LiteLLM Proxy CLI

The LiteLLM Proxy CLI is a command-line tool for managing your LiteLLM proxy server. It provides commands for managing models, viewing server status, and interacting with the proxy server.

Installation

bash

uv tool install 'litellm[proxy]'

Configuration

The CLI can be configured using environment variables or command-line options:

LITELLM_PROXY_URL: Base URL of the LiteLLM proxy server (default: http://localhost:4000)
LITELLM_PROXY_API_KEY: API key for authentication

Global Options

--version, -v: Print the LiteLLM Proxy client and server version and exit.

Example:

bash

lite version
# or
lite --version
# or
lite -v

Commands

Models Management

The CLI provides several commands for managing models on your LiteLLM proxy server:

List Models

View all available models:

bash

lite models list [--format table|json]

Options:

--format: Output format (table or json, default: table)

Model Information

Get detailed information about all models:

bash

lite models info [options]

Options:

--format: Output format (table or json, default: table)
--columns: Comma-separated list of columns to display. Valid columns:
- public_model
- upstream_model
- credential_name
- created_at
- updated_at
- id
- input_cost
- output_cost

Default columns: public_model, upstream_model, updated_at

Add Model

Add a new model to the proxy:

bash

lite models add <model-name> [options]

Options:

--param, -p: Model parameters in key=value format (can be specified multiple times)
--info, -i: Model info in key=value format (can be specified multiple times)

Example:

bash

lite models add gpt-4 -p api_key=sk-123 -p api_base=https://api.openai.com -i description="GPT-4 model"

Get Model Info

Get information about a specific model:

bash

lite models get [--id MODEL_ID] [--name MODEL_NAME]

Options:

--id: ID of the model to retrieve
--name: Name of the model to retrieve

Delete Model

Delete a model from the proxy:

bash

lite models delete <model-id>

Update Model

Update an existing model's configuration:

bash

lite models update <model-id> [options]

Options:

--param, -p: Model parameters in key=value format (can be specified multiple times)
--info, -i: Model info in key=value format (can be specified multiple times)

Import Models

Import models from a YAML file:

bash

lite models import models.yaml

Options:

--dry-run: Show what would be imported without making any changes.
--only-models-matching-regex <regex>: Only import models where litellm_params.model matches the given regex.
--only-access-groups-matching-regex <regex>: Only import models where at least one item in model_info.access_groups matches the given regex.

Examples:

Import all models from a YAML file:

bash

lite models import models.yaml

Dry run (show what would be imported):

bash

lite models import models.yaml --dry-run

Only import models where the model name contains 'gpt':

bash

lite models import models.yaml --only-models-matching-regex gpt

Only import models with access group containing 'beta':

bash

lite models import models.yaml --only-access-groups-matching-regex beta

Combine both filters:

bash

lite models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta

Credentials Management

The CLI provides commands for managing credentials on your LiteLLM proxy server:

List Credentials

View all available credentials:

bash

lite credentials list [--format table|json]

Options:

--format: Output format (table or json, default: table)

The table format displays:

Credential Name
Custom LLM Provider

Create Credential

Create a new credential:

bash

lite credentials create <credential-name> --info <json-string> --values <json-string>

Options:

--info: JSON string containing credential info (e.g., custom_llm_provider)
--values: JSON string containing credential values (e.g., api_key)

Example:

bash

lite credentials create azure-cred \
  --info '{"custom_llm_provider": "azure"}' \
  --values '{"api_key": "sk-123", "api_base": "https://example.azure.openai.com"}'

Get Credential

Get information about a specific credential:

bash

lite credentials get <credential-name>

Delete Credential

Delete a credential:

bash

lite credentials delete <credential-name>

Keys Management

The CLI provides commands for managing API keys on your LiteLLM proxy server:

List Keys

View all API keys:

bash

lite keys list [--format table|json] [options]

Options:

--format: Output format (table or json, default: table)
--page: Page number for pagination
--size: Number of items per page
--user-id: Filter keys by user ID
--team-id: Filter keys by team ID
--organization-id: Filter keys by organization ID
--key-hash: Filter by specific key hash
--key-alias: Filter by key alias
--return-full-object: Return the full key object
--include-team-keys: Include team keys in the response

Generate Key

Generate a new API key:

bash

lite keys generate [options]

Options:

--models: Comma-separated list of allowed models
--aliases: JSON string of model alias mappings
--spend: Maximum spend limit for this key
--duration: Duration for which the key is valid (e.g. '24h', '7d')
--key-alias: Alias/name for the key
--team-id: Team ID to associate the key with
--user-id: User ID to associate the key with
--budget-id: Budget ID to associate the key with
--config: JSON string of additional configuration parameters

Example:

bash

lite keys generate --models gpt-4,gpt-3.5-turbo --spend 100 --duration 24h --key-alias my-key --team-id team123

Delete Keys

Delete API keys by key or alias:

bash

lite keys delete [--keys <comma-separated-keys>] [--key-aliases <comma-separated-aliases>]

Options:

--keys: Comma-separated list of API keys to delete
--key-aliases: Comma-separated list of key aliases to delete

Example:

bash

lite keys delete --keys sk-key1,sk-key2 --key-aliases alias1,alias2

Get Key Info

Get information about a specific API key:

bash

lite keys info --key <key-hash>

Options:

--key: The key hash to get information about

Example:

bash

lite keys info --key sk-key1

User Management

The CLI provides commands for managing users on your LiteLLM proxy server:

List Users

View all users:

bash

lite users list

Get User Info

Get information about a specific user:

bash

lite users get --id <user-id>

Create User

Create a new user:

bash

lite users create --email [email protected] --role internal_user --alias "Alice" --team team1 --max-budget 100.0

Delete User

Delete one or more users by user_id:

bash

lite users delete <user-id-1> <user-id-2>

Chat Commands

The CLI provides commands for interacting with chat models through your LiteLLM proxy server:

Chat Completions

Create a chat completion:

bash

lite chat completions <model> [options]

Arguments:

model: The model to use (e.g., gpt-4, claude-2)

Options:

--message, -m: Messages in 'role:content' format. Can be specified multiple times to create a conversation.
--temperature, -t: Sampling temperature between 0 and 2
--top-p: Nucleus sampling parameter between 0 and 1
--n: Number of completions to generate
--max-tokens: Maximum number of tokens to generate
--presence-penalty: Presence penalty between -2.0 and 2.0
--frequency-penalty: Frequency penalty between -2.0 and 2.0
--user: Unique identifier for the end user

Examples:

Simple completion:

bash

lite chat completions gpt-4 -m "user:Hello, how are you?"

Multi-message conversation:

bash

lite chat completions gpt-4 \
  -m "system:You are a helpful assistant" \
  -m "user:What's the capital of France?" \
  -m "assistant:The capital of France is Paris." \
  -m "user:What's its population?"

With generation parameters:

bash

lite chat completions gpt-4 \
  -m "user:Write a story" \
  --temperature 0.7 \
  --max-tokens 500 \
  --top-p 0.9

HTTP Commands

The CLI provides commands for making direct HTTP requests to your LiteLLM proxy server:

Make HTTP Request

Make an HTTP request to any endpoint:

bash

lite http request <method> <uri> [options]

Arguments:

method: HTTP method (GET, POST, PUT, DELETE, etc.)
uri: URI path (will be appended to base_url)

Options:

--data, -d: Data to send in the request body (as JSON string)
--json, -j: JSON data to send in the request body (as JSON string)
--header, -H: HTTP headers in 'key:value' format. Can be specified multiple times.

Examples:

List models:

bash

lite http request GET /models

Create a chat completion:

bash

lite http request POST /chat/completions -j '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}'

Test connection with custom headers:

bash

lite http request GET /health/test_connection -H "X-Custom-Header:value"

Run a Coding Agent

Launch a coding agent with all of its LLM traffic routed through your LiteLLM proxy. Each supported agent is its own command, so there is nothing to remember beyond the agent's name:

bash

lite claude
lite codex
lite opencode

Anything you type after the agent name is forwarded to it untouched, so the usual flags keep working:

bash

lite claude --resume
lite codex exec "summarize the repo"

Each command resolves your LiteLLM key (logging in via SSO when none is stored and you are at a terminal; otherwise it expects LITELLM_PROXY_API_KEY or --api-key), checks the key against the proxy so bad credentials fail immediately instead of deep inside the agent, exports the environment variables the agent reads, then replaces itself with the agent process.

The right variables are picked per agent. Claude Code gets ANTHROPIC_BASE_URL (the proxy root, so it appends /v1/messages) and ANTHROPIC_AUTH_TOKEN, with any stray ANTHROPIC_API_KEY cleared so the proxy token wins. Codex and OpenCode get OPENAI_BASE_URL (the proxy plus /v1) and OPENAI_API_KEY. Codex ignores OPENAI_BASE_URL, so it is additionally pointed at the proxy through a custom provider passed as -c config overrides (HTTP/SSE Responses transport, since the proxy does not speak the Responses WebSocket protocol).

Options (these belong to the wrapper, so put them before the agent's own flags):

--skip-verify: Skip the pre-launch key check (useful offline or with non-standard auth).

To pin the model, pass the agent's own model flag (for example lite claude --model my-proxy-model or lite codex -m my-proxy-model), or export the variable the agent reads (ANTHROPIC_MODEL / ANTHROPIC_SMALL_FAST_MODEL for Claude Code); the wrapper preserves anything you already have set. Whatever model the agent ends up requesting must exist on the proxy, since requests land on the proxy's /v1/messages (Anthropic) or /v1/chat/completions and /v1/responses (OpenAI) endpoints.

About the `lite login` credential

The token minted by lite login is a short-lived, per-session agent credential, not a managed virtual key. It is scoped to the user and team you authenticated as, inherits that user's and team's models and budgets, and is enforced on the proxy exactly like a virtual key on the same team (guardrails, routing, logging, spend). Spend is tracked against the shared team and user budgets, so running several agents (or logging in more than once) does not hand each session its own separate budget; they all draw down the same team/user allowance. There is no separate per-session cap, so sustained agent use is not capped at a small chat-session limit.

The credential is short-lived by design (default 24h, configurable via LITELLM_CLI_JWT_EXPIRATION_HOURS); run lite login again to refresh it, which also re-reads your latest team and user settings. It does not appear in the Keys UI and cannot be rotated or revoked mid-session. lite claude, lite codex, and lite opencode work with it on a default deployment; EXPERIMENTAL_UI_LOGIN is not required. If you need a long-lived, rotatable key that shows up in the Keys UI, create a dedicated virtual key in the dashboard and pass it via --api-key or LITELLM_PROXY_API_KEY instead.

Environment Variables

The CLI respects the following environment variables:

LITELLM_PROXY_URL: Base URL of the proxy server
LITELLM_PROXY_API_KEY: API key for authentication

Examples

List all models in table format:

bash

lite models list

Add a new model with parameters:

bash

lite models add gpt-4 -p api_key=sk-123 -p max_tokens=2048

Get model information in JSON format:

bash

lite models info --format json

Update model parameters:

bash

lite models update model-123 -p temperature=0.7 -i description="Updated model"

List all credentials in table format:

bash

lite credentials list

Create a new credential for Azure:

bash

lite credentials create azure-prod \
  --info '{"custom_llm_provider": "azure"}' \
  --values '{"api_key": "sk-123", "api_base": "https://prod.azure.openai.com"}'

Make a custom HTTP request:

bash

lite http request POST /chat/completions \
  -j '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}' \
  -H "X-Custom-Header:value"

User management:

bash

# List users
lite users list

# Get user info
lite users get --id u1

# Create a user
lite users create --email [email protected] --role internal_user --alias "Alice" --team team1 --max-budget 100.0

# Delete users
lite users delete u1 u2

Import models from a YAML file (with filters):

bash

# Only import models where the model name contains 'gpt'
lite models import models.yaml --only-models-matching-regex gpt

# Only import models with access group containing 'beta'
lite models import models.yaml --only-access-groups-matching-regex beta

# Combine both filters
lite models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta

Error Handling

The CLI will display appropriate error messages when:

The proxy server is not accessible
Authentication fails
Invalid parameters are provided
The requested model or credential doesn't exist
Invalid JSON is provided for credential creation
Any other operation fails

For detailed debugging, use the --debug flag with any command.

LiteLLM Proxy CLI

LiteLLM Proxy CLI

Installation

Configuration

Global Options

Commands

Models Management

List Models

Model Information

Add Model

Get Model Info

Delete Model

Update Model

Import Models

Credentials Management

List Credentials

Create Credential

Get Credential

Delete Credential

Keys Management

List Keys

Generate Key

Delete Keys

Get Key Info

User Management

List Users

Get User Info

Create User

Delete User

Chat Commands

Chat Completions

HTTP Commands

Make HTTP Request

Run a Coding Agent

About the lite login credential

Environment Variables

Examples

Error Handling

About the `lite login` credential