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5fe6098350
# What does this PR do? This PR improves type hint cleanup in auto-generated provider documentation by adding regex logic. **Issues Fixed:** - Type hints with missing closing brackets (e.g., `list[str` instead of `list[str]`) - Types showing as `<class 'bool'>`, `<class 'str'>` instead of `bool`, `str` - The multi-line YAML frontmatter in index documentation files wasn't ideal, so we now add the proper `|` character. **Changes:** 1. Replaced string replacement (`.replace`) with regex-based type cleaning to preserve the trailing bracket in case of `list` and `dict`. 2. Adds the `|` character for multi-line YAML descriptions. 3. I have regenerated the docs. However, let me know if that's not needed. ## Test Plan 1. Ran uv run python scripts/provider_codegen.py - successfully regenerated all docs 2. We can see that the updated docs handle correctly type hint cleanup and multi-line yaml descriptions have now the `|` character. ### Note to the reviewer(s) This is my first contribution to your lovely repo! Initially I was going thourgh docs (wanted to use `remote::gemini` as provider) and realized the issue. I've read the [CONTRIBUTING.md](https://github.com/llamastack/llama-stack/blob/main/CONTRIBUTING.md) and decided to open the PR. Let me know if there's anything I did wrong and I'll update my PR! --------- Signed-off-by: thepetk <thepetk@gmail.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
66 lines
2.7 KiB
Text
66 lines
2.7 KiB
Text
---
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description: |
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Google Vertex AI inference provider enables you to use Google's Gemini models through Google Cloud's Vertex AI platform, providing several advantages:
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• Enterprise-grade security: Uses Google Cloud's security controls and IAM
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• Better integration: Seamless integration with other Google Cloud services
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• Advanced features: Access to additional Vertex AI features like model tuning and monitoring
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• Authentication: Uses Google Cloud Application Default Credentials (ADC) instead of API keys
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Configuration:
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- Set VERTEX_AI_PROJECT environment variable (required)
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- Set VERTEX_AI_LOCATION environment variable (optional, defaults to us-central1)
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- Use Google Cloud Application Default Credentials or service account key
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Authentication Setup:
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Option 1 (Recommended): gcloud auth application-default login
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Option 2: Set GOOGLE_APPLICATION_CREDENTIALS to service account key path
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Available Models:
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- vertex_ai/gemini-2.0-flash
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- vertex_ai/gemini-2.5-flash
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- vertex_ai/gemini-2.5-pro
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sidebar_label: Remote - Vertexai
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title: remote::vertexai
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---
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# remote::vertexai
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## Description
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Google Vertex AI inference provider enables you to use Google's Gemini models through Google Cloud's Vertex AI platform, providing several advantages:
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• Enterprise-grade security: Uses Google Cloud's security controls and IAM
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• Better integration: Seamless integration with other Google Cloud services
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• Advanced features: Access to additional Vertex AI features like model tuning and monitoring
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• Authentication: Uses Google Cloud Application Default Credentials (ADC) instead of API keys
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Configuration:
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- Set VERTEX_AI_PROJECT environment variable (required)
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- Set VERTEX_AI_LOCATION environment variable (optional, defaults to us-central1)
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- Use Google Cloud Application Default Credentials or service account key
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Authentication Setup:
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Option 1 (Recommended): gcloud auth application-default login
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Option 2: Set GOOGLE_APPLICATION_CREDENTIALS to service account key path
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Available Models:
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- vertex_ai/gemini-2.0-flash
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- vertex_ai/gemini-2.5-flash
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- vertex_ai/gemini-2.5-pro
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## Configuration
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| Field | Type | Required | Default | Description |
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|-------|------|----------|---------|-------------|
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| `allowed_models` | `list[str] \| None` | No | | List of models that should be registered with the model registry. If None, all models are allowed. |
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| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
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| `project` | `str` | No | | Google Cloud project ID for Vertex AI |
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| `location` | `str` | No | us-central1 | Google Cloud location for Vertex AI |
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## Sample Configuration
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```yaml
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project: ${env.VERTEX_AI_PROJECT:=}
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location: ${env.VERTEX_AI_LOCATION:=us-central1}
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```
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