bedrock-inference
Keywords: generative AI, Amazon AWS, Bedrock, API, wrapper, LLM, inference, NLP.
Bedrock Inference is a simple python package to handle 2FA and on-demand calls to AWS Bedrock foundation models.
Requirements
- An AWS IAM account
- An Access key ID (es: AKIAIOSFODNN7EXAMPLE) and its correspondent secret access key (es: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY) for API requests
- These credentials can be created through Home --> Security credentials --> Access Keys --> Create access key
- If you have AWS CLI installed and set up on your machine, chances are your credentials are already stored at ~/.aws/credentials and/or in the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables. In this case, the package will retrieve them automatically.
- Note: AWS CLI is not required to use bedrock-inference.
- A Multi-factor authentication device ARN (es: arn:aws:iam::012345678910:mfa/example_username)
- The ARN of your MFA device can be located at Home --> Security credentials --> Multi-factor authentication
- The 6 digits temp token generated by the MDA device (es: 366 712)
Installation
- Make sure you have the latest version of pip installed
pip install --upgrade pip
- Install araucanaxai through pip
pip install bedrock_inference
Usage
import from bedrock_inference import bedrock
# Authenticates through MFA and establish a session
session = bedrock.aws_login_mfa(arn="MFA_device_arn", token="MFA_token", aws_access_key_id="your_ID", aws_secret_access_key="your_key")
#session = bedrock.aws_login_mfa(arn="MFA_device_arn", token="MFA_token") #use this if you already have AWS credentials set up for API requests on your machine
# Instantiate youre Bedrock caller
caller = bedrock.Bedrock(session=session, region="your_aws_region")
#Check available models in your region
print(caller.list_models())
#Invoke the target AWS model and retrieve the generated answer
answer = caller.invoke_model(prompt="What's the conceptual opposite of 'Hello World'?", model_id="target_aws_model_id")
print(answer)
Contacts and Useful Links
-
Project Link: https://github.com/detsutut/bedrock-inference
-
Package Link: https://pypi.org/project/bedrock-inference/
License
Distributed under MIT License. See LICENSE for more information.
Metadata
Release files for bedrock-inference 0.0.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| bedrock_inference-0.0.13.tar.gz | 7.5 kB | Without provenance | Details for bedrock_inference-0.0.13.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| bedrock_inference-0.0.13-py3-none-any.whl | Python 3 | none | any | Details for bedrock_inference-0.0.13-py3-none-any.whl |
Total release size: 15.1 kB
Release files / bedrock_inference-0.0.13.tar.gz
| Download URL | bedrock_inference-0.0.13.tar.gz |
|---|---|
| Size | 7.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c85ac16b731d8a1eb723ace3962e6d8587b3bdc5a8aa8d9c35e24b9687eedd99
|
|
BLAKE2b-256 checksum How to use checksums |
7169dd62848860b19ce7a5be1dff12c8caad2296319674a0e2d65831fe672fa3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.12
|
Release files / bedrock_inference-0.0.13-py3-none-any.whl
| Download URL | bedrock_inference-0.0.13-py3-none-any.whl |
|---|---|
| Size | 7.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2b4a7dd09174f2e2b733dea799743e68d50523a1cf1b88abe05744c95df96bb2
|
|
BLAKE2b-256 checksum How to use checksums |
3e11d65b476b3b20eceb0df013d15bb6232e480a4d680e4f9ae1afcb165eec12
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.12
|
Security for bedrock-inference 0.0.13
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.