Strix LLM Documentation and Config Changes (#315)

* feat: add to readme new keys * feat: shoutout strix models, docs * fix: mypy error * fix: base api * docs: update quickstart and models * fixes: changes to docs uniform api_key variable naming * test: git commit hook * nevermind it was nothing * docs: Update default model to claude-sonnet-4.6 and improve Strix Router docs - Replace gpt-5 and opus-4.6 defaults with claude-sonnet-4.6 across all docs and code - Rewrite Strix Router (models.mdx) page with clearer structure and messaging - Add Strix Router as recommended option in overview.mdx and quickstart prerequisites - Update stale Claude 4.5 references to 4.6 in anthropic.mdx, openrouter.mdx, bug_report.md - Fix install.sh links to point to models.strix.ai and correct docs URLs - Update error message examples in main.py to use claude-sonnet-4-6 --------- Co-authored-by: 0xallam <ahmed39652003@gmail.com>
2026-02-19 13:43:18 -08:00
parent 30550dd189
commit e38f523a45
19 changed files with 208 additions and 74 deletions
--- a/.github/ISSUE_TEMPLATE/bug_report.md
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -27,7 +27,7 @@ If applicable, add screenshots to help explain your problem.
 - OS: [e.g. Ubuntu 22.04]
 - Strix Version or Commit: [e.g. 0.1.18]
 - Python Version: [e.g. 3.12]
- LLM Used: [e.g. GPT-5, Claude Sonnet 4]
+- LLM Used: [e.g. GPT-5, Claude Sonnet 4.6]

 **Additional context**
 Add any other context about the problem here.
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -30,7 +30,7 @@ Thank you for your interest in contributing to Strix! This guide will help you g

 3. **Configure your LLM provider**
   ```bash
-   export STRIX_LLM="openai/gpt-5"
+   export STRIX_LLM="anthropic/claude-sonnet-4-6"
   export LLM_API_KEY="your-api-key"
   ```

--- a/README.md
+++ b/README.md
@@ -72,7 +72,9 @@ Strix are autonomous AI agents that act just like real hackers - they run your c

 **Prerequisites:**
 - Docker (running)
- An LLM provider key (e.g. [get OpenAI API key](https://platform.openai.com/api-keys) or use a local LLM)
+- An LLM API key:
+  - Any [supported provider](https://docs.strix.ai/llm-providers/overview) (OpenAI, Anthropic, Google, etc.)
+  - Or [Strix Router](https://models.strix.ai) — single API key for multiple providers with $10 free credit on signup

 ### Installation & First Scan

@@ -84,7 +86,7 @@ curl -sSL https://strix.ai/install | bash
 pipx install strix-agent

 # Configure your AI provider
-export STRIX_LLM="openai/gpt-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"  # or "strix/claude-sonnet-4.6" via Strix Router (https://models.strix.ai)
 export LLM_API_KEY="your-api-key"

 # Run your first security assessment
@@ -201,7 +203,7 @@ jobs:
 ### Configuration

 ```bash
-export STRIX_LLM="openai/gpt-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"
 export LLM_API_KEY="your-api-key"

 # Optional
@@ -215,8 +217,8 @@ export STRIX_REASONING_EFFORT="high"  # control thinking effort (default: high,

 **Recommended models for best results:**

+- [Anthropic Claude Sonnet 4.6](https://claude.com/platform/api) — `anthropic/claude-sonnet-4-6`
 - [OpenAI GPT-5](https://openai.com/api/) — `openai/gpt-5`
- [Anthropic Claude Sonnet 4.5](https://claude.com/platform/api) — `anthropic/claude-sonnet-4-5`
 - [Google Gemini 3 Pro Preview](https://cloud.google.com/vertex-ai) — `vertex_ai/gemini-3-pro-preview`

 See the [LLM Providers documentation](https://docs.strix.ai/llm-providers/overview) for all supported providers including Vertex AI, Bedrock, Azure, and local models.
--- a/docs/advanced/configuration.mdx
+++ b/docs/advanced/configuration.mdx
@@ -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., `openai/gpt-5`, `anthropic/claude-sonnet-4-5`).
+  Model name in LiteLLM format (e.g., `anthropic/claude-sonnet-4-6`, `openai/gpt-5`).
 </ParamField>

 <ParamField path="LLM_API_KEY" type="string">
@@ -86,7 +86,7 @@ strix --target ./app --config /path/to/config.json
 ```json
 {
  "env": {
-    "STRIX_LLM": "openai/gpt-5",
+    "STRIX_LLM": "anthropic/claude-sonnet-4-6",
    "LLM_API_KEY": "sk-...",
    "STRIX_REASONING_EFFORT": "high"
  }
@@ -97,7 +97,7 @@ strix --target ./app --config /path/to/config.json

 ```bash
 # Required
-export STRIX_LLM="openai/gpt-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"
 export LLM_API_KEY="sk-..."

 # Optional: Enable web search
--- a/docs/contributing.mdx
+++ b/docs/contributing.mdx
@@ -32,7 +32,7 @@ description: "Contribute to Strix development"
  </Step>
  <Step title="Configure LLM">
    ```bash
-    export STRIX_LLM="openai/gpt-5"
+    export STRIX_LLM="anthropic/claude-sonnet-4-6"
    export LLM_API_KEY="your-api-key"
    ```
  </Step>
--- a/docs/index.mdx
+++ b/docs/index.mdx
@@ -78,7 +78,7 @@ Strix uses a graph of specialized agents for comprehensive security testing:
 curl -sSL https://strix.ai/install | bash

 # Configure
-export STRIX_LLM="openai/gpt-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"
 export LLM_API_KEY="your-api-key"

 # Scan
--- a/docs/integrations/github-actions.mdx
+++ b/docs/integrations/github-actions.mdx
@@ -35,7 +35,7 @@ Add these secrets to your repository:

 | Secret | Description |
 |--------|-------------|
-| `STRIX_LLM` | Model name (e.g., `openai/gpt-5`) |
+| `STRIX_LLM` | Model name (e.g., `anthropic/claude-sonnet-4-6`) |
 | `LLM_API_KEY` | API key for your LLM provider |

 ## Exit Codes
--- a/docs/llm-providers/anthropic.mdx
+++ b/docs/llm-providers/anthropic.mdx
@@ -6,7 +6,7 @@ description: "Configure Strix with Claude models"
 ## Setup

 ```bash
-export STRIX_LLM="anthropic/claude-sonnet-4-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"
 export LLM_API_KEY="sk-ant-..."
 ```

@@ -14,8 +14,8 @@ export LLM_API_KEY="sk-ant-..."

 | Model | Description |
 |-------|-------------|
-| `anthropic/claude-sonnet-4-5` | Best balance of intelligence and speed (recommended) |
-| `anthropic/claude-opus-4-5` | Maximum capability for deep analysis |
+| `anthropic/claude-sonnet-4-6` | Best balance of intelligence and speed (recommended) |
+| `anthropic/claude-opus-4-6` | Maximum capability for deep analysis |

 ## Get API Key

--- a/docs/llm-providers/models.mdx
+++ b/docs/llm-providers/models.mdx
@@ -0,0 +1,80 @@
+---
+title: "Strix Router"
+description: "Access top LLMs through a single API with high rate limits and zero data retention"
+---
+
+Strix Router gives you access to the best LLMs through a single API key.
+
+<Note>
+Strix Router is currently in **beta**. It's completely optional — Strix works with any [LiteLLM-compatible provider](/llm-providers/overview) using your own API keys, or with [local models](/llm-providers/local). Strix Router is just the setup we test and optimize for.
+</Note>
+
+## Why Use Strix Router?
+
+- **High rate limits** — No throttling during long-running scans
+- **Zero data retention** — Routes to providers with zero data retention policies enabled
+- **Failover & load balancing** — Automatic fallback across providers for reliability
+- **Simple setup** — One API key, one environment variable, no provider accounts needed
+- **No markup** — Same token pricing as the underlying providers, no extra fees
+- **$10 free credit** — Try it free on signup, no credit card required
+
+## Quick Start
+
+1. Get your API key at [models.strix.ai](https://models.strix.ai)
+2. Set your environment:
+
+```bash
+export LLM_API_KEY='your-strix-api-key'
+export STRIX_LLM='strix/claude-sonnet-4.6'
+```
+
+3. Run a scan:
+
+```bash
+strix --target ./your-app
+```
+
+## Available Models
+
+### Anthropic
+
+| Model | ID |
+|-------|-----|
+| Claude Sonnet 4.6 | `strix/claude-sonnet-4.6` |
+| Claude Opus 4.6 | `strix/claude-opus-4.6` |
+
+### OpenAI
+
+| Model | ID |
+|-------|-----|
+| GPT-5.2 | `strix/gpt-5.2` |
+| GPT-5.1 | `strix/gpt-5.1` |
+| GPT-5 | `strix/gpt-5` |
+| GPT-5.2 Codex | `strix/gpt-5.2-codex` |
+| GPT-5.1 Codex Max | `strix/gpt-5.1-codex-max` |
+| GPT-5.1 Codex | `strix/gpt-5.1-codex` |
+| GPT-5 Codex | `strix/gpt-5-codex` |
+
+### Google
+
+| Model | ID |
+|-------|-----|
+| Gemini 3 Pro | `strix/gemini-3-pro-preview` |
+| Gemini 3 Flash | `strix/gemini-3-flash-preview` |
+
+### Other
+
+| Model | ID |
+|-------|-----|
+| GLM-5 | `strix/glm-5` |
+| GLM-4.7 | `strix/glm-4.7` |
+
+## Configuration Reference
+
+<ParamField path="LLM_API_KEY" type="string" required>
+  Your Strix API key from [models.strix.ai](https://models.strix.ai).
+</ParamField>
+
+<ParamField path="STRIX_LLM" type="string" required>
+  Model ID from the tables above. Must be prefixed with `strix/`.
+</ParamField>
--- a/docs/llm-providers/openrouter.mdx
+++ b/docs/llm-providers/openrouter.mdx
@@ -19,7 +19,7 @@ Access any model on OpenRouter using the format `openrouter/<provider>/<model>`:
 | Model | Configuration |
 |-------|---------------|
 | GPT-5 | `openrouter/openai/gpt-5` |
-| Claude 4.5 Sonnet | `openrouter/anthropic/claude-sonnet-4.5` |
+| Claude Sonnet 4.6 | `openrouter/anthropic/claude-sonnet-4.6` |
 | Gemini 3 Pro | `openrouter/google/gemini-3-pro-preview` |
 | GLM-4.7 | `openrouter/z-ai/glm-4.7` |

--- a/docs/llm-providers/overview.mdx
+++ b/docs/llm-providers/overview.mdx
@@ -5,31 +5,54 @@ description: "Configure your AI model for Strix"

 Strix uses [LiteLLM](https://docs.litellm.ai/docs/providers) for model compatibility, supporting 100+ LLM providers.

-## Recommended Models
+## Strix Router (Recommended)

-For best results, use one of these models:
+The fastest way to get started. [Strix Router](/llm-providers/models) gives you access to tested models with the highest rate limits and zero data retention.
+
+```bash
+export STRIX_LLM="strix/claude-sonnet-4.6"
+export LLM_API_KEY="your-strix-api-key"
+```
+
+Get your API key at [models.strix.ai](https://models.strix.ai).
+
+## Bring Your Own Key
+
+You can also use any LiteLLM-compatible provider with your own API keys:

 | Model             | Provider      | Configuration                    |
 | ----------------- | ------------- | -------------------------------- |
+| Claude Sonnet 4.6 | Anthropic     | `anthropic/claude-sonnet-4-6`    |
 | GPT-5             | OpenAI        | `openai/gpt-5`                   |
-| Claude 4.5 Sonnet | Anthropic     | `anthropic/claude-sonnet-4-5`    |
 | Gemini 3 Pro      | Google Vertex | `vertex_ai/gemini-3-pro-preview` |

-## Quick Setup
-
 ```bash
-export STRIX_LLM="openai/gpt-5"
+export STRIX_LLM="anthropic/claude-sonnet-4-6"
 export LLM_API_KEY="your-api-key"
 ```

+## Local Models
+
+Run models locally with [Ollama](https://ollama.com), [LM Studio](https://lmstudio.ai), or any OpenAI-compatible server:
+
+```bash
+export STRIX_LLM="ollama/llama4"
+export LLM_API_BASE="http://localhost:11434"
+```
+
+See the [Local Models guide](/llm-providers/local) for setup instructions and recommended models.
+
 ## Provider Guides

 <CardGroup cols={2}>
+  <Card title="Strix Router" href="/llm-providers/models">
+    Recommended models router with high rate limits.
+  </Card>
  <Card title="OpenAI" href="/llm-providers/openai">
    GPT-5 and Codex models.
  </Card>
  <Card title="Anthropic" href="/llm-providers/anthropic">
-    Claude 4.5 Sonnet, Opus, and Haiku.
+    Claude Sonnet 4.6, Opus, and Haiku.
  </Card>
  <Card title="OpenRouter" href="/llm-providers/openrouter">
    Access 100+ models through a single API.
@@ -38,7 +61,7 @@ export LLM_API_KEY="your-api-key"
    Gemini 3 models via Google Cloud.
  </Card>
  <Card title="AWS Bedrock" href="/llm-providers/bedrock">
-    Claude 4.5 and Titan models via AWS.
+    Claude and Titan models via AWS.
  </Card>
  <Card title="Azure OpenAI" href="/llm-providers/azure">
    GPT-5 via Azure.
@@ -53,8 +76,8 @@ export LLM_API_KEY="your-api-key"
 Use LiteLLM's `provider/model-name` format:

 ```
+anthropic/claude-sonnet-4-6
 openai/gpt-5
-anthropic/claude-sonnet-4-5
 vertex_ai/gemini-3-pro-preview
 bedrock/anthropic.claude-4-5-sonnet-20251022-v1:0
 ollama/llama4
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
@@ -6,7 +6,7 @@ description: "Install Strix and run your first security scan"
 ## Prerequisites

 - Docker (running)
- An LLM provider API key (OpenAI, Anthropic, or local model)
+- An LLM API key — use [Strix Router](/llm-providers/models) for the easiest setup, or bring your own key from any [supported provider](/llm-providers/overview)

 ## Installation

@@ -27,13 +27,23 @@ description: "Install Strix and run your first security scan"

 Set your LLM provider:

-```bash
-export STRIX_LLM="openai/gpt-5"
-export LLM_API_KEY="your-api-key"
-```
+<Tabs>
+  <Tab title="Strix Router">
+    ```bash
+    export STRIX_LLM="strix/claude-sonnet-4.6"
+    export LLM_API_KEY="your-strix-api-key"
+    ```
+  </Tab>
+  <Tab title="Bring Your Own Key">
+    ```bash
+    export STRIX_LLM="anthropic/claude-sonnet-4-6"
+    export LLM_API_KEY="your-api-key"
+    ```
+  </Tab>
+</Tabs>

 <Tip>
-For best results, use `openai/gpt-5`, `anthropic/claude-sonnet-4-5`, or `vertex_ai/gemini-3-pro-preview`.
+For best results, use `strix/claude-sonnet-4.6`, `strix/claude-opus-4.6`, or `strix/gpt-5.2`.
 </Tip>

 ## Run Your First Scan
--- a/scripts/install.sh
+++ b/scripts/install.sh
@@ -335,14 +335,18 @@ echo -e "${MUTED}  AI Penetration Testing Agent${NC}"
 echo ""
 echo -e "${MUTED}To get started:${NC}"
 echo ""
-echo -e "  ${CYAN}1.${NC} Set your LLM provider:"
-echo -e "     ${MUTED}export STRIX_LLM='openai/gpt-5'${NC}"
-echo -e "     ${MUTED}export LLM_API_KEY='your-api-key'${NC}"
+echo -e "  ${CYAN}1.${NC} Get your Strix API key:"
+echo -e "     ${MUTED}https://models.strix.ai${NC}"
 echo ""
-echo -e "  ${CYAN}2.${NC} Run a penetration test:"
+echo -e "  ${CYAN}2.${NC} Set your environment:"
+echo -e "     ${MUTED}export LLM_API_KEY='your-api-key'${NC}"
+echo -e "     ${MUTED}export STRIX_LLM='strix/claude-sonnet-4.6'${NC}"
+echo ""
+echo -e "  ${CYAN}3.${NC} Run a penetration test:"
 echo -e "     ${MUTED}strix --target https://example.com${NC}"
 echo ""
 echo -e "${MUTED}For more information visit ${NC}https://strix.ai"
+echo -e "${MUTED}Supported models ${NC}https://docs.strix.ai/llm-providers/overview"
 echo -e "${MUTED}Join our community ${NC}https://discord.gg/strix-ai"
 echo ""

--- a/strix/config/config.py
+++ b/strix/config/config.py
@@ -5,6 +5,9 @@ from pathlib import Path
 from typing import Any


+STRIX_API_BASE = "https://models.strix.ai/api/v1"
+
+
 class Config:
    """Configuration Manager for Strix."""

@@ -177,3 +180,30 @@ def apply_saved_config(force: bool = False) -> dict[str, str]:

 def save_current_config() -> bool:
    return Config.save_current()
+
+
+def resolve_llm_config() -> tuple[str | None, str | None, str | None]:
+    """Resolve LLM model, api_key, and api_base based on STRIX_LLM prefix.
+
+    Returns:
+        tuple: (model_name, api_key, api_base)
+    """
+    model = Config.get("strix_llm")
+    if not model:
+        return None, None, None
+
+    api_key = Config.get("llm_api_key")
+
+    if model.startswith("strix/"):
+        model_name = "openai/" + model[6:]
+        api_base: str | None = STRIX_API_BASE
+    else:
+        model_name = model
+        api_base = (
+            Config.get("llm_api_base")
+            or Config.get("openai_api_base")
+            or Config.get("litellm_base_url")
+            or Config.get("ollama_api_base")
+        )
+
+    return model_name, api_key, api_base
--- a/strix/interface/main.py
+++ b/strix/interface/main.py
@@ -51,10 +51,13 @@ def validate_environment() -> None:  # noqa: PLR0912, PLR0915
    missing_required_vars = []
    missing_optional_vars = []

-    if not Config.get("strix_llm"):
+    strix_llm = Config.get("strix_llm")
+    uses_strix_models = strix_llm and strix_llm.startswith("strix/")
+
+    if not strix_llm:
        missing_required_vars.append("STRIX_LLM")

-    has_base_url = any(
+    has_base_url = uses_strix_models or any(
        [
            Config.get("llm_api_base"),
            Config.get("openai_api_base"),
@@ -96,7 +99,7 @@ def validate_environment() -> None:  # noqa: PLR0912, PLR0915
                error_text.append("• ", style="white")
                error_text.append("STRIX_LLM", style="bold cyan")
                error_text.append(
-                    " - Model name to use with litellm (e.g., 'openai/gpt-5')\n",
+                    " - Model name to use with litellm (e.g., 'anthropic/claude-sonnet-4-6')\n",
                    style="white",
                )

@@ -135,7 +138,10 @@ def validate_environment() -> None:  # noqa: PLR0912, PLR0915
                    )

        error_text.append("\nExample setup:\n", style="white")
-        error_text.append("export STRIX_LLM='openai/gpt-5'\n", style="dim white")
+        if uses_strix_models:
+            error_text.append("export STRIX_LLM='strix/claude-sonnet-4.6'\n", style="dim white")
+        else:
+            error_text.append("export STRIX_LLM='anthropic/claude-sonnet-4-6'\n", style="dim white")

        if missing_optional_vars:
            for var in missing_optional_vars:
@@ -198,17 +204,12 @@ def check_docker_installed() -> None:


 async def warm_up_llm() -> None:
+    from strix.config.config import resolve_llm_config
+
    console = Console()

    try:
-        model_name = Config.get("strix_llm")
-        api_key = Config.get("llm_api_key")
-        api_base = (
-            Config.get("llm_api_base")
-            or Config.get("openai_api_base")
-            or Config.get("litellm_base_url")
-            or Config.get("ollama_api_base")
-        )
+        model_name, api_key, api_base = resolve_llm_config()

        test_messages = [
            {"role": "system", "content": "You are a helpful assistant."},
--- a/strix/llm/config.py
+++ b/strix/llm/config.py
@@ -1,4 +1,5 @@
 from strix.config import Config
+from strix.config.config import resolve_llm_config


 class LLMConfig:
@@ -10,7 +11,8 @@ class LLMConfig:
        timeout: int | None = None,
        scan_mode: str = "deep",
    ):
-        self.model_name = model_name or Config.get("strix_llm")
+        resolved_model, self.api_key, self.api_base = resolve_llm_config()
+        self.model_name = model_name or resolved_model

        if not self.model_name:
            raise ValueError("STRIX_LLM environment variable must be set and not empty")
--- a/strix/llm/dedupe.py
+++ b/strix/llm/dedupe.py
@@ -5,7 +5,7 @@ from typing import Any

 import litellm

-from strix.config import Config
+from strix.config.config import resolve_llm_config


 logger = logging.getLogger(__name__)
@@ -155,14 +155,7 @@ def check_duplicate(

        comparison_data = {"candidate": candidate_cleaned, "existing_reports": existing_cleaned}

-        model_name = Config.get("strix_llm")
-        api_key = Config.get("llm_api_key")
-        api_base = (
-            Config.get("llm_api_base")
-            or Config.get("openai_api_base")
-            or Config.get("litellm_base_url")
-            or Config.get("ollama_api_base")
-        )
+        model_name, api_key, api_base = resolve_llm_config()

        messages = [
            {"role": "system", "content": DEDUPE_SYSTEM_PROMPT},
--- a/strix/llm/llm.py
+++ b/strix/llm/llm.py
@@ -200,15 +200,10 @@ class LLM:
            "stream_options": {"include_usage": True},
        }

-        if api_key := Config.get("llm_api_key"):
-            args["api_key"] = api_key
-        if api_base := (
-            Config.get("llm_api_base")
-            or Config.get("openai_api_base")
-            or Config.get("litellm_base_url")
-            or Config.get("ollama_api_base")
-        ):
-            args["api_base"] = api_base
+        if self.config.api_key:
+            args["api_key"] = self.config.api_key
+        if self.config.api_base:
+            args["api_base"] = self.config.api_base
        if self._supports_reasoning():
            args["reasoning_effort"] = self._reasoning_effort

--- a/strix/llm/memory_compressor.py
+++ b/strix/llm/memory_compressor.py
@@ -3,7 +3,7 @@ from typing import Any

 import litellm

-from strix.config import Config
+from strix.config.config import Config, resolve_llm_config


 logger = logging.getLogger(__name__)
@@ -104,13 +104,7 @@ def _summarize_messages(
    conversation = "\n".join(formatted)
    prompt = SUMMARY_PROMPT_TEMPLATE.format(conversation=conversation)

-    api_key = Config.get("llm_api_key")
-    api_base = (
-        Config.get("llm_api_base")
-        or Config.get("openai_api_base")
-        or Config.get("litellm_base_url")
-        or Config.get("ollama_api_base")
-    )
+    _, api_key, api_base = resolve_llm_config()

    try:
        completion_args: dict[str, Any] = {