--- title: "All settings" description: "```yaml environment_variables: {}" type: skill canonical_url: https://claudary.paisolsolutions.com/skills/config-settings source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:18:47.878Z license: CC-BY-4.0 attribution: "All settings — Claudary (https://claudary.paisolsolutions.com/skills/config-settings)" --- # All settings ```yaml environment_variables: {} ## Overview # All settings ```yaml environment_variables: {} model_list: - model_name: string litellm_params: {} model_info: id: string mode: embedding input_cost_per_token: 0 output_cost_per_token: 0 max_tokens: 2048 base_model: gpt-4-1106-preview additionalProp1: {} litellm_settings: # Logging/Callback settings success_callback: ["langfuse"] # list of success callbacks failure_callback: ["sentry"] # list of failure callbacks callbacks: ["otel"] # list of callbacks - runs on success and failure service_callbacks: ["datadog", "prometheus"] # logs redis, postgres failures on datadog, prometheus turn_off_message_logging: boolean # prevent the messages and responses from being logged to on your callbacks, but request metadata will still be logged. Useful for privacy/compliance when handling sensitive data. redact_user_api_key_info: boolean # Redact information about the user api key (hashed token, user_id, team id, etc.), from logs. Currently supported for Langfuse, OpenTelemetry, Logfire, ArizeAI logging. langfuse_default_tags: ["cache_hit", "cache_key", "proxy_base_url", "user_api_key_alias", "user_api_key_user_id", "user_api_key_user_email", "user_api_key_team_alias", "semantic-similarity", "proxy_base_url"] # default tags for Langfuse Logging # Networking settings request_timeout: 10 # (int) llm requesttimeout in seconds. Raise Timeout error if call takes longer than 10s. Sets litellm.request_timeout force_ipv4: boolean # If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API # Debugging - see debugging docs for more options # Use `--debug` or `--detailed_debug` CLI flags, or set LITELLM_LOG env var to "INFO", "DEBUG", or "ERROR" json_logs: boolean # if true, logs will be in json format # Fallbacks, reliability default_fallbacks: ["claude-opus"] # set default_fallbacks, in case a specific model group is misconfigured / bad. content_policy_fallbacks: [{ "gpt-3.5-turbo-small": ["claude-opus"] }] # fallbacks for ContentPolicyErrors context_window_fallbacks: [{ "gpt-3.5-turbo-small": ["gpt-3.5-turbo-large", "claude-opus"] }] # fallbacks for ContextWindowExceededErrors # MCP Aliases - Map aliases to MCP server names for easier tool access mcp_aliases: { "github": "github_mcp_server", "zapier": "zapier_mcp_server", "deepwiki": "deepwiki_mcp_server", } # Maps friendly aliases to MCP server names. Only the first alias for each server is used # Caching settings cache: true cache_params: # set cache params for redis type: redis # type of cache to initialize (options: "local", "redis", "s3", "gcs") # Optional - Redis Settings host: "localhost" # The host address for the Redis cache. Required if type is "redis". port: 6379 # The port number for the Redis cache. Required if type is "redis". password: "your_password" # The password for the Redis cache. Required if type is "redis". namespace: "litellm.caching.caching" # namespace for redis cache max_connections: 100 # [OPTIONAL] Set Maximum number of Redis connections. Passed directly to redis-py. # Optional - Redis Cluster Settings redis_startup_nodes: [{ "host": "127.0.0.1", "port": "7001" }] # Optional - Redis Sentinel Settings service_name: "mymaster" sentinel_nodes: [["localhost", 26379]] # Optional - GCP IAM Authentication for Redis gcp_service_account: "projects/-/serviceAccounts/your-sa@project.iam.gserviceaccount.com" # GCP service account for IAM authentication gcp_ssl_ca_certs: "./server-ca.pem" # Path to SSL CA certificate file for GCP Memorystore Redis ssl: true # Enable SSL for secure connections ssl_cert_reqs: null # Set to null for self-signed certificates ssl_check_hostname: false # Set to false for self-signed certificates # Optional - Qdrant Semantic Cache Settings qdrant_semantic_cache_embedding_model: openai-embedding # the model should be defined on the model_list qdrant_collection_name: test_collection qdrant_quantization_config: binary qdrant_semantic_cache_vector_size: 1536 # vector size must match embedding model dimensionality similarity_threshold: 0.8 # similarity threshold for semantic cache # Optional - S3 Cache Settings s3_bucket_name: cache-bucket-litellm # AWS Bucket Name for S3 s3_region_name: us-west-2 # AWS Region Name for S3 s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID # us os.environ/ to pass environment variables. This is AWS Access Key ID for S3 s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY # AWS Secret Access Key for S3 s3_endpoint_url: https://s3.amazonaws.com # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 bucket # Optional - GCS Cache Settings gcs_bucket_name: cache-bucket-litellm # GCS Bucket Name for caching gcs_path_service_account: os.environ/GCS_PATH_SERVICE_ACCOUNT # Path to GCS service account JSON file gcs_path: cache/ # [OPTIONAL] GCS path prefix for cache objects # Common Cache settings # Optional - Supported call types for caching supported_call_types: ["acompletion", "atext_completion", "aembedding", "atranscription"] # /chat/completions, /completions, /embeddings, /audio/transcriptions mode: default_off # if default_off, you need to opt in to caching on a per call basis ttl: 600 # ttl for caching disable_copilot_system_to_assistant: False # DEPRECATED - GitHub Copilot API supports system prompts. callback_settings: otel: message_logging: boolean # OTEL logging callback specific settings general_settings: completion_model: string store_prompts_in_spend_logs: boolean forward_client_headers_to_llm_api: boolean disable_spend_logs: boolean # turn off writing each transaction to the db disable_master_key_return: boolean # turn off returning master key on UI (checked on '/user/info' endpoint) disable_retry_on_max_parallel_request_limit_error: boolean # turn off retries when max parallel request limit is reached disable_reset_budget: boolean # turn off reset budget scheduled task disable_adding_master_key_hash_to_db: boolean # turn off storing master key hash in db, for spend tracking disable_responses_id_security: boolean # turn off response ID security checks that prevent users from accessing other users' responses enable_jwt_auth: boolean # allow proxy admin to auth in via jwt tokens with 'litellm_proxy_admin' in claims enforce_user_param: boolean # requires all openai endpoint requests to have a 'user' param reject_clientside_metadata_tags: boolean # if true, rejects requests with client-side 'metadata.tags' to prevent users from influencing budgets allowed_routes: ["route1", "route2"] # list of allowed proxy API routes - a user can access. (currently JWT-Auth only) key_management_system: google_kms # either google_kms or azure_kms master_key: string maximum_spend_logs_retention_period: 30d # The maximum time to retain spend logs before deletion. maximum_spend_logs_retention_interval: 1d # interval in which the spend log cleanup task should run in. user_mcp_management_mode: restricted # or "view_all" # Database Settings database_url: string database_connection_pool_limit: 0 # default 10 database_connection_timeout: 0 # default 60s allow_requests_on_db_unavailable: boolean # if true, will allow requests that can not connect to the DB to verify Virtual Key to still work custom_auth: string max_parallel_requests: 0 # the max parallel requests allowed per deployment global_max_parallel_requests: 0 # the max parallel requests allowed on the proxy all up infer_model_from_keys: true background_health_checks: true health_check_interval: 300 alerting: ["slack", "email"] alerting_threshold: 0 use_client_credentials_pass_through_routes: boolean # use client credentials for all pass through routes like "/vertex-ai", /bedrock/. When this is True Virtual Key auth will not be applied on these endpoints router_settings: routing_strategy: simple-shuffle # Literal["simple-shuffle", "least-busy", "usage-based-routing","latency-based-routing"], default="simple-shuffle" - RECOMMENDED for best performance redis_host: # string redis_password: # string redis_port: # string enable_pre_call_checks: true # bool - Before call is made check if a call is within model context window allowed_fails: 3 # cooldown model if it fails > 1 call in a minute. cooldown_time: 30 # (in seconds) how long to cooldown model if fails/min > allowed_fails disable_cooldowns: True # bool - Disable cooldowns for all models enable_tag_filtering: True # bool - Use tag based routing for requests tag_filtering_match_any: True # bool - Tag matching behavior (only when enable_tag_filtering=true). `true`: match if deployment has ANY requested tag; `false`: match only if deployment has ALL requested tags retry_policy: { # Dict[str, int]: retry policy for different types of exceptions "AuthenticationErrorRetries": 3, "TimeoutErrorRetries": 3, "RateLimitErrorRetries": 3, "ContentPolicyViolationErrorRetries": 4, "InternalServerErrorRetries": 4 } allowed_fails_policy: { "BadRequestErrorAllowedFails": 1000, # Allow 1000 BadRequestErrors before cooling down a deployment "AuthenticationErrorAllowedFails": 10, # int "TimeoutErrorAllowedFails": 12, # int "RateLimitErrorAllowedFails": 10000, # int "ContentPolicyViolationErrorAllowedFails": 15, # int "InternalServerErrorAllowedFails": 20, # int } content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for content policy violations fallbacks=[{"claude-2": ["my-fallback-model"]}] # List[Dict[str, List[str]]]: Fallback model for all errors ``` ### litellm_settings - Reference | Name | Type | Description | |------|------|-------------| | success_callback | array of strings | List of success callbacks. [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | | failure_callback | array of strings | List of failure callbacks [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | | callbacks | array of strings | List of callbacks - runs on success and failure [Doc Proxy logging callbacks](logging), [Doc Metrics](prometheus) | | service_callbacks | array of strings | System health monitoring - Logs redis, postgres failures on specified services (e.g. datadog, prometheus) [Doc Metrics](prometheus) | | turn_off_message_logging | boolean | If true, prevents messages and responses from being logged to callbacks, but request metadata will still be logged. Useful for privacy/compliance when handling sensitive data [Proxy Logging](logging) | | modify_params | boolean | If true, allows modifying the parameters of the request before it is sent to the LLM provider | | enable_preview_features | boolean | If true, enables preview features - e.g. Azure O1 Models with streaming support.| | LITELLM_DISABLE_STOP_SEQUENCE_LIMIT | Disable validation for stop sequence limit (default: 4) | | redact_user_api_key_info | boolean | If true, redacts information about the user api key from logs [Proxy Logging](logging#redacting-userapikeyinfo) | | mcp_aliases | object | Maps friendly aliases to MCP server names for easier tool access. Only the first alias for each server is used. [MCP Aliases](../mcp#mcp-aliases) | | langfuse_default_tags | array of strings | Default tags for Langfuse Logging. Use this if you want to control which LiteLLM-specific fields are logged as tags by the LiteLLM proxy. By default LiteLLM Proxy logs no LiteLLM-specific fields as tags. [Further docs](./logging#litellm-specific-tags-on-langfuse---cache_hit-cache_key) | | set_verbose | boolean | [DEPRECATED - see debugging docs](./debugging) Use `--debug` or `--detailed_debug` CLI flags, or set `LITELLM_LOG` env var to "INFO", "DEBUG", or "ERROR" instead. | | json_logs | boolean | If true, logs will be in json format. If you need to store the logs as JSON, just set the `litellm.json_logs = True`. We currently just log the raw POST request from litellm as a JSON [Further docs](./debugging) | | default_fallbacks | array of strings | List of fallback models to use if a specific model group is misconfigured / bad. [Further docs](./reliability#default-fallbacks) | | request_timeout | integer | The timeout for requests in seconds. If not set, the default value is `6000 seconds`. [For reference OpenAI Python SDK defaults to `600 seconds`.](https://github.com/openai/openai-python/blob/main/src/openai/_constants.py) | | force_ipv4 | boolean | If true, litellm will force ipv4 for all LLM requests. Some users have seen httpx ConnectionError when using ipv6 + Anthropic API | | content_policy_fallbacks | array of objects | Fallbacks to use when a ContentPolicyViolationError is encountered. [Further docs](./reliability#content-policy-fallbacks) | | context_window_fallbacks | array of objects | Fallbacks to use when a ContextWindowExceededError is encountered. [Further docs](./reliability#context-window-fallbacks) | | cache | boolean | If true, enables caching. [Further docs](./caching) | | cache_params | object | Parameters for the cache. [Further docs](./caching#supported-cache_params-on-proxy-configyaml) | | disable_end_user_cost_tracking | boolean | If true, turns off end user cost tracking on prometheus metrics + litellm spend logs table on proxy. | | disable_end_user_cost_tracking_prometheus_only | boolean | If true, turns off end user cost tracking on prometheus metrics only. | | key_generation_settings | object | Restricts who can generate keys. [Further docs](./virtual_keys.md#restricting-key-generation) | | disable_add_transform_inline_image_block | boolean | For Fireworks AI models - if true, turns off the auto-add of `#transform=inline` to the url of the image_url, if the model is not a vision model. | | use_chat_completions_url_for_anthropic_messages | boolean | If true, routes OpenAI `/v1/messages` requests through chat/completions instead of the Responses API. Can also be set via env var `LITELLM_USE_CHAT_COMPLETIONS_URL_FOR_ANTHROPIC_MESSAGES=true`. | | route_all_chat_openai_to_responses | boolean | If true, routes all OpenAI `/chat/completions` requests through the Responses API bridge. Recommended for OpenAI models. Can also be set via env var `LITELLM_ROUTE_ALL_CHAT_OPENAI_TO_RESPONSES=true`. | | skip_system_message_in_guardrail | boolean | If true, unified guardrails omit `role: system` from scanned input on **chat completions** and **Anthropic `/v1/messages`** only; the LLM still receives full messages. Per-guardrail override: `litellm_params.skip_system_message --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/config-settings) · https://claudary.paisolsolutions.com