calling-llms
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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- Repositório
- xberg-io/liter-llm
- Última atividade na origem
- 30 de setembro de 2026 às 16:23
- Idioma detectado do SKILL.md
- inglês
- Estrelas
- 260
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- 23
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Instruções da origem · Visualização somente leitura- name
- calling-llms
- description
- 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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# 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`.
Ver no GitHub