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This PR introduces both synchronous and asynchronous Arcade client implementations, providing a robust interface for interacting with the Arcade API. ## Key Features 1. Synchronous (`SyncArcade`) and Asynchronous (`AsyncArcade`) clients 2. Authentication and Tool resources 3. OpenAI chat completions integration 4. Comprehensive error handling ## Client Methods Both `SyncArcade` and `AsyncArcade` offer: - `auth.authorize()`: Initiate authorization - `auth.poll_authorization()`: Check authorization status - `tool.run()`: Execute a tool - `tool.get()`: Retrieve tool specification - `chat.create()`: Create chat completions ## Usage Examples ### Synchronous Authorization ```python from arcade.client import AuthProvider, SyncArcade client = SyncArcade(base_url="https://api.arcade.com", api_key="your_api_key") auth_response = client.auth.authorize( provider=AuthProvider.google, scopes=["https://www.googleapis.com/auth/gmail.readonly"], user_id="user123" ) print(f"Authorize at: {auth_response.auth_url}") ``` ### Asynchronous Authorization ```python import asyncio from arcade.client import AuthProvider, AsyncArcade async def authorize(): client = AsyncArcade(base_url="https://api.arcade.com", api_key="your_api_key") auth_response = await client.auth.authorize( provider=AuthProvider.slack_user, scopes=["chat:write", "im:write"], user_id="user456" ) print(f"Authorize at: {auth_response.auth_url}") asyncio.run(authorize()) ``` This implementation provides a flexible and powerful way to interact with Arcade services, supporting both synchronous and asynchronous workflows. |
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| arcade | ||
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| examples | ||
| schemas/preview | ||
| toolkits | ||
| .editorconfig | ||
| .gitignore | ||
| .pre-commit-config.yaml | ||
| .prettierrc.toml | ||
| CONTRIBUTING.md | ||
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| README.md | ||
Arcade AI
Arcade AI is the developer platform for building tools designed to be used with language models. With Arcade, developers can create, deploy, and easily integrate new tools with language models to enhance their capabilities.
arcade-ai
The arcade-ai package contains:
arcadeCLIarcade.sdkTool SDKarcade.actorserving tools with FastAPI, Flask, or Django
Installation
To install the Arcade AI package, execute the following command:
pip install arcade-ai
or install from source:
git clone https://github.com/arcadeai/arcade-ai.git
cd arcade-ai
pip install poetry
poetry install
First steps
Follow these steps if you've cloned the repo and installed the package from source:
cd examples/websearch
poetry install
arcade show arcade_websearch
This will show an output that looks like
┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━┓ ┃ Name ┃ Description ┃ Toolkit ┃ Version ┃ ┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━┩ │ SearchGoogle │ Search Google using SerpAPI and return organic search results. │ websearch │ 0.1.0 │ └──────────────┴────────────────────────────────────────────────────────────────┴───────────┴─────────┘
Predict the parameters with a model and run the tool with the predicted parameters. Arcade adds the execute choice to the tool, which allows you to run the tool with the predicted parameters in a single request.
> arcade run arcade_websearch "who is Sam Partee?" --choice "execute"
Running tool: SearchGoogle with params: {'query': 'Sam Partee'}
[{"position": 1, "title": "Sam Partee (@SamPartee) / X", "link": "https://twitter.com/sampartee", "redirect_link":
"https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://twitter.com/sampartee&ved=2ahUKEwjBwKiz3b6HAxV1VTABHXL8BZQQFnoECAYQAQ",
"displayed_link": "1.5K+ followers", "thumbnail":
.....
.. (truncated)
Arcade also adds the predict choice to the tool, which allows you to predict the parameters with a model.
> arcade run arcade_websearch "who is Sam Partee?" --choice "predict" # also the default
Running tool: SearchGoogle with params: {'query': 'Sam Partee'}
Sam Partee is a CTO, Co-founder of Arcade AI and former Machine Learning Engineer at companies like RedisInc and HPE_Cray. They have
expertise in AI/ML, vector search, Python, HPC, and are a sports fan.