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https://github.com/mblanke/StrikePackageGPT.git
synced 2026-03-01 14:20:21 -05:00
feat: Add HackGpt Enterprise features
- 6-Phase pentest methodology UI (Recon, Scanning, Vuln, Exploit, Report, Retest) - Phase-aware AI prompts with context from current phase - Attack chain analysis and visualization - CVSS-style severity badges (CRITICAL/HIGH/MEDIUM/LOW) - Findings sidebar with severity counts - Phase-specific tools and quick actions
This commit is contained in:
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services/llm-router/app/__init__.py
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services/llm-router/app/__init__.py
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services/llm-router/app/main.py
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services/llm-router/app/main.py
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"""
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LLM Router Service
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Routes requests to different LLM providers (OpenAI, Anthropic, Ollama)
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"""
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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from typing import Optional, Literal
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import httpx
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import os
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app = FastAPI(
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title="LLM Router",
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description="Routes requests to multiple LLM providers",
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version="0.1.0"
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)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Configuration from environment
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
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ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "")
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OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://192.168.1.50:11434")
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class ChatMessage(BaseModel):
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role: Literal["system", "user", "assistant"]
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content: str
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class ChatRequest(BaseModel):
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provider: Literal["openai", "anthropic", "ollama"] = "ollama"
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model: str = "llama3.2"
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messages: list[ChatMessage]
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temperature: float = 0.7
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max_tokens: int = 2048
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class ChatResponse(BaseModel):
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provider: str
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model: str
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content: str
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usage: Optional[dict] = None
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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return {"status": "healthy", "service": "llm-router"}
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@app.get("/providers")
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async def list_providers():
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"""List available LLM providers and their status"""
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# Dynamically fetch Ollama models
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ollama_models = []
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ollama_available = False
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try:
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async with httpx.AsyncClient() as client:
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response = await client.get(f"{OLLAMA_BASE_URL}/api/tags", timeout=5.0)
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if response.status_code == 200:
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data = response.json()
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ollama_models = [m["name"] for m in data.get("models", [])]
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ollama_available = True
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except Exception:
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ollama_models = ["llama3", "mistral", "codellama"] # fallback
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providers = {
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"openai": {"available": bool(OPENAI_API_KEY), "models": ["gpt-4o", "gpt-4o-mini", "gpt-4-turbo"]},
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"anthropic": {"available": bool(ANTHROPIC_API_KEY), "models": ["claude-sonnet-4-20250514", "claude-3-5-haiku-20241022"]},
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"ollama": {"available": ollama_available, "base_url": OLLAMA_BASE_URL, "models": ollama_models}
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}
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return providers
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@app.post("/chat", response_model=ChatResponse)
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async def chat(request: ChatRequest):
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"""Route chat request to specified LLM provider"""
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if request.provider == "openai":
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return await _call_openai(request)
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elif request.provider == "anthropic":
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return await _call_anthropic(request)
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elif request.provider == "ollama":
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return await _call_ollama(request)
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else:
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raise HTTPException(status_code=400, detail=f"Unknown provider: {request.provider}")
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async def _call_openai(request: ChatRequest) -> ChatResponse:
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"""Call OpenAI API"""
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if not OPENAI_API_KEY:
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raise HTTPException(status_code=503, detail="OpenAI API key not configured")
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async with httpx.AsyncClient() as client:
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response = await client.post(
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"https://api.openai.com/v1/chat/completions",
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headers={
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"Authorization": f"Bearer {OPENAI_API_KEY}",
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"Content-Type": "application/json"
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},
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json={
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"model": request.model,
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"messages": [m.model_dump() for m in request.messages],
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"temperature": request.temperature,
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"max_tokens": request.max_tokens
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},
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timeout=60.0
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)
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if response.status_code != 200:
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raise HTTPException(status_code=response.status_code, detail=response.text)
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data = response.json()
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return ChatResponse(
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provider="openai",
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model=request.model,
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content=data["choices"][0]["message"]["content"],
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usage=data.get("usage")
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)
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async def _call_anthropic(request: ChatRequest) -> ChatResponse:
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"""Call Anthropic API"""
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if not ANTHROPIC_API_KEY:
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raise HTTPException(status_code=503, detail="Anthropic API key not configured")
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# Extract system message if present
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system_msg = ""
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messages = []
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for msg in request.messages:
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if msg.role == "system":
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system_msg = msg.content
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else:
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messages.append({"role": msg.role, "content": msg.content})
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async with httpx.AsyncClient() as client:
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payload = {
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"model": request.model,
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"messages": messages,
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"max_tokens": request.max_tokens,
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"temperature": request.temperature
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}
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if system_msg:
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payload["system"] = system_msg
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response = await client.post(
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"https://api.anthropic.com/v1/messages",
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headers={
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"x-api-key": ANTHROPIC_API_KEY,
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"Content-Type": "application/json",
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"anthropic-version": "2023-06-01"
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},
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json=payload,
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timeout=60.0
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)
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if response.status_code != 200:
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raise HTTPException(status_code=response.status_code, detail=response.text)
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data = response.json()
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return ChatResponse(
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provider="anthropic",
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model=request.model,
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content=data["content"][0]["text"],
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usage=data.get("usage")
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)
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async def _call_ollama(request: ChatRequest) -> ChatResponse:
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"""Call Ollama API (local models)"""
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async with httpx.AsyncClient() as client:
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try:
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response = await client.post(
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f"{OLLAMA_BASE_URL}/api/chat",
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json={
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"model": request.model,
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"messages": [m.model_dump() for m in request.messages],
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"stream": False,
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"options": {
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"temperature": request.temperature,
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"num_predict": request.max_tokens
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}
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},
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timeout=120.0
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)
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if response.status_code != 200:
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raise HTTPException(status_code=response.status_code, detail=response.text)
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data = response.json()
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return ChatResponse(
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provider="ollama",
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model=request.model,
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content=data["message"]["content"],
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usage={
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"prompt_tokens": data.get("prompt_eval_count", 0),
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"completion_tokens": data.get("eval_count", 0)
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}
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)
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except httpx.ConnectError:
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raise HTTPException(status_code=503, detail="Ollama service not available")
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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