Overview

The project implements AI DIAL API for language models and embeddings from Vertex AI.

Supported models

The following models support POST SERVER_URL/openai/deployments/DEPLOYMENT_NAME/chat/completions endpoint along with optional support of /tokenize and /truncate_prompt endpoints:

Model	Deployment name	Modality	/tokenize	/truncate_prompt	tools/functions support
Gemini 1.5 Pro	gemini-1.5-pro-[preview-0409|001|002]	(text/pdf/image/audio/video)-to-text	✅	✅	✅
Gemini 1.5 Flash	gemini-1.5-flash-[001|002]	(text/pdf/image/audio/video)-to-text	✅	✅	✅
Gemini 1.0 Pro Vision	gemini-pro-vision	(text/pdf/image/video)-to-text	✅	✅	❌
Gemini 1.0 Pro	gemini-pro	text-to-text	✅	✅	✅
Imagen 2	imagegeneration@005	text-to-image	✅	✅	❌
PaLM 2 Chat Bison	chat-bison@001	text-to-text	✅	✅	❌
PaLM 2 Chat Bison	chat-bison@002	text-to-text	✅	✅	❌
PaLM 2 Chat Bison	chat-bison-32k@002	text-to-text	✅	✅	❌
Codey for Code Chat	codechat-bison@001	text-to-text	✅	✅	❌
Codey for Code Chat	codechat-bison@002	text-to-text	✅	✅	❌
Codey for Code Chat	codechat-bison-32k@002	text-to-text	✅	✅	❌

The models that support /truncate_prompt do also support max_prompt_tokens request parameter.

The following models support SERVER_URL/openai/deployments/DEPLOYMENT_NAME/embeddings endpoint:

Model	Deployment name	Language support	Modality
Gecko Embeddings for Text V1	textembedding-gecko@001	English	text-to-embedding
Gecko Embeddings for Text V3	textembedding-gecko@003	English	text-to-embedding
Embeddings for Text	text-embedding-004	English	text-to-embedding
Gecko Embeddings for Text Multilingual	textembedding-gecko-multilingual@001	Multilingual	text-to-embedding
Embeddings for Text Multilingual	text-multilingual-embedding-002	Multilingual	text-to-embedding
Multimodal embeddings	multimodalembedding@001	English	(text/image)-to-embedding

Developer environment

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.

IDE configuration

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

Run the development server:

make serve

Open localhost:5001/docs to make sure the server is up and running.

Environment Variables

Copy .env.example to .env and customize it for your environment:

Variable	Default	Description
GOOGLE_APPLICATION_CREDENTIALS		Filepath to JSON with credentials
DEFAULT_REGION		Default region for Vertex AI (e.g. "us-central1")
GCP_PROJECT_ID		GCP project ID
LOG_LEVEL	INFO	Log level. Use DEBUG for dev purposes and INFO in prod
AIDIAL_LOG_LEVEL	WARNING	AI DIAL SDK log level
WEB_CONCURRENCY	1	Number of workers for the server
DIAL_URL		URL of the core DIAL server. Optional. Used to access images stored in the DIAL File storage

Docker

Run the server in Docker:

make docker_serve

Lint

Run the linting before committing:

make lint

To auto-fix formatting issues run:

make format

Test

Run unit tests locally:

make test

Run unit tests in Docker:

make docker_test

Run integration tests locally:

make integration_tests

Clean

To remove the virtual environment and build artifacts:

make clean