calling-llms

<!-- AI-RULEZ :: GENERATED FILE — DO NOT EDIT Content-Hash: blake3:116e9240923b4f529f06471698b0e15ce1a14688a5beb1cae28e0b62e3a2837f Source-Hash: blake3:651c31e789b5b3a98bbebecbda0ea4f0b6222b63c8264db7c677af355c5fe27b Schema-Version: v1 --> # Calling LLMs Build a `ChatCompletionRequest` and send it with `client.chat(request)`. Create the client with `create_client(...)`. The model string is `provider/model`; the prefix selects the backend. ```python import asyncio, json, os from liter_llm import create_client from liter_llm._internal_bindings import ChatCompletionRequest async def main() -> None: client = create_client(api_key=os.environ["OPENAI_API_KEY"]) request = ChatCompletionRequest.from_json(json.dumps({ "model": "openai/gpt-4o", "messages": [ {"role": "system", "content": "You are concise."}, {"role": "user", "content": "Name three Rust crates for HTTP."}, ], })) response = await client.chat(request) print(response.choices[0].message.content) asyncio.run(main()) ``` ## Provider routing The model string's prefix selects the provider; build a request per backend: ```python ChatCompletionRequest.from_json('{"model":"anthropic/claude-sonnet-4-20250514","messages":[...]}') ChatCompletionRequest.from_json('{"model":"google/gemini-2.0-flash","messages":[...]}') ChatCompletionRequest.from_json('{"model":"groq/llama3-70b","messages":[...]}') ChatCompletionRequest.from_json('{"model":"mistral/mistral-large-latest","messages":[...]}') ChatCompletionRequest.from_json('{"model":"bedrock/anthropic.claude-v2","messages":[...]}') ``` Set `model_hint` at construction to drop the prefix on every call: ```python client = create_client(api_key="sk-...", model_hint="openai") # the request model can now omit the provider prefix: request = ChatCompletionRequest.from_json('{"model":"gpt-4o","messages":[...]}') await client.chat(request) # routes to OpenAI ``` ## Notes - Keys come from env vars (`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, …); never hardcode them. - Without a prefix and without `model_hint`, routing fails. - Python errors are typed exceptions exported from `liter_llm`: `AuthenticationError`, `RateLimitedError`, `BadRequestError`, `ContextWindowExceededError`, `ContentPolicyError`, `NotFoundError`, `ServerError`, `ServiceUnavailableError`, `LiterLlmTimeoutError`, `BudgetExceededError` — all subclasses of `LiterLlmError`.