Skip to main content

pydantic_ai_bedrock

Project description

pydantic_ai_bedrock

https://github.com/pydantic/pydantic-ai/issues/118#issuecomment-2589200395

Install

pip install pydantic_ai_bedrock

Usage

from pydantic_ai import Agent
from pydantic_ai_bedrock.bedrock import (
    BedrockModel,
)  # Replace with `pydantic_ai.bedrock import BedrockModel` when pydantic_ai support bedrock

model = BedrockModel(
    model_name="anthropic.claude-3-5-sonnet-20241022-v2:0",
)
agent = Agent(model, system_prompt="You are a helpful assistant.")


if __name__ == "__main__":
    result = agent.run_sync("Hello world!")
    print(result.data)
    print(result.usage())

Develop

Install pre-commit before commit

pip install pre-commit
pre-commit install

Install package locally

pip install -e .[test]

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

pydantic_ai_bedrock-0.1.0.tar.gz (18.7 kB view details)

Uploaded Source

Built Distribution

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

pydantic_ai_bedrock-0.1.0-py3-none-any.whl (6.6 kB view details)

Uploaded Python 3

File details

Details for the file pydantic_ai_bedrock-0.1.0.tar.gz.

File metadata

  • Download URL: pydantic_ai_bedrock-0.1.0.tar.gz
  • Upload date:
  • Size: 18.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for pydantic_ai_bedrock-0.1.0.tar.gz
Algorithm Hash digest
SHA256 7e01b4f4dd36451dad213826e7f7a1aef5655230915307562e6d5d9898980712
MD5 8ec80a8e9fb9dc19823a29df0de42979
BLAKE2b-256 a7ea7327833227c104f09445c774c16a548a5a4fcf9c6383efa2f70ff1d78a8a

See more details on using hashes here.

File details

Details for the file pydantic_ai_bedrock-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for pydantic_ai_bedrock-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 7b16c0e51e9ccfb48ba31ba8a2ec1646891365b2beba202327cf52bd90b5d4f9
MD5 28b582f57068bb4670d46eef967977ef
BLAKE2b-256 b156d85ed036be31804da04513b1b49cb06b30ce3afd53cee5c892c590021211

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