type hosted on the endpoint
+ messages=messages,
+ oci_signer=signer,
+ oci_region="us-chicago-1",
+ oci_serving_mode="DEDICATED",
+ oci_endpoint_id="ocid1.generativeaiendpoint.oc1...", # Your dedicated endpoint OCID
+ oci_compartment_id="",
+)
+print(response)
+```
+
+
+
+
+**Important:** When using `oci_serving_mode="DEDICATED"`:
+- The `model` parameter **must match the type of model hosted on your dedicated endpoint** (e.g., use `"oci/cohere.command-latest"` for Cohere models, `"oci/xai.grok-4"` for Grok models)
+- The model name determines the API format and vendor-specific handling (Cohere vs Generic)
+- The `oci_endpoint_id` parameter specifies your dedicated endpoint's OCID
+- If `oci_endpoint_id` is not provided, the `model` parameter will be used as the endpoint ID (for backward compatibility)
+
+**Example with Cohere Dedicated Endpoint:**
+```python
+# For a dedicated endpoint hosting a Cohere model
+response = completion(
+ model="oci/cohere.command-latest", # Use Cohere model name to get Cohere API format
+ messages=messages,
+ oci_region="us-chicago-1",
+ oci_user=,
+ oci_fingerprint=,
+ oci_tenancy=,
+ oci_serving_mode="DEDICATED",
+ oci_endpoint_id="ocid1.generativeaiendpoint.oc1...", # Your Cohere endpoint OCID
+ oci_key=,
+ oci_compartment_id=,
+)
+```
+
+## Optional Parameters
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `oci_region` | string | `us-ashburn-1` | OCI region where the GenAI service is deployed |
+| `oci_serving_mode` | string | `ON_DEMAND` | Service mode: `ON_DEMAND` for managed models or `DEDICATED` for dedicated endpoints |
+| `oci_endpoint_id` | string | Same as `model` | (For DEDICATED mode) The OCID of your dedicated endpoint |
+| `oci_compartment_id` | string | **Required** | The OCID of the OCI compartment containing your resources |
+| `oci_user` | string | - | (Manual auth) The OCID of the OCI user |
+| `oci_fingerprint` | string | - | (Manual auth) The fingerprint of the API signing key |
+| `oci_tenancy` | string | - | (Manual auth) The OCID of your OCI tenancy |
+| `oci_key` | string | - | (Manual auth) The private key content as a string |
+| `oci_key_file` | string | - | (Manual auth) Path to the private key file |
+| `oci_signer` | object | - | (SDK auth) OCI SDK Signer object for authentication |
\ No newline at end of file
diff --git a/docs/my-website/docs/providers/openai.md b/docs/my-website/docs/providers/openai.md
index e288f511558..2163d5e6119 100644
--- a/docs/my-website/docs/providers/openai.md
+++ b/docs/my-website/docs/providers/openai.md
@@ -176,6 +176,9 @@ os.environ["OPENAI_BASE_URL"] = "https://your_host/v1" # OPTIONAL
| gpt-5-mini-2025-08-07 | `response = completion(model="gpt-5-mini-2025-08-07", messages=messages)` |
| gpt-5-nano-2025-08-07 | `response = completion(model="gpt-5-nano-2025-08-07", messages=messages)` |
| gpt-5-pro | `response = completion(model="gpt-5-pro", messages=messages)` |
+| gpt-5.1 | `response = completion(model="gpt-5.1", messages=messages)` |
+| gpt-5.1-codex | `response = completion(model="gpt-5.1-codex", messages=messages)` |
+| gpt-5.1-codex-mini | `response = completion(model="gpt-5.1-codex-mini", messages=messages)` |
| gpt-4.1 | `response = completion(model="gpt-4.1", messages=messages)` |
| gpt-4.1-mini | `response = completion(model="gpt-4.1-mini", messages=messages)` |
| gpt-4.1-nano | `response = completion(model="gpt-4.1-nano", messages=messages)` |
@@ -477,6 +480,8 @@ curl -X POST 'http://0.0.0.0:4000/chat/completions' \
| `gpt-5-mini` | `medium` | `none`, `minimal`, `low`, `medium`, `high` |
| `gpt-5-nano` | `none` | `none`, `low`, `medium`, `high` |
| `gpt-5-codex` | `adaptive` | `low`, `medium`, `high` (no `minimal`) |
+| `gpt-5.1-codex` | `adaptive` | `low`, `medium`, `high` (no `minimal`) |
+| `gpt-5.1-codex-mini` | `adaptive` | `low`, `medium`, `high` (no `minimal`) |
| `gpt-5-pro` | `high` | `high` only |
**Note:**
@@ -486,6 +491,55 @@ curl -X POST 'http://0.0.0.0:4000/chat/completions' \
See [OpenAI Reasoning documentation](https://platform.openai.com/docs/guides/reasoning) for more details on organization verification requirements.
+### Verbosity Control for GPT-5 Models
+
+The `verbosity` parameter controls the length and detail of responses from GPT-5 family models. It accepts three values: `"low"`, `"medium"`, or `"high"`.
+
+**Supported models:** `gpt-5`, `gpt-5.1`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-pro`
+
+**Note:** GPT-5-Codex models (`gpt-5-codex`, `gpt-5.1-codex`, `gpt-5.1-codex-mini`) do **not** support the `verbosity` parameter.
+
+**Use cases:**
+- **`"low"`**: Best for concise answers or simple code generation (e.g., SQL queries)
+- **`"medium"`**: Default - balanced output length
+- **`"high"`**: Use when you need thorough explanations or extensive code refactoring
+
+
+
+```python
+import litellm
+
+# Low verbosity - concise responses
+response = litellm.completion(
+ model="gpt-5.1",
+ messages=[{"role": "user", "content": "Write a function to reverse a string"}],
+ verbosity="low"
+)
+
+# High verbosity - detailed responses
+response = litellm.completion(
+ model="gpt-5.1",
+ messages=[{"role": "user", "content": "Explain how neural networks work"}],
+ verbosity="high"
+)
+```
+
+
+
+```bash
+curl -X POST 'http://0.0.0.0:4000/chat/completions' \
+-H 'Content-Type: application/json' \
+-H 'Authorization: Bearer sk-1234' \
+-d '{
+ "model": "gpt-5.1",
+ "messages": [{"role": "user", "content": "Write a function to reverse a string"}],
+ "verbosity": "low"
+}'
+```
+
+
+
+
## OpenAI Chat Completion to Responses API Bridge
Call any Responses API model from OpenAI's `/chat/completions` endpoint.
diff --git a/docs/my-website/docs/providers/snowflake.md b/docs/my-website/docs/providers/snowflake.md
index 40deef87805..483bf939fe6 100644
--- a/docs/my-website/docs/providers/snowflake.md
+++ b/docs/my-website/docs/providers/snowflake.md
@@ -3,20 +3,15 @@ import TabItem from '@theme/TabItem';
# Snowflake
-| Property | Details |
-|-------|-------|
-| Description | The Snowflake Cortex LLM REST API lets you access the COMPLETE function via HTTP POST requests|
-| Provider Route on LiteLLM | `snowflake/` |
-| Link to Provider Doc | [Snowflake ↗](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-llm-rest-api) |
-| Base URL | `https://{account-id}.snowflakecomputing.com/api/v2/cortex/inference:complete` |
-| Supported OpenAI Endpoints | `/chat/completions`, `/completions` |
+| Property | Details |
+|----------------------------|-----------------------------------------------------------------------------------------------------------|
+| Description | The Snowflake Cortex LLM REST API lets you access the COMPLETE and EMBED functions via HTTP POST requests |
+| Provider Route on LiteLLM | `snowflake/` |
+| Link to Provider Doc | [Snowflake ↗](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-llm-rest-api) |
+| Base URLs | `https://{account-id}.snowflakecomputing.com/api/v2/cortex/inference:complete`,`https://{account-id}.snowflakecomputing.com/api/v2/cortex/inference:embed`|
+| Supported OpenAI Endpoints | `/chat/completions`, `/completions`, `/embeddings` |
-
-Currently, Snowflake's REST API does not have an endpoint for `snowflake-arctic-embed` embedding models. If you want to use these embedding models with Litellm, you can call them through our Hugging Face provider.
-
-Find the Arctic Embed models [here](https://huggingface.co/collections/Snowflake/arctic-embed-661fd57d50fab5fc314e4c18) on Hugging Face.
-
## Supported OpenAI Parameters
```
"temperature",
@@ -29,6 +24,9 @@ Find the Arctic Embed models [here](https://huggingface.co/collections/Snowflake
Snowflake does have API keys. Instead, you access the Snowflake API with your JWT token and account identifier.
+It is also possible to use [programmatic access tokens](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens) (PAT). It can be defined by using 'pat/' prefix
+
+
```python
import os
os.environ["SNOWFLAKE_JWT"] = "YOUR JWT"
@@ -37,17 +35,38 @@ os.environ["SNOWFLAKE_ACCOUNT_ID"] = "YOUR ACCOUNT IDENTIFIER"
## Usage
```python
-from litellm import completion
+from litellm import completion, embedding
## set ENV variables
-os.environ["SNOWFLAKE_JWT"] = "YOUR JWT"
+os.environ["SNOWFLAKE_JWT"] = "JWT_TOKEN"
os.environ["SNOWFLAKE_ACCOUNT_ID"] = "YOUR ACCOUNT IDENTIFIER"
-# Snowflake call
+# Snowflake completion call
response = completion(
model="snowflake/mistral-7b",
messages = [{ "content": "Hello, how are you?","role": "user"}]
)
+
+# Snowflake embedding call
+response = embedding(
+ model="snowflake/mistral-7b",
+ input = ["My text"]
+)
+
+# Pass`api_key` and `account_id` as parameters
+response = completion(
+ model="snowflake/mistral-7b",
+ messages = [{ "content": "Hello, how are you?","role": "user"}],
+ account_id="AAAA-BBBB",
+ api_key="JWT_TOKEN"
+)
+
+# using PAT
+response = completion(
+ model="snowflake/mistral-7b",
+ messages = [{ "content": "Hello, how are you?","role": "user"}],
+ api_key="pat/PAT_TOKEN"
+)
```
## Usage with LiteLLM Proxy
diff --git a/docs/my-website/docs/proxy/admin_ui_sso.md b/docs/my-website/docs/proxy/admin_ui_sso.md
index ae082848b6b..0438c264685 100644
--- a/docs/my-website/docs/proxy/admin_ui_sso.md
+++ b/docs/my-website/docs/proxy/admin_ui_sso.md
@@ -380,3 +380,54 @@ If you need to inspect the JWT fields received from your SSO provider by LiteLLM
Once redirected, you should see a page called "SSO Debug Information". This page displays the JWT fields received from your SSO provider (as shown in the image above)
+
+## Advanced
+
+### Manage User Roles via Azure App Roles
+
+Centralize role management by defining user permissions in Azure Entra ID. LiteLLM will automatically assign roles based on your Azure configuration when users sign in—no need to manually manage roles in LiteLLM.
+
+#### Step 1: Create App Roles on Azure App Registration
+
+1. Navigate to your App Registration on https://portal.azure.com/
+2. Go to **App roles** > **Create app role**
+3. Configure the app role using one of the [supported LiteLLM roles](./access_control.md#global-proxy-roles):
+ - **Display name**: Admin Viewer (or your preferred display name)
+ - **Value**: `proxy_admin_viewer` (must match one of the LiteLLM role values exactly)
+4. Click **Apply** to save the role
+5. Repeat for each LiteLLM role you want to use
+
+
+**Supported LiteLLM role values** (see [full role documentation](./access_control.md#global-proxy-roles)):
+- `proxy_admin` - Full admin access
+- `proxy_admin_viewer` - Read-only admin access
+- `internal_user` - Can create/view/delete own keys
+- `internal_user_viewer` - Can view own keys (read-only)
+
+
+
+---
+
+#### Step 2: Assign Users to App Roles
+
+1. Navigate to **Enterprise Applications** on https://portal.azure.com/
+2. Select your LiteLLM application
+3. Go to **Users and groups** > **Add user/group**
+4. Select the user
+5. Under **Select a role**, choose the app role you created (e.g., `proxy_admin_viewer`)
+6. Click **Assign** to save
+
+
+
+---
+
+#### Step 3: Sign in and verify
+
+1. Sign in to the LiteLLM UI via SSO
+2. LiteLLM will automatically extract the app role from the JWT token
+3. The user will be assigned the corresponding role (you can verify this in the UI by checking the user profile dropdown)
+
+
+
+**Note:** The role from Entra ID will take precedence over any existing role in the LiteLLM database. This ensures your SSO provider is the authoritative source for user roles.
+
diff --git a/docs/my-website/docs/proxy/ai_hub.md b/docs/my-website/docs/proxy/ai_hub.md
new file mode 100644
index 00000000000..a7865db6cdb
--- /dev/null
+++ b/docs/my-website/docs/proxy/ai_hub.md
@@ -0,0 +1,240 @@
+import Image from '@theme/IdealImage';
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# AI Hub
+
+Share models and agents with your organization. Show developers what's available without needing to rebuild them.
+
+This feature is **available in v1.74.3-stable and above**.
+
+## Overview
+
+Admin can select models/agents to expose on public AI hub → Users go to the public url and see what's available.
+
+
+
+## Models
+
+### How to use
+
+#### 1. Go to the Admin UI
+
+Navigate to the Model Hub page in the Admin UI (`PROXY_BASE_URL/ui/?login=success&page=model-hub-table`)
+
+
+
+#### 2. Select the models you want to expose
+
+Click on `Select Models to Make Public` and select the models you want to expose.
+
+
+
+#### 3. Confirm the changes
+
+
+
+#### 4. Success!
+
+Go to the public url (`PROXY_BASE_URL/ui/model_hub_table`) and see available models.
+
+
+
+### API Endpoints
+
+- `GET /public/model_hub` – returns the list of public model groups. Requires a valid user API key.
+- `GET /public/model_hub/info` – returns metadata (docs title, version, useful links) for the public model hub.
+
+## Agents
+
+:::info
+Agents are only available in v1.79.4-stable and above.
+:::
+
+Share pre-built agents (A2A spec) across your organization. Users can discover and use agents without rebuilding them.
+
+[**Demo Video**](https://drive.google.com/file/d/1r-_Rtiu04RW5Fwwu3_eshtA1oZtC3_DH/view?usp=sharing)
+
+### 1. Create an agent
+
+Create an agent that follows the [A2A spec](https://a2a.dev/).
+
+
+
+
+
+
+
+
+```bash
+curl -X POST 'http://0.0.0.0:4000/v1/agents' \
+--header 'Authorization: Bearer ' \
+--header 'Content-Type: application/json' \
+--data '{
+ "agent_name": "hello-world-agent",
+ "agent_card_params": {
+ "protocolVersion": "1.0",
+ "name": "Hello World Agent",
+ "description": "Just a hello world agent",
+ "url": "http://localhost:9999/",
+ "version": "1.0.0",
+ "defaultInputModes": ["text"],
+ "defaultOutputModes": ["text"],
+ "capabilities": {
+ "streaming": true
+ },
+ "skills": [
+ {
+ "id": "hello_world",
+ "name": "Returns hello world",
+ "description": "just returns hello world",
+ "tags": ["hello world"],
+ "examples": ["hi", "hello world"]
+ }
+ ]
+ }
+}'
+```
+
+**Expected Response**
+
+```json
+{
+ "agent_id": "123e4567-e89b-12d3-a456-426614174000",
+ "agent_name": "hello-world-agent",
+ "agent_card_params": {
+ "protocolVersion": "1.0",
+ "name": "Hello World Agent",
+ "description": "Just a hello world agent",
+ "url": "http://localhost:9999/",
+ "version": "1.0.0",
+ "defaultInputModes": ["text"],
+ "defaultOutputModes": ["text"],
+ "capabilities": {
+ "streaming": true
+ },
+ "skills": [
+ {
+ "id": "hello_world",
+ "name": "Returns hello world",
+ "description": "just returns hello world",
+ "tags": ["hello world"],
+ "examples": ["hi", "hello world"]
+ }
+ ]
+ },
+ "created_at": "2025-11-15T10:30:00Z",
+ "created_by": "user123"
+}
+```
+
+
+
+
+### 2. Make agent public
+
+Make the agent discoverable on the AI Hub.
+
+
+
+
+Navigate to the Agents Tab on the AI Hub page
+
+
+
+Select the agents you want to make public and click on `Make Public` button.
+
+
+
+
+
+
+**Option 1: Make single agent public**
+
+```bash
+curl -X POST 'http://0.0.0.0:4000/v1/agents/123e4567-e89b-12d3-a456-426614174000/make_public' \
+--header 'Authorization: Bearer ' \
+--header 'Content-Type: application/json'
+```
+
+**Option 2: Make multiple agents public**
+
+
+```bash
+curl -X POST 'http://0.0.0.0:4000/v1/agents/make_public' \
+--header 'Authorization: Bearer ' \
+--header 'Content-Type: application/json' \
+--data '{
+ "agent_ids": [
+ "123e4567-e89b-12d3-a456-426614174000",
+ "123e4567-e89b-12d3-a456-426614174001"
+ ]
+}'
+```
+
+**Expected Response**
+
+```json
+{
+ "message": "Successfully updated public agent groups",
+ "public_agent_groups": [
+ "123e4567-e89b-12d3-a456-426614174000"
+ ],
+ "updated_by": "user123"
+}
+```
+
+
+
+
+
+
+
+### 3. View public agents
+
+Users can now discover the agent via the public endpoint.
+
+
+
+
+
+
+
+
+
+```bash
+curl -X GET 'http://0.0.0.0:4000/public/agent_hub' \
+--header 'Authorization: Bearer '
+```
+
+**Expected Response**
+
+```json
+[
+ {
+ "protocolVersion": "1.0",
+ "name": "Hello World Agent",
+ "description": "Just a hello world agent",
+ "url": "http://localhost:9999/",
+ "version": "1.0.0",
+ "defaultInputModes": ["text"],
+ "defaultOutputModes": ["text"],
+ "capabilities": {
+ "streaming": true
+ },
+ "skills": [
+ {
+ "id": "hello_world",
+ "name": "Returns hello world",
+ "description": "just returns hello world",
+ "tags": ["hello world"],
+ "examples": ["hi", "hello world"]
+ }
+ ]
+ }
+]
+```
+
+
+
+
diff --git a/docs/my-website/docs/proxy/cli_sso.md b/docs/my-website/docs/proxy/cli_sso.md
index f7669d6a25c..cde6bf266d4 100644
--- a/docs/my-website/docs/proxy/cli_sso.md
+++ b/docs/my-website/docs/proxy/cli_sso.md
@@ -9,6 +9,26 @@ Use the litellm cli to authenticate to the LiteLLM Gateway. This is great if you
## Usage
+### Prerequisites - Start LiteLLM Proxy with Beta Flag
+
+:::warning[Beta Feature - Required]
+
+CLI SSO Authentication is currently in beta. You must set this environment variable **when starting up your LiteLLM Proxy**:
+
+```bash
+export EXPERIMENTAL_UI_LOGIN="True"
+litellm --config config.yaml
+```
+
+Or add it to your proxy startup command:
+
+```bash
+EXPERIMENTAL_UI_LOGIN="True" litellm --config config.yaml
+```
+
+:::
+
+### Steps
1. **Install the CLI**
@@ -33,6 +53,8 @@ Use the litellm cli to authenticate to the LiteLLM Gateway. This is great if you
2. **Set up environment variables**
+ On your local machine, set the proxy URL:
+
```bash
export LITELLM_PROXY_URL=http://localhost:4000
```
diff --git a/docs/my-website/docs/proxy/config_settings.md b/docs/my-website/docs/proxy/config_settings.md
index 4d02d5729bf..67b5ad26fb9 100644
--- a/docs/my-website/docs/proxy/config_settings.md
+++ b/docs/my-website/docs/proxy/config_settings.md
@@ -655,6 +655,7 @@ router_settings:
| LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRY_TIMEOUT | Timeout for retries of parallel requests in LiteLLM
| LITELLM_MIGRATION_DIR | Custom migrations directory for prisma migrations, used for baselining db in read-only file systems.
| LITELLM_HOSTED_UI | URL of the hosted UI for LiteLLM
+| LITELLM_UI_API_DOC_BASE_URL | Optional override for the API Reference base URL (used in sample code/docs) when the admin UI runs on a different host than the proxy. Defaults to `PROXY_BASE_URL` when unset.
| LITELM_ENVIRONMENT | Environment of LiteLLM Instance, used by logging services. Currently only used by DeepEval.
| LITELLM_KEY_ROTATION_ENABLED | Enable auto-key rotation for LiteLLM (boolean). Default is false.
| LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS | Interval in seconds for how often to run job that auto-rotates keys. Default is 86400 (24 hours).
diff --git a/docs/my-website/docs/proxy/control_plane_and_data_plane.md b/docs/my-website/docs/proxy/control_plane_and_data_plane.md
index db0b7884c92..b0fe2b71ee2 100644
--- a/docs/my-website/docs/proxy/control_plane_and_data_plane.md
+++ b/docs/my-website/docs/proxy/control_plane_and_data_plane.md
@@ -163,6 +163,10 @@ DISABLE_LLM_API_ENDPOINTS=true
- `/config/*` - Configuration updates
- All other administrative endpoints
+### `LITELLM_UI_API_DOC_BASE_URL`
+
+Optional override for the API Reference base URL (used in sample code/docs) when the admin UI runs on a different host than the proxy.
+
## Usage Patterns
diff --git a/docs/my-website/docs/proxy/db_info.md b/docs/my-website/docs/proxy/db_info.md
index 946089bf147..5ef9fa55043 100644
--- a/docs/my-website/docs/proxy/db_info.md
+++ b/docs/my-website/docs/proxy/db_info.md
@@ -46,8 +46,8 @@ You can see the full DB Schema [here](https://github.com/BerriAI/litellm/blob/ma
| Table Name | Description | Row Insert Frequency |
|------------|-------------|---------------------|
-| LiteLLM_SpendLogs | Detailed logs of all API requests. Records token usage, spend, and timing information. Tracks which models and keys were used. | **High - every LLM API request - Success or Failure** |
-| LiteLLM_AuditLog | Tracks changes to system configuration. Records who made changes and what was modified. Maintains history of updates to teams, users, and models. | **Off by default**, **High - when enabled** |
+| LiteLLM_SpendLogs | Detailed logs of all API requests. Records token usage, spend, and timing information. Tracks which models and keys were used. | **Medium - this is a batch process that runs on an interval.** |
+| LiteLLM_AuditLog | Tracks changes to system configuration. Records who made changes and what was modified. Maintains history of updates to teams, users, and models. | **Off by default**, **High - Runs on every change to an entity** |
## Disable `LiteLLM_SpendLogs`
diff --git a/docs/my-website/docs/proxy/dynamic_logging.md b/docs/my-website/docs/proxy/dynamic_logging.md
index 3bc9f72b033..42df221bb84 100644
--- a/docs/my-website/docs/proxy/dynamic_logging.md
+++ b/docs/my-website/docs/proxy/dynamic_logging.md
@@ -211,4 +211,64 @@ x-litellm-disable-callbacks: LANGFUSE,datadog,PROMETHEUS
x-litellm-disable-callbacks: langfuse,DATADOG,prometheus
```
+---
+
+## Disabling Dynamic Callback Management (Enterprise)
+
+Some organizations have compliance requirements where **all requests must be logged under all circumstances**. For these cases, you can disable dynamic callback management entirely to ensure users cannot disable any logging callbacks.
+
+### Use Case
+
+This is designed for enterprise scenarios where:
+- **Compliance requirements** mandate that all API requests must be logged
+- **Audit trails** must be complete with no gaps
+- **Security policies** require all traffic to be monitored
+- **No exceptions** can be made for callback disabling
+
+### How to Disable
+
+Set `allow_dynamic_callback_disabling` to `false` in your config.yaml:
+
+```yaml showLineNumbers title="config.yaml"
+litellm_settings:
+ allow_dynamic_callback_disabling: false
+```
+
+### Effect
+
+When disabled:
+- The `x-litellm-disable-callbacks` header will be **ignored**
+- All configured callbacks will **always execute** for every request
+- Users cannot bypass logging through headers or request metadata
+- All requests are guaranteed to be logged per your proxy configuration
+
+### Example: Compliance Logging Setup
+
+Here's a complete example for an organization requiring guaranteed logging:
+
+```yaml showLineNumbers title="config.yaml"
+# config.yaml
+model_list:
+ - model_name: gpt-4
+ litellm_params:
+ model: openai/gpt-4
+ api_key: os.environ/OPENAI_API_KEY
+
+litellm_settings:
+ callbacks: ["langfuse", "datadog", "s3"]
+ # Disable dynamic callback disabling for compliance
+ allow_dynamic_callback_disabling: false
+```
+
+With this configuration:
+- All requests will be logged to Langfuse, Datadog, and S3
+- Users cannot disable any of these callbacks via headers
+- Complete audit trail is guaranteed for compliance requirements
+
+:::info
+
+**Default Behavior**: Dynamic callback disabling is **enabled by default** (`allow_dynamic_callback_disabling: true`). You must explicitly set it to `false` to enforce guaranteed logging.
+
+:::
+
diff --git a/docs/my-website/docs/proxy/enterprise.md b/docs/my-website/docs/proxy/enterprise.md
index 42677264ff6..cfd6ab31015 100644
--- a/docs/my-website/docs/proxy/enterprise.md
+++ b/docs/my-website/docs/proxy/enterprise.md
@@ -32,13 +32,9 @@ Features:
- ✅ [Set Model budgets for Virtual Keys](./users#-virtual-key-model-specific)
- ✅ [Exporting LLM Logs to GCS Bucket, Azure Blob Storage](./proxy/bucket#🪣-logging-gcs-s3-buckets)
- ✅ [`/spend/report` API endpoint](cost_tracking.md#✨-enterprise-api-endpoints-to-get-spend)
-- **Prometheus Metrics**
- - ✅ [Prometheus Metrics - Num Requests, failures, LLM Provider Outages](prometheus)
- - ✅ [`x-ratelimit-remaining-requests`, `x-ratelimit-remaining-tokens` for LLM APIs on Prometheus](prometheus#✨-enterprise-llm-remaining-requests-and-remaining-tokens)
-- **Control Guardrails per API Key**
+- **Control Guardrails per API Key/Team**
- **Custom Branding**
- ✅ [Custom Branding + Routes on Swagger Docs](#swagger-docs---custom-routes--branding)
- - ✅ [Public Model Hub](#public-model-hub)
- ✅ [Custom Email Branding](./email.md#customizing-email-branding)
@@ -905,9 +901,11 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \
'
```
-## Public Model Hub
+## Public AI Hub
-Share a public page of available models for users
+Share a public page of available models and agents for users
+
+[Learn more](./ai_hub.md)
diff --git a/docs/my-website/docs/proxy/guardrails/custom_guardrail.md b/docs/my-website/docs/proxy/guardrails/custom_guardrail.md
index b8ba64d333a..365fdf81aa5 100644
--- a/docs/my-website/docs/proxy/guardrails/custom_guardrail.md
+++ b/docs/my-website/docs/proxy/guardrails/custom_guardrail.md
@@ -4,151 +4,86 @@ import TabItem from '@theme/TabItem';
# Custom Guardrail
-Use this is you want to write code to run a custom guardrail
+Use this if you want to write code to run a custom guardrail
## Quick Start
### 1. Write a `CustomGuardrail` Class
-A CustomGuardrail has 4 methods to enforce guardrails
-- `async_pre_call_hook` - (Optional) modify input or reject request before making LLM API call
-- `async_moderation_hook` - (Optional) reject request, runs while making LLM API call (help to lower latency)
-- `async_post_call_success_hook`- (Optional) apply guardrail on input/output, runs after making LLM API call
-- `async_post_call_streaming_iterator_hook` - (Optional) pass the entire stream to the guardrail
-
-
-**[See detailed spec of methods here](#customguardrail-methods)**
+The simplest way to create a custom guardrail is by implementing the `apply_guardrail` method. This method is called to check text content and can block requests by raising an exception.
**Example `CustomGuardrail` Class**
-Create a new file called `custom_guardrail.py` and add this code to it
+Create a new file called `custom_guardrail.py` and add this code to it:
+
```python
-from typing import Any, AsyncGenerator, Literal, Optional, Union
-
-import litellm
-from litellm._logging import verbose_proxy_logger
-from litellm.caching.caching import DualCache
+import os
+from typing import Optional, List
from litellm.integrations.custom_guardrail import CustomGuardrail
-from litellm.proxy._types import UserAPIKeyAuth
-from litellm.types.utils import ModelResponseStream
-
+from litellm.types.guardrails import PiiEntityType
+from litellm._logging import verbose_proxy_logger
+from litellm.llms.custom_httpx.http_handler import (
+ get_async_httpx_client,
+ httpxSpecialProvider,
+)
class myCustomGuardrail(CustomGuardrail):
- def __init__(
- self,
- **kwargs,
- ):
- # store kwargs as optional_params
- self.optional_params = kwargs
-
+ def __init__(self, api_key: Optional[str] = None, api_base: Optional[str] = None, **kwargs):
+ self.api_key = api_key or os.getenv("MY_GUARDRAIL_API_KEY")
+ self.api_base = api_base or os.getenv("MY_GUARDRAIL_API_BASE", "https://api.myguardrail.com")
super().__init__(**kwargs)
- async def async_pre_call_hook(
+ async def apply_guardrail(
self,
- user_api_key_dict: UserAPIKeyAuth,
- cache: DualCache,
- data: dict,
- call_type: Literal[
- "completion",
- "text_completion",
- "embeddings",
- "image_generation",
- "moderation",
- "audio_transcription",
- "pass_through_endpoint",
- "rerank"
- ],
- ) -> Optional[Union[Exception, str, dict]]:
+ text: str, # IMPORTANT: This is the text to check against your guardrail rules. It's extracted from the request or response across all LLM call types.
+ language: Optional[str] = None, # ignore
+ entities: Optional[List[PiiEntityType]] = None, # ignore
+ request_data: Optional[dict] = None, # ignore
+ ) -> str:
"""
- Runs before the LLM API call
- Runs on only Input
- Use this if you want to MODIFY the input
+ Check text content against your guardrail rules.
+ Raise an exception to block the request.
+ Return the text (optionally modified) to allow it through.
"""
+ result = await self._check_with_api(text, request_data)
+
+ if result.get("action") == "BLOCK":
+ raise Exception(f"Content blocked: {result.get('reason', 'Policy violation')}")
+
+ return text
- # In this guardrail, if a user inputs `litellm` we will mask it and then send it to the LLM
- _messages = data.get("messages")
- if _messages:
- for message in _messages:
- _content = message.get("content")
- if isinstance(_content, str):
- if "litellm" in _content.lower():
- _content = _content.replace("litellm", "********")
- message["content"] = _content
-
- verbose_proxy_logger.debug(
- "async_pre_call_hook: Message after masking %s", _messages
+ async def _check_with_api(self, text: str, request_data: Optional[dict]) -> dict:
+ async_client = get_async_httpx_client(llm_provider=httpxSpecialProvider.LoggingCallback)
+
+ headers = {
+ "Content-Type": "application/json",
+ "Authorization": f"Bearer {self.api_key}",
+ }
+
+ response = await async_client.post(
+ f"{self.api_base}/check",
+ headers=headers,
+ json={"text": text},
+ timeout=5,
)
-
- return data
-
- async def async_moderation_hook(
- self,
- data: dict,
- user_api_key_dict: UserAPIKeyAuth,
- call_type: Literal["completion", "embeddings", "image_generation", "moderation", "audio_transcription"],
- ):
- """
- Runs in parallel to LLM API call
- Runs on only Input
-
- This can NOT modify the input, only used to reject or accept a call before going to LLM API
- """
-
- # this works the same as async_pre_call_hook, but just runs in parallel as the LLM API Call
- # In this guardrail, if a user inputs `litellm` we will mask it.
- _messages = data.get("messages")
- if _messages:
- for message in _messages:
- _content = message.get("content")
- if isinstance(_content, str):
- if "litellm" in _content.lower():
- raise ValueError("Guardrail failed words - `litellm` detected")
-
- async def async_post_call_success_hook(
- self,
- data: dict,
- user_api_key_dict: UserAPIKeyAuth,
- response,
- ):
- """
- Runs on response from LLM API call
-
- It can be used to reject a response
-
- If a response contains the word "coffee" -> we will raise an exception
- """
- verbose_proxy_logger.debug("async_pre_call_hook response: %s", response)
- if isinstance(response, litellm.ModelResponse):
- for choice in response.choices:
- if isinstance(choice, litellm.Choices):
- verbose_proxy_logger.debug("async_pre_call_hook choice: %s", choice)
- if (
- choice.message.content
- and isinstance(choice.message.content, str)
- and "coffee" in choice.message.content
- ):
- raise ValueError("Guardrail failed Coffee Detected")
-
- async def async_post_call_streaming_iterator_hook(
- self,
- user_api_key_dict: UserAPIKeyAuth,
- response: Any,
- request_data: dict,
- ) -> AsyncGenerator[ModelResponseStream, None]:
- """
- Passes the entire stream to the guardrail
-
- This is useful for guardrails that need to see the entire response, such as PII masking.
-
- See Aim guardrail implementation for an example - https://github.com/BerriAI/litellm/blob/d0e022cfacb8e9ebc5409bb652059b6fd97b45c0/litellm/proxy/guardrails/guardrail_hooks/aim.py#L168
-
- Triggered by mode: 'post_call'
- """
- async for item in response:
- yield item
-
+
+ response.raise_for_status()
+ return response.json()
```
+:::tip Advanced: Using Individual Event Hooks
+
+If you need more fine-grained control, you can implement individual event hooks instead of (or in addition to) `apply_guardrail`:
+
+- `async_pre_call_hook` - Modify input or reject request before making LLM API call
+- `async_moderation_hook` - Reject request, runs in parallel with LLM API call (helps lower latency)
+- `async_post_call_success_hook` - Apply guardrail on input/output, runs after making LLM API call
+- `async_post_call_streaming_iterator_hook` - Pass the entire stream to the guardrail
+
+**[See examples of individual event hooks here](#advanced-individual-event-hooks)** | **[See detailed spec of methods here](#customguardrail-methods)**
+
+:::
+
### 2. Pass your custom guardrail class in LiteLLM `config.yaml`
In the config below, we point the guardrail to our custom guardrail by setting `guardrail: custom_guardrail.myCustomGuardrail`
@@ -166,9 +101,32 @@ model_list:
api_key: os.environ/OPENAI_API_KEY
guardrails:
- - guardrail_name: "custom-pre-guard"
+ - guardrail_name: "my-custom-guardrail"
litellm_params:
guardrail: custom_guardrail.myCustomGuardrail # 👈 Key change
+ mode: "during_call" # runs apply_guardrail method
+ api_key: os.environ/MY_GUARDRAIL_API_KEY
+ api_base: https://api.myguardrail.com
+```
+
+:::info Mode Options
+
+- `during_call` - Default mode, runs `apply_guardrail` method (or `async_moderation_hook` if using individual hooks)
+- `pre_call` - Runs `async_pre_call_hook` for input modification
+- `post_call` - Runs `async_post_call_success_hook` for output validation
+
+:::
+
+
+Advanced: Multiple modes with individual event hooks
+
+If you're using individual event hooks, you can configure multiple guardrails with different modes:
+
+```yaml
+guardrails:
+ - guardrail_name: "custom-pre-guard"
+ litellm_params:
+ guardrail: custom_guardrail.myCustomGuardrail
mode: "pre_call" # runs async_pre_call_hook
- guardrail_name: "custom-during-guard"
litellm_params:
@@ -180,6 +138,8 @@ guardrails:
mode: "post_call" # runs async_post_call_success_hook
```
+
+
### 3. Start LiteLLM Gateway
@@ -218,15 +178,76 @@ litellm --config config.yaml --detailed_debug
### 4. Test it
-#### Test `"custom-pre-guard"`
-
-
**[Langchain, OpenAI SDK Usage Examples](../proxy/user_keys#request-format)**
+
+
+
+This request will be blocked if it violates your guardrail policy:
+
+```shell
+curl -i -X POST http://localhost:4000/v1/chat/completions \
+-H "Content-Type: application/json" \
+-H "Authorization: Bearer sk-1234" \
+-d '{
+ "model": "gpt-4",
+ "messages": [
+ {
+ "role": "user",
+ "content": "Content that violates policy"
+ }
+ ],
+ "guardrails": ["my-custom-guardrail"]
+}'
+```
+
+Expected response when blocked:
+
+```json
+{
+ "error": {
+ "message": "Content blocked: Policy violation",
+ "type": "None",
+ "param": "None",
+ "code": "500"
+ }
+}
+```
+
+
+
+
+
+This request passes the guardrail:
+
+```shell
+curl -i http://localhost:4000/v1/chat/completions \
+ -H "Content-Type: application/json" \
+ -H "Authorization: Bearer sk-1234" \
+ -d '{
+ "model": "gpt-4",
+ "messages": [
+ {"role": "user", "content": "What is the weather like today?"}
+ ],
+ "guardrails": ["my-custom-guardrail"]
+ }'
+```
+
+
+
+
+
+
+Advanced: Testing individual event hooks
+
+If you're using individual event hooks, you can test each mode separately:
+
+#### Test `"custom-pre-guard"`
+
-Expect this to mask the word `litellm` before sending the request to the LLM API. [This runs the `async_pre_call_hook`](#1-write-a-customguardrail-class)
+Expect this to mask the word `litellm` before sending the request to the LLM API. [This runs the `async_pre_call_hook`](#advanced-individual-event-hooks)
```shell
curl -i -X POST http://localhost:4000/v1/chat/completions \
@@ -244,37 +265,6 @@ curl -i -X POST http://localhost:4000/v1/chat/completions \
}'
```
-Expected response after pre-guard
-
-```json
-{
- "id": "chatcmpl-9zREDkBIG20RJB4pMlyutmi1hXQWc",
- "choices": [
- {
- "finish_reason": "stop",
- "index": 0,
- "message": {
- "content": "It looks like you've chosen a string of asterisks. This could be a way to censor or hide certain text. However, without more context, I can't provide a specific word or phrase. If there's something specific you'd like me to say or if you need help with a topic, feel free to let me know!",
- "role": "assistant",
- "tool_calls": null,
- "function_call": null
- }
- }
- ],
- "created": 1724429701,
- "model": "gpt-4o-2024-05-13",
- "object": "chat.completion",
- "system_fingerprint": "fp_3aa7262c27",
- "usage": {
- "completion_tokens": 65,
- "prompt_tokens": 14,
- "total_tokens": 79
- },
- "service_tier": null
-}
-
-```
-
@@ -282,7 +272,7 @@ Expected response after pre-guard
```shell
curl -i http://localhost:4000/v1/chat/completions \
-H "Content-Type: application/json" \
- -H "Authorization: Bearer sk-npnwjPQciVRok5yNZgKmFQ" \
+ -H "Authorization: Bearer sk-1234" \
-d '{
"model": "gpt-3.5-turbo",
"messages": [
@@ -294,20 +284,14 @@ curl -i http://localhost:4000/v1/chat/completions \
-
-
#### Test `"custom-during-guard"`
-
-**[Langchain, OpenAI SDK Usage Examples](../proxy/user_keys#request-format)**
-
-Expect this to fail since since `litellm` is in the message content. [This runs the `async_moderation_hook`](#1-write-a-customguardrail-class)
-
+Expect this to fail since `litellm` is in the message content. [This runs the `async_moderation_hook`](#advanced-individual-event-hooks)
```shell
curl -i -X POST http://localhost:4000/v1/chat/completions \
@@ -325,7 +309,7 @@ curl -i -X POST http://localhost:4000/v1/chat/completions \
}'
```
-Expected response after running during-guard
+Expected response:
```json
{
@@ -345,7 +329,7 @@ Expected response after running during-guard
```shell
curl -i http://localhost:4000/v1/chat/completions \
-H "Content-Type: application/json" \
- -H "Authorization: Bearer sk-npnwjPQciVRok5yNZgKmFQ" \
+ -H "Authorization: Bearer sk-1234" \
-d '{
"model": "gpt-3.5-turbo",
"messages": [
@@ -357,21 +341,14 @@ curl -i http://localhost:4000/v1/chat/completions \
-
-
#### Test `"custom-post-guard"`
-
-
-**[Langchain, OpenAI SDK Usage Examples](../proxy/user_keys#request-format)**
-
-Expect this to fail since since `coffee` will be in the response content. [This runs the `async_post_call_success_hook`](#1-write-a-customguardrail-class)
-
+Expect this to fail since `coffee` will be in the response content. [This runs the `async_post_call_success_hook`](#advanced-individual-event-hooks)
```shell
curl -i -X POST http://localhost:4000/v1/chat/completions \
@@ -389,7 +366,7 @@ curl -i -X POST http://localhost:4000/v1/chat/completions \
}'
```
-Expected response after running during-guard
+Expected response:
```json
{
@@ -407,7 +384,7 @@ Expected response after running during-guard
```shell
- curl -i -X POST http://localhost:4000/v1/chat/completions \
+curl -i -X POST http://localhost:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-1234" \
-d '{
@@ -424,9 +401,10 @@ Expected response after running during-guard
-
+
+
## ✨ Pass additional parameters to guardrail
:::info
@@ -539,10 +517,162 @@ The `get_guardrail_dynamic_request_body_params` method will return:
}
```
+## Advanced: Individual Event Hooks
+
+Pro: More flexibility
+Con: You need to implement this for each LLM call type (chat completions, text completions, embeddings, image generation, moderation, audio transcription, pass through endpoint, rerank, etc. )
+
+For more fine-grained control over when and how your guardrail runs, you can implement individual event hooks. This gives you flexibility to:
+- Modify inputs before the LLM call
+- Run checks in parallel with the LLM call (lower latency)
+- Validate or modify outputs after the LLM call
+- Process streaming responses
+
+### Example with Individual Event Hooks
+
+```python
+from typing import Any, AsyncGenerator, Literal, Optional, Union
+
+import litellm
+from litellm._logging import verbose_proxy_logger
+from litellm.caching.caching import DualCache
+from litellm.integrations.custom_guardrail import CustomGuardrail
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.types.utils import ModelResponseStream, CallTypes
+
+
+class myCustomGuardrail(CustomGuardrail):
+ def __init__(
+ self,
+ **kwargs,
+ ):
+ # store kwargs as optional_params
+ self.optional_params = kwargs
+
+ super().__init__(**kwargs)
+
+ async def async_pre_call_hook(
+ self,
+ user_api_key_dict: UserAPIKeyAuth,
+ cache: DualCache,
+ data: dict,
+ call_type: Optional[CallTypes],
+ ) -> Optional[Union[Exception, str, dict]]:
+ """
+ Runs before the LLM API call
+ Runs on only Input
+ Use this if you want to MODIFY the input
+ """
+
+ # In this guardrail, if a user inputs `litellm` we will mask it and then send it to the LLM
+ _messages = data.get("messages")
+ if _messages:
+ for message in _messages:
+ _content = message.get("content")
+ if isinstance(_content, str):
+ if "litellm" in _content.lower():
+ _content = _content.replace("litellm", "********")
+ message["content"] = _content
+
+ verbose_proxy_logger.debug(
+ "async_pre_call_hook: Message after masking %s", _messages
+ )
+
+ return data
+
+ async def async_moderation_hook(
+ self,
+ data: dict,
+ user_api_key_dict: UserAPIKeyAuth,
+ call_type: Literal["completion", "embeddings", "image_generation", "moderation", "audio_transcription"],
+ ):
+ """
+ Runs in parallel to LLM API call
+ Runs on only Input
+
+ This can NOT modify the input, only used to reject or accept a call before going to LLM API
+ """
+
+ # this works the same as async_pre_call_hook, but just runs in parallel as the LLM API Call
+ # In this guardrail, if a user inputs `litellm` we will mask it.
+ _messages = data.get("messages")
+ if _messages:
+ for message in _messages:
+ _content = message.get("content")
+ if isinstance(_content, str):
+ if "litellm" in _content.lower():
+ raise ValueError("Guardrail failed words - `litellm` detected")
+
+ async def async_post_call_success_hook(
+ self,
+ data: dict,
+ user_api_key_dict: UserAPIKeyAuth,
+ response,
+ ):
+ """
+ Runs on response from LLM API call
+
+ It can be used to reject a response
+
+ If a response contains the word "coffee" -> we will raise an exception
+ """
+ verbose_proxy_logger.debug("async_pre_call_hook response: %s", response)
+ if isinstance(response, litellm.ModelResponse):
+ for choice in response.choices:
+ if isinstance(choice, litellm.Choices):
+ verbose_proxy_logger.debug("async_pre_call_hook choice: %s", choice)
+ if (
+ choice.message.content
+ and isinstance(choice.message.content, str)
+ and "coffee" in choice.message.content
+ ):
+ raise ValueError("Guardrail failed Coffee Detected")
+
+ async def async_post_call_streaming_iterator_hook(
+ self,
+ user_api_key_dict: UserAPIKeyAuth,
+ response: Any,
+ request_data: dict,
+ ) -> AsyncGenerator[ModelResponseStream, None]:
+ """
+ Passes the entire stream to the guardrail
+
+ This is useful for guardrails that need to see the entire response, such as PII masking.
+
+ See Aim guardrail implementation for an example - https://github.com/BerriAI/litellm/blob/d0e022cfacb8e9ebc5409bb652059b6fd97b45c0/litellm/proxy/guardrails/guardrail_hooks/aim.py#L168
+
+ Triggered by mode: 'post_call'
+ """
+ async for item in response:
+ yield item
+
+```
+
## **CustomGuardrail methods**
| Component | Description | Optional | Checked Data | Can Modify Input | Can Modify Output | Can Fail Call |
|-----------|-------------|----------|--------------|------------------|-------------------|----------------|
+| `apply_guardrail` | Simple method to check and optionally modify text | ✅ | INPUT or OUTPUT | ✅ | ✅ | ✅ |
| `async_pre_call_hook` | A hook that runs before the LLM API call | ✅ | INPUT | ✅ | ❌ | ✅ |
| `async_moderation_hook` | A hook that runs during the LLM API call| ✅ | INPUT | ❌ | ❌ | ✅ |
| `async_post_call_success_hook` | A hook that runs after a successful LLM API call| ✅ | INPUT, OUTPUT | ❌ | ✅ | ✅ |
+| `async_post_call_streaming_iterator_hook` | A hook that processes streaming responses | ✅ | OUTPUT | ❌ | ✅ | ✅ |
+
+
+## Frequently Asked Questions
+
+**Q. Is `apply_guardrail` relevant both in the request and in the response (pre_call, during_call and post_call hooks)?**
+
+**A.** Yes, one function works in both - See implementation [here](https://github.com/BerriAI/litellm/blob/0292b84dc47473ddeff29bd5a86f529bc523034b/litellm/proxy/utils.py#L825)
+
+**Q. What do I get in the inputs of `apply_guardrail`? What does each field represent (what is text, language, entities, request_data)?**
+
+**A.** The main one you should care about is 'text' - this is what you'll want to send to your api for verification - See implementation [here](https://github.com/BerriAI/litellm/blob/0292b84dc47473ddeff29bd5a86f529bc523034b/litellm/llms/anthropic/chat/guardrail_translation/handler.py#L102)
+
+**Q. Is this function agnostic to the LLM provider? Meaning does it pass the same values for OpenAI and Anthropic for example?
+
+**A.** Yes
+
+**Q. How do I know if my guardrail is running?**
+
+**A.** If you implement `apply_guardrail`, you can query the guardrail directly via [the `/apply_guardrail` API](../../apply_guardrail).
\ No newline at end of file
diff --git a/docs/my-website/docs/proxy/guardrails/ibm_guardrails.md b/docs/my-website/docs/proxy/guardrails/ibm_guardrails.md
index 0c13d2dcea9..43ba6622078 100644
--- a/docs/my-website/docs/proxy/guardrails/ibm_guardrails.md
+++ b/docs/my-website/docs/proxy/guardrails/ibm_guardrails.md
@@ -95,6 +95,7 @@ curl -i http://localhost:4000/v1/chat/completions \
These go under `optional_params`:
- `detector_params` - dict - Parameters to pass to your detector
+- `extra_headers` - dict - Additional headers to inject into requests to IBM Guardrails, as a key-value dict.
- `score_threshold` - float - Only count detections above this score (0.0 to 1.0)
- `block_on_detection` - bool - Block the request when violations found. Default: `true`
diff --git a/docs/my-website/docs/proxy/litellm_managed_files.md b/docs/my-website/docs/proxy/litellm_managed_files.md
index ab0e4b3a751..7aba173f35b 100644
--- a/docs/my-website/docs/proxy/litellm_managed_files.md
+++ b/docs/my-website/docs/proxy/litellm_managed_files.md
@@ -21,7 +21,7 @@ Available via the `litellm[proxy]` package or any `litellm` docker image.
| Proxy | ✅ | |
| SDK | ❌ | Requires postgres DB for storing file ids. |
| Available across all providers | ✅ | |
-| Supported endpoints | `/chat/completions`, `/batch`, `/fine_tuning` | |
+| Supported endpoints | `/chat/completions`, `/batch`, `/fine_tuning`, `/responses` | |
## Usage
@@ -424,4 +424,4 @@ No, as of `v1.71.2` users can only view/edit/delete files they have created.
## See Also
- [Managed Files w/ Finetuning APIs](../../docs/proxy/managed_finetuning)
-- [Managed Files w/ Batch APIs](../../docs/proxy/managed_batch)
\ No newline at end of file
+- [Managed Files w/ Batch APIs](../../docs/proxy/managed_batches)
\ No newline at end of file
diff --git a/docs/my-website/docs/proxy/logging.md b/docs/my-website/docs/proxy/logging.md
index cf36963b7e1..168c9e56e7d 100644
--- a/docs/my-website/docs/proxy/logging.md
+++ b/docs/my-website/docs/proxy/logging.md
@@ -2439,7 +2439,7 @@ Your logs should be available on DynamoDB
"S": "{'user': 'ishaan-2'}"
},
"response": {
- "S": "EmbeddingResponse(model='text-embedding-ada-002-v2', data=[{'embedding': [-0.03503197431564331, -0.020601635798811913, -0.015375726856291294,
+ "S": "EmbeddingResponse(model='text-embedding-ada-002', data=[{'embedding': [-0.03503197431564331, -0.020601635798811913, -0.015375726856291294,
}
}
```
diff --git a/docs/my-website/docs/proxy/managed_batches.md b/docs/my-website/docs/proxy/managed_batches.md
index 431d313fc18..4bd3b12d3af 100644
--- a/docs/my-website/docs/proxy/managed_batches.md
+++ b/docs/my-website/docs/proxy/managed_batches.md
@@ -260,4 +260,15 @@ print(f"status: {status}")
When a `target_model_names` is specified, the file is written to all deployments that match the `target_model_names`.
-No additional infrastructure is required.
\ No newline at end of file
+No additional infrastructure is required.
+
+## Could the batch be created at the eastus-01 deployment but a subsequent get of the batch could be routed to (a different) eastus2-01 deployment ?
+
+**A.** You can loadbalance b/w multiple models for the initial create batch. Once that's created - we return a file id, which encodes the model deployment used, so it's sticky and only sends any get/delete to that deployment.
+
+
+
+
+
+
+
diff --git a/docs/my-website/docs/proxy/management_cli.md b/docs/my-website/docs/proxy/management_cli.md
index 9ecc2ae8a34..23a56842105 100644
--- a/docs/my-website/docs/proxy/management_cli.md
+++ b/docs/my-website/docs/proxy/management_cli.md
@@ -67,7 +67,26 @@ For an indepth guide, see [CLI Authentication](./cli_sso).
:::
+### Prerequisites
+:::warning[Beta Feature - Required Environment Variable]
+
+CLI SSO Authentication is currently in beta. You must set this environment variable **when starting up your LiteLLM Proxy**:
+
+```bash
+export EXPERIMENTAL_UI_LOGIN="True"
+litellm --config config.yaml
+```
+
+Or add it to your proxy startup command:
+
+```bash
+EXPERIMENTAL_UI_LOGIN="True" litellm --config config.yaml
+```
+
+:::
+
+### Steps
1. **Set up the proxy URL**
diff --git a/docs/my-website/docs/proxy/model_hub.md b/docs/my-website/docs/proxy/model_hub.md
deleted file mode 100644
index 6c12194d751..00000000000
--- a/docs/my-website/docs/proxy/model_hub.md
+++ /dev/null
@@ -1,53 +0,0 @@
-import Image from '@theme/IdealImage';
-import Tabs from '@theme/Tabs';
-import TabItem from '@theme/TabItem';
-
-# Model Hub
-
-Tell developers what models are available on the proxy.
-
-This feature is **available in v1.74.3-stable and above**.
-
-## Overview
-
-Admin can select models to expose on public model hub -> Users can go to the public url (`/ui/model_hub_table`) and see available models.
-
-
-
-## How to use
-
-### 1. Go to the Admin UI
-
-Navigate to the Model Hub page in the Admin UI (`PROXY_BASE_URL/ui/?login=success&page=model-hub-table`)
-
-
-
-### 2. Select the models you want to expose
-
-Click on `Make Public` and select the models you want to expose.
-
-
-
-### 3. Confirm the changes
-
-
-
-### 4. Success!
-
-Go to the public url (`PROXY_BASE_URL/ui/model_hub_table`) and see available models.
-
-
-
-## API Endpoints
-
-LiteLLM also exposes REST endpoints:
-
-- `GET /public/model_hub` – returns the list of public model groups. Requires a valid user API key.
-- `GET /public/model_hub/info` – returns metadata (docs title, version, useful links) for the public model hub.
-- `GET /public/providers` – returns a sorted list of all providers supported by LiteLLM. No authentication required.
-
-Example:
-
-```bash
-curl -s PROXY_BASE_URL/public/providers | jq
-```
diff --git a/docs/my-website/docs/proxy/prometheus.md b/docs/my-website/docs/proxy/prometheus.md
index 283076195e2..2dae463514a 100644
--- a/docs/my-website/docs/proxy/prometheus.md
+++ b/docs/my-website/docs/proxy/prometheus.md
@@ -4,15 +4,6 @@ import Image from '@theme/IdealImage';
# 📈 Prometheus metrics
-:::info
-
-✨ Prometheus metrics is on LiteLLM Enterprise
-
-[Enterprise Pricing](https://www.litellm.ai/#pricing)
-
-[Get free 7-day trial key](https://www.litellm.ai/enterprise#trial)
-
-:::
LiteLLM Exposes a `/metrics` endpoint for Prometheus to Poll
@@ -23,11 +14,12 @@ If you're using the LiteLLM CLI with `litellm --config proxy_config.yaml` then y
Add this to your proxy config.yaml
```yaml
model_list:
- - model_name: gpt-4o
+ - model_name: gpt-4o
litellm_params:
model: gpt-4o
litellm_settings:
- callbacks: ["prometheus"]
+ callbacks:
+ - prometheus
```
Start the proxy
diff --git a/docs/my-website/docs/proxy/ui.md b/docs/my-website/docs/proxy/ui.md
index f7419d20740..f6fa02fb69b 100644
--- a/docs/my-website/docs/proxy/ui.md
+++ b/docs/my-website/docs/proxy/ui.md
@@ -59,11 +59,13 @@ Allow others to create/delete their own keys.
The Admin UI provides comprehensive model management capabilities:
- **Add Models**: Add new models through the UI without restarting the proxy
-- **Model Hub**: Make models public for developers to discover available models
+- **AI Hub**: Make models and agents public for developers to discover what's available
- **Price Data Sync**: Keep model pricing data up to date by syncing from GitHub
For detailed information on model management, see [Model Management](./model_management.md).
+For information on sharing models and agents, see [AI Hub](./ai_hub.md).
+
:::tip Sync Model Pricing Data
[Sync model pricing data from GitHub](./sync_models_github.md) to keep your model cost information current.
:::
diff --git a/docs/my-website/docs/proxy/ui_logs.md b/docs/my-website/docs/proxy/ui_logs.md
index cd2ee982232..61f328011c3 100644
--- a/docs/my-website/docs/proxy/ui_logs.md
+++ b/docs/my-website/docs/proxy/ui_logs.md
@@ -76,8 +76,6 @@ Set `SPEND_LOG_CLEANUP_BATCH_SIZE` to control how many logs are deleted per batc
For detailed architecture and how it works, see [Spend Logs Deletion](../proxy/spend_logs_deletion).
+## What gets logged?
-
-
-
-
+[Here's a schema](https://github.com/BerriAI/litellm/blob/1cdd4065a645021aea931afb9494e7694b4ec64b/schema.prisma#L285) breakdown of what gets logged.
diff --git a/docs/my-website/docs/secret_managers/aws_secret_manager.md b/docs/my-website/docs/secret_managers/aws_secret_manager.md
index 44fa23a4ae5..5b7ab1e3e7b 100644
--- a/docs/my-website/docs/secret_managers/aws_secret_manager.md
+++ b/docs/my-website/docs/secret_managers/aws_secret_manager.md
@@ -110,3 +110,57 @@ The `primary_secret_name` allows you to read multiple keys from a single AWS Sec
This reduces the number of AWS Secrets you need to manage.
+## IAM Role Assumption
+
+Use IAM roles instead of static AWS credentials for better security.
+
+### Basic IAM Role
+
+```yaml
+general_settings:
+ key_management_system: "aws_secret_manager"
+ key_management_settings:
+ store_virtual_keys: true
+ aws_region_name: "us-east-1"
+ aws_role_name: "arn:aws:iam::123456789012:role/LiteLLMSecretManagerRole"
+ aws_session_name: "litellm-session"
+```
+
+### Cross-Account Access
+
+```yaml
+general_settings:
+ key_management_system: "aws_secret_manager"
+ key_management_settings:
+ store_virtual_keys: true
+ aws_region_name: "us-east-1"
+ aws_role_name: "arn:aws:iam::999999999999:role/CrossAccountRole"
+ aws_external_id: "unique-external-id"
+```
+
+### EKS with IRSA
+
+```yaml
+general_settings:
+ key_management_system: "aws_secret_manager"
+ key_management_settings:
+ store_virtual_keys: true
+ aws_region_name: "us-east-1"
+ aws_role_name: "arn:aws:iam::123456789012:role/LiteLLMServiceAccountRole"
+ aws_web_identity_token: "os.environ/AWS_WEB_IDENTITY_TOKEN_FILE"
+```
+
+### Configuration Parameters
+
+| Parameter | Description |
+|-----------|-------------|
+| `aws_region_name` | AWS region |
+| `aws_role_name` | IAM role ARN to assume |
+| `aws_session_name` | Session name (optional) |
+| `aws_external_id` | External ID for cross-account |
+| `aws_profile_name` | AWS profile from `~/.aws/credentials` |
+| `aws_web_identity_token` | OIDC token path for IRSA |
+| `aws_sts_endpoint` | Custom STS endpoint for VPC |
+
+
+
diff --git a/docs/my-website/docs/tutorials/claude_responses_api.md b/docs/my-website/docs/tutorials/claude_responses_api.md
index 343f938b673..0dbb4a2f1e7 100644
--- a/docs/my-website/docs/tutorials/claude_responses_api.md
+++ b/docs/my-website/docs/tutorials/claude_responses_api.md
@@ -237,11 +237,8 @@ mcp_servers:
github_mcp:
url: "https://api.githubcopilot.com/mcp"
auth_type: oauth2
- authorization_url: https://github.com/login/oauth/authorize
- token_url: https://github.com/login/oauth/access_token
client_id: os.environ/GITHUB_OAUTH_CLIENT_ID
client_secret: os.environ/GITHUB_OAUTH_CLIENT_SECRET
- scopes: ["public_repo", "user:email"]
```
@@ -255,9 +252,6 @@ atlassian_mcp:
url: "https://mcp.atlassian.com/v1/sse"
transport: "sse"
auth_type: oauth2
- authorization_url: https://mcp.atlassian.com/v1/authorize
- token_url: https://cf.mcp.atlassian.com/v1/token
- registration_url: https://cf.mcp.atlassian.com/v1/register
```
diff --git a/docs/my-website/docs/vector_store_files.md b/docs/my-website/docs/vector_store_files.md
new file mode 100644
index 00000000000..1a972ebc43f
--- /dev/null
+++ b/docs/my-website/docs/vector_store_files.md
@@ -0,0 +1,120 @@
+# /vector_stores/\{vector_store_id\}/files
+
+Vector store files represent the individual files that live inside a vector store.
+
+| Feature | Supported |
+|---------|-----------|
+| Logging | ✅ (full request/response logging) |
+| Supported Providers | `openai` |
+
+
+## Supported operations
+
+| Operation | Description | OpenAI Python Client | LiteLLM Proxy |
+|-----------|-------------|----------------------|---------------|
+| Create vector store file | Attach a file to a vector store with optional chunking overrides | ✅ | ✅ |
+| List vector store files | Paginated listing with filters | ✅ | ✅ |
+| Retrieve vector store file | Fetch metadata for a single file | ✅ | ✅ |
+| Delete vector store file | Remove a file from a store (file object persists) | ✅ | ✅ |
+| Retrieve vector store file content | Stream processed chunks | ❌ | ✅ |
+| Update vector store file attributes | Patch custom attributes | ❌ | ✅ |
+
+:::note
+Vector store support currently works **only with OpenAI vector stores and OpenAI-uploaded file IDs**.
+:::
+
+
+## Create vector store file
+
+POST http://localhost:4000/v1/vector_stores/{vector_store_id}/files
+
+```python
+from openai import OpenAI
+
+client = OpenAI(
+ base_url="http://localhost:4000", # LiteLLM proxy or OpenAI base
+ api_key="sk-1234"
+)
+
+vector_store_file = client.vector_stores.files.create(
+ vector_store_id="vs_69172088a18c8191ab3e2621aa87d1ee",
+ file_id="file-NDbEDJTfqVh7S4Ugi3CGYw",
+ chunking_strategy={
+ "type": "static",
+ "static": {
+ "max_chunk_size_tokens": 800,
+ "chunk_overlap_tokens": 400,
+ },
+ },
+)
+
+print(vector_store_file)
+```
+
+## List vector store files
+
+GET http://localhost:4000/v1/vector_stores/{vector_store_id}/files
+
+Parameters:
+
+- `vector_store_id` (path, required)
+- `after` / `before` (query, optional) – pagination cursors
+- `filter` (query, optional) – `in_progress`, `completed`, `failed`, `cancelled`
+- `limit` (query, optional, default `20`, range `1-100`)
+- `order` (query, optional, default `desc`)
+
+```python
+vector_store_files = client.vector_stores.files.list(
+ vector_store_id="vs_abc123"
+)
+print(vector_store_files)
+```
+
+## Retrieve vector store file
+
+GET http://localhost:4000/v1/vector_stores/{vector_store_id}/files/{file_id}
+
+```python
+vector_store_file = client.vector_stores.files.retrieve(
+ vector_store_id="vs_abc123",
+ file_id="file-abc123"
+)
+print(vector_store_file)
+```
+
+## Delete vector store file
+
+DELETE http://localhost:4000/v1/vector_stores/{vector_store_id}/files/{file_id}
+
+```python
+deleted_vector_store_file = client.vector_stores.files.delete(
+ vector_store_id="vs_abc123",
+ file_id="file-abc123"
+)
+print(deleted_vector_store_file)
+```
+
+## Proxy-only endpoints
+
+When you need raw content chunks or attribute updates, call the LiteLLM Proxy directly.
+
+### Retrieve file content
+
+```bash
+curl -X GET "http://localhost:4000/v1/vector_stores/\{vector_store_id\}/files/\{file_id\}/content" \
+ -H "Authorization: Bearer sk-1234"
+```
+
+### Update file attributes
+
+```bash
+curl -X POST "http://localhost:4000/v1/vector_stores/\{vector_store_id\}/files/\{file_id\}" \
+ -H "Authorization: Bearer sk-1234" \
+ -H "Content-Type: application/json" \
+ -d '{
+ "attributes": {
+ "category": "support-faq",
+ "language": "en"
+ }
+ }'
+```
diff --git a/docs/my-website/docusaurus.config.js b/docs/my-website/docusaurus.config.js
index cec0479f673..32d5d800b71 100644
--- a/docs/my-website/docusaurus.config.js
+++ b/docs/my-website/docusaurus.config.js
@@ -101,6 +101,21 @@ const config = {
include: ['**/*.{md,mdx}'],
},
],
+ [
+ '@docusaurus/plugin-content-blog',
+ {
+ id: 'blog',
+ path: './blog',
+ routeBasePath: 'blog',
+ blogTitle: 'Blog',
+ blogSidebarTitle: 'All Posts',
+ blogSidebarCount: 'ALL',
+ postsPerPage: 10,
+ showReadingTime: false,
+ sortPosts: 'descending',
+ include: ['**/index.{md,mdx}'],
+ },
+ ],
() => ({
name: 'cripchat',
@@ -129,6 +144,7 @@ const config = {
docs: {
sidebarPath: require.resolve('./sidebars.js'),
},
+ blog: false, // Disable the default blog plugin from preset-classic
theme: {
customCss: require.resolve('./src/css/custom.css'),
},
@@ -177,6 +193,7 @@ const config = {
to: "docs/enterprise"
},
{ to: '/release_notes', label: 'Release Notes', position: 'left' },
+ { to: '/blog', label: 'Blog', position: 'left' },
{
href: 'https://models.litellm.ai/',
label: '💸 LLM Model Cost Map',
@@ -231,6 +248,11 @@ const config = {
],
copyright: `Copyright © ${new Date().getFullYear()} liteLLM`,
},
+ colorMode: {
+ defaultMode: 'light',
+ disableSwitch: false,
+ respectPrefersColorScheme: true,
+ },
prism: {
theme: lightCodeTheme,
darkTheme: darkCodeTheme,
diff --git a/docs/my-website/img/add_agent.png b/docs/my-website/img/add_agent.png
new file mode 100644
index 00000000000..f9a96b95e30
Binary files /dev/null and b/docs/my-website/img/add_agent.png differ
diff --git a/docs/my-website/img/agent_hub_clean.png b/docs/my-website/img/agent_hub_clean.png
new file mode 100644
index 00000000000..89537566f08
Binary files /dev/null and b/docs/my-website/img/agent_hub_clean.png differ
diff --git a/docs/my-website/img/ai_hub_with_agents.png b/docs/my-website/img/ai_hub_with_agents.png
new file mode 100644
index 00000000000..f61214636c1
Binary files /dev/null and b/docs/my-website/img/ai_hub_with_agents.png differ
diff --git a/docs/my-website/img/app_role2.png b/docs/my-website/img/app_role2.png
new file mode 100644
index 00000000000..81eaf8f96ae
Binary files /dev/null and b/docs/my-website/img/app_role2.png differ
diff --git a/docs/my-website/img/app_role3.png b/docs/my-website/img/app_role3.png
new file mode 100644
index 00000000000..e11d73ccc21
Binary files /dev/null and b/docs/my-website/img/app_role3.png differ
diff --git a/docs/my-website/img/app_roles.png b/docs/my-website/img/app_roles.png
new file mode 100644
index 00000000000..4587ab3a058
Binary files /dev/null and b/docs/my-website/img/app_roles.png differ
diff --git a/docs/my-website/img/enterprise_vs_oss.png b/docs/my-website/img/enterprise_vs_oss.png
deleted file mode 100644
index 2b88bdd33ef..00000000000
Binary files a/docs/my-website/img/enterprise_vs_oss.png and /dev/null differ
diff --git a/docs/my-website/img/enterprise_vs_oss_2.png b/docs/my-website/img/enterprise_vs_oss_2.png
new file mode 100644
index 00000000000..62ca1cded57
Binary files /dev/null and b/docs/my-website/img/enterprise_vs_oss_2.png differ
diff --git a/docs/my-website/img/favicon_converted.ico b/docs/my-website/img/favicon_converted.ico
new file mode 100644
index 00000000000..7c45601d5c3
Binary files /dev/null and b/docs/my-website/img/favicon_converted.ico differ
diff --git a/docs/my-website/img/make_agents_public.png b/docs/my-website/img/make_agents_public.png
new file mode 100644
index 00000000000..25cf57ae751
Binary files /dev/null and b/docs/my-website/img/make_agents_public.png differ
diff --git a/docs/my-website/img/public_agent_hub.png b/docs/my-website/img/public_agent_hub.png
new file mode 100644
index 00000000000..24f47da12b0
Binary files /dev/null and b/docs/my-website/img/public_agent_hub.png differ
diff --git a/docs/my-website/package-lock.json b/docs/my-website/package-lock.json
index cc20e0d8308..67f0ea79e68 100644
--- a/docs/my-website/package-lock.json
+++ b/docs/my-website/package-lock.json
@@ -12,7 +12,7 @@
"@docusaurus/plugin-google-gtag": "3.8.1",
"@docusaurus/plugin-ideal-image": "3.8.1",
"@docusaurus/preset-classic": "3.8.1",
- "@docusaurus/theme-mermaid": "^3.8.1",
+ "@docusaurus/theme-mermaid": "3.8.1",
"@inkeep/cxkit-docusaurus": "^0.5.89",
"@mdx-js/react": "^3.0.0",
"clsx": "^1.2.1",
@@ -27,13 +27,30 @@
"dotenv": "^16.4.5"
},
"engines": {
- "node": ">=16.14"
+ "node": ">=16.14",
+ "npm": ">=8.3.0"
+ }
+ },
+ "node_modules/@algolia/abtesting": {
+ "version": "1.10.0",
+ "resolved": "https://registry.npmjs.org/@algolia/abtesting/-/abtesting-1.10.0.tgz",
+ "integrity": "sha512-mQT3jwuTgX8QMoqbIR7mPlWkqQqBPQaPabQzm37xg2txMlaMogK/4hCiiESGdg39MlHZOVHeV+0VJuE7f5UK8A==",
+ "license": "MIT",
+ "dependencies": {
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
+ },
+ "engines": {
+ "node": ">= 14.0.0"
}
},
"node_modules/@algolia/autocomplete-core": {
"version": "1.17.9",
"resolved": "https://registry.npmjs.org/@algolia/autocomplete-core/-/autocomplete-core-1.17.9.tgz",
"integrity": "sha512-O7BxrpLDPJWWHv/DLA9DRFWs+iY1uOJZkqUwjS5HSZAGcl0hIVCQ97LTLewiZmZ402JYUrun+8NqFP+hCknlbQ==",
+ "license": "MIT",
"dependencies": {
"@algolia/autocomplete-plugin-algolia-insights": "1.17.9",
"@algolia/autocomplete-shared": "1.17.9"
@@ -43,6 +60,7 @@
"version": "1.17.9",
"resolved": "https://registry.npmjs.org/@algolia/autocomplete-plugin-algolia-insights/-/autocomplete-plugin-algolia-insights-1.17.9.tgz",
"integrity": "sha512-u1fEHkCbWF92DBeB/KHeMacsjsoI0wFhjZtlCq2ddZbAehshbZST6Hs0Avkc0s+4UyBGbMDnSuXHLuvRWK5iDQ==",
+ "license": "MIT",
"dependencies": {
"@algolia/autocomplete-shared": "1.17.9"
},
@@ -54,6 +72,7 @@
"version": "1.17.9",
"resolved": "https://registry.npmjs.org/@algolia/autocomplete-preset-algolia/-/autocomplete-preset-algolia-1.17.9.tgz",
"integrity": "sha512-Na1OuceSJeg8j7ZWn5ssMu/Ax3amtOwk76u4h5J4eK2Nx2KB5qt0Z4cOapCsxot9VcEN11ADV5aUSlQF4RhGjQ==",
+ "license": "MIT",
"dependencies": {
"@algolia/autocomplete-shared": "1.17.9"
},
@@ -66,98 +85,106 @@
"version": "1.17.9",
"resolved": "https://registry.npmjs.org/@algolia/autocomplete-shared/-/autocomplete-shared-1.17.9.tgz",
"integrity": "sha512-iDf05JDQ7I0b7JEA/9IektxN/80a2MZ1ToohfmNS3rfeuQnIKI3IJlIafD0xu4StbtQTghx9T3Maa97ytkXenQ==",
+ "license": "MIT",
"peerDependencies": {
"@algolia/client-search": ">= 4.9.1 < 6",
"algoliasearch": ">= 4.9.1 < 6"
}
},
"node_modules/@algolia/client-abtesting": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-abtesting/-/client-abtesting-5.27.0.tgz",
- "integrity": "sha512-SITU5umoknxETtw67TxJu9njyMkWiH8pM+Bvw4dzfuIrIAT6Y1rmwV4y0A0didWoT+6xVuammIykbtBMolBcmg==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-abtesting/-/client-abtesting-5.44.0.tgz",
+ "integrity": "sha512-KY5CcrWhRTUo/lV7KcyjrZkPOOF9bjgWpMj9z98VA+sXzVpZtkuskBLCKsWYFp2sbwchZFTd3wJM48H0IGgF7g==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0",
- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
- "@algolia/requester-node-http": "5.27.0"
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
"engines": {
"node": ">= 14.0.0"
}
},
"node_modules/@algolia/client-analytics": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-analytics/-/client-analytics-5.27.0.tgz",
- "integrity": "sha512-go1b9qIZK5vYEQ7jD2bsfhhhVsoh9cFxQ5xF8TzTsg2WOCZR3O92oXCkq15SOK0ngJfqDU6a/k0oZ4KuEnih1Q==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-analytics/-/client-analytics-5.44.0.tgz",
+ "integrity": "sha512-LKOCE8S4ewI9bN3ot9RZoYASPi8b78E918/DVPW3HHjCMUe6i+NjbNG6KotU4RpP6AhRWZjjswbOkWelUO+OoA==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0",
- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
- "@algolia/requester-node-http": "5.27.0"
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
"engines": {
"node": ">= 14.0.0"
}
},
"node_modules/@algolia/client-common": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-common/-/client-common-5.27.0.tgz",
- "integrity": "sha512-tnFOzdNuMzsz93kOClj3fKfuYoF3oYaEB5bggULSj075GJ7HUNedBEm7a6ScrjtnOaOtipbnT7veUpHA4o4wEQ==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-common/-/client-common-5.44.0.tgz",
+ "integrity": "sha512-1yyJm4OYC2cztbS28XYVWwLXdwpLsMG4LoZLOltVglQ2+hc/i9q9fUDZyjRa2Bqt4DmkIfezagfMrokhyH4uxQ==",
+ "license": "MIT",
"engines": {
"node": ">= 14.0.0"
}
},
"node_modules/@algolia/client-insights": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-insights/-/client-insights-5.27.0.tgz",
- "integrity": "sha512-y1qgw39qZijjQBXrqZTiwK1cWgWGRiLpJNWBv9w36nVMKfl9kInrfsYmdBAfmlhVgF/+Woe0y1jQ7pa4HyShAw==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-insights/-/client-insights-5.44.0.tgz",
+ "integrity": "sha512-wVQWK6jYYsbEOjIMI+e5voLGPUIbXrvDj392IckXaCPvQ6vCMTXakQqOYCd+znQdL76S+3wHDo77HZWiAYKrtA==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0",
- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
- "@algolia/requester-node-http": "5.27.0"
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
"engines": {
"node": ">= 14.0.0"
}
},
"node_modules/@algolia/client-personalization": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-personalization/-/client-personalization-5.27.0.tgz",
- "integrity": "sha512-XluG9qPZKEbiLoIfXTKbABsWDNOMPx0t6T2ImJTTeuX+U/zBdmfcqqgcgkqXp+vbXof/XX/4of9Eqo1JaqEmKw==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-personalization/-/client-personalization-5.44.0.tgz",
+ "integrity": "sha512-lkgRjOjOkqmIkebHjHpU9rLJcJNUDMm+eVSW/KJQYLjGqykEZxal+nYJJTBbLceEU2roByP/+27ZmgIwCdf0iA==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0",
- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
- "@algolia/requester-node-http": "5.27.0"
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
"engines": {
"node": ">= 14.0.0"
}
},
"node_modules/@algolia/client-query-suggestions": {
- "version": "5.27.0",
- "resolved": "https://registry.npmjs.org/@algolia/client-query-suggestions/-/client-query-suggestions-5.27.0.tgz",
- "integrity": "sha512-V8/To+SsAl2sdw2AAjeLJuCW1L+xpz+LAGerJK7HKqHzE5yQhWmIWZTzqYQcojkii4iBMYn0y3+uReWqT8XVSQ==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-query-suggestions/-/client-query-suggestions-5.44.0.tgz",
+ "integrity": "sha512-sYfhgwKu6NDVmZHL1WEKVLsOx/jUXCY4BHKLUOcYa8k4COCs6USGgz6IjFkUf+niwq8NCECMmTC4o/fVQOalsA==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0",
- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
- "@algolia/requester-node-http": "5.27.0"
+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
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}
},
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+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/client-search/-/client-search-5.44.0.tgz",
+ "integrity": "sha512-/FRKUM1G4xn3vV8+9xH1WJ9XknU8rkBGlefruq9jDhYUAvYozKimhrmC2pRqw/RyHhPivmgZCRuC8jHP8piz4Q==",
+ "license": "MIT",
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+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
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@@ -166,99 +193,95 @@
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"resolved": "https://registry.npmjs.org/@algolia/events/-/events-4.0.1.tgz",
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+ "integrity": "sha512-FQzvOCgoFXAbf5Y6mYozw2aj5KCJoA3m4heImceldzPSMbdyS4atVjJzXKMsfX3wnZTFYwkkt8/z8UesLHlSBQ==",
+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/@algolia/ingestion/-/ingestion-1.27.0.tgz",
- "integrity": "sha512-xNCyWeqpmEo4EdmpG57Fs1fJIQcPwt5NnJ6MBdXnUdMVXF4f5PHgza+HQWQQcYpCsune96jfmR0v7us6gRIlCw==",
+ "version": "1.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/ingestion/-/ingestion-1.44.0.tgz",
+ "integrity": "sha512-5+S5ynwMmpTpCLXGjTDpeIa81J+R4BLH0lAojOhmeGSeGEHQTqacl/4sbPyDTcidvnWhaqtyf8m42ue6lvISAw==",
+ "license": "MIT",
"dependencies": {
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- "@algolia/requester-browser-xhr": "5.27.0",
- "@algolia/requester-fetch": "5.27.0",
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+ "@algolia/client-common": "5.44.0",
+ "@algolia/requester-browser-xhr": "5.44.0",
+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
},
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}
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+ "version": "1.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/monitoring/-/monitoring-1.44.0.tgz",
+ "integrity": "sha512-xhaTN8pXJjR6zkrecg4Cc9YZaQK2LKm2R+LkbAq+AYGBCWJxtSGlNwftozZzkUyq4AXWoyoc0x2SyBtq5LRtqQ==",
+ "license": "MIT",
"dependencies": {
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+ "@algolia/client-common": "5.44.0",
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+ "@algolia/requester-node-http": "5.44.0"
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}
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- "resolved": "https://registry.npmjs.org/@algolia/recommend/-/recommend-5.27.0.tgz",
- "integrity": "sha512-cqfTMF1d1cc7hg0vITNAFxJZas7MJ4Obc36WwkKpY23NOtGb+4tH9X7UKlQa2PmTgbXIANoJ/DAQTeiVlD2I4Q==",
+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/recommend/-/recommend-5.44.0.tgz",
+ "integrity": "sha512-GNcite/uOIS7wgRU1MT7SdNIupGSW+vbK9igIzMePvD2Dl8dy0O3urKPKIbTuZQqiVH1Cb84y5cgLvwNrdCj/Q==",
+ "license": "MIT",
"dependencies": {
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+ "@algolia/client-common": "5.44.0",
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+ "@algolia/requester-fetch": "5.44.0",
+ "@algolia/requester-node-http": "5.44.0"
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}
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+ "resolved": "https://registry.npmjs.org/@algolia/requester-browser-xhr/-/requester-browser-xhr-5.44.0.tgz",
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+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0"
+ "@algolia/client-common": "5.44.0"
},
"engines": {
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}
},
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- "version": "5.27.0",
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+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/requester-fetch/-/requester-fetch-5.44.0.tgz",
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+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0"
+ "@algolia/client-common": "5.44.0"
},
"engines": {
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}
},
"node_modules/@algolia/requester-node-http": {
- "version": "5.27.0",
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+ "version": "5.44.0",
+ "resolved": "https://registry.npmjs.org/@algolia/requester-node-http/-/requester-node-http-5.44.0.tgz",
+ "integrity": "sha512-MULm0qeAIk4cdzZ/ehJnl1o7uB5NMokg83/3MKhPq0Pk7+I0uELGNbzIfAkvkKKEYcHALemKdArtySF9eKzh/A==",
+ "license": "MIT",
"dependencies": {
- "@algolia/client-common": "5.27.0"
+ "@algolia/client-common": "5.44.0"
},
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}
},
- "node_modules/@ampproject/remapping": {
- "version": "2.3.0",
- "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz",
- "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==",
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- "@jridgewell/trace-mapping": "^0.3.24"
- },
- "engines": {
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"resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-1.1.0.tgz",
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+ "license": "MIT",
"dependencies": {
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"tinyexec": "^1.0.1"
@@ -268,9 +291,10 @@
}
},
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- "resolved": "https://registry.npmjs.org/@antfu/utils/-/utils-8.1.1.tgz",
- "integrity": "sha512-Mex9nXf9vR6AhcXmMrlz/HVgYYZpVGJ6YlPgwl7UnaFpnshXs6EK/oa5Gpf3CzENMjkvEx2tQtntGnb7UtSTOQ==",
+ "version": "9.3.0",
+ "resolved": "https://registry.npmjs.org/@antfu/utils/-/utils-9.3.0.tgz",
+ "integrity": "sha512-9hFT4RauhcUzqOE4f1+frMKLZrgNog5b06I7VmZQV1BkvwvqrbC8EBZf3L1eEL2AKb6rNKjER0sEvJiSP1FXEA==",
+ "license": "MIT",
"funding": {
"url": "https://github.com/sponsors/antfu"
}
@@ -279,6 +303,7 @@
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"resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz",
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+ "license": "MIT",
"dependencies": {
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"js-tokens": "^4.0.0",
@@ -289,28 +314,30 @@
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- "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.27.5.tgz",
- "integrity": "sha512-KiRAp/VoJaWkkte84TvUd9qjdbZAdiqyvMxrGl1N6vzFogKmaLgoM3L1kgtLicp2HP5fBJS8JrZKLVIZGVJAVg==",
+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.28.5.tgz",
+ "integrity": "sha512-6uFXyCayocRbqhZOB+6XcuZbkMNimwfVGFji8CTZnCzOHVGvDqzvitu1re2AU5LROliz7eQPhB8CpAMvnx9EjA==",
+ "license": "MIT",
"engines": {
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}
},
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- "version": "7.27.4",
- "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.27.4.tgz",
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.28.5.tgz",
+ "integrity": "sha512-e7jT4DxYvIDLk1ZHmU/m/mB19rex9sv0c2ftBtjSBv+kVM/902eh0fINUzD7UwLLNR+jU585GxUJ8/EBfAM5fw==",
+ "license": "MIT",
"dependencies": {
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"@babel/code-frame": "^7.27.1",
- "@babel/generator": "^7.27.3",
+ "@babel/generator": "^7.28.5",
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- "@babel/helper-module-transforms": "^7.27.3",
- "@babel/helpers": "^7.27.4",
- "@babel/parser": "^7.27.4",
+ "@babel/helper-module-transforms": "^7.28.3",
+ "@babel/helpers": "^7.28.4",
+ "@babel/parser": "^7.28.5",
"@babel/template": "^7.27.2",
- "@babel/traverse": "^7.27.4",
- "@babel/types": "^7.27.3",
+ "@babel/traverse": "^7.28.5",
+ "@babel/types": "^7.28.5",
+ "@jridgewell/remapping": "^2.3.5",
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"debug": "^4.1.0",
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@@ -329,19 +356,21 @@
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
},
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- "version": "7.27.5",
- "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.27.5.tgz",
- "integrity": "sha512-ZGhA37l0e/g2s1Cnzdix0O3aLYm66eF8aufiVteOgnwxgnRP8GoyMj7VWsgWnQbVKXyge7hqrFh2K2TQM6t1Hw==",
+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.28.5.tgz",
+ "integrity": "sha512-3EwLFhZ38J4VyIP6WNtt2kUdW9dokXA9Cr4IVIFHuCpZ3H8/YFOl5JjZHisrn1fATPBmKKqXzDFvh9fUwHz6CQ==",
+ "license": "MIT",
"dependencies": {
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- "@babel/types": "^7.27.3",
- "@jridgewell/gen-mapping": "^0.3.5",
- "@jridgewell/trace-mapping": "^0.3.25",
+ "@babel/parser": "^7.28.5",
+ "@babel/types": "^7.28.5",
+ "@jridgewell/gen-mapping": "^0.3.12",
+ "@jridgewell/trace-mapping": "^0.3.28",
"jsesc": "^3.0.2"
},
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@@ -352,6 +381,7 @@
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+ "license": "MIT",
"dependencies": {
"@babel/types": "^7.27.3"
},
@@ -363,6 +393,7 @@
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+ "license": "MIT",
"dependencies": {
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
},
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/helper-create-class-features-plugin/-/helper-create-class-features-plugin-7.28.5.tgz",
+ "integrity": "sha512-q3WC4JfdODypvxArsJQROfupPBq9+lMwjKq7C33GhbFYJsufD0yd/ziwD+hJucLeWsnFPWZjsU2DNFqBPE7jwQ==",
+ "license": "MIT",
"dependencies": {
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- "@babel/helper-member-expression-to-functions": "^7.27.1",
+ "@babel/helper-annotate-as-pure": "^7.27.3",
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- "@babel/traverse": "^7.27.1",
+ "@babel/traverse": "^7.28.5",
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
},
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/helper-create-regexp-features-plugin/-/helper-create-regexp-features-plugin-7.28.5.tgz",
+ "integrity": "sha512-N1EhvLtHzOvj7QQOUCCS3NrPJP8c5W6ZXCHDn7Yialuy1iu4r5EmIYkXlKNqT99Ciw+W0mDqWoR6HWMZlFP3hw==",
+ "license": "MIT",
"dependencies": {
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- "regexpu-core": "^6.2.0",
+ "@babel/helper-annotate-as-pure": "^7.27.3",
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
},
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+ "version": "0.6.5",
+ "resolved": "https://registry.npmjs.org/@babel/helper-define-polyfill-provider/-/helper-define-polyfill-provider-0.6.5.tgz",
+ "integrity": "sha512-uJnGFcPsWQK8fvjgGP5LZUZZsYGIoPeRjSF5PGwrelYgq7Q15/Ft9NGFp1zglwgIv//W0uG4BevRuSJRyylZPg==",
+ "license": "MIT",
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}
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+ "license": "MIT",
+ "engines": {
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+ }
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+ "license": "MIT",
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+ "@babel/traverse": "^7.28.5",
+ "@babel/types": "^7.28.5"
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+ "license": "MIT",
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+ "license": "MIT",
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- "@babel/traverse": "^7.27.3"
+ "@babel/traverse": "^7.28.3"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
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}
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+ "license": "MIT",
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}
},
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- "resolved": "https://registry.npmjs.org/@babel/helper-wrap-function/-/helper-wrap-function-7.27.1.tgz",
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+ "version": "7.28.3",
+ "resolved": "https://registry.npmjs.org/@babel/helper-wrap-function/-/helper-wrap-function-7.28.3.tgz",
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+ "license": "MIT",
"dependencies": {
- "@babel/template": "^7.27.1",
- "@babel/traverse": "^7.27.1",
- "@babel/types": "^7.27.1"
+ "@babel/template": "^7.27.2",
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+ "@babel/types": "^7.28.2"
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+ "license": "MIT",
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- "@babel/types": "^7.27.6"
+ "@babel/types": "^7.28.4"
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+ "version": "7.28.5",
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+ "license": "MIT",
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+ "@babel/types": "^7.28.5"
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@@ -616,12 +676,13 @@
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-bugfix-firefox-class-in-computed-class-key/-/plugin-bugfix-firefox-class-in-computed-class-key-7.28.5.tgz",
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+ "license": "MIT",
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- "@babel/traverse": "^7.27.1"
+ "@babel/traverse": "^7.28.5"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "resolved": "https://registry.npmjs.org/@babel/plugin-bugfix-v8-static-class-fields-redefine-readonly/-/plugin-bugfix-v8-static-class-fields-redefine-readonly-7.28.3.tgz",
+ "integrity": "sha512-b6YTX108evsvE4YgWyQ921ZAFFQm3Bn+CA3+ZXlNVnPhx+UfsVURoPjfGAPCjBgrqo30yX/C2nZGX96DxvR9Iw==",
+ "license": "MIT",
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- "@babel/traverse": "^7.27.1"
+ "@babel/traverse": "^7.28.3"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "version": "7.28.0",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-async-generator-functions/-/plugin-transform-async-generator-functions-7.28.0.tgz",
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+ "license": "MIT",
"dependencies": {
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- "@babel/traverse": "^7.27.1"
+ "@babel/traverse": "^7.28.0"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "@babel/helper-create-class-features-plugin": "^7.28.3",
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},
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+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-classes/-/plugin-transform-classes-7.28.4.tgz",
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+ "license": "MIT",
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+ "@babel/helper-annotate-as-pure": "^7.27.3",
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- "@babel/traverse": "^7.27.1",
- "globals": "^11.1.0"
+ "@babel/traverse": "^7.28.4"
},
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+ "license": "MIT",
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-destructuring/-/plugin-transform-destructuring-7.28.5.tgz",
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+ "license": "MIT",
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+ "@babel/helper-plugin-utils": "^7.27.1",
+ "@babel/traverse": "^7.28.5"
},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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},
@@ -992,10 +1079,27 @@
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}
},
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+ "version": "7.28.0",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-explicit-resource-management/-/plugin-transform-explicit-resource-management-7.28.0.tgz",
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+ "license": "MIT",
+ "dependencies": {
+ "@babel/helper-plugin-utils": "^7.27.1",
+ "@babel/plugin-transform-destructuring": "^7.28.0"
+ },
+ "engines": {
+ "node": ">=6.9.0"
+ },
+ "peerDependencies": {
+ "@babel/core": "^7.0.0-0"
+ }
+ },
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-exponentiation-operator/-/plugin-transform-exponentiation-operator-7.28.5.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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},
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-logical-assignment-operators/-/plugin-transform-logical-assignment-operators-7.28.5.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-modules-systemjs/-/plugin-transform-modules-systemjs-7.28.5.tgz",
+ "integrity": "sha512-vn5Jma98LCOeBy/KpeQhXcV2WZgaRUtjwQmjoBuLNlOmkg0fB5pdvYVeWRYI69wWKwK2cD1QbMiUQnoujWvrew==",
+ "license": "MIT",
"dependencies": {
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+ "@babel/helper-module-transforms": "^7.28.3",
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- "@babel/traverse": "^7.27.1"
+ "@babel/helper-validator-identifier": "^7.28.5",
+ "@babel/traverse": "^7.28.5"
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "version": "7.28.4",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-object-rest-spread/-/plugin-transform-object-rest-spread-7.28.4.tgz",
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+ "license": "MIT",
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- "@babel/plugin-transform-destructuring": "^7.27.3",
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+ "@babel/plugin-transform-destructuring": "^7.28.0",
+ "@babel/plugin-transform-parameters": "^7.27.7",
+ "@babel/traverse": "^7.28.4"
},
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"dependencies": {
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-optional-chaining/-/plugin-transform-optional-chaining-7.28.5.tgz",
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+ "license": "MIT",
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@@ -1288,9 +1412,10 @@
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+ "version": "7.27.7",
+ "resolved": "https://registry.npmjs.org/@babel/plugin-transform-parameters/-/plugin-transform-parameters-7.27.7.tgz",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "@babel/compat-data": "^7.28.5",
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- "babel-plugin-polyfill-regenerator": "^0.6.1",
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
@@ -1733,6 +1884,7 @@
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+ "license": "MIT",
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@@ -1743,13 +1895,14 @@
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+ "version": "7.28.5",
+ "resolved": "https://registry.npmjs.org/@babel/preset-react/-/preset-react-7.28.5.tgz",
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+ "license": "MIT",
"dependencies": {
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@@ -1762,15 +1915,16 @@
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+ "license": "MIT",
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+ "@babel/plugin-transform-typescript": "^7.28.5"
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@@ -1902,6 +2068,7 @@
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"url": "https://opencollective.com/csstools"
}
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"engines": {
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}
@@ -1942,6 +2110,7 @@
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}
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},
@@ -2011,6 +2182,7 @@
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}
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+ "license": "MIT",
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}
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}
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"funding": [
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@@ -2379,6 +2652,7 @@
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}
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},
@@ -2400,6 +2674,7 @@
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}
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@@ -2425,6 +2700,7 @@
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},
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"url": "https://opencollective.com/csstools"
}
],
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@@ -2527,6 +2807,7 @@
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}
],
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},
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}
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@@ -2597,6 +2880,7 @@
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}
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@@ -2624,6 +2908,7 @@
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@@ -2650,6 +2935,7 @@
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@@ -2675,6 +2961,7 @@
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"funding": [
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@@ -2699,11 +2986,12 @@
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"funding": [
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"url": "https://opencollective.com/csstools"
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@@ -2751,6 +3040,7 @@
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"funding": [
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@@ -2777,11 +3067,12 @@
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}
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},
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@@ -2805,6 +3096,7 @@
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@@ -2841,6 +3134,7 @@
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@@ -2867,6 +3161,7 @@
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"funding": [
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@@ -2893,8 +3188,9 @@
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@@ -2944,6 +3241,7 @@
"url": "https://opencollective.com/csstools"
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"engines": {
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},
@@ -2965,6 +3263,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "BSD-3-Clause",
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},
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+ "license": "MIT",
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+ "license": "MIT",
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}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
@@ -3642,6 +3970,7 @@
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+ "license": "MIT",
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@@ -3654,6 +3983,7 @@
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+ "license": "MIT",
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@@ -3675,6 +4005,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
@@ -3713,6 +4045,7 @@
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+ "license": "MIT",
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@@ -3725,6 +4058,7 @@
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+ "license": "MIT",
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@@ -3745,6 +4079,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -3789,6 +4125,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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@@ -3816,28 +4154,31 @@
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+ "version": "1.7.3",
+ "resolved": "https://registry.npmjs.org/@floating-ui/core/-/core-1.7.3.tgz",
+ "integrity": "sha512-sGnvb5dmrJaKEZ+LDIpguvdX3bDlEllmv4/ClQ9awcmCZrlx5jQyyMWFM5kBI+EyNOCDDiKk8il0zeuX3Zlg/w==",
+ "license": "MIT",
"dependencies": {
- "@floating-ui/utils": "^0.2.9"
+ "@floating-ui/utils": "^0.2.10"
}
},
"node_modules/@floating-ui/dom": {
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- "resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.7.1.tgz",
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+ "version": "1.7.4",
+ "resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.7.4.tgz",
+ "integrity": "sha512-OOchDgh4F2CchOX94cRVqhvy7b3AFb+/rQXyswmzmGakRfkMgoWVjfnLWkRirfLEfuD4ysVW16eXzwt3jHIzKA==",
+ "license": "MIT",
"dependencies": {
- "@floating-ui/core": "^1.7.1",
- "@floating-ui/utils": "^0.2.9"
+ "@floating-ui/core": "^1.7.3",
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},
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+ "version": "2.1.6",
+ "resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.1.6.tgz",
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+ "license": "MIT",
"dependencies": {
- "@floating-ui/dom": "^1.0.0"
+ "@floating-ui/dom": "^1.7.4"
},
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"react": ">=16.8.0",
@@ -3845,19 +4186,22 @@
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+ "version": "0.2.10",
+ "resolved": "https://registry.npmjs.org/@floating-ui/utils/-/utils-0.2.10.tgz",
+ "integrity": "sha512-aGTxbpbg8/b5JfU1HXSrbH3wXZuLPJcNEcZQFMxLs3oSzgtVu6nFPkbbGGUvBcUjKV2YyB9Wxxabo+HEH9tcRQ==",
+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/@hapi/hoek/-/hoek-9.3.0.tgz",
- "integrity": "sha512-/c6rf4UJlmHlC9b5BaNvzAcFv7HZ2QHaV0D4/HNlBdvFnvQq8RI4kYdhyPCl7Xj+oWvTWQ8ujhqS53LIgAe6KQ=="
+ "integrity": "sha512-/c6rf4UJlmHlC9b5BaNvzAcFv7HZ2QHaV0D4/HNlBdvFnvQq8RI4kYdhyPCl7Xj+oWvTWQ8ujhqS53LIgAe6KQ==",
+ "license": "BSD-3-Clause"
},
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"resolved": "https://registry.npmjs.org/@hapi/topo/-/topo-5.1.0.tgz",
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+ "license": "BSD-3-Clause",
"dependencies": {
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}
@@ -3865,45 +4209,38 @@
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+ "integrity": "sha512-+wluvCrRhXrhyOmRDJ3q8mux9JkKy5SJ/v8ol2tu4FVjyYvtEzkc/3pK15ET6RKg4b4w4BmTk1+gsCUhf21Ykg==",
+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/@iconify/utils/-/utils-2.3.0.tgz",
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+ "license": "Inkeep, Inc. Customer License (IICL) v1.1"
},
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+ "@inkeep/cxkit-react": "0.5.107",
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},
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+ "license": "Inkeep, Inc. Customer License (IICL) v1.1",
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- "@inkeep/cxkit-color-mode": "0.5.91",
- "@inkeep/cxkit-theme": "0.5.91",
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+ "license": "MIT",
"engines": {
"node": ">=6"
}
@@ -3981,6 +4324,7 @@
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+ "license": "MIT",
"dependencies": {
"@types/prismjs": "^1.26.0",
"clsx": "^2.0.0"
@@ -3990,21 +4334,23 @@
}
},
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+ "version": "0.5.107",
+ "resolved": "https://registry.npmjs.org/@inkeep/cxkit-react/-/cxkit-react-0.5.107.tgz",
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+ "license": "Inkeep, Inc. Customer License (IICL) v1.1",
"dependencies": {
- "@inkeep/cxkit-styled": "0.5.91",
+ "@inkeep/cxkit-styled": "0.5.107",
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"lucide-react": "^0.503.0"
}
},
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+ "version": "0.5.107",
+ "resolved": "https://registry.npmjs.org/@inkeep/cxkit-styled/-/cxkit-styled-0.5.107.tgz",
+ "integrity": "sha512-wEmnE2en4ijscv0QYvWY8sWkZoXmfNxXWuzSe2GhkaxMT1oVcausSTl6lwYMy+LFcD8BZf3C83P+5p2tOSc2vA==",
+ "license": "Inkeep, Inc. Customer License (IICL) v1.1",
"dependencies": {
- "@inkeep/cxkit-primitives": "0.5.91",
+ "@inkeep/cxkit-primitives": "0.5.107",
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"clsx": "2.1.1",
"merge-anything": "5.1.7",
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+ "license": "MIT",
"engines": {
"node": ">=6"
}
},
"node_modules/@inkeep/cxkit-theme": {
- "version": "0.5.91",
- "resolved": "https://registry.npmjs.org/@inkeep/cxkit-theme/-/cxkit-theme-0.5.91.tgz",
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+ "version": "0.5.107",
+ "resolved": "https://registry.npmjs.org/@inkeep/cxkit-theme/-/cxkit-theme-0.5.107.tgz",
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+ "license": "Inkeep, Inc. Customer License (IICL) v1.1",
"dependencies": {
"colorjs.io": "0.5.2"
}
},
"node_modules/@inkeep/cxkit-types": {
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+ "version": "0.5.107",
+ "resolved": "https://registry.npmjs.org/@inkeep/cxkit-types/-/cxkit-types-0.5.107.tgz",
+ "integrity": "sha512-YJSTUMRJkWzPLQtk0c0waK8UVCgPX/G78DBdgvGXy5MjG4xDonrns4ZlLH9Xu/lt7iD1+MVGSaEl3XKNrSuphw==",
+ "license": "Inkeep, Inc. Customer License (IICL) v1.1"
},
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"resolved": "https://registry.npmjs.org/@jest/schemas/-/schemas-29.6.3.tgz",
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+ "license": "MIT",
"dependencies": {
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},
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"resolved": "https://registry.npmjs.org/@jest/types/-/types-29.6.3.tgz",
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+ "license": "MIT",
"dependencies": {
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@@ -4060,52 +4411,55 @@
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+ "version": "0.3.13",
+ "resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.13.tgz",
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+ "license": "MIT",
"dependencies": {
- "@jridgewell/set-array": "^1.2.1",
- "@jridgewell/sourcemap-codec": "^1.4.10",
+ "@jridgewell/sourcemap-codec": "^1.5.0",
+ "@jridgewell/trace-mapping": "^0.3.24"
+ }
+ },
+ "node_modules/@jridgewell/remapping": {
+ "version": "2.3.5",
+ "resolved": "https://registry.npmjs.org/@jridgewell/remapping/-/remapping-2.3.5.tgz",
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+ "license": "MIT",
+ "dependencies": {
+ "@jridgewell/gen-mapping": "^0.3.5",
"@jridgewell/trace-mapping": "^0.3.24"
- },
- "engines": {
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}
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+ "license": "MIT",
"engines": {
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}
},
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- "resolved": "https://registry.npmjs.org/@jridgewell/source-map/-/source-map-0.3.6.tgz",
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+ "license": "MIT",
"dependencies": {
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}
},
"node_modules/@jridgewell/sourcemap-codec": {
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+ "license": "MIT"
},
"node_modules/@jridgewell/trace-mapping": {
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- "resolved": "https://registry.npmjs.org/@jridgewell/trace-mapping/-/trace-mapping-0.3.25.tgz",
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+ "resolved": "https://registry.npmjs.org/@jridgewell/trace-mapping/-/trace-mapping-0.3.31.tgz",
+ "integrity": "sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw==",
+ "license": "MIT",
"dependencies": {
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@@ -4115,6 +4469,39 @@
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+ "license": "Apache-2.0",
+ "engines": {
+ "node": ">=10.0"
+ },
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/streamich"
+ },
+ "peerDependencies": {
+ "tslib": "2"
+ }
+ },
+ "node_modules/@jsonjoy.com/buffers": {
+ "version": "1.2.1",
+ "resolved": "https://registry.npmjs.org/@jsonjoy.com/buffers/-/buffers-1.2.1.tgz",
+ "integrity": "sha512-12cdlDwX4RUM3QxmUbVJWqZ/mrK6dFQH4Zxq6+r1YXKXYBNgZXndx2qbCJwh3+WWkCSn67IjnlG3XYTvmvYtgA==",
+ "license": "Apache-2.0",
+ "engines": {
+ "node": ">=10.0"
+ },
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/streamich"
+ },
+ "peerDependencies": {
+ "tslib": "2"
+ }
+ },
+ "node_modules/@jsonjoy.com/codegen": {
+ "version": "1.0.0",
+ "resolved": "https://registry.npmjs.org/@jsonjoy.com/codegen/-/codegen-1.0.0.tgz",
+ "integrity": "sha512-E8Oy+08cmCf0EK/NMxpaJZmOxPqM+6iSe2S4nlSBrPZOORoDJILxtbSUEDKQyTamm/BVAhIGllOBNU79/dwf0g==",
+ "license": "Apache-2.0",
"engines": {
"node": ">=10.0"
},
@@ -4127,14 +4514,39 @@
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- "resolved": "https://registry.npmjs.org/@jsonjoy.com/json-pack/-/json-pack-1.2.0.tgz",
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+ "version": "1.21.0",
+ "resolved": "https://registry.npmjs.org/@jsonjoy.com/json-pack/-/json-pack-1.21.0.tgz",
+ "integrity": "sha512-+AKG+R2cfZMShzrF2uQw34v3zbeDYUqnQ+jg7ORic3BGtfw9p/+N6RJbq/kkV8JmYZaINknaEQ2m0/f693ZPpg==",
+ "license": "Apache-2.0",
"dependencies": {
- "@jsonjoy.com/base64": "^1.1.1",
- "@jsonjoy.com/util": "^1.1.2",
+ "@jsonjoy.com/base64": "^1.1.2",
+ "@jsonjoy.com/buffers": "^1.2.0",
+ "@jsonjoy.com/codegen": "^1.0.0",
+ "@jsonjoy.com/json-pointer": "^1.0.2",
+ "@jsonjoy.com/util": "^1.9.0",
"hyperdyperid": "^1.2.0",
- "thingies": "^1.20.0"
+ "thingies": "^2.5.0",
+ "tree-dump": "^1.1.0"
+ },
+ "engines": {
+ "node": ">=10.0"
+ },
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/streamich"
+ },
+ "peerDependencies": {
+ "tslib": "2"
+ }
+ },
+ "node_modules/@jsonjoy.com/json-pointer": {
+ "version": "1.0.2",
+ "resolved": "https://registry.npmjs.org/@jsonjoy.com/json-pointer/-/json-pointer-1.0.2.tgz",
+ "integrity": "sha512-Fsn6wM2zlDzY1U+v4Nc8bo3bVqgfNTGcn6dMgs6FjrEnt4ZCe60o6ByKRjOGlI2gow0aE/Q41QOigdTqkyK5fg==",
+ "license": "Apache-2.0",
+ "dependencies": {
+ "@jsonjoy.com/codegen": "^1.0.0",
+ "@jsonjoy.com/util": "^1.9.0"
},
"engines": {
"node": ">=10.0"
@@ -4148,9 +4560,14 @@
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+ "resolved": "https://registry.npmjs.org/@jsonjoy.com/util/-/util-1.9.0.tgz",
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+ "license": "Apache-2.0",
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+ "@jsonjoy.com/codegen": "^1.0.0"
+ },
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},
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+ "license": "MIT"
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- "resolved": "https://registry.npmjs.org/@mdx-js/mdx/-/mdx-3.1.0.tgz",
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+ "resolved": "https://registry.npmjs.org/@mdx-js/mdx/-/mdx-3.1.1.tgz",
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+ "license": "MIT",
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"@types/hast": "^3.0.0",
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+ "acorn": "^8.0.0",
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+ "license": "MIT",
"dependencies": {
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},
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+ "version": "0.6.3",
+ "resolved": "https://registry.npmjs.org/@mermaid-js/parser/-/parser-0.6.3.tgz",
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+ "license": "MIT",
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}
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
"node": ">= 8"
}
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+ "license": "MIT",
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@@ -4262,6 +4687,7 @@
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+ "license": "MIT",
"engines": {
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}
@@ -4270,6 +4696,7 @@
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+ "license": "MIT",
"dependencies": {
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},
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+ "integrity": "sha512-9ByhssR2fPVsNZj478qUUbKfmL0+t5BDVyjShtyZZLiK7ZDAArFFfopyOTj0M05wE2tJPisA4iTnnXl2YoPvOA==",
+ "license": "ISC"
},
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"resolved": "https://registry.npmjs.org/@pnpm/npm-conf/-/npm-conf-2.3.1.tgz",
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+ "license": "MIT",
"dependencies": {
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+ "integrity": "sha512-wwQAWhWSuHaag8c4q/KN/vCoeOJYshAIvMQwD4GpSb3OiZklFfvAgmj0VCBBImRpuF/aFgIRzllXlVX93Jevww==",
+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/@radix-ui/number/-/number-1.1.0.tgz",
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+ "version": "1.1.1",
+ "resolved": "https://registry.npmjs.org/@radix-ui/number/-/number-1.1.1.tgz",
+ "integrity": "sha512-MkKCwxlXTgz6CFoJx3pCwn07GKp36+aZyu/u2Ln2VrA5DcdyCZkASEDBTd8x5whTQQL5CiYf4prXKLcgQdv29g==",
+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.1.2.tgz",
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+ "version": "1.1.3",
+ "resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.1.3.tgz",
+ "integrity": "sha512-JTF99U/6XIjCBo0wqkU5sK10glYe27MRRsfwoiq5zzOEZLHU3A3KCMa5X/azekYRCJ0HlwI0crAXS/5dEHTzDg==",
+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/@radix-ui/react-arrow/-/react-arrow-1.1.7.tgz",
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+ "license": "MIT",
"dependencies": {
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},
@@ -4332,10 +4765,52 @@
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}
},
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+ "resolved": "https://registry.npmjs.org/@radix-ui/react-primitive/-/react-primitive-2.1.3.tgz",
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+ "license": "MIT",
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+ },
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+ "@types/react-dom": "*",
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+ "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
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+ "peerDependenciesMeta": {
+ "@types/react": {
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+ "@types/react-dom": {
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+ "resolved": "https://registry.npmjs.org/@radix-ui/react-slot/-/react-slot-1.2.3.tgz",
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+ "license": "MIT",
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+ },
+ "peerDependencies": {
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+ "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
+ },
+ "peerDependenciesMeta": {
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
+ "peerDependencies": {
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+ "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
+ },
+ "peerDependenciesMeta": {
+ "@types/react": {
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+ }
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+ "resolved": "https://registry.npmjs.org/@radix-ui/react-use-layout-effect/-/react-use-layout-effect-1.1.0.tgz",
+ "integrity": "sha512-+FPE0rOdziWSrH9athwI1R0HDVbWlEhd+FR+aSDk4uWGmSJ9Z54sdZVDQPZAinJhJXwfT+qnj969mCsT2gfm5w==",
+ "license": "MIT",
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+ "license": "MIT",
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+ "integrity": "sha512-SJ31y+Q/zAyShtXJc8x83i9TYdbAfHZ++tUZnvjJJqFjzsdUnKsxPL6IEtBlxKkU7yzer//GQtZSV4GbldL3YA==",
+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -4593,15 +5097,31 @@
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+ "license": "MIT",
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@@ -4686,10 +5210,52 @@
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -5375,15 +6133,23 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ },
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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}
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+ "license": "MIT",
"dependencies": {
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}
},
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+ "license": "MIT",
"dependencies": {
"@types/http-errors": "*",
"@types/node": "*",
- "@types/send": "*"
+ "@types/send": "<1"
+ }
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+ "node_modules/@types/serve-static/node_modules/@types/send": {
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+ "resolved": "https://registry.npmjs.org/@types/send/-/send-0.17.6.tgz",
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+ "license": "MIT",
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+ "@types/node": "*"
}
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+ "license": "MIT",
"optional": true
},
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+ "license": "MIT"
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+ "license": "MIT",
"dependencies": {
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}
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- "resolved": "https://registry.npmjs.org/@types/yargs/-/yargs-17.0.33.tgz",
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+ "license": "MIT",
"dependencies": {
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}
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT"
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+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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}
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+ "license": "Apache-2.0",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "(MIT OR CC0-1.0)",
"engines": {
"node": ">=10"
},
@@ -7524,6 +8489,7 @@
"engines": [
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],
+ "license": "Apache-2.0",
"bin": {
"ansi-html": "bin/ansi-html"
}
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
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+ "license": "ISC",
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+ "license": "MIT"
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+ "license": "Python-2.0"
},
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"resolved": "https://registry.npmjs.org/aria-hidden/-/aria-hidden-1.2.6.tgz",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"bin": {
"astring": "bin/astring"
}
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+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.21.tgz",
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"funding": [
{
"type": "opencollective",
@@ -7627,10 +8603,11 @@
"url": "https://github.com/sponsors/ai"
}
],
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+ "fraction.js": "^5.3.4",
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+ "version": "1.7.3",
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+ "license": "Apache-2.0",
+ "peerDependencies": {
+ "react-native-b4a": "*"
+ },
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+ "react-native-b4a": {
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+ }
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"resolved": "https://registry.npmjs.org/babel-loader/-/babel-loader-9.2.1.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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}
},
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+ "version": "0.4.14",
+ "resolved": "https://registry.npmjs.org/babel-plugin-polyfill-corejs2/-/babel-plugin-polyfill-corejs2-0.4.14.tgz",
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+ "license": "MIT",
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- "@babel/helper-define-polyfill-provider": "^0.6.4",
+ "@babel/compat-data": "^7.27.7",
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+ "license": "ISC",
"bin": {
"semver": "bin/semver.js"
}
},
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+ "version": "0.13.0",
+ "resolved": "https://registry.npmjs.org/babel-plugin-polyfill-corejs3/-/babel-plugin-polyfill-corejs3-0.13.0.tgz",
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+ "license": "MIT",
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+ "@babel/helper-define-polyfill-provider": "^0.6.5",
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+ "license": "MIT",
"dependencies": {
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+ "@babel/helper-define-polyfill-provider": "^0.6.5"
},
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
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+ "license": "MIT"
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+ "license": "Apache-2.0",
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+ "bare-abort-controller": "*"
+ },
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+ "bare-abort-controller": {
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+ "version": "4.5.1",
+ "resolved": "https://registry.npmjs.org/bare-fs/-/bare-fs-4.5.1.tgz",
+ "integrity": "sha512-zGUCsm3yv/ePt2PHNbVxjjn0nNB1MkIaR4wOCxJ2ig5pCf5cCVAYJXVhQg/3OhhJV6DB1ts7Hv0oUaElc2TPQg==",
+ "license": "Apache-2.0",
"optional": true,
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"bare-path": "^3.0.0",
- "bare-stream": "^2.6.4"
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+ "bare-url": "^2.2.2",
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@@ -7761,9 +8766,10 @@
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+ "license": "Apache-2.0",
"optional": true,
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+ "license": "Apache-2.0",
"optional": true,
"dependencies": {
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}
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+ "license": "Apache-2.0",
"optional": true,
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@@ -7799,6 +8807,16 @@
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+ "resolved": "https://registry.npmjs.org/bare-url/-/bare-url-2.3.2.tgz",
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+ "license": "Apache-2.0",
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+ }
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@@ -7816,17 +8834,29 @@
"type": "consulting",
"url": "https://feross.org/support"
}
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+ "resolved": "https://registry.npmjs.org/baseline-browser-mapping/-/baseline-browser-mapping-2.8.28.tgz",
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+ "license": "Apache-2.0",
+ "bin": {
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+ }
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+ "license": "MIT"
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+ "license": "MIT",
"engines": {
"node": "*"
}
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+ "license": "MIT",
"engines": {
"node": ">=8"
},
@@ -7842,10 +8873,28 @@
"url": "https://github.com/sponsors/sindresorhus"
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+ },
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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{
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@@ -7951,11 +9028,13 @@
"url": "https://github.com/sponsors/ai"
}
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@@ -7982,6 +9061,7 @@
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}
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+ "license": "MIT",
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+ "resolved": "https://registry.npmjs.org/cacheable-request/-/cacheable-request-10.2.14.tgz",
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+ "license": "MIT",
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+ "engines": {
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+ "license": "MIT",
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+ },
+ "funding": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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"engines": {
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+ "license": "MIT",
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{
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@@ -8122,12 +9243,14 @@
"type": "github",
"url": "https://github.com/sponsors/ai"
}
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+ "license": "MIT",
"funding": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
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+ "license": "MIT",
"funding": {
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"url": "https://github.com/sponsors/wooorm"
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+ "license": "MIT",
"funding": {
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"url": "https://github.com/sponsors/wooorm"
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+ "license": "MIT",
"funding": {
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "Apache-2.0",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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}
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}
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+ "license": "Apache-2.0",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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}
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- },
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+ "license": "BSD-3-Clause",
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+ "license": "ISC",
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+ "license": "ISC",
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+ "license": "BSD-3-Clause",
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+ "license": "BSD-3-Clause",
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+ "license": "ISC"
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+ "license": "ISC",
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+ "license": "ISC",
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+ "license": "ISC",
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+ "license": "ISC",
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+ "license": "ISC",
"dependencies": {
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+ "license": "MIT",
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}
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+ },
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "Apache-2.0",
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@@ -9986,12 +11257,14 @@
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+ "license": "BSD-2-Clause",
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"dev": true,
+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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}
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "resolved": "https://registry.npmjs.org/error-ex/-/error-ex-1.3.4.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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@@ -10296,10 +11601,24 @@
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+ "resolved": "https://registry.npmjs.org/esprima/-/esprima-4.0.1.tgz",
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+ "license": "BSD-2-Clause",
+ "bin": {
+ "esparse": "bin/esparse.js",
+ "esvalidate": "bin/esvalidate.js"
+ },
+ "engines": {
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+ "license": "BSD-2-Clause",
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+ "license": "BSD-2-Clause",
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "version": "3.5.0",
+ "resolved": "https://registry.npmjs.org/estree-util-value-to-estree/-/estree-util-value-to-estree-3.5.0.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"engines": {
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+ "integrity": "sha512-8guHBZCwKnFhYdHr2ysuRWErTwhoN2X8XELRlrRwpmfeY2jjuUN4taQMsULKUVo1K4DvZl+0pgfyoysHxvmvEw==",
+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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}
},
+ "node_modules/events-universal": {
+ "version": "1.0.1",
+ "resolved": "https://registry.npmjs.org/events-universal/-/events-universal-1.0.1.tgz",
+ "integrity": "sha512-LUd5euvbMLpwOF8m6ivPCbhQeSiYVNb8Vs0fQ8QjXo0JTkEHpz8pxdQf0gStltaPpw0Cca8b39KxvK9cfKRiAw==",
+ "license": "Apache-2.0",
+ "dependencies": {
+ "bare-events": "^2.7.0"
+ }
+ },
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+ "license": "MIT",
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+ "license": "(MIT OR WTFPL)",
"engines": {
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@@ -10512,6 +11858,7 @@
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+ "license": "MIT",
"dependencies": {
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@@ -10553,10 +11900,23 @@
"url": "https://opencollective.com/express"
}
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+ "resolved": "https://registry.npmjs.org/content-disposition/-/content-disposition-0.5.4.tgz",
+ "integrity": "sha512-FveZTNuGw04cxlAiWbzi6zTAL/lhehaWbTtgluJh4/E95DqMwTmha3KZN1aAWA8cFIhHzMZUvLevkw5Rqk+tSQ==",
+ "license": "MIT",
+ "dependencies": {
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+ },
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+ }
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+ "license": "MIT",
"dependencies": {
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@@ -10564,22 +11924,41 @@
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@@ -10630,12 +12013,14 @@
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+ "license": "ISC",
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@@ -10652,10 +12038,23 @@
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}
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+ "license": "MIT",
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@@ -10682,10 +12106,42 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "BSD-3-Clause",
"bin": {
"flat": "cli.js"
}
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"funding": [
{
"type": "individual",
"url": "https://github.com/sponsors/RubenVerborgh"
}
],
+ "license": "MIT",
"engines": {
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@@ -10814,12 +12278,10 @@
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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},
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- "type": "patreon",
+ "type": "github",
"url": "https://github.com/sponsors/rawify"
}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "node": ">=18"
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+ "license": "MIT",
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@@ -11061,15 +12565,63 @@
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+ "license": "MIT",
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+ },
+ "funding": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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}
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+ "license": "BSD-3-Clause",
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
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}
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
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"clean-css": "^5.2.2",
@@ -11491,6 +13146,7 @@
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}
],
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@@ -11498,15 +13154,23 @@
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}
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+ "resolved": "https://registry.npmjs.org/http-cache-semantics/-/http-cache-semantics-4.2.0.tgz",
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+ "license": "BSD-2-Clause"
+ },
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"resolved": "https://registry.npmjs.org/http-deceiver/-/http-deceiver-1.2.7.tgz",
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+ "integrity": "sha512-LmpOGxTfbpgtGVxJrj5k7asXHCgNZp5nLfp+hWc8QQRqtb7fUy6kRY3BO1h9ddF6yIPYUARgxGOwB42DnxIaNw==",
+ "license": "MIT"
},
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+ "license": "MIT",
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@@ -11518,15 +13182,23 @@
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+ "version": "2.0.4",
+ "resolved": "https://registry.npmjs.org/inherits/-/inherits-2.0.4.tgz",
+ "integrity": "sha512-k/vGaX4/Yla3WzyMCvTQOXYeIHvqOKtnqBduzTHpzpQZzAskKMhZ2K+EnBiSM9zGSoIFeMpXKxa4dYeZIQqewQ==",
+ "license": "ISC"
+ },
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"resolved": "https://registry.npmjs.org/http-parser-js/-/http-parser-js-0.5.10.tgz",
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+ "integrity": "sha512-Pysuw9XpUq5dVc/2SMHpuTY01RFl8fttgcyunjL7eEMhGM3cI4eOmiCycJDVCo/7O7ClfQD3SaI6ftDzqOXYMA==",
+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
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+ "license": "Apache-2.0",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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}
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- "resolved": "https://registry.npmjs.org/iconv-lite/-/iconv-lite-0.4.24.tgz",
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+ "version": "0.6.3",
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+ "license": "MIT",
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- "safer-buffer": ">= 2.1.2 < 3"
+ "safer-buffer": ">= 2.1.2 < 3.0.0"
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+ "license": "ISC",
"engines": {
"node": "^10 || ^12 || >= 14"
},
@@ -11650,12 +13331,14 @@
"type": "consulting",
"url": "https://feross.org/support"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -11686,10 +13371,20 @@
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+ "license": "MIT",
+ "engines": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "ISC"
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},
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- "resolved": "https://registry.npmjs.org/inline-style-parser/-/inline-style-parser-0.2.4.tgz",
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+ "resolved": "https://registry.npmjs.org/inline-style-parser/-/inline-style-parser-0.2.6.tgz",
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+ "license": "MIT"
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+ "license": "ISC",
"engines": {
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}
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+ "license": "MIT",
"dependencies": {
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}
},
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- "resolved": "https://registry.npmjs.org/ipaddr.js/-/ipaddr.js-1.9.1.tgz",
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+ "version": "2.2.0",
+ "resolved": "https://registry.npmjs.org/ipaddr.js/-/ipaddr.js-2.2.0.tgz",
+ "integrity": "sha512-Ag3wB2o37wslZS19hZqorUnrnzSkpOVy+IiiDEiTqNubEYpYuHWIf6K4psgN2ZWKExS4xhVCrRVfb/wfW8fWJA==",
+ "license": "MIT",
"engines": {
- "node": ">= 0.10"
+ "node": ">= 10"
}
},
"node_modules/is-alphabetical": {
"version": "2.0.1",
"resolved": "https://registry.npmjs.org/is-alphabetical/-/is-alphabetical-2.0.1.tgz",
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
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+ "license": "MIT",
"dependencies": {
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+ "integrity": "sha512-zz06S8t0ozoDXMG+ube26zeCTNXcKIPJZJi8hBrF4idCLms4CG9QtK7qBl1boi5ODzFpjswb5JPmHCbMpjaYzg==",
+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
@@ -11825,6 +13535,7 @@
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+ "license": "MIT",
"bin": {
"is-docker": "cli.js"
},
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
"bin": {
"is-docker": "cli.js"
},
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+ "license": "MIT",
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@@ -11926,9 +13645,10 @@
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+ "resolved": "https://registry.npmjs.org/is-network-error/-/is-network-error-1.3.0.tgz",
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+ "license": "MIT",
"engines": {
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},
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+ "resolved": "https://registry.npmjs.org/is-npm/-/is-npm-6.1.0.tgz",
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+ "license": "MIT",
"engines": {
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},
@@ -11947,10 +13668,20 @@
"url": "https://github.com/sponsors/sindresorhus"
}
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+ "resolved": "https://registry.npmjs.org/is-number/-/is-number-7.0.0.tgz",
+ "integrity": "sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng==",
+ "license": "MIT",
+ "engines": {
+ "node": ">=0.12.0"
+ }
+ },
"node_modules/is-obj": {
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"resolved": "https://registry.npmjs.org/is-obj/-/is-obj-1.0.1.tgz",
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+ "license": "MIT",
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}
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+ "license": "MIT",
"engines": {
"node": ">=8"
}
},
+ "node_modules/is-plain-obj": {
+ "version": "4.1.0",
+ "resolved": "https://registry.npmjs.org/is-plain-obj/-/is-plain-obj-4.1.0.tgz",
+ "integrity": "sha512-+Pgi+vMuUNkJyExiMBt5IlFoMyKnr5zhJ4Uspz58WOhBF5QoIZkFyNHIbBAtHwzVAgk5RtndVNsDRN61/mmDqg==",
+ "license": "MIT",
+ "engines": {
+ "node": ">=12"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
+ },
"node_modules/is-plain-object": {
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"resolved": "https://registry.npmjs.org/is-plain-object/-/is-plain-object-2.0.4.tgz",
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+ "license": "MIT",
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},
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
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},
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+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
"engines": {
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}
},
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- "resolved": "https://registry.npmjs.org/isarray/-/isarray-1.0.0.tgz",
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+ "version": "0.0.1",
+ "resolved": "https://registry.npmjs.org/isarray/-/isarray-0.0.1.tgz",
+ "integrity": "sha512-D2S+3GLxWH+uhrNEcoh/fnmYeP8E8/zHl644d/jdA0g2uyXvy3sb0qxotE+ne0LtccHknQzWwZEzhak7oJ0COQ==",
+ "license": "MIT"
},
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- "integrity": "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="
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+ "license": "ISC"
},
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"dependencies": {
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@@ -12066,6 +13821,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"bin": {
"jiti": "bin/jiti.js"
}
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+ "license": "BSD-3-Clause",
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],
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+ "license": "MIT",
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+ "license": "MIT",
"bin": {
"marked": "bin/marked.js"
},
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+ "license": "MIT",
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}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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},
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+ "license": "MIT",
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@@ -12538,12 +14357,14 @@
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"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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},
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+ "license": "MIT",
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+ "license": "MIT",
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"ccount": "^2.0.0",
@@ -12616,6 +14440,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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@@ -12634,12 +14459,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/mdast-util-gfm-footnote/-/mdast-util-gfm-footnote-2.1.0.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "integrity": "sha512-GaqWWShW4kv/G9IEucWScBx9G1/vsFZZJUO+tD26M8J8z3Kw5RDQjaoZe03YAClgeS/SWPOcb4nkFBTEi5DUEA==",
+ "license": "CC0-1.0"
},
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"resolved": "https://registry.npmjs.org/media-typer/-/media-typer-0.3.0.tgz",
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+ "license": "MIT",
"engines": {
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}
},
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- "resolved": "https://registry.npmjs.org/memfs/-/memfs-4.17.2.tgz",
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+ "version": "4.51.0",
+ "resolved": "https://registry.npmjs.org/memfs/-/memfs-4.51.0.tgz",
+ "integrity": "sha512-4zngfkVM/GpIhC8YazOsM6E8hoB33NP0BCESPOA6z7qaL6umPJNqkO8CNYaLV2FB2MV6H1O3x2luHHOSqppv+A==",
+ "license": "Apache-2.0",
"dependencies": {
- "@jsonjoy.com/json-pack": "^1.0.3",
- "@jsonjoy.com/util": "^1.3.0",
- "tree-dump": "^1.0.1",
+ "@jsonjoy.com/json-pack": "^1.11.0",
+ "@jsonjoy.com/util": "^1.9.0",
+ "glob-to-regex.js": "^1.0.1",
+ "thingies": "^2.5.0",
+ "tree-dump": "^1.0.3",
"tslib": "^2.0.0"
},
- "engines": {
- "node": ">= 4.0.0"
- },
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@@ -12870,6 +14710,7 @@
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+ "license": "MIT",
"dependencies": {
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},
@@ -12884,6 +14725,7 @@
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+ "license": "MIT",
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
@@ -12891,37 +14733,40 @@
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+ "integrity": "sha512-abv/qOcuPfk3URPfDzmZU1LKmuw8kT+0nIHvKrKgFrwifol/doWcdA4ZqsWQ8ENrFKkd67Mfpo/LovbIUsbt3w==",
+ "license": "MIT"
},
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"integrity": "sha512-8q7VEgMJW4J8tcfVPy8g09NcQwZdbwFEqhe/WZkoIzjn/3TGDwtOCYtXGxA3O8tPzpczCCDgv+P2P5y00ZJOOg==",
+ "license": "MIT",
"engines": {
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}
},
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- "resolved": "https://registry.npmjs.org/mermaid/-/mermaid-11.10.0.tgz",
- "integrity": "sha512-oQsFzPBy9xlpnGxUqLbVY8pvknLlsNIJ0NWwi8SUJjhbP1IT0E0o1lfhU4iYV3ubpy+xkzkaOyDUQMn06vQElQ==",
+ "version": "11.12.1",
+ "resolved": "https://registry.npmjs.org/mermaid/-/mermaid-11.12.1.tgz",
+ "integrity": "sha512-UlIZrRariB11TY1RtTgUWp65tphtBv4CSq7vyS2ZZ2TgoMjs2nloq+wFqxiwcxlhHUvs7DPGgMjs2aeQxz5h9g==",
+ "license": "MIT",
"dependencies": {
- "@braintree/sanitize-url": "^7.0.4",
- "@iconify/utils": "^2.1.33",
- "@mermaid-js/parser": "^0.6.2",
+ "@braintree/sanitize-url": "^7.1.1",
+ "@iconify/utils": "^3.0.1",
+ "@mermaid-js/parser": "^0.6.3",
"@types/d3": "^7.4.3",
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"cytoscape-cose-bilkent": "^4.1.0",
"cytoscape-fcose": "^2.2.0",
"d3": "^7.9.0",
"d3-sankey": "^0.12.3",
- "dagre-d3-es": "7.0.11",
- "dayjs": "^1.11.13",
+ "dagre-d3-es": "7.0.13",
+ "dayjs": "^1.11.18",
"dompurify": "^3.2.5",
"katex": "^0.16.22",
"khroma": "^2.1.0",
"lodash-es": "^4.17.21",
- "marked": "^16.0.0",
+ "marked": "^16.2.1",
"roughjs": "^4.6.6",
"stylis": "^4.3.6",
"ts-dedent": "^2.2.0",
@@ -12929,9 +14774,10 @@
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- "resolved": "https://registry.npmjs.org/marked/-/marked-16.1.2.tgz",
- "integrity": "sha512-rNQt5EvRinalby7zJZu/mB+BvaAY2oz3wCuCjt1RDrWNpS1Pdf9xqMOeC9Hm5adBdcV/3XZPJpG58eT+WBc0XQ==",
+ "version": "16.4.2",
+ "resolved": "https://registry.npmjs.org/marked/-/marked-16.4.2.tgz",
+ "integrity": "sha512-TI3V8YYWvkVf3KJe1dRkpnjs68JUPyEa5vjKrp1XEEJUAOaQc+Qj+L1qWbPd0SJuAdQkFU0h73sXXqwDYxsiDA==",
+ "license": "MIT",
"bin": {
"marked": "bin/marked.js"
},
@@ -12947,6 +14793,7 @@
"https://github.com/sponsors/broofa",
"https://github.com/sponsors/ctavan"
],
+ "license": "MIT",
"bin": {
"uuid": "dist/esm/bin/uuid"
}
@@ -12955,6 +14802,7 @@
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+ "license": "MIT",
"engines": {
"node": ">= 0.6"
}
@@ -12973,6 +14821,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"@types/debug": "^4.0.0",
"debug": "^4.0.0",
@@ -13007,6 +14856,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"decode-named-character-reference": "^1.0.0",
"devlop": "^1.0.0",
@@ -13040,6 +14890,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-character": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -13059,6 +14910,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -13077,12 +14929,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-extension-directive": {
"version": "3.0.2",
"resolved": "https://registry.npmjs.org/micromark-extension-directive/-/micromark-extension-directive-3.0.2.tgz",
"integrity": "sha512-wjcXHgk+PPdmvR58Le9d7zQYWy+vKEU9Se44p2CrCDPiLr2FMyiT4Fyb5UFKFC66wGB3kPlgD7q3TnoqPS7SZA==",
+ "license": "MIT",
"dependencies": {
"devlop": "^1.0.0",
"micromark-factory-space": "^2.0.0",
@@ -13111,6 +14965,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-character": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -13130,6 +14985,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -13148,12 +15004,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-extension-frontmatter": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/micromark-extension-frontmatter/-/micromark-extension-frontmatter-2.0.0.tgz",
"integrity": "sha512-C4AkuM3dA58cgZha7zVnuVxBhDsbttIMiytjgsM2XbHAB2faRVaHRle40558FBN+DJcrLNCoqG5mlrpdU4cRtg==",
+ "license": "MIT",
"dependencies": {
"fault": "^2.0.0",
"micromark-util-character": "^2.0.0",
@@ -13179,6 +15037,7 @@
"url": "https://opencollective.com/unified"
}
],
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"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
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+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/micromark-extension-gfm/-/micromark-extension-gfm-3.0.0.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -13247,6 +15109,7 @@
"url": "https://opencollective.com/unified"
}
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@@ -13265,12 +15128,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
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+ "license": "MIT",
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"micromark-core-commonmark": "^2.0.0",
@@ -13300,6 +15165,7 @@
"url": "https://opencollective.com/unified"
}
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"micromark-util-types": "^2.0.0"
@@ -13319,6 +15185,7 @@
"url": "https://opencollective.com/unified"
}
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@@ -13337,12 +15204,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
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"resolved": "https://registry.npmjs.org/micromark-extension-gfm-strikethrough/-/micromark-extension-gfm-strikethrough-2.1.0.tgz",
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+ "license": "MIT",
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@@ -13369,12 +15238,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
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+ "license": "MIT",
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"micromark-factory-space": "^2.0.0",
@@ -13401,6 +15272,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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"micromark-util-types": "^2.0.0"
@@ -13420,6 +15292,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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@@ -13438,12 +15311,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
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},
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+ "license": "MIT",
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+ "license": "MIT",
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"micromark-factory-space": "^2.0.0",
@@ -13482,6 +15358,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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"micromark-util-types": "^2.0.0"
@@ -13501,6 +15378,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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@@ -13519,7 +15397,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
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"version": "3.0.1",
@@ -13535,6 +15414,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"devlop": "^1.0.0",
@@ -13560,6 +15440,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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"micromark-util-types": "^2.0.0"
@@ -13579,6 +15460,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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@@ -13597,12 +15479,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/micromark-extension-mdx-jsx/-/micromark-extension-mdx-jsx-3.0.2.tgz",
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+ "license": "MIT",
"dependencies": {
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"devlop": "^1.0.0",
@@ -13634,6 +15518,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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"micromark-util-types": "^2.0.0"
@@ -13653,6 +15538,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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@@ -13671,12 +15557,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-extension-mdx-md": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/micromark-extension-mdx-md/-/micromark-extension-mdx-md-2.0.0.tgz",
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+ "license": "MIT",
"dependencies": {
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},
@@ -13689,6 +15577,7 @@
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+ "license": "MIT",
"dependencies": {
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"acorn-jsx": "^5.0.0",
@@ -13708,6 +15597,7 @@
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+ "license": "MIT",
"dependencies": {
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"devlop": "^1.0.0",
@@ -13738,6 +15628,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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@@ -13756,7 +15647,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-destination": {
"version": "2.0.1",
@@ -13772,6 +15664,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-symbol": "^2.0.0",
@@ -13792,6 +15685,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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@@ -13810,7 +15704,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-label": {
"version": "2.0.1",
@@ -13826,6 +15721,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"devlop": "^1.0.0",
"micromark-util-character": "^2.0.0",
@@ -13847,6 +15743,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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@@ -13865,7 +15762,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-mdx-expression": {
"version": "2.0.3",
@@ -13881,6 +15779,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"devlop": "^1.0.0",
@@ -13907,6 +15806,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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"micromark-util-types": "^2.0.0"
@@ -13926,6 +15826,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -13944,7 +15845,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-space": {
"version": "1.1.0",
@@ -13960,6 +15862,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-types": "^1.0.0"
@@ -13978,7 +15881,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-title": {
"version": "2.0.1",
@@ -13994,6 +15898,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-factory-space": "^2.0.0",
"micromark-util-character": "^2.0.0",
@@ -14015,6 +15920,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-character": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14034,6 +15940,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14052,7 +15959,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-factory-whitespace": {
"version": "2.0.1",
@@ -14068,6 +15976,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-factory-space": "^2.0.0",
"micromark-util-character": "^2.0.0",
@@ -14089,6 +15998,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-character": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14108,6 +16018,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14126,7 +16037,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-character": {
"version": "1.2.0",
@@ -14142,6 +16054,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-types": "^1.0.0"
@@ -14160,7 +16073,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-chunked": {
"version": "2.0.1",
@@ -14176,6 +16090,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0"
}
@@ -14193,7 +16108,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-classify-character": {
"version": "2.0.1",
@@ -14209,6 +16125,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-symbol": "^2.0.0",
@@ -14229,6 +16146,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14247,7 +16165,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-combine-extensions": {
"version": "2.0.1",
@@ -14263,6 +16182,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-types": "^2.0.0"
@@ -14282,6 +16202,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0"
}
@@ -14299,7 +16220,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-decode-string": {
"version": "2.0.1",
@@ -14315,6 +16237,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"decode-named-character-reference": "^1.0.0",
"micromark-util-character": "^2.0.0",
@@ -14336,6 +16259,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-symbol": "^2.0.0",
"micromark-util-types": "^2.0.0"
@@ -14354,7 +16278,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-encode": {
"version": "2.0.1",
@@ -14369,7 +16294,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-events-to-acorn": {
"version": "2.0.3",
@@ -14385,6 +16311,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"@types/unist": "^3.0.0",
@@ -14408,7 +16335,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-html-tag-name": {
"version": "2.0.1",
@@ -14423,7 +16351,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-normalize-identifier": {
"version": "2.0.1",
@@ -14439,6 +16368,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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}
@@ -14456,7 +16386,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-resolve-all": {
"version": "2.0.1",
@@ -14472,6 +16403,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"micromark-util-types": "^2.0.0"
}
@@ -14490,6 +16422,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-encode": "^2.0.0",
@@ -14510,6 +16443,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-types": "^2.0.0"
@@ -14528,7 +16462,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-subtokenize": {
"version": "2.1.0",
@@ -14544,6 +16479,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
"devlop": "^1.0.0",
"micromark-util-chunked": "^2.0.0",
@@ -14564,7 +16500,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-symbol": {
"version": "1.1.0",
@@ -14579,7 +16516,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark-util-types": {
"version": "2.0.2",
@@ -14594,7 +16532,8 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/micromark/node_modules/micromark-factory-space": {
"version": "2.0.1",
@@ -14610,6 +16549,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
"dependencies": {
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"micromark-util-types": "^2.0.0"
@@ -14629,6 +16569,7 @@
"url": "https://opencollective.com/unified"
}
],
+ "license": "MIT",
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@@ -14647,12 +16588,14 @@
"type": "OpenCollective",
"url": "https://opencollective.com/unified"
}
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},
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"resolved": "https://registry.npmjs.org/micromatch/-/micromatch-4.0.8.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
"bin": {
"mime": "cli.js"
},
@@ -14673,9 +16617,10 @@
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
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},
@@ -14691,26 +16637,32 @@
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+ "license": "MIT",
"engines": {
"node": ">=6"
}
},
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+ "version": "3.1.0",
+ "resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-3.1.0.tgz",
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+ "license": "MIT",
+ "engines": {
+ "node": ">=10"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
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+ "license": "MIT",
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+ "license": "ISC"
},
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"resolved": "https://registry.npmjs.org/minimatch/-/minimatch-3.1.2.tgz",
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+ "license": "ISC",
"dependencies": {
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+ "license": "MIT",
"funding": {
"url": "https://github.com/sponsors/ljharb"
}
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+ "license": "MIT"
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+ "license": "MIT"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/multicast-dns/-/multicast-dns-7.2.5.tgz",
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+ "license": "MIT",
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"thunky": "^1.0.2"
@@ -14816,6 +16778,7 @@
"url": "https://github.com/sponsors/ai"
}
],
+ "license": "MIT",
"bin": {
"nanoid": "bin/nanoid.cjs"
},
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+ "license": "MIT"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT"
},
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"version": "1.0.0",
@@ -14881,6 +16850,7 @@
"url": "https://paypal.me/jimmywarting"
}
],
+ "license": "MIT",
"engines": {
"node": ">=10.5.0"
}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "(BSD-3-Clause OR GPL-2.0)",
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}
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
+ "engines": {
+ "node": ">=14.16"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "BSD-2-Clause",
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@@ -14993,10 +16985,42 @@
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+ "url": "https://github.com/sponsors/epoberezkin"
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ }
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+ "license": "MIT",
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+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
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+ "license": "ISC"
},
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"dependencies": {
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},
@@ -15639,9 +17565,10 @@
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+ "version": "2.3.0",
+ "resolved": "https://registry.npmjs.org/pkg-types/-/pkg-types-2.3.0.tgz",
+ "integrity": "sha512-SIqCzDRg0s9npO5XQ3tNZioRY1uK06lA41ynBC1YmFTmnY6FjUjVt6s4LoADmwoig1qqD0oK8h1p/8mlMx8Oig==",
+ "license": "MIT",
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+ "license": "MIT"
},
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"resolved": "https://registry.npmjs.org/points-on-path/-/points-on-path-0.2.1.tgz",
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+ "license": "MIT",
"dependencies": {
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"points-on-curve": "0.2.0"
@@ -15680,6 +17609,7 @@
"url": "https://github.com/sponsors/ai"
}
],
+ "license": "MIT",
"dependencies": {
"nanoid": "^3.3.11",
"picocolors": "^1.1.1",
@@ -15703,6 +17633,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT",
"dependencies": {
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},
@@ -15717,6 +17648,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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@@ -15744,6 +17677,7 @@
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+ "license": "MIT",
"dependencies": {
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},
@@ -15755,9 +17689,9 @@
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+ "version": "7.0.12",
+ "resolved": "https://registry.npmjs.org/postcss-color-functional-notation/-/postcss-color-functional-notation-7.0.12.tgz",
+ "integrity": "sha512-TLCW9fN5kvO/u38/uesdpbx3e8AkTYhMvDZYa9JpmImWuTE99bDQ7GU7hdOADIZsiI9/zuxfAJxny/khknp1Zw==",
"funding": [
{
"type": "github",
@@ -15768,11 +17702,12 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT-0",
"dependencies": {
- "@csstools/css-color-parser": "^3.0.10",
+ "@csstools/css-color-parser": "^3.1.0",
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"@csstools/css-tokenizer": "^3.0.4",
- "@csstools/postcss-progressive-custom-properties": "^4.1.0",
+ "@csstools/postcss-progressive-custom-properties": "^4.2.1",
"@csstools/utilities": "^2.0.0"
},
"engines": {
@@ -15796,6 +17731,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT",
"dependencies": {
"@csstools/utilities": "^2.0.0",
"postcss-value-parser": "^4.2.0"
@@ -15821,6 +17757,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT-0",
"dependencies": {
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@@ -15836,6 +17773,7 @@
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+ "license": "MIT",
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@@ -15853,6 +17791,7 @@
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+ "license": "MIT",
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"postcss-value-parser": "^4.2.0"
@@ -15878,6 +17817,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT",
"dependencies": {
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"@csstools/css-parser-algorithms": "^3.0.5",
@@ -15905,6 +17845,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT",
"dependencies": {
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"@csstools/css-parser-algorithms": "^3.0.5",
@@ -15933,6 +17874,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT",
"dependencies": {
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@@ -15950,6 +17892,7 @@
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+ "license": "MIT",
"dependencies": {
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"util-deprecate": "^1.0.2"
@@ -15972,6 +17915,7 @@
"url": "https://opencollective.com/csstools"
}
],
+ "license": "MIT-0",
"dependencies": {
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},
@@ -15986,6 +17930,7 @@
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+ "license": "MIT",
"dependencies": {
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@@ -15998,6 +17943,7 @@
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+ "license": "MIT",
"engines": {
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},
@@ -16009,6 +17955,7 @@
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+ "license": "MIT",
"engines": {
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},
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+ "license": "MIT",
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@@ -16066,8 +18016,9 @@
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}
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@@ -16092,6 +18043,7 @@
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@@ -16128,6 +18081,7 @@
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}
@@ -16172,6 +18128,7 @@
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}
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},
@@ -16193,6 +18150,7 @@
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}
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"funding": [
{
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@@ -16218,11 +18176,12 @@
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}
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@@ -16267,6 +18227,7 @@
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@@ -16477,6 +18451,7 @@
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@@ -16503,6 +18478,7 @@
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}
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+ "license": "MIT-0",
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},
@@ -16524,6 +18500,7 @@
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@@ -16717,6 +18706,7 @@
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+ "license": "MIT",
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@@ -16749,6 +18740,7 @@
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"postcss-image-set-function": "^7.0.0",
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"postcss-opacity-percentage": "^3.0.0",
@@ -16860,6 +18856,7 @@
"url": "https://opencollective.com/csstools"
}
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},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"peerDependencies": {
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}
@@ -16947,6 +18949,7 @@
"url": "https://opencollective.com/csstools"
}
],
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -17159,12 +19153,14 @@
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
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+ "license": "ISC"
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+ "license": "MIT",
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@@ -17209,15 +19209,26 @@
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+ "license": "MIT",
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+ }
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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{
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@@ -17272,7 +19286,8 @@
"type": "individual",
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}
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@@ -17291,12 +19306,14 @@
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}
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+ "license": "MIT",
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+ "license": "MIT",
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}
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+ "license": "MIT",
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@@ -17334,10 +19354,32 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ },
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+ "license": "MIT",
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+ "license": "MIT",
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}
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},
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -17584,23 +19643,11 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -17707,12 +19754,16 @@
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+ "license": "MIT",
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+ "version": "10.2.2",
+ "resolved": "https://registry.npmjs.org/regenerate-unicode-properties/-/regenerate-unicode-properties-10.2.2.tgz",
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+ "license": "MIT",
"dependencies": {
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},
@@ -17756,16 +19810,17 @@
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- "resolved": "https://registry.npmjs.org/regexpu-core/-/regexpu-core-6.2.0.tgz",
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+ "version": "6.4.0",
+ "resolved": "https://registry.npmjs.org/regexpu-core/-/regexpu-core-6.4.0.tgz",
+ "integrity": "sha512-0ghuzq67LI9bLXpOX/ISfve/Mq33a4aFRzoQYhnnok1JOFpmE/A2TBGkNVenOGEeSBCjIiWcc6MVOG5HEQv0sA==",
+ "license": "MIT",
"dependencies": {
"regenerate": "^1.4.2",
- "regenerate-unicode-properties": "^10.2.0",
+ "regenerate-unicode-properties": "^10.2.2",
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- "regjsparser": "^0.12.0",
+ "regjsparser": "^0.13.0",
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- "unicode-match-property-value-ecmascript": "^2.1.0"
+ "unicode-match-property-value-ecmascript": "^2.2.1"
},
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+ "license": "MIT",
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},
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT"
},
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- "resolved": "https://registry.npmjs.org/regjsparser/-/regjsparser-0.12.0.tgz",
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+ "version": "0.13.0",
+ "resolved": "https://registry.npmjs.org/regjsparser/-/regjsparser-0.13.0.tgz",
+ "integrity": "sha512-NZQZdC5wOE/H3UT28fVGL+ikOZcEzfMGk/c3iN9UGxzWHMa1op7274oyiUVrAG4B2EuFhus8SvkaYnhvW92p9Q==",
+ "license": "BSD-2-Clause",
"dependencies": {
- "jsesc": "~3.0.2"
+ "jsesc": "~3.1.0"
},
"bin": {
"regjsparser": "bin/parser"
}
},
- "node_modules/regjsparser/node_modules/jsesc": {
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- "bin": {
- "jsesc": "bin/jsesc"
- },
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- }
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"engines": {
"node": ">= 0.10"
}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"dependencies": {
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@@ -17922,9 +19977,10 @@
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+ "version": "3.1.1",
+ "resolved": "https://registry.npmjs.org/remark-mdx/-/remark-mdx-3.1.1.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "BSD-2-Clause",
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+ "license": "BSD-2-Clause",
"funding": {
"url": "https://github.com/fb55/entities?sponsor=1"
}
@@ -18065,6 +20130,7 @@
"url": "https://github.com/sponsors/fb55"
}
],
+ "license": "MIT",
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"domhandler": "^4.0.0",
@@ -18072,21 +20138,11 @@
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
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+ "resolved": "https://registry.npmjs.org/resolve/-/resolve-1.22.11.tgz",
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+ "license": "MIT",
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+ "is-core-module": "^2.16.1",
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+ "license": "MIT"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT"
+ },
+ "node_modules/responselike": {
+ "version": "3.0.0",
+ "resolved": "https://registry.npmjs.org/responselike/-/responselike-3.0.0.tgz",
+ "integrity": "sha512-40yHxbNcl2+rzXvZuVkrYohathsSJlMTXKryG5y8uciHv1+xDLHQpgjG64JUO9nrEq2jGLH6IZ8BcZyw3wrweg==",
+ "license": "MIT",
+ "dependencies": {
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+ },
+ "engines": {
+ "node": ">=14.16"
+ },
+ "funding": {
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+ }
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"resolved": "https://registry.npmjs.org/retry/-/retry-0.13.1.tgz",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"engines": {
"iojs": ">=1.0.0",
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@@ -18169,12 +20248,14 @@
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+ "integrity": "sha512-IXgzBWvWQwE6PrDI05OvmXUIruQTcoMDzRsOd5CDvHCVLcLHMTSYvOK5Cm46kWqlV3yAbuSpBZdJ5oP5OUoStg==",
+ "license": "Unlicense"
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT"
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"hasInstallScript": true,
+ "license": "Apache-2.0",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
},
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+ "resolved": "https://registry.npmjs.org/shell-quote/-/shell-quote-1.8.3.tgz",
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+ "license": "MIT",
+ "engines": {
+ "node": ">= 0.4"
+ },
+ "funding": {
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+ }
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "ISC"
},
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@@ -18751,7 +20838,8 @@
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"url": "https://feross.org/support"
}
- ]
+ ],
+ "license": "MIT"
},
"node_modules/simple-get": {
"version": "4.0.1",
@@ -18771,54 +20859,33 @@
"url": "https://feross.org/support"
}
],
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- "funding": {
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- "engines": {
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+ "license": "MIT",
"dependencies": {
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}
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+ "version": "0.3.4",
+ "resolved": "https://registry.npmjs.org/is-arrayish/-/is-arrayish-0.3.4.tgz",
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+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT"
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"bin": {
"uuid": "dist/bin/uuid"
}
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+ "license": "MIT",
"engines": {
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}
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+ "version": "0.7.6",
+ "resolved": "https://registry.npmjs.org/source-map/-/source-map-0.7.6.tgz",
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+ "license": "BSD-3-Clause",
"engines": {
- "node": ">= 8"
+ "node": ">= 12"
}
},
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+ "license": "BSD-3-Clause",
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+ "license": "MIT",
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+ "license": "BSD-3-Clause",
"engines": {
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
@@ -18967,6 +21037,7 @@
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+ "license": "MIT",
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+ "license": "MIT",
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+ "node_modules/sprintf-js": {
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+ "integrity": "sha512-D9cPgkvLlV3t3IzL0D0YLvGA9Ahk4PcvVwUbN0dSGr1aP0Nrt4AEnTUbuGvquEC0mA64Gqt1fzirlRs5ibXx8g==",
+ "license": "BSD-3-Clause"
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"engines": {
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}
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+ "version": "3.10.0",
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+ "integrity": "sha512-5GS12FdOZNliM5mAOxFRg7Ir0pWz8MdpYm6AY6VPkGpbA7ZzmbzNcBJQ0GPvvyWgcY7QAhCgf9Uy89I03faLkg==",
+ "license": "MIT"
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+ "license": "MIT",
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+ "version": "1.3.0",
+ "resolved": "https://registry.npmjs.org/string_decoder/-/string_decoder-1.3.0.tgz",
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+ "license": "MIT",
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+ "safe-buffer": "~5.2.0"
}
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- "node_modules/string_decoder/node_modules/safe-buffer": {
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+ "license": "MIT",
"dependencies": {
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+ "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.2.2.tgz",
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+ "license": "MIT",
"engines": {
"node": ">=12"
},
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+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.2.tgz",
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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"is-obj": "^1.0.1",
@@ -19120,10 +21188,23 @@
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}
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+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
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+ "license": "MIT",
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+ },
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+ }
+ },
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
"node": ">=6"
}
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+ "license": "MIT",
"engines": {
"node": ">=8"
},
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+ "resolved": "https://registry.npmjs.org/style-to-js/-/style-to-js-1.1.19.tgz",
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+ "license": "MIT",
"dependencies": {
- "style-to-object": "1.0.9"
+ "style-to-object": "1.0.12"
}
},
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- "resolved": "https://registry.npmjs.org/style-to-object/-/style-to-object-1.0.9.tgz",
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+ "version": "1.0.12",
+ "resolved": "https://registry.npmjs.org/style-to-object/-/style-to-object-1.0.12.tgz",
+ "integrity": "sha512-ddJqYnoT4t97QvN2C95bCgt+m7AAgXjVnkk/jxAfmp7EAB8nnqqZYEbMd3em7/vEomDb2LAQKAy1RFfv41mdNw==",
+ "license": "MIT",
"dependencies": {
- "inline-style-parser": "0.2.4"
+ "inline-style-parser": "0.2.6"
}
},
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"resolved": "https://registry.npmjs.org/stylehacks/-/stylehacks-6.1.1.tgz",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT"
},
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+ "license": "MIT",
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},
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+ "license": "MIT",
"engines": {
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+ "integrity": "sha512-e4hG1hRwoOdRb37cIMSgzNsxyzKfayW6VOflrwvR+/bzrkyxY/31WkbgnQpgtrNp1SdpJvpUAGTa/ZoiPNDuRQ==",
+ "license": "MIT"
},
"node_modules/svgo": {
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"resolved": "https://registry.npmjs.org/svgo/-/svgo-3.3.2.tgz",
"integrity": "sha512-OoohrmuUlBs8B8o6MB2Aevn+pRIH9zDALSR+6hhqVfa6fRwG/Qw9VUMSMW9VNg2CFc/MTIfabtdOVl9ODIJjpw==",
+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"engines": {
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}
@@ -19246,17 +21338,23 @@
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/dcastil"
}
},
"node_modules/tapable": {
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- "resolved": "https://registry.npmjs.org/tapable/-/tapable-2.2.2.tgz",
- "integrity": "sha512-Re10+NauLTMCudc7T5WLFLAwDhQ0JWdrMK+9B2M8zR5hRExKmsRDCBA7/aV/pNJFltmBFO5BAMlQFi/vq3nKOg==",
+ "version": "2.3.0",
+ "resolved": "https://registry.npmjs.org/tapable/-/tapable-2.3.0.tgz",
+ "integrity": "sha512-g9ljZiwki/LfxmQADO3dEY1CbpmXT5Hm2fJ+QaGKwSXUylMybePR7/67YW7jOrrvjEgL1Fmz5kzyAjWVWLlucg==",
+ "license": "MIT",
"engines": {
"node": ">=6"
+ },
+ "funding": {
+ "type": "opencollective",
+ "url": "https://opencollective.com/webpack"
}
},
"node_modules/tar-fs": {
@@ -19273,10 +21371,11 @@
"bare-path": "^3.0.0"
}
},
- "node_modules/tar-fs/node_modules/tar-stream": {
+ "node_modules/tar-stream": {
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"resolved": "https://registry.npmjs.org/tar-stream/-/tar-stream-3.1.7.tgz",
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+ "license": "MIT",
"dependencies": {
"b4a": "^1.6.4",
"fast-fifo": "^1.2.0",
@@ -19284,12 +21383,13 @@
}
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- "resolved": "https://registry.npmjs.org/terser/-/terser-5.42.0.tgz",
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+ "version": "5.44.1",
+ "resolved": "https://registry.npmjs.org/terser/-/terser-5.44.1.tgz",
+ "integrity": "sha512-t/R3R/n0MSwnnazuPpPNVO60LX0SKL45pyl9YlvxIdkH0Of7D5qM2EVe+yASRIlY5pZ73nclYJfNANGWPwFDZw==",
+ "license": "BSD-2-Clause",
"dependencies": {
"@jridgewell/source-map": "^0.3.3",
- "acorn": "^8.14.0",
+ "acorn": "^8.15.0",
"commander": "^2.20.0",
"source-map-support": "~0.5.20"
},
@@ -19304,6 +21404,7 @@
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+ "license": "MIT",
"dependencies": {
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@@ -19337,6 +21438,7 @@
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+ "license": "MIT",
"dependencies": {
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"merge-stream": "^2.0.0",
@@ -19350,6 +21452,7 @@
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+ "license": "MIT",
"dependencies": {
"has-flag": "^4.0.0"
},
@@ -19363,23 +21466,30 @@
"node_modules/terser/node_modules/commander": {
"version": "2.20.3",
"resolved": "https://registry.npmjs.org/commander/-/commander-2.20.3.tgz",
- "integrity": "sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ=="
+ "integrity": "sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==",
+ "license": "MIT"
},
"node_modules/text-decoder": {
"version": "1.2.3",
"resolved": "https://registry.npmjs.org/text-decoder/-/text-decoder-1.2.3.tgz",
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+ "license": "Apache-2.0",
"dependencies": {
"b4a": "^1.6.4"
}
},
"node_modules/thingies": {
- "version": "1.21.0",
- "resolved": "https://registry.npmjs.org/thingies/-/thingies-1.21.0.tgz",
- "integrity": "sha512-hsqsJsFMsV+aD4s3CWKk85ep/3I9XzYV/IXaSouJMYIoDlgyi11cBhsqYe9/geRfB0YIikBQg6raRaM+nIMP9g==",
+ "version": "2.5.0",
+ "resolved": "https://registry.npmjs.org/thingies/-/thingies-2.5.0.tgz",
+ "integrity": "sha512-s+2Bwztg6PhWUD7XMfeYm5qliDdSiZm7M7n8KjTkIsm3l/2lgVRc2/Gx/v+ZX8lT4FMA+i8aQvhcWylldc+ZNw==",
+ "license": "MIT",
"engines": {
"node": ">=10.18"
},
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/streamich"
+ },
"peerDependencies": {
"tslib": "^2"
}
@@ -19387,27 +21497,35 @@
"node_modules/thunky": {
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"resolved": "https://registry.npmjs.org/thunky/-/thunky-1.1.0.tgz",
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+ "integrity": "sha512-eHY7nBftgThBqOyHGVN+l8gF0BucP09fMo0oO/Lb0w1OF80dJv+lDVpXG60WMQvkcxAkNybKsrEIE3ZtKGmPrA==",
+ "license": "MIT"
},
"node_modules/tiny-invariant": {
"version": "1.3.3",
"resolved": "https://registry.npmjs.org/tiny-invariant/-/tiny-invariant-1.3.3.tgz",
- "integrity": "sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg=="
+ "integrity": "sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg==",
+ "license": "MIT"
},
"node_modules/tiny-warning": {
"version": "1.0.3",
"resolved": "https://registry.npmjs.org/tiny-warning/-/tiny-warning-1.0.3.tgz",
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+ "integrity": "sha512-lBN9zLN/oAf68o3zNXYrdCt1kP8WsiGW8Oo2ka41b2IM5JL/S1CTyX1rW0mb/zSuJun0ZUrDxx4sqvYS2FWzPA==",
+ "license": "MIT"
},
"node_modules/tinyexec": {
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- "resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-1.0.1.tgz",
- "integrity": "sha512-5uC6DDlmeqiOwCPmK9jMSdOuZTh8bU39Ys6yidB+UTt5hfZUPGAypSgFRiEp+jbi9qH40BLDvy85jIU88wKSqw=="
+ "version": "1.0.2",
+ "resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-1.0.2.tgz",
+ "integrity": "sha512-W/KYk+NFhkmsYpuHq5JykngiOCnxeVL8v8dFnqxSD8qEEdRfXk1SDM6JzNqcERbcGYj9tMrDQBYV9cjgnunFIg==",
+ "license": "MIT",
+ "engines": {
+ "node": ">=18"
+ }
},
"node_modules/tinypool": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/tinypool/-/tinypool-1.1.1.tgz",
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+ "license": "MIT",
"engines": {
"node": "^18.0.0 || >=20.0.0"
}
@@ -19416,6 +21534,7 @@
"version": "5.0.1",
"resolved": "https://registry.npmjs.org/to-regex-range/-/to-regex-range-5.0.1.tgz",
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+ "license": "MIT",
"dependencies": {
"is-number": "^7.0.0"
},
@@ -19423,18 +21542,11 @@
"node": ">=8.0"
}
},
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "Apache-2.0",
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+ "license": "MIT",
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+ "license": "MIT",
"funding": {
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+ "license": "Apache-2.0",
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+ "license": "(MIT OR CC0-1.0)",
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+ "license": "MIT",
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+ "license": "MIT"
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+ "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.16.0.tgz",
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+ "license": "MIT"
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+ "license": "MIT",
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}
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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- "resolved": "https://registry.npmjs.org/unicode-property-aliases-ecmascript/-/unicode-property-aliases-ecmascript-2.1.0.tgz",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -19612,21 +21743,11 @@
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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@@ -19700,9 +21826,10 @@
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+ "version": "6.0.2",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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}
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"funding": [
{
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@@ -19746,6 +21875,7 @@
"url": "https://github.com/sponsors/ai"
}
],
+ "license": "MIT",
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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+ "license": "MIT",
"engines": {
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+ "license": "MIT",
"engines": {
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},
@@ -19827,18 +21961,11 @@
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+ "license": "BSD-2-Clause",
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+ "license": "MIT",
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},
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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}
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+ "license": "MIT"
},
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+ "license": "MIT"
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
"engines": {
"node": ">= 0.4.0"
}
@@ -20024,6 +22190,7 @@
"https://github.com/sponsors/broofa",
"https://github.com/sponsors/ctavan"
],
+ "license": "MIT",
"bin": {
"uuid": "dist/bin/uuid"
}
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"node_modules/value-equal": {
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+ "license": "MIT"
},
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+ "license": "MIT",
"engines": {
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}
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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@@ -20068,9 +22239,10 @@
}
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+ "version": "4.0.3",
+ "resolved": "https://registry.npmjs.org/vfile-message/-/vfile-message-4.0.3.tgz",
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+ "license": "MIT",
"dependencies": {
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+ "license": "MIT",
"engines": {
"node": ">=14.0.0"
}
@@ -20092,6 +22265,7 @@
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+ "license": "MIT",
"dependencies": {
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},
@@ -20103,6 +22277,7 @@
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+ "license": "MIT",
"dependencies": {
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"vscode-languageserver-types": "3.17.5"
@@ -20111,22 +22286,26 @@
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"resolved": "https://registry.npmjs.org/vscode-languageserver-textdocument/-/vscode-languageserver-textdocument-1.0.12.tgz",
- "integrity": "sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA=="
+ "integrity": "sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA==",
+ "license": "MIT"
},
"node_modules/vscode-languageserver-types": {
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"resolved": "https://registry.npmjs.org/vscode-languageserver-types/-/vscode-languageserver-types-3.17.5.tgz",
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+ "integrity": "sha512-Ld1VelNuX9pdF39h2Hgaeb5hEZM2Z3jUrrMgWQAu82jMtZp7p3vJT3BzToKtZI7NgQssZje5o0zryOrhQvzQAg==",
+ "license": "MIT"
},
"node_modules/vscode-uri": {
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"resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-3.0.8.tgz",
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+ "integrity": "sha512-AyFQ0EVmsOZOlAnxoFOGOq1SQDWAB7C6aqMGS23svWAllfOaxbuFvcT8D1i8z3Gyn8fraVeZNNmN6e9bxxXkKw==",
+ "license": "MIT"
},
"node_modules/watchpack": {
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"integrity": "sha512-c5EGNOiyxxV5qmTtAB7rbiXxi1ooX1pQKMLX/MIabJjRA0SJBQOjKF+KSVfHkr9U1cADPon0mRiVe/riyaiDUA==",
+ "license": "MIT",
"dependencies": {
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@@ -20139,6 +22318,7 @@
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+ "license": "MIT",
"dependencies": {
"minimalistic-assert": "^1.0.0"
}
@@ -20147,6 +22327,7 @@
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+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
@@ -20156,6 +22337,7 @@
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+ "license": "MIT",
"engines": {
"node": ">= 14"
}
@@ -20163,23 +22345,26 @@
"node_modules/webidl-conversions": {
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"resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",
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+ "integrity": "sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==",
+ "license": "BSD-2-Clause"
},
"node_modules/webpack": {
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- "resolved": "https://registry.npmjs.org/webpack/-/webpack-5.99.9.tgz",
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+ "version": "5.102.1",
+ "resolved": "https://registry.npmjs.org/webpack/-/webpack-5.102.1.tgz",
+ "integrity": "sha512-7h/weGm9d/ywQ6qzJ+Xy+r9n/3qgp/thalBbpOi5i223dPXKi04IBtqPN9nTd+jBc7QKfvDbaBnFipYp4sJAUQ==",
+ "license": "MIT",
"dependencies": {
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- "@types/estree": "^1.0.6",
+ "@types/estree": "^1.0.8",
"@types/json-schema": "^7.0.15",
"@webassemblyjs/ast": "^1.14.1",
"@webassemblyjs/wasm-edit": "^1.14.1",
"@webassemblyjs/wasm-parser": "^1.14.1",
- "acorn": "^8.14.0",
- "browserslist": "^4.24.0",
+ "acorn": "^8.15.0",
+ "acorn-import-phases": "^1.0.3",
+ "browserslist": "^4.26.3",
"chrome-trace-event": "^1.0.2",
- "enhanced-resolve": "^5.17.1",
+ "enhanced-resolve": "^5.17.3",
"es-module-lexer": "^1.2.1",
"eslint-scope": "5.1.1",
"events": "^3.2.0",
@@ -20189,11 +22374,11 @@
"loader-runner": "^4.2.0",
"mime-types": "^2.1.27",
"neo-async": "^2.6.2",
- "schema-utils": "^4.3.2",
- "tapable": "^2.1.1",
+ "schema-utils": "^4.3.3",
+ "tapable": "^2.3.0",
"terser-webpack-plugin": "^5.3.11",
- "watchpack": "^2.4.1",
- "webpack-sources": "^3.2.3"
+ "watchpack": "^2.4.4",
+ "webpack-sources": "^3.3.3"
},
"bin": {
"webpack": "bin/webpack.js"
@@ -20215,6 +22400,7 @@
"version": "4.10.2",
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+ "license": "MIT",
"dependencies": {
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"acorn": "^8.0.4",
@@ -20240,32 +22426,20 @@
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+ "license": "MIT",
"engines": {
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}
},
- "node_modules/webpack-bundle-analyzer/node_modules/gzip-size": {
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- "integrity": "sha512-ax7ZYomf6jqPTQ4+XCpUGyXKHk5WweS+e05MBO4/y3WJ5RkmPXNKvX+bx1behVILVwr6JSQvZAku021CHPXG3Q==",
- "dependencies": {
- "duplexer": "^0.1.2"
- },
- "engines": {
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- },
- "funding": {
- "url": "https://github.com/sponsors/sindresorhus"
- }
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"node_modules/webpack-dev-middleware": {
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+ "license": "MIT",
"engines": {
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},
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}
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+ "license": "MIT",
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"is-inside-container": "^1.0.0",
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+ "license": "MIT",
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+ "license": "MIT",
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+ "license": "MIT",
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- },
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- "funding": {
- "url": "https://github.com/sponsors/sindresorhus"
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+ "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==",
+ "license": "MIT"
},
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+ "license": "MIT",
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+ "license": "MIT",
"dependencies": {
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@@ -20517,21 +22676,11 @@
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+ "license": "MIT",
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+ "license": "Apache-2.0",
"dependencies": {
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+ "license": "Apache-2.0",
"engines": {
"node": ">=0.8.0"
}
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+ "license": "MIT",
"dependencies": {
"tr46": "~0.0.3",
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+ "license": "ISC",
"dependencies": {
"isexe": "^2.0.0"
},
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+ "license": "MIT",
"dependencies": {
"string-width": "^5.0.1"
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"node_modules/wildcard": {
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+ "integrity": "sha512-CC1bOL87PIWSBhDcTrdeLo6eGT7mCFtrg0uIJtqJUFyK+eJnzl8A1niH56uu7KMa5XFrtiV+AQuHO3n7DsHnLQ==",
+ "license": "MIT"
},
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+ "license": "MIT",
"dependencies": {
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@@ -20624,9 +22780,10 @@
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+ "version": "6.2.2",
+ "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.2.2.tgz",
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+ "license": "MIT",
"engines": {
"node": ">=12"
},
@@ -20635,9 +22792,10 @@
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+ "version": "6.2.3",
+ "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.3.tgz",
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+ "license": "MIT",
"engines": {
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},
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+ "version": "7.1.2",
+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.2.tgz",
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+ "license": "MIT",
"dependencies": {
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},
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+ "license": "ISC"
},
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+ "license": "ISC",
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+ "license": "MIT",
"engines": {
"node": ">=8.3.0"
},
@@ -20695,10 +22857,41 @@
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+ "resolved": "https://registry.npmjs.org/wsl-utils/-/wsl-utils-0.1.0.tgz",
+ "integrity": "sha512-h3Fbisa2nKGPxCpm89Hk33lBLsnaGBvctQopaBSOW/uIs6FTe1ATyAnKFJrzVs9vpGdsTe73WF3V4lIsk4Gacw==",
+ "license": "MIT",
+ "dependencies": {
+ "is-wsl": "^3.1.0"
+ },
+ "engines": {
+ "node": ">=18"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
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+ "version": "3.1.0",
+ "resolved": "https://registry.npmjs.org/is-wsl/-/is-wsl-3.1.0.tgz",
+ "integrity": "sha512-UcVfVfaK4Sc4m7X3dUSoHoozQGBEFeDC+zVo06t98xe8CzHSZZBekNXH+tu0NalHolcJ/QAGqS46Hef7QXBIMw==",
+ "license": "MIT",
+ "dependencies": {
+ "is-inside-container": "^1.0.0"
+ },
+ "engines": {
+ "node": ">=16"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
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+ "license": "MIT",
"engines": {
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},
@@ -20710,6 +22903,7 @@
"version": "1.6.11",
"resolved": "https://registry.npmjs.org/xml-js/-/xml-js-1.6.11.tgz",
"integrity": "sha512-7rVi2KMfwfWFl+GpPg6m80IVMWXLRjO+PxTq7V2CDhoGak0wzYzFgUY2m4XJ47OGdXd8eLE8EmwfAmdjw7lC1g==",
+ "license": "MIT",
"dependencies": {
"sax": "^1.2.4"
},
@@ -20720,12 +22914,14 @@
"node_modules/yallist": {
"version": "3.1.1",
"resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
- "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g=="
+ "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
+ "license": "ISC"
},
"node_modules/yocto-queue": {
- "version": "1.2.1",
- "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-1.2.1.tgz",
- "integrity": "sha512-AyeEbWOu/TAXdxlV9wmGcR0+yh2j3vYPGOECcIj2S7MkrLyC7ne+oye2BKTItt0ii2PHk4cDy+95+LshzbXnGg==",
+ "version": "1.2.2",
+ "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-1.2.2.tgz",
+ "integrity": "sha512-4LCcse/U2MHZ63HAJVE+v71o7yOdIe4cZ70Wpf8D/IyjDKYQLV5GD46B+hSTjJsvV5PztjvHoU580EftxjDZFQ==",
+ "license": "MIT",
"engines": {
"node": ">=12.20"
},
@@ -20737,6 +22933,7 @@
"version": "2.0.4",
"resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz",
"integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==",
+ "license": "MIT",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/wooorm"
diff --git a/docs/my-website/package.json b/docs/my-website/package.json
index d73633817b4..784a5e4b578 100644
--- a/docs/my-website/package.json
+++ b/docs/my-website/package.json
@@ -18,7 +18,7 @@
"@docusaurus/plugin-google-gtag": "3.8.1",
"@docusaurus/plugin-ideal-image": "3.8.1",
"@docusaurus/preset-classic": "3.8.1",
- "@docusaurus/theme-mermaid": "^3.8.1",
+ "@docusaurus/theme-mermaid": "3.8.1",
"@inkeep/cxkit-docusaurus": "^0.5.89",
"@mdx-js/react": "^3.0.0",
"clsx": "^1.2.1",
@@ -45,12 +45,19 @@
]
},
"engines": {
- "node": ">=16.14"
+ "node": ">=16.14",
+ "npm": ">=8.3.0"
+ },
+ "resolutions": {
+ "webpack-dev-server": ">=5.2.1",
+ "form-data": ">=4.0.4",
+ "mermaid": ">=11.10.0",
+ "gray-matter": "4.0.3"
},
"overrides": {
"webpack-dev-server": ">=5.2.1",
"form-data": ">=4.0.4",
"mermaid": ">=11.10.0",
- "js-yaml": ">=4.1.1"
+ "gray-matter": "4.0.3"
}
}
diff --git a/docs/my-website/release_notes/authors.yml b/docs/my-website/release_notes/authors.yml
new file mode 100644
index 00000000000..aaa3d51ec97
--- /dev/null
+++ b/docs/my-website/release_notes/authors.yml
@@ -0,0 +1,18 @@
+krrish:
+ name: Krrish Dholakia
+ title: CEO, LiteLLM
+ url: https://www.linkedin.com/in/krish-d/
+ image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
+
+ishaan:
+ name: Ishaan Jaffer
+ title: CTO, LiteLLM
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
+
+# Alias for typo in name
+ishaan-alt:
+ name: Ishaan Jaff
+ title: CTO, LiteLLM
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
diff --git a/docs/my-website/release_notes/v1.79.3-stable/index.md b/docs/my-website/release_notes/v1.79.3-stable/index.md
index f081fa614eb..c4f3ba1e017 100644
--- a/docs/my-website/release_notes/v1.79.3-stable/index.md
+++ b/docs/my-website/release_notes/v1.79.3-stable/index.md
@@ -1,5 +1,5 @@
---
-title: "[Preview] v1.79.3-stable - Built-in Guardrails on AI Gateway"
+title: "v1.79.3-stable - Built-in Guardrails on AI Gateway"
slug: "v1-79-3"
date: 2025-11-08T10:00:00
authors:
@@ -27,7 +27,7 @@ import TabItem from '@theme/TabItem';
docker run \
-e STORE_MODEL_IN_DB=True \
-p 4000:4000 \
-ghcr.io/berriai/litellm:v1.79.3.rc.1
+ghcr.io/berriai/litellm:v1.79.3-stable
```
diff --git a/docs/my-website/release_notes/v1.80.0-stable/index.md b/docs/my-website/release_notes/v1.80.0-stable/index.md
new file mode 100644
index 00000000000..9c643a48adb
--- /dev/null
+++ b/docs/my-website/release_notes/v1.80.0-stable/index.md
@@ -0,0 +1,523 @@
+---
+title: "[Preview] v1.80.0-stable - Agent Hub Support"
+slug: "v1-80-0"
+date: 2025-11-15T10:00:00
+authors:
+ - name: Krrish Dholakia
+ title: CEO, LiteLLM
+ url: https://www.linkedin.com/in/krish-d/
+ image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
+ - name: Ishaan Jaff
+ title: CTO, LiteLLM
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
+hide_table_of_contents: false
+---
+
+import Image from '@theme/IdealImage';
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+## Deploy this version
+
+
+
+
+``` showLineNumbers title="docker run litellm"
+docker run \
+-e STORE_MODEL_IN_DB=True \
+-p 4000:4000 \
+ghcr.io/berriai/litellm:v1.80.0.rc.2
+```
+
+
+
+
+
+``` showLineNumbers title="pip install litellm"
+pip install litellm==1.80.0
+```
+
+
+
+
+---
+
+## Key Highlights
+
+- **🆕 Agent Hub Support** - Register and make agents public for your organization
+- **RunwayML Provider** - Complete video generation, image generation, and text-to-speech support
+- **GPT-5.1 Family Support** - Day-0 support for OpenAI's latest GPT-5.1 and GPT-5.1-Codex models
+- **Prometheus OSS** - Prometheus metrics now available in open-source version
+- **Vector Store Files API** - Complete OpenAI-compatible Vector Store Files API with full CRUD operations
+- **Embeddings Performance** - O(1) lookup optimization for router embeddings with shared sessions
+
+---
+
+### Agent Hub
+
+
+
+This release adds support for registering and making agents public for your organization. This is great for **Proxy Admins** who want a central place to make agents built in their organization, discoverable to their users.
+
+Here's the flow:
+1. Add agent to litellm.
+2. Make it public.
+3. Allow anyone to discover it on the public AI Hub page.
+
+[**Get Started with Agent Hub**](../../docs/proxy/ai_hub)
+
+
+### Performance – `/embeddings` 13× Lower p95 Latency
+
+This update significantly improves `/embeddings` latency by routing it through the same optimized pipeline as `/chat/completions`, benefiting from all previously applied networking optimizations.
+
+### Results
+
+| Metric | Before | After | Improvement |
+| --- | --- | --- | --- |
+| p95 latency | 5,700 ms | **430 ms** | −92% (~13× faster)** |
+| p99 latency | 7,200 ms | **780 ms** | −89% |
+| Average latency | 844 ms | **262 ms** | −69% |
+| Median latency | 290 ms | **230 ms** | −21% |
+| RPS | 1,216.7 | **1,219.7** | **+0.25%** |
+
+### Test Setup
+
+| Category | Specification |
+| --- | --- |
+| **Load Testing** | Locust: 1,000 concurrent users, 500 ramp-up |
+| **System** | 4 vCPUs, 8 GB RAM, 4 workers, 4 instances |
+| **Database** | PostgreSQL (Redis unused) |
+| **Configuration** | [config.yaml](https://gist.github.com/AlexsanderHamir/550791675fd752befcac6a9e44024652) |
+| **Load Script** | [no_cache_hits.py](https://gist.github.com/AlexsanderHamir/99d673bf74cdd81fd39f59fa9048f2e8) |
+
+---
+
+### 🆕 RunwayML
+
+Complete integration for RunwayML's Gen-4 family of models, supporting video generation, image generation, and text-to-speech.
+
+**Supported Endpoints:**
+- `/v1/videos` - Video generation (Gen-4 Turbo, Gen-4 Aleph, Gen-3A Turbo)
+- `/v1/images/generations` - Image generation (Gen-4 Image, Gen-4 Image Turbo)
+- `/v1/audio/speech` - Text-to-speech (ElevenLabs Multilingual v2)
+
+**Quick Start:**
+
+```bash showLineNumbers title="Generate Video with RunwayML"
+curl --location 'http://localhost:4000/v1/videos' \
+--header 'Content-Type: application/json' \
+--header 'Authorization: Bearer sk-1234' \
+--data '{
+ "model": "runwayml/gen4_turbo",
+ "prompt": "A high quality demo video of litellm ai gateway",
+ "input_reference": "https://example.com/image.jpg",
+ "seconds": 5,
+ "size": "1280x720"
+}'
+```
+
+[Get Started with RunwayML](../../docs/providers/runwayml/videos)
+
+---
+
+### Prometheus Metrics - Open Source
+
+Prometheus metrics are now available in the open-source version of LiteLLM, providing comprehensive observability for your AI Gateway without requiring an enterprise license.
+
+**Quick Start:**
+
+```yaml
+litellm_settings:
+ success_callback: ["prometheus"]
+ failure_callback: ["prometheus"]
+```
+
+[Get Started with Prometheus](../../docs/proxy/logging#prometheus)
+
+---
+
+### Vector Store Files API
+
+Complete OpenAI-compatible Vector Store Files API now stable, enabling full file lifecycle management within vector stores.
+
+**Supported Endpoints:**
+- `POST /v1/vector_stores/{vector_store_id}/files` - Create vector store file
+- `GET /v1/vector_stores/{vector_store_id}/files` - List vector store files
+- `GET /v1/vector_stores/{vector_store_id}/files/{file_id}` - Retrieve vector store file
+- `GET /v1/vector_stores/{vector_store_id}/files/{file_id}/content` - Retrieve file content
+- `DELETE /v1/vector_stores/{vector_store_id}/files/{file_id}` - Delete vector store file
+- `DELETE /v1/vector_stores/{vector_store_id}` - Delete vector store
+
+**Quick Start:**
+
+```bash showLineNumbers title="Create Vector Store File"
+curl --location 'http://localhost:4000/v1/vector_stores/vs_123/files' \
+--header 'Content-Type: application/json' \
+--header 'Authorization: Bearer sk-1234' \
+--data '{
+ "file_id": "file_abc"
+}'
+```
+
+[Get Started with Vector Stores](../../docs/vector_store_files)
+
+---
+
+## New Providers and Endpoints
+
+### New Providers
+
+| Provider | Supported Endpoints | Description |
+| -------- | ------------------- | ----------- |
+| **[RunwayML](../../docs/providers/runwayml/videos)** | `/v1/videos`, `/v1/images/generations`, `/v1/audio/speech` | Gen-4 video generation, image generation, and text-to-speech |
+
+### New LLM API Endpoints
+
+| Endpoint | Method | Description | Documentation |
+| -------- | ------ | ----------- | ------------- |
+| `/v1/vector_stores/{vector_store_id}/files` | POST | Create vector store file | [Docs](../../docs/vector_store_files) |
+| `/v1/vector_stores/{vector_store_id}/files` | GET | List vector store files | [Docs](../../docs/vector_store_files) |
+| `/v1/vector_stores/{vector_store_id}/files/{file_id}` | GET | Retrieve vector store file | [Docs](../../docs/vector_store_files) |
+| `/v1/vector_stores/{vector_store_id}/files/{file_id}/content` | GET | Retrieve file content | [Docs](../../docs/vector_store_files) |
+| `/v1/vector_stores/{vector_store_id}/files/{file_id}` | DELETE | Delete vector store file | [Docs](../../docs/vector_store_files) |
+| `/v1/vector_stores/{vector_store_id}` | DELETE | Delete vector store | [Docs](../../docs/vector_store_files) |
+
+---
+
+## New Models / Updated Models
+
+#### New Model Support
+
+| Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) | Features |
+| -------- | ----- | -------------- | ------------------- | -------------------- | -------- |
+| OpenAI | `gpt-5.1` | 272K | $1.25 | $10.00 | Reasoning, vision, PDF input, responses API |
+| OpenAI | `gpt-5.1-2025-11-13` | 272K | $1.25 | $10.00 | Reasoning, vision, PDF input, responses API |
+| OpenAI | `gpt-5.1-chat-latest` | 128K | $1.25 | $10.00 | Reasoning, vision, PDF input |
+| OpenAI | `gpt-5.1-codex` | 272K | $1.25 | $10.00 | Responses API, reasoning, vision |
+| OpenAI | `gpt-5.1-codex-mini` | 272K | $0.25 | $2.00 | Responses API, reasoning, vision |
+| Moonshot | `moonshot/kimi-k2-thinking` | 262K | $0.60 | $2.50 | Function calling, web search, reasoning |
+| Mistral | `mistral/magistral-medium-2509` | 40K | $2.00 | $5.00 | Reasoning, function calling |
+| Vertex AI | `vertex_ai/moonshotai/kimi-k2-thinking-maas` | 256K | $0.60 | $2.50 | Function calling, web search |
+| OpenRouter | `openrouter/deepseek/deepseek-v3.2-exp` | 164K | $0.20 | $0.40 | Function calling, prompt caching |
+| OpenRouter | `openrouter/minimax/minimax-m2` | 205K | $0.26 | $1.02 | Function calling, reasoning |
+| OpenRouter | `openrouter/z-ai/glm-4.6` | 203K | $0.40 | $1.75 | Function calling, reasoning |
+| OpenRouter | `openrouter/z-ai/glm-4.6:exacto` | 203K | $0.45 | $1.90 | Function calling, reasoning |
+| Voyage | `voyage/voyage-3.5` | 32K | $0.06 | - | Embeddings |
+| Voyage | `voyage/voyage-3.5-lite` | 32K | $0.02 | - | Embeddings |
+
+#### Video Generation Models
+
+| Provider | Model | Cost Per Second | Resolutions | Features |
+| -------- | ----- | --------------- | ----------- | -------- |
+| RunwayML | `runwayml/gen4_turbo` | $0.05 | 1280x720, 720x1280 | Text + image to video |
+| RunwayML | `runwayml/gen4_aleph` | $0.15 | 1280x720, 720x1280 | Text + image to video |
+| RunwayML | `runwayml/gen3a_turbo` | $0.05 | 1280x720, 720x1280 | Text + image to video |
+
+#### Image Generation Models
+
+| Provider | Model | Cost Per Image | Resolutions | Features |
+| -------- | ----- | -------------- | ----------- | -------- |
+| RunwayML | `runwayml/gen4_image` | $0.05 | 1280x720, 1920x1080 | Text + image to image |
+| RunwayML | `runwayml/gen4_image_turbo` | $0.02 | 1280x720, 1920x1080 | Text + image to image |
+| Fal.ai | `fal_ai/fal-ai/flux-pro/v1.1` | $0.04/image | - | Image generation |
+| Fal.ai | `fal_ai/fal-ai/flux/schnell` | $0.003/image | - | Fast image generation |
+| Fal.ai | `fal_ai/fal-ai/bytedance/seedream/v3/text-to-image` | $0.03/image | - | Image generation |
+| Fal.ai | `fal_ai/fal-ai/bytedance/dreamina/v3.1/text-to-image` | $0.03/image | - | Image generation |
+| Fal.ai | `fal_ai/fal-ai/ideogram/v3` | $0.06/image | - | Image generation |
+| Fal.ai | `fal_ai/fal-ai/imagen4/preview/fast` | $0.02/image | - | Fast image generation |
+| Fal.ai | `fal_ai/fal-ai/imagen4/preview/ultra` | $0.06/image | - | High-quality image generation |
+
+#### Audio Models
+
+| Provider | Model | Cost | Features |
+| -------- | ----- | ---- | -------- |
+| RunwayML | `runwayml/eleven_multilingual_v2` | $0.0003/char | Text-to-speech |
+
+#### Features
+
+- **[OpenAI](../../docs/providers/openai)**
+ - Add GPT-5.1 family support with reasoning capabilities - [PR #16598](https://github.com/BerriAI/litellm/pull/16598)
+ - Add support for `reasoning_effort='none'` for GPT-5.1 - [PR #16658](https://github.com/BerriAI/litellm/pull/16658)
+ - Add `verbosity` parameter support for GPT-5 family models - [PR #16660](https://github.com/BerriAI/litellm/pull/16660)
+ - Fix forward OpenAI organization for image generation - [PR #16607](https://github.com/BerriAI/litellm/pull/16607)
+
+- **[Gemini (Google AI Studio + Vertex AI)](../../docs/providers/gemini)**
+ - Add support for `reasoning_effort='none'` for Gemini models - [PR #16548](https://github.com/BerriAI/litellm/pull/16548)
+ - Add all Gemini image models support in image generation - [PR #16526](https://github.com/BerriAI/litellm/pull/16526)
+ - Add Gemini image edit support - [PR #16430](https://github.com/BerriAI/litellm/pull/16430)
+ - Fix preserve non-ASCII characters in function call arguments - [PR #16550](https://github.com/BerriAI/litellm/pull/16550)
+ - Fix Gemini conversation format issue with MCP auto-execution - [PR #16592](https://github.com/BerriAI/litellm/pull/16592)
+
+- **[Bedrock](../../docs/providers/bedrock)**
+ - Add support for filtering knowledge base queries - [PR #16543](https://github.com/BerriAI/litellm/pull/16543)
+ - Ensure correct `aws_region` is used when provided dynamically for embeddings - [PR #16547](https://github.com/BerriAI/litellm/pull/16547)
+ - Add support for custom KMS encryption keys in Bedrock Batch operations - [PR #16662](https://github.com/BerriAI/litellm/pull/16662)
+ - Add bearer token authentication support for AgentCore - [PR #16556](https://github.com/BerriAI/litellm/pull/16556)
+ - Fix AgentCore SSE stream iterator to async for proper streaming support - [PR #16293](https://github.com/BerriAI/litellm/pull/16293)
+
+- **[Anthropic](../../docs/providers/anthropic)**
+ - Add context management param support - [PR #16528](https://github.com/BerriAI/litellm/pull/16528)
+ - Fix preserve `$defs` for Anthropic tools input schema - [PR #16648](https://github.com/BerriAI/litellm/pull/16648)
+ - Fix support Anthropic tool_use and tool_result in token counter - [PR #16351](https://github.com/BerriAI/litellm/pull/16351)
+
+- **[Vertex AI](../../docs/providers/vertex_ai)**
+ - Add Vertex Kimi-K2-Thinking support - [PR #16671](https://github.com/BerriAI/litellm/pull/16671)
+ - Add `vertex_credentials` support to `litellm.rerank()` - [PR #16479](https://github.com/BerriAI/litellm/pull/16479)
+
+- **[Mistral](../../docs/providers/mistral)**
+ - Fix Magistral streaming to emit reasoning chunks - [PR #16434](https://github.com/BerriAI/litellm/pull/16434)
+
+- **[Moonshot (Kimi)](../../docs/providers/moonshot)**
+ - Add Kimi K2 thinking model support - [PR #16445](https://github.com/BerriAI/litellm/pull/16445)
+
+- **[SambaNova](../../docs/providers/sambanova)**
+ - Fix SambaNova API rejecting requests when message content is passed as a list format - [PR #16612](https://github.com/BerriAI/litellm/pull/16612)
+
+- **[VLLM](../../docs/providers/vllm)**
+ - Fix use vllm passthrough config for hosted vllm provider instead of raising error - [PR #16537](https://github.com/BerriAI/litellm/pull/16537)
+ - Add headers to VLLM Passthrough requests with success event logging - [PR #16532](https://github.com/BerriAI/litellm/pull/16532)
+
+- **[Azure](../../docs/providers/azure)**
+ - Fix improve Azure auth parameter handling for None values - [PR #14436](https://github.com/BerriAI/litellm/pull/14436)
+
+- **[Groq](../../docs/providers/groq)**
+ - Fix parse failed chunks for Groq - [PR #16595](https://github.com/BerriAI/litellm/pull/16595)
+
+- **[Voyage](../../docs/providers/voyage)**
+ - Add Voyage 3.5 and 3.5-lite embeddings pricing and doc update - [PR #16641](https://github.com/BerriAI/litellm/pull/16641)
+
+- **[Fal.ai](../../docs/image_generation)**
+ - Add fal-ai/flux/schnell support - [PR #16580](https://github.com/BerriAI/litellm/pull/16580)
+ - Add all Imagen4 variants of fal ai in model map - [PR #16579](https://github.com/BerriAI/litellm/pull/16579)
+
+### Bug Fixes
+
+- **General**
+ - Fix sanitize null token usage in OpenAI-compatible responses - [PR #16493](https://github.com/BerriAI/litellm/pull/16493)
+ - Fix apply provided timeout value to ClientTimeout.total - [PR #16395](https://github.com/BerriAI/litellm/pull/16395)
+ - Fix raising wrong 429 error on wrong exception - [PR #16482](https://github.com/BerriAI/litellm/pull/16482)
+ - Add new models, delete repeat models, update pricing - [PR #16491](https://github.com/BerriAI/litellm/pull/16491)
+ - Update model logging format for custom LLM provider - [PR #16485](https://github.com/BerriAI/litellm/pull/16485)
+
+---
+
+## LLM API Endpoints
+
+#### New Endpoints
+
+- **[GET /providers](../../docs/proxy/management_endpoints)**
+ - Add GET list of providers endpoint - [PR #16432](https://github.com/BerriAI/litellm/pull/16432)
+
+#### Features
+
+- **[Video Generation API](../../docs/video_generation)**
+ - Allow internal users to access video generation routes - [PR #16472](https://github.com/BerriAI/litellm/pull/16472)
+
+- **[Vector Stores API](../../docs/vector_stores)**
+ - Vector store files stable release with complete CRUD operations - [PR #16643](https://github.com/BerriAI/litellm/pull/16643)
+ - `POST /v1/vector_stores/{vector_store_id}/files` - Create vector store file
+ - `GET /v1/vector_stores/{vector_store_id}/files` - List vector store files
+ - `GET /v1/vector_stores/{vector_store_id}/files/{file_id}` - Retrieve vector store file
+ - `GET /v1/vector_stores/{vector_store_id}/files/{file_id}/content` - Retrieve file content
+ - `DELETE /v1/vector_stores/{vector_store_id}/files/{file_id}` - Delete vector store file
+ - `DELETE /v1/vector_stores/{vector_store_id}` - Delete vector store
+ - Ensure users can access `search_results` for both stream + non-stream response - [PR #16459](https://github.com/BerriAI/litellm/pull/16459)
+
+#### Bugs
+
+- **[Video Generation API](../../docs/video_generation)**
+ - Fix use GET for `/v1/videos/{video_id}/content` - [PR #16672](https://github.com/BerriAI/litellm/pull/16672)
+
+- **General**
+ - Fix remove generic exception handling - [PR #16599](https://github.com/BerriAI/litellm/pull/16599)
+
+---
+
+## Management Endpoints / UI
+
+#### Features
+
+- **Proxy CLI Auth**
+ - Fix remove strict master_key check in add_deployment - [PR #16453](https://github.com/BerriAI/litellm/pull/16453)
+
+- **Virtual Keys**
+ - UI - Add Tags To Edit Key Flow - [PR #16500](https://github.com/BerriAI/litellm/pull/16500)
+ - UI - Test Key Page show models based on selected endpoint - [PR #16452](https://github.com/BerriAI/litellm/pull/16452)
+ - UI - Expose user_alias in view and update path - [PR #16669](https://github.com/BerriAI/litellm/pull/16669)
+
+- **Models + Endpoints**
+ - UI - Add LiteLLM Params to Edit Model - [PR #16496](https://github.com/BerriAI/litellm/pull/16496)
+ - UI - Add Model use backend data - [PR #16664](https://github.com/BerriAI/litellm/pull/16664)
+ - UI - Remove Description Field from LLM Credentials - [PR #16608](https://github.com/BerriAI/litellm/pull/16608)
+ - UI - Add RunwayML on Admin UI supported models/providers - [PR #16606](https://github.com/BerriAI/litellm/pull/16606)
+ - Infra - Migrate Add Model Fields to Backend - [PR #16620](https://github.com/BerriAI/litellm/pull/16620)
+ - Add API Endpoint for creating model access group - [PR #16663](https://github.com/BerriAI/litellm/pull/16663)
+
+- **Teams**
+ - UI - Invite User Searchable Team Select - [PR #16454](https://github.com/BerriAI/litellm/pull/16454)
+ - Fix use user budget instead of key budget when creating new team - [PR #16074](https://github.com/BerriAI/litellm/pull/16074)
+
+- **Budgets**
+ - UI - Move Budgets out of Experimental - [PR #16544](https://github.com/BerriAI/litellm/pull/16544)
+
+- **Guardrails**
+ - UI - Config Guardrails should not be deletable from table - [PR #16540](https://github.com/BerriAI/litellm/pull/16540)
+ - Fix remove enterprise restriction from guardrails list endpoint - [PR #15333](https://github.com/BerriAI/litellm/pull/15333)
+
+- **Callbacks**
+ - UI - New Callbacks table - [PR #16512](https://github.com/BerriAI/litellm/pull/16512)
+ - Fix delete callbacks failing - [PR #16473](https://github.com/BerriAI/litellm/pull/16473)
+
+- **Usage & Analytics**
+ - UI - Improve Usage Indicator - [PR #16504](https://github.com/BerriAI/litellm/pull/16504)
+ - UI - Model Info Page Health Check - [PR #16416](https://github.com/BerriAI/litellm/pull/16416)
+ - Infra - Show Deprecation Warning for Model Analytics Tab - [PR #16417](https://github.com/BerriAI/litellm/pull/16417)
+ - Fix Litellm tags usage add request_id - [PR #16111](https://github.com/BerriAI/litellm/pull/16111)
+
+- **Health Check**
+ - Add Langfuse OTEL and SQS to Health Check - [PR #16514](https://github.com/BerriAI/litellm/pull/16514)
+
+- **General UI**
+ - UI - Normalize table action columns appearance - [PR #16657](https://github.com/BerriAI/litellm/pull/16657)
+ - UI - Button Styles and Sizing in Settings Pages - [PR #16600](https://github.com/BerriAI/litellm/pull/16600)
+ - UI - SSO Modal Cosmetic Changes - [PR #16554](https://github.com/BerriAI/litellm/pull/16554)
+ - Fix UI logos loading with SERVER_ROOT_PATH - [PR #16618](https://github.com/BerriAI/litellm/pull/16618)
+ - Fix remove misleading 'Custom' option mention from OpenAI endpoint tooltips - [PR #16622](https://github.com/BerriAI/litellm/pull/16622)
+
+#### Bugs
+
+- **Management Endpoints**
+ - Fix inconsistent error responses in customer management endpoints - [PR #16450](https://github.com/BerriAI/litellm/pull/16450)
+ - Fix correct date range filtering in /spend/logs endpoint - [PR #16443](https://github.com/BerriAI/litellm/pull/16443)
+ - Fix /spend/logs/ui Access Control - [PR #16446](https://github.com/BerriAI/litellm/pull/16446)
+ - Add pagination for /spend/logs/session/ui endpoint - [PR #16603](https://github.com/BerriAI/litellm/pull/16603)
+ - Fix LiteLLM Usage shows key_hash - [PR #16471](https://github.com/BerriAI/litellm/pull/16471)
+ - Fix app_roles missing from jwt payload - [PR #16448](https://github.com/BerriAI/litellm/pull/16448)
+
+---
+
+## Logging / Guardrail / Prompt Management Integrations
+
+
+#### New Integration
+
+- **🆕 [Zscaler AI Guard](../../docs/proxy/guardrails/zscaler_ai_guard)**
+ - Add Zscaler AI Guard hook for security policy enforcement - [PR #15691](https://github.com/BerriAI/litellm/pull/15691)
+
+#### Logging
+
+- **[Langfuse](../../docs/proxy/logging#langfuse)**
+ - Fix handle null usage values to prevent validation errors - [PR #16396](https://github.com/BerriAI/litellm/pull/16396)
+
+- **[CloudZero](../../docs/proxy/logging)**
+ - Fix updated spend would not be sent to CloudZero - [PR #16201](https://github.com/BerriAI/litellm/pull/16201)
+
+#### Guardrails
+
+- **[IBM Detector](../../docs/proxy/guardrails)**
+ - Ensure detector-id is passed as header to IBM detector server - [PR #16649](https://github.com/BerriAI/litellm/pull/16649)
+
+#### Prompt Management
+
+- **[Custom Prompt Management](../../docs/proxy/prompt_management)**
+ - Add SDK focused examples for custom prompt management - [PR #16441](https://github.com/BerriAI/litellm/pull/16441)
+
+---
+
+## Spend Tracking, Budgets and Rate Limiting
+
+- **End User Budgets**
+ - Allow pointing max_end_user budget to an id, so the default ID applies to all end users - [PR #16456](https://github.com/BerriAI/litellm/pull/16456)
+
+---
+
+## MCP Gateway
+
+- **Configuration**
+ - Add dynamic OAuth2 metadata discovery for MCP servers - [PR #16676](https://github.com/BerriAI/litellm/pull/16676)
+ - Fix allow tool call even when server name prefix is missing - [PR #16425](https://github.com/BerriAI/litellm/pull/16425)
+ - Fix exclude unauthorized MCP servers from allowed server list - [PR #16551](https://github.com/BerriAI/litellm/pull/16551)
+ - Fix unable to delete MCP server from permission settings - [PR #16407](https://github.com/BerriAI/litellm/pull/16407)
+ - Fix avoid crashing when MCP server record lacks credentials - [PR #16601](https://github.com/BerriAI/litellm/pull/16601)
+
+---
+
+## Agents
+
+- **[Agent Registration (A2A Spec)](../../docs/agents)**
+ - Support agent registration + discovery following Agent-to-Agent specification - [PR #16615](https://github.com/BerriAI/litellm/pull/16615)
+
+---
+
+## Performance / Loadbalancing / Reliability improvements
+
+- **Embeddings Performance**
+ - Use router's O(1) lookup and shared sessions for embeddings - [PR #16344](https://github.com/BerriAI/litellm/pull/16344)
+
+- **Router Reliability**
+ - Support default fallbacks for unknown models - [PR #16419](https://github.com/BerriAI/litellm/pull/16419)
+
+- **Callback Management**
+ - Add atexit handlers to flush callbacks for async completions - [PR #16487](https://github.com/BerriAI/litellm/pull/16487)
+
+---
+
+## General Proxy Improvements
+
+- **Configuration Management**
+ - Fix update model_cost_map_url to use environment variable - [PR #16429](https://github.com/BerriAI/litellm/pull/16429)
+
+---
+
+## Documentation Updates
+
+- **Provider Documentation**
+ - Fix streaming example in README - [PR #16461](https://github.com/BerriAI/litellm/pull/16461)
+ - Update broken Slack invite links to support page - [PR #16546](https://github.com/BerriAI/litellm/pull/16546)
+ - Fix code block indentation for fallbacks page - [PR #16542](https://github.com/BerriAI/litellm/pull/16542)
+ - Documentation code example corrections - [PR #16502](https://github.com/BerriAI/litellm/pull/16502)
+ - Document `reasoning_effort` summary field options - [PR #16549](https://github.com/BerriAI/litellm/pull/16549)
+
+- **API Documentation**
+ - Add docs on APIs for model access management - [PR #16673](https://github.com/BerriAI/litellm/pull/16673)
+ - Add docs for showing how to auto reload new pricing data - [PR #16675](https://github.com/BerriAI/litellm/pull/16675)
+ - LiteLLM Quick start - show how model resolution works - [PR #16602](https://github.com/BerriAI/litellm/pull/16602)
+ - Add docs for tracking callback failure - [PR #16474](https://github.com/BerriAI/litellm/pull/16474)
+
+- **General Documentation**
+ - Fix container api link in release page - [PR #16440](https://github.com/BerriAI/litellm/pull/16440)
+ - Add softgen to projects that are using litellm - [PR #16423](https://github.com/BerriAI/litellm/pull/16423)
+
+---
+
+## New Contributors
+
+* @artplan1 made their first contribution in [PR #16423](https://github.com/BerriAI/litellm/pull/16423)
+* @JehandadK made their first contribution in [PR #16472](https://github.com/BerriAI/litellm/pull/16472)
+* @vmiscenko made their first contribution in [PR #16453](https://github.com/BerriAI/litellm/pull/16453)
+* @mcowger made their first contribution in [PR #16429](https://github.com/BerriAI/litellm/pull/16429)
+* @yellowsubmarine372 made their first contribution in [PR #16395](https://github.com/BerriAI/litellm/pull/16395)
+* @Hebruwu made their first contribution in [PR #16201](https://github.com/BerriAI/litellm/pull/16201)
+* @jwang-gif made their first contribution in [PR #15691](https://github.com/BerriAI/litellm/pull/15691)
+* @AnthonyMonaco made their first contribution in [PR #16502](https://github.com/BerriAI/litellm/pull/16502)
+* @andrewm4894 made their first contribution in [PR #16487](https://github.com/BerriAI/litellm/pull/16487)
+* @f14-bertolotti made their first contribution in [PR #16485](https://github.com/BerriAI/litellm/pull/16485)
+* @busla made their first contribution in [PR #16293](https://github.com/BerriAI/litellm/pull/16293)
+* @MightyGoldenOctopus made their first contribution in [PR #16537](https://github.com/BerriAI/litellm/pull/16537)
+* @ultmaster made their first contribution in [PR #14436](https://github.com/BerriAI/litellm/pull/14436)
+* @bchrobot made their first contribution in [PR #16542](https://github.com/BerriAI/litellm/pull/16542)
+* @sep-grindr made their first contribution in [PR #16622](https://github.com/BerriAI/litellm/pull/16622)
+* @pnookala-godaddy made their first contribution in [PR #16607](https://github.com/BerriAI/litellm/pull/16607)
+* @dtunikov made their first contribution in [PR #16592](https://github.com/BerriAI/litellm/pull/16592)
+* @lukapecnik made their first contribution in [PR #16648](https://github.com/BerriAI/litellm/pull/16648)
+* @jyeros made their first contribution in [PR #16618](https://github.com/BerriAI/litellm/pull/16618)
+
+---
+
+## Full Changelog
+
+**[View complete changelog on GitHub](https://github.com/BerriAI/litellm/compare/v1.79.3.rc.1...v1.80.0.rc.1)**
+
+---
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index 99472981f0c..432d2d109eb 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -146,13 +146,13 @@ const sidebars = {
type: "category",
label: "Admin UI",
items: [
+ "proxy/ui",
"proxy/admin_ui_sso",
"proxy/custom_root_ui",
"proxy/custom_sso",
- "proxy/model_hub",
+ "proxy/ai_hub",
"proxy/public_teams",
"proxy/self_serve",
- "proxy/ui",
"proxy/ui/bulk_edit_users",
"proxy/ui_credentials",
"tutorials/scim_litellm",
@@ -368,6 +368,7 @@ const sidebars = {
]
},
"videos",
+ "vector_store_files",
{
type: "category",
label: "/mcp - Model Context Protocol",
diff --git a/docs/my-website/static/img/favicon.ico b/docs/my-website/static/img/favicon.ico
index 88caa2b8315..7c45601d5c3 100644
Binary files a/docs/my-website/static/img/favicon.ico and b/docs/my-website/static/img/favicon.ico differ
diff --git a/enterprise/dist/litellm_enterprise-0.1.21-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.21-py3-none-any.whl
new file mode 100644
index 00000000000..6452930c9f0
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diff --git a/enterprise/dist/litellm_enterprise-0.1.21.tar.gz b/enterprise/dist/litellm_enterprise-0.1.21.tar.gz
new file mode 100644
index 00000000000..ed6ebc3834e
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diff --git a/enterprise/dist/litellm_enterprise-0.1.22-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.22-py3-none-any.whl
new file mode 100644
index 00000000000..6ad5b7041c5
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diff --git a/enterprise/dist/litellm_enterprise-0.1.22.tar.gz b/enterprise/dist/litellm_enterprise-0.1.22.tar.gz
new file mode 100644
index 00000000000..9db2c14b12f
Binary files /dev/null and b/enterprise/dist/litellm_enterprise-0.1.22.tar.gz differ
diff --git a/enterprise/litellm_enterprise/enterprise_callbacks/callback_controls.py b/enterprise/litellm_enterprise/enterprise_callbacks/callback_controls.py
index ff3e9a744c1..8824f4c02de 100644
--- a/enterprise/litellm_enterprise/enterprise_callbacks/callback_controls.py
+++ b/enterprise/litellm_enterprise/enterprise_callbacks/callback_controls.py
@@ -40,7 +40,7 @@ class EnterpriseCallbackControls:
#########################################################
# premium user check
#########################################################
- if not EnterpriseCallbackControls._premium_user_check():
+ if not EnterpriseCallbackControls._should_allow_dynamic_callback_disabling():
return False
#########################################################
if isinstance(callback, str):
@@ -84,8 +84,15 @@ class EnterpriseCallbackControls:
return None
@staticmethod
- def _premium_user_check():
+ def _should_allow_dynamic_callback_disabling():
+ import litellm
from litellm.proxy.proxy_server import premium_user
+
+ # Check if admin has disabled this feature
+ if litellm.allow_dynamic_callback_disabling is not True:
+ verbose_logger.debug("Dynamic callback disabling is disabled by admin via litellm.allow_dynamic_callback_disabling")
+ return False
+
if premium_user:
return True
verbose_logger.warning(f"Disabling callbacks using request headers is an enterprise feature. {CommonProxyErrors.not_premium_user.value}")
diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
index 80cc77883fe..608bb495885 100644
--- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
+++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
@@ -296,6 +296,16 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
file_ids, user_api_key_dict.parent_otel_span
)
+ data["model_file_id_mapping"] = model_file_id_mapping
+ elif call_type == CallTypes.aresponses.value or call_type == CallTypes.responses.value:
+ # Handle managed files in responses API input
+ input_data = data.get("input")
+ if input_data:
+ file_ids = self.get_file_ids_from_responses_input(input_data)
+ if file_ids:
+ model_file_id_mapping = await self.get_model_file_id_mapping(
+ file_ids, user_api_key_dict.parent_otel_span
+ )
data["model_file_id_mapping"] = model_file_id_mapping
elif call_type == CallTypes.afile_content.value:
retrieve_file_id = cast(Optional[str], data.get("file_id"))
@@ -453,6 +463,47 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
file_ids.append(file_id)
return file_ids
+ def get_file_ids_from_responses_input(
+ self, input: Union[str, List[Dict[str, Any]]]
+ ) -> List[str]:
+ """
+ Gets file ids from responses API input.
+
+ The input can be:
+ - A string (no files)
+ - A list of input items, where each item can have:
+ - type: "input_file" with file_id
+ - content: a list that can contain items with type: "input_file" and file_id
+ """
+ file_ids: List[str] = []
+
+ if isinstance(input, str):
+ return file_ids
+
+ if not isinstance(input, list):
+ return file_ids
+
+ for item in input:
+ if not isinstance(item, dict):
+ continue
+
+ # Check for direct input_file type
+ if item.get("type") == "input_file":
+ file_id = item.get("file_id")
+ if file_id:
+ file_ids.append(file_id)
+
+ # Check for input_file in content array
+ content = item.get("content")
+ if isinstance(content, list):
+ for content_item in content:
+ if isinstance(content_item, dict) and content_item.get("type") == "input_file":
+ file_id = content_item.get("file_id")
+ if file_id:
+ file_ids.append(file_id)
+
+ return file_ids
+
async def get_model_file_id_mapping(
self, file_ids: List[str], litellm_parent_otel_span: Span
) -> dict:
@@ -478,7 +529,6 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
for file_id in file_ids:
## CHECK IF FILE ID IS MANAGED BY LITELM
is_base64_unified_file_id = _is_base64_encoded_unified_file_id(file_id)
-
if is_base64_unified_file_id:
litellm_managed_file_ids.append(file_id)
@@ -489,6 +539,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
unified_file_object = await self.get_unified_file_id(
file_id, litellm_parent_otel_span
)
+
if unified_file_object:
file_id_mapping[file_id] = unified_file_object.model_mappings
@@ -764,18 +815,21 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
llm_router: Router,
**data: Dict,
) -> OpenAIFileObject:
- file_id = convert_b64_uid_to_unified_uid(file_id)
+
+ # file_id = convert_b64_uid_to_unified_uid(file_id)
model_file_id_mapping = await self.get_model_file_id_mapping(
[file_id], litellm_parent_otel_span
)
+
specific_model_file_id_mapping = model_file_id_mapping.get(file_id)
if specific_model_file_id_mapping:
- for model_id, file_id in specific_model_file_id_mapping.items():
- await llm_router.afile_delete(model=model_id, file_id=file_id, **data) # type: ignore
+ for model_id, model_file_id in specific_model_file_id_mapping.items():
+ await llm_router.afile_delete(model=model_id, file_id=model_file_id, **data) # type: ignore
stored_file_object = await self.delete_unified_file_id(
file_id, litellm_parent_otel_span
)
+
if stored_file_object:
return stored_file_object
else:
@@ -796,6 +850,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
model_file_id_mapping
or await self.get_model_file_id_mapping([file_id], litellm_parent_otel_span)
)
+
specific_model_file_id_mapping = model_file_id_mapping.get(file_id)
if specific_model_file_id_mapping:
diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml
index 1d1fa64549c..2c1fa9945bb 100644
--- a/enterprise/pyproject.toml
+++ b/enterprise/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm-enterprise"
-version = "0.1.20"
+version = "0.1.22"
description = "Package for LiteLLM Enterprise features"
authors = ["BerriAI"]
readme = "README.md"
@@ -22,7 +22,7 @@ requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.commitizen]
-version = "0.1.20"
+version = "0.1.22"
version_files = [
"pyproject.toml:version",
"../requirements.txt:litellm-enterprise==",
diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.5-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.5-py3-none-any.whl
new file mode 100644
index 00000000000..c2561652dda
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diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.5.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.5.tar.gz
new file mode 100644
index 00000000000..728636d207a
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diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.6-py3-none-any.whl b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.6-py3-none-any.whl
new file mode 100644
index 00000000000..346c07b06ea
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diff --git a/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.6.tar.gz b/litellm-proxy-extras/dist/litellm_proxy_extras-0.4.6.tar.gz
new file mode 100644
index 00000000000..3a25d44425d
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diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20251114182247_agents_table/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251114182247_agents_table/migration.sql
new file mode 100644
index 00000000000..28760dcfe48
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251114182247_agents_table/migration.sql
@@ -0,0 +1,17 @@
+-- CreateTable
+CREATE TABLE "LiteLLM_AgentsTable" (
+ "agent_id" TEXT NOT NULL,
+ "agent_name" TEXT NOT NULL,
+ "litellm_params" JSONB,
+ "agent_card_params" JSONB NOT NULL,
+ "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+ "created_by" TEXT NOT NULL,
+ "updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+ "updated_by" TEXT NOT NULL,
+
+ CONSTRAINT "LiteLLM_AgentsTable_pkey" PRIMARY KEY ("agent_id")
+);
+
+-- CreateIndex
+CREATE UNIQUE INDEX "LiteLLM_AgentsTable_agent_name_key" ON "LiteLLM_AgentsTable"("agent_name");
+
diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120021_baseline_diff/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120021_baseline_diff/migration.sql
new file mode 100644
index 00000000000..2f725d83806
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120021_baseline_diff/migration.sql
@@ -0,0 +1,2 @@
+-- This is an empty migration.
+
diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120539_baseline_diff/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120539_baseline_diff/migration.sql
new file mode 100644
index 00000000000..2f725d83806
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251115120539_baseline_diff/migration.sql
@@ -0,0 +1,2 @@
+-- This is an empty migration.
+
diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20251119131227_add_prompt_versioning/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251119131227_add_prompt_versioning/migration.sql
new file mode 100644
index 00000000000..a9d9528bd24
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20251119131227_add_prompt_versioning/migration.sql
@@ -0,0 +1,12 @@
+-- DropIndex
+DROP INDEX "LiteLLM_PromptTable_prompt_id_key";
+
+-- AlterTable
+ALTER TABLE "LiteLLM_PromptTable" ADD COLUMN "version" INTEGER NOT NULL DEFAULT 1;
+
+-- CreateIndex
+CREATE INDEX "LiteLLM_PromptTable_prompt_id_idx" ON "LiteLLM_PromptTable"("prompt_id");
+
+-- CreateIndex
+CREATE UNIQUE INDEX "LiteLLM_PromptTable_prompt_id_version_key" ON "LiteLLM_PromptTable"("prompt_id", "version");
+
diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
index 88904561129..6cfbb90c362 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
+++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
@@ -54,6 +54,19 @@ model LiteLLM_ProxyModelTable {
updated_by String
}
+
+// Agents on proxy
+model LiteLLM_AgentsTable {
+ agent_id String @id @default(uuid())
+ agent_name String @unique
+ litellm_params Json?
+ agent_card_params Json
+ created_at DateTime @default(now()) @map("created_at")
+ created_by String
+ updated_at DateTime @default(now()) @updatedAt @map("updated_at")
+ updated_by String
+}
+
model LiteLLM_OrganizationTable {
organization_id String @id @default(uuid())
organization_alias String
@@ -548,11 +561,15 @@ model LiteLLM_GuardrailsTable {
// Prompt table for storing prompt configurations
model LiteLLM_PromptTable {
id String @id @default(uuid())
- prompt_id String @unique
+ prompt_id String
+ version Int @default(1)
litellm_params Json
prompt_info Json?
created_at DateTime @default(now())
updated_at DateTime @updatedAt
+
+ @@unique([prompt_id, version])
+ @@index([prompt_id])
}
model LiteLLM_HealthCheckTable {
@@ -610,4 +627,4 @@ model LiteLLM_CacheConfig {
cache_settings Json
created_at DateTime @default(now())
updated_at DateTime @updatedAt
-}
+}
\ No newline at end of file
diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml
index 0451a6c4538..78e34ccd01a 100644
--- a/litellm-proxy-extras/pyproject.toml
+++ b/litellm-proxy-extras/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm-proxy-extras"
-version = "0.4.4"
+version = "0.4.6"
description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
authors = ["BerriAI"]
readme = "README.md"
@@ -22,7 +22,7 @@ requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.commitizen]
-version = "0.4.4"
+version = "0.4.6"
version_files = [
"pyproject.toml:version",
"../requirements.txt:litellm-proxy-extras==",
diff --git a/litellm/__init__.py b/litellm/__init__.py
index 4993570aded..b46a165ed10 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -181,22 +181,22 @@ prometheus_initialize_budget_metrics: Optional[bool] = False
require_auth_for_metrics_endpoint: Optional[bool] = False
argilla_batch_size: Optional[int] = None
datadog_use_v1: Optional[bool] = False # if you want to use v1 datadog logged payload.
-gcs_pub_sub_use_v1: Optional[
- bool
-] = False # if you want to use v1 gcs pubsub logged payload
-generic_api_use_v1: Optional[
- bool
-] = False # if you want to use v1 generic api logged payload
+gcs_pub_sub_use_v1: Optional[bool] = (
+ False # if you want to use v1 gcs pubsub logged payload
+)
+generic_api_use_v1: Optional[bool] = (
+ False # if you want to use v1 generic api logged payload
+)
argilla_transformation_object: Optional[Dict[str, Any]] = None
-_async_input_callback: List[
- Union[str, Callable, CustomLogger]
-] = [] # internal variable - async custom callbacks are routed here.
-_async_success_callback: List[
- Union[str, Callable, CustomLogger]
-] = [] # internal variable - async custom callbacks are routed here.
-_async_failure_callback: List[
- Union[str, Callable, CustomLogger]
-] = [] # internal variable - async custom callbacks are routed here.
+_async_input_callback: List[Union[str, Callable, CustomLogger]] = (
+ []
+) # internal variable - async custom callbacks are routed here.
+_async_success_callback: List[Union[str, Callable, CustomLogger]] = (
+ []
+) # internal variable - async custom callbacks are routed here.
+_async_failure_callback: List[Union[str, Callable, CustomLogger]] = (
+ []
+) # internal variable - async custom callbacks are routed here.
pre_call_rules: List[Callable] = []
post_call_rules: List[Callable] = []
turn_off_message_logging: Optional[bool] = False
@@ -204,18 +204,18 @@ log_raw_request_response: bool = False
redact_messages_in_exceptions: Optional[bool] = False
redact_user_api_key_info: Optional[bool] = False
filter_invalid_headers: Optional[bool] = False
-add_user_information_to_llm_headers: Optional[
- bool
-] = None # adds user_id, team_id, token hash (params from StandardLoggingMetadata) to request headers
+add_user_information_to_llm_headers: Optional[bool] = (
+ None # adds user_id, team_id, token hash (params from StandardLoggingMetadata) to request headers
+)
store_audit_logs = False # Enterprise feature, allow users to see audit logs
### end of callbacks #############
-email: Optional[
- str
-] = None # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
-token: Optional[
- str
-] = None # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
+email: Optional[str] = (
+ None # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
+)
+token: Optional[str] = (
+ None # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
+)
telemetry = True
max_tokens: int = DEFAULT_MAX_TOKENS # OpenAI Defaults
drop_params = bool(os.getenv("LITELLM_DROP_PARAMS", False))
@@ -271,9 +271,9 @@ use_client: bool = False
ssl_verify: Union[str, bool] = True
ssl_security_level: Optional[str] = None
ssl_certificate: Optional[str] = None
-ssl_ecdh_curve: Optional[
- str
-] = None # Set to 'X25519' to disable PQC and improve performance
+ssl_ecdh_curve: Optional[str] = (
+ None # Set to 'X25519' to disable PQC and improve performance
+)
disable_streaming_logging: bool = False
disable_token_counter: bool = False
disable_add_transform_inline_image_block: bool = False
@@ -319,20 +319,24 @@ enable_loadbalancing_on_batch_endpoints: Optional[bool] = None
enable_caching_on_provider_specific_optional_params: bool = (
False # feature-flag for caching on optional params - e.g. 'top_k'
)
-caching: bool = False # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
-caching_with_models: bool = False # # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
-cache: Optional[
- Cache
-] = None # cache object <- use this - https://docs.litellm.ai/docs/caching
+caching: bool = (
+ False # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
+)
+caching_with_models: bool = (
+ False # # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
+)
+cache: Optional[Cache] = (
+ None # cache object <- use this - https://docs.litellm.ai/docs/caching
+)
default_in_memory_ttl: Optional[float] = None
default_redis_ttl: Optional[float] = None
default_redis_batch_cache_expiry: Optional[float] = None
model_alias_map: Dict[str, str] = {}
model_group_settings: Optional["ModelGroupSettings"] = None
max_budget: float = 0.0 # set the max budget across all providers
-budget_duration: Optional[
- str
-] = None # proxy only - resets budget after fixed duration. You can set duration as seconds ("30s"), minutes ("30m"), hours ("30h"), days ("30d").
+budget_duration: Optional[str] = (
+ None # proxy only - resets budget after fixed duration. You can set duration as seconds ("30s"), minutes ("30m"), hours ("30h"), days ("30d").
+)
default_soft_budget: float = (
DEFAULT_SOFT_BUDGET # by default all litellm proxy keys have a soft budget of 50.0
)
@@ -341,7 +345,9 @@ forward_traceparent_to_llm_provider: bool = False
_current_cost = 0.0 # private variable, used if max budget is set
error_logs: Dict = {}
-add_function_to_prompt: bool = False # if function calling not supported by api, append function call details to system prompt
+add_function_to_prompt: bool = (
+ False # if function calling not supported by api, append function call details to system prompt
+)
client_session: Optional[httpx.Client] = None
aclient_session: Optional[httpx.AsyncClient] = None
model_fallbacks: Optional[List] = None # Deprecated for 'litellm.fallbacks'
@@ -379,8 +385,12 @@ prometheus_metrics_config: Optional[List] = None
disable_add_prefix_to_prompt: bool = (
False # used by anthropic, to disable adding prefix to prompt
)
-disable_copilot_system_to_assistant: bool = False # If false (default), converts all 'system' role messages to 'assistant' for GitHub Copilot compatibility. Set to true to disable this behavior.
+disable_copilot_system_to_assistant: bool = (
+ False # If false (default), converts all 'system' role messages to 'assistant' for GitHub Copilot compatibility. Set to true to disable this behavior.
+)
+public_mcp_servers: Optional[List[str]] = None
public_model_groups: Optional[List[str]] = None
+public_agent_groups: Optional[List[str]] = None
public_model_groups_links: Dict[str, str] = {}
#### REQUEST PRIORITIZATION #######
priority_reservation: Optional[Dict[str, Union[float, PriorityReservationDict]]] = None
@@ -390,13 +400,17 @@ priority_reservation_settings: "PriorityReservationSettings" = (
######## Networking Settings ########
-use_aiohttp_transport: bool = True # Older variable, aiohttp is now the default. use disable_aiohttp_transport instead.
+use_aiohttp_transport: bool = (
+ True # Older variable, aiohttp is now the default. use disable_aiohttp_transport instead.
+)
aiohttp_trust_env: bool = False # set to true to use HTTP_ Proxy settings
disable_aiohttp_transport: bool = False # Set this to true to use httpx instead
disable_aiohttp_trust_env: bool = (
False # When False, aiohttp will respect HTTP(S)_PROXY env vars
)
-force_ipv4: bool = False # when True, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6.
+force_ipv4: bool = (
+ False # when True, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6.
+)
module_level_aclient = AsyncHTTPHandler(
timeout=request_timeout, client_alias="module level aclient"
)
@@ -410,13 +424,14 @@ fallbacks: Optional[List] = None
context_window_fallbacks: Optional[List] = None
content_policy_fallbacks: Optional[List] = None
allowed_fails: int = 3
-num_retries_per_request: Optional[
- int
-] = None # for the request overall (incl. fallbacks + model retries)
+allow_dynamic_callback_disabling: bool = True
+num_retries_per_request: Optional[int] = (
+ None # for the request overall (incl. fallbacks + model retries)
+)
####### SECRET MANAGERS #####################
-secret_manager_client: Optional[
- Any
-] = None # list of instantiated key management clients - e.g. azure kv, infisical, etc.
+secret_manager_client: Optional[Any] = (
+ None # list of instantiated key management clients - e.g. azure kv, infisical, etc.
+)
_google_kms_resource_name: Optional[str] = None
_key_management_system: Optional[KeyManagementSystem] = None
_key_management_settings: KeyManagementSettings = KeyManagementSettings()
@@ -426,9 +441,9 @@ output_parse_pii: bool = False
from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
model_cost = get_model_cost_map(url=model_cost_map_url)
-cost_discount_config: Dict[
- str, float
-] = {} # Provider-specific cost discounts {"vertex_ai": 0.05} = 5% discount
+cost_discount_config: Dict[str, float] = (
+ {}
+) # Provider-specific cost discounts {"vertex_ai": 0.05} = 5% discount
custom_prompt_dict: Dict[str, dict] = {}
check_provider_endpoint = False
@@ -1328,6 +1343,9 @@ from .llms.watsonx.completion.transformation import IBMWatsonXAIConfig
from .llms.watsonx.chat.transformation import IBMWatsonXChatConfig
from .llms.watsonx.embed.transformation import IBMWatsonXEmbeddingConfig
from .llms.github_copilot.chat.transformation import GithubCopilotConfig
+from .llms.github_copilot.responses.transformation import (
+ GithubCopilotResponsesAPIConfig,
+)
from .llms.nebius.chat.transformation import NebiusConfig
from .llms.wandb.chat.transformation import WandbConfig
from .llms.dashscope.chat.transformation import DashScopeChatConfig
@@ -1342,6 +1360,7 @@ from .llms.ovhcloud.chat.transformation import OVHCloudChatConfig
from .llms.ovhcloud.embedding.transformation import OVHCloudEmbeddingConfig
from .llms.cometapi.embed.transformation import CometAPIEmbeddingConfig
from .llms.lemonade.chat.transformation import LemonadeChatConfig
+from .llms.snowflake.embedding.transformation import SnowflakeEmbeddingConfig
from .main import * # type: ignore
from .integrations import *
from .llms.custom_httpx.async_client_cleanup import close_litellm_async_clients
@@ -1386,6 +1405,20 @@ from .search.main import *
from .realtime_api.main import _arealtime
from .fine_tuning.main import *
from .files.main import *
+from .vector_store_files.main import (
+ acreate as avector_store_file_create,
+ adelete as avector_store_file_delete,
+ alist as avector_store_file_list,
+ aretrieve as avector_store_file_retrieve,
+ aretrieve_content as avector_store_file_content,
+ aupdate as avector_store_file_update,
+ create as vector_store_file_create,
+ delete as vector_store_file_delete,
+ list as vector_store_file_list,
+ retrieve as vector_store_file_retrieve,
+ retrieve_content as vector_store_file_content,
+ update as vector_store_file_update,
+)
from .scheduler import *
from .cost_calculator import response_cost_calculator, cost_per_token
@@ -1409,12 +1442,12 @@ from .types.llms.custom_llm import CustomLLMItem
from .types.utils import GenericStreamingChunk
custom_provider_map: List[CustomLLMItem] = []
-_custom_providers: List[
- str
-] = [] # internal helper util, used to track names of custom providers
-disable_hf_tokenizer_download: Optional[
- bool
-] = None # disable huggingface tokenizer download. Defaults to openai clk100
+_custom_providers: List[str] = (
+ []
+) # internal helper util, used to track names of custom providers
+disable_hf_tokenizer_download: Optional[bool] = (
+ None # disable huggingface tokenizer download. Defaults to openai clk100
+)
global_disable_no_log_param: bool = False
### CLI UTILITIES ###
diff --git a/litellm/batches/main.py b/litellm/batches/main.py
index 48521e5fba0..5279dd70bc4 100644
--- a/litellm/batches/main.py
+++ b/litellm/batches/main.py
@@ -17,6 +17,8 @@ from functools import partial
from typing import Any, Coroutine, Dict, Literal, Optional, Union, cast
import httpx
+from openai.types.batch import BatchRequestCounts
+from openai.types.batch import Metadata as BatchMetadata
import litellm
from litellm._logging import verbose_logger
@@ -223,10 +225,12 @@ def create_batch(
api_key=optional_params.api_key,
logging_obj=litellm_logging_obj,
_is_async=_is_async,
- client=client
- if client is not None
- and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
- else None,
+ client=(
+ client
+ if client is not None
+ and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
+ else None
+ ),
timeout=timeout,
model=model,
)
@@ -609,10 +613,12 @@ def retrieve_batch(
function_id="batch_retrieve",
),
_is_async=_is_async,
- client=client
- if client is not None
- and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
- else None,
+ client=(
+ client
+ if client is not None
+ and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
+ else None
+ ),
timeout=timeout,
model=model,
)
@@ -799,6 +805,7 @@ def list_batches(
async def acancel_batch(
batch_id: str,
+ model: Optional[str] = None,
custom_llm_provider: Literal["openai", "azure"] = "openai",
metadata: Optional[Dict[str, str]] = None,
extra_headers: Optional[Dict[str, str]] = None,
@@ -813,11 +820,13 @@ async def acancel_batch(
try:
loop = asyncio.get_event_loop()
kwargs["acancel_batch"] = True
+ model = kwargs.pop("model", None)
# Use a partial function to pass your keyword arguments
func = partial(
cancel_batch,
batch_id,
+ model,
custom_llm_provider,
metadata,
extra_headers,
@@ -840,7 +849,8 @@ async def acancel_batch(
def cancel_batch(
batch_id: str,
- custom_llm_provider: Literal["openai", "azure"] = "openai",
+ model: Optional[str] = None,
+ custom_llm_provider: Union[Literal["openai", "azure"], str] = "openai",
metadata: Optional[Dict[str, str]] = None,
extra_headers: Optional[Dict[str, str]] = None,
extra_body: Optional[Dict[str, str]] = None,
@@ -852,6 +862,17 @@ def cancel_batch(
LiteLLM Equivalent of POST https://api.openai.com/v1/batches/{batch_id}/cancel
"""
try:
+
+ try:
+ if model is not None:
+ _, custom_llm_provider, _, _ = get_llm_provider(
+ model=model,
+ custom_llm_provider=custom_llm_provider,
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ f"litellm.batches.main.py::cancel_batch() - Error inferring custom_llm_provider - {str(e)}"
+ )
optional_params = GenericLiteLLMParams(**kwargs)
litellm_params = get_litellm_params(
custom_llm_provider=custom_llm_provider,
@@ -1005,21 +1026,28 @@ def _handle_async_invoke_status(
created_at=status_response["submitTime"],
in_progress_at=status_response["lastModifiedTime"],
completed_at=status_response.get("endTime"),
- failed_at=status_response.get("endTime")
- if status_response["status"] == "failed"
- else None,
- request_counts={
- "total": 1,
- "completed": 1 if status_response["status"] == "completed" else 0,
- "failed": 1 if status_response["status"] == "failed" else 0,
- },
- metadata={
- "output_file_id": status_response["outputDataConfig"][
- "s3OutputDataConfig"
- ]["s3Uri"],
- "failure_message": status_response.get("failureMessage"),
- "model_arn": status_response["modelArn"],
- },
+ failed_at=(
+ status_response.get("endTime")
+ if status_response["status"] == "failed"
+ else None
+ ),
+ request_counts=BatchRequestCounts(
+ total=1,
+ completed=1 if status_response["status"] == "completed" else 0,
+ failed=1 if status_response["status"] == "failed" else 0,
+ ),
+ metadata=dict(
+ **{
+ "output_file_id": status_response["outputDataConfig"][
+ "s3OutputDataConfig"
+ ]["s3Uri"],
+ "failure_message": status_response.get("failureMessage") or "",
+ "model_arn": status_response["modelArn"],
+ }
+ ),
+ completion_window="24h",
+ endpoint="/v1/embeddings",
+ input_file_id="",
)
return result
diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index 8c3ebd51036..3ac5a28f900 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -26,7 +26,12 @@ from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
from litellm.llms.base_llm.bridges.completion_transformation import (
CompletionTransformationBridge,
)
-from litellm.types.llms.openai import ChatCompletionToolParamFunctionChunk, Reasoning
+from litellm.types.llms.openai import (
+ ChatCompletionToolParamFunctionChunk,
+ Reasoning,
+ ResponsesAPIOptionalRequestParams,
+ ResponsesAPIStreamEvents,
+)
if TYPE_CHECKING:
from openai.types.responses import ResponseInputImageParam
@@ -165,13 +170,13 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
litellm_logging_obj: "LiteLLMLoggingObj",
client: Optional[Any] = None,
) -> dict:
- from litellm.types.llms.openai import ResponsesAPIOptionalRequestParams
-
(
input_items,
instructions,
) = self.convert_chat_completion_messages_to_responses_api(messages)
+ optional_params = self._extract_extra_body_params(optional_params)
+
# Build responses API request using the reverse transformation logic
responses_api_request = ResponsesAPIOptionalRequestParams()
@@ -194,9 +199,9 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
)
elif key in ResponsesAPIOptionalRequestParams.__annotations__.keys():
responses_api_request[key] = value # type: ignore
- elif key in ("metadata"):
+ elif key == "metadata":
responses_api_request["metadata"] = value
- elif key in ("previous_response_id"):
+ elif key == "previous_response_id":
responses_api_request["previous_response_id"] = value
elif key == "reasoning_effort":
responses_api_request["reasoning"] = self._map_reasoning_effort(value)
@@ -538,6 +543,35 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
return cast(List["ALL_RESPONSES_API_TOOL_PARAMS"], responses_tools)
+ def _extract_extra_body_params(self, optional_params: dict):
+ """
+ Extract extra_body from optional_params and separate supported Responses API params
+ from unsupported ones. Supported params are moved to top-level optional_params,
+ unsupported params remain in extra_body.
+ """
+ # Extract extra_body and separate supported params from unsupported ones
+ extra_body = optional_params.pop("extra_body", None) or {}
+ if not extra_body:
+ return optional_params
+
+ supported_responses_api_params = set(
+ ResponsesAPIOptionalRequestParams.__annotations__.keys()
+ )
+ # Also include params we handle specially
+ supported_responses_api_params.update({
+ "previous_response_id",
+ "reasoning_effort", # We map this to "reasoning"
+ })
+
+ # Extract supported params from extra_body and merge into optional_params
+ extra_body_copy = extra_body.copy()
+ for key, value in extra_body_copy.items():
+ if key in supported_responses_api_params:
+ # Prefer extra_body value if it exists (may have more complete info like summary in reasoning_effort)
+ optional_params[key] = extra_body.pop(key)
+
+ return optional_params
+
def _map_reasoning_effort(self, reasoning_effort: Union[str, Dict[str, Any]]) -> Optional[Reasoning]:
# If dict is passed, convert it directly to Reasoning object
if isinstance(reasoning_effort, dict):
@@ -619,6 +653,8 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
# Handle different event types from responses API
event_type = parsed_chunk.get("type")
+ if isinstance(event_type, ResponsesAPIStreamEvents):
+ event_type = event_type.value
verbose_logger.debug(f"Chat provider: Processing event type: {event_type}")
if event_type == "response.created":
@@ -638,7 +674,7 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
index=0,
type="function",
function=ChatCompletionToolCallFunctionChunk(
- name=parsed_chunk.get("name", None),
+ name=output_item.get("name", None),
arguments=parsed_chunk.get("arguments", ""),
),
),
@@ -684,7 +720,7 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
index=0,
type="function",
function=ChatCompletionToolCallFunctionChunk(
- name=parsed_chunk.get("name", None),
+ name=output_item.get("name", None),
arguments="", # responses API sends everything again, we don't
),
),
diff --git a/litellm/constants.py b/litellm/constants.py
index d22772c7fbd..bc72e93850b 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -1,7 +1,9 @@
import os
from typing import List, Literal
-DEFAULT_HEALTH_CHECK_PROMPT = str(os.getenv("DEFAULT_HEALTH_CHECK_PROMPT", "test from litellm"))
+DEFAULT_HEALTH_CHECK_PROMPT = str(
+ os.getenv("DEFAULT_HEALTH_CHECK_PROMPT", "test from litellm")
+)
AZURE_DEFAULT_RESPONSES_API_VERSION = str(
os.getenv("AZURE_DEFAULT_RESPONSES_API_VERSION", "preview")
)
@@ -18,7 +20,9 @@ DEFAULT_SQS_FLUSH_INTERVAL_SECONDS = int(
DEFAULT_NUM_WORKERS_LITELLM_PROXY = int(
os.getenv("DEFAULT_NUM_WORKERS_LITELLM_PROXY", 1)
)
-DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE = int(os.getenv("DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE", 1))
+DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE = int(
+ os.getenv("DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE", 1)
+)
DEFAULT_SQS_BATCH_SIZE = int(os.getenv("DEFAULT_SQS_BATCH_SIZE", 512))
SQS_SEND_MESSAGE_ACTION = "SendMessage"
SQS_API_VERSION = "2012-11-05"
@@ -85,8 +89,12 @@ MAX_TOKEN_TRIMMING_ATTEMPTS = int(
os.getenv("MAX_TOKEN_TRIMMING_ATTEMPTS", 10)
) # Maximum number of attempts to trim the message
-RUNWAYML_DEFAULT_API_VERSION = str(os.getenv("RUNWAYML_DEFAULT_API_VERSION", "2024-11-06"))
-RUNWAYML_POLLING_TIMEOUT = int(os.getenv("RUNWAYML_POLLING_TIMEOUT", 600)) # 10 minutes default for image generation
+RUNWAYML_DEFAULT_API_VERSION = str(
+ os.getenv("RUNWAYML_DEFAULT_API_VERSION", "2024-11-06")
+)
+RUNWAYML_POLLING_TIMEOUT = int(
+ os.getenv("RUNWAYML_POLLING_TIMEOUT", 600)
+) # 10 minutes default for image generation
########## Networking constants ##############################################################
_DEFAULT_TTL_FOR_HTTPX_CLIENTS = 3600 # 1 hour, re-use the same httpx client for 1 hour
@@ -110,22 +118,21 @@ REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES = (
DEFAULT_SSL_CIPHERS = os.getenv(
"LITELLM_SSL_CIPHERS",
# Priority 1: TLS 1.3 ciphers (fastest, ~50ms handshake)
- "TLS_AES_256_GCM_SHA384:" # Fastest observed in testing
- "TLS_AES_128_GCM_SHA256:" # Slightly faster than 256-bit
- "TLS_CHACHA20_POLY1305_SHA256:" # Fast on ARM/mobile
+ "TLS_AES_256_GCM_SHA384:" # Fastest observed in testing
+ "TLS_AES_128_GCM_SHA256:" # Slightly faster than 256-bit
+ "TLS_CHACHA20_POLY1305_SHA256:" # Fast on ARM/mobile
# Priority 2: TLS 1.2 ECDHE+GCM (fast, ~100ms handshake, widely supported)
"ECDHE-RSA-AES256-GCM-SHA384:"
"ECDHE-RSA-AES128-GCM-SHA256:"
"ECDHE-ECDSA-AES256-GCM-SHA384:"
"ECDHE-ECDSA-AES128-GCM-SHA256:"
# Priority 3: Additional modern ciphers (good balance)
- "ECDHE-RSA-CHACHA20-POLY1305:"
- "ECDHE-ECDSA-CHACHA20-POLY1305:"
+ "ECDHE-RSA-CHACHA20-POLY1305:" "ECDHE-ECDSA-CHACHA20-POLY1305:"
# Priority 4: Widely compatible fallbacks (slower but universally supported)
- "ECDHE-RSA-AES256-SHA384:" # Common fallback
- "ECDHE-RSA-AES128-SHA256:" # Very widely supported
- "AES256-GCM-SHA384:" # Non-PFS fallback (compatibility)
- "AES128-GCM-SHA256", # Last resort (maximum compatibility)
+ "ECDHE-RSA-AES256-SHA384:" # Common fallback
+ "ECDHE-RSA-AES128-SHA256:" # Very widely supported
+ "AES256-GCM-SHA384:" # Non-PFS fallback (compatibility)
+ "AES128-GCM-SHA256", # Last resort (maximum compatibility)
)
########### v2 Architecture constants for managing writing updates to the database ###########
@@ -282,7 +289,9 @@ ANTHROPIC_WEB_SEARCH_TOOL_MAX_USES = {
DEFAULT_IMAGE_ENDPOINT_MODEL = "dall-e-2"
DEFAULT_VIDEO_ENDPOINT_MODEL = "sora-2"
-DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS = int(os.getenv("DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS", 8))
+DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS = int(
+ os.getenv("DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS", 8)
+)
### DATAFORSEO CONSTANTS ###
DEFAULT_DATAFORSEO_LOCATION_CODE = int(
@@ -371,7 +380,7 @@ LITELLM_CHAT_PROVIDERS = [
"vercel_ai_gateway",
"wandb",
"ovhcloud",
- "lemonade"
+ "lemonade",
]
LITELLM_EMBEDDING_PROVIDERS_SUPPORTING_INPUT_ARRAY_OF_TOKENS = [
@@ -475,6 +484,7 @@ DEFAULT_CHAT_COMPLETION_PARAM_VALUES = {
"additional_drop_params": None,
"messages": None,
"reasoning_effort": None,
+ "verbosity": None,
"thinking": None,
"web_search_options": None,
"service_tier": None,
@@ -630,7 +640,7 @@ clarifai_models: set = set(
"clarifai/qwen.qwenLM.Qwen3-14B",
"clarifai/qwen.qwenLM.QwQ-32B-AWQ",
"clarifai/anthropic.completion.claude-3_5-haiku",
- "clarifai/anthropic.completion.claude-3_7-sonnet",
+ "clarifai/anthropic.completion.claude-3_7-sonnet",
]
)
@@ -796,28 +806,22 @@ WANDB_MODELS: set = set(
# openai models
"openai/gpt-oss-120b",
"openai/gpt-oss-20b",
-
# zai-org models
"zai-org/GLM-4.5",
-
# Qwen models
"Qwen/Qwen3-235B-A22B-Instruct-2507",
"Qwen/Qwen3-Coder-480B-A35B-Instruct",
"Qwen/Qwen3-235B-A22B-Thinking-2507",
-
# moonshotai
"moonshotai/Kimi-K2-Instruct",
-
# meta models
"meta-llama/Llama-3.1-8B-Instruct",
"meta-llama/Llama-3.3-70B-Instruct",
"meta-llama/Llama-4-Scout-17B-16E-Instruct",
-
# deepseek-ai
"deepseek-ai/DeepSeek-V3.1",
"deepseek-ai/DeepSeek-R1-0528",
"deepseek-ai/DeepSeek-V3-0324",
-
# microsoft
"microsoft/Phi-4-mini-instruct",
]
@@ -1031,13 +1035,17 @@ LITELLM_INTERNAL_JOBS_SERVICE_ACCOUNT_NAME = "litellm_internal_jobs"
# Key Rotation Constants
LITELLM_KEY_ROTATION_ENABLED = os.getenv("LITELLM_KEY_ROTATION_ENABLED", "false")
-LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS = int(os.getenv("LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS", 86400)) # 24 hours default
+LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS = int(
+ os.getenv("LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS", 86400)
+) # 24 hours default
UI_SESSION_TOKEN_TEAM_ID = "litellm-dashboard"
LITELLM_PROXY_ADMIN_NAME = "default_user_id"
########################### CLI SSO AUTHENTICATION CONSTANTS ###########################
LITELLM_CLI_SOURCE_IDENTIFIER = "litellm-cli"
LITELLM_CLI_SESSION_TOKEN_PREFIX = "litellm-session-token"
+CLI_SSO_SESSION_CACHE_KEY_PREFIX = "cli_sso_session"
+CLI_JWT_TOKEN_NAME = "cli-jwt-token"
########################### DB CRON JOB NAMES ###########################
DB_SPEND_UPDATE_JOB_NAME = "db_spend_update_job"
@@ -1059,14 +1067,28 @@ PROXY_BATCH_POLLING_INTERVAL = int(os.getenv("PROXY_BATCH_POLLING_INTERVAL", 360
PROXY_BUDGET_RESCHEDULER_MAX_TIME = int(
os.getenv("PROXY_BUDGET_RESCHEDULER_MAX_TIME", 605)
)
-PROXY_BATCH_WRITE_AT = int(os.getenv("PROXY_BATCH_WRITE_AT", 10)) # in seconds, increased from 10
+PROXY_BATCH_WRITE_AT = int(
+ os.getenv("PROXY_BATCH_WRITE_AT", 10)
+) # in seconds, increased from 10
# APScheduler Configuration - MEMORY LEAK FIX
# These settings prevent memory leaks in APScheduler's normalize() and _apply_jitter() functions
-APSCHEDULER_COALESCE = os.getenv("APSCHEDULER_COALESCE", "True").lower() in ["true", "1"] # collapse many missed runs into one
-APSCHEDULER_MISFIRE_GRACE_TIME = int(os.getenv("APSCHEDULER_MISFIRE_GRACE_TIME", 3600)) # ignore runs older than 1 hour (was 120)
-APSCHEDULER_MAX_INSTANCES = int(os.getenv("APSCHEDULER_MAX_INSTANCES", 1)) # prevent concurrent job instances
-APSCHEDULER_REPLACE_EXISTING = os.getenv("APSCHEDULER_REPLACE_EXISTING", "True").lower() in ["true", "1"] # always replace existing jobs
+APSCHEDULER_COALESCE = os.getenv("APSCHEDULER_COALESCE", "True").lower() in [
+ "true",
+ "1",
+] # collapse many missed runs into one
+APSCHEDULER_MISFIRE_GRACE_TIME = int(
+ os.getenv("APSCHEDULER_MISFIRE_GRACE_TIME", 3600)
+) # ignore runs older than 1 hour (was 120)
+APSCHEDULER_MAX_INSTANCES = int(
+ os.getenv("APSCHEDULER_MAX_INSTANCES", 1)
+) # prevent concurrent job instances
+APSCHEDULER_REPLACE_EXISTING = os.getenv(
+ "APSCHEDULER_REPLACE_EXISTING", "True"
+).lower() in [
+ "true",
+ "1",
+] # always replace existing jobs
DEFAULT_HEALTH_CHECK_INTERVAL = int(
os.getenv("DEFAULT_HEALTH_CHECK_INTERVAL", 300)
@@ -1096,6 +1118,8 @@ SECRET_MANAGER_REFRESH_INTERVAL = int(
)
LITELLM_SETTINGS_SAFE_DB_OVERRIDES = [
"default_internal_user_params",
+ "public_mcp_servers",
+ "public_agent_groups",
"public_model_groups",
"public_model_groups_links",
]
diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index d1c7ede6552..0f5195e31af 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -133,6 +133,25 @@ def _cost_per_token_custom_pricing_helper(
return None
+def _transcription_usage_has_token_details(
+ usage_block: Optional[Usage],
+) -> bool:
+ if usage_block is None:
+ return False
+
+ prompt_tokens_val = getattr(usage_block, "prompt_tokens", 0) or 0
+ completion_tokens_val = getattr(usage_block, "completion_tokens", 0) or 0
+ prompt_details = getattr(usage_block, "prompt_tokens_details", None)
+
+ if prompt_details is not None:
+ audio_token_count = getattr(prompt_details, "audio_tokens", 0) or 0
+ text_token_count = getattr(prompt_details, "text_tokens", 0) or 0
+ if audio_token_count > 0 or text_token_count > 0:
+ return True
+
+ return (prompt_tokens_val > 0) or (completion_tokens_val > 0)
+
+
def cost_per_token( # noqa: PLR0915
model: str = "",
prompt_tokens: int = 0,
@@ -324,19 +343,18 @@ def cost_per_token( # noqa: PLR0915
usage=usage_block, model=model, custom_llm_provider=custom_llm_provider
)
elif call_type == "atranscription" or call_type == "transcription":
-
- if model == "gpt-4o-mini-transcribe":
+ if _transcription_usage_has_token_details(usage_block):
return openai_cost_per_token(
- model=model,
+ model=model_without_prefix,
usage=usage_block,
service_tier=service_tier,
)
- else:
- return openai_cost_per_second(
- model=model,
- custom_llm_provider=custom_llm_provider,
- duration=audio_transcription_file_duration,
- )
+
+ return openai_cost_per_second(
+ model=model_without_prefix,
+ custom_llm_provider=custom_llm_provider,
+ duration=audio_transcription_file_duration,
+ )
elif call_type == "search" or call_type == "asearch":
# Search providers use per-query pricing
from litellm.search import search_provider_cost_per_query
diff --git a/litellm/experimental_mcp_client/client.py b/litellm/experimental_mcp_client/client.py
index 6aa671a5011..943cc6b2d53 100644
--- a/litellm/experimental_mcp_client/client.py
+++ b/litellm/experimental_mcp_client/client.py
@@ -5,17 +5,24 @@ LiteLLM Proxy uses this MCP Client to connnect to other MCP servers.
import asyncio
import base64
from datetime import timedelta
-from typing import Callable, Dict, List, Optional, Union
+from typing import Awaitable, Callable, Dict, List, Optional, TypeVar, Union
import httpx
-from mcp import ClientSession, StdioServerParameters
+from mcp import ClientSession, ReadResourceResult, Resource, StdioServerParameters
from mcp.client.sse import sse_client
from mcp.client.stdio import stdio_client
from mcp.client.streamable_http import streamablehttp_client
-from mcp.types import CallToolRequestParams as MCPCallToolRequestParams
+from mcp.types import (
+ CallToolRequestParams as MCPCallToolRequestParams,
+ GetPromptRequestParams,
+ GetPromptResult,
+ Prompt,
+ ResourceTemplate,
+)
from mcp.types import CallToolResult as MCPCallToolResult
from mcp.types import TextContent
from mcp.types import Tool as MCPTool
+from pydantic import AnyUrl
from litellm._logging import verbose_logger
from litellm.llms.custom_httpx.http_handler import get_ssl_configuration
@@ -34,6 +41,9 @@ def to_basic_auth(auth_value: str) -> str:
return base64.b64encode(auth_value.encode("utf-8")).decode()
+TSessionResult = TypeVar("TSessionResult")
+
+
class MCPClient:
"""
MCP Client supporting:
@@ -58,12 +68,6 @@ class MCPClient:
self.auth_type: MCPAuthType = auth_type
self.timeout: float = timeout
self._mcp_auth_value: Optional[Union[str, Dict[str, str]]] = None
- self._session: Optional[ClientSession] = None
- self._context = None
- self._transport_ctx = None
- self._transport = None
- self._session_ctx = None
- self._task: Optional[asyncio.Task] = None
self.stdio_config: Optional[MCPStdioConfig] = stdio_config
self.extra_headers: Optional[Dict[str, str]] = extra_headers
self.ssl_verify: Optional[VerifyTypes] = ssl_verify
@@ -71,33 +75,14 @@ class MCPClient:
if auth_value:
self.update_auth_value(auth_value)
- async def __aenter__(self):
- """
- Enable async context manager support.
- Initializes the transport and session.
- """
- try:
- await self.connect()
- return self
- except Exception:
- await self.disconnect()
- raise
-
- async def connect(self):
- """Initialize the transport and session."""
- if self._session:
- verbose_logger.debug(
- f"MCP client already connected to {self.server_url or 'stdio'}"
- )
- return # Already connected
-
- verbose_logger.info(
- f"MCP client connecting to {self.server_url or 'stdio'} via {self.transport_type}"
- )
+ async def run_with_session(
+ self, operation: Callable[[ClientSession], Awaitable[TSessionResult]]
+ ) -> TSessionResult:
+ """Open a session, run the provided coroutine, and clean up."""
+ transport_ctx = None
try:
if self.transport_type == MCPTransport.stdio:
- # For stdio transport, use stdio_client with command-line parameters
if not self.stdio_config:
raise ValueError("stdio_config is required for stdio transport")
@@ -106,117 +91,43 @@ class MCPClient:
args=self.stdio_config.get("args", []),
env=self.stdio_config.get("env", {}),
)
-
- self._transport_ctx = stdio_client(server_params)
- self._transport = await self._transport_ctx.__aenter__()
- self._session_ctx = ClientSession(
- self._transport[0], self._transport[1]
- )
- self._session = await self._session_ctx.__aenter__()
- await self._session.initialize()
- verbose_logger.info(
- f"MCP client successfully connected via stdio: {self.stdio_config.get('command', '')}"
- )
+ transport_ctx = stdio_client(server_params)
elif self.transport_type == MCPTransport.sse:
headers = self._get_auth_headers()
httpx_client_factory = self._create_httpx_client_factory()
- self._transport_ctx = sse_client(
+ transport_ctx = sse_client(
url=self.server_url,
timeout=self.timeout,
headers=headers,
httpx_client_factory=httpx_client_factory,
)
- self._transport = await self._transport_ctx.__aenter__()
- self._session_ctx = ClientSession(
- self._transport[0], self._transport[1]
- )
- self._session = await self._session_ctx.__aenter__()
- await self._session.initialize()
- verbose_logger.info(
- f"MCP client successfully connected via SSE to {self.server_url}"
- )
- else: # http
+ else:
headers = self._get_auth_headers()
httpx_client_factory = self._create_httpx_client_factory()
verbose_logger.debug(
"litellm headers for streamablehttp_client: %s", headers
)
- self._transport_ctx = streamablehttp_client(
+ transport_ctx = streamablehttp_client(
url=self.server_url,
timeout=timedelta(seconds=self.timeout),
headers=headers,
httpx_client_factory=httpx_client_factory,
)
- self._transport = await self._transport_ctx.__aenter__()
- self._session_ctx = ClientSession(
- self._transport[0], self._transport[1]
- )
- self._session = await self._session_ctx.__aenter__()
- await self._session.initialize()
- verbose_logger.info(
- f"MCP client successfully connected via HTTP to {self.server_url}"
- )
- except ValueError as e:
- # Re-raise ValueError exceptions (like missing stdio_config)
- verbose_logger.warning(f"MCP client connection failed: {str(e)}")
- await self.disconnect()
+
+ if transport_ctx is None:
+ raise RuntimeError("Failed to create transport context")
+
+ async with transport_ctx as transport:
+ read_stream, write_stream = transport[0], transport[1]
+ session_ctx = ClientSession(read_stream, write_stream)
+ async with session_ctx as session:
+ await session.initialize()
+ return await operation(session)
+ except Exception:
+ verbose_logger.warning(
+ "MCP client run_with_session failed for %s", self.server_url or "stdio"
+ )
raise
- except Exception as e:
- verbose_logger.warning(f"MCP client connection failed: {str(e)}")
- await self.disconnect()
- # Don't raise other exceptions, let the calling code handle it gracefully
- # This allows the server manager to continue with other servers
- # Instead of raising, we'll let the calling code handle the failure
- pass
-
- async def __aexit__(self, exc_type, exc_val, exc_tb):
- """Cleanup when exiting context manager."""
- await self.disconnect()
-
- async def disconnect(self):
- """Clean up session and connections."""
- verbose_logger.info(
- f"MCP client disconnecting from {self.server_url or 'stdio'}"
- )
-
- if self._task and not self._task.done():
- verbose_logger.debug("MCP client cancelling background task")
- self._task.cancel()
- try:
- await self._task
- except asyncio.CancelledError:
- pass
-
- if self._session:
- try:
- verbose_logger.debug("MCP client closing session")
- await self._session_ctx.__aexit__(None, None, None) # type: ignore
- except Exception as e:
- verbose_logger.debug(
- f"Error closing MCP session: {type(e).__name__}: {str(e)}"
- )
- pass
- self._session = None
- self._session_ctx = None
-
- if self._transport_ctx:
- try:
- verbose_logger.debug("MCP client closing transport")
- await self._transport_ctx.__aexit__(None, None, None)
- except Exception as e:
- verbose_logger.debug(
- f"Error closing MCP transport: {type(e).__name__}: {str(e)}"
- )
- pass
- self._transport_ctx = None
- self._transport = None
-
- if self._context:
- try:
- await self._context.__aexit__(None, None, None) # type: ignore
- except Exception:
- pass
- self._context = None
def update_auth_value(self, mcp_auth_value: Union[str, Dict[str, str]]):
"""
@@ -294,24 +205,11 @@ class MCPClient:
f"MCP client listing tools from {self.server_url or 'stdio'}"
)
- if not self._session:
- verbose_logger.debug("MCP client session not found, attempting to connect")
- try:
- await self.connect()
- except Exception as e:
- verbose_logger.error(
- f"MCP client connection failed during list_tools: {type(e).__name__}: {str(e)}"
- )
- return []
-
- if self._session is None:
- verbose_logger.error(
- "MCP client session is not initialized after connection attempt"
- )
- return []
+ async def _list_tools_operation(session: ClientSession):
+ return await session.list_tools()
try:
- result = await self._session.list_tools()
+ result = await self.run_with_session(_list_tools_operation)
tool_count = len(result.tools)
tool_names = [tool.name for tool in result.tools]
verbose_logger.info(
@@ -320,11 +218,10 @@ class MCPClient:
return result.tools
except asyncio.CancelledError:
verbose_logger.warning("MCP client list_tools was cancelled")
- await self.disconnect()
raise
except Exception as e:
error_type = type(e).__name__
- verbose_logger.error(
+ verbose_logger.exception(
f"MCP client list_tools failed - "
f"Error Type: {error_type}, "
f"Error: {str(e)}, "
@@ -339,7 +236,6 @@ class MCPClient:
"the MCP server may have crashed, disconnected, or timed out"
)
- await self.disconnect()
# Return empty list instead of raising to allow graceful degradation
return []
@@ -353,55 +249,21 @@ class MCPClient:
f"MCP client calling tool '{call_tool_request_params.name}' with arguments: {call_tool_request_params.arguments}"
)
- if not self._session:
- verbose_logger.warning(
- "MCP client session not found, attempting to connect"
- )
- try:
- await self.connect()
- except Exception as e:
- verbose_logger.error(
- f"MCP client connection failed before tool call: {type(e).__name__}: {str(e)}"
- )
- return MCPCallToolResult(
- content=[TextContent(type="text", text=f"{str(e)}")], isError=True
- )
-
- if self._session is None:
- verbose_logger.error(
- "MCP client session is not initialized after connection attempt"
- )
- return MCPCallToolResult(
- content=[
- TextContent(
- type="text", text="MCP client session is not initialized"
- )
- ],
- isError=True,
- )
-
- # Check session and transport state before calling tool
- verbose_logger.debug(
- f"MCP client state before tool call - "
- f"session: {'active' if self._session else 'none'}, "
- f"transport: {'active' if self._transport else 'none'}, "
- f"session_ctx: {'active' if self._session_ctx else 'none'}, "
- f"transport_ctx: {'active' if self._transport_ctx else 'none'}"
- )
-
- try:
+ async def _call_tool_operation(session: ClientSession):
verbose_logger.debug("MCP client sending tool call to session")
- tool_result = await self._session.call_tool(
+ return await session.call_tool(
name=call_tool_request_params.name,
arguments=call_tool_request_params.arguments,
)
+
+ try:
+ tool_result = await self.run_with_session(_call_tool_operation)
verbose_logger.info(
f"MCP client tool call '{call_tool_request_params.name}' completed successfully"
)
return tool_result
except asyncio.CancelledError:
verbose_logger.warning("MCP client tool call was cancelled")
- await self.disconnect()
raise
except Exception as e:
import traceback
@@ -424,11 +286,9 @@ class MCPClient:
if "BrokenResourceError" in error_type or "Broken" in error_type:
verbose_logger.error(
"MCP client detected broken connection/stream - "
- "the MCP server may have crashed, disconnected, or timed out. "
- "Session and transport will be disconnected."
+ "the MCP server may have crashed, disconnected, or timed out."
)
- await self.disconnect()
# Return a default error result instead of raising
return MCPCallToolResult(
content=[
@@ -436,3 +296,218 @@ class MCPClient:
], # Empty content for error case
isError=True,
)
+
+ async def list_prompts(self) -> List[Prompt]:
+ """List available prompts from the server."""
+ verbose_logger.debug(
+ f"MCP client listing tools from {self.server_url or 'stdio'}"
+ )
+
+ async def _list_prompts_operation(session: ClientSession):
+ return await session.list_prompts()
+
+ try:
+ result = await self.run_with_session(_list_prompts_operation)
+ prompt_count = len(result.prompts)
+ prompt_names = [prompt.name for prompt in result.prompts]
+ verbose_logger.info(
+ f"MCP client listed {prompt_count} tools from {self.server_url or 'stdio'}: {prompt_names}"
+ )
+ return result.prompts
+ except asyncio.CancelledError:
+ verbose_logger.warning("MCP client list_prompts was cancelled")
+ raise
+ except Exception as e:
+ error_type = type(e).__name__
+ verbose_logger.error(
+ f"MCP client list_prompts failed - "
+ f"Error Type: {error_type}, "
+ f"Error: {str(e)}, "
+ f"Server: {self.server_url or 'stdio'}, "
+ f"Transport: {self.transport_type}"
+ )
+
+ # Check if it's a stream/connection error
+ if "BrokenResourceError" in error_type or "Broken" in error_type:
+ verbose_logger.error(
+ "MCP client detected broken connection/stream during list_tools - "
+ "the MCP server may have crashed, disconnected, or timed out"
+ )
+
+ # Return empty list instead of raising to allow graceful degradation
+ return []
+
+ async def get_prompt(
+ self, get_prompt_request_params: GetPromptRequestParams
+ ) -> GetPromptResult:
+ """Fetch a prompt definition from the MCP server."""
+ verbose_logger.info(
+ f"MCP client fetching prompt '{get_prompt_request_params.name}' with arguments: {get_prompt_request_params.arguments}"
+ )
+
+ async def _get_prompt_operation(session: ClientSession):
+ verbose_logger.debug("MCP client sending get_prompt request to session")
+ return await session.get_prompt(
+ name=get_prompt_request_params.name,
+ arguments=get_prompt_request_params.arguments,
+ )
+
+ try:
+ get_prompt_result = await self.run_with_session(_get_prompt_operation)
+ verbose_logger.info(
+ f"MCP client get_prompt '{get_prompt_request_params.name}' completed successfully"
+ )
+ return get_prompt_result
+ except asyncio.CancelledError:
+ verbose_logger.warning("MCP client get_prompt was cancelled")
+ raise
+ except Exception as e:
+ import traceback
+
+ error_trace = traceback.format_exc()
+ verbose_logger.debug(f"MCP client get_prompt traceback:\n{error_trace}")
+
+ # Log detailed error information
+ error_type = type(e).__name__
+ verbose_logger.error(
+ f"MCP client get_prompt failed - "
+ f"Error Type: {error_type}, "
+ f"Error: {str(e)}, "
+ f"Prompt: {get_prompt_request_params.name}, "
+ f"Server: {self.server_url or 'stdio'}, "
+ f"Transport: {self.transport_type}"
+ )
+
+ # Check if it's a stream/connection error
+ if "BrokenResourceError" in error_type or "Broken" in error_type:
+ verbose_logger.error(
+ "MCP client detected broken connection/stream during get_prompt - "
+ "the MCP server may have crashed, disconnected, or timed out."
+ )
+
+ raise
+
+ async def list_resources(self) -> list[Resource]:
+ """List available resources from the server."""
+ verbose_logger.debug(
+ f"MCP client listing resources from {self.server_url or 'stdio'}"
+ )
+
+ async def _list_resources_operation(session: ClientSession):
+ return await session.list_resources()
+
+ try:
+ result = await self.run_with_session(_list_resources_operation)
+ resource_count = len(result.resources)
+ resource_names = [resource.name for resource in result.resources]
+ verbose_logger.info(
+ f"MCP client listed {resource_count} resources from {self.server_url or 'stdio'}: {resource_names}"
+ )
+ return result.resources
+ except asyncio.CancelledError:
+ verbose_logger.warning("MCP client list_resources was cancelled")
+ raise
+ except Exception as e:
+ error_type = type(e).__name__
+ verbose_logger.error(
+ f"MCP client list_resources failed - "
+ f"Error Type: {error_type}, "
+ f"Error: {str(e)}, "
+ f"Server: {self.server_url or 'stdio'}, "
+ f"Transport: {self.transport_type}"
+ )
+
+ # Check if it's a stream/connection error
+ if "BrokenResourceError" in error_type or "Broken" in error_type:
+ verbose_logger.error(
+ "MCP client detected broken connection/stream during list_resources - "
+ "the MCP server may have crashed, disconnected, or timed out"
+ )
+
+ # Return empty list instead of raising to allow graceful degradation
+ return []
+
+ async def list_resource_templates(self) -> list[ResourceTemplate]:
+ """List available resource templates from the server."""
+ verbose_logger.debug(
+ f"MCP client listing resource templates from {self.server_url or 'stdio'}"
+ )
+
+ async def _list_resource_templates_operation(session: ClientSession):
+ return await session.list_resource_templates()
+
+ try:
+ result = await self.run_with_session(_list_resource_templates_operation)
+ resource_template_count = len(result.resourceTemplates)
+ resource_template_names = [
+ resourceTemplate.name for resourceTemplate in result.resourceTemplates
+ ]
+ verbose_logger.info(
+ f"MCP client listed {resource_template_count} resource templates from {self.server_url or 'stdio'}: {resource_template_names}"
+ )
+ return result.resourceTemplates
+ except asyncio.CancelledError:
+ verbose_logger.warning("MCP client list_resource_templates was cancelled")
+ raise
+ except Exception as e:
+ error_type = type(e).__name__
+ verbose_logger.error(
+ f"MCP client list_resource_templates failed - "
+ f"Error Type: {error_type}, "
+ f"Error: {str(e)}, "
+ f"Server: {self.server_url or 'stdio'}, "
+ f"Transport: {self.transport_type}"
+ )
+
+ # Check if it's a stream/connection error
+ if "BrokenResourceError" in error_type or "Broken" in error_type:
+ verbose_logger.error(
+ "MCP client detected broken connection/stream during list_resource_templates - "
+ "the MCP server may have crashed, disconnected, or timed out"
+ )
+
+ # Return empty list instead of raising to allow graceful degradation
+ return []
+
+ async def read_resource(self, url: AnyUrl) -> ReadResourceResult:
+ """Fetch resource contents from the MCP server."""
+ verbose_logger.info(f"MCP client fetching resource '{url}'")
+
+ async def _read_resource_operation(session: ClientSession):
+ verbose_logger.debug("MCP client sending read_resource request to session")
+ return await session.read_resource(url)
+
+ try:
+ read_resource_result = await self.run_with_session(_read_resource_operation)
+ verbose_logger.info(
+ f"MCP client read_resource '{url}' completed successfully"
+ )
+ return read_resource_result
+ except asyncio.CancelledError:
+ verbose_logger.warning("MCP client read_resource was cancelled")
+ raise
+ except Exception as e:
+ import traceback
+
+ error_trace = traceback.format_exc()
+ verbose_logger.debug(f"MCP client read_resource traceback:\n{error_trace}")
+
+ # Log detailed error information
+ error_type = type(e).__name__
+ verbose_logger.error(
+ f"MCP client read_resource failed - "
+ f"Error Type: {error_type}, "
+ f"Error: {str(e)}, "
+ f"Url: {url}, "
+ f"Server: {self.server_url or 'stdio'}, "
+ f"Transport: {self.transport_type}"
+ )
+
+ # Check if it's a stream/connection error
+ if "BrokenResourceError" in error_type or "Broken" in error_type:
+ verbose_logger.error(
+ "MCP client detected broken connection/stream during read_resource - "
+ "the MCP server may have crashed, disconnected, or timed out."
+ )
+
+ raise
diff --git a/litellm/files/main.py b/litellm/files/main.py
index 9c85fa10565..535772fa42c 100644
--- a/litellm/files/main.py
+++ b/litellm/files/main.py
@@ -95,7 +95,9 @@ async def acreate_file(
def create_file(
file: FileTypes,
purpose: Literal["assistants", "batch", "fine-tune"],
- custom_llm_provider: Optional[Literal["openai", "azure", "vertex_ai", "bedrock"]] = None,
+ custom_llm_provider: Optional[
+ Literal["openai", "azure", "vertex_ai", "bedrock"]
+ ] = None,
extra_headers: Optional[Dict[str, str]] = None,
extra_body: Optional[Dict[str, str]] = None,
**kwargs,
@@ -155,10 +157,12 @@ def create_file(
api_key=optional_params.api_key,
logging_obj=logging_obj,
_is_async=_is_async,
- client=client
- if client is not None
- and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
- else None,
+ client=(
+ client
+ if client is not None
+ and isinstance(client, (HTTPHandler, AsyncHTTPHandler))
+ else None
+ ),
timeout=timeout,
)
elif custom_llm_provider == "openai":
@@ -441,12 +445,14 @@ async def afile_delete(
"""
try:
loop = asyncio.get_event_loop()
+ model = kwargs.pop("model", None)
kwargs["is_async"] = True
# Use a partial function to pass your keyword arguments
func = partial(
file_delete,
file_id,
+ model,
custom_llm_provider,
extra_headers,
extra_body,
@@ -470,7 +476,8 @@ async def afile_delete(
@client
def file_delete(
file_id: str,
- custom_llm_provider: Literal["openai", "azure"] = "openai",
+ model: Optional[str] = None,
+ custom_llm_provider: Union[Literal["openai", "azure"], str] = "openai",
extra_headers: Optional[Dict[str, str]] = None,
extra_body: Optional[Dict[str, str]] = None,
**kwargs,
@@ -481,6 +488,13 @@ def file_delete(
LiteLLM Equivalent of DELETE https://api.openai.com/v1/files
"""
try:
+ try:
+ if model is not None:
+ _, custom_llm_provider, _, _ = get_llm_provider(
+ model, custom_llm_provider
+ )
+ except Exception:
+ pass
optional_params = GenericLiteLLMParams(**kwargs)
litellm_params_dict = get_litellm_params(**kwargs)
### TIMEOUT LOGIC ###
@@ -566,7 +580,7 @@ def file_delete(
)
else:
raise litellm.exceptions.BadRequestError(
- message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
+ message="LiteLLM doesn't support {} for 'delete_batch'. Only 'openai' is supported.".format(
custom_llm_provider
),
model="n/a",
diff --git a/litellm/integrations/arize/_utils.py b/litellm/integrations/arize/_utils.py
index 10597d6e713..c9a1531b5d4 100644
--- a/litellm/integrations/arize/_utils.py
+++ b/litellm/integrations/arize/_utils.py
@@ -208,7 +208,10 @@ def set_attributes(
)
try:
+ # Remove secret_fields to prevent leaking sensitive data (e.g., authorization headers)
optional_params = kwargs.get("optional_params", {})
+ if isinstance(optional_params, dict):
+ optional_params.pop("secret_fields", None)
litellm_params = kwargs.get("litellm_params", {})
standard_logging_payload: Optional[StandardLoggingPayload] = kwargs.get(
"standard_logging_object"
diff --git a/litellm/integrations/callback_configs.json b/litellm/integrations/callback_configs.json
new file mode 100644
index 00000000000..d8a96e71769
--- /dev/null
+++ b/litellm/integrations/callback_configs.json
@@ -0,0 +1,404 @@
+[
+ {
+ "id": "arize",
+ "displayName": "Arize",
+ "logo": "arize.png",
+ "supports_key_team_logging": true,
+ "dynamic_params": {
+ "arize_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "Arize API key for authentication",
+ "required": true
+ },
+ "arize_space_key": {
+ "type": "password",
+ "ui_name": "Space Key",
+ "description": "Arize Space key to identify your workspace",
+ "required": true
+ }
+ },
+ "description": "Arize Logging Integration"
+ },
+ {
+ "id": "braintrust",
+ "displayName": "Braintrust",
+ "logo": "braintrust.png",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "braintrust_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "Braintrust API key for authentication",
+ "required": true
+ },
+ "braintrust_project_name": {
+ "type": "text",
+ "ui_name": "Project Name",
+ "description": "Name of the Braintrust project to log to",
+ "required": true
+ }
+ },
+ "description": "Braintrust Logging Integration"
+ },
+ {
+ "id": "custom_callback_api",
+ "displayName": "Custom Callback API",
+ "logo": "custom.svg",
+ "supports_key_team_logging": true,
+ "dynamic_params": {
+ "custom_callback_api_url": {
+ "type": "text",
+ "ui_name": "Callback URL",
+ "description": "Your custom webhook/API endpoint URL to receive logs",
+ "required": true
+ },
+ "custom_callback_api_headers": {
+ "type": "text",
+ "ui_name": "Headers (JSON)",
+ "description": "Custom HTTP headers as JSON string (e.g., {\"Authorization\": \"Bearer token\"})",
+ "required": false
+ }
+ },
+ "description": "Custom Callback API Logging Integration"
+ },
+ {
+ "id": "datadog",
+ "displayName": "Datadog",
+ "logo": "datadog.png",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "dd_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "Datadog API key for authentication",
+ "required": true
+ },
+ "dd_site": {
+ "type": "text",
+ "ui_name": "Site",
+ "description": "Datadog site URL (e.g., us5.datadoghq.com)",
+ "required": true
+ }
+ },
+ "description": "Datadog Logging Integration"
+ },
+ {
+ "id": "lago",
+ "displayName": "Lago",
+ "logo": "lago.svg",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "lago_api_url": {
+ "type": "text",
+ "ui_name": "API URL",
+ "description": "Lago API base URL",
+ "required": true
+ },
+ "lago_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "Lago API key for authentication",
+ "required": true
+ }
+ },
+ "description": "Lago Billing Logging Integration"
+ },
+ {
+ "id": "langfuse",
+ "displayName": "Langfuse",
+ "logo": "langfuse.png",
+ "supports_key_team_logging": true,
+ "dynamic_params": {
+ "langfuse_public_key": {
+ "type": "text",
+ "ui_name": "Public Key",
+ "description": "Langfuse public key",
+ "required": true
+ },
+ "langfuse_secret_key": {
+ "type": "password",
+ "ui_name": "Secret Key",
+ "description": "Langfuse secret key for authentication",
+ "required": true
+ },
+ "langfuse_host": {
+ "type": "text",
+ "ui_name": "Host URL",
+ "description": "Langfuse host URL (default: https://cloud.langfuse.com)",
+ "required": false
+ }
+ },
+ "description": "Langfuse v2 Logging Integration"
+ },
+ {
+ "id": "langfuse_otel",
+ "displayName": "Langfuse OTEL",
+ "logo": "langfuse.png",
+ "supports_key_team_logging": true,
+ "dynamic_params": {
+ "langfuse_public_key": {
+ "type": "text",
+ "ui_name": "Public Key",
+ "description": "Langfuse public key",
+ "required": true
+ },
+ "langfuse_secret_key": {
+ "type": "password",
+ "ui_name": "Secret Key",
+ "description": "Langfuse secret key for authentication",
+ "required": true
+ },
+ "langfuse_host": {
+ "type": "text",
+ "ui_name": "Host URL",
+ "description": "Langfuse host URL (default: https://cloud.langfuse.com)",
+ "required": false
+ }
+ },
+ "description": "Langfuse v3 OTEL Logging Integration"
+ },
+ {
+ "id": "langsmith",
+ "displayName": "LangSmith",
+ "logo": "langsmith.png",
+ "supports_key_team_logging": true,
+ "dynamic_params": {
+ "langsmith_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "LangSmith API key for authentication",
+ "required": true
+ },
+ "langsmith_project": {
+ "type": "text",
+ "ui_name": "Project Name",
+ "description": "LangSmith project name (default: litellm-completion)",
+ "required": false
+ },
+ "langsmith_base_url": {
+ "type": "text",
+ "ui_name": "Base URL",
+ "description": "LangSmith base URL (default: https://api.smith.langchain.com)",
+ "required": false
+ },
+ "langsmith_sampling_rate": {
+ "type": "number",
+ "ui_name": "Sampling Rate",
+ "description": "Sampling rate for logging (0.0 to 1.0, default: 1.0)",
+ "required": false
+ }
+ },
+ "description": "Langsmith Logging Integration"
+ },
+ {
+ "id": "openmeter",
+ "displayName": "OpenMeter",
+ "logo": "openmeter.png",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "openmeter_api_key": {
+ "type": "password",
+ "ui_name": "API Key",
+ "description": "OpenMeter API key for authentication",
+ "required": true
+ },
+ "openmeter_base_url": {
+ "type": "text",
+ "ui_name": "Base URL",
+ "description": "OpenMeter base URL (default: https://openmeter.cloud)",
+ "required": false
+ }
+ },
+ "description": "OpenMeter Logging Integration"
+ },
+ {
+ "id": "otel",
+ "displayName": "Open Telemetry",
+ "logo": "otel.png",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "otel_endpoint": {
+ "type": "text",
+ "ui_name": "Endpoint URL",
+ "description": "OpenTelemetry collector endpoint URL",
+ "required": true
+ },
+ "otel_headers": {
+ "type": "text",
+ "ui_name": "Headers",
+ "description": "Headers for OTEL exporter (e.g., x-honeycomb-team=YOUR_API_KEY)",
+ "required": false
+ }
+ },
+ "description": "OpenTelemetry Logging Integration"
+ },
+ {
+ "id": "s3",
+ "displayName": "S3",
+ "logo": "aws.svg",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "s3_bucket_name": {
+ "type": "text",
+ "ui_name": "Bucket Name",
+ "description": "AWS S3 bucket name to store logs",
+ "required": true
+ },
+ "s3_region_name": {
+ "type": "text",
+ "ui_name": "AWS Region",
+ "description": "AWS region name (e.g., us-east-1)",
+ "required": false
+ },
+ "s3_aws_access_key_id": {
+ "type": "password",
+ "ui_name": "AWS Access Key ID",
+ "description": "AWS access key ID for authentication",
+ "required": false
+ },
+ "s3_aws_secret_access_key": {
+ "type": "password",
+ "ui_name": "AWS Secret Access Key",
+ "description": "AWS secret access key for authentication",
+ "required": false
+ },
+ "s3_aws_session_token": {
+ "type": "password",
+ "ui_name": "AWS Session Token",
+ "description": "AWS session token for temporary credentials",
+ "required": false
+ },
+ "s3_endpoint_url": {
+ "type": "text",
+ "ui_name": "S3 Endpoint URL",
+ "description": "Custom S3 endpoint URL (for MinIO or custom S3-compatible services)",
+ "required": false
+ },
+ "s3_path": {
+ "type": "text",
+ "ui_name": "S3 Path Prefix",
+ "description": "Path prefix within the bucket for organizing logs",
+ "required": false
+ }
+ },
+ "description": "S3 Bucket (AWS) Logging Integration"
+ },
+ {
+ "id": "sqs",
+ "displayName": "SQS",
+ "logo": "aws.svg",
+ "supports_key_team_logging": false,
+ "dynamic_params": {
+ "sqs_queue_url": {
+ "type": "text",
+ "ui_name": "Queue URL",
+ "description": "AWS SQS Queue URL",
+ "required": true
+ },
+ "sqs_region_name": {
+ "type": "text",
+ "ui_name": "AWS Region",
+ "description": "AWS region name (e.g., us-east-1)",
+ "required": false
+ },
+ "sqs_aws_access_key_id": {
+ "type": "password",
+ "ui_name": "AWS Access Key ID",
+ "description": "AWS access key ID for authentication",
+ "required": false
+ },
+ "sqs_aws_secret_access_key": {
+ "type": "password",
+ "ui_name": "AWS Secret Access Key",
+ "description": "AWS secret access key for authentication",
+ "required": false
+ },
+ "sqs_aws_session_token": {
+ "type": "password",
+ "ui_name": "AWS Session Token",
+ "description": "AWS session token for temporary credentials",
+ "required": false
+ },
+ "sqs_aws_session_name": {
+ "type": "text",
+ "ui_name": "AWS Session Name",
+ "description": "Name for AWS session",
+ "required": false
+ },
+ "sqs_aws_profile_name": {
+ "type": "text",
+ "ui_name": "AWS Profile Name",
+ "description": "AWS profile name from credentials file",
+ "required": false
+ },
+ "sqs_aws_role_name": {
+ "type": "text",
+ "ui_name": "AWS Role Name",
+ "description": "AWS IAM role name to assume",
+ "required": false
+ },
+ "sqs_aws_web_identity_token": {
+ "type": "password",
+ "ui_name": "AWS Web Identity Token",
+ "description": "AWS web identity token for authentication",
+ "required": false
+ },
+ "sqs_aws_sts_endpoint": {
+ "type": "text",
+ "ui_name": "AWS STS Endpoint",
+ "description": "AWS STS endpoint URL",
+ "required": false
+ },
+ "sqs_endpoint_url": {
+ "type": "text",
+ "ui_name": "SQS Endpoint URL",
+ "description": "Custom SQS endpoint URL (for LocalStack or custom endpoints)",
+ "required": false
+ },
+ "sqs_api_version": {
+ "type": "text",
+ "ui_name": "API Version",
+ "description": "SQS API version",
+ "required": false
+ },
+ "sqs_use_ssl": {
+ "type": "boolean",
+ "ui_name": "Use SSL",
+ "description": "Whether to use SSL for SQS connections",
+ "required": false
+ },
+ "sqs_verify": {
+ "type": "boolean",
+ "ui_name": "Verify SSL",
+ "description": "Whether to verify SSL certificates",
+ "required": false
+ },
+ "sqs_strip_base64_files": {
+ "type": "boolean",
+ "ui_name": "Strip Base64 Files",
+ "description": "Remove base64-encoded files from logs to reduce payload size",
+ "required": false
+ },
+ "sqs_aws_use_application_level_encryption": {
+ "type": "boolean",
+ "ui_name": "Use Application-Level Encryption",
+ "description": "Enable application-level encryption for SQS messages",
+ "required": false
+ },
+ "sqs_app_encryption_key_b64": {
+ "type": "password",
+ "ui_name": "Encryption Key (Base64)",
+ "description": "Base64-encoded encryption key for application-level encryption",
+ "required": false
+ },
+ "sqs_app_encryption_aad": {
+ "type": "text",
+ "ui_name": "Encryption AAD",
+ "description": "Additional authenticated data for encryption",
+ "required": false
+ }
+ },
+ "description": "SQS Queue (AWS) Logging Integration"
+ }
+]
diff --git a/litellm/integrations/dotprompt/dotprompt_manager.py b/litellm/integrations/dotprompt/dotprompt_manager.py
index 0f0d7b938f3..7aaa6cc9628 100644
--- a/litellm/integrations/dotprompt/dotprompt_manager.py
+++ b/litellm/integrations/dotprompt/dotprompt_manager.py
@@ -108,7 +108,7 @@ class DotpromptManager(CustomPromptManagement):
Compile a .prompt file into a PromptManagementClient structure.
This method:
- 1. Loads the prompt template from the .prompt file
+ 1. Loads the prompt template from the .prompt file (with optional version)
2. Renders it with the provided variables
3. Converts the rendered text into chat messages
4. Extracts model and optional parameters from metadata
@@ -116,13 +116,22 @@ class DotpromptManager(CustomPromptManagement):
try:
- # Get the prompt template
- template = self.prompt_manager.get_prompt(prompt_id)
+ # Get the prompt template (versioned or base)
+ template = self.prompt_manager.get_prompt(
+ prompt_id=prompt_id, version=prompt_version
+ )
if template is None:
- raise ValueError(f"Prompt '{prompt_id}' not found in prompt directory")
+ version_str = f" (version {prompt_version})" if prompt_version else ""
+ raise ValueError(
+ f"Prompt '{prompt_id}'{version_str} not found in prompt directory"
+ )
- # Render the template with variables
- rendered_content = self.prompt_manager.render(prompt_id, prompt_variables)
+ # Render the template with variables (pass version for proper lookup)
+ rendered_content = self.prompt_manager.render(
+ prompt_id=prompt_id,
+ prompt_variables=prompt_variables,
+ version=prompt_version,
+ )
# Convert rendered content to chat messages
messages = self._convert_to_messages(rendered_content)
diff --git a/litellm/integrations/dotprompt/prompt_manager.py b/litellm/integrations/dotprompt/prompt_manager.py
index 9623ddab5fb..fc5a325ffe1 100644
--- a/litellm/integrations/dotprompt/prompt_manager.py
+++ b/litellm/integrations/dotprompt/prompt_manager.py
@@ -183,7 +183,10 @@ class PromptManager:
return frontmatter, template_content
def render(
- self, prompt_id: str, prompt_variables: Optional[Dict[str, Any]] = None
+ self,
+ prompt_id: str,
+ prompt_variables: Optional[Dict[str, Any]] = None,
+ version: Optional[int] = None,
) -> str:
"""
Render a prompt template with the given variables.
@@ -191,6 +194,7 @@ class PromptManager:
Args:
prompt_id: The ID of the prompt template to render
prompt_variables: Variables to substitute in the template
+ version: Optional version number. If provided, looks for {prompt_id}.v{version}
Returns:
The rendered prompt string
@@ -199,13 +203,16 @@ class PromptManager:
KeyError: If prompt_id is not found
ValueError: If template rendering fails
"""
- if prompt_id not in self.prompts:
+ # Get the template (versioned or base)
+ template = self.get_prompt(prompt_id=prompt_id, version=version)
+
+ if template is None:
available_prompts = list(self.prompts.keys())
+ version_str = f" (version {version})" if version else ""
raise KeyError(
- f"Prompt '{prompt_id}' not found. Available prompts: {available_prompts}"
+ f"Prompt '{prompt_id}'{version_str} not found. Available prompts: {available_prompts}"
)
- template = self.prompts[prompt_id]
variables = prompt_variables or {}
# Validate input variables against schema if defined
@@ -254,8 +261,26 @@ class PromptManager:
return type_mapping.get(schema_type.lower(), str) # type: ignore
- def get_prompt(self, prompt_id: str) -> Optional[PromptTemplate]:
- """Get a prompt template by ID."""
+ def get_prompt(
+ self, prompt_id: str, version: Optional[int] = None
+ ) -> Optional[PromptTemplate]:
+ """
+ Get a prompt template by ID and optional version.
+
+ Args:
+ prompt_id: The base prompt ID
+ version: Optional version number. If provided, looks for {prompt_id}.v{version}
+
+ Returns:
+ The prompt template if found, None otherwise
+ """
+ if version is not None:
+ # Try versioned prompt first: prompt_id.v{version}
+ versioned_id = f"{prompt_id}.v{version}"
+ if versioned_id in self.prompts:
+ return self.prompts[versioned_id]
+
+ # Fall back to base prompt_id
return self.prompts.get(prompt_id)
def list_prompts(self) -> List[str]:
diff --git a/litellm/integrations/langfuse/langfuse.py b/litellm/integrations/langfuse/langfuse.py
index c2a2cc77950..12eb00efa9e 100644
--- a/litellm/integrations/langfuse/langfuse.py
+++ b/litellm/integrations/langfuse/langfuse.py
@@ -228,6 +228,8 @@ class LangFuseLogger:
functions = optional_params.pop("functions", None)
tools = optional_params.pop("tools", None)
+ # Remove secret_fields to prevent leaking sensitive data (e.g., authorization headers)
+ optional_params.pop("secret_fields", None)
if functions is not None:
prompt["functions"] = functions
if tools is not None:
diff --git a/enterprise/litellm_enterprise/integrations/prometheus.py b/litellm/integrations/prometheus.py
similarity index 98%
rename from enterprise/litellm_enterprise/integrations/prometheus.py
rename to litellm/integrations/prometheus.py
index 57db14fec40..8186006f8c8 100644
--- a/enterprise/litellm_enterprise/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -41,21 +41,9 @@ class PrometheusLogger(CustomLogger):
try:
from prometheus_client import Counter, Gauge, Histogram
- from litellm.proxy.proxy_server import CommonProxyErrors, premium_user
-
# Always initialize label_filters, even for non-premium users
self.label_filters = self._parse_prometheus_config()
- if premium_user is not True:
- verbose_logger.warning(
- f"🚨🚨🚨 Prometheus Metrics is on LiteLLM Enterprise\n🚨 {CommonProxyErrors.not_premium_user.value}"
- )
- self.litellm_not_a_premium_user_metric = Counter(
- name="litellm_not_a_premium_user_metric",
- documentation=f"🚨🚨🚨 Prometheus Metrics is on LiteLLM Enterprise. 🚨 {CommonProxyErrors.not_premium_user.value}",
- )
- return
-
# Create metric factory functions
self._counter_factory = self._create_metric_factory(Counter)
self._gauge_factory = self._create_metric_factory(Gauge)
@@ -2184,9 +2172,6 @@ class PrometheusLogger(CustomLogger):
It emits the current remaining budget metrics for all Keys and Teams.
"""
- from enterprise.litellm_enterprise.integrations.prometheus import (
- PrometheusLogger,
- )
from litellm.constants import PROMETHEUS_BUDGET_METRICS_REFRESH_INTERVAL_MINUTES
from litellm.integrations.custom_logger import CustomLogger
@@ -2213,26 +2198,19 @@ class PrometheusLogger(CustomLogger):
)
@staticmethod
- def _mount_metrics_endpoint(premium_user: bool):
+ def _mount_metrics_endpoint():
"""
Mount the Prometheus metrics endpoint with optional authentication.
Args:
- premium_user (bool): Whether the user is a premium user
require_auth (bool, optional): Whether to require authentication for the metrics endpoint.
Defaults to False.
"""
from prometheus_client import make_asgi_app
from litellm._logging import verbose_proxy_logger
- from litellm.proxy._types import CommonProxyErrors
from litellm.proxy.proxy_server import app
- if premium_user is not True:
- verbose_proxy_logger.warning(
- f"Prometheus metrics are only available for premium users. {CommonProxyErrors.not_premium_user.value}"
- )
-
# Create metrics ASGI app
if "PROMETHEUS_MULTIPROC_DIR" in os.environ:
from prometheus_client import CollectorRegistry, multiprocess
diff --git a/litellm/litellm_core_utils/custom_logger_registry.py b/litellm/litellm_core_utils/custom_logger_registry.py
index 09794bf2677..80f2f195839 100644
--- a/litellm/litellm_core_utils/custom_logger_registry.py
+++ b/litellm/litellm_core_utils/custom_logger_registry.py
@@ -16,14 +16,16 @@ from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheCont
from litellm.integrations.argilla import ArgillaLogger
from litellm.integrations.azure_storage.azure_storage import AzureBlobStorageLogger
from litellm.integrations.bitbucket import BitBucketPromptManager
-from litellm.integrations.gitlab import GitLabPromptManager
from litellm.integrations.braintrust_logging import BraintrustLogger
+from litellm.integrations.cloudzero.cloudzero import CloudZeroLogger
from litellm.integrations.datadog.datadog import DataDogLogger
from litellm.integrations.datadog.datadog_llm_obs import DataDogLLMObsLogger
from litellm.integrations.deepeval import DeepEvalLogger
+from litellm.integrations.dotprompt import DotpromptManager
from litellm.integrations.galileo import GalileoObserve
from litellm.integrations.gcs_bucket.gcs_bucket import GCSBucketLogger
from litellm.integrations.gcs_pubsub.pub_sub import GcsPubSubLogger
+from litellm.integrations.gitlab import GitLabPromptManager
from litellm.integrations.humanloop import HumanloopLogger
from litellm.integrations.lago import LagoLogger
from litellm.integrations.langfuse.langfuse_prompt_management import (
@@ -36,13 +38,7 @@ from litellm.integrations.openmeter import OpenMeterLogger
from litellm.integrations.opentelemetry import OpenTelemetry
from litellm.integrations.opik.opik import OpikLogger
from litellm.integrations.posthog import PostHogLogger
-
-try:
- from litellm_enterprise.integrations.prometheus import PrometheusLogger
-except Exception:
- PrometheusLogger = None
-from litellm.integrations.cloudzero.cloudzero import CloudZeroLogger
-from litellm.integrations.dotprompt import DotpromptManager
+from litellm.integrations.prometheus import PrometheusLogger
from litellm.integrations.s3_v2 import S3Logger
from litellm.integrations.sqs import SQSLogger
from litellm.integrations.vector_store_integrations.vector_store_pre_call_hook import (
diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index fb25c5ed840..ef0ebe074d7 100644
--- a/litellm/litellm_core_utils/get_llm_provider_logic.py
+++ b/litellm/litellm_core_utils/get_llm_provider_logic.py
@@ -693,12 +693,12 @@ def _get_openai_compatible_provider_info( # noqa: PLR0915
) # type: ignore
dynamic_api_key = api_key or get_secret_str("NOVITA_API_KEY")
elif custom_llm_provider == "snowflake":
- api_base = (
- api_base
- or get_secret_str("SNOWFLAKE_API_BASE")
- or f"https://{get_secret('SNOWFLAKE_ACCOUNT_ID')}.snowflakecomputing.com/api/v2/cortex/inference:complete"
- ) # type: ignore
- dynamic_api_key = api_key or get_secret_str("SNOWFLAKE_JWT")
+ (
+ api_base,
+ dynamic_api_key,
+ ) = litellm.SnowflakeConfig()._get_openai_compatible_provider_info(
+ api_base, api_key
+ )
elif custom_llm_provider == "gradient_ai":
(
api_base,
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 41a5eed55d8..e5c52ce48ae 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -58,6 +58,7 @@ from litellm.integrations.custom_guardrail import CustomGuardrail
from litellm.integrations.custom_logger import CustomLogger
from litellm.integrations.deepeval.deepeval import DeepEvalLogger
from litellm.integrations.mlflow import MlflowLogger
+from litellm.integrations.prometheus import PrometheusLogger
from litellm.integrations.sqs import SQSLogger
from litellm.litellm_core_utils.get_litellm_params import get_litellm_params
from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import (
@@ -176,7 +177,6 @@ try:
from litellm_enterprise.enterprise_callbacks.send_emails.smtp_email import (
SMTPEmailLogger,
)
- from litellm_enterprise.integrations.prometheus import PrometheusLogger
from litellm_enterprise.litellm_core_utils.litellm_logging import (
StandardLoggingPayloadSetup as EnterpriseStandardLoggingPayloadSetup,
)
@@ -194,7 +194,6 @@ except Exception as e:
PagerDutyAlerting = CustomLogger # type: ignore
EnterpriseCallbackControls = None # type: ignore
EnterpriseStandardLoggingPayloadSetupVAR = None
- PrometheusLogger = None
_in_memory_loggers: List[Any] = []
### GLOBAL VARIABLES ###
@@ -586,7 +585,10 @@ class Logging(LiteLLMLoggingBaseClass):
custom_logger = (
prompt_management_logger
or self.get_custom_logger_for_prompt_management(
- model=model, non_default_params=non_default_params
+ model=model,
+ non_default_params=non_default_params,
+ prompt_id=prompt_id,
+ dynamic_callback_params=self.standard_callback_dynamic_params,
)
)
@@ -623,7 +625,11 @@ class Logging(LiteLLMLoggingBaseClass):
custom_logger = (
prompt_management_logger
or self.get_custom_logger_for_prompt_management(
- model=model, tools=tools, non_default_params=non_default_params
+ model=model,
+ tools=tools,
+ non_default_params=non_default_params,
+ prompt_id=prompt_id,
+ dynamic_callback_params=self.standard_callback_dynamic_params,
)
)
@@ -647,19 +653,69 @@ class Logging(LiteLLMLoggingBaseClass):
self.messages = messages
return model, messages, non_default_params
+ def _auto_detect_prompt_management_logger(
+ self,
+ prompt_id: str,
+ dynamic_callback_params: StandardCallbackDynamicParams,
+ ) -> Optional[CustomLogger]:
+ """
+ Auto-detect which prompt management system owns the given prompt_id.
+
+ This allows a user to just pass prompt_id in the completion call and it will be auto-detected which system owns this prompt.
+
+ Args:
+ prompt_id: The prompt ID to check
+ dynamic_callback_params: Dynamic callback parameters for should_run_prompt_management checks
+
+ Returns:
+ A CustomLogger instance if a matching prompt management system is found, None otherwise
+ """
+ prompt_management_loggers = (
+ litellm.logging_callback_manager.get_custom_loggers_for_type(
+ callback_type=CustomPromptManagement
+ )
+ )
+
+ for logger in prompt_management_loggers:
+ if isinstance(logger, CustomPromptManagement):
+ try:
+ if logger.should_run_prompt_management(
+ prompt_id=prompt_id,
+ dynamic_callback_params=dynamic_callback_params,
+ ):
+ self.model_call_details["prompt_integration"] = (
+ logger.__class__.__name__
+ )
+ return logger
+ except Exception:
+ # If check fails, continue to next logger
+ continue
+
+ return None
+
def get_custom_logger_for_prompt_management(
- self, model: str, non_default_params: Dict, tools: Optional[List[Dict]] = None
+ self,
+ model: str,
+ non_default_params: Dict,
+ tools: Optional[List[Dict]] = None,
+ prompt_id: Optional[str] = None,
+ dynamic_callback_params: Optional[StandardCallbackDynamicParams] = None,
) -> Optional[CustomLogger]:
"""
Get a custom logger for prompt management based on model name or available callbacks.
Args:
model: The model name to check for prompt management integration
+ non_default_params: Non-default parameters passed to the completion call
+ tools: Optional tools passed to the completion call
+ prompt_id: Optional prompt ID to auto-detect which system owns this prompt
+ dynamic_callback_params: Dynamic callback parameters for should_run_prompt_management checks
Returns:
A CustomLogger instance if one is found, None otherwise
"""
# First check if model starts with a known custom logger compatible callback
+ # This takes precedence for backward compatibility
for callback_name in litellm._known_custom_logger_compatible_callbacks:
if model.startswith(callback_name):
custom_logger = _init_custom_logger_compatible_class(
@@ -671,7 +727,16 @@ class Logging(LiteLLMLoggingBaseClass):
self.model_call_details["prompt_integration"] = model.split("/")[0]
return custom_logger
- # Then check for any registered CustomPromptManagement loggers
+ # If prompt_id is provided, try to auto-detect which system has this prompt
+ if prompt_id and dynamic_callback_params is not None:
+ auto_detected_logger = self._auto_detect_prompt_management_logger(
+ prompt_id=prompt_id,
+ dynamic_callback_params=dynamic_callback_params,
+ )
+ if auto_detected_logger is not None:
+ return auto_detected_logger
+
+ # Then check for any registered CustomPromptManagement loggers (fallback)
prompt_management_loggers = (
litellm.logging_callback_manager.get_custom_loggers_for_type(
callback_type=CustomPromptManagement
@@ -1475,33 +1540,58 @@ class Logging(LiteLLMLoggingBaseClass):
if self.model_call_details["litellm_params"]["metadata"] is None:
self.model_call_details["litellm_params"]["metadata"] = {}
self.model_call_details["litellm_params"]["metadata"]["hidden_params"] = getattr(logging_result, "_hidden_params", {}) # type: ignore
-
+
if "response_cost" in hidden_params:
self.model_call_details["response_cost"] = hidden_params["response_cost"]
else:
- self.model_call_details["response_cost"] = self._response_cost_calculator(result=logging_result)
-
- self.model_call_details["standard_logging_object"] = get_standard_logging_object_payload(
- kwargs=self.model_call_details,
- init_response_obj=logging_result,
- start_time=start_time,
- end_time=end_time,
- logging_obj=self,
- status="success",
- standard_built_in_tools_params=self.standard_built_in_tools_params,
+ self.model_call_details["response_cost"] = self._response_cost_calculator(
+ result=logging_result
+ )
+
+ self.model_call_details["standard_logging_object"] = (
+ get_standard_logging_object_payload(
+ kwargs=self.model_call_details,
+ init_response_obj=logging_result,
+ start_time=start_time,
+ end_time=end_time,
+ logging_obj=self,
+ status="success",
+ standard_built_in_tools_params=self.standard_built_in_tools_params,
+ )
)
def _transform_usage_objects(self, result):
if isinstance(result, ResponsesAPIResponse):
result = result.model_copy()
- transformed_usage = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(result.usage)
- setattr(result, "usage", transformed_usage.model_dump() if hasattr(transformed_usage, "model_dump") else dict(transformed_usage))
- if (standard_logging_payload := self.model_call_details.get("standard_logging_object")) is not None:
- standard_logging_payload["response"] = result.model_dump() if hasattr(result, "model_dump") else dict(result)
+ transformed_usage = (
+ ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(
+ result.usage
+ )
+ )
+ setattr(
+ result,
+ "usage",
+ (
+ transformed_usage.model_dump()
+ if hasattr(transformed_usage, "model_dump")
+ else dict(transformed_usage)
+ ),
+ )
+ if (
+ standard_logging_payload := self.model_call_details.get(
+ "standard_logging_object"
+ )
+ ) is not None:
+ standard_logging_payload["response"] = (
+ result.model_dump()
+ if hasattr(result, "model_dump")
+ else dict(result)
+ )
elif isinstance(result, TranscriptionResponse):
from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import (
TranscriptionUsageObjectTransformation,
)
+
result = result.model_copy()
transformed_usage = TranscriptionUsageObjectTransformation.transform_transcription_usage_object(result.usage) # type: ignore
setattr(result, "usage", transformed_usage)
@@ -1522,40 +1612,67 @@ class Logging(LiteLLMLoggingBaseClass):
end_time = datetime.datetime.now()
if self.completion_start_time is None:
self.completion_start_time = end_time
- self.model_call_details["completion_start_time"] = self.completion_start_time
-
+ self.model_call_details["completion_start_time"] = (
+ self.completion_start_time
+ )
+
self.model_call_details["log_event_type"] = "successful_api_call"
self.model_call_details["end_time"] = end_time
self.model_call_details["cache_hit"] = cache_hit
-
+
if self.call_type == CallTypes.anthropic_messages.value:
result = self._handle_anthropic_messages_response_logging(result=result)
- elif self.call_type == CallTypes.generate_content.value or self.call_type == CallTypes.agenerate_content.value:
- result = self._handle_non_streaming_google_genai_generate_content_response_logging(result=result)
-
+ elif (
+ self.call_type == CallTypes.generate_content.value
+ or self.call_type == CallTypes.agenerate_content.value
+ ):
+ result = self._handle_non_streaming_google_genai_generate_content_response_logging(
+ result=result
+ )
+
logging_result = self.normalize_logging_result(result=result)
- if standard_logging_object is None and result is not None and self.stream is not True:
- if self._is_recognized_call_type_for_logging(logging_result=logging_result):
- self._process_hidden_params_and_response_cost(logging_result=logging_result, start_time=start_time, end_time=end_time)
- elif isinstance(result, dict) or isinstance(result, list):
- self.model_call_details["standard_logging_object"] = get_standard_logging_object_payload(
- kwargs=self.model_call_details,
- init_response_obj=result,
+ if (
+ standard_logging_object is None
+ and result is not None
+ and self.stream is not True
+ ):
+ if self._is_recognized_call_type_for_logging(
+ logging_result=logging_result
+ ):
+ self._process_hidden_params_and_response_cost(
+ logging_result=logging_result,
start_time=start_time,
end_time=end_time,
- logging_obj=self,
- status="success",
- standard_built_in_tools_params=self.standard_built_in_tools_params,
+ )
+ elif isinstance(result, dict) or isinstance(result, list):
+ self.model_call_details["standard_logging_object"] = (
+ get_standard_logging_object_payload(
+ kwargs=self.model_call_details,
+ init_response_obj=result,
+ start_time=start_time,
+ end_time=end_time,
+ logging_obj=self,
+ status="success",
+ standard_built_in_tools_params=self.standard_built_in_tools_params,
+ )
)
elif standard_logging_object is not None:
- self.model_call_details["standard_logging_object"] = standard_logging_object
+ self.model_call_details["standard_logging_object"] = (
+ standard_logging_object
+ )
else:
self.model_call_details["response_cost"] = None
result = self._transform_usage_objects(result=result)
-
- if litellm.max_budget and self.stream is False and result is not None and isinstance(result, dict) and "content" in result:
+
+ if (
+ litellm.max_budget
+ and self.stream is False
+ and result is not None
+ and isinstance(result, dict)
+ and "content" in result
+ ):
time_diff = (end_time - start_time).total_seconds()
float_diff = float(time_diff)
litellm._current_cost += litellm.completion_cost(
@@ -3340,8 +3457,6 @@ def _init_custom_logger_compatible_class( # noqa: PLR0915
_in_memory_loggers.append(_literalai_logger)
return _literalai_logger # type: ignore
elif logging_integration == "prometheus":
- if PrometheusLogger is None:
- raise ValueError("PrometheusLogger is not initialized")
for callback in _in_memory_loggers:
if isinstance(callback, PrometheusLogger):
return callback # type: ignore
diff --git a/litellm/litellm_core_utils/llm_response_utils/get_formatted_prompt.py b/litellm/litellm_core_utils/llm_response_utils/get_formatted_prompt.py
index fffaad79b9e..f7406398a46 100644
--- a/litellm/litellm_core_utils/llm_response_utils/get_formatted_prompt.py
+++ b/litellm/litellm_core_utils/llm_response_utils/get_formatted_prompt.py
@@ -4,6 +4,7 @@ from typing import List, Literal
def get_formatted_prompt(
data: dict,
call_type: Literal[
+ "acompletion",
"completion",
"embedding",
"image_generation",
@@ -18,7 +19,7 @@ def get_formatted_prompt(
Returns a string.
"""
prompt = ""
- if call_type == "completion":
+ if call_type == "acompletion" or call_type == "completion":
for message in data["messages"]:
if message.get("content", None) is not None:
content = message.get("content")
diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 69e3cc43322..c50ceeabdb2 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -437,6 +437,66 @@ def update_messages_with_model_file_ids(
return messages
+def update_responses_input_with_model_file_ids(
+ input: Any,
+) -> Union[str, List[Dict[str, Any]]]:
+ """
+ Updates responses API input with provider-specific file IDs.
+ File IDs are always inside the content array, not as direct input_file items.
+
+ For managed files (unified file IDs), decodes the base64-encoded unified file ID
+ and extracts the llm_output_file_id directly.
+ """
+ from litellm.proxy.openai_files_endpoints.common_utils import (
+ _is_base64_encoded_unified_file_id,
+ convert_b64_uid_to_unified_uid,
+ )
+
+ if isinstance(input, str):
+ return input
+
+ if not isinstance(input, list):
+ return input
+
+ updated_input = []
+ for item in input:
+ if not isinstance(item, dict):
+ updated_input.append(item)
+ continue
+
+ updated_item = item.copy()
+ content = item.get("content")
+ if isinstance(content, list):
+ updated_content = []
+ for content_item in content:
+ if isinstance(content_item, dict) and content_item.get("type") == "input_file":
+ file_id = content_item.get("file_id")
+ if file_id:
+ # Check if this is a managed file ID (base64-encoded unified file ID)
+ is_unified_file_id = _is_base64_encoded_unified_file_id(file_id)
+ if is_unified_file_id:
+ unified_file_id = convert_b64_uid_to_unified_uid(file_id)
+ if "llm_output_file_id," in unified_file_id:
+ provider_file_id = unified_file_id.split("llm_output_file_id,")[1].split(";")[0]
+ else:
+ # Fallback: keep original if we can't extract
+ provider_file_id = file_id
+ updated_content_item = content_item.copy()
+ updated_content_item["file_id"] = provider_file_id
+ updated_content.append(updated_content_item)
+ else:
+ updated_content.append(content_item)
+ else:
+ updated_content.append(content_item)
+ else:
+ updated_content.append(content_item)
+ updated_item["content"] = updated_content
+
+ updated_input.append(updated_item)
+
+ return updated_input
+
+
def extract_file_data(file_data: FileTypes) -> ExtractedFileData:
"""
Extracts and processes file data from various input formats.
diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index 717c2607657..44987bd1d08 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -1,3 +1,4 @@
+import base64
import copy
import hashlib
import json
@@ -1161,8 +1162,58 @@ def _gemini_tool_call_invoke_helper(
return function_call
+def _get_thought_signature_from_tool(tool: dict, model: Optional[str] = None) -> Optional[str]:
+ """Extract thought signature from tool call's provider_specific_fields.
+
+ Checks both tool.provider_specific_fields and tool.function.provider_specific_fields.
+ If no signature is found and model is gemini-3, returns a dummy signature.
+ """
+ # First check tool's provider_specific_fields
+ provider_fields = tool.get("provider_specific_fields") or {}
+ if isinstance(provider_fields, dict):
+ signature = provider_fields.get("thought_signature")
+ if signature:
+ return signature
+
+ # Then check function's provider_specific_fields
+ function = tool.get("function")
+ if function:
+ if isinstance(function, dict):
+ func_provider_fields = function.get("provider_specific_fields") or {}
+ if isinstance(func_provider_fields, dict):
+ signature = func_provider_fields.get("thought_signature")
+ if signature:
+ return signature
+ elif hasattr(function, "provider_specific_fields") and function.provider_specific_fields:
+ if isinstance(function.provider_specific_fields, dict):
+ signature = function.provider_specific_fields.get("thought_signature")
+ if signature:
+ return signature
+
+ # If no signature found and model is gemini-3, return dummy signature
+ from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexGeminiConfig
+ if model and VertexGeminiConfig._is_gemini_3_or_newer(model):
+ return _get_dummy_thought_signature()
+
+ return None
+
+
+def _get_dummy_thought_signature() -> str:
+ """Generate a dummy thought signature for models that require it.
+
+ This is used when transferring conversation history from older models
+ (like gemini-2.5-flash) to gemini-3, which requires thought_signature
+ for strict validation.
+ """
+ # Return a base64-encoded dummy signature string
+ # Below dummy signature is recommended by google - https://ai.google.dev/gemini-api/docs/thought-signatures#faqs
+ dummy_data = b"skip_thought_signature_validator"
+ return base64.b64encode(dummy_data).decode("utf-8")
+
+
def convert_to_gemini_tool_call_invoke(
message: ChatCompletionAssistantMessage,
+ model: Optional[str] = None,
) -> List[VertexPartType]:
"""
OpenAI tool invokes:
@@ -1207,8 +1258,9 @@ def convert_to_gemini_tool_call_invoke(
_parts_list: List[VertexPartType] = []
tool_calls = message.get("tool_calls", None)
function_call = message.get("function_call", None)
+
if tool_calls is not None:
- for tool in tool_calls:
+ for idx, tool in enumerate(tool_calls):
if "function" in tool:
gemini_function_call: Optional[VertexFunctionCall] = (
_gemini_tool_call_invoke_helper(
@@ -1216,9 +1268,14 @@ def convert_to_gemini_tool_call_invoke(
)
)
if gemini_function_call is not None:
- _parts_list.append(
- VertexPartType(function_call=gemini_function_call)
- )
+ part_dict: VertexPartType = {
+ "function_call": gemini_function_call
+ }
+ thought_signature = _get_thought_signature_from_tool(dict(tool), model=model)
+ if thought_signature:
+ part_dict["thoughtSignature"] = thought_signature
+
+ _parts_list.append(part_dict)
else: # don't silently drop params. Make it clear to user what's happening.
raise Exception(
"function_call missing. Received tool call with 'type': 'function'. No function call in argument - {}".format(
@@ -1230,7 +1287,25 @@ def convert_to_gemini_tool_call_invoke(
function_call_params=function_call
)
if gemini_function_call is not None:
- _parts_list.append(VertexPartType(function_call=gemini_function_call))
+ part_dict_function: VertexPartType = {
+ "function_call": gemini_function_call
+ }
+
+ # Extract thought signature from function_call's provider_specific_fields
+ thought_signature = None
+ provider_fields = function_call.get("provider_specific_fields") if isinstance(function_call, dict) else {}
+ if isinstance(provider_fields, dict):
+ thought_signature = provider_fields.get("thought_signature")
+
+ # If no signature found and model is gemini-3, use dummy signature
+ from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexGeminiConfig
+ if not thought_signature and model and VertexGeminiConfig._is_gemini_3_or_newer(model):
+ thought_signature = _get_dummy_thought_signature()
+
+ if thought_signature:
+ part_dict_function["thoughtSignature"] = thought_signature
+
+ _parts_list.append(part_dict_function)
else: # don't silently drop params. Make it clear to user what's happening.
raise Exception(
"function_call missing. Received tool call with 'type': 'function'. No function call in argument - {}".format(
@@ -2496,7 +2571,6 @@ def stringify_json_tool_call_content(messages: List) -> List:
###### AMAZON BEDROCK #######
-import base64
from email.message import Message
import httpx
diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
index 2f85c7aef60..ddcf81b5ba5 100644
--- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
+++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
@@ -137,6 +137,7 @@ class ChunkProcessor:
"name": None,
"type": None,
"arguments": [],
+ "provider_specific_fields": None,
}
if hasattr(tool_call, "id") and tool_call.id:
@@ -156,22 +157,48 @@ class ChunkProcessor:
tool_call_map[index]["arguments"].append(
tool_call.function.arguments
)
+
+ # Preserve provider_specific_fields from streaming chunks
+ provider_fields = None
+ if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields:
+ provider_fields = tool_call.provider_specific_fields
+ elif hasattr(tool_call, "function") and hasattr(tool_call.function, "provider_specific_fields") and tool_call.function.provider_specific_fields:
+ provider_fields = tool_call.function.provider_specific_fields
+
+ if provider_fields:
+ # Merge provider_specific_fields if multiple chunks have them
+ if tool_call_map[index]["provider_specific_fields"] is None:
+ tool_call_map[index]["provider_specific_fields"] = {}
+ if isinstance(provider_fields, dict):
+ tool_call_map[index]["provider_specific_fields"].update(
+ provider_fields
+ )
# Convert the map to a list of tool calls
for index in sorted(tool_call_map.keys()):
tool_call_data = tool_call_map[index]
if tool_call_data["id"] and tool_call_data["name"]:
combined_arguments = "".join(tool_call_data["arguments"]) or "{}"
- tool_calls_list.append(
- ChatCompletionMessageToolCall(
- id=tool_call_data["id"],
- function=Function(
- arguments=combined_arguments,
- name=tool_call_data["name"],
- ),
- type=tool_call_data["type"] or "function",
- )
+
+ # Build function - provider_specific_fields should be on tool_call level, not function level
+ function = Function(
+ arguments=combined_arguments,
+ name=tool_call_data["name"],
)
+
+ # Prepare params for ChatCompletionMessageToolCall
+ tool_call_params = {
+ "id": tool_call_data["id"],
+ "function": function,
+ "type": tool_call_data["type"] or "function",
+ }
+
+ # Add provider_specific_fields if present (for thought signatures in Gemini 3)
+ if tool_call_data.get("provider_specific_fields"):
+ tool_call_params["provider_specific_fields"] = tool_call_data["provider_specific_fields"]
+
+ tool_call = ChatCompletionMessageToolCall(**tool_call_params)
+ tool_calls_list.append(tool_call)
return tool_calls_list
diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index 6aeb4f5bb9a..0e956b10f3f 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -129,7 +129,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
"parallel_tool_calls",
"response_format",
"user",
- "web_search_options",
+ "web_search_options"
]
if "claude-3-7-sonnet" in model or supports_reasoning(
@@ -646,6 +646,16 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
)
return tools
+ def _ensure_context_management_beta_header(self, headers: dict) -> None:
+ beta_value = ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
+ existing_beta = headers.get("anthropic-beta")
+ if existing_beta is None:
+ headers["anthropic-beta"] = beta_value
+ return
+ existing_values = [beta.strip() for beta in existing_beta.split(",")]
+ if beta_value not in existing_values:
+ headers["anthropic-beta"] = f"{existing_beta}, {beta_value}"
+
def update_headers_with_optional_anthropic_beta(
self, headers: dict, optional_params: dict
) -> dict:
@@ -661,9 +671,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
elif tool.get("type", None) and tool.get("type").startswith(
ANTHROPIC_HOSTED_TOOLS.MEMORY.value
):
- headers["anthropic-beta"] = (
- ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
- )
+ headers[
+ "anthropic-beta"
+ ] = ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
+ if optional_params.get("context_management") is not None:
+ self._ensure_context_management_beta_header(headers)
return headers
def transform_request(
@@ -973,13 +985,21 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
):
text_content = prefix_prompt + text_content
+ context_management: Optional[Dict] = completion_response.get(
+ "context_management"
+ )
+
+ provider_specific_fields: Dict[str, Any] = {
+ "citations": citations,
+ "thinking_blocks": thinking_blocks,
+ }
+ if context_management is not None:
+ provider_specific_fields["context_management"] = context_management
+
_message = litellm.Message(
tool_calls=tool_calls,
content=text_content or None,
- provider_specific_fields={
- "citations": citations,
- "thinking_blocks": thinking_blocks,
- },
+ provider_specific_fields=provider_specific_fields,
thinking_blocks=thinking_blocks,
reasoning_content=reasoning_content,
)
@@ -1012,6 +1032,16 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
model_response.created = int(time.time())
model_response.model = completion_response["model"]
+ context_management_response = completion_response.get("context_management")
+ if context_management_response is not None:
+ _hidden_params["context_management"] = context_management_response
+ try:
+ model_response.__dict__["context_management"] = (
+ context_management_response
+ )
+ except Exception:
+ pass
+
model_response._hidden_params = _hidden_params
return model_response
diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index a786f06921f..0e905014fe2 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -3,6 +3,7 @@ from typing import (
TYPE_CHECKING,
Any,
AsyncIterator,
+ Dict,
List,
Literal,
Optional,
@@ -129,6 +130,39 @@ class LiteLLMAnthropicMessagesAdapter:
### FOR [BETA] `/v1/messages` endpoint support
+ def _extract_signature_from_tool_call(
+ self, tool_call: Any
+ ) -> Optional[str]:
+ """
+ Extract signature from a tool call's provider_specific_fields.
+ Only checks provider_specific_fields, not thinking blocks.
+ """
+ signature = None
+
+ if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields:
+ if "thought_signature" in tool_call.provider_specific_fields:
+ signature = tool_call.provider_specific_fields["thought_signature"]
+ elif (
+ hasattr(tool_call.function, "provider_specific_fields")
+ and tool_call.function.provider_specific_fields
+ ):
+ if "thought_signature" in tool_call.function.provider_specific_fields:
+ signature = tool_call.function.provider_specific_fields["thought_signature"]
+
+ return signature
+
+ def _extract_signature_from_tool_use_content(
+ self, content: Dict[str, Any]
+ ) -> Optional[str]:
+ """
+ Extract signature from a tool_use content block's provider_specific_fields.
+ """
+ provider_specific_fields = content.get("provider_specific_fields", {})
+ if provider_specific_fields:
+ return provider_specific_fields.get("signature")
+ return None
+
+
def translatable_anthropic_params(self) -> List:
"""
Which anthropic params, we need to translate to the openai format.
@@ -263,10 +297,18 @@ class LiteLLMAnthropicMessagesAdapter:
else:
assistant_message_str += content.get("text", "")
elif content.get("type") == "tool_use":
- function_chunk = ChatCompletionToolCallFunctionChunk(
- name=content.get("name", ""),
- arguments=json.dumps(content.get("input", {})),
- )
+ function_chunk: ChatCompletionToolCallFunctionChunk = {
+ "name": content.get("name", ""),
+ "arguments": json.dumps(content.get("input", {})),
+ }
+ signature = self._extract_signature_from_tool_use_content(content)
+
+ if signature:
+ provider_specific_fields: Dict[str, Any] = (
+ function_chunk.get("provider_specific_fields") or {}
+ )
+ provider_specific_fields["thought_signature"] = signature
+ function_chunk["provider_specific_fields"] = provider_specific_fields
tool_calls.append(
ChatCompletionAssistantToolCall(
@@ -512,18 +554,27 @@ class LiteLLMAnthropicMessagesAdapter:
and len(choice.message.tool_calls) > 0
):
for tool_call in choice.message.tool_calls:
- new_content.append(
- AnthropicResponseContentBlockToolUse(
- type="tool_use",
- id=tool_call.id,
- name=tool_call.function.name or "",
- input=(
- json.loads(tool_call.function.arguments)
- if tool_call.function.arguments
- else {}
- ),
- )
+ # Extract signature from provider_specific_fields only
+ signature = self._extract_signature_from_tool_call(tool_call)
+
+ provider_specific_fields = {}
+ if signature:
+ provider_specific_fields["signature"] = signature
+
+ tool_use_block = AnthropicResponseContentBlockToolUse(
+ type="tool_use",
+ id=tool_call.id,
+ name=tool_call.function.name or "",
+ input=(
+ json.loads(tool_call.function.arguments)
+ if tool_call.function.arguments
+ else {}
+ ),
)
+ # Add provider_specific_fields if signature is present
+ if provider_specific_fields:
+ tool_use_block.provider_specific_fields = provider_specific_fields
+ new_content.append(tool_use_block)
# Handle text content
elif choice.message.content is not None:
new_content.append(
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
index 85b9ae1f034..99d19f0460c 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
@@ -6,7 +6,10 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
from litellm.llms.base_llm.anthropic_messages.transformation import (
BaseAnthropicMessagesConfig,
)
-from litellm.types.llms.anthropic import AnthropicMessagesRequest
+from litellm.types.llms.anthropic import (
+ ANTHROPIC_BETA_HEADER_VALUES,
+ AnthropicMessagesRequest,
+)
from litellm.types.llms.anthropic_messages.anthropic_response import (
AnthropicMessagesResponse,
)
@@ -32,6 +35,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
"tools",
"tool_choice",
"thinking",
+ "context_management",
# TODO: Add Anthropic `metadata` support
# "metadata",
]
@@ -71,6 +75,11 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
if "content-type" not in headers:
headers["content-type"] = "application/json"
+ headers = self._update_headers_with_optional_anthropic_beta(
+ headers=headers,
+ context_management=optional_params.get("context_management"),
+ )
+
return headers, api_base
def transform_anthropic_messages_request(
@@ -142,3 +151,18 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
request_body=request_body,
litellm_logging_obj=litellm_logging_obj,
)
+
+ @staticmethod
+ def _update_headers_with_optional_anthropic_beta(
+ headers: dict, context_management: Optional[Dict]
+ ) -> dict:
+ if context_management is None:
+ return headers
+
+ existing_beta = headers.get("anthropic-beta")
+ beta_value = ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value
+ if existing_beta is None:
+ headers["anthropic-beta"] = beta_value
+ elif beta_value not in [beta.strip() for beta in existing_beta.split(",")]:
+ headers["anthropic-beta"] = f"{existing_beta}, {beta_value}"
+ return headers
diff --git a/litellm/llms/azure/text_to_speech/transformation.py b/litellm/llms/azure/text_to_speech/transformation.py
index 0f8911ac2b8..df582c3c09b 100644
--- a/litellm/llms/azure/text_to_speech/transformation.py
+++ b/litellm/llms/azure/text_to_speech/transformation.py
@@ -382,6 +382,15 @@ class AzureAVATextToSpeechConfig(BaseTextToSpeechConfig):
return f"https://{region}.{self.TTS_SPEECH_DOMAIN}{self.TTS_ENDPOINT_PATH}"
return f"https://{self.TTS_SPEECH_DOMAIN}{self.TTS_ENDPOINT_PATH}"
+
+ def is_ssml_input(self, input: str) -> bool:
+ """
+ Returns True if input is SSML, False otherwise
+
+ Based on https://www.w3.org/TR/speech-synthesis/ all SSML must start with
+ """
+ return "" in input or ", it's passed through as-is without transformation
+
Returns:
TextToSpeechRequestData: Contains SSML body and Azure-specific headers
"""
@@ -414,7 +426,15 @@ class AzureAVATextToSpeechConfig(BaseTextToSpeechConfig):
)
headers["X-Microsoft-OutputFormat"] = output_format
- # Build SSML
+ # Auto-detect SSML: if input contains , pass it through as-is
+ # Similar to Vertex AI behavior - check if input looks like SSML
+ if self.is_ssml_input(input=input):
+ return TextToSpeechRequestData(
+ ssml_body=input,
+ headers=headers,
+ )
+
+ # Build SSML from plain text
rate = optional_params.get("rate", "0%")
style = optional_params.get("style")
styledegree = optional_params.get("styledegree")
diff --git a/litellm/llms/base_llm/vector_store_files/transformation.py b/litellm/llms/base_llm/vector_store_files/transformation.py
new file mode 100644
index 00000000000..f751022faaf
--- /dev/null
+++ b/litellm/llms/base_llm/vector_store_files/transformation.py
@@ -0,0 +1,226 @@
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
+
+import httpx
+
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.vector_store_files import (
+ VectorStoreFileAuthCredentials,
+ VectorStoreFileChunkingStrategy,
+ VectorStoreFileContentResponse,
+ VectorStoreFileCreateRequest,
+ VectorStoreFileDeleteResponse,
+ VectorStoreFileListQueryParams,
+ VectorStoreFileListResponse,
+ VectorStoreFileObject,
+ VectorStoreFileUpdateRequest,
+)
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ from ..chat.transformation import BaseLLMException as _BaseLLMException
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+ BaseLLMException = _BaseLLMException
+else:
+ LiteLLMLoggingObj = Any
+ BaseLLMException = Any
+
+
+class BaseVectorStoreFilesConfig(ABC):
+ """Base configuration contract for provider-specific vector store file implementations."""
+
+ def get_supported_openai_params(
+ self,
+ operation: str,
+ ) -> Tuple[str, ...]:
+ """Return the set of OpenAI params supported for the given operation."""
+
+ return tuple()
+
+ def map_openai_params(
+ self,
+ *,
+ operation: str,
+ non_default_params: Dict[str, Any],
+ optional_params: Dict[str, Any],
+ drop_params: bool,
+ ) -> Dict[str, Any]:
+ """Map non-default OpenAI params to provider-specific params."""
+
+ return optional_params
+
+ @abstractmethod
+ def get_auth_credentials(
+ self, litellm_params: Dict[str, Any]
+ ) -> VectorStoreFileAuthCredentials:
+ ...
+
+ @abstractmethod
+ def get_vector_store_file_endpoints_by_type(self) -> Dict[
+ str, Tuple[Tuple[str, str], ...]
+ ]:
+ ...
+
+ @abstractmethod
+ def validate_environment(
+ self,
+ *,
+ headers: Dict[str, str],
+ litellm_params: Optional[GenericLiteLLMParams],
+ ) -> Dict[str, str]:
+ return {}
+
+ @abstractmethod
+ def get_complete_url(
+ self,
+ *,
+ api_base: Optional[str],
+ vector_store_id: str,
+ litellm_params: Dict[str, Any],
+ ) -> str:
+ if api_base is None:
+ raise ValueError("api_base is required")
+ return api_base
+
+ @abstractmethod
+ def transform_create_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ create_request: VectorStoreFileCreateRequest,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_create_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ ...
+
+ @abstractmethod
+ def transform_list_vector_store_files_request(
+ self,
+ *,
+ vector_store_id: str,
+ query_params: VectorStoreFileListQueryParams,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_list_vector_store_files_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileListResponse:
+ ...
+
+ @abstractmethod
+ def transform_retrieve_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_retrieve_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ ...
+
+ @abstractmethod
+ def transform_retrieve_vector_store_file_content_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_retrieve_vector_store_file_content_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileContentResponse:
+ ...
+
+ @abstractmethod
+ def transform_update_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ update_request: VectorStoreFileUpdateRequest,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_update_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ ...
+
+ @abstractmethod
+ def transform_delete_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ ...
+
+ @abstractmethod
+ def transform_delete_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileDeleteResponse:
+ ...
+
+ def get_error_class(
+ self,
+ *,
+ error_message: str,
+ status_code: int,
+ headers: Union[Dict[str, Any], httpx.Headers],
+ ) -> BaseLLMException:
+ from ..chat.transformation import BaseLLMException
+
+ raise BaseLLMException(
+ status_code=status_code,
+ message=error_message,
+ headers=headers,
+ )
+
+ def sign_request(
+ self,
+ *,
+ headers: Dict[str, str],
+ optional_params: Dict[str, Any],
+ request_data: Dict[str, Any],
+ api_base: str,
+ api_key: Optional[str] = None,
+ ) -> Tuple[Dict[str, str], Optional[bytes]]:
+ return headers, None
+
+ def prepare_chunking_strategy(
+ self,
+ chunking_strategy: Optional[VectorStoreFileChunkingStrategy],
+ ) -> Optional[VectorStoreFileChunkingStrategy]:
+ return chunking_strategy
diff --git a/litellm/llms/bedrock/chat/invoke_handler.py b/litellm/llms/bedrock/chat/invoke_handler.py
index 53cbafcbe6a..71429e4191f 100644
--- a/litellm/llms/bedrock/chat/invoke_handler.py
+++ b/litellm/llms/bedrock/chat/invoke_handler.py
@@ -493,9 +493,9 @@ class BedrockLLM(BaseAWSLLM):
content=None,
)
model_response.choices[0].message = _message # type: ignore
- model_response._hidden_params["original_response"] = (
- outputText # allow user to access raw anthropic tool calling response
- )
+ model_response._hidden_params[
+ "original_response"
+ ] = outputText # allow user to access raw anthropic tool calling response
if (
_is_function_call is True
and stream is not None
@@ -793,9 +793,9 @@ class BedrockLLM(BaseAWSLLM):
): # completion(top_k=3) > anthropic_config(top_k=3) <- allows for dynamic variables to be passed in
inference_params[k] = v
if stream is True:
- inference_params["stream"] = (
- True # cohere requires stream = True in inference params
- )
+ inference_params[
+ "stream"
+ ] = True # cohere requires stream = True in inference params
data = json.dumps({"prompt": prompt, **inference_params})
elif provider == "anthropic":
if model.startswith("anthropic.claude-3"):
@@ -1184,6 +1184,7 @@ class AWSEventStreamDecoder:
self.parser = EventStreamJSONParser()
self.content_blocks: List[ContentBlockDeltaEvent] = []
self.tool_calls_index: Optional[int] = None
+ self.response_id: Optional[str] = None
def check_empty_tool_call_args(self) -> bool:
"""
@@ -1247,6 +1248,17 @@ class AWSEventStreamDecoder:
def converse_chunk_parser(self, chunk_data: dict) -> ModelResponseStream:
try:
+ # Capture the conversationId from the first messageStart event
+ # and use it as the consistent ID for all subsequent chunks.
+ if self.response_id is None:
+ if "messageStart" in chunk_data:
+ conversation_id = chunk_data["messageStart"].get("conversationId")
+ if conversation_id:
+ self.response_id = f"chatcmpl-{conversation_id}"
+ else:
+ # Fallback to generating a UUID if the first chunk is not messageStart
+ self.response_id = f"chatcmpl-{uuid.uuid4()}"
+
verbose_logger.debug("\n\nRaw Chunk: {}\n\n".format(chunk_data))
text = ""
tool_use: Optional[ChatCompletionToolCallChunk] = None
@@ -1378,6 +1390,7 @@ class AWSEventStreamDecoder:
),
)
],
+ id=self.response_id,
usage=usage,
provider_specific_fields=model_response_provider_specific_fields,
)
diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py
index 05c640aa580..6b0aef31ff6 100644
--- a/litellm/llms/custom_httpx/llm_http_handler.py
+++ b/litellm/llms/custom_httpx/llm_http_handler.py
@@ -48,6 +48,9 @@ from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfi
from litellm.llms.base_llm.search.transformation import BaseSearchConfig, SearchResponse
from litellm.llms.base_llm.text_to_speech.transformation import BaseTextToSpeechConfig
from litellm.llms.base_llm.vector_store.transformation import BaseVectorStoreConfig
+from litellm.llms.base_llm.vector_store_files.transformation import (
+ BaseVectorStoreFilesConfig,
+)
from litellm.llms.base_llm.videos.transformation import BaseVideoConfig
from litellm.llms.custom_httpx.http_handler import (
AsyncHTTPHandler,
@@ -92,6 +95,15 @@ from litellm.types.vector_stores import (
VectorStoreSearchOptionalRequestParams,
VectorStoreSearchResponse,
)
+from litellm.types.vector_store_files import (
+ VectorStoreFileContentResponse,
+ VectorStoreFileCreateRequest,
+ VectorStoreFileDeleteResponse,
+ VectorStoreFileListQueryParams,
+ VectorStoreFileListResponse,
+ VectorStoreFileObject,
+ VectorStoreFileUpdateRequest,
+)
from litellm.types.videos.main import VideoObject
from litellm.utils import (
CustomStreamWrapper,
@@ -1128,6 +1140,7 @@ class BaseLLMHTTPHandler:
atranscription: bool = False,
headers: Optional[Dict[str, Any]] = None,
provider_config: Optional[BaseAudioTranscriptionConfig] = None,
+ shared_session: Optional["ClientSession"] = None,
) -> Union[TranscriptionResponse, Coroutine[Any, Any, TranscriptionResponse]]:
if provider_config is None:
raise ValueError(
@@ -1150,6 +1163,7 @@ class BaseLLMHTTPHandler:
client=client,
headers=headers,
provider_config=provider_config,
+ shared_session=shared_session,
)
# Prepare the request
@@ -1214,6 +1228,7 @@ class BaseLLMHTTPHandler:
client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
headers: Optional[Dict[str, Any]] = None,
provider_config: Optional[BaseAudioTranscriptionConfig] = None,
+ shared_session: Optional["ClientSession"] = None,
) -> TranscriptionResponse:
if provider_config is None:
raise ValueError(
@@ -1242,6 +1257,7 @@ class BaseLLMHTTPHandler:
async_httpx_client = get_async_httpx_client(
llm_provider=litellm.LlmProviders(custom_llm_provider),
params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ shared_session=shared_session,
)
else:
async_httpx_client = client
@@ -3529,6 +3545,7 @@ class BaseLLMHTTPHandler:
BaseImageEditConfig,
BaseImageGenerationConfig,
BaseVectorStoreConfig,
+ BaseVectorStoreFilesConfig,
BaseGoogleGenAIGenerateContentConfig,
BaseAnthropicMessagesConfig,
BaseBatchesConfig,
@@ -4094,7 +4111,7 @@ class BaseLLMHTTPHandler:
sync_httpx_client = client
headers = video_generation_provider_config.validate_environment(
- api_key=api_key,
+ api_key=api_key or litellm_params.get("api_key", None),
headers=video_generation_optional_request_params.get("extra_headers", {})
or {},
model=model,
@@ -4194,7 +4211,7 @@ class BaseLLMHTTPHandler:
async_httpx_client = client
headers = video_generation_provider_config.validate_environment(
- api_key=api_key,
+ api_key=api_key or litellm_params.get("api_key", None),
headers=video_generation_optional_request_params.get("extra_headers", {})
or {},
model=model,
@@ -6000,6 +6017,909 @@ class BaseLLMHTTPHandler:
response=response,
)
+ #####################################################################
+ ################ Vector Store Files HANDLERS ########################
+ #####################################################################
+ async def async_vector_store_file_create_handler(
+ self,
+ *,
+ vector_store_id: str,
+ create_request: VectorStoreFileCreateRequest,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_body: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileObject:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ request_dict = dict(create_request)
+ if extra_body:
+ request_dict.update(extra_body)
+
+ (
+ url,
+ request_body,
+ ) = vector_store_files_provider_config.transform_create_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ create_request=cast(VectorStoreFileCreateRequest, request_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_body,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.post(
+ url=url, headers=headers, json=request_body, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_create_vector_store_file_response(
+ response=response
+ )
+
+ def vector_store_file_create_handler(
+ self,
+ *,
+ vector_store_id: str,
+ create_request: VectorStoreFileCreateRequest,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_body: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[VectorStoreFileObject, Coroutine[Any, Any, VectorStoreFileObject]]:
+ if _is_async:
+ return self.async_vector_store_file_create_handler(
+ vector_store_id=vector_store_id,
+ create_request=create_request,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ extra_body=extra_body,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ request_dict = dict(create_request)
+ if extra_body:
+ request_dict.update(extra_body)
+
+ (
+ url,
+ request_body,
+ ) = vector_store_files_provider_config.transform_create_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ create_request=cast(VectorStoreFileCreateRequest, request_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_body,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.post(
+ url=url, headers=headers, json=request_body, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_create_vector_store_file_response(
+ response=response
+ )
+
+ async def async_vector_store_file_list_handler(
+ self,
+ *,
+ vector_store_id: str,
+ query_params: VectorStoreFileListQueryParams,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_query: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileListResponse:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ params_dict = dict(query_params)
+ if extra_query:
+ params_dict.update(extra_query)
+
+ (
+ url,
+ request_params,
+ ) = vector_store_files_provider_config.transform_list_vector_store_files_request(
+ vector_store_id=vector_store_id,
+ query_params=cast(VectorStoreFileListQueryParams, params_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_list_vector_store_files_response(
+ response=response
+ )
+
+ def vector_store_file_list_handler(
+ self,
+ *,
+ vector_store_id: str,
+ query_params: VectorStoreFileListQueryParams,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_query: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[
+ VectorStoreFileListResponse, Coroutine[Any, Any, VectorStoreFileListResponse]
+ ]:
+ if _is_async:
+ return self.async_vector_store_file_list_handler(
+ vector_store_id=vector_store_id,
+ query_params=query_params,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ extra_query=extra_query,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ params_dict = dict(query_params)
+ if extra_query:
+ params_dict.update(extra_query)
+
+ (
+ url,
+ request_params,
+ ) = vector_store_files_provider_config.transform_list_vector_store_files_request(
+ vector_store_id=vector_store_id,
+ query_params=cast(VectorStoreFileListQueryParams, params_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_list_vector_store_files_response(
+ response=response
+ )
+
+ async def async_vector_store_file_retrieve_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileObject:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_retrieve_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_retrieve_vector_store_file_response(
+ response=response
+ )
+
+ def vector_store_file_retrieve_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[VectorStoreFileObject, Coroutine[Any, Any, VectorStoreFileObject]]:
+ if _is_async:
+ return self.async_vector_store_file_retrieve_handler(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_retrieve_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_retrieve_vector_store_file_response(
+ response=response
+ )
+
+ async def async_vector_store_file_content_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileContentResponse:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_retrieve_vector_store_file_content_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_retrieve_vector_store_file_content_response(
+ response=response
+ )
+
+ def vector_store_file_content_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[
+ VectorStoreFileContentResponse,
+ Coroutine[Any, Any, VectorStoreFileContentResponse],
+ ]:
+ if _is_async:
+ return self.async_vector_store_file_content_handler(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_retrieve_vector_store_file_content_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.get(
+ url=url, headers=headers, params=request_params
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_retrieve_vector_store_file_content_response(
+ response=response
+ )
+
+ async def async_vector_store_file_update_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ update_request: VectorStoreFileUpdateRequest,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_body: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileObject:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ request_dict = dict(update_request)
+ if extra_body:
+ request_dict.update(extra_body)
+
+ (
+ url,
+ request_body,
+ ) = vector_store_files_provider_config.transform_update_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ update_request=cast(VectorStoreFileUpdateRequest, request_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_body,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.post(
+ url=url, headers=headers, json=request_body, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_update_vector_store_file_response(
+ response=response
+ )
+
+ def vector_store_file_update_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ update_request: VectorStoreFileUpdateRequest,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ extra_body: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[VectorStoreFileObject, Coroutine[Any, Any, VectorStoreFileObject]]:
+ if _is_async:
+ return self.async_vector_store_file_update_handler(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ update_request=update_request,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ extra_body=extra_body,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ request_dict = dict(update_request)
+ if extra_body:
+ request_dict.update(extra_body)
+
+ (
+ url,
+ request_body,
+ ) = vector_store_files_provider_config.transform_update_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ update_request=cast(VectorStoreFileUpdateRequest, request_dict),
+ api_base=api_base,
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_body,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.post(
+ url=url, headers=headers, json=request_body, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_update_vector_store_file_response(
+ response=response
+ )
+
+ async def async_vector_store_file_delete_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ ) -> VectorStoreFileDeleteResponse:
+ if client is None or not isinstance(client, AsyncHTTPHandler):
+ async_httpx_client = get_async_httpx_client(
+ llm_provider=litellm.LlmProviders(custom_llm_provider),
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+ )
+ else:
+ async_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_delete_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = await async_httpx_client.delete(
+ url=url, headers=headers, params=request_params, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_delete_vector_store_file_response(
+ response=response
+ )
+
+ def vector_store_file_delete_handler(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ vector_store_files_provider_config: BaseVectorStoreFilesConfig,
+ custom_llm_provider: str,
+ litellm_params: GenericLiteLLMParams,
+ logging_obj: LiteLLMLoggingObj,
+ extra_headers: Optional[Dict[str, Any]] = None,
+ timeout: Optional[Union[float, httpx.Timeout]] = None,
+ client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+ _is_async: bool = False,
+ ) -> Union[
+ VectorStoreFileDeleteResponse,
+ Coroutine[Any, Any, VectorStoreFileDeleteResponse],
+ ]:
+ if _is_async:
+ return self.async_vector_store_file_delete_handler(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ vector_store_files_provider_config=vector_store_files_provider_config,
+ custom_llm_provider=custom_llm_provider,
+ litellm_params=litellm_params,
+ logging_obj=logging_obj,
+ extra_headers=extra_headers,
+ timeout=timeout,
+ client=client if isinstance(client, AsyncHTTPHandler) else None,
+ )
+
+ if client is None or not isinstance(client, HTTPHandler):
+ sync_httpx_client = _get_httpx_client(
+ params={"ssl_verify": litellm_params.get("ssl_verify", None)}
+ )
+ else:
+ sync_httpx_client = client
+
+ headers = vector_store_files_provider_config.validate_environment(
+ headers=extra_headers or {}, litellm_params=litellm_params
+ )
+ if extra_headers:
+ headers.update(extra_headers)
+
+ api_base = vector_store_files_provider_config.get_complete_url(
+ api_base=litellm_params.api_base,
+ vector_store_id=vector_store_id,
+ litellm_params=dict(litellm_params),
+ )
+
+ url, request_params = (
+ vector_store_files_provider_config.transform_delete_vector_store_file_request(
+ vector_store_id=vector_store_id,
+ file_id=file_id,
+ api_base=api_base,
+ )
+ )
+
+ logging_obj.pre_call(
+ input="",
+ api_key="",
+ additional_args={
+ "complete_input_dict": request_params,
+ "api_base": api_base,
+ "headers": headers,
+ },
+ )
+
+ try:
+ response = sync_httpx_client.delete(
+ url=url, headers=headers, params=request_params, timeout=timeout
+ )
+ except Exception as e:
+ raise self._handle_error(
+ e=e, provider_config=vector_store_files_provider_config
+ )
+
+ return vector_store_files_provider_config.transform_delete_vector_store_file_response(
+ response=response
+ )
+
#####################################################################
################ Google GenAI GENERATE CONTENT HANDLER ###########################
#####################################################################
diff --git a/litellm/llms/fal_ai/__init__.py b/litellm/llms/fal_ai/__init__.py
index 1f4cbe0e9ce..34cac014ce9 100644
--- a/litellm/llms/fal_ai/__init__.py
+++ b/litellm/llms/fal_ai/__init__.py
@@ -2,6 +2,7 @@ from .cost_calculator import cost_calculator
from .image_generation import (
FalAIBaseConfig,
FalAIBriaConfig,
+ FalAIFluxProV11Config,
FalAIFluxProV11UltraConfig,
FalAIFluxSchnellConfig,
FalAIImageGenerationConfig,
@@ -18,6 +19,7 @@ __all__ = [
"FalAIImagen4Config",
"FalAIRecraftV3Config",
"FalAIBriaConfig",
+ "FalAIFluxProV11Config",
"FalAIFluxProV11UltraConfig",
"FalAIFluxSchnellConfig",
"FalAIStableDiffusionConfig",
diff --git a/litellm/llms/fal_ai/image_generation/__init__.py b/litellm/llms/fal_ai/image_generation/__init__.py
index b4ae6734c64..27817ae5a5f 100644
--- a/litellm/llms/fal_ai/image_generation/__init__.py
+++ b/litellm/llms/fal_ai/image_generation/__init__.py
@@ -3,12 +3,18 @@ from litellm.llms.base_llm.image_generation.transformation import (
)
from .bria_transformation import FalAIBriaConfig
+from .flux_pro_v11_transformation import FalAIFluxProV11Config
from .flux_pro_v11_ultra_transformation import FalAIFluxProV11UltraConfig
from .flux_schnell_transformation import FalAIFluxSchnellConfig
from .imagen4_transformation import FalAIImagen4Config
from .recraft_v3_transformation import FalAIRecraftV3Config
+from .ideogram_v3_transformation import FalAIIdeogramV3Config
from .stable_diffusion_transformation import FalAIStableDiffusionConfig
from .transformation import FalAIBaseConfig, FalAIImageGenerationConfig
+from .bytedance_transformation import (
+ FalAIBytedanceSeedreamV3Config,
+ FalAIBytedanceDreaminaV31Config,
+)
__all__ = [
"FalAIBaseConfig",
@@ -16,9 +22,13 @@ __all__ = [
"FalAIImagen4Config",
"FalAIRecraftV3Config",
"FalAIBriaConfig",
+ "FalAIFluxProV11Config",
"FalAIFluxProV11UltraConfig",
"FalAIFluxSchnellConfig",
"FalAIStableDiffusionConfig",
+ "FalAIBytedanceSeedreamV3Config",
+ "FalAIBytedanceDreaminaV31Config",
+ "FalAIIdeogramV3Config",
]
@@ -41,10 +51,18 @@ def get_fal_ai_image_generation_config(model: str) -> BaseImageGenerationConfig:
return FalAIRecraftV3Config()
elif "bria" in model_lower:
return FalAIBriaConfig()
- elif "flux-pro" in model_lower and "ultra" in model_lower:
- return FalAIFluxProV11UltraConfig()
+ elif "flux-pro" in model_lower:
+ if "ultra" in model_lower:
+ return FalAIFluxProV11UltraConfig()
+ return FalAIFluxProV11Config()
elif "flux/schnell" in model_lower or "flux-schnell" in model_lower or "schnell" in model_lower:
return FalAIFluxSchnellConfig()
+ elif "bytedance/seedream" in model_lower:
+ return FalAIBytedanceSeedreamV3Config()
+ elif "bytedance/dreamina" in model_lower:
+ return FalAIBytedanceDreaminaV31Config()
+ elif "ideogram" in model_lower:
+ return FalAIIdeogramV3Config()
elif "stable-diffusion" in model_lower:
return FalAIStableDiffusionConfig()
diff --git a/litellm/llms/fal_ai/image_generation/bytedance_transformation.py b/litellm/llms/fal_ai/image_generation/bytedance_transformation.py
new file mode 100644
index 00000000000..d6aa242edc4
--- /dev/null
+++ b/litellm/llms/fal_ai/image_generation/bytedance_transformation.py
@@ -0,0 +1,106 @@
+from typing import Any
+
+from .flux_pro_v11_ultra_transformation import FalAIFluxProV11UltraConfig
+
+
+class FalAIBytedanceBaseConfig(FalAIFluxProV11UltraConfig):
+ """
+ Shared configuration for Fal AI ByteDance text-to-image models that follow
+ the Flux Schnell style parameter mapping.
+
+ These models accept the OpenAI-compatible `size` parameter in LiteLLM
+ requests but expect `image_size` enums or custom size objects on Fal AI.
+ """
+
+ _OPENAI_SIZE_TO_IMAGE_SIZE = {
+ "1024x1024": "square_hd",
+ "512x512": "square",
+ "1792x1024": "landscape_16_9",
+ "1024x1792": "portrait_16_9",
+ "1024x768": "landscape_4_3",
+ "768x1024": "portrait_4_3",
+ }
+
+ def map_openai_params(
+ self,
+ non_default_params: dict,
+ optional_params: dict,
+ model: str,
+ drop_params: bool,
+ ) -> dict:
+ supported_params = self.get_supported_openai_params(model)
+
+ param_mapping = {
+ "n": "num_images",
+ "response_format": "output_format",
+ "size": "image_size",
+ }
+
+ for k in non_default_params.keys():
+ if k not in optional_params.keys():
+ if k in supported_params:
+ mapped_key = param_mapping.get(k, k)
+ mapped_value = non_default_params[k]
+
+ if k == "response_format":
+ if mapped_value in ["b64_json", "url"]:
+ mapped_value = "jpeg"
+ elif k == "size":
+ mapped_value = self._map_image_size(mapped_value)
+
+ optional_params[mapped_key] = mapped_value
+ elif drop_params:
+ continue
+ else:
+ raise ValueError(
+ f"Parameter {k} is not supported for model {model}. "
+ f"Supported parameters are {supported_params}. "
+ "Set drop_params=True to drop unsupported parameters."
+ )
+
+ return optional_params
+
+ def _map_image_size(self, size: Any) -> Any:
+ if isinstance(size, dict):
+ return size
+
+ if not isinstance(size, str):
+ return size
+
+ if size in self._OPENAI_SIZE_TO_IMAGE_SIZE:
+ return self._OPENAI_SIZE_TO_IMAGE_SIZE[size]
+
+ if "x" in size:
+ try:
+ width_str, height_str = size.split("x")
+ width = int(width_str)
+ height = int(height_str)
+ return {"width": width, "height": height}
+ except (ValueError, AttributeError, ZeroDivisionError):
+ pass
+
+ return "landscape_4_3"
+
+
+class FalAIBytedanceSeedreamV3Config(FalAIBytedanceBaseConfig):
+ """
+ Configuration for Fal AI ByteDance Seedream v3 text-to-image model.
+
+ Model endpoint: fal-ai/bytedance/seedream/v3/text-to-image
+ Documentation: https://fal.ai/models/fal-ai/bytedance/seedream/v3/text-to-image
+ """
+
+ IMAGE_GENERATION_ENDPOINT: str = "fal-ai/bytedance/seedream/v3/text-to-image"
+
+
+class FalAIBytedanceDreaminaV31Config(FalAIBytedanceBaseConfig):
+ """
+ Configuration for Fal AI ByteDance Dreamina v3.1 text-to-image model.
+
+ Model endpoint: fal-ai/bytedance/dreamina/v3.1/text-to-image
+ Documentation: https://fal.ai/models/fal-ai/bytedance/dreamina/v3.1/text-to-image
+ """
+
+ IMAGE_GENERATION_ENDPOINT: str = "fal-ai/bytedance/dreamina/v3.1/text-to-image"
+
+
diff --git a/litellm/llms/fal_ai/image_generation/flux_pro_v11_transformation.py b/litellm/llms/fal_ai/image_generation/flux_pro_v11_transformation.py
new file mode 100644
index 00000000000..682ee0c2670
--- /dev/null
+++ b/litellm/llms/fal_ai/image_generation/flux_pro_v11_transformation.py
@@ -0,0 +1,91 @@
+from typing import Any
+
+from .flux_pro_v11_ultra_transformation import FalAIFluxProV11UltraConfig
+
+
+class FalAIFluxProV11Config(FalAIFluxProV11UltraConfig):
+ """
+ Configuration for Fal AI Flux Pro v1.1 model.
+
+ FLUX Pro v1.1 leverages the same overall request/response structure as the
+ Ultra variant but expects the `image_size` parameter instead of
+ `aspect_ratio`.
+
+ Model endpoint: fal-ai/flux-pro/v1.1
+ Documentation: https://fal.ai/models/fal-ai/flux-pro/v1.1
+ """
+
+ IMAGE_GENERATION_ENDPOINT: str = "fal-ai/flux-pro/v1.1"
+
+ _OPENAI_SIZE_TO_IMAGE_SIZE = {
+ "1024x1024": "square_hd",
+ "512x512": "square",
+ "1792x1024": "landscape_16_9",
+ "1024x1792": "portrait_16_9",
+ "1024x768": "landscape_4_3",
+ "768x1024": "portrait_4_3",
+ }
+
+ def map_openai_params(
+ self,
+ non_default_params: dict,
+ optional_params: dict,
+ model: str,
+ drop_params: bool,
+ ) -> dict:
+ """
+ Override size handling to map to Flux Pro v1.1 image_size enums/object.
+ """
+ supported_params = self.get_supported_openai_params(model)
+
+ param_mapping = {
+ "n": "num_images",
+ "response_format": "output_format",
+ "size": "image_size",
+ }
+
+ for k in non_default_params.keys():
+ if k not in optional_params.keys():
+ if k in supported_params:
+ mapped_key = param_mapping.get(k, k)
+ mapped_value = non_default_params[k]
+
+ if k == "response_format":
+ if mapped_value in ["b64_json", "url"]:
+ mapped_value = "jpeg"
+ elif k == "size":
+ mapped_value = self._map_image_size(mapped_value)
+
+ optional_params[mapped_key] = mapped_value
+ elif drop_params:
+ continue
+ else:
+ raise ValueError(
+ f"Parameter {k} is not supported for model {model}. "
+ f"Supported parameters are {supported_params}. "
+ "Set drop_params=True to drop unsupported parameters."
+ )
+
+ return optional_params
+
+ def _map_image_size(self, size: Any) -> Any:
+ if isinstance(size, dict):
+ return size
+ if not isinstance(size, str):
+ return size
+
+ if size in self._OPENAI_SIZE_TO_IMAGE_SIZE:
+ return self._OPENAI_SIZE_TO_IMAGE_SIZE[size]
+
+ if "x" in size:
+ try:
+ width_str, height_str = size.split("x")
+ width = int(width_str)
+ height = int(height_str)
+ return {"width": width, "height": height}
+ except (ValueError, AttributeError, ZeroDivisionError):
+ pass
+
+ return "landscape_4_3"
+
+
diff --git a/litellm/llms/fal_ai/image_generation/ideogram_v3_transformation.py b/litellm/llms/fal_ai/image_generation/ideogram_v3_transformation.py
new file mode 100644
index 00000000000..f05ffa888ef
--- /dev/null
+++ b/litellm/llms/fal_ai/image_generation/ideogram_v3_transformation.py
@@ -0,0 +1,193 @@
+from typing import TYPE_CHECKING, Any, List, Optional
+
+import httpx
+
+from litellm.types.llms.openai import OpenAIImageGenerationOptionalParams
+from litellm.types.utils import ImageObject, ImageResponse
+
+from .transformation import FalAIBaseConfig
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+ LiteLLMLoggingObj = Any
+
+
+class FalAIIdeogramV3Config(FalAIBaseConfig):
+ """
+ Configuration for fal-ai/ideogram/v3 image generation.
+
+ The Ideogram v3 endpoint exposes multiple generation modes (text-to-image,
+ remixing, reframing, background replacement, character workflows, etc.).
+ LiteLLM focuses on the text-to-image interface to maintain OpenAI parity.
+
+ Model endpoint: fal-ai/ideogram/v3
+ Documentation: https://fal.ai/models/fal-ai/ideogram/v3
+ """
+
+ IMAGE_GENERATION_ENDPOINT: str = "fal-ai/ideogram/v3"
+
+ _OPENAI_SIZE_TO_IMAGE_SIZE = {
+ "1024x1024": "square_hd",
+ "512x512": "square",
+ "1024x768": "landscape_4_3",
+ "768x1024": "portrait_4_3",
+ "1536x1024": "landscape_16_9",
+ "1024x1536": "portrait_16_9",
+ }
+
+ def get_supported_openai_params(
+ self, model: str
+ ) -> List[OpenAIImageGenerationOptionalParams]:
+ """
+ Ideogram v3 accepts the core OpenAI image parameters.
+ """
+
+ return [
+ "n",
+ "response_format",
+ "size",
+ ]
+
+ def map_openai_params(
+ self,
+ non_default_params: dict,
+ optional_params: dict,
+ model: str,
+ drop_params: bool,
+ ) -> dict:
+ """
+ Map OpenAI-style parameters onto Ideogram's request schema.
+ """
+
+ supported_params = self.get_supported_openai_params(model)
+
+ for k in non_default_params.keys():
+ if k in optional_params:
+ continue
+
+ if k not in supported_params:
+ if drop_params:
+ continue
+ raise ValueError(
+ f"Parameter {k} is not supported for model {model}. "
+ f"Supported parameters are {supported_params}. "
+ "Set drop_params=True to drop unsupported parameters."
+ )
+
+ value = non_default_params[k]
+
+ if k == "n":
+ optional_params["num_images"] = value
+ elif k == "size":
+ optional_params["image_size"] = self._map_image_size(value)
+ elif k == "response_format":
+ # Ideogram always returns URLs; nothing to map but don't error.
+ continue
+
+ return optional_params
+
+ def _map_image_size(self, size: Any) -> Any:
+ if isinstance(size, dict):
+ width = size.get("width")
+ height = size.get("height")
+ if isinstance(width, int) and isinstance(height, int):
+ return {"width": width, "height": height}
+ return size
+
+ if not isinstance(size, str):
+ return size
+
+ normalized = size.strip()
+ if normalized in self._OPENAI_SIZE_TO_IMAGE_SIZE:
+ return self._OPENAI_SIZE_TO_IMAGE_SIZE[normalized]
+
+ if "x" in normalized:
+ try:
+ width_str, height_str = normalized.split("x")
+ width = int(width_str)
+ height = int(height_str)
+ return {"width": width, "height": height}
+ except (ValueError, AttributeError):
+ pass
+
+ # Fallback to a safe default that Ideogram accepts.
+ return "square_hd"
+
+ def transform_image_generation_request(
+ self,
+ model: str,
+ prompt: str,
+ optional_params: dict,
+ litellm_params: dict,
+ headers: dict,
+ ) -> dict:
+ """
+ Construct the request payload for Ideogram v3.
+
+ Required:
+ - prompt: text prompt describing the scene.
+
+ Optional (subset):
+ - rendering_speed, style_preset, style, style_codes, color_palette,
+ image_urls, style_reference_images, expand_prompt, seed,
+ negative_prompt, image_size, etc.
+ """
+
+ return {
+ "prompt": prompt,
+ **optional_params,
+ }
+
+ def transform_image_generation_response(
+ self,
+ model: str,
+ raw_response: httpx.Response,
+ model_response: ImageResponse,
+ logging_obj: LiteLLMLoggingObj,
+ request_data: dict,
+ optional_params: dict,
+ litellm_params: dict,
+ encoding: Any,
+ api_key: Optional[str] = None,
+ json_mode: Optional[bool] = None,
+ ) -> ImageResponse:
+ """
+ Parse Ideogram v3 responses which contain a list of File objects.
+ """
+
+ try:
+ response_data = raw_response.json()
+ except Exception as e:
+ raise self.get_error_class(
+ error_message=f"Error transforming image generation response: {e}",
+ status_code=raw_response.status_code,
+ headers=raw_response.headers,
+ )
+
+ if not model_response.data:
+ model_response.data = []
+
+ images = response_data.get("images", [])
+ if isinstance(images, list):
+ for image_entry in images:
+ if isinstance(image_entry, dict):
+ url = image_entry.get("url")
+ else:
+ url = image_entry
+
+ model_response.data.append(
+ ImageObject(
+ url=url,
+ b64_json=None,
+ )
+ )
+
+ if hasattr(model_response, "_hidden_params") and "seed" in response_data:
+ model_response._hidden_params["seed"] = response_data["seed"]
+
+ return model_response
+
+
diff --git a/litellm/llms/gemini/chat/transformation.py b/litellm/llms/gemini/chat/transformation.py
index e889126883c..c5e2d8b3dac 100644
--- a/litellm/llms/gemini/chat/transformation.py
+++ b/litellm/llms/gemini/chat/transformation.py
@@ -99,7 +99,7 @@ class GoogleAIStudioGeminiConfig(VertexGeminiConfig):
return supported_params
def _transform_messages(
- self, messages: List[AllMessageValues]
+ self, messages: List[AllMessageValues], model: Optional[str] = None
) -> List[ContentType]:
"""
Google AI Studio Gemini does not support HTTP/HTTPS URLs for files.
@@ -140,4 +140,4 @@ class GoogleAIStudioGeminiConfig(VertexGeminiConfig):
except Exception:
# If conversion fails, leave as is and let the API handle it
pass
- return _gemini_convert_messages_with_history(messages=messages)
+ return _gemini_convert_messages_with_history(messages=messages, model=model)
diff --git a/litellm/llms/github_copilot/responses/transformation.py b/litellm/llms/github_copilot/responses/transformation.py
new file mode 100644
index 00000000000..a85c37fd9b8
--- /dev/null
+++ b/litellm/llms/github_copilot/responses/transformation.py
@@ -0,0 +1,304 @@
+"""
+GitHub Copilot Responses API Configuration.
+
+This module provides the configuration for GitHub Copilot's Responses API,
+which is required for models like gpt-5.1-codex that only support the /responses endpoint.
+
+Implementation based on analysis of the copilot-api project by caozhiyuan:
+https://github.com/caozhiyuan/copilot-api
+"""
+from typing import TYPE_CHECKING, Any, Dict, Optional, Union
+from uuid import uuid4
+
+from litellm._logging import verbose_logger
+from litellm.exceptions import AuthenticationError
+from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
+from litellm.types.llms.openai import (
+ ResponseInputParam,
+ ResponsesAPIOptionalRequestParams,
+)
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.utils import LlmProviders
+
+from ..authenticator import Authenticator
+from ..common_utils import GetAPIKeyError
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+ LiteLLMLoggingObj = Any
+
+# GitHub Copilot API Constants (from copilot-api)
+COPILOT_VERSION = "0.26.7"
+EDITOR_PLUGIN_VERSION = f"copilot-chat/{COPILOT_VERSION}"
+USER_AGENT = f"GitHubCopilotChat/{COPILOT_VERSION}"
+API_VERSION = "2025-04-01"
+
+
+class GithubCopilotResponsesAPIConfig(OpenAIResponsesAPIConfig):
+ """
+ Configuration for GitHub Copilot's Responses API.
+
+ Inherits from OpenAIResponsesAPIConfig since GitHub Copilot's Responses API
+ is compatible with OpenAI's Responses API specification.
+
+ Key differences from OpenAI:
+ - Uses OAuth Device Flow authentication (handled by Authenticator)
+ - Uses api.githubcopilot.com as the API base
+ - Requires specific headers for VSCode/Copilot integration
+ - Supports vision requests with special header
+ - Requires X-Initiator header based on input analysis
+
+ Reference: https://api.githubcopilot.com/
+ """
+
+ GITHUB_COPILOT_API_BASE = "https://api.githubcopilot.com"
+
+ def __init__(self) -> None:
+ super().__init__()
+ self.authenticator = Authenticator()
+
+ @property
+ def custom_llm_provider(self) -> LlmProviders:
+ """Return the GitHub Copilot provider identifier."""
+ return LlmProviders.GITHUB_COPILOT
+
+ def get_supported_openai_params(self, model: str) -> list:
+ """
+ Get supported parameters for GitHub Copilot Responses API.
+
+ GitHub Copilot supports all standard OpenAI Responses API parameters.
+ """
+ return super().get_supported_openai_params(model)
+
+ def map_openai_params(
+ self,
+ response_api_optional_params: ResponsesAPIOptionalRequestParams,
+ model: str,
+ drop_params: bool,
+ ) -> Dict:
+ """
+ Map parameters for GitHub Copilot Responses API.
+
+ GitHub Copilot uses the same parameter format as OpenAI,
+ so no transformation is needed.
+ """
+ return dict(response_api_optional_params)
+
+ def validate_environment(
+ self,
+ headers: dict,
+ model: str,
+ litellm_params: Optional[GenericLiteLLMParams],
+ ) -> dict:
+ """
+ Validate environment and set up headers for GitHub Copilot API.
+
+ Uses the Authenticator to obtain GitHub Copilot API key via OAuth Device Flow,
+ then configures all required headers for the Responses API.
+
+ Headers include:
+ - Authorization with API key
+ - Standard GitHub Copilot headers (editor-version, user-agent, etc.)
+ - X-Initiator based on input analysis
+ - copilot-vision-request if vision content detected
+ - User-provided extra_headers (merged with priority)
+ """
+ try:
+ # Get GitHub Copilot API key via OAuth
+ api_key = self.authenticator.get_api_key()
+
+ if not api_key:
+ raise AuthenticationError(
+ model=model,
+ llm_provider="github_copilot",
+ message="GitHub Copilot API key is required. Please authenticate via OAuth Device Flow.",
+ )
+
+ # Get default headers (from copilot-api configuration)
+ default_headers = self._get_default_headers(api_key)
+
+ # Merge with existing headers (user's extra_headers take priority)
+ merged_headers = {**default_headers, **headers}
+
+ # Analyze input to determine additional headers
+ input_param = self._get_input_from_params(litellm_params)
+
+ # Add X-Initiator header based on input analysis
+ if input_param is not None:
+ initiator = self._get_initiator(input_param)
+ merged_headers["X-Initiator"] = initiator
+ verbose_logger.debug(
+ f"GitHub Copilot Responses API: Set X-Initiator={initiator}"
+ )
+
+ # Add vision header if input contains images
+ if self._has_vision_input(input_param):
+ merged_headers["copilot-vision-request"] = "true"
+ verbose_logger.debug(
+ "GitHub Copilot Responses API: Enabled vision request"
+ )
+
+ verbose_logger.debug(
+ f"GitHub Copilot Responses API: Successfully configured headers for model {model}"
+ )
+
+ return merged_headers
+
+ except GetAPIKeyError as e:
+ raise AuthenticationError(
+ model=model,
+ llm_provider="github_copilot",
+ message=str(e),
+ )
+
+ def get_complete_url(
+ self,
+ api_base: Optional[str],
+ litellm_params: dict,
+ ) -> str:
+ """
+ Get the complete URL for GitHub Copilot Responses API endpoint.
+
+ Returns: https://api.githubcopilot.com/responses
+
+ Note: Currently only supports individual accounts.
+ Business/enterprise accounts (api.business.githubcopilot.com) can be
+ added in the future by detecting account type.
+ """
+ # Use provided api_base or fall back to authenticator's base or default
+ api_base = (
+ api_base
+ or self.authenticator.get_api_base()
+ or self.GITHUB_COPILOT_API_BASE
+ )
+
+ # Remove trailing slashes
+ api_base = api_base.rstrip("/")
+
+ # Return the responses endpoint
+ return f"{api_base}/responses"
+
+ # ==================== Helper Methods ====================
+
+ def _get_default_headers(self, api_key: str) -> Dict[str, str]:
+ """
+ Get default headers for GitHub Copilot Responses API.
+
+ Based on copilot-api's header configuration.
+ """
+ return {
+ "Authorization": f"Bearer {api_key}",
+ "content-type": "application/json",
+ "copilot-integration-id": "vscode-chat",
+ "editor-version": "vscode/1.95.0", # Fixed version for stability
+ "editor-plugin-version": EDITOR_PLUGIN_VERSION,
+ "user-agent": USER_AGENT,
+ "openai-intent": "conversation-panel",
+ "x-github-api-version": API_VERSION,
+ "x-request-id": str(uuid4()),
+ "x-vscode-user-agent-library-version": "electron-fetch",
+ }
+
+ def _get_input_from_params(
+ self, litellm_params: Optional[GenericLiteLLMParams]
+ ) -> Optional[Union[str, ResponseInputParam]]:
+ """
+ Extract input parameter from litellm_params.
+
+ The input parameter contains the conversation history and is needed
+ for vision detection and initiator determination.
+ """
+ if litellm_params is None:
+ return None
+
+ # Try to get input from litellm_params
+ # This might be in different locations depending on how LiteLLM structures it
+ if hasattr(litellm_params, "input"):
+ return litellm_params.input
+
+ # If not found, return None and let the API handle it
+ return None
+
+ def _get_initiator(self, input_param: Union[str, ResponseInputParam]) -> str:
+ """
+ Determine X-Initiator header value based on input analysis.
+
+ Based on copilot-api's hasAgentInitiator logic:
+ - Returns "agent" if input contains assistant role or items without role
+ - Returns "user" otherwise
+
+ Args:
+ input_param: The input parameter (string or list of input items)
+
+ Returns:
+ "agent" or "user"
+ """
+ # If input is a string, it's user-initiated
+ if isinstance(input_param, str):
+ return "user"
+
+ # If input is a list, analyze items
+ if isinstance(input_param, list):
+ for item in input_param:
+ if not isinstance(item, dict):
+ continue
+
+ # Check if item has no role (agent-initiated)
+ if "role" not in item or not item.get("role"):
+ return "agent"
+
+ # Check if role is assistant (agent-initiated)
+ role = item.get("role")
+ if isinstance(role, str) and role.lower() == "assistant":
+ return "agent"
+
+ # Default to user-initiated
+ return "user"
+
+ def _has_vision_input(self, input_param: Union[str, ResponseInputParam]) -> bool:
+ """
+ Check if input contains vision content (images).
+
+ Based on copilot-api's hasVisionInput and containsVisionContent logic.
+ Recursively searches for input_image type in the input structure.
+
+ Args:
+ input_param: The input parameter to analyze
+
+ Returns:
+ True if input contains image content, False otherwise
+ """
+ return self._contains_vision_content(input_param)
+
+ def _contains_vision_content(self, value: Any) -> bool:
+ """
+ Recursively check if a value contains vision content.
+
+ Looks for items with type="input_image" in the structure.
+ """
+ if value is None:
+ return False
+
+ # Check arrays
+ if isinstance(value, list):
+ return any(self._contains_vision_content(item) for item in value)
+
+ # Only check dict/object types
+ if not isinstance(value, dict):
+ return False
+
+ # Check if this item is an input_image
+ item_type = value.get("type")
+ if isinstance(item_type, str) and item_type.lower() == "input_image":
+ return True
+
+ # Check content field recursively
+ if "content" in value and isinstance(value["content"], list):
+ return any(
+ self._contains_vision_content(item) for item in value["content"]
+ )
+
+ return False
diff --git a/litellm/llms/oci/chat/transformation.py b/litellm/llms/oci/chat/transformation.py
index 167ba26bacb..f0e2db9a08b 100644
--- a/litellm/llms/oci/chat/transformation.py
+++ b/litellm/llms/oci/chat/transformation.py
@@ -765,9 +765,10 @@ class OCIChatConfig(BaseConfig):
)
if oci_serving_mode == "DEDICATED":
+ oci_endpoint_id = optional_params.get("oci_endpoint_id", model)
servingMode = OCIServingMode(
servingType="DEDICATED",
- endpointId=model,
+ endpointId=oci_endpoint_id,
)
else:
servingMode = OCIServingMode(
diff --git a/litellm/llms/openai/chat/gpt_5_transformation.py b/litellm/llms/openai/chat/gpt_5_transformation.py
index 183f60debbd..d18f898cf1c 100644
--- a/litellm/llms/openai/chat/gpt_5_transformation.py
+++ b/litellm/llms/openai/chat/gpt_5_transformation.py
@@ -30,7 +30,7 @@ class OpenAIGPT5Config(OpenAIGPTConfig):
from litellm.utils import supports_tool_choice
base_gpt_series_params = super().get_supported_openai_params(model=model)
- gpt_5_only_params = ["reasoning_effort"]
+ gpt_5_only_params = ["reasoning_effort", "verbosity"]
base_gpt_series_params.extend(gpt_5_only_params)
if not supports_tool_choice(model=model):
base_gpt_series_params.remove("tool_choice")
diff --git a/litellm/llms/openai/transcriptions/handler.py b/litellm/llms/openai/transcriptions/handler.py
index 4d60b8a8310..e241d2c1c7d 100644
--- a/litellm/llms/openai/transcriptions/handler.py
+++ b/litellm/llms/openai/transcriptions/handler.py
@@ -1,10 +1,13 @@
-from typing import Optional, Union, cast
+from typing import TYPE_CHECKING, Optional, Union, cast
import httpx
from openai import AsyncOpenAI, OpenAI
from pydantic import BaseModel
import litellm
+
+if TYPE_CHECKING:
+ from aiohttp import ClientSession
from litellm.litellm_core_utils.audio_utils.utils import get_audio_file_name
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.llms.base_llm.audio_transcription.transformation import (
@@ -89,6 +92,7 @@ class OpenAIAudioTranscription(OpenAIChatCompletion):
client=None,
atranscription: bool = False,
provider_config: Optional[BaseAudioTranscriptionConfig] = None,
+ shared_session: Optional["ClientSession"] = None,
) -> TranscriptionResponse:
"""
Handle audio transcription request
@@ -116,6 +120,7 @@ class OpenAIAudioTranscription(OpenAIChatCompletion):
client=client,
max_retries=max_retries,
logging_obj=logging_obj,
+ shared_session=shared_session,
)
openai_client: OpenAI = self._get_openai_client( # type: ignore
@@ -170,6 +175,7 @@ class OpenAIAudioTranscription(OpenAIChatCompletion):
api_base: Optional[str] = None,
client=None,
max_retries=None,
+ shared_session: Optional["ClientSession"] = None,
):
try:
openai_aclient: AsyncOpenAI = self._get_openai_client( # type: ignore
@@ -179,6 +185,7 @@ class OpenAIAudioTranscription(OpenAIChatCompletion):
timeout=timeout,
max_retries=max_retries,
client=client,
+ shared_session=shared_session,
)
## LOGGING
diff --git a/litellm/llms/openai/vector_store_files/transformation.py b/litellm/llms/openai/vector_store_files/transformation.py
new file mode 100644
index 00000000000..8953e404f3e
--- /dev/null
+++ b/litellm/llms/openai/vector_store_files/transformation.py
@@ -0,0 +1,258 @@
+from typing import Any, Dict, Optional, Tuple, cast
+
+import httpx
+
+import litellm
+from litellm.llms.base_llm.vector_store_files.transformation import (
+ BaseVectorStoreFilesConfig,
+)
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.vector_store_files import (
+ VectorStoreFileAuthCredentials,
+ VectorStoreFileContentResponse,
+ VectorStoreFileCreateRequest,
+ VectorStoreFileDeleteResponse,
+ VectorStoreFileListQueryParams,
+ VectorStoreFileListResponse,
+ VectorStoreFileObject,
+ VectorStoreFileUpdateRequest,
+)
+from litellm.utils import add_openai_metadata
+
+
+def _clean_dict(source: Dict[str, Any]) -> Dict[str, Any]:
+ return {k: v for k, v in source.items() if v is not None}
+
+
+class OpenAIVectorStoreFilesConfig(BaseVectorStoreFilesConfig):
+ ASSISTANTS_HEADER_KEY = "OpenAI-Beta"
+ ASSISTANTS_HEADER_VALUE = "assistants=v2"
+
+ def get_auth_credentials(
+ self, litellm_params: Dict[str, Any]
+ ) -> VectorStoreFileAuthCredentials:
+ api_key = litellm_params.get("api_key")
+ if api_key is None:
+ raise ValueError("api_key is required")
+ return {
+ "headers": {
+ "Authorization": f"Bearer {api_key}",
+ }
+ }
+
+ def get_vector_store_file_endpoints_by_type(self) -> Dict[
+ str, Tuple[Tuple[str, str], ...]
+ ]:
+ return {
+ "read": (
+ ("GET", "/vector_stores/{vector_store_id}/files"),
+ ("GET", "/vector_stores/{vector_store_id}/files/{file_id}"),
+ (
+ "GET",
+ "/vector_stores/{vector_store_id}/files/{file_id}/content",
+ ),
+ ),
+ "write": (
+ ("POST", "/vector_stores/{vector_store_id}/files"),
+ ("POST", "/vector_stores/{vector_store_id}/files/{file_id}"),
+ ("DELETE", "/vector_stores/{vector_store_id}/files/{file_id}"),
+ ),
+ }
+
+ def validate_environment(
+ self,
+ *,
+ headers: Dict[str, str],
+ litellm_params: Optional[GenericLiteLLMParams],
+ ) -> Dict[str, str]:
+ litellm_params = litellm_params or GenericLiteLLMParams()
+ api_key = (
+ litellm_params.api_key
+ or litellm.api_key
+ or litellm.openai_key
+ or get_secret_str("OPENAI_API_KEY")
+ )
+ headers.update(
+ {
+ "Authorization": f"Bearer {api_key}",
+ "Content-Type": "application/json",
+ }
+ )
+ if self.ASSISTANTS_HEADER_KEY not in headers:
+ headers[self.ASSISTANTS_HEADER_KEY] = self.ASSISTANTS_HEADER_VALUE
+ return headers
+
+ def get_complete_url(
+ self,
+ *,
+ api_base: Optional[str],
+ vector_store_id: str,
+ litellm_params: Dict[str, Any],
+ ) -> str:
+ base_url = (
+ api_base
+ or litellm.api_base
+ or get_secret_str("OPENAI_BASE_URL")
+ or get_secret_str("OPENAI_API_BASE")
+ or "https://api.openai.com/v1"
+ )
+ base_url = base_url.rstrip("/")
+ return f"{base_url}/vector_stores/{vector_store_id}/files"
+
+ def transform_create_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ create_request: VectorStoreFileCreateRequest,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ payload: Dict[str, Any] = _clean_dict(dict(create_request))
+ attributes = payload.get("attributes")
+ if isinstance(attributes, dict):
+ filtered_attributes = add_openai_metadata(attributes)
+ if filtered_attributes is not None:
+ payload["attributes"] = filtered_attributes
+ else:
+ payload.pop("attributes", None)
+ url = api_base
+ return url, payload
+
+ def transform_create_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ try:
+ return cast(VectorStoreFileObject, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
+
+ def transform_list_vector_store_files_request(
+ self,
+ *,
+ vector_store_id: str,
+ query_params: VectorStoreFileListQueryParams,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ params = _clean_dict(dict(query_params))
+ return api_base, params
+
+ def transform_list_vector_store_files_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileListResponse:
+ try:
+ return cast(VectorStoreFileListResponse, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
+
+ def transform_retrieve_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ return f"{api_base}/{file_id}", {}
+
+ def transform_retrieve_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ try:
+ return cast(VectorStoreFileObject, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
+
+ def transform_retrieve_vector_store_file_content_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ return f"{api_base}/{file_id}/content", {}
+
+ def transform_retrieve_vector_store_file_content_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileContentResponse:
+ try:
+ return cast(VectorStoreFileContentResponse, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
+
+ def transform_update_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ update_request: VectorStoreFileUpdateRequest,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ payload: Dict[str, Any] = dict(update_request)
+ attributes = payload.get("attributes")
+ if isinstance(attributes, dict):
+ filtered_attributes = add_openai_metadata(attributes)
+ if filtered_attributes is not None:
+ payload["attributes"] = filtered_attributes
+ else:
+ payload.pop("attributes", None)
+ return f"{api_base}/{file_id}", payload
+
+ def transform_update_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileObject:
+ try:
+ return cast(VectorStoreFileObject, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
+
+ def transform_delete_vector_store_file_request(
+ self,
+ *,
+ vector_store_id: str,
+ file_id: str,
+ api_base: str,
+ ) -> Tuple[str, Dict[str, Any]]:
+ return f"{api_base}/{file_id}", {}
+
+ def transform_delete_vector_store_file_response(
+ self,
+ *,
+ response: httpx.Response,
+ ) -> VectorStoreFileDeleteResponse:
+ try:
+ return cast(VectorStoreFileDeleteResponse, response.json())
+ except Exception as exc: # noqa: BLE001
+ raise self.get_error_class(
+ error_message=str(exc),
+ status_code=response.status_code,
+ headers=response.headers,
+ )
diff --git a/litellm/llms/openai/vector_stores/transformation.py b/litellm/llms/openai/vector_stores/transformation.py
index 5689e249bc0..c763ed1c8da 100644
--- a/litellm/llms/openai/vector_stores/transformation.py
+++ b/litellm/llms/openai/vector_stores/transformation.py
@@ -145,6 +145,8 @@ class OpenAIVectorStoreConfig(BaseVectorStoreConfig):
) -> Tuple[str, Dict]:
url = api_base # Base URL for creating vector stores
metadata = vector_store_create_optional_params.get("metadata", None)
+ metadata_payload = add_openai_metadata(metadata)
+
typed_request_body = VectorStoreCreateRequest(
name=vector_store_create_optional_params.get("name", None),
file_ids=vector_store_create_optional_params.get("file_ids", None),
@@ -154,7 +156,7 @@ class OpenAIVectorStoreConfig(BaseVectorStoreConfig):
chunking_strategy=vector_store_create_optional_params.get(
"chunking_strategy", None
),
- metadata=add_openai_metadata(metadata) if metadata is not None else None,
+ metadata=metadata_payload,
)
dict_request_body = cast(dict, typed_request_body)
diff --git a/litellm/llms/openai/videos/transformation.py b/litellm/llms/openai/videos/transformation.py
index 9848477f32d..d1d3fc2919e 100644
--- a/litellm/llms/openai/videos/transformation.py
+++ b/litellm/llms/openai/videos/transformation.py
@@ -4,6 +4,7 @@ from typing import cast
import httpx
from httpx._types import RequestFiles
+from litellm.llms.base_llm.videos.transformation import BaseVideoConfig
from litellm.types.videos.main import VideoCreateOptionalRequestParams
from litellm.types.llms.openai import CreateVideoRequest
from litellm.types.router import GenericLiteLLMParams
@@ -15,15 +16,12 @@ from litellm.llms.openai.image_edit.transformation import ImageEditRequestUtils
if TYPE_CHECKING:
from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
- from ...base_llm.videos.transformation import BaseVideoConfig as _BaseVideoConfig
from ...base_llm.chat.transformation import BaseLLMException as _BaseLLMException
LiteLLMLoggingObj = _LiteLLMLoggingObj
- BaseVideoConfig = _BaseVideoConfig
BaseLLMException = _BaseLLMException
else:
LiteLLMLoggingObj = Any
- BaseVideoConfig = Any
BaseLLMException = Any
@@ -178,10 +176,10 @@ class OpenAIVideoConfig(BaseVideoConfig):
# Construct the URL for video content download
url = f"{api_base.rstrip('/')}/{original_video_id}/content"
- # Add video_id as query parameter
- params = {"video_id": original_video_id}
-
- return url, params
+ # No additional data needed for GET content request
+ data: Dict[str, Any] = {}
+
+ return url, data
def transform_video_remix_request(
self,
@@ -404,4 +402,4 @@ class OpenAIVideoConfig(BaseVideoConfig):
if isinstance(image, BufferedReader):
files_list.append((field_name, (image.name, image, image_content_type)))
else:
- files_list.append((field_name, ("input_reference.png", image, image_content_type)))
\ No newline at end of file
+ files_list.append((field_name, ("input_reference.png", image, image_content_type)))
diff --git a/litellm/llms/snowflake/chat/transformation.py b/litellm/llms/snowflake/chat/transformation.py
index 4c0258d9f4b..62ede0aeaf8 100644
--- a/litellm/llms/snowflake/chat/transformation.py
+++ b/litellm/llms/snowflake/chat/transformation.py
@@ -7,12 +7,14 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import httpx
-from litellm.secret_managers.main import get_secret_str
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ChatCompletionMessageToolCall, Function, ModelResponse
from ...openai_like.chat.transformation import OpenAIGPTConfig
+from ..utils import SnowflakeBaseConfig
+
+
if TYPE_CHECKING:
from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
@@ -21,7 +23,7 @@ else:
LiteLLMLoggingObj = Any
-class SnowflakeConfig(OpenAIGPTConfig):
+class SnowflakeConfig(SnowflakeBaseConfig, OpenAIGPTConfig):
"""
Reference: https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-llm-rest-api
@@ -33,40 +35,6 @@ class SnowflakeConfig(OpenAIGPTConfig):
def get_config(cls):
return super().get_config()
- def get_supported_openai_params(self, model: str) -> List[str]:
- return [
- "temperature",
- "max_tokens",
- "top_p",
- "response_format",
- "tools",
- "tool_choice",
- ]
-
- def map_openai_params(
- self,
- non_default_params: dict,
- optional_params: dict,
- model: str,
- drop_params: bool,
- ) -> dict:
- """
- If any supported_openai_params are in non_default_params, add them to optional_params, so they are used in API call
-
- Args:
- non_default_params (dict): Non-default parameters to filter.
- optional_params (dict): Optional parameters to update.
- model (str): Model name for parameter support check.
-
- Returns:
- dict: Updated optional_params with supported non-default parameters.
- """
- supported_openai_params = self.get_supported_openai_params(model)
- for param, value in non_default_params.items():
- if param in supported_openai_params:
- optional_params[param] = value
- return optional_params
-
def _transform_tool_calls_from_snowflake_to_openai(
self, content_list: List[Dict[str, Any]]
) -> Tuple[str, Optional[List[ChatCompletionMessageToolCall]]]:
@@ -169,53 +137,6 @@ class SnowflakeConfig(OpenAIGPTConfig):
returned_response._hidden_params["model"] = model
return returned_response
- def validate_environment(
- self,
- headers: dict,
- model: str,
- messages: List[AllMessageValues],
- optional_params: dict,
- litellm_params: dict,
- api_key: Optional[str] = None,
- api_base: Optional[str] = None,
- ) -> dict:
- """
- Return headers to use for Snowflake completion request
-
- Snowflake REST API Ref: https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-llm-rest-api#api-reference
- Expected headers:
- {
- "Content-Type": "application/json",
- "Accept": "application/json",
- "Authorization": "Bearer " + ,
- "X-Snowflake-Authorization-Token-Type": "KEYPAIR_JWT"
- }
- """
-
- if api_key is None:
- raise ValueError("Missing Snowflake JWT key")
-
- headers.update(
- {
- "Content-Type": "application/json",
- "Accept": "application/json",
- "Authorization": "Bearer " + api_key,
- "X-Snowflake-Authorization-Token-Type": "KEYPAIR_JWT",
- }
- )
- return headers
-
- def _get_openai_compatible_provider_info(
- self, api_base: Optional[str], api_key: Optional[str]
- ) -> Tuple[Optional[str], Optional[str]]:
- api_base = (
- api_base
- or f"""https://{get_secret_str("SNOWFLAKE_ACCOUNT_ID")}.snowflakecomputing.com/api/v2/cortex/inference:complete"""
- or get_secret_str("SNOWFLAKE_API_BASE")
- )
- dynamic_api_key = api_key or get_secret_str("SNOWFLAKE_JWT")
- return api_base, dynamic_api_key
-
def get_complete_url(
self,
api_base: Optional[str],
@@ -228,10 +149,10 @@ class SnowflakeConfig(OpenAIGPTConfig):
"""
If api_base is not provided, use the default DeepSeek /chat/completions endpoint.
"""
- if not api_base:
- api_base = f"""https://{get_secret_str("SNOWFLAKE_ACCOUNT_ID")}.snowflakecomputing.com/api/v2/cortex/inference:complete"""
- return api_base
+ api_base = self._get_api_base(api_base, optional_params)
+
+ return f"{api_base}/cortex/inference:complete"
def _transform_tools(self, tools: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""
@@ -279,9 +200,7 @@ class SnowflakeConfig(OpenAIGPTConfig):
}
# Add description if present
if "description" in function:
- snowflake_tool["tool_spec"]["description"] = function[
- "description"
- ]
+ snowflake_tool["tool_spec"]["description"] = function["description"]
snowflake_tools.append(snowflake_tool)
diff --git a/litellm/llms/snowflake/embedding/transformation.py b/litellm/llms/snowflake/embedding/transformation.py
new file mode 100644
index 00000000000..83716f3ef26
--- /dev/null
+++ b/litellm/llms/snowflake/embedding/transformation.py
@@ -0,0 +1,69 @@
+from typing import Optional, Union
+
+import httpx
+
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+from litellm.types.llms.openai import AllEmbeddingInputValues
+from litellm.types.utils import EmbeddingResponse
+
+from ..utils import SnowflakeException, SnowflakeBaseConfig
+
+
+class SnowflakeEmbeddingConfig(SnowflakeBaseConfig, BaseEmbeddingConfig):
+ """
+ source: https://docs.snowflake.com/developer-guide/snowflake-rest-api/reference/cortex-embed
+ """
+
+ def get_complete_url(
+ self,
+ api_base: Optional[str],
+ api_key: Optional[str],
+ model: str,
+ optional_params: dict,
+ litellm_params: dict,
+ stream: Optional[bool] = None,
+ ) -> str:
+ api_base = self._get_api_base(api_base, optional_params)
+
+ return f"{api_base}/cortex/inference:embed"
+
+ def transform_embedding_request(
+ self,
+ model: str,
+ input: AllEmbeddingInputValues,
+ optional_params: dict,
+ headers: dict,
+ ) -> dict:
+ return {"text": input, "model": model, **optional_params}
+
+ def transform_embedding_response(
+ self,
+ model: str,
+ raw_response: httpx.Response,
+ model_response: EmbeddingResponse,
+ logging_obj: LiteLLMLoggingObj,
+ api_key: Optional[str],
+ request_data: dict,
+ optional_params: dict,
+ litellm_params: dict,
+ ) -> EmbeddingResponse:
+ response_json = raw_response.json()
+ # convert embeddings to 1d array
+ for item in response_json["data"]:
+ item["embedding"] = item["embedding"][0]
+ returned_response = EmbeddingResponse(**response_json)
+
+ returned_response.model = "snowflake/" + (returned_response.model or "")
+
+ if model is not None:
+ returned_response._hidden_params["model"] = model
+ return returned_response
+
+ def get_error_class(
+ self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
+ ) -> BaseLLMException:
+ return SnowflakeException(
+ message=error_message, status_code=status_code, headers=headers
+ )
diff --git a/litellm/llms/snowflake/utils.py b/litellm/llms/snowflake/utils.py
new file mode 100644
index 00000000000..9d458f6ece3
--- /dev/null
+++ b/litellm/llms/snowflake/utils.py
@@ -0,0 +1,118 @@
+from typing import TYPE_CHECKING, Any, List, Optional, Tuple
+
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+ LiteLLMLoggingObj = Any
+
+
+class SnowflakeException(BaseLLMException):
+ """Snowflake AI Endpoints exception handling class"""
+
+ pass
+
+
+class SnowflakeBaseConfig:
+ def get_supported_openai_params(self, model: str) -> List[str]:
+ return [
+ "temperature",
+ "max_tokens",
+ "top_p",
+ "response_format",
+ "tools",
+ "tool_choice",
+ ]
+
+ def map_openai_params(
+ self,
+ non_default_params: dict,
+ optional_params: dict,
+ model: str,
+ drop_params: bool,
+ ) -> dict:
+ """
+ If any supported_openai_params are in non_default_params, add them to optional_params, so they are used in API call
+
+ Args:
+ non_default_params (dict): Non-default parameters to filter.
+ optional_params (dict): Optional parameters to update.
+ model (str): Model name for parameter support check.
+
+ Returns:
+ dict: Updated optional_params with supported non-default parameters.
+ """
+ supported_openai_params = self.get_supported_openai_params(model)
+ for param, value in non_default_params.items():
+ if param in supported_openai_params:
+ optional_params[param] = value
+ return optional_params
+
+ def _get_api_base(self, api_base, optional_params):
+ if not api_base:
+ if "account_id" in optional_params:
+ account_id = optional_params.pop("account_id")
+ else:
+ account_id = get_secret_str("SNOWFLAKE_ACCOUNT_ID")
+ if account_id is None:
+ raise ValueError("Missing snowflake account_id")
+ api_base = f"https://{account_id}.snowflakecomputing.com/api/v2"
+
+ api_base = api_base.rstrip("/")
+ if not api_base.endswith("/api/v2"):
+ api_base += "/api/v2"
+ return api_base
+
+ def validate_environment(
+ self,
+ headers: dict,
+ model: str,
+ messages: List[AllMessageValues],
+ optional_params: dict,
+ litellm_params: dict,
+ api_key: Optional[str] = None,
+ api_base: Optional[str] = None,
+ ) -> dict:
+ """
+ Return headers to use for Snowflake completion request
+
+ Snowflake REST API Ref: https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-llm-rest-api#api-reference
+ Expected headers:
+ {
+ "Content-Type": "application/json",
+ "Accept": "application/json",
+ "Authorization": "Bearer " + ,
+ "X-Snowflake-Authorization-Token-Type": "KEYPAIR_JWT"
+ }
+ """
+
+ auth_type = "KEYPAIR_JWT"
+
+ if api_key is None:
+ raise ValueError("Missing Snowflake JWT key")
+ else:
+ pat_key_prefix = "pat/"
+ if api_key.startswith(pat_key_prefix):
+ api_key = api_key[len(pat_key_prefix) :]
+ auth_type = "PROGRAMMATIC_ACCESS_TOKEN"
+
+ headers.update(
+ {
+ "Content-Type": "application/json",
+ "Accept": "application/json",
+ "Authorization": "Bearer " + api_key,
+ "X-Snowflake-Authorization-Token-Type": auth_type,
+ }
+ )
+ return headers
+
+ def _get_openai_compatible_provider_info(
+ self, api_base: Optional[str], api_key: Optional[str]
+ ) -> Tuple[Optional[str], Optional[str]]:
+ dynamic_api_key = api_key or get_secret_str("SNOWFLAKE_JWT")
+ return api_base, dynamic_api_key
diff --git a/litellm/llms/vertex_ai/context_caching/transformation.py b/litellm/llms/vertex_ai/context_caching/transformation.py
index bb40b7665c1..bc5c1b451f1 100644
--- a/litellm/llms/vertex_ai/context_caching/transformation.py
+++ b/litellm/llms/vertex_ai/context_caching/transformation.py
@@ -173,7 +173,7 @@ def transform_openai_messages_to_gemini_context_caching(
supports_system_message=supports_system_message, messages=messages
)
- transformed_messages = _gemini_convert_messages_with_history(messages=new_messages)
+ transformed_messages = _gemini_convert_messages_with_history(messages=new_messages, model=model)
model_name = "models/{}".format(model)
diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py
index 08c91a6fad1..e4fcd35b954 100644
--- a/litellm/llms/vertex_ai/gemini/transformation.py
+++ b/litellm/llms/vertex_ai/gemini/transformation.py
@@ -64,7 +64,25 @@ else:
LiteLLMLoggingObj = Any
-def _process_gemini_image(image_url: str, format: Optional[str] = None) -> PartType:
+def _map_openai_detail_to_media_resolution(
+ detail: Optional[str],
+) -> Optional[Literal["low", "medium", "high"]]:
+ """
+ Map OpenAI's "detail" parameter to Gemini's "media_resolution" parameter.
+ """
+ if detail == "low":
+ return "low"
+ elif detail == "high":
+ return "high"
+ # "auto" or None means let the model decide, so we don't set media_resolution
+ return None
+
+
+def _process_gemini_image(
+ image_url: str,
+ format: Optional[str] = None,
+ media_resolution: Optional[Literal["low", "medium", "high"]] = None,
+) -> PartType:
"""
Given an image URL, return the appropriate PartType for Gemini
"""
@@ -99,8 +117,19 @@ def _process_gemini_image(image_url: str, format: Optional[str] = None) -> PartT
elif "http://" in image_url or "https://" in image_url or "base64" in image_url:
# https links for unsupported mime types and base64 images
image = convert_to_anthropic_image_obj(image_url, format=format)
- _blob = BlobType(data=image["data"], mime_type=image["media_type"])
- return PartType(inline_data=_blob)
+ _blob: BlobType = {"data": image["data"], "mime_type": image["media_type"]}
+ if media_resolution is not None:
+ _blob["media_resolution"] = media_resolution
+
+ # Convert snake_case keys to camelCase for JSON serialization
+ # The TypedDict uses snake_case, but the API expects camelCase
+ _blob_dict = dict(_blob)
+ if "media_resolution" in _blob_dict:
+ _blob_dict["mediaResolution"] = _blob_dict.pop("media_resolution")
+ if "mime_type" in _blob_dict:
+ _blob_dict["mimeType"] = _blob_dict.pop("mime_type")
+
+ return PartType(inline_data=cast(BlobType, _blob_dict))
raise Exception("Invalid image received - {}".format(image_url))
except Exception as e:
raise e
@@ -166,6 +195,7 @@ def check_if_part_exists_in_parts(
def _gemini_convert_messages_with_history( # noqa: PLR0915
messages: List[AllMessageValues],
+ model: Optional[str] = None,
) -> List[ContentType]:
"""
Converts given messages from OpenAI format to Gemini format
@@ -205,13 +235,18 @@ def _gemini_convert_messages_with_history( # noqa: PLR0915
element = cast(ChatCompletionImageObject, element)
img_element = element
format: Optional[str] = None
+ media_resolution: Optional[Literal["low", "medium", "high"]] = None
if isinstance(img_element["image_url"], dict):
image_url = img_element["image_url"]["url"]
format = img_element["image_url"].get("format")
+ detail = img_element["image_url"].get("detail")
+ media_resolution = _map_openai_detail_to_media_resolution(detail)
else:
image_url = img_element["image_url"]
_part = _process_gemini_image(
- image_url=image_url, format=format
+ image_url=image_url,
+ format=format,
+ media_resolution=media_resolution,
)
_parts.append(_part)
elif element["type"] == "input_audio":
@@ -250,7 +285,8 @@ def _gemini_convert_messages_with_history( # noqa: PLR0915
)
try:
_part = _process_gemini_image(
- image_url=passed_file, format=format
+ image_url=passed_file,
+ format=format,
)
_parts.append(_part)
except Exception:
@@ -344,7 +380,7 @@ def _gemini_convert_messages_with_history( # noqa: PLR0915
or assistant_msg.get("function_call") is not None
): # support assistant tool invoke conversion
gemini_tool_call_parts = convert_to_gemini_tool_call_invoke(
- assistant_msg
+ assistant_msg, model=model
)
## check if gemini_tool_call already exists in assistant_content
for gemini_tool_call_part in gemini_tool_call_parts:
@@ -448,11 +484,11 @@ def _transform_request_body(
try:
if custom_llm_provider == "gemini":
content = litellm.GoogleAIStudioGeminiConfig()._transform_messages(
- messages=messages
+ messages=messages, model=model
)
else:
content = litellm.VertexGeminiConfig()._transform_messages(
- messages=messages
+ messages=messages, model=model
)
tools: Optional[Tools] = optional_params.pop("tools", None)
tool_choice: Optional[ToolConfig] = optional_params.pop("tool_choice", None)
diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
index cbd8cf320c7..d49d86f8ca4 100644
--- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
+++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
@@ -217,7 +217,22 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
@classmethod
def get_config(cls):
return super().get_config()
-
+
+ @staticmethod
+ def _is_gemini_3_or_newer(model: str) -> bool:
+ """
+ Check if the model is Gemini 3 Pro or newer.
+
+ Gemini 3 models include:
+ - gemini-3-pro-preview
+ - Any future Gemini 3.x models
+ """
+ # Check for Gemini 3 models
+ if "gemini-3" in model:
+ return True
+
+ return False
+
def _supports_penalty_parameters(self, model: str) -> bool:
unsupported_models = ["gemini-2.5-pro-preview-06-05"]
if model in unsupported_models:
@@ -245,11 +260,11 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
"parallel_tool_calls",
"web_search_options",
]
-
+
# Add penalty parameters only for non-preview models
if self._supports_penalty_parameters(model):
supported_params.extend(["frequency_penalty", "presence_penalty"])
-
+
if supports_reasoning(model):
supported_params.append("reasoning_effort")
supported_params.append("thinking")
@@ -293,14 +308,14 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
) -> Tuple[dict, Optional[dict]]:
"""
Extract location configuration from googleMaps tool for Vertex AI toolConfig.
-
+
Supports two interface styles:
1. Nested (recommended): {"enableWidget": "...", "retrievalConfig": {"latitude": ..., "longitude": ...}}
2. Flat (backward compat): {"enableWidget": "...", "latitude": ..., "longitude": ...}
-
+
Args:
google_maps_config: The googleMaps tool configuration from LiteLLM
-
+
Returns:
Tuple of (cleaned_google_maps_config, retrieval_config):
- cleaned_google_maps_config: googleMaps config without location fields
@@ -310,7 +325,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
latitude = google_maps_config.get("latitude")
longitude = google_maps_config.get("longitude")
language_code = google_maps_config.get("languageCode")
-
+
if latitude is not None and longitude is not None:
retrieval_config = {
"latLng": {
@@ -320,21 +335,17 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
}
if language_code is not None:
retrieval_config["languageCode"] = language_code
-
+
# Remove location fields from tool definition
cleaned_config = {
k: v
for k, v in google_maps_config.items()
if k not in ["latitude", "longitude", "languageCode"]
}
-
+
return cleaned_config, retrieval_config
-
- def get_tool_value(
- self,
- tool: dict,
- tool_name: str
- ) -> Optional[dict]:
+
+ def get_tool_value(self, tool: dict, tool_name: str) -> Optional[dict]:
"""
Helper function to get tool value handling both camelCase and underscore_case variants
@@ -358,19 +369,19 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
else:
return None
- def _map_function( # noqa: PLR0915
+ def _map_function( # noqa: PLR0915
self, value: List[dict], optional_params: dict
) -> List[Tools]:
"""
Map OpenAI-style tools/functions to Vertex AI format.
-
+
Args:
value: List of tool definitions
optional_params: Request-scoped parameters to store retrieval config
-
+
Returns:
List of mapped tools in Vertex AI format
-
+
Side effects:
May add 'toolConfig' with 'retrievalConfig' to optional_params if
googleMaps tools contain location data
@@ -417,25 +428,43 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
tool_name = list(tool.keys())[0] if len(tool.keys()) == 1 else None
if tool_name and (
- tool_name == "codeExecution" or tool_name == VertexToolName.CODE_EXECUTION.value
+ tool_name == "codeExecution"
+ or tool_name == VertexToolName.CODE_EXECUTION.value
): # code_execution maintained for backwards compatibility
code_execution = self.get_tool_value(tool, "codeExecution")
elif tool_name and tool_name == VertexToolName.GOOGLE_SEARCH.value:
- googleSearch = self.get_tool_value(tool, VertexToolName.GOOGLE_SEARCH.value)
- elif tool_name and tool_name == VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value:
- googleSearchRetrieval = self.get_tool_value(tool, VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value)
+ googleSearch = self.get_tool_value(
+ tool, VertexToolName.GOOGLE_SEARCH.value
+ )
+ elif (
+ tool_name and tool_name == VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value
+ ):
+ googleSearchRetrieval = self.get_tool_value(
+ tool, VertexToolName.GOOGLE_SEARCH_RETRIEVAL.value
+ )
elif tool_name and tool_name == VertexToolName.ENTERPRISE_WEB_SEARCH.value:
- enterpriseWebSearch = self.get_tool_value(tool, VertexToolName.ENTERPRISE_WEB_SEARCH.value)
- elif tool_name and (tool_name == VertexToolName.URL_CONTEXT.value or tool_name == "urlContext"):
+ enterpriseWebSearch = self.get_tool_value(
+ tool, VertexToolName.ENTERPRISE_WEB_SEARCH.value
+ )
+ elif tool_name and (
+ tool_name == VertexToolName.URL_CONTEXT.value
+ or tool_name == "urlContext"
+ ):
urlContext = self.get_tool_value(tool, tool_name)
elif tool_name and (
- tool_name == VertexToolName.GOOGLE_MAPS.value or tool_name == "google_maps"
+ tool_name == VertexToolName.GOOGLE_MAPS.value
+ or tool_name == "google_maps"
):
- google_maps_value = self.get_tool_value(tool, VertexToolName.GOOGLE_MAPS.value)
-
+ google_maps_value = self.get_tool_value(
+ tool, VertexToolName.GOOGLE_MAPS.value
+ )
+
# Extract and transform location configuration for toolConfig
if google_maps_value is not None:
- googleMaps, google_maps_retrieval_config = self._extract_google_maps_retrieval_config(
+ (
+ googleMaps,
+ google_maps_retrieval_config,
+ ) = self._extract_google_maps_retrieval_config(
google_maps_config=google_maps_value
)
elif openai_function_object is not None:
@@ -475,13 +504,15 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
_tools[VertexToolName.URL_CONTEXT.value] = urlContext
if googleMaps is not None:
_tools[VertexToolName.GOOGLE_MAPS.value] = googleMaps
-
+
# Add retrieval config to toolConfig if googleMaps has location data
if google_maps_retrieval_config is not None:
if "toolConfig" not in optional_params:
optional_params["toolConfig"] = {}
- optional_params["toolConfig"]["retrievalConfig"] = google_maps_retrieval_config
-
+ optional_params["toolConfig"][
+ "retrievalConfig"
+ ] = google_maps_retrieval_config
+
return [_tools]
def _map_response_schema(self, value: dict) -> dict:
@@ -575,10 +606,83 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
else:
raise ValueError(f"Invalid reasoning effort: {reasoning_effort}")
+ @staticmethod
+ def _map_reasoning_effort_to_thinking_level(
+ reasoning_effort: str,
+ model: Optional[str] = None,
+ ) -> GeminiThinkingConfig:
+ """
+ Map reasoning_effort to thinking_level for Gemini 3+ models.
+ Args:
+ reasoning_effort: The reasoning effort value
+ model: The model name
+
+ Returns:
+ GeminiThinkingConfig with thinkingLevel and includeThoughts
+ """
+ if reasoning_effort == "minimal":
+ return {"thinkingLevel": "low", "includeThoughts": True}
+ elif reasoning_effort == "low":
+ return {"thinkingLevel": "low", "includeThoughts": True}
+ elif reasoning_effort == "medium":
+ return {
+ "thinkingLevel": "high",
+ "includeThoughts": True,
+ } # medium is not out yet
+ elif reasoning_effort == "high":
+ return {"thinkingLevel": "high", "includeThoughts": True}
+ elif reasoning_effort == "disable":
+ # Gemini 3 cannot fully disable thinking, so we use "low" but hide thoughts
+ return {"thinkingLevel": "low", "includeThoughts": False}
+ elif reasoning_effort == "none":
+ return {"thinkingLevel": "low", "includeThoughts": False}
+ else:
+ raise ValueError(f"Invalid reasoning effort: {reasoning_effort}")
+
@staticmethod
def _is_thinking_budget_zero(thinking_budget: Optional[int]) -> bool:
return thinking_budget is not None and thinking_budget == 0
+ @staticmethod
+ def _validate_thinking_config_conflicts(
+ optional_params: Dict,
+ param_name: str,
+ param_description: str = "thinking_budget",
+ ) -> None:
+ """
+ Validate that thinking_level and thinking_budget are not both specified.
+ """
+ if "thinkingConfig" in optional_params:
+ existing_config = optional_params["thinkingConfig"]
+ if "thinkingLevel" in existing_config:
+ raise litellm.utils.UnsupportedParamsError(
+ message=(
+ f"Cannot specify both `{param_name}` (which maps to `{param_description}`) "
+ "and `thinking_level` in the same request. "
+ "For Gemini 3 models, use `thinking_level` instead."
+ ),
+ status_code=400,
+ )
+
+ @staticmethod
+ def _validate_thinking_level_conflicts(
+ optional_params: Dict,
+ ) -> None:
+ """
+ Validate that thinking_level and thinking_budget are not both specified.
+ Called when setting thinking_level.
+ """
+ if "thinkingConfig" in optional_params:
+ existing_config = optional_params["thinkingConfig"]
+ if "thinkingBudget" in existing_config:
+ raise litellm.utils.UnsupportedParamsError(
+ message=(
+ "Cannot specify both `thinking_level` and `thinking_budget` in the same request. "
+ "For Gemini 3 models, use `thinking_level` instead of `thinking_budget`."
+ ),
+ status_code=400,
+ )
+
@staticmethod
def _map_thinking_param(
thinking_param: AnthropicThinkingParam,
@@ -672,6 +776,13 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
) -> Dict:
for param, value in non_default_params.items():
if param == "temperature":
+ if VertexGeminiConfig._is_gemini_3_or_newer(model):
+ if value is not None and value < 1.0:
+ verbose_logger.info(
+ f"Warning: Setting temperature < 1.0 for Gemini 3 models ({model}) "
+ "can cause infinite loops, degraded reasoning performance, and failure on complex tasks. "
+ "Strongly recommended to use temperature = 1.0 (default)."
+ )
optional_params["temperature"] = value
elif param == "top_p":
optional_params["top_p"] = value
@@ -734,12 +845,31 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
elif param == "seed":
optional_params["seed"] = value
elif param == "reasoning_effort" and isinstance(value, str):
- optional_params[
- "thinkingConfig"
- ] = VertexGeminiConfig._map_reasoning_effort_to_thinking_budget(
- value, model
+ # Validate no conflict with thinking_level
+ VertexGeminiConfig._validate_thinking_config_conflicts(
+ optional_params=optional_params,
+ param_name="reasoning_effort",
+ param_description="thinking_budget",
)
+ if VertexGeminiConfig._is_gemini_3_or_newer(model):
+ optional_params[
+ "thinkingConfig"
+ ] = VertexGeminiConfig._map_reasoning_effort_to_thinking_level(
+ value, model
+ )
+ else:
+ optional_params[
+ "thinkingConfig"
+ ] = VertexGeminiConfig._map_reasoning_effort_to_thinking_budget(
+ value, model
+ )
elif param == "thinking":
+ # Validate no conflict with thinking_level
+ VertexGeminiConfig._validate_thinking_config_conflicts(
+ optional_params=optional_params,
+ param_name="thinking",
+ param_description="thinking_budget",
+ )
optional_params[
"thinkingConfig"
] = VertexGeminiConfig._map_thinking_param(
@@ -764,6 +894,18 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
elif "AUDIO" not in optional_params["responseModalities"]:
optional_params["responseModalities"].append("AUDIO")
+ # Set default temperature to 1.0 for Gemini 3 models if not specified
+ if VertexGeminiConfig._is_gemini_3_or_newer(model):
+ if "temperature" not in optional_params:
+ optional_params["temperature"] = 1.0
+ thinking_config = optional_params.get("thinkingConfig", {})
+ if (
+ "thinkingLevel" not in thinking_config
+ and "thinkingBudget" not in thinking_config
+ ):
+ thinking_config["thinkingLevel"] = "low"
+ optional_params["thinkingConfig"] = thinking_config
+
return optional_params
def get_mapped_special_auth_params(self) -> dict:
@@ -1025,19 +1167,35 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
_tools: List[ChatCompletionToolCallChunk] = []
for part in parts:
if "functionCall" in part:
- _function_chunk = ChatCompletionToolCallFunctionChunk(
- name=part["functionCall"]["name"],
- arguments=json.dumps(part["functionCall"]["args"], ensure_ascii=False),
- )
+ _function_chunk: ChatCompletionToolCallFunctionChunk = {
+ "name": part["functionCall"]["name"],
+ "arguments": json.dumps(
+ part["functionCall"]["args"], ensure_ascii=False
+ ),
+ }
+ # Extract thought signature if present
+ thought_signature = part.get("thoughtSignature")
+
if is_function_call is True:
- function = _function_chunk
+ function_dict: Dict[str, Any] = dict(_function_chunk)
+ if thought_signature:
+ if "provider_specific_fields" not in function_dict:
+ function_dict["provider_specific_fields"] = {}
+ function_dict["provider_specific_fields"][
+ "thought_signature"
+ ] = thought_signature
+ function = cast(ChatCompletionToolCallFunctionChunk, function_dict)
else:
- _tool_response_chunk = ChatCompletionToolCallChunk(
- id=f"call_{uuid.uuid4().hex[:28]}",
- type="function",
- function=_function_chunk,
- index=cumulative_tool_call_idx,
- )
+ _tool_response_chunk: ChatCompletionToolCallChunk = {
+ "id": f"call_{uuid.uuid4().hex[:28]}",
+ "type": "function",
+ "function": _function_chunk,
+ "index": cumulative_tool_call_idx,
+ }
+ if thought_signature:
+ _tool_response_chunk["provider_specific_fields"] = { # type: ignore
+ "thought_signature": thought_signature
+ }
_tools.append(_tool_response_chunk)
cumulative_tool_call_idx += 1
if len(_tools) == 0:
@@ -1374,7 +1532,6 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
annotations: List[ChatCompletionAnnotation] = []
-
for metadata in grounding_metadata:
# Extract groundingSupports - these map text segments to sources
grounding_supports = metadata.get("groundingSupports", [])
@@ -1395,23 +1552,23 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
segment = support.get("segment", {})
start_index = segment.get("startIndex")
end_index = segment.get("endIndex")
-
+
# Get the chunk indices for this support
chunk_indices = support.get("groundingChunkIndices", [])
-
+
if start_index is not None and end_index is not None and chunk_indices:
# Use the first chunk's URL for the annotation
first_chunk_idx = chunk_indices[0]
if first_chunk_idx in chunk_to_uri_map:
uri_info = chunk_to_uri_map[first_chunk_idx]
-
+
url_citation: ChatCompletionAnnotationURLCitation = {
"start_index": start_index,
"end_index": end_index,
"url": uri_info["url"],
"title": uri_info["title"],
}
-
+
annotation: ChatCompletionAnnotation = {
"type": "url_citation",
"url_citation": url_citation,
@@ -1511,9 +1668,11 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
chat_completion_message["reasoning_content"] = reasoning_content
if candidate_grounding_metadata:
- annotations = VertexGeminiConfig._convert_grounding_metadata_to_annotations(
- grounding_metadata=candidate_grounding_metadata,
- content_text=content,
+ annotations = (
+ VertexGeminiConfig._convert_grounding_metadata_to_annotations(
+ grounding_metadata=candidate_grounding_metadata,
+ content_text=content,
+ )
)
if annotations:
chat_completion_message["annotations"] = annotations # type: ignore
@@ -1541,6 +1700,19 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
if thinking_blocks is not None:
chat_completion_message["thinking_blocks"] = thinking_blocks # type: ignore
+ # Convert thinking_blocks to reasoning_content for streaming
+ # This ensures reasoning_content is available in streaming responses
+ if isinstance(model_response, ModelResponseStream) and reasoning_content is None:
+ reasoning_content_parts = []
+ for block in thinking_blocks:
+ thinking_text = block.get("thinking")
+ if thinking_text:
+ reasoning_content_parts.append(thinking_text)
+
+ if reasoning_content_parts:
+ reasoning_content = "\n".join(reasoning_content_parts)
+ chat_completion_message["reasoning_content"] = reasoning_content
+
if isinstance(model_response, ModelResponseStream):
choice = VertexGeminiConfig._create_streaming_choice(
chat_completion_message=chat_completion_message,
@@ -1718,9 +1890,9 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
return model_response
def _transform_messages(
- self, messages: List[AllMessageValues]
+ self, messages: List[AllMessageValues], model: Optional[str] = None
) -> List[ContentType]:
- return _gemini_convert_messages_with_history(messages=messages)
+ return _gemini_convert_messages_with_history(messages=messages, model=model)
def get_error_class(
self, error_message: str, status_code: int, headers: Union[Dict, httpx.Headers]
@@ -1779,7 +1951,9 @@ async def make_call(
)
try:
- response = await client.post(api_base, headers=headers, data=data, stream=True, logging_obj=logging_obj)
+ response = await client.post(
+ api_base, headers=headers, data=data, stream=True, logging_obj=logging_obj
+ )
response.raise_for_status()
except httpx.HTTPStatusError as e:
exception_string = str(await e.response.aread())
@@ -1826,7 +2000,9 @@ def make_sync_call(
if client is None:
client = HTTPHandler() # Create a new client if none provided
- response = client.post(api_base, headers=headers, data=data, stream=True, logging_obj=logging_obj)
+ response = client.post(
+ api_base, headers=headers, data=data, stream=True, logging_obj=logging_obj
+ )
if response.status_code != 200 and response.status_code != 201:
raise VertexAIError(
@@ -1881,7 +2057,6 @@ class VertexLLM(VertexBase):
gemini_api_key: Optional[str] = None,
extra_headers: Optional[dict] = None,
) -> CustomStreamWrapper:
-
should_use_v1beta1_features = self.is_using_v1beta1_features(
optional_params=optional_params
)
@@ -1918,8 +2093,8 @@ class VertexLLM(VertexBase):
**data,
vertex_project=vertex_project,
vertex_location=vertex_location,
- vertex_auth_header=auth_header) # type: ignore
-
+ vertex_auth_header=auth_header,
+ ) # type: ignore
## LOGGING
logging_obj.pre_call(
@@ -2012,7 +2187,8 @@ class VertexLLM(VertexBase):
**data,
vertex_project=vertex_project,
vertex_location=vertex_location,
- vertex_auth_header=auth_header) # type: ignore
+ vertex_auth_header=auth_header,
+ ) # type: ignore
_async_client_params = {}
if timeout:
@@ -2036,7 +2212,10 @@ class VertexLLM(VertexBase):
try:
response = await client.post(
- api_base, headers=headers, json=cast(dict, request_body), logging_obj=logging_obj
+ api_base,
+ headers=headers,
+ json=cast(dict, request_body),
+ logging_obj=logging_obj,
) # type: ignore
response.raise_for_status()
except httpx.HTTPStatusError as err:
@@ -2190,9 +2369,10 @@ class VertexLLM(VertexBase):
## TRANSFORMATION ##
data = sync_transform_request_body(
**transform_request_params,
- vertex_project=vertex_project,
+ vertex_project=vertex_project,
vertex_location=vertex_location,
- vertex_auth_header=auth_header)
+ vertex_auth_header=auth_header,
+ )
## LOGGING
logging_obj.pre_call(
diff --git a/litellm/llms/vertex_ai/image_edit/__init__.py b/litellm/llms/vertex_ai/image_edit/__init__.py
new file mode 100644
index 00000000000..44914e861a7
--- /dev/null
+++ b/litellm/llms/vertex_ai/image_edit/__init__.py
@@ -0,0 +1,39 @@
+from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig
+from litellm.llms.vertex_ai.common_utils import VertexAIModelRoute, get_vertex_ai_model_route
+
+from .cost_calculator import cost_calculator
+from .vertex_gemini_transformation import VertexAIGeminiImageEditConfig
+from .vertex_imagen_transformation import VertexAIImagenImageEditConfig
+
+__all__ = [
+ "VertexAIGeminiImageEditConfig",
+ "VertexAIImagenImageEditConfig",
+ "get_vertex_ai_image_edit_config",
+ "cost_calculator"
+]
+
+
+def get_vertex_ai_image_edit_config(model: str) -> BaseImageEditConfig:
+ """
+ Get the appropriate image edit config for a Vertex AI model.
+
+ Routes to the correct transformation class based on the model type:
+ - Gemini models use generateContent API (VertexAIGeminiImageEditConfig)
+ - Imagen models use predict API (VertexAIImagenImageEditConfig)
+
+ Args:
+ model: The model name (e.g., "gemini-2.5-flash", "imagegeneration@006")
+
+ Returns:
+ BaseImageEditConfig: The appropriate configuration class
+ """
+ # Determine the model route
+ model_route = get_vertex_ai_model_route(model)
+
+ if model_route == VertexAIModelRoute.GEMINI:
+ # Gemini models use generateContent API
+ return VertexAIGeminiImageEditConfig()
+ else:
+ # Default to Imagen for other models (imagegeneration, etc.)
+ # This includes NON_GEMINI models like imagegeneration@006
+ return VertexAIImagenImageEditConfig()
diff --git a/litellm/llms/vertex_ai/image_edit/cost_calculator.py b/litellm/llms/vertex_ai/image_edit/cost_calculator.py
new file mode 100644
index 00000000000..b346622a336
--- /dev/null
+++ b/litellm/llms/vertex_ai/image_edit/cost_calculator.py
@@ -0,0 +1,34 @@
+"""
+Vertex AI Image Edit Cost Calculator
+"""
+
+from typing import Any
+
+import litellm
+from litellm.types.utils import ImageResponse
+
+
+def cost_calculator(
+ model: str,
+ image_response: Any,
+) -> float:
+ """
+ Vertex AI image edit cost calculator.
+
+ Mirrors image generation pricing: charge per returned image based on
+ model metadata (`output_cost_per_image`).
+ """
+ model_info = litellm.get_model_info(
+ model=model,
+ custom_llm_provider="vertex_ai",
+ )
+
+ output_cost_per_image: float = model_info.get("output_cost_per_image") or 0.0
+
+ if not isinstance(image_response, ImageResponse):
+ raise ValueError(
+ f"image_response must be of type ImageResponse got type={type(image_response)}"
+ )
+
+ num_images = len(image_response.data or [])
+ return output_cost_per_image * num_images
diff --git a/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
new file mode 100644
index 00000000000..469340f6bba
--- /dev/null
+++ b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
@@ -0,0 +1,263 @@
+import base64
+import json
+import os
+from io import BufferedReader, BytesIO
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union, cast
+
+import httpx
+from httpx._types import RequestFiles
+
+import litellm
+
+from litellm.images.utils import ImageEditRequestUtils
+from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig
+from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.images.main import ImageEditOptionalRequestParams
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.utils import FileTypes, ImageObject, ImageResponse, OpenAIImage
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+ LiteLLMLoggingObj = Any
+
+
+class VertexAIGeminiImageEditConfig(BaseImageEditConfig, VertexLLM):
+ """
+ Vertex AI Gemini Image Edit Configuration
+
+ Uses generateContent API for Gemini models on Vertex AI
+ """
+ SUPPORTED_PARAMS: List[str] = ["size"]
+
+ def __init__(self) -> None:
+ BaseImageEditConfig.__init__(self)
+ VertexLLM.__init__(self)
+
+ def get_supported_openai_params(self, model: str) -> List[str]:
+ return list(self.SUPPORTED_PARAMS)
+
+ def map_openai_params(
+ self,
+ image_edit_optional_params: ImageEditOptionalRequestParams,
+ model: str,
+ drop_params: bool,
+ ) -> Dict[str, Any]:
+ supported_params = self.get_supported_openai_params(model)
+ filtered_params = {
+ key: value
+ for key, value in image_edit_optional_params.items()
+ if key in supported_params
+ }
+
+ mapped_params: Dict[str, Any] = {}
+
+ if "size" in filtered_params:
+ mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(
+ filtered_params["size"] # type: ignore[arg-type]
+ )
+
+ return mapped_params
+
+ def _resolve_vertex_project(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_project", None)
+ or os.environ.get("VERTEXAI_PROJECT")
+ or getattr(litellm, "vertex_project", None)
+ or get_secret_str("VERTEXAI_PROJECT")
+ )
+
+ def _resolve_vertex_location(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_location", None)
+ or os.environ.get("VERTEXAI_LOCATION")
+ or os.environ.get("VERTEX_LOCATION")
+ or getattr(litellm, "vertex_location", None)
+ or get_secret_str("VERTEXAI_LOCATION")
+ or get_secret_str("VERTEX_LOCATION")
+ )
+
+ def _resolve_vertex_credentials(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_credentials", None)
+ or os.environ.get("VERTEXAI_CREDENTIALS")
+ or getattr(litellm, "vertex_credentials", None)
+ or os.environ.get("GOOGLE_APPLICATION_CREDENTIALS")
+ or get_secret_str("VERTEXAI_CREDENTIALS")
+ )
+
+ def validate_environment(
+ self,
+ headers: dict,
+ model: str,
+ api_key: Optional[str] = None,
+ ) -> dict:
+ headers = headers or {}
+ vertex_project = self._resolve_vertex_project()
+ vertex_credentials = self._resolve_vertex_credentials()
+ access_token, _ = self._ensure_access_token(
+ credentials=vertex_credentials,
+ project_id=vertex_project,
+ custom_llm_provider="vertex_ai",
+ )
+ return self.set_headers(access_token, headers)
+
+ def get_complete_url(
+ self,
+ model: str,
+ api_base: Optional[str],
+ litellm_params: dict,
+ ) -> str:
+ """
+ Get the complete URL for Vertex AI Gemini generateContent API
+ """
+ vertex_project = self._resolve_vertex_project()
+ vertex_location = self._resolve_vertex_location()
+
+ if not vertex_project or not vertex_location:
+ raise ValueError("vertex_project and vertex_location are required for Vertex AI")
+
+ # Use the model name as provided, handling vertex_ai prefix
+ model_name = model
+ if model.startswith("vertex_ai/"):
+ model_name = model.replace("vertex_ai/", "")
+
+ if api_base:
+ base_url = api_base.rstrip("/")
+ else:
+ base_url = f"https://{vertex_location}-aiplatform.googleapis.com"
+
+ return f"{base_url}/v1/projects/{vertex_project}/locations/{vertex_location}/publishers/google/models/{model_name}:generateContent"
+
+ def transform_image_edit_request( # type: ignore[override]
+ self,
+ model: str,
+ prompt: str,
+ image: FileTypes,
+ image_edit_optional_request_params: Dict[str, Any],
+ litellm_params: GenericLiteLLMParams,
+ headers: dict,
+ ) -> Tuple[Dict[str, Any], Optional[RequestFiles]]:
+ inline_parts = self._prepare_inline_image_parts(image)
+ if not inline_parts:
+ raise ValueError("Vertex AI Gemini image edit requires at least one image.")
+
+ # Correct format for Vertex AI Gemini image editing
+ contents = {
+ "role": "USER",
+ "parts": inline_parts + [{"text": prompt}]
+ }
+
+ request_body: Dict[str, Any] = {"contents": contents}
+
+ # Generation config with proper structure for image editing
+ generation_config: Dict[str, Any] = {
+ "response_modalities": ["IMAGE"]
+ }
+
+ # Add image-specific configuration
+ image_config: Dict[str, Any] = {}
+ if "aspectRatio" in image_edit_optional_request_params:
+ image_config["aspect_ratio"] = image_edit_optional_request_params["aspectRatio"]
+
+ if image_config:
+ generation_config["image_config"] = image_config
+
+ request_body["generationConfig"] = generation_config
+
+ payload: Any = json.dumps(request_body)
+ empty_files = cast(RequestFiles, [])
+ return cast(Tuple[Dict[str, Any], Optional[RequestFiles]], (payload, empty_files))
+
+ def transform_image_edit_response(
+ self,
+ model: str,
+ raw_response: httpx.Response,
+ logging_obj: Any,
+ ) -> ImageResponse:
+ model_response = ImageResponse()
+ try:
+ response_json = raw_response.json()
+ except Exception as exc:
+ raise self.get_error_class(
+ error_message=f"Error transforming image edit response: {exc}",
+ status_code=raw_response.status_code,
+ headers=raw_response.headers,
+ )
+
+ candidates = response_json.get("candidates", [])
+ data_list: List[ImageObject] = []
+
+ for candidate in candidates:
+ content = candidate.get("content", {})
+ parts = content.get("parts", [])
+ for part in parts:
+ inline_data = part.get("inlineData")
+ if inline_data and inline_data.get("data"):
+ data_list.append(
+ ImageObject(
+ b64_json=inline_data["data"],
+ url=None,
+ )
+ )
+
+ model_response.data = cast(List[OpenAIImage], data_list)
+ return model_response
+
+ def _map_size_to_aspect_ratio(self, size: str) -> str:
+ """Map OpenAI size format to Gemini aspect ratio format"""
+ aspect_ratio_map = {
+ "1024x1024": "1:1",
+ "1792x1024": "16:9",
+ "1024x1792": "9:16",
+ "1280x896": "4:3",
+ "896x1280": "3:4",
+ }
+ return aspect_ratio_map.get(size, "1:1")
+
+ def _prepare_inline_image_parts(
+ self, image: Union[FileTypes, List[FileTypes]]
+ ) -> List[Dict[str, Any]]:
+ images: List[FileTypes]
+ if isinstance(image, list):
+ images = image
+ else:
+ images = [image]
+
+ inline_parts: List[Dict[str, Any]] = []
+ for img in images:
+ if img is None:
+ continue
+
+ mime_type = ImageEditRequestUtils.get_image_content_type(img)
+ image_bytes = self._read_all_bytes(img)
+ inline_parts.append(
+ {
+ "inlineData": {
+ "mimeType": mime_type,
+ "data": base64.b64encode(image_bytes).decode("utf-8"),
+ }
+ }
+ )
+
+ return inline_parts
+
+ def _read_all_bytes(self, image: FileTypes) -> bytes:
+ if isinstance(image, bytes):
+ return image
+ if isinstance(image, BytesIO):
+ current_pos = image.tell()
+ image.seek(0)
+ data = image.read()
+ image.seek(current_pos)
+ return data
+ if isinstance(image, BufferedReader):
+ current_pos = image.tell()
+ image.seek(0)
+ data = image.read()
+ image.seek(current_pos)
+ return data
+ raise ValueError("Unsupported image type for Vertex AI Gemini image edit.")
diff --git a/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py b/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py
new file mode 100644
index 00000000000..caf347a1fb4
--- /dev/null
+++ b/litellm/llms/vertex_ai/image_edit/vertex_imagen_transformation.py
@@ -0,0 +1,345 @@
+import base64
+import json
+import os
+from io import BufferedRandom, BufferedReader, BytesIO
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union, cast
+
+import httpx
+from httpx._types import RequestFiles
+
+import litellm
+
+from litellm.llms.base_llm.image_edit.transformation import BaseImageEditConfig
+from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.images.main import ImageEditOptionalRequestParams
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.utils import FileTypes, ImageObject, ImageResponse, OpenAIImage
+
+if TYPE_CHECKING:
+ from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+ LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+ LiteLLMLoggingObj = Any
+
+
+class VertexAIImagenImageEditConfig(BaseImageEditConfig, VertexLLM):
+ """
+ Vertex AI Imagen Image Edit Configuration
+
+ Uses predict API for Imagen models on Vertex AI
+ """
+ SUPPORTED_PARAMS: List[str] = ["n", "size", "mask"]
+
+ def __init__(self) -> None:
+ BaseImageEditConfig.__init__(self)
+ VertexLLM.__init__(self)
+
+ def get_supported_openai_params(self, model: str) -> List[str]:
+ return list(self.SUPPORTED_PARAMS)
+
+ def map_openai_params(
+ self,
+ image_edit_optional_params: ImageEditOptionalRequestParams,
+ model: str,
+ drop_params: bool,
+ ) -> Dict[str, Any]:
+ supported_params = self.get_supported_openai_params(model)
+ filtered_params = {
+ key: value
+ for key, value in image_edit_optional_params.items()
+ if key in supported_params
+ }
+
+ mapped_params: Dict[str, Any] = {}
+
+ # Map OpenAI parameters to Imagen format
+ if "n" in filtered_params:
+ mapped_params["sampleCount"] = filtered_params["n"]
+
+ if "size" in filtered_params:
+ mapped_params["aspectRatio"] = self._map_size_to_aspect_ratio(
+ filtered_params["size"] # type: ignore[arg-type]
+ )
+
+ if "mask" in filtered_params:
+ mapped_params["mask"] = filtered_params["mask"]
+
+ return mapped_params
+
+ def _resolve_vertex_project(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_project", None)
+ or os.environ.get("VERTEXAI_PROJECT")
+ or getattr(litellm, "vertex_project", None)
+ or get_secret_str("VERTEXAI_PROJECT")
+ )
+
+ def _resolve_vertex_location(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_location", None)
+ or os.environ.get("VERTEXAI_LOCATION")
+ or os.environ.get("VERTEX_LOCATION")
+ or getattr(litellm, "vertex_location", None)
+ or get_secret_str("VERTEXAI_LOCATION")
+ or get_secret_str("VERTEX_LOCATION")
+ )
+
+ def _resolve_vertex_credentials(self) -> Optional[str]:
+ return (
+ getattr(self, "_vertex_credentials", None)
+ or os.environ.get("VERTEXAI_CREDENTIALS")
+ or getattr(litellm, "vertex_credentials", None)
+ or os.environ.get("GOOGLE_APPLICATION_CREDENTIALS")
+ or get_secret_str("VERTEXAI_CREDENTIALS")
+ )
+
+ def validate_environment(
+ self,
+ headers: dict,
+ model: str,
+ api_key: Optional[str] = None,
+ ) -> dict:
+ headers = headers or {}
+ vertex_project = self._resolve_vertex_project()
+ vertex_credentials = self._resolve_vertex_credentials()
+ access_token, _ = self._ensure_access_token(
+ credentials=vertex_credentials,
+ project_id=vertex_project,
+ custom_llm_provider="vertex_ai",
+ )
+ return self.set_headers(access_token, headers)
+
+ def get_complete_url(
+ self,
+ model: str,
+ api_base: Optional[str],
+ litellm_params: dict,
+ ) -> str:
+ """
+ Get the complete URL for Vertex AI Imagen predict API
+ """
+ vertex_project = self._resolve_vertex_project()
+ vertex_location = self._resolve_vertex_location()
+
+ if not vertex_project or not vertex_location:
+ raise ValueError("vertex_project and vertex_location are required for Vertex AI")
+
+ # Use the model name as provided, handling vertex_ai prefix
+ model_name = model
+ if model.startswith("vertex_ai/"):
+ model_name = model.replace("vertex_ai/", "")
+
+ if api_base:
+ base_url = api_base.rstrip("/")
+ else:
+ base_url = f"https://{vertex_location}-aiplatform.googleapis.com"
+
+ return f"{base_url}/v1/projects/{vertex_project}/locations/{vertex_location}/publishers/google/models/{model_name}:predict"
+
+ def transform_image_edit_request( # type: ignore[override]
+ self,
+ model: str,
+ prompt: str,
+ image: FileTypes,
+ image_edit_optional_request_params: Dict[str, Any],
+ litellm_params: GenericLiteLLMParams,
+ headers: dict,
+ ) -> Tuple[Dict[str, Any], Optional[RequestFiles]]:
+ # Prepare reference images in the correct Imagen format
+ reference_images = self._prepare_reference_images(image, image_edit_optional_request_params)
+ if not reference_images:
+ raise ValueError("Vertex AI Imagen image edit requires at least one reference image.")
+
+ # Correct Imagen instances format
+ instances = [
+ {
+ "prompt": prompt,
+ "referenceImages": reference_images
+ }
+ ]
+
+ # Extract OpenAI parameters and set sensible defaults for Vertex AI-specific parameters
+ sample_count = image_edit_optional_request_params.get("sampleCount", 1)
+ # Use sensible defaults for Vertex AI-specific parameters (not exposed to users)
+ edit_mode = "EDIT_MODE_INPAINT_INSERTION" # Default edit mode
+ base_steps = 50 # Default number of steps
+
+ # Imagen parameters with correct structure
+ parameters = {
+ "sampleCount": sample_count,
+ "editMode": edit_mode,
+ "editConfig": {
+ "baseSteps": base_steps
+ }
+ }
+
+ # Set default values for Vertex AI-specific parameters (not configurable by users via OpenAI API)
+ parameters["guidanceScale"] = 7.5 # Default guidance scale
+ parameters["seed"] = None # Let Vertex AI choose random seed
+
+ request_body: Dict[str, Any] = {
+ "instances": instances,
+ "parameters": parameters
+ }
+
+ payload: Any = json.dumps(request_body)
+ empty_files = cast(RequestFiles, [])
+ return cast(Tuple[Dict[str, Any], Optional[RequestFiles]], (payload, empty_files))
+
+ def transform_image_edit_response(
+ self,
+ model: str,
+ raw_response: httpx.Response,
+ logging_obj: Any,
+ ) -> ImageResponse:
+ model_response = ImageResponse()
+ try:
+ response_json = raw_response.json()
+ except Exception as exc:
+ raise self.get_error_class(
+ error_message=f"Error transforming image edit response: {exc}",
+ status_code=raw_response.status_code,
+ headers=raw_response.headers,
+ )
+
+ predictions = response_json.get("predictions", [])
+ data_list: List[ImageObject] = []
+
+ for prediction in predictions:
+ # Imagen returns images as bytesBase64Encoded
+ if "bytesBase64Encoded" in prediction:
+ data_list.append(
+ ImageObject(
+ b64_json=prediction["bytesBase64Encoded"],
+ url=None,
+ )
+ )
+
+ model_response.data = cast(List[OpenAIImage], data_list)
+ return model_response
+
+ def _map_size_to_aspect_ratio(self, size: str) -> str:
+ """Map OpenAI size format to Imagen aspect ratio format"""
+ aspect_ratio_map = {
+ "1024x1024": "1:1",
+ "1792x1024": "16:9",
+ "1024x1792": "9:16",
+ "1280x896": "4:3",
+ "896x1280": "3:4",
+ }
+ return aspect_ratio_map.get(size, "1:1")
+
+ def _prepare_reference_images(
+ self, image: Union[FileTypes, List[FileTypes]],
+ image_edit_optional_request_params: Dict[str, Any]
+ ) -> List[Dict[str, Any]]:
+ """
+ Prepare reference images in the correct Imagen API format
+ """
+ images: List[FileTypes]
+ if isinstance(image, list):
+ images = image
+ else:
+ images = [image]
+
+ reference_images: List[Dict[str, Any]] = []
+
+ for idx, img in enumerate(images):
+ if img is None:
+ continue
+
+ image_bytes = self._read_all_bytes(img)
+ base64_data = base64.b64encode(image_bytes).decode("utf-8")
+
+ # Create reference image structure
+ reference_image = {
+ "referenceType": "REFERENCE_TYPE_RAW",
+ "referenceId": idx + 1,
+ "referenceImage": {
+ "bytesBase64Encoded": base64_data
+ }
+ }
+
+ reference_images.append(reference_image)
+
+ # Handle mask image if provided (for inpainting)
+ mask_image = image_edit_optional_request_params.get("mask")
+ if mask_image is not None:
+ mask_bytes = self._read_all_bytes(mask_image)
+ mask_base64 = base64.b64encode(mask_bytes).decode("utf-8")
+
+ mask_reference = {
+ "referenceType": "REFERENCE_TYPE_MASK",
+ "referenceId": len(reference_images) + 1,
+ "referenceImage": {
+ "bytesBase64Encoded": mask_base64
+ },
+ "maskImageConfig": {
+ "maskMode": "MASK_MODE_USER_PROVIDED",
+ "dilation": 0.03 # Default dilation value (not configurable via OpenAI API)
+ }
+ }
+ reference_images.append(mask_reference)
+
+ return reference_images
+
+ def _read_all_bytes(self, image: Any) -> bytes:
+ if isinstance(image, (list, tuple)):
+ for item in image:
+ if item is not None:
+ return self._read_all_bytes(item)
+ raise ValueError("Unsupported image type for Vertex AI Imagen image edit.")
+
+ if isinstance(image, dict):
+ for key in ("data", "bytes", "content"):
+ if key in image and image[key] is not None:
+ value = image[key]
+ if isinstance(value, str):
+ try:
+ return base64.b64decode(value)
+ except Exception:
+ continue
+ return self._read_all_bytes(value)
+ if "path" in image:
+ return self._read_all_bytes(image["path"])
+
+ if isinstance(image, bytes):
+ return image
+ if isinstance(image, bytearray):
+ return bytes(image)
+ if isinstance(image, BytesIO):
+ current_pos = image.tell()
+ image.seek(0)
+ data = image.read()
+ image.seek(current_pos)
+ return data
+ if isinstance(image, (BufferedReader, BufferedRandom)):
+ stream_pos: Optional[int] = None
+ try:
+ stream_pos = image.tell()
+ except Exception:
+ stream_pos = None
+ if stream_pos is not None:
+ image.seek(0)
+ data = image.read()
+ if stream_pos is not None:
+ image.seek(stream_pos)
+ return data
+ if isinstance(image, (str, Path)):
+ path_obj = Path(image)
+ if not path_obj.exists():
+ raise ValueError(
+ f"Mask/image path does not exist for Vertex AI Imagen image edit: {path_obj}"
+ )
+ return path_obj.read_bytes()
+ if hasattr(image, "read"):
+ data = image.read()
+ if isinstance(data, str):
+ data = data.encode("utf-8")
+ return data
+ raise ValueError(
+ f"Unsupported image type for Vertex AI Imagen image edit. Got type={type(image)}"
+ )
diff --git a/litellm/main.py b/litellm/main.py
index 23ffa90e2db..1e3826b9a60 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -390,6 +390,7 @@ async def acompletion(
reasoning_effort: Optional[
Literal["none", "minimal", "low", "medium", "high", "default"]
] = None,
+ verbosity: Optional[Literal["low", "medium", "high"]] = None,
safety_identifier: Optional[str] = None,
service_tier: Optional[str] = None,
# set api_base, api_version, api_key
@@ -961,6 +962,7 @@ def completion( # type: ignore # noqa: PLR0915
reasoning_effort: Optional[
Literal["none", "minimal", "low", "medium", "high", "default"]
] = None,
+ verbosity: Optional[Literal["low", "medium", "high"]] = None,
response_format: Optional[Union[dict, Type[BaseModel]]] = None,
seed: Optional[int] = None,
tools: Optional[List] = None,
@@ -2084,10 +2086,10 @@ def completion( # type: ignore # noqa: PLR0915
if extra_headers is not None:
optional_params["extra_headers"] = extra_headers
- if (
- litellm.enable_preview_features and metadata is not None
- ): # [PREVIEW] allow metadata to be passed to OPENAI
- optional_params["metadata"] = add_openai_metadata(metadata)
+ if litellm.enable_preview_features:
+ metadata_payload = add_openai_metadata(metadata)
+ if metadata_payload is not None:
+ optional_params["metadata"] = metadata_payload
## LOAD CONFIG - if set
config = litellm.OpenAIConfig.get_config()
@@ -4820,6 +4822,22 @@ def embedding( # noqa: PLR0915
print_verbose=print_verbose,
litellm_params=litellm_params_dict,
)
+ elif custom_llm_provider == "snowflake":
+ api_key = api_key or get_secret_str("SNOWFLAKE_JWT")
+ response = base_llm_http_handler.embedding(
+ model=model,
+ input=input,
+ custom_llm_provider=custom_llm_provider,
+ api_base=api_base,
+ api_key=api_key,
+ logging_obj=logging,
+ timeout=timeout,
+ model_response=EmbeddingResponse(),
+ optional_params=optional_params,
+ client=client,
+ aembedding=aembedding,
+ litellm_params={},
+ )
else:
raise LiteLLMUnknownProvider(
model=model, custom_llm_provider=custom_llm_provider
@@ -5498,6 +5516,7 @@ def transcription(
atranscription = kwargs.pop("atranscription", False)
litellm_logging_obj: LiteLLMLoggingObj = kwargs.get("litellm_logging_obj") # type: ignore
extra_headers = kwargs.get("extra_headers", None)
+ shared_session = kwargs.get("shared_session", None)
kwargs.pop("tags", [])
non_default_params = get_non_default_transcription_params(kwargs)
@@ -5635,6 +5654,7 @@ def transcription(
api_key=api_key,
provider_config=provider_config,
litellm_params=litellm_params_dict,
+ shared_session=shared_session,
)
elif provider_config is not None:
response = base_llm_http_handler.audio_transcriptions(
@@ -5661,6 +5681,7 @@ def transcription(
custom_llm_provider=custom_llm_provider,
headers={},
provider_config=provider_config,
+ shared_session=shared_session,
)
# Calculate and add duration if response is missing it
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 0fe71e4541e..b4b4f763860 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -462,39 +462,45 @@
"cache_creation_input_token_cost": 1.25e-06,
"cache_read_input_token_cost": 1e-07,
"input_cost_per_token": 1e-06,
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"anthropic.claude-haiku-4-5@20251001": {
"cache_creation_input_token_cost": 1.25e-06,
"cache_read_input_token_cost": 1e-07,
"input_cost_per_token": 1e-06,
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"anthropic.claude-3-5-sonnet-20240620-v1:0": {
"input_cost_per_token": 3e-06,
@@ -930,20 +936,23 @@
"cache_creation_input_token_cost": 1.375e-06,
"cache_read_input_token_cost": 1.1e-07,
"input_cost_per_token": 1.1e-06,
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"apac.anthropic.claude-3-sonnet-20240229-v1:0": {
"input_cost_per_token": 3e-06,
@@ -1224,6 +1233,228 @@
"supports_system_messages": true,
"supports_tool_choice": true
},
+ "azure/eu/gpt-5-2025-08-07": {
+ "cache_read_input_token_cost": 1.375e-07,
+ "input_cost_per_token": 1.375e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5-mini-2025-08-07": {
+ "cache_read_input_token_cost": 2.75e-08,
+ "input_cost_per_token": 2.75e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.2e-06,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5.1": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5.1-chat": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5.1-codex": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5.1-codex-mini": {
+ "cache_read_input_token_cost": 2.8e-08,
+ "input_cost_per_token": 2.75e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 2.2e-06,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/eu/gpt-5-nano-2025-08-07": {
+ "cache_read_input_token_cost": 5.5e-09,
+ "input_cost_per_token": 5.5e-08,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 4.4e-07,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/eu/o1-2024-12-17": {
"cache_read_input_token_cost": 8.25e-06,
"input_cost_per_token": 1.65e-05,
@@ -1366,6 +1597,132 @@
"supports_tool_choice": true,
"supports_vision": true
},
+ "azure/global/gpt-5.1": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/global/gpt-5.1-chat": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/global/gpt-5.1-codex": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/global/gpt-5.1-codex-mini": {
+ "cache_read_input_token_cost": 2.5e-08,
+ "input_cost_per_token": 2.5e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 2e-06,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/gpt-3.5-turbo": {
"input_cost_per_token": 5e-07,
"litellm_provider": "azure",
@@ -1882,6 +2239,68 @@
"supports_tool_choice": true,
"supports_vision": true
},
+ "azure/gpt-audio-2025-08-28": {
+ "input_cost_per_audio_token": 4e-05,
+ "input_cost_per_token": 2.5e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 128000,
+ "max_output_tokens": 16384,
+ "max_tokens": 16384,
+ "mode": "chat",
+ "output_cost_per_audio_token": 8e-05,
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions"
+ ],
+ "supported_modalities": [
+ "text",
+ "audio"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "audio"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_prompt_caching": false,
+ "supports_reasoning": false,
+ "supports_response_schema": false,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": false
+ },
+ "azure/gpt-audio-mini-2025-10-06": {
+ "input_cost_per_audio_token": 1e-05,
+ "input_cost_per_token": 6e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 128000,
+ "max_output_tokens": 16384,
+ "max_tokens": 16384,
+ "mode": "chat",
+ "output_cost_per_audio_token": 2e-05,
+ "output_cost_per_token": 2.4e-06,
+ "supported_endpoints": [
+ "/v1/chat/completions"
+ ],
+ "supported_modalities": [
+ "text",
+ "audio"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "audio"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_prompt_caching": false,
+ "supports_reasoning": false,
+ "supports_response_schema": false,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": false
+ },
"azure/gpt-4o-audio-preview-2024-12-17": {
"input_cost_per_audio_token": 4e-05,
"input_cost_per_token": 2.5e-06,
@@ -1995,6 +2414,70 @@
"supports_system_messages": true,
"supports_tool_choice": true
},
+ "azure/gpt-realtime-2025-08-28": {
+ "cache_creation_input_audio_token_cost": 4e-06,
+ "cache_read_input_token_cost": 4e-06,
+ "input_cost_per_audio_token": 3.2e-05,
+ "input_cost_per_image": 5e-06,
+ "input_cost_per_token": 4e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 32000,
+ "max_output_tokens": 4096,
+ "max_tokens": 4096,
+ "mode": "chat",
+ "output_cost_per_audio_token": 6.4e-05,
+ "output_cost_per_token": 1.6e-05,
+ "supported_endpoints": [
+ "/v1/realtime"
+ ],
+ "supported_modalities": [
+ "text",
+ "image",
+ "audio"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "audio"
+ ],
+ "supports_audio_input": true,
+ "supports_audio_output": true,
+ "supports_function_calling": true,
+ "supports_parallel_function_calling": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true
+ },
+ "azure/gpt-realtime-mini-2025-10-06": {
+ "cache_creation_input_audio_token_cost": 3e-07,
+ "cache_read_input_token_cost": 6e-08,
+ "input_cost_per_audio_token": 1e-05,
+ "input_cost_per_image": 8e-07,
+ "input_cost_per_token": 6e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 32000,
+ "max_output_tokens": 4096,
+ "max_tokens": 4096,
+ "mode": "chat",
+ "output_cost_per_audio_token": 2e-05,
+ "output_cost_per_token": 2.4e-06,
+ "supported_endpoints": [
+ "/v1/realtime"
+ ],
+ "supported_modalities": [
+ "text",
+ "image",
+ "audio"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "audio"
+ ],
+ "supports_audio_input": true,
+ "supports_audio_output": true,
+ "supports_function_calling": true,
+ "supports_parallel_function_calling": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true
+ },
"azure/gpt-4o-mini-transcribe": {
"input_cost_per_audio_token": 3e-06,
"input_cost_per_token": 1.25e-06,
@@ -2082,6 +2565,155 @@
"/v1/audio/transcriptions"
]
},
+ "azure/gpt-4o-transcribe-diarize": {
+ "input_cost_per_audio_token": 6e-06,
+ "input_cost_per_token": 2.5e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 16000,
+ "max_output_tokens": 2000,
+ "mode": "audio_transcription",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/audio/transcriptions"
+ ]
+ },
+ "azure/gpt-5.1-2025-11-13": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "cache_read_input_token_cost_priority": 2.5e-07,
+ "input_cost_per_token": 1.25e-06,
+ "input_cost_per_token_priority": 2.5e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "output_cost_per_token_priority": 2e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_service_tier": true,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-chat-2025-11-13": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "cache_read_input_token_cost_priority": 2.5e-07,
+ "input_cost_per_token": 1.25e-06,
+ "input_cost_per_token_priority": 2.5e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 128000,
+ "max_output_tokens": 16384,
+ "max_tokens": 16384,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "output_cost_per_token_priority": 2e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": false,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": false,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": false,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-codex-2025-11-13": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "cache_read_input_token_cost_priority": 2.5e-07,
+ "input_cost_per_token": 1.25e-06,
+ "input_cost_per_token_priority": 2.5e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 1e-05,
+ "output_cost_per_token_priority": 2e-05,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-codex-mini-2025-11-13": {
+ "cache_read_input_token_cost": 2.5e-08,
+ "cache_read_input_token_cost_priority": 4.5e-08,
+ "input_cost_per_token": 2.5e-07,
+ "input_cost_per_token_priority": 4.5e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 2e-06,
+ "output_cost_per_token_priority": 3.6e-06,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/gpt-5": {
"cache_read_input_token_cost": 1.25e-07,
"input_cost_per_token": 1.25e-06,
@@ -2398,6 +3030,132 @@
"supports_tool_choice": true,
"supports_vision": true
},
+ "azure/gpt-5.1": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-chat": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-codex": {
+ "cache_read_input_token_cost": 1.25e-07,
+ "input_cost_per_token": 1.25e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 1e-05,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/gpt-5.1-codex-mini": {
+ "cache_read_input_token_cost": 2.5e-08,
+ "input_cost_per_token": 2.5e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 2e-06,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/gpt-image-1": {
"input_cost_per_pixel": 4.0054321e-08,
"litellm_provider": "azure",
@@ -2738,14 +3496,14 @@
},
"azure/o3-2025-04-16": {
"deprecation_date": "2026-04-16",
- "cache_read_input_token_cost": 2.5e-06,
- "input_cost_per_token": 1e-05,
+ "cache_read_input_token_cost": 5e-07,
+ "input_cost_per_token": 2e-06,
"litellm_provider": "azure",
"max_input_tokens": 200000,
"max_output_tokens": 100000,
"max_tokens": 100000,
"mode": "chat",
- "output_cost_per_token": 4e-05,
+ "output_cost_per_token": 8e-06,
"supported_endpoints": [
"/v1/chat/completions",
"/v1/batch",
@@ -3004,6 +3762,107 @@
"litellm_provider": "azure",
"mode": "audio_speech"
},
+ "azure/us/gpt-4.1-2025-04-14": {
+ "deprecation_date": "2026-11-04",
+ "cache_read_input_token_cost": 5.5e-07,
+ "input_cost_per_token": 2.2e-06,
+ "input_cost_per_token_batches": 1.1e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 1047576,
+ "max_output_tokens": 32768,
+ "max_tokens": 32768,
+ "mode": "chat",
+ "output_cost_per_token": 8.8e-06,
+ "output_cost_per_token_batches": 4.4e-06,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_prompt_caching": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "supports_web_search": false
+ },
+ "azure/us/gpt-4.1-mini-2025-04-14": {
+ "deprecation_date": "2026-11-04",
+ "cache_read_input_token_cost": 1.1e-07,
+ "input_cost_per_token": 4.4e-07,
+ "input_cost_per_token_batches": 2.2e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 1047576,
+ "max_output_tokens": 32768,
+ "max_tokens": 32768,
+ "mode": "chat",
+ "output_cost_per_token": 1.76e-06,
+ "output_cost_per_token_batches": 8.8e-07,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
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+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_prompt_caching": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "supports_web_search": false
+ },
+ "azure/us/gpt-4.1-nano-2025-04-14": {
+ "deprecation_date": "2026-11-04",
+ "cache_read_input_token_cost": 2.5e-08,
+ "input_cost_per_token": 1.1e-07,
+ "input_cost_per_token_batches": 6e-08,
+ "litellm_provider": "azure",
+ "max_input_tokens": 1047576,
+ "max_output_tokens": 32768,
+ "max_tokens": 32768,
+ "mode": "chat",
+ "output_cost_per_token": 4.4e-07,
+ "output_cost_per_token_batches": 2.2e-07,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_prompt_caching": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/us/gpt-4o-2024-08-06": {
"deprecation_date": "2026-02-27",
"cache_read_input_token_cost": 1.375e-06,
@@ -3118,6 +3977,228 @@
"supports_system_messages": true,
"supports_tool_choice": true
},
+ "azure/us/gpt-5-2025-08-07": {
+ "cache_read_input_token_cost": 1.375e-07,
+ "input_cost_per_token": 1.375e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5-mini-2025-08-07": {
+ "cache_read_input_token_cost": 2.75e-08,
+ "input_cost_per_token": 2.75e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.2e-06,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5-nano-2025-08-07": {
+ "cache_read_input_token_cost": 5.5e-09,
+ "input_cost_per_token": 5.5e-08,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 4.4e-07,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
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+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5.1": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5.1-chat": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text",
+ "image"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5.1-codex": {
+ "cache_read_input_token_cost": 1.4e-07,
+ "input_cost_per_token": 1.38e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 1.1e-05,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
+ "azure/us/gpt-5.1-codex-mini": {
+ "cache_read_input_token_cost": 2.8e-08,
+ "input_cost_per_token": 2.75e-07,
+ "litellm_provider": "azure",
+ "max_input_tokens": 272000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "responses",
+ "output_cost_per_token": 2.2e-06,
+ "supported_endpoints": [
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_native_streaming": true,
+ "supports_parallel_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": false,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/us/o1-2024-12-17": {
"cache_read_input_token_cost": 8.25e-06,
"input_cost_per_token": 1.65e-05,
@@ -3163,6 +4244,36 @@
"supports_prompt_caching": true,
"supports_vision": false
},
+ "azure/us/o3-2025-04-16": {
+ "deprecation_date": "2026-04-16",
+ "cache_read_input_token_cost": 5.5e-07,
+ "input_cost_per_token": 2.2e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 100000,
+ "max_tokens": 100000,
+ "mode": "chat",
+ "output_cost_per_token": 8.8e-06,
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/batch",
+ "/v1/responses"
+ ],
+ "supported_modalities": [
+ "text",
+ "image"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_function_calling": true,
+ "supports_parallel_function_calling": false,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/us/o3-mini-2025-01-31": {
"cache_read_input_token_cost": 6.05e-07,
"input_cost_per_token": 1.21e-06,
@@ -3179,6 +4290,23 @@
"supports_tool_choice": true,
"supports_vision": false
},
+ "azure/us/o4-mini-2025-04-16": {
+ "cache_read_input_token_cost": 3.1e-07,
+ "input_cost_per_token": 1.21e-06,
+ "litellm_provider": "azure",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 100000,
+ "max_tokens": 100000,
+ "mode": "chat",
+ "output_cost_per_token": 4.84e-06,
+ "supports_function_calling": true,
+ "supports_parallel_function_calling": false,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true
+ },
"azure/whisper-1": {
"input_cost_per_second": 0.0001,
"litellm_provider": "azure",
@@ -8257,20 +9385,23 @@
"cache_read_input_token_cost": 1.1e-07,
"input_cost_per_token": 1.1e-06,
"deprecation_date": "2026-10-15",
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"eu.anthropic.claude-3-5-sonnet-20240620-v1:0": {
"input_cost_per_token": 3e-06,
@@ -8515,10 +9646,18 @@
"/v1/images/generations"
]
},
+ "fal_ai/fal-ai/flux-pro/v1.1": {
+ "litellm_provider": "fal_ai",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.04,
+ "supported_endpoints": [
+ "/v1/images/generations"
+ ]
+ },
"fal_ai/fal-ai/flux-pro/v1.1-ultra": {
"litellm_provider": "fal_ai",
"mode": "image_generation",
- "output_cost_per_image": 0.0398,
+ "output_cost_per_image": 0.06,
"supported_endpoints": [
"/v1/images/generations"
]
@@ -8531,6 +9670,30 @@
"/v1/images/generations"
]
},
+ "fal_ai/fal-ai/bytedance/seedream/v3/text-to-image": {
+ "litellm_provider": "fal_ai",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.03,
+ "supported_endpoints": [
+ "/v1/images/generations"
+ ]
+ },
+ "fal_ai/fal-ai/bytedance/dreamina/v3.1/text-to-image": {
+ "litellm_provider": "fal_ai",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.03,
+ "supported_endpoints": [
+ "/v1/images/generations"
+ ]
+ },
+ "fal_ai/fal-ai/ideogram/v3": {
+ "litellm_provider": "fal_ai",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.06,
+ "supported_endpoints": [
+ "/v1/images/generations"
+ ]
+ },
"fal_ai/fal-ai/imagen4/preview": {
"litellm_provider": "fal_ai",
"mode": "image_generation",
@@ -8719,6 +9882,18 @@
"supports_response_schema": true,
"supports_tool_choice": true
},
+ "fireworks_ai/accounts/fireworks/models/deepseek-v3p1-terminus": {
+ "input_cost_per_token": 5.6e-07,
+ "litellm_provider": "fireworks_ai",
+ "max_input_tokens": 128000,
+ "max_output_tokens": 8192,
+ "max_tokens": 8192,
+ "mode": "chat",
+ "output_cost_per_token": 1.68e-06,
+ "source": "https://fireworks.ai/pricing",
+ "supports_response_schema": true,
+ "supports_tool_choice": true
+ },
"fireworks_ai/accounts/fireworks/models/firefunction-v2": {
"input_cost_per_token": 9e-07,
"litellm_provider": "fireworks_ai",
@@ -8797,6 +9972,20 @@
"supports_response_schema": true,
"supports_tool_choice": true
},
+ "fireworks_ai/accounts/fireworks/models/kimi-k2-thinking": {
+ "input_cost_per_token": 6e-07,
+ "litellm_provider": "fireworks_ai",
+ "max_input_tokens": 262144,
+ "max_output_tokens": 262144,
+ "max_tokens": 262144,
+ "mode": "chat",
+ "output_cost_per_token": 2.5e-06,
+ "source": "https://fireworks.ai/pricing",
+ "supports_function_calling": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_web_search": true
+ },
"fireworks_ai/accounts/fireworks/models/llama-v3p1-405b-instruct": {
"input_cost_per_token": 3e-06,
"litellm_provider": "fireworks_ai",
@@ -10583,6 +11772,102 @@
"supports_vision": true,
"supports_web_search": true
},
+ "gemini-3-pro-preview": {
+ "cache_read_input_token_cost": 2e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 4e-07,
+ "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07,
+ "input_cost_per_token": 2e-06,
+ "input_cost_per_token_above_200k_tokens": 4e-06,
+ "input_cost_per_token_batches": 1e-06,
+ "litellm_provider": "vertex_ai-language-models",
+ "max_audio_length_hours": 8.4,
+ "max_audio_per_prompt": 1,
+ "max_images_per_prompt": 3000,
+ "max_input_tokens": 1048576,
+ "max_output_tokens": 65535,
+ "max_pdf_size_mb": 30,
+ "max_tokens": 65535,
+ "max_video_length": 1,
+ "max_videos_per_prompt": 10,
+ "mode": "chat",
+ "output_cost_per_token": 1.2e-05,
+ "output_cost_per_token_above_200k_tokens": 1.8e-05,
+ "output_cost_per_token_batches": 6e-06,
+ "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/completions",
+ "/v1/batch"
+ ],
+ "supported_modalities": [
+ "text",
+ "image",
+ "audio",
+ "video"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_audio_input": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_video_input": true,
+ "supports_vision": true,
+ "supports_web_search": true
+ },
+ "vertex_ai/gemini-3-pro-preview": {
+ "cache_read_input_token_cost": 2e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 4e-07,
+ "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07,
+ "input_cost_per_token": 2e-06,
+ "input_cost_per_token_above_200k_tokens": 4e-06,
+ "input_cost_per_token_batches": 1e-06,
+ "litellm_provider": "vertex_ai",
+ "max_audio_length_hours": 8.4,
+ "max_audio_per_prompt": 1,
+ "max_images_per_prompt": 3000,
+ "max_input_tokens": 1048576,
+ "max_output_tokens": 65535,
+ "max_pdf_size_mb": 30,
+ "max_tokens": 65535,
+ "max_video_length": 1,
+ "max_videos_per_prompt": 10,
+ "mode": "chat",
+ "output_cost_per_token": 1.2e-05,
+ "output_cost_per_token_above_200k_tokens": 1.8e-05,
+ "output_cost_per_token_batches": 6e-06,
+ "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/completions",
+ "/v1/batch"
+ ],
+ "supported_modalities": [
+ "text",
+ "image",
+ "audio",
+ "video"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_audio_input": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_video_input": true,
+ "supports_vision": true,
+ "supports_web_search": true
+ },
"gemini-2.5-pro-exp-03-25": {
"cache_read_input_token_cost": 3.125e-07,
"input_cost_per_token": 1.25e-06,
@@ -12242,6 +13527,55 @@
"supports_web_search": true,
"tpm": 800000
},
+ "gemini/gemini-3-pro-preview": {
+ "cache_read_input_token_cost": 2e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 4e-07,
+ "input_cost_per_token": 2e-06,
+ "input_cost_per_token_above_200k_tokens": 4e-06,
+ "input_cost_per_token_batches": 1e-06,
+ "litellm_provider": "gemini",
+ "max_audio_length_hours": 8.4,
+ "max_audio_per_prompt": 1,
+ "max_images_per_prompt": 3000,
+ "max_input_tokens": 1048576,
+ "max_output_tokens": 65535,
+ "max_pdf_size_mb": 30,
+ "max_tokens": 65535,
+ "max_video_length": 1,
+ "max_videos_per_prompt": 10,
+ "mode": "chat",
+ "output_cost_per_token": 1.2e-05,
+ "output_cost_per_token_above_200k_tokens": 1.8e-05,
+ "output_cost_per_token_batches": 6e-06,
+ "rpm": 2000,
+ "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
+ "supported_endpoints": [
+ "/v1/chat/completions",
+ "/v1/completions",
+ "/v1/batch"
+ ],
+ "supported_modalities": [
+ "text",
+ "image",
+ "audio",
+ "video"
+ ],
+ "supported_output_modalities": [
+ "text"
+ ],
+ "supports_audio_input": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_system_messages": true,
+ "supports_tool_choice": true,
+ "supports_video_input": true,
+ "supports_vision": true,
+ "supports_web_search": true,
+ "tpm": 800000
+ },
"gemini/gemini-2.5-pro-exp-03-25": {
"cache_read_input_token_cost": 0.0,
"input_cost_per_token": 0.0,
@@ -12585,7 +13919,7 @@
"supports_audio_output": false,
"supports_function_calling": true,
"supports_response_schema": true,
- "supports_system_messages": true,
+ "supports_system_messages": false,
"supports_tool_choice": true,
"supports_vision": true
},
@@ -12794,12 +14128,13 @@
"input_cost_per_token": 1.1e-06,
"litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
@@ -15561,20 +16896,23 @@
"cache_creation_input_token_cost": 1.375e-06,
"cache_read_input_token_cost": 1.1e-07,
"input_cost_per_token": 1.1e-06,
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"lambda_ai/deepseek-llama3.3-70b": {
"input_cost_per_token": 2e-07,
@@ -20754,16 +22092,6 @@
"output_cost_per_token": 0.0,
"output_vector_size": 1536
},
- "text-embedding-ada-002-v2": {
- "input_cost_per_token": 1e-07,
- "input_cost_per_token_batches": 5e-08,
- "litellm_provider": "openai",
- "max_input_tokens": 8191,
- "max_tokens": 8191,
- "mode": "embedding",
- "output_cost_per_token": 0.0,
- "output_cost_per_token_batches": 0.0
- },
"text-embedding-large-exp-03-07": {
"input_cost_per_character": 2.5e-08,
"input_cost_per_token": 1e-07,
@@ -21352,20 +22680,23 @@
"cache_creation_input_token_cost": 1.375e-06,
"cache_read_input_token_cost": 1.1e-07,
"input_cost_per_token": 1.1e-06,
- "litellm_provider": "bedrock",
+ "litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"source": "https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock",
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
- "supports_tool_choice": true
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
},
"us.anthropic.claude-3-5-sonnet-20240620-v1:0": {
"input_cost_per_token": 3e-06,
@@ -21523,14 +22854,16 @@
"input_cost_per_token": 1.1e-06,
"litellm_provider": "bedrock_converse",
"max_input_tokens": 200000,
- "max_output_tokens": 8192,
- "max_tokens": 8192,
+ "max_output_tokens": 64000,
+ "max_tokens": 64000,
"mode": "chat",
"output_cost_per_token": 5.5e-06,
"supports_assistant_prefill": true,
+ "supports_computer_use": true,
"supports_function_calling": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
+ "supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_vision": true,
@@ -23157,6 +24490,12 @@
"supports_reasoning": true,
"supports_tool_choice": true
},
+ "vertex_ai/gemini-2.5-flash-image": {
+ "litellm_provider": "vertex_ai-language-models",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.039,
+ "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation#edit-an-image"
+ },
"vertex_ai/imagegeneration@006": {
"litellm_provider": "vertex_ai-image-models",
"mode": "image_generation",
@@ -23181,6 +24520,12 @@
"output_cost_per_image": 0.04,
"source": "https://cloud.google.com/vertex-ai/generative-ai/pricing"
},
+ "vertex_ai/imagen-3.0-capability-001": {
+ "litellm_provider": "vertex_ai-image-models",
+ "mode": "image_generation",
+ "output_cost_per_image": 0.04,
+ "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/image/edit-insert-objects"
+ },
"vertex_ai/imagen-4.0-fast-generate-001": {
"litellm_provider": "vertex_ai-image-models",
"mode": "image_generation",
@@ -23676,7 +25021,7 @@
"max_input_tokens": 1024,
"max_tokens": 1024,
"mode": "video_generation",
- "output_cost_per_second": 0.4,
+ "output_cost_per_second": 0.15,
"source": "https://ai.google.dev/gemini-api/docs/video",
"supported_modalities": [
"text"
@@ -23690,7 +25035,35 @@
"max_input_tokens": 1024,
"max_tokens": 1024,
"mode": "video_generation",
- "output_cost_per_second": 0.75,
+ "output_cost_per_second": 0.4,
+ "source": "https://ai.google.dev/gemini-api/docs/video",
+ "supported_modalities": [
+ "text"
+ ],
+ "supported_output_modalities": [
+ "video"
+ ]
+ },
+ "vertex_ai/veo-3.0-fast-generate-001": {
+ "litellm_provider": "vertex_ai-video-models",
+ "max_input_tokens": 1024,
+ "max_tokens": 1024,
+ "mode": "video_generation",
+ "output_cost_per_second": 0.15,
+ "source": "https://ai.google.dev/gemini-api/docs/video",
+ "supported_modalities": [
+ "text"
+ ],
+ "supported_output_modalities": [
+ "video"
+ ]
+ },
+ "vertex_ai/veo-3.0-generate-001": {
+ "litellm_provider": "vertex_ai-video-models",
+ "max_input_tokens": 1024,
+ "max_tokens": 1024,
+ "mode": "video_generation",
+ "output_cost_per_second": 0.4,
"source": "https://ai.google.dev/gemini-api/docs/video",
"supported_modalities": [
"text"
diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
index aefbbc8d4a2..f28c9b5acbe 100644
--- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
+++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
@@ -10,25 +10,39 @@ import asyncio
import datetime
import hashlib
import json
-from typing import Any, Dict, List, Optional, Set, Union, cast
+import re
+from typing import Any, Dict, List, Optional, Set, Tuple, Union, cast
+from urllib.parse import urlparse
from fastapi import HTTPException
-from mcp.types import CallToolRequestParams as MCPCallToolRequestParams
+from httpx import HTTPStatusError
+from mcp import ReadResourceResult, Resource
+from mcp.types import (
+ CallToolRequestParams as MCPCallToolRequestParams,
+ GetPromptRequestParams,
+ GetPromptResult,
+ Prompt,
+ ResourceTemplate,
+)
from mcp.types import CallToolResult
from mcp.types import Tool as MCPTool
+from pydantic import AnyUrl
+
+import litellm
from litellm._logging import verbose_logger
from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException
from litellm.experimental_mcp_client.client import MCPClient
+from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import (
MCPRequestHandler,
)
from litellm.proxy._experimental.mcp_server.utils import (
- add_server_prefix_to_tool_name,
- get_server_name_prefix_tool_mcp,
+ add_server_prefix_to_name,
get_server_prefix,
is_tool_name_prefixed,
normalize_server_name,
+ split_server_prefix_from_name,
validate_mcp_server_name,
)
from litellm.proxy._types import (
@@ -38,12 +52,15 @@ from litellm.proxy._types import (
MCPTransportType,
UserAPIKeyAuth,
)
-from litellm.proxy.common_utils.encrypt_decrypt_utils import (
- decrypt_value_helper,
-)
+from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper
from litellm.proxy.utils import ProxyLogging
+from litellm.types.llms.custom_http import httpxSpecialProvider
from litellm.types.mcp import MCPAuth, MCPStdioConfig
-from litellm.types.mcp_server.mcp_server_manager import MCPInfo, MCPServer
+from litellm.types.mcp_server.mcp_server_manager import (
+ MCPInfo,
+ MCPOAuthMetadata,
+ MCPServer,
+)
def _deserialize_json_dict(data: Any) -> Optional[Dict[str, str]]:
@@ -100,7 +117,7 @@ class MCPServerManager:
"""
return self.config_mcp_servers | self.registry
- def load_servers_from_config(
+ async def load_servers_from_config(
self,
mcp_servers_config: Dict[str, Any],
mcp_aliases: Optional[Dict[str, str]] = None,
@@ -180,35 +197,57 @@ class MCPServerManager:
)()
name_for_prefix = get_server_prefix(temp_server)
+ server_url = server_config.get("url", None) or ""
# Generate stable server ID based on parameters
server_id = self._generate_stable_server_id(
server_name=server_name,
- url=server_config.get("url", None) or "",
+ url=server_url,
transport=server_config.get("transport", MCPTransport.http),
auth_type=server_config.get("auth_type", None),
alias=alias,
)
+ auth_type = server_config.get("auth_type", None)
+ if server_url and auth_type is not None and auth_type == MCPAuth.oauth2:
+ mcp_oauth_metadata = await self._descovery_metadata(
+ server_url=server_url,
+ )
+ else:
+ mcp_oauth_metadata = None
+
+ resolved_scopes = server_config.get("scopes") or (
+ mcp_oauth_metadata.scopes if mcp_oauth_metadata else None
+ )
+ resolved_authorization_url = server_config.get("authorization_url") or (
+ mcp_oauth_metadata.authorization_url if mcp_oauth_metadata else None
+ )
+ resolved_token_url = server_config.get("token_url") or (
+ mcp_oauth_metadata.token_url if mcp_oauth_metadata else None
+ )
+ resolved_registration_url = server_config.get("registration_url") or (
+ mcp_oauth_metadata.registration_url if mcp_oauth_metadata else None
+ )
+
new_server = MCPServer(
server_id=server_id,
name=name_for_prefix,
alias=alias,
server_name=server_name,
spec_path=server_config.get("spec_path", None),
- url=server_config.get("url", None) or "",
+ url=server_url,
command=server_config.get("command", None) or "",
args=server_config.get("args", None) or [],
env=server_config.get("env", None) or {},
# oauth specific fields
client_id=server_config.get("client_id", None),
client_secret=server_config.get("client_secret", None),
- scopes=server_config.get("scopes", None),
- authorization_url=server_config.get("authorization_url", None),
- token_url=server_config.get("token_url", None),
- registration_url=server_config.get("registration_url", None),
+ scopes=resolved_scopes,
+ authorization_url=resolved_authorization_url,
+ token_url=resolved_token_url,
+ registration_url=resolved_registration_url,
# TODO: utility fn the default values
transport=server_config.get("transport", MCPTransport.http),
- auth_type=server_config.get("auth_type", None),
+ auth_type=auth_type,
authentication_token=server_config.get(
"authentication_token", server_config.get("auth_value", None)
),
@@ -327,7 +366,7 @@ class MCPServerManager:
base_tool_name = operation_id.replace(" ", "_").lower()
# Add server prefix to tool name
- prefixed_tool_name = add_server_prefix_to_tool_name(
+ prefixed_tool_name = add_server_prefix_to_name(
base_tool_name, server_prefix
)
@@ -356,12 +395,12 @@ class MCPServerManager:
)
# Update tool name to server name mapping (for both prefixed and base names)
- self.tool_name_to_mcp_server_name_mapping[
- base_tool_name
- ] = server_prefix
- self.tool_name_to_mcp_server_name_mapping[
- prefixed_tool_name
- ] = server_prefix
+ self.tool_name_to_mcp_server_name_mapping[base_tool_name] = (
+ server_prefix
+ )
+ self.tool_name_to_mcp_server_name_mapping[prefixed_tool_name] = (
+ server_prefix
+ )
registered_count += 1
verbose_logger.debug(
@@ -685,12 +724,436 @@ class MCPServerManager:
f"Failed to get tools from server {server.name}: {str(e)}"
)
return []
- finally:
- if client:
+
+ async def get_prompts_from_server(
+ self,
+ server: MCPServer,
+ mcp_auth_header: Optional[Union[str, Dict[str, str]]] = None,
+ extra_headers: Optional[Dict[str, str]] = None,
+ add_prefix: bool = True,
+ ) -> List[Prompt]:
+ """
+ Helper method to get prompts from a single MCP server with prefixed names.
+
+ Args:
+ server (MCPServer): The server to query prompts from
+ mcp_auth_header: Optional auth header for MCP server
+
+ Returns:
+ List[Prompt]: List of prompts available on the server with prefixed names
+ """
+
+ verbose_logger.debug(f"Connecting to url: {server.url}")
+ verbose_logger.info(f"get_prompts_from_server for {server.name}...")
+
+ client = None
+
+ try:
+ if server.static_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ extra_headers.update(server.static_headers)
+
+ client = self._create_mcp_client(
+ server=server,
+ mcp_auth_header=mcp_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ prompts = await client.list_prompts()
+
+ prefixed_or_original_prompts = self._create_prefixed_prompts(
+ prompts, server, add_prefix=add_prefix
+ )
+
+ return prefixed_or_original_prompts
+
+ except Exception as e:
+ verbose_logger.warning(
+ f"Failed to get prompts from server {server.name}: {str(e)}"
+ )
+ return []
+
+ async def get_resources_from_server(
+ self,
+ server: MCPServer,
+ mcp_auth_header: Optional[Union[str, Dict[str, str]]] = None,
+ extra_headers: Optional[Dict[str, str]] = None,
+ add_prefix: bool = True,
+ ) -> List[Resource]:
+ """Fetch available resources from a single MCP server."""
+
+ verbose_logger.debug(f"Connecting to url: {server.url}")
+ verbose_logger.info(f"get_resources_from_server for {server.name}...")
+
+ client = None
+
+ try:
+ if server.static_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ extra_headers.update(server.static_headers)
+
+ client = self._create_mcp_client(
+ server=server,
+ mcp_auth_header=mcp_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ resources = await client.list_resources()
+
+ prefixed_resources = self._create_prefixed_resources(
+ resources, server, add_prefix=add_prefix
+ )
+
+ return prefixed_resources
+
+ except Exception as e:
+ verbose_logger.warning(
+ f"Failed to get resources from server {server.name}: {str(e)}"
+ )
+ return []
+
+ async def get_resource_templates_from_server(
+ self,
+ server: MCPServer,
+ mcp_auth_header: Optional[Union[str, Dict[str, str]]] = None,
+ extra_headers: Optional[Dict[str, str]] = None,
+ add_prefix: bool = True,
+ ) -> List[ResourceTemplate]:
+ """Fetch available resource templates from a single MCP server."""
+
+ verbose_logger.debug(f"Connecting to url: {server.url}")
+ verbose_logger.info(f"get_resource_templates_from_server for {server.name}...")
+
+ client = None
+
+ try:
+ if server.static_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ extra_headers.update(server.static_headers)
+
+ client = self._create_mcp_client(
+ server=server,
+ mcp_auth_header=mcp_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ resource_templates = await client.list_resource_templates()
+
+ prefixed_templates = self._create_prefixed_resource_templates(
+ resource_templates, server, add_prefix=add_prefix
+ )
+
+ return prefixed_templates
+
+ except Exception as e:
+ verbose_logger.warning(
+ f"Failed to get resource templates from server {server.name}: {str(e)}"
+ )
+ return []
+
+ async def read_resource_from_server(
+ self,
+ server: MCPServer,
+ url: AnyUrl,
+ mcp_auth_header: Optional[Union[str, Dict[str, str]]] = None,
+ extra_headers: Optional[Dict[str, str]] = None,
+ ) -> ReadResourceResult:
+ """Read resource contents from a specific MCP server."""
+
+ verbose_logger.debug(f"Connecting to url: {server.url}")
+ verbose_logger.info(f"read_resource_from_server for {server.name}...")
+
+ if server.static_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ extra_headers.update(server.static_headers)
+
+ client = self._create_mcp_client(
+ server=server,
+ mcp_auth_header=mcp_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ return await client.read_resource(url)
+
+ async def get_prompt_from_server(
+ self,
+ server: MCPServer,
+ prompt_name: str,
+ arguments: Optional[Dict[str, Any]] = None,
+ mcp_auth_header: Optional[Union[str, Dict[str, str]]] = None,
+ extra_headers: Optional[Dict[str, str]] = None,
+ ) -> GetPromptResult:
+ """Fetch a specific prompt definition from a single MCP server."""
+
+ verbose_logger.debug(f"Connecting to url: {server.url}")
+ verbose_logger.info(f"get_prompt_from_server for {server.name}...")
+
+ if server.static_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ extra_headers.update(server.static_headers)
+
+ client = self._create_mcp_client(
+ server=server,
+ mcp_auth_header=mcp_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ get_prompt_request_params = GetPromptRequestParams(
+ name=prompt_name,
+ arguments=arguments,
+ )
+ return await client.get_prompt(get_prompt_request_params)
+
+ async def _descovery_metadata(
+ self,
+ server_url: str,
+ ) -> Optional[MCPOAuthMetadata]:
+ """Discover OAuth metadata by following RFC 9728 (protected resource metadata discovery)."""
+
+ try:
+ client = get_async_httpx_client(llm_provider=httpxSpecialProvider.MCP)
+ response = await client.get(server_url)
+ response.raise_for_status()
+ verbose_logger.warning(
+ "MCP OAuth discovery unexpectedly succeeded for %s; server did not challenge",
+ server_url,
+ )
+ raise RuntimeError("OAuth discovery must not succeed without a challenge")
+ except HTTPStatusError as exc:
+ verbose_logger.debug(
+ "MCP OAuth discovery for %s received status error: %s",
+ server_url,
+ exc,
+ )
+
+ header_value: Optional[str] = None
+ if exc.response is not None:
+ header_value = exc.response.headers.get(
+ "WWW-Authenticate"
+ ) or exc.response.headers.get("www-authenticate")
+
+ resource_metadata_url, scopes = self._parse_www_authenticate_header(
+ header_value
+ )
+
+ authorization_servers: List[str] = []
+ resource_scopes: Optional[List[str]] = None
+ if resource_metadata_url:
+ (
+ authorization_servers,
+ resource_scopes,
+ ) = await self._fetch_oauth_metadata_from_resource(
+ resource_metadata_url
+ )
+ else:
+ (
+ authorization_servers,
+ resource_scopes,
+ ) = await self._attempt_well_known_discovery(server_url)
+
+ metadata = None
+ if not authorization_servers:
try:
- await client.disconnect()
+ parsed_url = urlparse(server_url)
+ if parsed_url.scheme and parsed_url.netloc:
+ authorization_servers = [
+ f"{parsed_url.scheme}://{parsed_url.netloc}"
+ ]
except Exception:
- pass
+ authorization_servers = []
+
+ if authorization_servers:
+ metadata = await self._fetch_authorization_server_metadata(
+ authorization_servers
+ )
+
+ preferred_scopes = scopes or resource_scopes
+ if metadata is None and preferred_scopes:
+ metadata = MCPOAuthMetadata(scopes=preferred_scopes)
+ elif metadata is not None and preferred_scopes:
+ metadata.scopes = preferred_scopes
+
+ return metadata
+ except Exception as exc: # pragma: no cover - network/transient issues
+ verbose_logger.debug(
+ "MCP OAuth discovery failed for %s: %s", server_url, exc
+ )
+ return None
+
+ def _parse_www_authenticate_header(
+ self, header_value: Optional[str]
+ ) -> Tuple[Optional[str], Optional[List[str]]]:
+ if not header_value:
+ return None, None
+
+ _, _, params_section = header_value.partition(" ")
+ params_section = params_section or header_value
+
+ param_pattern = re.compile(r"([a-zA-Z0-9_]+)\s*=\s*\"?([^\",]+)\"?")
+ params: Dict[str, str] = {
+ match.group(1).lower(): match.group(2).strip()
+ for match in param_pattern.finditer(params_section)
+ }
+
+ resource_metadata_url = params.get("resource_metadata")
+
+ scope_value = params.get("scope")
+ scopes_list = [s for s in (scope_value.split() if scope_value else []) if s]
+ scopes = scopes_list or None
+
+ return resource_metadata_url, scopes
+
+ async def _fetch_oauth_metadata_from_resource(
+ self, resource_metadata_url: str
+ ) -> Tuple[List[str], Optional[List[str]]]:
+ if not resource_metadata_url:
+ return [], None
+
+ try:
+ client = get_async_httpx_client(
+ llm_provider=httpxSpecialProvider.MCP,
+ params={"timeout": 10.0},
+ )
+ response = await client.get(resource_metadata_url)
+ response.raise_for_status()
+ data = response.json()
+ except Exception as exc: # pragma: no cover - network issues
+ verbose_logger.debug(
+ "Failed to fetch MCP OAuth metadata from %s: %s",
+ resource_metadata_url,
+ exc,
+ )
+ return [], None
+
+ raw_servers = data.get("authorization_servers")
+ if isinstance(raw_servers, list):
+ authorization_servers = [
+ entry
+ for entry in raw_servers
+ if isinstance(entry, str) and entry.strip() != ""
+ ]
+ else:
+ authorization_servers = []
+
+ scopes = self._extract_scopes(
+ data.get("scopes_supported") or data.get("scopes")
+ )
+
+ return authorization_servers, scopes
+
+ async def _attempt_well_known_discovery(
+ self, server_url: str
+ ) -> Tuple[List[str], Optional[List[str]]]:
+ try:
+ parsed = urlparse(server_url)
+ except Exception:
+ return [], None
+
+ if not parsed.scheme or not parsed.netloc:
+ return [], None
+
+ base = f"{parsed.scheme}://{parsed.netloc}"
+ path = parsed.path or ""
+ path = path.strip("/")
+
+ candidate_urls: List[str] = []
+ if path:
+ candidate_urls.append(f"{base}/.well-known/oauth-protected-resource/{path}")
+ candidate_urls.append(f"{base}/.well-known/oauth-protected-resource")
+
+ for url in candidate_urls:
+ (
+ authorization_servers,
+ scopes,
+ ) = await self._fetch_oauth_metadata_from_resource(url)
+ if authorization_servers:
+ return authorization_servers, scopes
+
+ return [], None
+
+ async def _fetch_authorization_server_metadata(
+ self, authorization_servers: List[str]
+ ) -> Optional[MCPOAuthMetadata]:
+ for issuer in authorization_servers:
+ metadata = await self._fetch_single_authorization_server_metadata(issuer)
+ if metadata is not None:
+ return metadata
+ return None
+
+ async def _fetch_single_authorization_server_metadata(
+ self, issuer_url: str
+ ) -> Optional[MCPOAuthMetadata]:
+ try:
+ parsed = urlparse(issuer_url)
+ except Exception:
+ return None
+
+ if not parsed.scheme or not parsed.netloc:
+ return None
+
+ base = f"{parsed.scheme}://{parsed.netloc}"
+ path = (parsed.path or "").strip("/")
+
+ candidate_urls: List[str] = []
+ if path:
+ candidate_urls.append(
+ f"{base}/.well-known/oauth-authorization-server/{path}"
+ )
+ candidate_urls.append(f"{base}/.well-known/openid-configuration/{path}")
+ candidate_urls.append(f"{base}/.well-known/oauth-authorization-server")
+ candidate_urls.append(f"{base}/.well-known/openid-configuration")
+ candidate_urls.append(issuer_url.rstrip("/"))
+
+ for url in candidate_urls:
+ try:
+ client = get_async_httpx_client(
+ llm_provider=httpxSpecialProvider.MCP,
+ params={"timeout": 10.0},
+ )
+ response = await client.get(url)
+ response.raise_for_status()
+ data = response.json()
+ except Exception as exc: # pragma: no cover - network issues
+ verbose_logger.debug(
+ "Failed to fetch authorization metadata from %s: %s",
+ url,
+ exc,
+ )
+ continue
+
+ scopes = self._extract_scopes(data.get("scopes_supported"))
+ metadata = MCPOAuthMetadata(
+ scopes=scopes,
+ authorization_url=data.get("authorization_endpoint"),
+ token_url=data.get("token_endpoint"),
+ registration_url=data.get("registration_endpoint"),
+ )
+
+ if any(
+ [
+ metadata.scopes,
+ metadata.authorization_url,
+ metadata.token_url,
+ metadata.registration_url,
+ ]
+ ):
+ return metadata
+
+ return None
+
+ def _extract_scopes(self, scopes_value: Any) -> Optional[List[str]]:
+ if isinstance(scopes_value, str):
+ scopes = [s.strip() for s in scopes_value.split() if s.strip()]
+ return scopes or None
+ if isinstance(scopes_value, list):
+ scopes = [s for s in scopes_value if isinstance(s, str) and s.strip()]
+ return scopes or None
+ return None
async def _fetch_tools_with_timeout(
self, client: MCPClient, server_name: str
@@ -708,8 +1171,6 @@ class MCPServerManager:
async def _list_tools_task():
try:
- await client.connect()
-
tools = await client.list_tools()
verbose_logger.debug(f"Tools from {server_name}: {tools}")
return tools
@@ -721,11 +1182,6 @@ class MCPServerManager:
f"Client operation failed for {server_name}: {str(e)}"
)
return []
- finally:
- try:
- await client.disconnect()
- except Exception:
- pass
try:
return await asyncio.wait_for(_list_tools_task(), timeout=30.0)
@@ -763,7 +1219,7 @@ class MCPServerManager:
prefix = get_server_prefix(server)
for tool in tools:
- prefixed_name = add_server_prefix_to_tool_name(tool.name, prefix)
+ prefixed_name = add_server_prefix_to_name(tool.name, prefix)
name_to_use = prefixed_name if add_prefix else tool.name
@@ -783,6 +1239,82 @@ class MCPServerManager:
)
return prefixed_tools
+ def _create_prefixed_prompts(
+ self, prompts: List[Prompt], server: MCPServer, add_prefix: bool = True
+ ) -> List[Prompt]:
+ """
+ Create prefixed prompts and update prompt mapping.
+
+ Args:
+ prompts: List of original prompts from server
+ server: Server instance
+
+ Returns:
+ List of prompts with prefixed names
+ """
+ prefixed_prompts = []
+ prefix = get_server_prefix(server)
+
+ for prompt in prompts:
+ prefixed_name = add_server_prefix_to_name(prompt.name, prefix)
+
+ name_to_use = prefixed_name if add_prefix else prompt.name
+
+ prompt.name = name_to_use
+ prefixed_prompts.append(prompt)
+
+ verbose_logger.info(
+ f"Successfully fetched {len(prefixed_prompts)} prompts from server {server.name}"
+ )
+ return prefixed_prompts
+
+ def _create_prefixed_resources(
+ self, resources: List[Resource], server: MCPServer, add_prefix: bool = True
+ ) -> List[Resource]:
+ """Prefix resource names and track origin server for read requests."""
+
+ prefixed_resources: List[Resource] = []
+ prefix = get_server_prefix(server)
+
+ for resource in resources:
+ name_to_use = (
+ add_server_prefix_to_name(resource.name, prefix)
+ if add_prefix
+ else resource.name
+ )
+ resource.name = name_to_use
+ prefixed_resources.append(resource)
+
+ verbose_logger.info(
+ f"Successfully fetched {len(prefixed_resources)} resources from server {server.name}"
+ )
+ return prefixed_resources
+
+ def _create_prefixed_resource_templates(
+ self,
+ resource_templates: List[ResourceTemplate],
+ server: MCPServer,
+ add_prefix: bool = True,
+ ) -> List[ResourceTemplate]:
+ """Prefix resource template names for multi-server scenarios."""
+
+ prefixed_templates: List[ResourceTemplate] = []
+ prefix = get_server_prefix(server)
+
+ for resource_template in resource_templates:
+ name_to_use = (
+ add_server_prefix_to_name(resource_template.name, prefix)
+ if add_prefix
+ else resource_template.name
+ )
+ resource_template.name = name_to_use
+ prefixed_templates.append(resource_template)
+
+ verbose_logger.info(
+ f"Successfully fetched {len(prefixed_templates)} resource templates from server {server.name}"
+ )
+ return prefixed_templates
+
def check_allowed_or_banned_tools(self, tool_name: str, server: MCPServer) -> bool:
"""
Check if the tool is allowed or banned for the given server
@@ -817,7 +1349,7 @@ class MCPServerManager:
HTTPException: If allowed_params is configured for this tool but arguments contain disallowed params
"""
from litellm.proxy._experimental.mcp_server.utils import (
- get_server_name_prefix_tool_mcp,
+ split_server_prefix_from_name,
)
# If no allowed_params configured, return all arguments
@@ -825,7 +1357,7 @@ class MCPServerManager:
return
# Get the unprefixed tool name to match against config
- unprefixed_tool_name, _ = get_server_name_prefix_tool_mcp(tool_name)
+ unprefixed_tool_name, _ = split_server_prefix_from_name(tool_name)
# Check both prefixed and unprefixed tool names
allowed_params_list = server.allowed_params.get(
@@ -1169,14 +1701,12 @@ class MCPServerManager:
)
async def _call_tool_via_client(client, params):
- async with client:
- return await client.call_tool(params)
+ return await client.call_tool(params)
tasks.append(
asyncio.create_task(_call_tool_via_client(client, call_tool_params))
)
- # IMPORTANT: Must await tasks INSIDE the context manager to keep connection alive
try:
mcp_responses = await asyncio.gather(*tasks)
except (
@@ -1228,7 +1758,7 @@ class MCPServerManager:
start_time = datetime.datetime.now()
# Get the MCP server
- prefixed_tool_name = add_server_prefix_to_tool_name(name, server_name)
+ prefixed_tool_name = add_server_prefix_to_name(name, server_name)
mcp_server = self._get_mcp_server_from_tool_name(prefixed_tool_name)
if mcp_server is None:
raise ValueError(f"Tool {name} not found")
@@ -1334,7 +1864,7 @@ class MCPServerManager:
for tool in tools:
# The tool.name here is already prefixed from _get_tools_from_server
# Extract original name for mapping
- original_name, _ = get_server_name_prefix_tool_mcp(tool.name)
+ original_name, _ = split_server_prefix_from_name(tool.name)
self.tool_name_to_mcp_server_name_mapping[original_name] = server.name
self.tool_name_to_mcp_server_name_mapping[tool.name] = server.name
@@ -1362,7 +1892,7 @@ class MCPServerManager:
(
original_tool_name,
server_name_from_prefix,
- ) = get_server_name_prefix_tool_mcp(tool_name)
+ ) = split_server_prefix_from_name(tool_name)
if original_tool_name in self.tool_name_to_mcp_server_name_mapping:
for server in self.get_registry().values():
if normalize_server_name(server.name) == normalize_server_name(
@@ -1408,11 +1938,16 @@ class MCPServerManager:
return server
return None
- def get_mcp_servers_from_ids(self, server_ids: List[str]) -> List[MCPServer]:
- servers = []
- registry = self.get_registry()
- for server in registry.values():
- if server.server_id in server_ids:
+ def get_public_mcp_servers(self) -> List[MCPServer]:
+ """
+ Get the public MCP servers
+ """
+ servers: List[MCPServer] = []
+ if litellm.public_mcp_servers is None:
+ return servers
+ for server_id in litellm.public_mcp_servers:
+ server = self.get_mcp_server_by_id(server_id)
+ if server:
servers.append(server)
return servers
diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index e427507a4b8..4288f25740c 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -76,12 +76,12 @@ if MCP_AVAILABLE:
mcp_auth_header=server_auth_header,
add_prefix=False,
)
-
+
# Filter tools based on allowed_tools configuration
# Only filter if allowed_tools is explicitly configured (not None and not empty)
if server.allowed_tools is not None and len(server.allowed_tools) > 0:
tools = filter_tools_by_allowed_tools(tools, server)
-
+
return _create_tool_response_objects(tools, server.mcp_info)
########################################################
@@ -212,7 +212,9 @@ if MCP_AVAILABLE:
from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException
from litellm.proxy.proxy_server import add_litellm_data_to_request, proxy_config
- from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import MCPRequestHandler
+ from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import (
+ MCPRequestHandler,
+ )
try:
data = await request.json()
@@ -222,21 +224,27 @@ if MCP_AVAILABLE:
user_api_key_dict=user_api_key_dict,
proxy_config=proxy_config,
)
-
+
# FIX: Extract MCP auth headers from request
# The UI sends bearer token in x-mcp-auth header and server-specific headers,
# but they weren't being extracted and passed to call_mcp_tool.
# This fix ensures auth headers are properly extracted from the HTTP request
# and passed through to the MCP server for authentication.
- mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(request.headers)
- mcp_server_auth_headers = MCPRequestHandler._get_mcp_server_auth_headers_from_headers(request.headers)
-
+ mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(
+ request.headers
+ )
+ mcp_server_auth_headers = (
+ MCPRequestHandler._get_mcp_server_auth_headers_from_headers(
+ request.headers
+ )
+ )
+
# Add extracted headers to data dict to pass to call_mcp_tool
if mcp_auth_header:
data["mcp_auth_header"] = mcp_auth_header
if mcp_server_auth_headers:
data["mcp_server_auth_headers"] = mcp_server_auth_headers
-
+
result = await call_mcp_tool(**data)
return result
except BlockedPiiEntityError as e:
@@ -296,7 +304,6 @@ if MCP_AVAILABLE:
Returns:
Operation result or error response
"""
- client = None
try:
client = global_mcp_server_manager._create_mcp_client(
server=MCPServer(
@@ -315,13 +322,6 @@ if MCP_AVAILABLE:
except Exception as e:
verbose_logger.error(f"Error in MCP operation: {e}", exc_info=True)
return {"status": "error", "message": "An internal error has occurred."}
- finally:
- # Ensure client is properly disconnected before response is sent
- if client is not None:
- try:
- await client.disconnect()
- except Exception as e:
- verbose_logger.warning(f"Error disconnecting MCP client: {e}")
@router.post("/test/connection")
async def test_connection(
@@ -332,7 +332,10 @@ if MCP_AVAILABLE:
"""
async def _test_connection_operation(client):
- await client.connect()
+ async def _noop(session):
+ return "ok"
+
+ await client.run_with_session(_noop)
return {"status": "ok"}
return await _execute_with_mcp_client(request, _test_connection_operation)
@@ -347,7 +350,13 @@ if MCP_AVAILABLE:
"""
async def _list_tools_operation(client):
- list_tools_result: List[MCPTool] = await client.list_tools()
+ async def _list_tools_session_operation(session):
+ return await session.list_tools()
+
+ list_tools_response = await client.run_with_session(
+ _list_tools_session_operation
+ )
+ list_tools_result: List[MCPTool] = list_tools_response.tools
model_dumped_tools: List[dict] = [
tool.model_dump() for tool in list_tools_result
]
diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py
index ce29d2d32e1..61123743c60 100644
--- a/litellm/proxy/_experimental/mcp_server/server.py
+++ b/litellm/proxy/_experimental/mcp_server/server.py
@@ -8,7 +8,15 @@ from datetime import datetime
from typing import Any, AsyncIterator, Dict, List, Optional, Tuple, Union
from fastapi import FastAPI, HTTPException
-from pydantic import ConfigDict
+from mcp import ReadResourceResult, Resource
+from mcp.server.lowlevel.helper_types import ReadResourceContents
+from mcp.types import (
+ BlobResourceContents,
+ GetPromptResult,
+ ResourceTemplate,
+ TextResourceContents,
+)
+from pydantic import AnyUrl, ConfigDict
from starlette.types import Receive, Scope, Send
from litellm._logging import verbose_logger
@@ -54,6 +62,7 @@ if MCP_AVAILABLE:
from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
from mcp.types import EmbeddedResource, ImageContent, TextContent
from mcp.types import Tool as MCPTool
+ from mcp.types import Prompt
from litellm.proxy._experimental.mcp_server.auth.litellm_auth_handler import (
MCPAuthenticatedUser,
@@ -66,7 +75,7 @@ if MCP_AVAILABLE:
global_mcp_tool_registry,
)
from litellm.proxy._experimental.mcp_server.utils import (
- get_server_name_prefix_tool_mcp,
+ split_server_prefix_from_name,
)
######################################################
@@ -303,6 +312,208 @@ if MCP_AVAILABLE:
return response
+ @server.list_prompts()
+ async def list_prompts() -> List[Prompt]:
+ """
+ List all available prompts
+ """
+ try:
+ # Get user authentication from context variable
+ (
+ user_api_key_auth,
+ mcp_auth_header,
+ mcp_servers,
+ mcp_server_auth_headers,
+ oauth2_headers,
+ raw_headers,
+ ) = get_auth_context()
+ verbose_logger.debug(
+ f"MCP list_prompts - User API Key Auth from context: {user_api_key_auth}"
+ )
+ verbose_logger.debug(
+ f"MCP list_prompts - MCP servers from context: {mcp_servers}"
+ )
+ verbose_logger.debug(
+ f"MCP list_prompts - MCP server auth headers: {list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None}"
+ )
+ # Get mcp_servers from context variable
+ verbose_logger.debug("MCP list_prompts - Calling _list_prompts")
+ prompts = await _list_mcp_prompts(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.info(
+ f"MCP list_prompts - Successfully returned {len(prompts)} prompts"
+ )
+ return prompts
+ except Exception as e:
+ verbose_logger.exception(f"Error in list_prompts endpoint: {str(e)}")
+ # Return empty list instead of failing completely
+ # This prevents the HTTP stream from failing and allows the client to get a response
+ return []
+
+ @server.get_prompt()
+ async def get_prompt(
+ name: str, arguments: dict[str, str] | None
+ ) -> GetPromptResult:
+ """
+ Get a specific prompt with the provided arguments
+
+ Args:
+ name (str): Name of the prompt to get
+ arguments (Dict[str, Any] | None): Arguments to pass to the prompt
+
+ Returns:
+ GetPromptResult: Getting prompt execution results
+ """
+
+ # Validate arguments
+ (
+ user_api_key_auth,
+ mcp_auth_header,
+ mcp_servers,
+ mcp_server_auth_headers,
+ oauth2_headers,
+ raw_headers,
+ ) = get_auth_context()
+
+ verbose_logger.debug(
+ f"MCP mcp_server_tool_call - User API Key Auth from context: {user_api_key_auth}"
+ )
+ return await mcp_get_prompt(
+ name=name,
+ arguments=arguments,
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ @server.list_resources()
+ async def list_resources() -> List[Resource]:
+ """List all available resources."""
+ try:
+ (
+ user_api_key_auth,
+ mcp_auth_header,
+ mcp_servers,
+ mcp_server_auth_headers,
+ oauth2_headers,
+ raw_headers,
+ ) = get_auth_context()
+ verbose_logger.debug(
+ f"MCP list_resources - User API Key Auth from context: {user_api_key_auth}"
+ )
+ verbose_logger.debug(
+ f"MCP list_resources - MCP servers from context: {mcp_servers}"
+ )
+ verbose_logger.debug(
+ f"MCP list_resources - MCP server auth headers: {list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None}"
+ )
+
+ resources = await _list_mcp_resources(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.info(
+ f"MCP list_resources - Successfully returned {len(resources)} resources"
+ )
+ return resources
+ except Exception as e:
+ verbose_logger.exception(f"Error in list_resources endpoint: {str(e)}")
+ return []
+
+ @server.list_resource_templates()
+ async def list_resource_templates() -> List[ResourceTemplate]:
+ """List all available resource templates."""
+ try:
+ (
+ user_api_key_auth,
+ mcp_auth_header,
+ mcp_servers,
+ mcp_server_auth_headers,
+ oauth2_headers,
+ raw_headers,
+ ) = get_auth_context()
+ verbose_logger.debug(
+ f"MCP list_resource_templates - User API Key Auth from context: {user_api_key_auth}"
+ )
+ verbose_logger.debug(
+ f"MCP list_resource_templates - MCP servers from context: {mcp_servers}"
+ )
+ verbose_logger.debug(
+ f"MCP list_resource_templates - MCP server auth headers: {list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None}"
+ )
+
+ resource_templates = await _list_mcp_resource_templates(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.info(
+ "MCP list_resource_templates - Successfully returned "
+ f"{len(resource_templates)} resource templates"
+ )
+ return resource_templates
+ except Exception as e:
+ verbose_logger.exception(
+ f"Error in list_resource_templates endpoint: {str(e)}"
+ )
+ return []
+
+ @server.read_resource()
+ async def read_resource(url: AnyUrl) -> list[ReadResourceContents]:
+ (
+ user_api_key_auth,
+ mcp_auth_header,
+ mcp_servers,
+ mcp_server_auth_headers,
+ oauth2_headers,
+ raw_headers,
+ ) = get_auth_context()
+
+ read_resource_result = await mcp_read_resource(
+ url=url,
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ normalized_contents: List[ReadResourceContents] = []
+ for content in read_resource_result.contents:
+ if isinstance(content, TextResourceContents):
+ normalized_contents.append(
+ ReadResourceContents(
+ content=content.text,
+ mime_type=content.mimeType,
+ )
+ )
+ elif isinstance(content, BlobResourceContents):
+ normalized_contents.append(
+ ReadResourceContents(
+ content=content.blob,
+ mime_type=None,
+ )
+ )
+
+ return normalized_contents
+
########################################################
############ End of MCP Server Routes ##################
########################################################
@@ -379,7 +590,7 @@ if MCP_AVAILABLE:
True if the tool name (prefixed or unprefixed) is in the filter list
"""
from litellm.proxy._experimental.mcp_server.utils import (
- get_server_name_prefix_tool_mcp,
+ split_server_prefix_from_name,
)
# Check if the full name is in the list
@@ -387,7 +598,7 @@ if MCP_AVAILABLE:
return True
# Check if the unprefixed name is in the list
- unprefixed_name, _ = get_server_name_prefix_tool_mcp(tool_name)
+ unprefixed_name, _ = split_server_prefix_from_name(tool_name)
return unprefixed_name in filter_list
def filter_tools_by_allowed_tools(
@@ -428,6 +639,56 @@ if MCP_AVAILABLE:
return tools_to_return
+ async def _get_allowed_mcp_servers(
+ user_api_key_auth: Optional[UserAPIKeyAuth],
+ mcp_servers: Optional[List[str]],
+ ) -> List[MCPServer]:
+ """Return allowed MCP servers for a request after applying filters."""
+ allowed_mcp_server_ids = (
+ await global_mcp_server_manager.get_allowed_mcp_servers(user_api_key_auth)
+ )
+ allowed_mcp_servers = global_mcp_server_manager.get_mcp_servers_from_ids(
+ allowed_mcp_server_ids
+ )
+
+ if mcp_servers is not None:
+ allowed_mcp_servers = await _get_allowed_mcp_servers_from_mcp_server_names(
+ mcp_servers=mcp_servers,
+ allowed_mcp_servers=allowed_mcp_servers,
+ )
+
+ return allowed_mcp_servers
+
+ def _prepare_mcp_server_headers(
+ server: MCPServer,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]],
+ mcp_auth_header: Optional[str],
+ oauth2_headers: Optional[Dict[str, str]],
+ raw_headers: Optional[Dict[str, str]],
+ ) -> Tuple[Optional[Union[Dict[str, str], str]], Optional[Dict[str, str]]]:
+ """Build auth and extra headers for a server."""
+ server_auth_header: Optional[Union[Dict[str, str], str]] = None
+ if mcp_server_auth_headers and server.alias is not None:
+ server_auth_header = mcp_server_auth_headers.get(server.alias)
+ elif mcp_server_auth_headers and server.server_name is not None:
+ server_auth_header = mcp_server_auth_headers.get(server.server_name)
+
+ extra_headers: Optional[Dict[str, str]] = None
+ if server.auth_type == MCPAuth.oauth2:
+ extra_headers = oauth2_headers
+
+ if server.extra_headers and raw_headers:
+ if extra_headers is None:
+ extra_headers = {}
+ for header in server.extra_headers:
+ if header in raw_headers:
+ extra_headers[header] = raw_headers[header]
+
+ if server_auth_header is None:
+ server_auth_header = mcp_auth_header
+
+ return server_auth_header, extra_headers
+
async def _get_tools_from_mcp_servers(
user_api_key_auth: Optional[UserAPIKeyAuth],
mcp_auth_header: Optional[str],
@@ -452,19 +713,10 @@ if MCP_AVAILABLE:
if not MCP_AVAILABLE:
return []
- # Get allowed MCP servers based on user permissions
- allowed_mcp_server_ids = (
- await global_mcp_server_manager.get_allowed_mcp_servers(user_api_key_auth)
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
)
- allowed_mcp_servers = global_mcp_server_manager.get_mcp_servers_from_ids(
- allowed_mcp_server_ids
- )
-
- if mcp_servers is not None:
- allowed_mcp_servers = await _get_allowed_mcp_servers_from_mcp_server_names(
- mcp_servers=mcp_servers,
- allowed_mcp_servers=allowed_mcp_servers,
- )
# Decide whether to add prefix based on number of allowed servers
add_prefix = not (len(allowed_mcp_servers) == 1)
@@ -475,27 +727,13 @@ if MCP_AVAILABLE:
if server is None:
continue
- # Get server-specific auth header if available
- server_auth_header: Optional[Union[Dict[str, str], str]] = None
- if mcp_server_auth_headers and server.alias is not None:
- server_auth_header = mcp_server_auth_headers.get(server.alias)
- elif mcp_server_auth_headers and server.server_name is not None:
- server_auth_header = mcp_server_auth_headers.get(server.server_name)
-
- extra_headers: Optional[Dict[str, str]] = None
- if server.auth_type == MCPAuth.oauth2:
- extra_headers = oauth2_headers
-
- if server.extra_headers and raw_headers:
- if extra_headers is None:
- extra_headers = {}
- for header in server.extra_headers:
- if header in raw_headers:
- extra_headers[header] = raw_headers[header]
-
- # Fall back to deprecated mcp_auth_header if no server-specific header found
- if server_auth_header is None:
- server_auth_header = mcp_auth_header
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
try:
tools = await global_mcp_server_manager._get_tools_from_server(
@@ -530,6 +768,195 @@ if MCP_AVAILABLE:
return all_tools
+ async def _get_prompts_from_mcp_servers(
+ user_api_key_auth: Optional[UserAPIKeyAuth],
+ mcp_auth_header: Optional[str],
+ mcp_servers: Optional[List[str]],
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[Prompt]:
+ """
+ Helper method to fetch prompt from MCP servers based on server filtering criteria.
+
+ Args:
+ user_api_key_auth: User authentication info for access control
+ mcp_auth_header: Optional auth header for MCP server (deprecated)
+ mcp_servers: Optional list of server names/aliases to filter by
+ mcp_server_auth_headers: Optional dict of server-specific auth headers
+ oauth2_headers: Optional dict of oauth2 headers
+
+ Returns:
+ List[Prompt]: Combined list of prompts from filtered servers
+ """
+ if not MCP_AVAILABLE:
+ return []
+
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
+ )
+
+ # Decide whether to add prefix based on number of allowed servers
+ add_prefix = not (len(allowed_mcp_servers) == 1)
+
+ # Get prompts from each allowed server
+ all_prompts = []
+ for server in allowed_mcp_servers:
+ if server is None:
+ continue
+
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ try:
+ prompts = await global_mcp_server_manager.get_prompts_from_server(
+ server=server,
+ mcp_auth_header=server_auth_header,
+ extra_headers=extra_headers,
+ add_prefix=add_prefix,
+ )
+
+ all_prompts.extend(prompts)
+
+ verbose_logger.debug(
+ f"Successfully fetched {len(prompts)} prompts from server {server.name}"
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ f"Error getting prompts from server {server.name}: {str(e)}"
+ )
+ # Continue with other servers instead of failing completely
+
+ verbose_logger.info(
+ f"Successfully fetched {len(all_prompts)} prompts total from all MCP servers"
+ )
+
+ return all_prompts
+
+ async def _get_resources_from_mcp_servers(
+ user_api_key_auth: Optional[UserAPIKeyAuth],
+ mcp_auth_header: Optional[str],
+ mcp_servers: Optional[List[str]],
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[Resource]:
+ """Fetch resources from allowed MCP servers."""
+
+ if not MCP_AVAILABLE:
+ return []
+
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
+ )
+
+ add_prefix = not (len(allowed_mcp_servers) == 1)
+
+ all_resources: List[Resource] = []
+ for server in allowed_mcp_servers:
+ if server is None:
+ continue
+
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ try:
+ resources = await global_mcp_server_manager.get_resources_from_server(
+ server=server,
+ mcp_auth_header=server_auth_header,
+ extra_headers=extra_headers,
+ add_prefix=add_prefix,
+ )
+ all_resources.extend(resources)
+
+ verbose_logger.debug(
+ f"Successfully fetched {len(resources)} resources from server {server.name}"
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ f"Error getting resources from server {server.name}: {str(e)}"
+ )
+
+ verbose_logger.info(
+ f"Successfully fetched {len(all_resources)} resources total from all MCP servers"
+ )
+
+ return all_resources
+
+ async def _get_resource_templates_from_mcp_servers(
+ user_api_key_auth: Optional[UserAPIKeyAuth],
+ mcp_auth_header: Optional[str],
+ mcp_servers: Optional[List[str]],
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[ResourceTemplate]:
+ """Fetch resource templates from allowed MCP servers."""
+
+ if not MCP_AVAILABLE:
+ return []
+
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
+ )
+
+ add_prefix = not (len(allowed_mcp_servers) == 1)
+
+ all_resource_templates: List[ResourceTemplate] = []
+ for server in allowed_mcp_servers:
+ if server is None:
+ continue
+
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ try:
+ resource_templates = (
+ await global_mcp_server_manager.get_resource_templates_from_server(
+ server=server,
+ mcp_auth_header=server_auth_header,
+ extra_headers=extra_headers,
+ add_prefix=add_prefix,
+ )
+ )
+ all_resource_templates.extend(resource_templates)
+ verbose_logger.debug(
+ "Successfully fetched %s resource templates from server %s",
+ len(resource_templates),
+ server.name,
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ "Error getting resource templates from server %s: %s",
+ server.name,
+ str(e),
+ )
+
+ verbose_logger.info(
+ "Successfully fetched %s resource templates total from all MCP servers",
+ len(all_resource_templates),
+ )
+
+ return all_resource_templates
+
async def filter_tools_by_key_team_permissions(
tools: List[MCPTool],
server_id: str,
@@ -553,7 +980,7 @@ if MCP_AVAILABLE:
filtered_tools = []
for t in tools:
# Get tool name without server prefix
- unprefixed_tool_name, _ = get_server_name_prefix_tool_mcp(t.name)
+ unprefixed_tool_name, _ = split_server_prefix_from_name(t.name)
if unprefixed_tool_name in allowed_tool_names:
filtered_tools.append(t)
else:
@@ -606,6 +1033,118 @@ if MCP_AVAILABLE:
return managed_tools
+ async def _list_mcp_prompts(
+ user_api_key_auth: Optional[UserAPIKeyAuth] = None,
+ mcp_auth_header: Optional[str] = None,
+ mcp_servers: Optional[List[str]] = None,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[Prompt]:
+ """
+ List all available MCP prompts.
+
+ Args:
+ user_api_key_auth: User authentication info for access control
+ mcp_auth_header: Optional auth header for MCP server (deprecated)
+ mcp_servers: Optional list of server names/aliases to filter by
+ mcp_server_auth_headers: Optional dict of server-specific auth headers {server_alias: auth_value}
+
+ Returns:
+ List[Prompt]: Combined list of tools from all accessible servers
+ """
+ if not MCP_AVAILABLE:
+ return []
+ # Get tools from managed MCP servers with error handling
+ managed_prompts = []
+ try:
+ managed_prompts = await _get_prompts_from_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.debug(
+ f"Successfully fetched {len(managed_prompts)} prompts from managed MCP servers"
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ f"Error getting tools from managed MCP servers: {str(e)}"
+ )
+ # Continue with empty managed tools list instead of failing completely
+
+ return managed_prompts
+
+ async def _list_mcp_resources(
+ user_api_key_auth: Optional[UserAPIKeyAuth] = None,
+ mcp_auth_header: Optional[str] = None,
+ mcp_servers: Optional[List[str]] = None,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[Resource]:
+ """List all available MCP resources."""
+
+ if not MCP_AVAILABLE:
+ return []
+
+ managed_resources: List[Resource] = []
+ try:
+ managed_resources = await _get_resources_from_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.debug(
+ f"Successfully fetched {len(managed_resources)} resources from managed MCP servers"
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ f"Error getting resources from managed MCP servers: {str(e)}"
+ )
+
+ return managed_resources
+
+ async def _list_mcp_resource_templates(
+ user_api_key_auth: Optional[UserAPIKeyAuth] = None,
+ mcp_auth_header: Optional[str] = None,
+ mcp_servers: Optional[List[str]] = None,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> List[ResourceTemplate]:
+ """List all available MCP resource templates."""
+
+ if not MCP_AVAILABLE:
+ return []
+
+ managed_resource_templates: List[ResourceTemplate] = []
+ try:
+ managed_resource_templates = await _get_resource_templates_from_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_auth_header=mcp_auth_header,
+ mcp_servers=mcp_servers,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+ verbose_logger.debug(
+ "Successfully fetched %s resource templates from managed MCP servers",
+ len(managed_resource_templates),
+ )
+ except Exception as e:
+ verbose_logger.exception(
+ "Error getting resource templates from managed MCP servers: %s",
+ str(e),
+ )
+
+ return managed_resource_templates
+
@client
async def call_mcp_tool(
name: str,
@@ -640,24 +1179,31 @@ if MCP_AVAILABLE:
allowed_mcp_servers = await _get_allowed_mcp_servers_from_mcp_server_names(
mcp_servers=mcp_servers,
- allowed_mcp_servers=allowed_mcp_servers
+ allowed_mcp_servers=allowed_mcp_servers,
)
- server_name: Optional[str]
- if len(allowed_mcp_servers) == 1:
- original_tool_name, server_name = name, allowed_mcp_servers[0].server_name
- else:
- # Remove prefix from tool name for logging and processing
- original_tool_name, server_name = get_server_name_prefix_tool_mcp(name)
+ # Track resolved MCP server for both permission checks and dispatch
+ mcp_server: Optional[MCPServer] = None
- if not server_name or not MCPRequestHandler.is_tool_allowed(
- allowed_mcp_servers=[server.name for server in allowed_mcp_servers],
- server_name=server_name,
- ):
- raise HTTPException(
- status_code=403,
- detail=f"User not allowed to call this tool. Allowed MCP servers: {allowed_mcp_servers}",
- )
+ # Remove prefix from tool name for logging and processing
+ original_tool_name, server_name = split_server_prefix_from_name(name)
+
+ # If tool name is unprefixed, resolve its server so we can enforce permissions
+ if not server_name:
+ mcp_server = global_mcp_server_manager._get_mcp_server_from_tool_name(name)
+ if mcp_server:
+ server_name = mcp_server.name
+
+ # Only enforce server-level permissions when we can resolve a server
+ if server_name:
+ if not MCPRequestHandler.is_tool_allowed(
+ allowed_mcp_servers=[server.name for server in allowed_mcp_servers],
+ server_name=server_name,
+ ):
+ raise HTTPException(
+ status_code=403,
+ detail=f"User not allowed to call this tool. Allowed MCP servers: {allowed_mcp_servers}",
+ )
standard_logging_mcp_tool_call: StandardLoggingMCPToolCall = (
_get_standard_logging_mcp_tool_call(
@@ -686,9 +1232,11 @@ if MCP_AVAILABLE:
# Primary and recommended way to use external MCP servers
#########################################################
else:
- mcp_server: Optional[
- MCPServer
- ] = global_mcp_server_manager._get_mcp_server_from_tool_name(name)
+ # If we haven't already resolved the server, do it now for dispatch
+ if mcp_server is None:
+ mcp_server = global_mcp_server_manager._get_mcp_server_from_tool_name(
+ name
+ )
if mcp_server:
standard_logging_mcp_tool_call["mcp_server_cost_info"] = (
mcp_server.mcp_info or {}
@@ -726,6 +1274,110 @@ if MCP_AVAILABLE:
)
return response
+ async def mcp_get_prompt(
+ name: str,
+ arguments: Optional[Dict[str, Any]] = None,
+ user_api_key_auth: Optional[UserAPIKeyAuth] = None,
+ mcp_auth_header: Optional[str] = None,
+ mcp_servers: Optional[List[str]] = None,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> GetPromptResult:
+ """
+ Fetch a specific MCP prompt, handling both prefixed and unprefixed names.
+ """
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
+ )
+
+ if not allowed_mcp_servers:
+ raise HTTPException(
+ status_code=403,
+ detail="User not allowed to get this prompt.",
+ )
+
+ # Decide whether to add prefix based on number of allowed servers
+ add_prefix = not (len(allowed_mcp_servers) == 1)
+
+ if add_prefix:
+ original_prompt_name, server_name = split_server_prefix_from_name(name)
+ else:
+ original_prompt_name = name
+ server_name = allowed_mcp_servers[0].name
+
+ server = next((s for s in allowed_mcp_servers if s.name == server_name), None)
+ if server is None:
+ raise HTTPException(
+ status_code=403,
+ detail="User not allowed to get this prompt.",
+ )
+
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ return await global_mcp_server_manager.get_prompt_from_server(
+ server=server,
+ prompt_name=original_prompt_name,
+ arguments=arguments,
+ mcp_auth_header=server_auth_header,
+ extra_headers=extra_headers,
+ )
+
+ async def mcp_read_resource(
+ url: AnyUrl,
+ user_api_key_auth: Optional[UserAPIKeyAuth] = None,
+ mcp_auth_header: Optional[str] = None,
+ mcp_servers: Optional[List[str]] = None,
+ mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
+ oauth2_headers: Optional[Dict[str, str]] = None,
+ raw_headers: Optional[Dict[str, str]] = None,
+ ) -> ReadResourceResult:
+ """Read resource contents from upstream MCP servers."""
+
+ allowed_mcp_servers = await _get_allowed_mcp_servers(
+ user_api_key_auth=user_api_key_auth,
+ mcp_servers=mcp_servers,
+ )
+
+ if not allowed_mcp_servers:
+ raise HTTPException(
+ status_code=403,
+ detail="User not allowed to read this resource.",
+ )
+
+ if len(allowed_mcp_servers) != 1:
+ raise HTTPException(
+ status_code=400,
+ detail=(
+ "Multiple MCP servers configured; read_resource currently "
+ "supports exactly one allowed server."
+ ),
+ )
+
+ server = allowed_mcp_servers[0]
+
+ server_auth_header, extra_headers = _prepare_mcp_server_headers(
+ server=server,
+ mcp_server_auth_headers=mcp_server_auth_headers,
+ mcp_auth_header=mcp_auth_header,
+ oauth2_headers=oauth2_headers,
+ raw_headers=raw_headers,
+ )
+
+ return await global_mcp_server_manager.read_resource_from_server(
+ server=server,
+ url=url,
+ mcp_auth_header=server_auth_header,
+ extra_headers=extra_headers,
+ )
+
def _get_standard_logging_mcp_tool_call(
name: str,
arguments: Dict[str, Any],
diff --git a/litellm/proxy/_experimental/mcp_server/utils.py b/litellm/proxy/_experimental/mcp_server/utils.py
index fb28eaf8cf2..d801b312aac 100644
--- a/litellm/proxy/_experimental/mcp_server/utils.py
+++ b/litellm/proxy/_experimental/mcp_server/utils.py
@@ -13,6 +13,7 @@ LITELLM_MCP_SERVER_DESCRIPTION = "MCP Server for LiteLLM"
MCP_TOOL_PREFIX_SEPARATOR = os.environ.get("MCP_TOOL_PREFIX_SEPARATOR", "-")
MCP_TOOL_PREFIX_FORMAT = "{server_name}{separator}{tool_name}"
+
def is_mcp_available() -> bool:
"""
Returns True if the MCP module is available, False otherwise
@@ -23,92 +24,81 @@ def is_mcp_available() -> bool:
except ImportError:
return False
+
def normalize_server_name(server_name: str) -> str:
"""
Normalize server name by replacing spaces with underscores
"""
return server_name.replace(" ", "_")
+
def validate_and_normalize_mcp_server_payload(payload: Any) -> None:
"""
Validate and normalize MCP server payload fields (server_name and alias).
-
+
This function:
1. Validates that server_name and alias don't contain the MCP_TOOL_PREFIX_SEPARATOR
2. Normalizes alias by replacing spaces with underscores
3. Sets default alias if not provided (using server_name as base)
-
+
Args:
payload: The payload object containing server_name and alias fields
-
+
Raises:
HTTPException: If validation fails
"""
# Server name validation: disallow '-'
- if hasattr(payload, 'server_name') and payload.server_name:
+ if hasattr(payload, "server_name") and payload.server_name:
validate_mcp_server_name(payload.server_name, raise_http_exception=True)
-
+
# Alias validation: disallow '-'
- if hasattr(payload, 'alias') and payload.alias:
+ if hasattr(payload, "alias") and payload.alias:
validate_mcp_server_name(payload.alias, raise_http_exception=True)
-
+
# Alias normalization and defaulting
- alias = getattr(payload, 'alias', None)
- server_name = getattr(payload, 'server_name', None)
-
+ alias = getattr(payload, "alias", None)
+ server_name = getattr(payload, "server_name", None)
+
if not alias and server_name:
alias = normalize_server_name(server_name)
elif alias:
alias = normalize_server_name(alias)
-
+
# Update the payload with normalized alias
- if hasattr(payload, 'alias'):
+ if hasattr(payload, "alias"):
payload.alias = alias
-def add_server_prefix_to_tool_name(tool_name: str, server_name: str) -> str:
- """
- Add server name prefix to tool name
- Args:
- tool_name: Original tool name
- server_name: MCP server name
-
- Returns:
- Prefixed tool name in format: server_name::tool_name
- """
+def add_server_prefix_to_name(name: str, server_name: str) -> str:
+ """Add server name prefix to any MCP resource name."""
formatted_server_name = normalize_server_name(server_name)
return MCP_TOOL_PREFIX_FORMAT.format(
server_name=formatted_server_name,
separator=MCP_TOOL_PREFIX_SEPARATOR,
- tool_name=tool_name
+ tool_name=name,
)
+
def get_server_prefix(server: Any) -> str:
"""Return the prefix for a server: alias if present, else server_name, else server_id"""
- if hasattr(server, 'alias') and server.alias:
+ if hasattr(server, "alias") and server.alias:
return server.alias
- if hasattr(server, 'server_name') and server.server_name:
+ if hasattr(server, "server_name") and server.server_name:
return server.server_name
- if hasattr(server, 'server_id'):
+ if hasattr(server, "server_id"):
return server.server_id
return ""
-def get_server_name_prefix_tool_mcp(prefixed_tool_name: str) -> Tuple[str, str]:
- """
- Remove server name prefix from tool name
- Args:
- prefixed_tool_name: Tool name with server prefix
-
- Returns:
- Tuple of (original_tool_name, server_name)
- """
- if MCP_TOOL_PREFIX_SEPARATOR in prefixed_tool_name:
- parts = prefixed_tool_name.split(MCP_TOOL_PREFIX_SEPARATOR, 1)
+def split_server_prefix_from_name(prefixed_name: str) -> Tuple[str, str]:
+ """Return the unprefixed name plus the server name used as prefix."""
+ if MCP_TOOL_PREFIX_SEPARATOR in prefixed_name:
+ parts = prefixed_name.split(MCP_TOOL_PREFIX_SEPARATOR, 1)
if len(parts) == 2:
- return parts[1], parts[0] # tool_name, server_name
- return prefixed_tool_name, "" # No prefix found, return original name
+ return parts[1], parts[0]
+ return prefixed_name, ""
+
def is_tool_name_prefixed(tool_name: str) -> bool:
"""
@@ -122,14 +112,17 @@ def is_tool_name_prefixed(tool_name: str) -> bool:
"""
return MCP_TOOL_PREFIX_SEPARATOR in tool_name
-def validate_mcp_server_name(server_name: str, raise_http_exception: bool = False) -> None:
+
+def validate_mcp_server_name(
+ server_name: str, raise_http_exception: bool = False
+) -> None:
"""
Validate that MCP server name does not contain 'MCP_TOOL_PREFIX_SEPARATOR'.
-
+
Args:
server_name: The server name to validate
raise_http_exception: If True, raises HTTPException instead of generic Exception
-
+
Raises:
Exception or HTTPException: If server name contains 'MCP_TOOL_PREFIX_SEPARATOR'
"""
@@ -138,9 +131,9 @@ def validate_mcp_server_name(server_name: str, raise_http_exception: bool = Fals
if raise_http_exception:
from fastapi import HTTPException
from starlette import status
+
raise HTTPException(
- status_code=status.HTTP_400_BAD_REQUEST,
- detail={"error": error_message}
+ status_code=status.HTTP_400_BAD_REQUEST, detail={"error": error_message}
)
else:
raise Exception(error_message)
diff --git a/litellm/proxy/_experimental/out/_next/static/nynjENYG9eyWwqRWz7fGE/_buildManifest.js b/litellm/proxy/_experimental/out/_next/static/RP6qFLO9Sa0mS2DSQFL5i/_buildManifest.js
similarity index 100%
rename from litellm/proxy/_experimental/out/_next/static/nynjENYG9eyWwqRWz7fGE/_buildManifest.js
rename to litellm/proxy/_experimental/out/_next/static/RP6qFLO9Sa0mS2DSQFL5i/_buildManifest.js
diff --git a/litellm/proxy/_experimental/out/_next/static/nynjENYG9eyWwqRWz7fGE/_ssgManifest.js b/litellm/proxy/_experimental/out/_next/static/RP6qFLO9Sa0mS2DSQFL5i/_ssgManifest.js
similarity index 100%
rename from litellm/proxy/_experimental/out/_next/static/nynjENYG9eyWwqRWz7fGE/_ssgManifest.js
rename to litellm/proxy/_experimental/out/_next/static/RP6qFLO9Sa0mS2DSQFL5i/_ssgManifest.js
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1116-2d5ec30ef7d86f0e.js b/litellm/proxy/_experimental/out/_next/static/chunks/1116-2d5ec30ef7d86f0e.js
deleted file mode 100644
index 7c33ceca243..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1116-2d5ec30ef7d86f0e.js
+++ /dev/null
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similarity index 99%
rename from litellm/proxy/_experimental/out/_next/static/chunks/1739-30569ada7b1a5a9c.js
rename to litellm/proxy/_experimental/out/_next/static/chunks/1739-b555a2473b0946bb.js
index cb322679d89..53682fe3e67 100644
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new file mode 100644
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new file mode 100644
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deleted file mode 100644
index f673220808f..00000000000
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