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ElshadHu
2026-01-14 03:25:34 -05:00
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docs/en/ai-providers.md
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@@ -33,6 +33,21 @@ Optional custom endpoint:
GOOGLE_BASE_URL=https://your-custom-endpoint
```
### Google Vertex AI (Enterprise GCP)
Google Vertex AI offers enterprise-grade features and data residency. **Express Mode** allows for simple API key authentication, making it compatible with edge runtimes like Vercel and Cloudflare.
```bash
GOOGLE_VERTEX_API_KEY=your_api_key
AI_MODEL=gemini-2.0-flash
```
Optional custom endpoint:
```bash
GOOGLE_VERTEX_BASE_URL=https://your-custom-endpoint
```
### OpenAI
```bash
env.example
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@@ -42,13 +42,11 @@ AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
# Google Vertex AI Configuration (Enterprise GCP)
# For enterprise users needing data residency, VPC Service Controls, or GCP integration
# Uses GCP service account authentication instead of API keys
# GOOGLE_VERTEX_PROJECT=your-gcp-project-id # Required: GCP project ID
# GOOGLE_VERTEX_LOCATION=us-central1 # Optional: defaults to us-central1
# GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json # Path to service account key file
# Note: When running on GCP (Cloud Run, GKE, Compute Engine), uses Application Default Credentials automatically
# GOOGLE_VERTEX_API_KEY= # Required: Express Mode API key
# GOOGLE_VERTEX_BASE_URL=https://... # Optional: Custom endpoint URL
# Note: Gemini 2.5/3 models automatically enable reasoning display (includeThoughts: true)
# GOOGLE_VERTEX_THINKING_BUDGET=8192 # Optional: Gemini 2.5 thinking budget in tokens (1024-100000)
# GOOGLE_VERTEX_THINKING_LEVEL=high # Optional: Gemini 3 thinking level (low/high)
# GOOGLE_VERTEX_THINKING_LEVEL=high # Optional: Gemini 3 thinking level (minimal/low/medium/high)
# Azure OpenAI Configuration
# Configure endpoint using ONE of these methods: