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Rename litellm-proxy CLI command to lite

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The proxy management CLI was invoked as litellm-proxy, which is a lot to
type for an everyday command. Rename the console script entry point to
lite and update the in-CLI usage examples, help text, error messages and
docs to match.
This commit is contained in:
Claude 2026-06-07 01:13:47 +00:00
parent 4ef889077d
commit 7a680c0201
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9 changed files with 78 additions and 78 deletions
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2
litellm/litellm_core_utils/cli_token_utils.py
View file

@ -37,7 +37,7 @@ def get_litellm_gateway_api_key(
"""
Get the stored CLI API key for use with LiteLLM SDK.
This function reads the token file created by `litellm-proxy login`
This function reads the token file created by `lite login`
and returns the API key for use in Python scripts.
Args:

14
litellm/proxy/client/README.md
View file

@ -338,9 +338,9 @@ sequenceDiagram
The CLI provides three authentication commands:
- **`litellm-proxy login`** - Start SSO authentication flow
- **`litellm-proxy logout`** - Clear stored authentication token
- **`litellm-proxy whoami`** - Show current authentication status
- **`lite login`** - Start SSO authentication flow
- **`lite logout`** - Clear stored authentication token
- **`lite whoami`** - Show current authentication status
### Authentication Flow Steps
@ -382,14 +382,14 @@ Once authenticated, the CLI will automatically use the stored token for all requ
```bash
# Login
litellm-proxy login
lite login
# Use CLI without specifying API key
litellm-proxy models list
lite models list
# Check authentication status
litellm-proxy whoami
lite whoami
# Logout
litellm-proxy logout
lite logout
```

120
litellm/proxy/client/cli/README.md
View file

@ -22,11 +22,11 @@ The CLI can be configured using environment variables or command-line options:
Example:
```bash
litellm-proxy version
lite version
# or
litellm-proxy --version
lite --version
# or
litellm-proxy -v
lite -v
```
## Commands
@ -40,7 +40,7 @@ The CLI provides several commands for managing models on your LiteLLM proxy serv
View all available models:
```bash
litellm-proxy models list [--format table|json]
lite models list [--format table|json]
```
Options:
@ -52,7 +52,7 @@ Options:
Get detailed information about all models:
```bash
litellm-proxy models info [options]
lite models info [options]
```
Options:
@ -75,7 +75,7 @@ Default columns: `public_model`, `upstream_model`, `updated_at`
Add a new model to the proxy:
```bash
litellm-proxy models add <model-name> [options]
lite models add <model-name> [options]
```
Options:
@ -86,7 +86,7 @@ Options:
Example:
```bash
litellm-proxy models add gpt-4 -p api_key=sk-123 -p api_base=https://api.openai.com -i description="GPT-4 model"
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
@ -94,7 +94,7 @@ litellm-proxy models add gpt-4 -p api_key=sk-123 -p api_base=https://api.openai.
Get information about a specific model:
```bash
litellm-proxy models get [--id MODEL_ID] [--name MODEL_NAME]
lite models get [--id MODEL_ID] [--name MODEL_NAME]
```
Options:
@ -107,7 +107,7 @@ Options:
Delete a model from the proxy:
```bash
litellm-proxy models delete <model-id>
lite models delete <model-id>
```
#### Update Model
@ -115,7 +115,7 @@ litellm-proxy models delete <model-id>
Update an existing model's configuration:
```bash
litellm-proxy models update <model-id> [options]
lite models update <model-id> [options]
```
Options:
@ -128,7 +128,7 @@ Options:
Import models from a YAML file:
```bash
litellm-proxy models import models.yaml
lite models import models.yaml
```
Options:
@ -142,31 +142,31 @@ Examples:
1. Import all models from a YAML file:
```bash
litellm-proxy models import models.yaml
lite models import models.yaml
```
2. Dry run (show what would be imported):
```bash
litellm-proxy models import models.yaml --dry-run
lite models import models.yaml --dry-run
```
3. Only import models where the model name contains 'gpt':
```bash
litellm-proxy models import models.yaml --only-models-matching-regex gpt
lite models import models.yaml --only-models-matching-regex gpt
```
4. Only import models with access group containing 'beta':
```bash
litellm-proxy models import models.yaml --only-access-groups-matching-regex beta
lite models import models.yaml --only-access-groups-matching-regex beta
```
5. Combine both filters:
```bash
litellm-proxy models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta
lite models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta
```
### Credentials Management
@ -178,7 +178,7 @@ The CLI provides commands for managing credentials on your LiteLLM proxy server:
View all available credentials:
```bash
litellm-proxy credentials list [--format table|json]
lite credentials list [--format table|json]
```
Options:
@ -194,7 +194,7 @@ The table format displays:
Create a new credential:
```bash
litellm-proxy credentials create <credential-name> --info <json-string> --values <json-string>
lite credentials create <credential-name> --info <json-string> --values <json-string>
```
Options:
@ -205,7 +205,7 @@ Options:
Example:
```bash
litellm-proxy credentials create azure-cred \
lite credentials create azure-cred \
--info '{"custom_llm_provider": "azure"}' \
--values '{"api_key": "sk-123", "api_base": "https://example.azure.openai.com"}'
```
@ -215,7 +215,7 @@ litellm-proxy credentials create azure-cred \
Get information about a specific credential:
```bash
litellm-proxy credentials get <credential-name>
lite credentials get <credential-name>
```
#### Delete Credential
@ -223,7 +223,7 @@ litellm-proxy credentials get <credential-name>
Delete a credential:
```bash
litellm-proxy credentials delete <credential-name>
lite credentials delete <credential-name>
```
### Keys Management
@ -235,7 +235,7 @@ The CLI provides commands for managing API keys on your LiteLLM proxy server:
View all API keys:
```bash
litellm-proxy keys list [--format table|json] [options]
lite keys list [--format table|json] [options]
```
Options:
@ -256,7 +256,7 @@ Options:
Generate a new API key:
```bash
litellm-proxy keys generate [options]
lite keys generate [options]
```
Options:
@ -274,7 +274,7 @@ Options:
Example:
```bash
litellm-proxy keys generate --models gpt-4,gpt-3.5-turbo --spend 100 --duration 24h --key-alias my-key --team-id team123
lite keys generate --models gpt-4,gpt-3.5-turbo --spend 100 --duration 24h --key-alias my-key --team-id team123
```
#### Delete Keys
@ -282,7 +282,7 @@ litellm-proxy keys generate --models gpt-4,gpt-3.5-turbo --spend 100 --duration
Delete API keys by key or alias:
```bash
litellm-proxy keys delete [--keys <comma-separated-keys>] [--key-aliases <comma-separated-aliases>]
lite keys delete [--keys <comma-separated-keys>] [--key-aliases <comma-separated-aliases>]
```
Options:
@ -293,7 +293,7 @@ Options:
Example:
```bash
litellm-proxy keys delete --keys sk-key1,sk-key2 --key-aliases alias1,alias2
lite keys delete --keys sk-key1,sk-key2 --key-aliases alias1,alias2
```
#### Get Key Info
@ -301,7 +301,7 @@ litellm-proxy keys delete --keys sk-key1,sk-key2 --key-aliases alias1,alias2
Get information about a specific API key:
```bash
litellm-proxy keys info --key <key-hash>
lite keys info --key <key-hash>
```
Options:
@ -311,7 +311,7 @@ Options:
Example:
```bash
litellm-proxy keys info --key sk-key1
lite keys info --key sk-key1
```
### User Management
@ -323,7 +323,7 @@ The CLI provides commands for managing users on your LiteLLM proxy server:
View all users:
```bash
litellm-proxy users list
lite users list
```
#### Get User Info
@ -331,7 +331,7 @@ litellm-proxy users list
Get information about a specific user:
```bash
litellm-proxy users get --id <user-id>
lite users get --id <user-id>
```
#### Create User
@ -339,7 +339,7 @@ litellm-proxy users get --id <user-id>
Create a new user:
```bash
litellm-proxy users create --email user@example.com --role internal_user --alias "Alice" --team team1 --max-budget 100.0
lite users create --email user@example.com --role internal_user --alias "Alice" --team team1 --max-budget 100.0
```
#### Delete User
@ -347,7 +347,7 @@ litellm-proxy users create --email user@example.com --role internal_user --alias
Delete one or more users by user_id:
```bash
litellm-proxy users delete <user-id-1> <user-id-2>
lite users delete <user-id-1> <user-id-2>
```
### Chat Commands
@ -359,7 +359,7 @@ The CLI provides commands for interacting with chat models through your LiteLLM
Create a chat completion:
```bash
litellm-proxy chat completions <model> [options]
lite chat completions <model> [options]
```
Arguments:
@ -379,12 +379,12 @@ Examples:
1. Simple completion:
```bash
litellm-proxy chat completions gpt-4 -m "user:Hello, how are you?"
lite chat completions gpt-4 -m "user:Hello, how are you?"
```
2. Multi-message conversation:
```bash
litellm-proxy chat completions gpt-4 \
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." \
@ -393,7 +393,7 @@ litellm-proxy chat completions gpt-4 \
3. With generation parameters:
```bash
litellm-proxy chat completions gpt-4 \
lite chat completions gpt-4 \
-m "user:Write a story" \
--temperature 0.7 \
--max-tokens 500 \
@ -409,7 +409,7 @@ The CLI provides commands for making direct HTTP requests to your LiteLLM proxy
Make an HTTP request to any endpoint:
```bash
litellm-proxy http request <method> <uri> [options]
lite http request <method> <uri> [options]
```
Arguments:
@ -425,17 +425,17 @@ Examples:
1. List models:
```bash
litellm-proxy http request GET /models
lite http request GET /models
```
2. Create a chat completion:
```bash
litellm-proxy http request POST /chat/completions -j '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}'
lite http request POST /chat/completions -j '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}'
```
3. Test connection with custom headers:
```bash
litellm-proxy http request GET /health/test_connection -H "X-Custom-Header:value"
lite http request GET /health/test_connection -H "X-Custom-Header:value"
```
### Run a Coding Agent
@ -443,16 +443,16 @@ litellm-proxy http request GET /health/test_connection -H "X-Custom-Header:value
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
litellm-proxy claude
litellm-proxy codex
litellm-proxy opencode
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
litellm-proxy claude --resume
litellm-proxy codex exec "summarize the repo"
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.
@ -463,7 +463,7 @@ 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 `litellm-proxy claude --model my-proxy-model` or `litellm-proxy 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.
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.
## Environment Variables
@ -477,37 +477,37 @@ The CLI respects the following environment variables:
1. List all models in table format:
```bash
litellm-proxy models list
lite models list
```
2. Add a new model with parameters:
```bash
litellm-proxy models add gpt-4 -p api_key=sk-123 -p max_tokens=2048
lite models add gpt-4 -p api_key=sk-123 -p max_tokens=2048
```
3. Get model information in JSON format:
```bash
litellm-proxy models info --format json
lite models info --format json
```
4. Update model parameters:
```bash
litellm-proxy models update model-123 -p temperature=0.7 -i description="Updated model"
lite models update model-123 -p temperature=0.7 -i description="Updated model"
```
5. List all credentials in table format:
```bash
litellm-proxy credentials list
lite credentials list
```
6. Create a new credential for Azure:
```bash
litellm-proxy credentials create azure-prod \
lite credentials create azure-prod \
--info '{"custom_llm_provider": "azure"}' \
--values '{"api_key": "sk-123", "api_base": "https://prod.azure.openai.com"}'
```
@ -515,7 +515,7 @@ litellm-proxy credentials create azure-prod \
7. Make a custom HTTP request:
```bash
litellm-proxy http request POST /chat/completions \
lite http request POST /chat/completions \
-j '{"model": "gpt-4", "messages": [{"role": "user", "content": "Hello"}]}' \
-H "X-Custom-Header:value"
```
@ -524,29 +524,29 @@ litellm-proxy http request POST /chat/completions \
```bash
# List users
litellm-proxy users list
lite users list
# Get user info
litellm-proxy users get --id u1
lite users get --id u1
# Create a user
litellm-proxy users create --email a@b.com --role internal_user --alias "Alice" --team team1 --max-budget 100.0
lite users create --email a@b.com --role internal_user --alias "Alice" --team team1 --max-budget 100.0
# Delete users
litellm-proxy users delete u1 u2
lite users delete u1 u2
```
9. Import models from a YAML file (with filters):
```bash
# Only import models where the model name contains 'gpt'
litellm-proxy models import models.yaml --only-models-matching-regex gpt
lite models import models.yaml --only-models-matching-regex gpt
# Only import models with access group containing 'beta'
litellm-proxy models import models.yaml --only-access-groups-matching-regex beta
lite models import models.yaml --only-access-groups-matching-regex beta
# Combine both filters
litellm-proxy models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta
lite models import models.yaml --only-models-matching-regex gpt --only-access-groups-matching-regex beta
```
## Error Handling

6
litellm/proxy/client/cli/commands/agents.py
View file

@ -137,7 +137,7 @@ def verify_proxy_key(
if resp.status_code in (401, 403):
raise AgentRunError(
f"LiteLLM rejected your key (HTTP {resp.status_code}). "
"Run `litellm-proxy login` to refresh it, or pass a valid --api-key."
"Run `lite login` to refresh it, or pass a valid --api-key."
)
@ -197,7 +197,7 @@ def _resolve_api_key(ctx: click.Context) -> str:
if not _is_interactive():
raise click.ClickException(
"No LiteLLM key found. Set LITELLM_PROXY_API_KEY (or pass --api-key) for "
"non-interactive use, or run `litellm-proxy login` from a terminal."
"non-interactive use, or run `lite login` from a terminal."
)
click.echo("No LiteLLM credentials found; starting login...")
@ -252,7 +252,7 @@ def _make_agent_command(binary: str, display_name: str) -> click.Command:
def agent_commands() -> List[click.Command]:
"""Build one top-level command per known agent, e.g. `litellm-proxy claude`."""
"""Build one top-level command per known agent, e.g. `lite claude`."""
return [
_make_agent_command(binary, name)
for binary, (name, _profiles) in _KNOWN_AGENTS.items()

2
litellm/proxy/client/cli/commands/auth.py
View file

@ -624,7 +624,7 @@ def whoami():
token_data = load_token()
if not token_data:
click.echo("❌ Not authenticated. Run 'litellm-proxy login' to authenticate.")
click.echo("❌ Not authenticated. Run 'lite login' to authenticate.")
return
click.echo("✅ Authenticated")

6
litellm/proxy/client/cli/commands/chat.py
View file

@ -122,13 +122,13 @@ def chat(
Examples:
# Chat with a specific model
litellm-proxy chat gpt-4
lite chat gpt-4
# Chat without specifying model (will show model selection)
litellm-proxy chat
lite chat
# Chat with custom settings
litellm-proxy chat gpt-4 --temperature 0.9 --system "You are a helpful coding assistant"
lite chat gpt-4 --temperature 0.9 --system "You are a helpful coding assistant"
"""
console = Console()

2
litellm/proxy/client/cli/interface.py
View file

@ -161,7 +161,7 @@ def execute_command(user_input: str, ctx: click.Context):
# Execute the command
try:
# Create a new argument list for click to parse
sys.argv = ["litellm-proxy"] + [command] + args
sys.argv = ["lite"] + [command] + args
# Get the command object and invoke it
cmd = cli.commands[command]

2
pyproject.toml
View file

@ -132,7 +132,7 @@ proxy-runtime = [
[project.scripts]
litellm = "litellm:run_server"
litellm-proxy = "litellm.proxy.client.cli:cli"
lite = "litellm.proxy.client.cli:cli"
[dependency-groups]
dev = [

2
tests/test_litellm/proxy/client/cli/test_auth_commands.py
View file

@ -517,7 +517,7 @@ class TestWhoamiCommand:
assert result.exit_code == 0
assert "❌ Not authenticated" in result.output
assert "Run 'litellm-proxy login'" in result.output
assert "Run 'lite login'" in result.output
def test_whoami_old_token(self):
"""Test whoami with old token showing warning"""