Skip to main content

A Python toolkit for advanced data processing and API interactions

Project description

descartkit

LLM

Three steps to use models

Step1, llm_config.yaml

matter that needs attention

  1. custom_model_name used for models.get_model_instance()
  2. custom_model_name.name should specify the name of the model supported by the current company
models:
  openai:
    custom_model_name:
      name: "gpt-4o"
      short_name: "OIG4"
      company: "openai"
      max_input_token: 8100
      max_output_token: 2048
      top_p: 0.5
      top_k: 1
      temperature: 0.5
      input_token_fee_pm: 30.0
      output_token_fee_pm: 60.0
      train_token_fee_pm: 0.0
      keys:
        - name: "openai_key1"
        - name: "openai_key2"

  siliconflow:
    qw-72b-p:
      name: "Qwen/QVQ-72B-Preview"
      short_name: "QW-72B-P"
      company: "siliconflow"
      max_input_token: 8100
      max_output_token: 2048
      top_p: 0.5
      top_k: 1
      temperature: 0.5
      input_token_fee_pm: 30.0
      output_token_fee_pm: 60.0
      train_token_fee_pm: 0.0
      keys:
        - name: "siliconflow_1"
Step2, llm_keys.yaml
  1. The keys name of the model in llm_config.yaml corresponds to llm_keys.yaml one by one
keys:
  openai_key1: "xx"
  openai_key2: "xx"
  anthropic_key1: "your_anthropic_api_key_1"
  anthropic_key2: "your_anthropic_api_key_2"
Step3, load models
from descartcan.llm.config import load_models_from_yaml
from descartcan.llm import LLMClient


async def main():
    # The first method
    models = load_models_from_yaml(config_file="examples/llm_config.yaml", keys_file="examples/llm_keys.yaml")
    print(models.list_models())

    resp = await models.get_model_instance("gpt-4o").chat("who r u?")
    print(resp)

    # The second method
    client = LLMClient(config_file="llm_config.yaml", keys_file="llm_keys.yaml")
    print(client.list_models())
    resp = await client.chat("qw-72b-p", "who r u?", system_prompt="")
    print(resp)
    async for chunk in client.chat_stream("qw-72b-p", "who r u?", system_prompt=""):
        print(chunk)


if __name__ == '__main__':
    import asyncio

    asyncio.run(main())

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

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

descartcan-2025.4.2.1-py3-none-any.whl (50.4 kB view details)

Uploaded Python 3

File details

Details for the file descartcan-2025.4.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for descartcan-2025.4.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1bbd77ea7c70c2437c6c59eb390c5d68e599fe85f00f9d427b90bbd384a683e5
MD5 3ff3884491d6a5d27e90ecfc8b3bccb3
BLAKE2b-256 0cbf0adcfee5a3f730010299704175ae317da858c8298d9fab54027603028310

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