The project implements AI DIAL API for language models from AWS Bedrock.
The following models support POST SERVER_URL/openai/deployments/DEPLOYMENT_NAME/chat/completions
endpoint along with an optional support of POST /tokenize
and POST /truncate_prompt
endpoints:
Note that a model supports /truncate_prompt
endpoint if and only if it supports max_prompt_tokens
request parameter.
Vendor | Model | Deployment name | Modality | /tokenize |
/truncate_prompt , max_prompt_tokens |
tools/functions |
---|---|---|---|---|---|---|
Anthropic | Claude 3.5 Sonnet | [us.|eu.]anthropic.claude-3-5-sonnet-20240620-v1:0 | text-to-text, image-to-text | π‘ | π‘ | β |
Anthropic | Claude 3.5 Sonnet 2.0 | [us.]anthropic.claude-3-5-sonnet-20241022-v2:0 | text-to-text, image-to-text | π‘ | π‘ | β |
Anthropic | Claude 3 Sonnet | [us.|eu.]anthropic.claude-3-sonnet-20240229-v1:0 | text-to-text, image-to-text | π‘ | π‘ | β |
Anthropic | Claude 3 Haiku | [us.|eu.]anthropic.claude-3-haiku-20240307-v1:0 | text-to-text, image-to-text | π‘ | π‘ | β |
Anthropic | Claude 3 Opus | [us.]anthropic.claude-3-opus-20240229-v1:0 | text-to-text, image-to-text | π‘ | π‘ | β |
Anthropic | Claude 2.1 | anthropic.claude-v2:1 | text-to-text | β | β | β |
Anthropic | Claude 2 | anthropic.claude-v2 | text-to-text | β | β | β |
Anthropic | Claude Instant 1.2 | anthropic.claude-instant-v1 | text-to-text | π‘ | π‘ | β |
Meta | Llama 3.1 405B Instruct | meta.llama3-1-405b-instruct-v1:0 | text-to-text | π‘ | π‘ | β |
Meta | Llama 3.1 70B Instruct | meta.llama3-1-70b-instruct-v1:0 | text-to-text | π‘ | π‘ | β |
Meta | Llama 3.1 8B Instruct | meta.llama3-1-8b-instruct-v1:0 | text-to-text | π‘ | π‘ | β |
Meta | Llama 3 Chat 70B Instruct | meta.llama3-70b-instruct-v1:0 | text-to-text | π‘ | π‘ | β |
Meta | Llama 3 Chat 8B Instruct | meta.llama3-8b-instruct-v1:0 | text-to-text | π‘ | π‘ | β |
Meta | Llama 2 Chat 70B | meta.llama2-70b-chat-v1 | text-to-text | π‘ | π‘ | β |
Meta | Llama 2 Chat 13B | meta.llama2-13b-chat-v1 | text-to-text | π‘ | π‘ | β |
Stability AI | SDXL 1.0 | stability.stable-diffusion-xl-v1 | text-to-image | β | π‘ | β |
Stability AI | SD3 Large 1.0 | stability.sd3-large-v1:0 | text-to-image / image-to-image | β | π‘ | β |
Stability AI | Stale Image Ultra 1.0 | stability.stable-image-ultra-v1:0 | text-to-image | β | π‘ | β |
Stability AI | Stale Image Core 1.0 | stability.stable-image-core-v1:0 | text-to-image | β | π‘ | β |
Amazon | Titan Text G1 - Express | amazon.titan-tg1-large | text-to-text | π‘ | π‘ | β |
AI21 Labs | Jurassic-2 Ultra | ai21.j2-jumbo-instruct | text-to-text | π‘ | π‘ | β |
AI21 Labs | Jurassic-2 Ultra v1 | ai21.j2-ultra-v1 | text-to-text | π‘ | π‘ | β |
AI21 Labs | Jurassic-2 Mid | ai21.j2-grande-instruct | text-to-text | π‘ | π‘ | β |
AI21 Labs | Jurassic-2 Mid v1 | ai21.j2-mid-v1 | text-to-text | π‘ | π‘ | β |
Cohere | Command | cohere.command-text-v14 | text-to-text | π‘ | π‘ | β |
Cohere | Command Light | cohere.command-light-text-v14 | text-to-text | π‘ | π‘ | β |
β , π‘, and β denote degrees of support of the given feature:
/tokenize , /truncate_prompt , max_prompt_token |
tools/functions | |
---|---|---|
β | Fully supported via an official tokenization algorithm | Fully supported via native tools API or official prompts to enable tools |
π‘ | Partially supported, because tokenization algorithm wasn't made public by the model vendor. An approximate tokenization algorithm is used instead. It conservatively counts every byte in UTF-8 encoding of a string as a single token. |
Partially supported, because the model doesn't support tools natively. Prompt engineering is used instead to emulate tools, which may not be very reliable. |
β | Not supported | Not supported |
The following models support SERVER_URL/openai/deployments/DEPLOYMENT_NAME/embeddings
endpoint:
Model | Deployment name | Modality |
---|---|---|
Titan Multimodal Embeddings Generation 1 (G1) | amazon.titan-embed-image-v1 | image/text-to-embedding |
Amazon Titan Text Embeddings V2 | amazon.titan-embed-text-v2:0 | text-to-embedding |
Titan Embeddings G1 β Text v1.2 | amazon.titan-embed-text-v1 | text-to-embedding |
Cohere Embed English | cohere.embed-english-v3 | text-to-embedding |
Cohere Multilingual | cohere.embed-multilingual-v3 | text-to-embedding |
This project uses Python>=3.11 and Poetry>=1.6.1 as a dependency manager.
Check out Poetry's documentation on how to install it on your system before proceeding.
To install requirements:
poetry install
This will install all requirements for running the package, linting, formatting and tests.
The recommended IDE is VSCode. Open the project in VSCode and install the recommended extensions.
The VSCode is configured to use PEP-8 compatible formatter Black.
Alternatively you can use PyCharm.
Set-up the Black formatter for PyCharm manually or install PyCharm>=2023.2 with built-in Black support.
Run the development server:
make serve
Open localhost:5001/docs
to make sure the server is up and running.
Copy .env.example
to .env
and customize it for your environment:
Variable | Default | Description |
---|---|---|
AWS_ACCESS_KEY_ID | NA | AWS credentials with access to Bedrock service |
AWS_SECRET_ACCESS_KEY | NA | AWS credentials with access to Bedrock service |
AWS_DEFAULT_REGION | AWS region e.g. us-east-1 |
|
AWS_ASSUME_ROLE_ARN | AWS assume role arn e.g. arn:aws:iam::123456789012:role/RoleName |
|
LOG_LEVEL | INFO | Log level. Use DEBUG for dev purposes and INFO in prod |
AIDIAL_LOG_LEVEL | WARNING | AI DIAL SDK log level |
DIAL_URL | URL of the core DIAL server. If defined, images generated by Stability are uploaded to the DIAL file storage and attachments are returned with URLs pointing to the images. Otherwise, the images are returned as base64 encoded strings. | |
WEB_CONCURRENCY | 1 | Number of workers for the server |
If you use DIAL Core load balancing mechanism, you can provide extraData
upstream setting with different aws account credentials/regions to use different model deployments:
{
"upstreams": [
{
"extraData": {
"region": "eu-west-1",
"aws_access_key_id": "key_id_1",
"aws_secret_access_key": "access_key_1"
}
},
{
"extraData": {
"region": "eu-west-1",
"aws_access_key_id": "key_id_2",
"aws_secret_access_key": "access_key_2"
}
},
{
"extraData": {
"region": "eu-west-1",
"aws_assume_role_arn": "arn:aws:iam::123456789012:role/BedrockAccessAdapterRoleName"
}
}
]
}
Supported extraData
fields:
region
aws_access_key_id
aws_secret_access_key
aws_assume_role_arn
Run the server in Docker:
make docker_serve
Run the linting before committing:
make lint
To auto-fix formatting issues run:
make format
Run unit tests locally:
make test
Run unit tests in Docker:
make docker_test
Run integration tests locally:
make integration_tests
To remove the virtual environment and build artifacts:
make clean