Skip to main content

Lightweight, easy, and consistent LLM-interface across providers and functionality.

Project description

sik-llms

  • Easy llm interface; eliminates parsing json responses or building up json for functions/tools
    • OpenAI and any OpenAI-compatible API
    • Anthropic
  • Sync and Async support
  • Functions/Tools
  • Structured Output
    • Supports Anthropic models even though structured output is not natively supported in their models
  • Reasoning mode in OpenAI and Anthropic
  • ReasoningAgent that iteratively reasons and calls tool

See examples

from sik_llms import create_client, user_message, ResponseChunk

model = create_client(
    model_name='gpt-4o-mini',  # or e.g. 'claude-3-7-sonnet-latest'
    temperature=0.1,
)
messages = [
    system_message("You are a helpful assistant."),
    user_message("What is the capital of France?"),
]

# sync
response = model(messages=messages)

# async
response = await model.run_async(messages=messages)

# async streaming
responses = []
summary = None
async for response in model.stream(messages=messages):
    if isinstance(response, TextChunkEvent):
        print(response.content, end="")
        responses.append(response)
    else:
        summary = response

print(summary)

Installation

uv install sik-llms or pip install sik-llms

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sik_llms-0.3.13.tar.gz (116.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sik_llms-0.3.13-py3-none-any.whl (39.3 kB view details)

Uploaded Python 3

File details

Details for the file sik_llms-0.3.13.tar.gz.

File metadata

  • Download URL: sik_llms-0.3.13.tar.gz
  • Upload date:
  • Size: 116.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.24

File hashes

Hashes for sik_llms-0.3.13.tar.gz
Algorithm Hash digest
SHA256 286839183369abf384d923da8e352ffc9a1a84c5afe58d4078c1d1b8eb212eac
MD5 54e4419e8d4270756f8715214035f8bc
BLAKE2b-256 6295e807f5385d390d11b8d16a1e725e58db869f08f188ad9d34d75abde5a02c

See more details on using hashes here.

File details

Details for the file sik_llms-0.3.13-py3-none-any.whl.

File metadata

  • Download URL: sik_llms-0.3.13-py3-none-any.whl
  • Upload date:
  • Size: 39.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.24

File hashes

Hashes for sik_llms-0.3.13-py3-none-any.whl
Algorithm Hash digest
SHA256 37c32c2fdcf2fc717ed85c94844a728e568ce645e5212d0d9e8ecf79e6dfccde
MD5 a0dceb1132c717c887a81663ec589480
BLAKE2b-256 0ed6c004bb271500320a87e3e0a4af7fcea4f41da8111e56ee003600fd9b551a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page