llm-taxi
Installation
pip install llm-taxi
Usage
Use as a library
import asyncio
from llm_taxi.conversation import Message, Role
from llm_taxi.factory import embedding, llm
async def main():
# Non-streaming response
client = llm(model="openai:gpt-3.5-turbo")
messages = [
Message(role=Role.User, content="What is the capital of France?"),
]
response = await client.response(messages)
print(response)
# Streaming response
client = llm(model="mistral:mistral-small")
messages = [
Message(role=Role.User, content="Tell me a joke."),
]
response = await client.streaming_response(messages)
async for chunk in response:
print(chunk, end="", flush=True)
print()
# Embed text
embedder = embedding("openai:text-embedding-ada-002")
embeddings = await embedder.embed_text("Hello, world!")
print(embeddings[:10])
# Embed texts
embedder = embedding("mistral:mistral-embed")
embeddings = await embedder.embed_texts(["Hello, world!"])
print(embeddings[0][:10])
if __name__ == "__main__":
asyncio.run(main())
Common parameters
temperaturemax_tokenstop_ktop_pstopseedpresence_penaltyfrequency_penaltyresponse_formattoolstool_choice
Command line interface
llm-taxi --model openai:gpt-3.5-turbo-16k
See all supported arguments
llm-taxi --help
Supported Providers
| Provider | LLM | Embedding |
|---|---|---|
| Anthropic | ✅ | |
| DashScope | ✅ | |
| DeepInfra | ✅ | |
| DeepSeek | ✅ | |
| ✅ | ✅ | |
| Groq | ✅ | |
| Mistral | ✅ | ✅ |
| OpenAI | ✅ | ✅ |
| OpenRouter | ✅ | |
| Perplexity | ✅ | |
| Together | ✅ | |
| BigModel | ✅ |
Metadata
Release files for llm-taxi 0.7.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_taxi-0.7.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / llm_taxi-0.7.0.tar.gz
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