api
FreeUse liter-llm api reference documentation.
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Use when running the `liter-llm api` OpenAI-compatible gateway — virtual keys, per-key rate limits, budgets, cost tracking, and model routing. Covers the TOML config and the 22 REST endpoints.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
liter-llm api is a drop-in OpenAI-compatible gateway: 22 REST endpoints that
route to 174 providers, with multi-tenant virtual keys, rate limits, budgets,
and cost tracking.
liter-llm api --config liter-llm-proxy.toml
The proxy auto-discovers liter-llm-proxy.toml in the current directory.
[server]
host = "0.0.0.0"
port = 4000
[general]
master_key = "${LITER_LLM_MASTER_KEY}"
# Each [[models]] entry maps a routable name to a provider/model and its key.
[[models]]
name = "gpt-4o"
provider_model = "openai/gpt-4o"
api_key = "${OPENAI_API_KEY}"
[[models]]
name = "claude-sonnet"
provider_model = "anthropic/claude-sonnet-4-20250514"
api_key = "${ANTHROPIC_API_KEY}"
# Virtual keys scope which configured model names a caller may use.
[[keys]]
key = "sk-team-frontend"
models = ["gpt-4o", "claude-sonnet"]
rpm = 60
tpm = 100000
budget_limit = 50.0
${ENV_VAR} interpolation keeps secrets out of the file.
curl http://localhost:4000/v1/chat/completions \
-H "Authorization: Bearer sk-team-frontend" \
-d '{"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]}'
master_key administers them./openapi.json.docker run -p 4000:4000 -e LITER_LLM_MASTER_KEY=sk-key ghcr.io/xberg-io/liter-llm.No reviews yet. Tell others what you thought.
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Use liter-llm api reference documentation.
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Use liter-llm cli reference documentation.
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Universal LLM API client for 174 providers with native bindings for 14 languages. Use when writing code that calls LLM APIs via liter-llm in Python, TypeScript, Rust, Go, Java, C#, Ruby, PHP, Elixir, WASM, or C, when running the OpenAI-compatible proxy, or when calling LLMs through the MCP server. Covers chat, streaming, tool calling, embeddings, image generation, speech, transcription, moderation, web search, OCR, reranking, provider routing, middleware, and configuration.
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Use when sending chat completions through liter-llm and routing to a specific provider via the `provider/model` prefix. Covers the chat call shape, provider routing, model_hint, message roles, and error categories.
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Use when generating embeddings, calling the 12 web-search providers, or running OCR over documents with the 4 OCR providers through liter-llm. Covers embed, search, and ocr methods plus reranking.
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Use when streaming tokens incrementally from an LLM via liter-llm over SSE or async iterators. Covers chat_stream, delta handling, and null-content chunks.
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