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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,2 +1,2 @@ | ||
| configured_endpoints: 7 | ||
| openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/arcade-ai%2Farcade-engine-5d0034cce7bb0c697f3ec08ab4d585002898a26e9e0e03f42ae2515f1cc56087.yml | ||
| openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/arcade-ai%2Farcade-engine-2f4d672c34ee530fb7290e2fb799d907aba7d9e47030659422f4e7760625be90.yml |
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|---|---|---|
|
|
@@ -15,29 +15,35 @@ The REST API documentation can be found on [arcade-ai.com](https://arcade-ai.com | |
| ## Installation | ||
|
|
||
| ```sh | ||
| # install from PyPI | ||
| pip install --pre arcadepy | ||
| # install from the production repo | ||
| pip install git+ssh://[email protected]/ArcadeAI/arcade-py.git | ||
| ``` | ||
|
|
||
| > [!NOTE] | ||
| > Once this package is [published to PyPI](https://app.stainlessapi.com/docs/guides/publish), this will become: `pip install --pre arcadepy` | ||
| ## Usage | ||
|
|
||
| The full API of this library can be found in [api.md](api.md). | ||
|
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| ```python | ||
| import os | ||
| from arcadepy import ArcadeAI | ||
|
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| client = ArcadeAI( | ||
| # This is the default and can be omitted | ||
| api_key=os.environ.get("ARCADE_API_KEY"), | ||
| # defaults to "production". | ||
| environment="staging", | ||
| ) | ||
|
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| response = client.tools.execute( | ||
| tool_response = client.tools.execute( | ||
| inputs="[object Object]", | ||
| tool_name="Google.ListEmails", | ||
| tool_version="0.1.0", | ||
| user_id="dev@arcade-ai.com", | ||
| user_id="user@example.com", | ||
| ) | ||
| print(response.invocation_id) | ||
| print(tool_response.invocation_id) | ||
| ``` | ||
|
|
||
| While you can provide an `api_key` keyword argument, | ||
|
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@@ -50,23 +56,26 @@ so that your API Key is not stored in source control. | |
| Simply import `AsyncArcadeAI` instead of `ArcadeAI` and use `await` with each API call: | ||
|
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| ```python | ||
| import os | ||
| import asyncio | ||
| from arcadepy import AsyncArcadeAI | ||
|
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| client = AsyncArcadeAI( | ||
| # This is the default and can be omitted | ||
| api_key=os.environ.get("ARCADE_API_KEY"), | ||
| # defaults to "production". | ||
| environment="staging", | ||
| ) | ||
|
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|
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| async def main() -> None: | ||
| response = await client.tools.execute( | ||
| tool_response = await client.tools.execute( | ||
| inputs="[object Object]", | ||
| tool_name="Google.ListEmails", | ||
| tool_version="0.1.0", | ||
| user_id="dev@arcade-ai.com", | ||
| user_id="user@example.com", | ||
| ) | ||
| print(response.invocation_id) | ||
| print(tool_response.invocation_id) | ||
|
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|
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| asyncio.run(main()) | ||
|
|
@@ -99,7 +108,14 @@ from arcadepy import ArcadeAI | |
| client = ArcadeAI() | ||
|
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||
| try: | ||
| client.chat.completions() | ||
| client.chat.completions( | ||
| messages=[ | ||
| { | ||
| "role": "user", | ||
| "content": "Hello, how can I use Arcade AI?", | ||
| } | ||
| ], | ||
| ) | ||
| except arcadepy.APIConnectionError as e: | ||
| print("The server could not be reached") | ||
| print(e.__cause__) # an underlying Exception, likely raised within httpx. | ||
|
|
@@ -142,7 +158,14 @@ client = ArcadeAI( | |
| ) | ||
|
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| # Or, configure per-request: | ||
| client.with_options(max_retries=5).chat.completions() | ||
| client.with_options(max_retries=5).chat.completions( | ||
| messages=[ | ||
| { | ||
| "role": "user", | ||
| "content": "Hello, how can I use Arcade AI?", | ||
| } | ||
| ], | ||
| ) | ||
| ``` | ||
|
|
||
| ### Timeouts | ||
|
|
@@ -165,7 +188,14 @@ client = ArcadeAI( | |
| ) | ||
|
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||
| # Override per-request: | ||
| client.with_options(timeout=5.0).chat.completions() | ||
| client.with_options(timeout=5.0).chat.completions( | ||
| messages=[ | ||
| { | ||
| "role": "user", | ||
| "content": "Hello, how can I use Arcade AI?", | ||
| } | ||
| ], | ||
| ) | ||
| ``` | ||
|
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||
| On timeout, an `APITimeoutError` is thrown. | ||
|
|
@@ -204,7 +234,12 @@ The "raw" Response object can be accessed by prefixing `.with_raw_response.` to | |
| from arcadepy import ArcadeAI | ||
|
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||
| client = ArcadeAI() | ||
| response = client.chat.with_raw_response.completions() | ||
| response = client.chat.with_raw_response.completions( | ||
| messages=[{ | ||
| "role": "user", | ||
| "content": "Hello, how can I use Arcade AI?", | ||
| }], | ||
| ) | ||
| print(response.headers.get('X-My-Header')) | ||
|
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| chat = response.parse() # get the object that `chat.completions()` would have returned | ||
|
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@@ -222,7 +257,14 @@ The above interface eagerly reads the full response body when you make the reque | |
| To stream the response body, use `.with_streaming_response` instead, which requires a context manager and only reads the response body once you call `.read()`, `.text()`, `.json()`, `.iter_bytes()`, `.iter_text()`, `.iter_lines()` or `.parse()`. In the async client, these are async methods. | ||
|
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| ```python | ||
| with client.chat.with_streaming_response.completions() as response: | ||
| with client.chat.with_streaming_response.completions( | ||
| messages=[ | ||
| { | ||
| "role": "user", | ||
| "content": "Hello, how can I use Arcade AI?", | ||
| } | ||
| ], | ||
| ) as response: | ||
| print(response.headers.get("X-My-Header")) | ||
|
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||
| for line in response.iter_lines(): | ||
|
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