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@@ -28,7 +28,7 @@ Target-specific workflows built on the same engine:
|
||||
- **Open-source CLI (self-hosted):** free, fully local, BYO LLM key, needs Docker. Best for local dev loops, air-gapped/offline, and full control.
|
||||
```bash
|
||||
curl -sSL https://strix.ai/install | bash # install
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3" # any LiteLLM model id, or vercel_ai_gateway/zai/glm-5.3
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3" # any LiteLLM model id
|
||||
export LLM_API_KEY="<key>"
|
||||
strix -n -t ./ --scan-mode quick --max-budget 10 # headless scan; always use -n
|
||||
```
|
||||
|
||||
+1
-1
@@ -31,7 +31,7 @@ Thank you for your interest in contributing to Strix! This guide will help you g
|
||||
|
||||
3. **Configure your LLM provider**
|
||||
```bash
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3" # or vercel_ai_gateway/zai/glm-5.3
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
```
|
||||
|
||||
|
||||
@@ -84,8 +84,7 @@ Strix are autonomous AI penetration testing agents that act just like real hacke
|
||||
curl -sSL https://strix.ai/install | bash
|
||||
|
||||
# Configure your AI provider
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3" # Vercel AI Gateway
|
||||
# export STRIX_LLM="openrouter/z-ai/glm-5.3" # OpenRouter
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
|
||||
# Run your first security assessment
|
||||
@@ -297,8 +296,7 @@ jobs:
|
||||
### Configuration
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3" # Vercel AI Gateway
|
||||
# export STRIX_LLM="openrouter/z-ai/glm-5.3" # OpenRouter
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
|
||||
# Optional
|
||||
@@ -354,14 +352,12 @@ Each server's tools are namespaced by `name`, for example `github_list_issues`.
|
||||
|
||||
**Recommended models for best results:**
|
||||
|
||||
- [Z.ai GLM-5.3 on Vercel AI Gateway](https://vercel.com/ai-gateway/models/glm-5.3) - `vercel_ai_gateway/zai/glm-5.3` (recommended)
|
||||
- [Z.ai GLM-5.3 on OpenRouter](https://openrouter.ai/z-ai/glm-5.3) - `openrouter/z-ai/glm-5.3` (recommended)
|
||||
- [DeepSeek V4.1 Flash on OpenRouter](https://openrouter.ai/deepseek/deepseek-v4.1-flash-1017) - `openrouter/deepseek/deepseek-v4.1-flash-1017`
|
||||
- [OpenAI GPT-6.1 Sol](https://openai.com/api/) - `openai/gpt-6.1-sol` (needs [Daybreak](https://openai.com/daybreak/) access)
|
||||
- [Anthropic Claude Opus 5.5](https://claude.com/platform/api) - `anthropic/claude-opus-5-5` (needs [CVP](https://support.claude.com/en/articles/14604842-cyber-verification-program) access)
|
||||
- [Google Gemini 4 Argon](https://cloud.google.com/vertex-ai) - `vertex_ai/gemini-4-argon` (needs [Fairwind](https://deepmind.google/fairwind-program/) access)
|
||||
- [Z.ai GLM-5.3 on OpenRouter](https://openrouter.ai/z-ai/glm-5.3) - `openrouter/z-ai/glm-5.3` (the default pick)
|
||||
- [OpenAI GPT-5.4](https://openai.com/api/) - `openai/gpt-5.4`
|
||||
- [Anthropic Claude Sonnet 4.6](https://claude.com/platform/api) - `anthropic/claude-sonnet-4-6`
|
||||
- [Google Gemini 3 Pro Preview](https://cloud.google.com/vertex-ai) - `vertex_ai/gemini-3-pro-preview`
|
||||
- [DeepSeek V4 Pro](https://platform.deepseek.com) - `deepseek/deepseek-v4-pro`
|
||||
- [Moonshot Kimi K3.1 Pro](https://platform.kimi.ai) - `moonshot/kimi-k3.1-pro`
|
||||
- [Moonshot Kimi K3](https://platform.kimi.ai) - `moonshot/kimi-k3`
|
||||
|
||||
See the [LLM Providers documentation](https://docs.strix.ai/llm-providers/overview) for all supported providers including Vertex AI, Bedrock, Azure, and local models.
|
||||
|
||||
|
||||
@@ -8,7 +8,7 @@ Configure Strix using environment variables or a config file.
|
||||
## LLM Configuration
|
||||
|
||||
<ParamField path="STRIX_LLM" type="string" required>
|
||||
Model name in LiteLLM format (e.g., `openrouter/z-ai/glm-5.3`, `openai/gpt-6.1-sol`).
|
||||
Model name in LiteLLM format (e.g., `openrouter/z-ai/glm-5.3`, `openai/gpt-5.4`).
|
||||
</ParamField>
|
||||
|
||||
<ParamField path="LLM_API_KEY" type="string">
|
||||
|
||||
+1
-1
@@ -35,8 +35,8 @@
|
||||
"llm-providers/overview",
|
||||
"llm-providers/openai",
|
||||
"llm-providers/anthropic",
|
||||
"llm-providers/vercel-ai-gateway",
|
||||
"llm-providers/openrouter",
|
||||
"llm-providers/vercel-ai-gateway",
|
||||
"llm-providers/vertex",
|
||||
"llm-providers/bedrock",
|
||||
"llm-providers/azure",
|
||||
|
||||
+1
-15
@@ -73,20 +73,7 @@ Strix uses a graph of specialized agents for comprehensive security testing:
|
||||
|
||||
## Quick Example
|
||||
|
||||
<CodeGroup>
|
||||
```bash Vercel AI Gateway
|
||||
# Install
|
||||
curl -sSL https://strix.ai/install | bash
|
||||
|
||||
# Configure
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
|
||||
# Scan
|
||||
strix --target ./your-app
|
||||
```
|
||||
|
||||
```bash OpenRouter
|
||||
```bash
|
||||
# Install
|
||||
curl -sSL https://strix.ai/install | bash
|
||||
|
||||
@@ -97,7 +84,6 @@ export LLM_API_KEY="your-api-key"
|
||||
# Scan
|
||||
strix --target ./your-app
|
||||
```
|
||||
</CodeGroup>
|
||||
|
||||
## Community
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@ description: "Configure Strix with Claude models"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="anthropic/claude-sonnet-5-5"
|
||||
export STRIX_LLM="anthropic/claude-sonnet-4-6"
|
||||
export LLM_API_KEY="sk-ant-..."
|
||||
```
|
||||
|
||||
@@ -14,12 +14,8 @@ export LLM_API_KEY="sk-ant-..."
|
||||
|
||||
| Model | Description |
|
||||
|-------|-------------|
|
||||
| `anthropic/claude-sonnet-5-5` | Best balance of intelligence and speed |
|
||||
| `anthropic/claude-opus-5-5` | Maximum capability for deep analysis |
|
||||
|
||||
<Note>
|
||||
Security testing with Claude needs the [Cyber Verification Program](https://support.claude.com/en/articles/14604842-cyber-verification-program) (CVP). Without it the safety classifiers block most offensive tasks. Red Team Access covers authorized penetration testing.
|
||||
</Note>
|
||||
| `anthropic/claude-sonnet-4-6` | Best balance of intelligence and speed |
|
||||
| `anthropic/claude-opus-4-6` | Maximum capability for deep analysis |
|
||||
|
||||
## Get API Key
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@ description: "Configure Strix with OpenAI models via Azure"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="azure/your-gpt6-deployment"
|
||||
export STRIX_LLM="azure/your-gpt5-deployment"
|
||||
export AZURE_API_KEY="your-azure-api-key"
|
||||
export AZURE_API_BASE="https://your-resource.openai.azure.com"
|
||||
export AZURE_API_VERSION="2025-11-01-preview"
|
||||
@@ -24,7 +24,7 @@ export AZURE_API_VERSION="2025-11-01-preview"
|
||||
## Example
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="azure/gpt-6.1-sol-deployment"
|
||||
export STRIX_LLM="azure/gpt-5.4-deployment"
|
||||
export AZURE_API_KEY="abc123..."
|
||||
export AZURE_API_BASE="https://mycompany.openai.azure.com"
|
||||
export AZURE_API_VERSION="2025-11-01-preview"
|
||||
@@ -33,9 +33,5 @@ export AZURE_API_VERSION="2025-11-01-preview"
|
||||
## Prerequisites
|
||||
|
||||
1. Create an Azure OpenAI resource
|
||||
2. Deploy a model such as GPT-6.1 Sol
|
||||
2. Deploy a model (e.g., GPT-5.4)
|
||||
3. Get the endpoint URL and API key from the Azure portal
|
||||
|
||||
<Note>
|
||||
Security testing with OpenAI models needs [Daybreak](https://openai.com/daybreak/) access, also on Azure.
|
||||
</Note>
|
||||
@@ -6,7 +6,7 @@ description: "Configure Strix with models via AWS Bedrock"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="bedrock/us.anthropic.claude-sonnet-5-5"
|
||||
export STRIX_LLM="bedrock/anthropic.claude-4-5-sonnet-20251022-v1:0"
|
||||
```
|
||||
|
||||
No API key required—uses AWS credentials from environment.
|
||||
@@ -36,13 +36,10 @@ Automatically uses instance role credentials.
|
||||
|
||||
| Model | Description |
|
||||
|-------|-------------|
|
||||
| `bedrock/us.anthropic.claude-sonnet-5-5` | Claude Sonnet 5.5 |
|
||||
| `bedrock/us.anthropic.claude-opus-5-5` | Claude Opus 5.5 |
|
||||
| `bedrock/us.anthropic.claude-haiku-5-5` | Claude Haiku 5.5 |
|
||||
|
||||
<Note>
|
||||
Security testing with Claude needs the [Cyber Verification Program](https://support.claude.com/en/articles/14604842-cyber-verification-program) (CVP), also on Bedrock.
|
||||
</Note>
|
||||
| `bedrock/anthropic.claude-4-5-sonnet-20251022-v1:0` | Claude 4.5 Sonnet |
|
||||
| `bedrock/anthropic.claude-4-5-opus-20251022-v1:0` | Claude 4.5 Opus |
|
||||
| `bedrock/anthropic.claude-4-5-haiku-20251022-v1:0` | Claude 4.5 Haiku |
|
||||
| `bedrock/amazon.titan-text-premier-v2:0` | Amazon Titan Premier v2 |
|
||||
|
||||
## Prerequisites
|
||||
|
||||
|
||||
@@ -8,7 +8,7 @@ description: "Configure Strix with Novita AI models"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="openai/zai-org/glm-5.3"
|
||||
export STRIX_LLM="openai/moonshotai/kimi-k2.5"
|
||||
export LLM_API_KEY="your-novita-api-key"
|
||||
export LLM_API_BASE="https://api.novita.ai/openai"
|
||||
```
|
||||
@@ -18,12 +18,11 @@ export LLM_API_BASE="https://api.novita.ai/openai"
|
||||
| Model | Configuration |
|
||||
|-------|---------------|
|
||||
| GLM-5.3 | `openai/zai-org/glm-5.3` |
|
||||
| Kimi K3.1 Pro | `openai/moonshotai/kimi-k3.1-pro` |
|
||||
| Kimi K3 | `openai/moonshotai/kimi-k3` |
|
||||
| DeepSeek V4.1 Flash | `openai/deepseek/deepseek-v4.1-flash-1017` |
|
||||
| DeepSeek V4 Pro | `openai/deepseek/deepseek-v4-pro` |
|
||||
| MiniMax M3.1 Flash | `openai/minimax/minimax-m3.1-flash` |
|
||||
| GLM-5.3 Flash | `openai/zai-org/glm-5.3-flash` |
|
||||
| Kimi K2.5 | `openai/moonshotai/kimi-k2.5` |
|
||||
| GLM-5 | `openai/zai-org/glm-5` |
|
||||
| MiniMax M2.5 | `openai/minimax/minimax-m2.5` |
|
||||
|
||||
## Get API Key
|
||||
|
||||
|
||||
@@ -6,23 +6,13 @@ description: "Configure Strix with OpenAI models"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="openai/gpt-6.1-sol"
|
||||
export STRIX_LLM="openai/gpt-5.4"
|
||||
export LLM_API_KEY="sk-..."
|
||||
```
|
||||
|
||||
## Available Models
|
||||
|
||||
| Model | Description |
|
||||
|-------|-------------|
|
||||
| `openai/gpt-6.1-sol` | Best balance of capability and cost for agentic security work |
|
||||
| `openai/gpt-6-astra` | Flagship, maximum capability |
|
||||
| `openai/gpt-6-luna` | Fast and cheap |
|
||||
|
||||
See [OpenAI Models Documentation](https://platform.openai.com/docs/models) for the full list.
|
||||
|
||||
<Note>
|
||||
Security testing with OpenAI models needs [Daybreak](https://openai.com/daybreak/) (Trusted Access for Cyber). Without it the models refuse most offensive tasks. [Request access](https://openai.com/form/enterprise-trusted-access-for-cyber/).
|
||||
</Note>
|
||||
See [OpenAI Models Documentation](https://platform.openai.com/docs/models) for the full list of available models.
|
||||
|
||||
## Get API Key
|
||||
|
||||
@@ -35,7 +25,7 @@ Security testing with OpenAI models needs [Daybreak](https://openai.com/daybreak
|
||||
For OpenAI-compatible APIs:
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="openai/gpt-6.1-sol"
|
||||
export STRIX_LLM="openai/gpt-5.4"
|
||||
export LLM_API_KEY="your-key"
|
||||
export LLM_API_BASE="https://your-proxy.com/v1"
|
||||
```
|
||||
@@ -18,19 +18,13 @@ Access any model on OpenRouter using the format `openrouter/<provider>/<model>`:
|
||||
|
||||
| Model | Configuration |
|
||||
|-------|---------------|
|
||||
| GLM-5.3 (recommended) | `openrouter/z-ai/glm-5.3` |
|
||||
| GPT-6.1 Sol | `openrouter/openai/gpt-6.1-sol` |
|
||||
| GPT-6 Astra | `openrouter/openai/gpt-6-astra` |
|
||||
| Claude Opus 5.5 | `openrouter/anthropic/claude-opus-5.5` |
|
||||
| Claude Sonnet 5.5 | `openrouter/anthropic/claude-sonnet-5.5` |
|
||||
| Gemini 4 Argon | `openrouter/google/gemini-4-argon` |
|
||||
| Gemini 3.8 Flash | `openrouter/google/gemini-3.8-flash` |
|
||||
| DeepSeek V4.1 Flash | `openrouter/deepseek/deepseek-v4.1-flash-1017` |
|
||||
| GLM-5.3 (default) | `openrouter/z-ai/glm-5.3` |
|
||||
| GPT-5.4 | `openrouter/openai/gpt-5.4` |
|
||||
| Claude Sonnet 4.6 | `openrouter/anthropic/claude-sonnet-4.6` |
|
||||
| Gemini 3 Pro | `openrouter/google/gemini-3-pro-preview` |
|
||||
| DeepSeek V4 Pro | `openrouter/deepseek/deepseek-v4-pro` |
|
||||
| Kimi K3.1 Pro | `openrouter/moonshotai/kimi-k3.1-pro` |
|
||||
| GLM-5.3 Flash | `openrouter/z-ai/glm-5.3-flash` |
|
||||
|
||||
OpenAI, Anthropic and Gemini models keep their provider safeguards on OpenRouter. Security testing with them needs [Daybreak](https://openai.com/daybreak/), [CVP](https://support.claude.com/en/articles/14604842-cyber-verification-program) or [Fairwind](https://deepmind.google/fairwind-program/) access.
|
||||
| Kimi K3 | `openrouter/moonshotai/kimi-k3` |
|
||||
| GLM-4.7 | `openrouter/z-ai/glm-4.7` |
|
||||
|
||||
## Get API Key
|
||||
|
||||
|
||||
@@ -9,33 +9,19 @@ Strix uses [LiteLLM](https://docs.litellm.ai/docs/providers) for model compatibi
|
||||
|
||||
Set your model and API key:
|
||||
|
||||
| Model | Provider | Configuration |
|
||||
| --------------------- | ------------------------- | -------------------------------- |
|
||||
| GLM-5.3 (recommended) | Vercel AI Gateway | `vercel_ai_gateway/zai/glm-5.3` |
|
||||
| GLM-5.3 (recommended) | OpenRouter | `openrouter/z-ai/glm-5.3` |
|
||||
| GPT-6.1 Sol | OpenAI | `openai/gpt-6.1-sol` |
|
||||
| Claude Opus 5.5 | Anthropic | `anthropic/claude-opus-5-5` |
|
||||
| Claude Sonnet 5.5 | Anthropic | `anthropic/claude-sonnet-5-5` |
|
||||
| Gemini 4 Argon | Google Vertex | `vertex_ai/gemini-4-argon` |
|
||||
| DeepSeek V4.1 Flash | DeepSeek | `deepseek/deepseek-flash` |
|
||||
| DeepSeek V4 Pro | DeepSeek | `deepseek/deepseek-v4-pro` |
|
||||
| Kimi K3.1 Pro | Moonshot | `moonshot/kimi-k3.1-pro` |
|
||||
| Model | Provider | Configuration |
|
||||
| -------------------- | ----------------- | -------------------------------- |
|
||||
| GLM-5.3 (default) | Z.ai (OpenRouter) | `openrouter/z-ai/glm-5.3` |
|
||||
| GPT-5.4 | OpenAI | `openai/gpt-5.4` |
|
||||
| Claude Sonnet 4.6 | Anthropic | `anthropic/claude-sonnet-4-6` |
|
||||
| Gemini 3 Pro | Google Vertex | `vertex_ai/gemini-3-pro-preview` |
|
||||
| DeepSeek V4 Pro | DeepSeek | `deepseek/deepseek-v4-pro` |
|
||||
| Kimi K3 | Moonshot | `moonshot/kimi-k3` |
|
||||
|
||||
<Note>
|
||||
Frontier OpenAI, Anthropic and Gemini models need a cyber access program for security testing: [Daybreak](https://openai.com/daybreak/) for OpenAI, the [Cyber Verification Program](https://support.claude.com/en/articles/14604842-cyber-verification-program) for Anthropic, and the [Fairwind Program](https://deepmind.google/fairwind-program/) for Gemini.
|
||||
</Note>
|
||||
|
||||
<CodeGroup>
|
||||
```bash Vercel AI Gateway
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
```
|
||||
|
||||
```bash OpenRouter
|
||||
```bash
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
```
|
||||
</CodeGroup>
|
||||
|
||||
## Local Models
|
||||
|
||||
@@ -61,7 +47,7 @@ See the [Local Models guide](/llm-providers/local) for setup instructions and re
|
||||
Access 100+ models through a single API.
|
||||
</Card>
|
||||
<Card title="Vercel AI Gateway" href="/llm-providers/vercel-ai-gateway">
|
||||
Access 100+ models through one OpenAI-compatible endpoint.
|
||||
Access models from multiple providers through one endpoint.
|
||||
</Card>
|
||||
<Card title="Google Vertex AI" href="/llm-providers/vertex">
|
||||
Gemini 3 models via Google Cloud.
|
||||
@@ -83,9 +69,9 @@ Use LiteLLM's `provider/model-name` format:
|
||||
|
||||
```
|
||||
openrouter/z-ai/glm-5.3
|
||||
openai/gpt-6.1-sol
|
||||
anthropic/claude-sonnet-5-5
|
||||
vertex_ai/gemini-4-argon
|
||||
bedrock/us.anthropic.claude-sonnet-5-5
|
||||
openai/gpt-5.4
|
||||
anthropic/claude-sonnet-4-6
|
||||
vertex_ai/gemini-3-pro-preview
|
||||
bedrock/anthropic.claude-4-5-sonnet-20251022-v1:0
|
||||
ollama/llama4
|
||||
```
|
||||
@@ -1,47 +1,32 @@
|
||||
---
|
||||
title: "Vercel AI Gateway"
|
||||
description: "Configure Strix with models through Vercel AI Gateway"
|
||||
description: "Configure Strix with models via Vercel AI Gateway"
|
||||
---
|
||||
|
||||
[Vercel AI Gateway](https://vercel.com/docs/ai-gateway) provides access to 100+ models from multiple providers through one OpenAI-compatible API.
|
||||
[Vercel AI Gateway](https://vercel.com/docs/ai-gateway) provides an OpenAI-compatible API for models from multiple providers.
|
||||
|
||||
## Setup
|
||||
|
||||
Create an [AI Gateway API key](https://vercel.com/docs/ai-gateway/authentication-and-byok), then configure Strix:
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3"
|
||||
export STRIX_LLM="openai/anthropic/claude-opus-5"
|
||||
export LLM_API_KEY="your-ai-gateway-api-key"
|
||||
export LLM_API_BASE="https://ai-gateway.vercel.sh/v1"
|
||||
```
|
||||
|
||||
The `vercel_ai_gateway/` prefix selects the Gateway. The remaining value is the [AI Gateway model ID](https://vercel.com/docs/ai-gateway/models-and-providers).
|
||||
The first `openai/` segment tells Strix to use its OpenAI-compatible client. The remaining value is the [AI Gateway model ID](https://vercel.com/docs/ai-gateway/models-and-providers).
|
||||
|
||||
## Available Models
|
||||
|
||||
Access any model on the Gateway using the format `vercel_ai_gateway/<provider>/<model>`:
|
||||
|
||||
| Model | Configuration |
|
||||
|-------|---------------|
|
||||
| GLM-5.3 (recommended) | `vercel_ai_gateway/zai/glm-5.3` |
|
||||
| GPT-6.1 Sol | `vercel_ai_gateway/openai/gpt-6.1-sol` |
|
||||
| GPT-6 Astra | `vercel_ai_gateway/openai/gpt-6-astra` |
|
||||
| Claude Opus 5.5 | `vercel_ai_gateway/anthropic/claude-opus-5.5` |
|
||||
| Claude Sonnet 5.5 | `vercel_ai_gateway/anthropic/claude-sonnet-5.5` |
|
||||
| Gemini 4 Argon | `vercel_ai_gateway/google/gemini-4-argon` |
|
||||
| Gemini 3.8 Flash | `vercel_ai_gateway/google/gemini-3.8-flash` |
|
||||
| DeepSeek V4.1 Flash | `vercel_ai_gateway/deepseek/deepseek-v4.1-flash-1017` |
|
||||
| DeepSeek V4 Pro | `vercel_ai_gateway/deepseek/deepseek-v4-pro` |
|
||||
| Kimi K3.1 Pro | `vercel_ai_gateway/moonshotai/kimi-k3.1-pro` |
|
||||
| GLM-5.3 Flash | `vercel_ai_gateway/zai/glm-5.3-flash` |
|
||||
|
||||
OpenAI, Anthropic and Gemini models keep their provider safeguards on the Gateway. Security testing with them needs [Daybreak](https://openai.com/daybreak/), [CVP](https://support.claude.com/en/articles/14604842-cyber-verification-program) or [Fairwind](https://deepmind.google/fairwind-program/) access.
|
||||
|
||||
The full list is at the [AI Gateway models page](https://vercel.com/ai-gateway/models) or the models endpoint:
|
||||
Use any language model returned by the AI Gateway models endpoint:
|
||||
|
||||
```text
|
||||
https://ai-gateway.vercel.sh/v1/models
|
||||
```
|
||||
|
||||
Prefix its model ID with `openai/` when setting `STRIX_LLM`. For example, the Gateway model ID `anthropic/claude-opus-5` becomes `openai/anthropic/claude-opus-5` in Strix.
|
||||
|
||||
## Get API Key
|
||||
|
||||
1. Open the [AI Gateway API key settings](https://vercel.com/docs/ai-gateway/authentication-and-byok)
|
||||
@@ -50,6 +35,5 @@ https://ai-gateway.vercel.sh/v1/models
|
||||
|
||||
## Benefits
|
||||
|
||||
- **Single API** — Access models from OpenAI, Anthropic, Google, Z.ai, and more
|
||||
- **Bring your own keys** — Route through your own provider accounts when you want
|
||||
- **Cost tracking** — Monitor Gateway usage and cost in Vercel
|
||||
- Access models from multiple providers through one endpoint
|
||||
- Track Gateway usage and cost in Vercel
|
||||
@@ -6,7 +6,7 @@ description: "Configure Strix with Gemini models via Google Cloud"
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
export STRIX_LLM="vertex_ai/gemini-4-argon"
|
||||
export STRIX_LLM="vertex_ai/gemini-3-pro-preview"
|
||||
```
|
||||
|
||||
No API key required—uses Google Cloud Application Default Credentials.
|
||||
@@ -29,12 +29,8 @@ export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"
|
||||
|
||||
| Model | Description |
|
||||
|-------|-------------|
|
||||
| `vertex_ai/gemini-4-argon` | Best overall performance for security testing |
|
||||
| `vertex_ai/gemini-3.8-flash` | Faster and cheaper |
|
||||
|
||||
<Note>
|
||||
Security testing with Gemini needs the [Fairwind Program](https://deepmind.google/fairwind-program/). Without it the cyber guardrails block most offensive tasks.
|
||||
</Note>
|
||||
| `vertex_ai/gemini-3-pro-preview` | Best overall performance for security testing |
|
||||
| `vertex_ai/gemini-3-flash-preview` | Faster and cheaper |
|
||||
|
||||
## Project Configuration
|
||||
|
||||
|
||||
+3
-10
@@ -25,22 +25,15 @@ description: "Install Strix and run your first security scan"
|
||||
|
||||
## Configuration
|
||||
|
||||
Set your LLM provider. We recommend GLM-5.3 through [Vercel AI Gateway](/llm-providers/vercel-ai-gateway) or [OpenRouter](/llm-providers/openrouter):
|
||||
Set your LLM provider:
|
||||
|
||||
<CodeGroup>
|
||||
```bash Vercel AI Gateway
|
||||
export STRIX_LLM="vercel_ai_gateway/zai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
```
|
||||
|
||||
```bash OpenRouter
|
||||
```bash
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3"
|
||||
export LLM_API_KEY="your-api-key"
|
||||
```
|
||||
</CodeGroup>
|
||||
|
||||
<Tip>
|
||||
For best results, use `zai/glm-5.3`, `deepseek/deepseek-v4.1-flash-1017`, `anthropic/claude-opus-5-5` (needs [CVP](https://support.claude.com/en/articles/14604842-cyber-verification-program) access), or `openai/gpt-6.1-sol` (needs [Daybreak](https://openai.com/daybreak/) access).
|
||||
For best results, use `openrouter/z-ai/glm-5.3` (the default pick), `openai/gpt-5.4`, `anthropic/claude-opus-4-6`, or `openai/gpt-5.2`.
|
||||
</Tip>
|
||||
|
||||
## Run Your First Scan
|
||||
|
||||
@@ -63,7 +63,7 @@ jobs:
|
||||
fi
|
||||
```
|
||||
|
||||
Then tell the user to add two repository secrets: `STRIX_LLM` (model id, for example `openrouter/z-ai/glm-5.3`) and `LLM_API_KEY` (the provider key). Do not create these values yourself.
|
||||
Then tell the user to add two repository secrets: `STRIX_LLM` (model id, for example `openai/gpt-5.4`) and `LLM_API_KEY` (the provider key). Do not create these values yourself.
|
||||
|
||||
Notes:
|
||||
- In CI/headless runs Strix automatically scopes to the PR's changed files (`--scope-mode auto`). If diff resolution fails, keep `fetch-depth: 0` or set `--diff-base` to the PR's actual base branch — use `origin/${{ github.base_ref }}` in GitHub Actions rather than a hard-coded `origin/main`, since repos use different default branches.
|
||||
|
||||
@@ -47,7 +47,7 @@ If unsure and the user has (or will create) an app.strix.ai account, prefer **Cl
|
||||
```
|
||||
3. **LLM configured** — two environment variables:
|
||||
```bash
|
||||
export STRIX_LLM="openrouter/z-ai/glm-5.3" # any LiteLLM model id (openai/..., anthropic/..., openrouter/...)
|
||||
export STRIX_LLM="openai/gpt-5.4" # any LiteLLM model id (openai/..., anthropic/..., openrouter/...)
|
||||
export LLM_API_KEY="<provider api key>"
|
||||
```
|
||||
Ask the user for these if unset. Never hardcode or commit keys.
|
||||
|
||||
@@ -620,15 +620,6 @@ def _finish_tool_use_behavior(
|
||||
|
||||
|
||||
_COVERAGE_TOOLS: tuple[Tool, ...] = (record_coverage, update_coverage, list_coverage)
|
||||
_FINISH_SCAN_COVERAGE_STEP = re.compile(
|
||||
r"\n5\. \*\*Coverage reconciliation\.\*\*.*?(?=\n\n)", re.DOTALL
|
||||
)
|
||||
|
||||
|
||||
def _without_coverage_step(tool: FunctionTool) -> FunctionTool:
|
||||
description = _FINISH_SCAN_COVERAGE_STEP.sub("", tool.description)
|
||||
return dataclasses.replace(tool, description=description)
|
||||
|
||||
|
||||
_BASE_TOOLS: tuple[Tool, ...] = (
|
||||
think,
|
||||
@@ -728,7 +719,6 @@ def build_strix_agent(
|
||||
is_whitebox: bool = False,
|
||||
is_diff_scoped: bool = False,
|
||||
interactive: bool = False,
|
||||
parallel_tool_calls: bool = False,
|
||||
chat_completions_tools: bool = False,
|
||||
strict_tool_schemas: bool = True,
|
||||
system_prompt_context: dict[str, Any] | None = None,
|
||||
@@ -766,7 +756,6 @@ def build_strix_agent(
|
||||
is_root=is_root,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=parallel_tool_calls,
|
||||
system_prompt_context=system_prompt_context,
|
||||
supports_images=supports_images,
|
||||
report_tool=report_tool.name,
|
||||
@@ -780,8 +769,6 @@ def build_strix_agent(
|
||||
base_tools = [report_tool if t is create_vulnerability_report else t for t in _BASE_TOOLS]
|
||||
if not coverage_tools:
|
||||
base_tools = [t for t in base_tools if t not in _COVERAGE_TOOLS]
|
||||
if finish_tool is finish_scan:
|
||||
finish_tool = _without_coverage_step(finish_scan)
|
||||
if is_root:
|
||||
tools: list[Tool] = [*base_tools, *agent_tools, finish_tool]
|
||||
else:
|
||||
@@ -834,7 +821,6 @@ def make_child_factory(
|
||||
is_whitebox: bool = False,
|
||||
is_diff_scoped: bool = False,
|
||||
interactive: bool = False,
|
||||
parallel_tool_calls: bool = False,
|
||||
chat_completions_tools: bool = False,
|
||||
strict_tool_schemas: bool = True,
|
||||
system_prompt_context: dict[str, Any] | None = None,
|
||||
@@ -858,7 +844,6 @@ def make_child_factory(
|
||||
is_whitebox=is_whitebox,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=parallel_tool_calls,
|
||||
chat_completions_tools=chat_completions_tools,
|
||||
strict_tool_schemas=strict_tool_schemas,
|
||||
system_prompt_context=system_prompt_context,
|
||||
|
||||
@@ -83,7 +83,6 @@ def render_system_prompt(
|
||||
is_root: bool = False,
|
||||
is_diff_scoped: bool = False,
|
||||
interactive: bool = False,
|
||||
parallel_tool_calls: bool = False,
|
||||
system_prompt_context: dict[str, Any] | None = None,
|
||||
include_scope: bool = True,
|
||||
supports_images: bool = True,
|
||||
@@ -135,7 +134,6 @@ def render_system_prompt(
|
||||
requested_skill_names=[name for name in skill_content if name not in shared],
|
||||
available_skills=get_available_skills(),
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=parallel_tool_calls,
|
||||
is_root=is_root,
|
||||
system_prompt_context=system_prompt_context or {},
|
||||
include_scope=include_scope,
|
||||
|
||||
@@ -44,11 +44,7 @@ INTERACTIVE BEHAVIOR:
|
||||
- If you end a turn on plain text and the nudge arrives, your words already reached the user. Do not repeat them: call wait_for_user.
|
||||
- You can narrate while you work — plain text is shown to the user as you go. Narrating is free; wait_for_user is specifically the act of WAITING for the user, so do not call it just to give a status update.
|
||||
- Respond naturally when the user asks questions or gives instructions.
|
||||
{%- if parallel_tool_calls %}
|
||||
- While actively working on a task, every turn should carry a tool call (independent calls can go in the same turn) — use think to plan, the appropriate tool to act, and wait_for_user only when you genuinely need the user.
|
||||
{%- else %}
|
||||
- While actively working on a task, every turn should carry exactly one tool call — use think to plan, the appropriate tool to act, and wait_for_user only when you genuinely need the user.
|
||||
{%- endif %}
|
||||
- Never loop through think or other tools just to prepare, polish, confirm, or announce an answer. Once you know the answer, write it and call wait_for_user.
|
||||
{% else %}
|
||||
AUTONOMOUS BEHAVIOR:
|
||||
@@ -59,9 +55,6 @@ AUTONOMOUS BEHAVIOR:
|
||||
- There is no user attached to this run, so there is nobody to ask and nothing to yield to. If there is nothing left to execute: do NOT send filler/repetitive text — either call wait_for_agents (only if you are genuinely expecting another agent to message you) or finish your work (subagents: agent_finish; root: finish_scan)
|
||||
- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If waiting on another agent, use wait_for_agents; when done, use agent_finish (subagents) or finish_scan (root)
|
||||
- A text-only turn does nothing: it neither ends the run nor yields — it just wastes a turn and forces a retry. The lifecycle tools (``finish_scan`` for root, ``agent_finish`` for subagents) are the ONLY way to terminate, and the report flows through them. If you find yourself wanting to say "Done!" or "Scan complete" without a tool call, call the lifecycle tool instead.
|
||||
{%- if parallel_tool_calls %}
|
||||
- Read-only calls can go together in one turn: when several file reads or searches don't depend on each other's output, issue them as separate tool calls in the same turn rather than one per turn. Anything else — writing files, running commands that change state, sending requests, creating or messaging agents, reporting, or finishing — goes alone in its own turn.
|
||||
{%- endif %}
|
||||
{% endif %}
|
||||
</communication_rules>
|
||||
|
||||
|
||||
@@ -65,10 +65,6 @@ class LlmSettings(BaseSettings):
|
||||
default=False,
|
||||
alias="STRIX_FORCE_REQUIRED_TOOL_CHOICE",
|
||||
)
|
||||
parallel_tool_calls: bool = Field(
|
||||
default=False,
|
||||
alias="STRIX_PARALLEL_TOOL_CALLS",
|
||||
)
|
||||
prompt_cache: bool = Field(
|
||||
default=True,
|
||||
alias="STRIX_PROMPT_CACHE",
|
||||
|
||||
@@ -1009,7 +1009,7 @@ async def _append_tool_required_message(
|
||||
message = (
|
||||
"Your previous message ended a turn without a tool call. Plain text never ends "
|
||||
"execution and never hands control to the user: it is shown to the user, and the "
|
||||
"run continues. Continue immediately and call a tool. "
|
||||
"run continues. Continue immediately and call exactly one tool. "
|
||||
"If you have nothing to do until the user replies, call wait_for_user; your "
|
||||
"text already reached them, so do not repeat it. "
|
||||
"If you are blocked waiting for another agent, call wait_for_agents. "
|
||||
@@ -1021,7 +1021,7 @@ async def _append_tool_required_message(
|
||||
message = (
|
||||
"Your previous response ended the autonomous run without a lifecycle tool "
|
||||
"call. That is invalid in non-interactive mode; plain text final answers are "
|
||||
"ignored. Continue immediately and call a tool. "
|
||||
"ignored. Continue immediately and call exactly one tool. "
|
||||
f"If your work is complete, call {finish_tool}. "
|
||||
"If you are blocked waiting for another agent, call wait_for_agents. "
|
||||
"Otherwise use the appropriate execution or planning tool. "
|
||||
|
||||
@@ -247,7 +247,6 @@ def make_model_settings(
|
||||
*,
|
||||
model_name: str,
|
||||
force_required_tool_choice: bool = False,
|
||||
parallel_tool_calls: bool = False,
|
||||
request_timeout: float | None = None,
|
||||
prompt_cache: bool = True,
|
||||
extra_headers: dict[str, str] | None = None,
|
||||
@@ -256,7 +255,7 @@ def make_model_settings(
|
||||
) -> ModelSettings:
|
||||
headers = _request_headers(model_name, extra_headers)
|
||||
model_settings = ModelSettings(
|
||||
parallel_tool_calls=parallel_tool_calls if has_tools else None,
|
||||
parallel_tool_calls=False if has_tools else None,
|
||||
retry=DEFAULT_MODEL_RETRY,
|
||||
include_usage=True,
|
||||
extra_args=request_timeout_extra_args(request_timeout),
|
||||
|
||||
@@ -176,17 +176,13 @@ def _compose_root_instructions_override(
|
||||
is_whitebox: bool,
|
||||
is_diff_scoped: bool,
|
||||
interactive: bool,
|
||||
parallel_tool_calls: bool,
|
||||
system_prompt_context: dict[str, Any],
|
||||
supports_images: bool,
|
||||
report_tool: str,
|
||||
coverage_tools: bool,
|
||||
replace_scan_prompt: bool = False,
|
||||
) -> str | None:
|
||||
if root_instructions_override is None:
|
||||
return None
|
||||
if replace_scan_prompt:
|
||||
return f"{root_instructions_override}\n\n{render_scope_prompt(system_prompt_context)}"
|
||||
|
||||
base_instructions = render_system_prompt(
|
||||
skills=skills,
|
||||
@@ -195,7 +191,6 @@ def _compose_root_instructions_override(
|
||||
is_root=True,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=parallel_tool_calls,
|
||||
system_prompt_context=system_prompt_context,
|
||||
include_scope=False,
|
||||
supports_images=supports_images,
|
||||
@@ -228,7 +223,6 @@ async def run_strix_scan(
|
||||
cleanup_on_exit: bool = True,
|
||||
event_sink: StreamEventSink | None = None,
|
||||
root_instructions_override: str | None = None,
|
||||
replace_root_scan_prompt: bool = False,
|
||||
extra_system_prompt_context: dict[str, Any] | None = None,
|
||||
status_sink: StatusSink | None = None,
|
||||
mcp_connection_requests: list[McpConnectionRequest] | None = None,
|
||||
@@ -242,8 +236,6 @@ async def run_strix_scan(
|
||||
|
||||
``root_instructions_override`` adds root scan instructions to the rendered
|
||||
root prompt without replacing the system-verified scope block.
|
||||
``replace_root_scan_prompt=True`` makes it the root's whole prompt, followed
|
||||
by the scope, instead of adding it to the rendered scan prompt.
|
||||
``extra_files`` entries (``{"workspace_path", "content"}``) are placed into
|
||||
the sandbox workspace at session bring-up; see
|
||||
:func:`strix.runtime.session_manager.create_or_reuse`.
|
||||
@@ -426,7 +418,6 @@ async def run_strix_scan(
|
||||
settings.llm.reasoning_effort,
|
||||
model_name=resolved_model,
|
||||
force_required_tool_choice=settings.llm.force_required_tool_choice,
|
||||
parallel_tool_calls=settings.llm.parallel_tool_calls,
|
||||
request_timeout=settings.llm.timeout,
|
||||
prompt_cache=settings.llm.prompt_cache,
|
||||
extra_headers=settings.llm.extra_headers,
|
||||
@@ -522,12 +513,10 @@ async def run_strix_scan(
|
||||
is_whitebox=is_whitebox,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=settings.llm.parallel_tool_calls,
|
||||
system_prompt_context=root_context,
|
||||
supports_images=supports_images,
|
||||
report_tool=report_tool.name,
|
||||
coverage_tools=coverage_tools,
|
||||
replace_scan_prompt=replace_root_scan_prompt,
|
||||
)
|
||||
|
||||
root_agent = build_strix_agent(
|
||||
@@ -538,7 +527,6 @@ async def run_strix_scan(
|
||||
is_whitebox=is_whitebox,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=settings.llm.parallel_tool_calls,
|
||||
chat_completions_tools=chat_completions_tools,
|
||||
strict_tool_schemas=strict_tool_schemas,
|
||||
system_prompt_context=root_context,
|
||||
@@ -563,7 +551,6 @@ async def run_strix_scan(
|
||||
is_whitebox=is_whitebox,
|
||||
is_diff_scoped=is_diff_scoped,
|
||||
interactive=interactive,
|
||||
parallel_tool_calls=settings.llm.parallel_tool_calls,
|
||||
chat_completions_tools=chat_completions_tools,
|
||||
strict_tool_schemas=strict_tool_schemas,
|
||||
system_prompt_context=scope_context,
|
||||
|
||||
@@ -66,33 +66,6 @@ def _apply_sandbox_network(create_kwargs: dict[str, Any]) -> None:
|
||||
create_kwargs.pop("ports", None)
|
||||
|
||||
|
||||
_SANDBOX_DEVICES_ENV = "STRIX_DOCKER_SANDBOX_DEVICES"
|
||||
|
||||
|
||||
def _sandbox_devices() -> list[str]:
|
||||
raw = os.environ.get(_SANDBOX_DEVICES_ENV, "")
|
||||
return [item.strip() for item in raw.split(",") if item.strip()]
|
||||
|
||||
|
||||
def _apply_sandbox_devices(create_kwargs: dict[str, Any]) -> None:
|
||||
"""Pass the host devices listed in ``STRIX_DOCKER_SANDBOX_DEVICES`` through.
|
||||
|
||||
Comma-separated device paths, each mapped to the same path in the container
|
||||
with ``rwm`` access. A tunnel brought up inside the sandbox (OpenVPN,
|
||||
Tailscale) needs ``/dev/net/tun``: Docker's default device cgroup denies it
|
||||
even with ``NET_ADMIN``. Unset means no extra devices.
|
||||
"""
|
||||
devices = _sandbox_devices()
|
||||
if not devices:
|
||||
return
|
||||
existing = [str(item) for item in (create_kwargs.get("devices") or [])]
|
||||
for path in devices:
|
||||
spec = f"{path}:{path}:rwm"
|
||||
if spec not in existing and path not in existing:
|
||||
existing.append(spec)
|
||||
create_kwargs["devices"] = existing
|
||||
|
||||
|
||||
def _apply_resource_limits(create_kwargs: dict[str, Any]) -> None:
|
||||
"""Apply optional cgroup resource caps from the environment. Unset/blank
|
||||
values leave docker's default (unbounded), so this is opt-in per host."""
|
||||
@@ -260,7 +233,6 @@ class StrixDockerSandboxClient(DockerSandboxClient):
|
||||
extra_hosts["host.docker.internal"] = "host-gateway"
|
||||
|
||||
_apply_sandbox_network(create_kwargs)
|
||||
_apply_sandbox_devices(create_kwargs)
|
||||
_apply_resource_limits(create_kwargs)
|
||||
_apply_log_limits(create_kwargs)
|
||||
_apply_run_labels(create_kwargs)
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
---
|
||||
name: diff
|
||||
description: Methodology for diff-scoped review of a pull request, commit, or branch — what counts as in scope, how far to follow a change, and what not to report
|
||||
template: jinja
|
||||
---
|
||||
|
||||
# Diff-Scoped Review
|
||||
@@ -70,14 +69,9 @@ When it is not, the closure rules apply unchanged: a complete
|
||||
source → control → sink → impact trace through the changed code is
|
||||
reportable at reduced confidence, with the missing runtime proof named in
|
||||
`confidence_rationale`. A candidate you can neither confirm nor rule out
|
||||
{% if coverage_tools %}
|
||||
with a named control is an `open_proof_gap` — record it as
|
||||
`needs_follow_up` coverage rather than dropping it because the
|
||||
environment was inconvenient.
|
||||
{% else %}
|
||||
with a named control is an `open_proof_gap` — carry it up as an open
|
||||
item rather than dropping it because the environment was inconvenient.
|
||||
{% endif %}
|
||||
|
||||
## Reporting
|
||||
|
||||
@@ -86,9 +80,7 @@ plainly which part of the diff introduced or exposed it. A reviewer
|
||||
reading your report next to the diff should be able to see the connection
|
||||
without re-deriving your analysis.
|
||||
|
||||
{% if coverage_tools %}
|
||||
Record coverage per changed component, not per changed file — a
|
||||
formatting-only file and a rewritten auth module are not equal rows.
|
||||
{% endif %}
|
||||
State which changed areas you reviewed and cleared, so the author knows
|
||||
what a clean result actually covered.
|
||||
@@ -104,10 +104,6 @@ def test_report_tool_replaces_create_vulnerability_report() -> None:
|
||||
assert "create_vulnerability_report" not in agent.instructions
|
||||
|
||||
|
||||
def _descriptions(tools: list[Any]) -> list[str]:
|
||||
return [t.description for t in tools if isinstance(t, FunctionTool)]
|
||||
|
||||
|
||||
def test_coverage_tools_can_be_turned_off() -> None:
|
||||
coverage = {"record_coverage", "update_coverage", "list_coverage"}
|
||||
for is_root in (True, False):
|
||||
@@ -120,22 +116,6 @@ def test_coverage_tools_can_be_turned_off() -> None:
|
||||
assert "- COVERAGE" in on.instructions
|
||||
assert "## Recording Closure" in on.instructions
|
||||
assert not any(name in off.instructions for name in coverage)
|
||||
on_descriptions = "\n".join(_descriptions(on.tools))
|
||||
off_descriptions = "\n".join(_descriptions(off.tools))
|
||||
if is_root:
|
||||
assert "Coverage reconciliation" in on_descriptions
|
||||
assert "Coverage reconciliation" not in off_descriptions
|
||||
assert not any(name in off_descriptions for name in coverage)
|
||||
|
||||
diff_on = factory.build_strix_agent(is_root=True, is_diff_scoped=True)
|
||||
diff_off = factory.build_strix_agent(is_root=True, is_diff_scoped=True, coverage_tools=False)
|
||||
assert isinstance(diff_on.instructions, str)
|
||||
assert isinstance(diff_off.instructions, str)
|
||||
assert "Record coverage per changed component" in diff_on.instructions
|
||||
assert "`needs_follow_up` coverage" in diff_on.instructions
|
||||
assert "Record coverage per changed component" not in diff_off.instructions
|
||||
assert "`needs_follow_up` coverage" not in diff_off.instructions
|
||||
assert not any(name in diff_off.instructions for name in coverage)
|
||||
|
||||
|
||||
def test_instructions_override_is_used_verbatim() -> None:
|
||||
|
||||
@@ -1,32 +0,0 @@
|
||||
"""``STRIX_DOCKER_SANDBOX_DEVICES`` passes host devices through to the sandbox container."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from strix.runtime import docker_client
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
import pytest
|
||||
|
||||
|
||||
def test_unset_adds_no_devices(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
monkeypatch.delenv(docker_client._SANDBOX_DEVICES_ENV, raising=False)
|
||||
kwargs: dict[str, object] = {}
|
||||
docker_client._apply_sandbox_devices(kwargs)
|
||||
assert kwargs == {}
|
||||
|
||||
|
||||
def test_devices_are_mapped_to_the_same_path_rwm(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
monkeypatch.setenv(docker_client._SANDBOX_DEVICES_ENV, " /dev/net/tun, /dev/kvm ,,")
|
||||
kwargs: dict[str, object] = {}
|
||||
docker_client._apply_sandbox_devices(kwargs)
|
||||
assert kwargs["devices"] == ["/dev/net/tun:/dev/net/tun:rwm", "/dev/kvm:/dev/kvm:rwm"]
|
||||
|
||||
|
||||
def test_existing_devices_are_kept_and_not_duplicated(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
monkeypatch.setenv(docker_client._SANDBOX_DEVICES_ENV, "/dev/fuse,/dev/net/tun")
|
||||
kwargs: dict[str, object] = {"devices": ["/dev/fuse"]}
|
||||
docker_client._apply_sandbox_devices(kwargs)
|
||||
assert kwargs["devices"] == ["/dev/fuse", "/dev/net/tun:/dev/net/tun:rwm"]
|
||||
@@ -314,12 +314,6 @@ def test_make_model_settings_disables_parallel_tool_calls_by_default() -> None:
|
||||
assert make_model_settings("none", model_name="gpt-4o").parallel_tool_calls is False
|
||||
|
||||
|
||||
def test_make_model_settings_enables_parallel_tool_calls_when_requested() -> None:
|
||||
settings = make_model_settings("none", model_name="gpt-4o", parallel_tool_calls=True)
|
||||
|
||||
assert settings.parallel_tool_calls is True
|
||||
|
||||
|
||||
def test_make_model_settings_omits_parallel_tool_calls_without_tools() -> None:
|
||||
settings = make_model_settings("none", model_name="gpt-4o", has_tools=False)
|
||||
|
||||
|
||||
@@ -25,7 +25,6 @@ def _wire_runner(monkeypatch: pytest.MonkeyPatch, tmp_path: Any) -> None:
|
||||
model="openai/gpt-4o",
|
||||
reasoning_effort="high",
|
||||
force_required_tool_choice=False,
|
||||
parallel_tool_calls=False,
|
||||
timeout=300,
|
||||
prompt_cache=True,
|
||||
extra_headers=None,
|
||||
|
||||
@@ -41,7 +41,6 @@ def _settings() -> Any:
|
||||
model="openai/gpt-4o",
|
||||
reasoning_effort="high",
|
||||
force_required_tool_choice=False,
|
||||
parallel_tool_calls=False,
|
||||
timeout=300,
|
||||
prompt_cache=True,
|
||||
extra_headers=None,
|
||||
|
||||
@@ -39,7 +39,6 @@ async def test_persistent_rate_limit_stops_gracefully(
|
||||
model="openai/gpt-4o",
|
||||
reasoning_effort="high",
|
||||
force_required_tool_choice=False,
|
||||
parallel_tool_calls=False,
|
||||
timeout=300,
|
||||
prompt_cache=True,
|
||||
extra_headers=None,
|
||||
|
||||
@@ -61,14 +61,12 @@ def _patch_engine_scaffold(
|
||||
model="openai/gpt-4o",
|
||||
reasoning_effort="high",
|
||||
force_required_tool_choice=False,
|
||||
parallel_tool_calls=False,
|
||||
timeout=300,
|
||||
prompt_cache=True,
|
||||
extra_headers=None,
|
||||
extra_body=None,
|
||||
),
|
||||
runtime=types.SimpleNamespace(max_context_images=3),
|
||||
telemetry=types.SimpleNamespace(run_record_timings=False),
|
||||
)
|
||||
monkeypatch.setattr(runner, "load_settings", lambda: settings)
|
||||
monkeypatch.setattr(runner, "configure_sdk_model_defaults", lambda _settings: None)
|
||||
@@ -162,36 +160,6 @@ async def test_root_prompt_options_flow_into_root_agent(
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_replace_root_scan_prompt_drops_the_scan_prompt(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
tmp_path: Any,
|
||||
) -> None:
|
||||
scope_context = {
|
||||
"scope_source": "user_scan_config",
|
||||
"authorized_targets": [
|
||||
{"type": "web_application", "value": "https://example.com", "workspace_path": ""},
|
||||
],
|
||||
}
|
||||
captured = _patch_engine_scaffold(monkeypatch, tmp_path, scope_context)
|
||||
|
||||
await runner.run_strix_scan(
|
||||
scan_config={"targets": [], "scan_mode": "deep"},
|
||||
scan_id="scan-replace",
|
||||
image="img",
|
||||
coordinator=AgentCoordinator(),
|
||||
root_instructions_override="CUSTOM SCAN PROMPT",
|
||||
replace_root_scan_prompt=True,
|
||||
)
|
||||
|
||||
instructions_override = captured["kwargs"]["instructions_override"]
|
||||
assert instructions_override.startswith("CUSTOM SCAN PROMPT")
|
||||
assert instructions_override.count("SCOPE:") == 1
|
||||
assert "https://example.com" in instructions_override
|
||||
assert "<root_scan_instructions_override>" not in instructions_override
|
||||
assert "application security validation agent" not in instructions_override
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extra_system_prompt_context_cannot_override_scope_context(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
@@ -317,19 +285,6 @@ async def test_unknown_tool_calls_are_returned_to_the_model(
|
||||
assert captured["run_config"].tool_not_found_behavior == "return_error_to_model"
|
||||
|
||||
|
||||
@pytest.mark.parametrize("interactive", [False, True])
|
||||
def test_parallel_tool_calls_prompt_is_opt_in(interactive: bool) -> None:
|
||||
default = render_system_prompt(include_scope=False, interactive=interactive)
|
||||
parallel = render_system_prompt(
|
||||
include_scope=False, interactive=interactive, parallel_tool_calls=True
|
||||
)
|
||||
|
||||
assert "Read-only calls can go together" not in default
|
||||
assert ("Read-only calls can go together" in parallel) is not interactive
|
||||
assert ("exactly one tool call" in default) is interactive
|
||||
assert "exactly one tool call" not in parallel
|
||||
|
||||
|
||||
def test_scope_is_rendered_once_at_the_end_of_the_prompt() -> None:
|
||||
prompt = render_system_prompt(
|
||||
system_prompt_context={
|
||||
|
||||
@@ -49,7 +49,6 @@ def _settings() -> Any:
|
||||
model="openai/gpt-4o",
|
||||
reasoning_effort="high",
|
||||
force_required_tool_choice=False,
|
||||
parallel_tool_calls=False,
|
||||
timeout=300,
|
||||
prompt_cache=True,
|
||||
extra_headers=None,
|
||||
|
||||
Reference in new issue
Block a user