Add configurable default LLM provider and model preferences

Co-authored-by: mblanke <9078342+mblanke@users.noreply.github.com>

.env.example

@@ -7,3 +7,10 @@ ANTHROPIC_API_KEY=
 
 # Ollama Configuration
 OLLAMA_BASE_URL=http://ollama:11434
+
+# Default LLM Provider and Model
+# These are used when no explicit provider/model is specified in API requests
+# Can be changed via API: POST /api/llm/preferences
+DEFAULT_LLM_PROVIDER=ollama
+DEFAULT_LLM_MODEL=llama3.2
+# Available providers: ollama, ollama-local, ollama-network, openai, anthropic

FEATURES.md

@@ -434,8 +434,9 @@ Returns: { title, description, tips, example }
 
 ```
 POST /api/llm/chat
-Body: { message: string, session_id?: string, context?: string }
+Body: { message: string, session_id?: string, context?: string, provider?: string, model?: string }
 Returns: { message: string, success: boolean }
+Note: If provider/model not specified, uses default preferences
 
 GET /api/llm/autocomplete?partial_text=...&context_type=...
 Returns: { suggestions: [...] }
@@ -443,8 +444,21 @@ Returns: { suggestions: [...] }
 POST /api/llm/explain
 Body: { item: string, item_type?: string, context?: {...} }
 Returns: { explanation: string, item_type: string }
+
+GET /api/llm/preferences
+Returns: { current: { provider: string, model: string }, available_providers: [...] }
+
+POST /api/llm/preferences
+Body: { provider: string, model: string }
+Returns: { status: string, provider: string, model: string, message: string }
 ```
 
+**LLM Provider Selection:**
+- Set default LLM provider and model via environment variables: `DEFAULT_LLM_PROVIDER`, `DEFAULT_LLM_MODEL`
+- Change defaults at runtime via `/api/llm/preferences` endpoint
+- Override per-request by specifying `provider` and `model` in request body
+- Available providers: `ollama`, `ollama-local`, `ollama-network`, `openai`, `anthropic`
+
 ### Config Validation
 
 ```

docker-compose.yml

@@ -29,6 +29,8 @@ services:
     environment:
       - LLM_ROUTER_URL=http://strikepackage-llm-router:8000
       - KALI_EXECUTOR_URL=http://strikepackage-kali-executor:8002
+      - DEFAULT_LLM_PROVIDER=${DEFAULT_LLM_PROVIDER:-ollama}
+      - DEFAULT_LLM_MODEL=${DEFAULT_LLM_MODEL:-llama3.2}
     depends_on:
       - llm-router
       - kali-executor

services/hackgpt-api/app/main.py

@@ -32,10 +32,18 @@ app.add_middleware(
 LLM_ROUTER_URL = os.getenv("LLM_ROUTER_URL", "http://strikepackage-llm-router:8000")
 KALI_EXECUTOR_URL = os.getenv("KALI_EXECUTOR_URL", "http://strikepackage-kali-executor:8002")
 
+# Default LLM Configuration (can be overridden via environment or API)
+DEFAULT_LLM_PROVIDER = os.getenv("DEFAULT_LLM_PROVIDER", "ollama")
+DEFAULT_LLM_MODEL = os.getenv("DEFAULT_LLM_MODEL", "llama3.2")
+
 # In-memory storage (use Redis in production)
 tasks: Dict[str, Any] = {}
 sessions: Dict[str, Dict] = {}
 scan_results: Dict[str, Any] = {}
+llm_preferences: Dict[str, Any] = {
+    "provider": DEFAULT_LLM_PROVIDER,
+    "model": DEFAULT_LLM_MODEL
+}
 
 
 # ============== Models ==============
@@ -50,22 +58,27 @@ class ChatRequest(BaseModel):
     message: str
     session_id: Optional[str] = None
     context: Optional[str] = None
-    provider: str = "ollama"
-    model: str = "llama3.2"
+    provider: Optional[str] = None  # None means use default
+    model: Optional[str] = None  # None means use default
 
 
 class PhaseChatRequest(BaseModel):
     message: str
     phase: str
-    provider: str = "ollama"
-    model: str = "llama3.2"
+    provider: Optional[str] = None  # None means use default
+    model: Optional[str] = None  # None means use default
     findings: List[Dict[str, Any]] = []
 
 
 class AttackChainRequest(BaseModel):
     findings: List[Dict[str, Any]]
-    provider: str = "ollama"
-    model: str = "llama3.2"
+    provider: Optional[str] = None  # None means use default
+    model: Optional[str] = None  # None means use default
+
+
+class LLMPreferencesRequest(BaseModel):
+    provider: str
+    model: str
 
 
 class CommandRequest(BaseModel):
@@ -335,7 +348,7 @@ async def health_check():
 
 @app.post("/chat")
 async def security_chat(request: ChatRequest):
-    """Chat with security-focused AI assistant"""
+    """Chat with security-focused AI assistant - uses default LLM preferences if not specified"""
     messages = [
         {
             "role": "system",
@@ -357,8 +370,8 @@ vulnerabilities and defenses."""
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": request.provider,
-                    "model": request.model,
+                    "provider": request.provider or llm_preferences["provider"],
+                    "model": request.model or llm_preferences["model"],
                     "messages": messages,
                     "temperature": 0.7,
                     "max_tokens": 2048
@@ -376,7 +389,7 @@ vulnerabilities and defenses."""
 
 @app.post("/chat/phase")
 async def phase_aware_chat(request: PhaseChatRequest):
-    """Phase-aware chat with context from current pentest phase"""
+    """Phase-aware chat with context from current pentest phase - uses default LLM preferences if not specified"""
     phase_prompt = PHASE_PROMPTS.get(request.phase, PHASE_PROMPTS["recon"])
     
     # Build context from findings if available
@@ -400,8 +413,8 @@ async def phase_aware_chat(request: PhaseChatRequest):
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": request.provider,
-                    "model": request.model,
+                    "provider": request.provider or llm_preferences["provider"],
+                    "model": request.model or llm_preferences["model"],
                     "messages": messages,
                     "temperature": 0.7,
                     "max_tokens": 2048
@@ -515,8 +528,8 @@ Only return valid JSON."""
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": request.provider,
-                    "model": request.model,
+                    "provider": request.provider or llm_preferences["provider"],
+                    "model": request.model or llm_preferences["model"],
                     "messages": messages,
                     "temperature": 0.3,
                     "max_tokens": 2048
@@ -919,7 +932,7 @@ def parse_gobuster_output(output: str) -> Dict[str, Any]:
 
 @app.post("/ai-scan")
 async def ai_assisted_scan(request: ChatRequest, background_tasks: BackgroundTasks):
-    """Use AI to determine and run appropriate scan."""
+    """Use AI to determine and run appropriate scan - uses default LLM preferences if not specified"""
     # Get AI suggestion
     messages = [
         {"role": "system", "content": SECURITY_PROMPTS["command_assist"]},
@@ -931,8 +944,8 @@ async def ai_assisted_scan(request: ChatRequest, background_tasks: BackgroundTas
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": request.provider,
-                    "model": request.model,
+                    "provider": request.provider or llm_preferences["provider"],
+                    "model": request.model or llm_preferences["model"],
                     "messages": messages,
                     "temperature": 0.3,
                     "max_tokens": 1024
@@ -995,8 +1008,8 @@ async def run_analysis(task_id: str, request: SecurityAnalysisRequest):
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": "ollama",
-                    "model": "llama3.2",
+                    "provider": llm_preferences["provider"],
+                    "model": llm_preferences["model"],
                     "messages": [
                         {"role": "system", "content": prompt},
                         {"role": "user", "content": f"Analyze target: {request.target}\nOptions: {request.options}"}
@@ -1060,7 +1073,7 @@ async def list_tools():
 
 @app.post("/suggest-command")
 async def suggest_command(request: ChatRequest):
-    """Get AI-suggested security commands based on context"""
+    """Get AI-suggested security commands based on context - uses default LLM preferences if not specified"""
     messages = [
         {
             "role": "system",
@@ -1083,8 +1096,8 @@ Only suggest commands for legitimate security testing purposes."""
             response = await client.post(
                 f"{LLM_ROUTER_URL}/chat",
                 json={
-                    "provider": request.provider,
-                    "model": request.model,
+                    "provider": request.provider or llm_preferences["provider"],
+                    "model": request.model or llm_preferences["model"],
                     "messages": messages,
                     "temperature": 0.3,
                     "max_tokens": 1024
@@ -1231,18 +1244,18 @@ async def llm_chat_help(
     message: str,
     session_id: Optional[str] = None,
     context: Optional[str] = None,
-    provider: str = "ollama",
-    model: str = "llama3.2"
+    provider: Optional[str] = None,
+    model: Optional[str] = None
 ):
-    """LLM-powered chat help"""
+    """LLM-powered chat help - uses default preferences if provider/model not specified"""
     try:
         from . import llm_help
         result = await llm_help.chat_completion(
             message=message,
             session_id=session_id,
             context=context,
-            provider=provider,
-            model=model
+            provider=provider or llm_preferences["provider"],
+            model=model or llm_preferences["model"]
         )
         return result
     except Exception as e:
@@ -1398,6 +1411,80 @@ async def send_push_notification(
         raise HTTPException(status_code=500, detail=f"Push notification error: {str(e)}")
 
 
+# ============== LLM Preferences ==============
+
+@app.get("/api/llm/preferences")
+async def get_llm_preferences():
+    """
+    Get current default LLM provider and model preferences.
+    
+    Returns:
+        Dictionary with provider, model, and available options
+    """
+    try:
+        # Get available providers from LLM router
+        async with httpx.AsyncClient() as client:
+            response = await client.get(f"{LLM_ROUTER_URL}/providers", timeout=10.0)
+            available_providers = response.json() if response.status_code == 200 else []
+        
+        return {
+            "current": {
+                "provider": llm_preferences["provider"],
+                "model": llm_preferences["model"]
+            },
+            "available_providers": available_providers,
+            "description": "Current default LLM provider and model. These are used when no explicit provider/model is specified in API requests."
+        }
+    except Exception as e:
+        return {
+            "current": {
+                "provider": llm_preferences["provider"],
+                "model": llm_preferences["model"]
+            },
+            "available_providers": [],
+            "error": str(e)
+        }
+
+
+@app.post("/api/llm/preferences")
+async def set_llm_preferences(request: LLMPreferencesRequest):
+    """
+    Set default LLM provider and model preferences.
+    
+    Args:
+        request: LLMPreferencesRequest with provider and model
+        
+    Returns:
+        Updated preferences
+    """
+    # Validate provider is available
+    try:
+        async with httpx.AsyncClient() as client:
+            response = await client.get(f"{LLM_ROUTER_URL}/providers", timeout=10.0)
+            if response.status_code == 200:
+                available_providers = response.json()
+                provider_names = [p["name"] for p in available_providers]
+                if request.provider not in provider_names:
+                    raise HTTPException(
+                        status_code=400,
+                        detail=f"Provider '{request.provider}' not available. Available: {provider_names}"
+                    )
+    except httpx.ConnectError:
+        # LLM router not available, proceed anyway
+        pass
+    
+    # Update preferences
+    llm_preferences["provider"] = request.provider
+    llm_preferences["model"] = request.model
+    
+    return {
+        "status": "updated",
+        "provider": llm_preferences["provider"],
+        "model": llm_preferences["model"],
+        "message": f"Default LLM set to {request.provider}/{request.model}"
+    }
+
+
 if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=8001)