microdao-daarion/services/router/tool_manager.py

"""
Tool Manager for Helion Agent
Implements OpenAI-compatible function calling for DeepSeek, Mistral, Grok
"""

import os
from agent_tools_config import get_agent_tools, is_tool_allowed
import json
import logging
import httpx
from typing import Dict, List, Any, Optional
from dataclasses import dataclass

logger = logging.getLogger(__name__)

# Tool definitions in OpenAI function calling format
# ORDER MATTERS: Memory/Graph tools first, then web search as fallback
TOOL_DEFINITIONS = [
    # PRIORITY 1: Internal knowledge sources (use FIRST)
    {
        "type": "function",
        "function": {
            "name": "memory_search",
            "description": "🔍 ПЕРШИЙ КРОК для пошуку! Шукає в моїй пам'яті: збережені факти, документи, розмови. ЗАВЖДИ використовуй спочатку перед web_search!",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Що шукати в пам'яті"
                    }
                },
                "required": ["query"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "graph_query",
            "description": "🔍 Пошук в Knowledge Graph - зв'язки між проєктами, людьми, темами Energy Union. Використовуй для питань про проєкти, партнерів, технології.",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Що шукати (назва проєкту, людини, теми)"
                    },
                    "entity_type": {
                        "type": "string",
                        "enum": ["User", "Topic", "Project", "Fact"],
                        "description": "Тип сутності для пошуку"
                    }
                },
                "required": ["query"]
            }
        }
    },
    # PRIORITY 2: Web search (use ONLY if memory/graph don't have info)
    {
        "type": "function",
        "function": {
            "name": "web_search",
            "description": "🌐 Пошук в інтернеті. Використовуй ТІЛЬКИ якщо memory_search і graph_query не знайшли потрібної інформації!",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Пошуковий запит"
                    },
                    "max_results": {
                        "type": "integer",
                        "description": "Максимальна кількість результатів (1-10)",
                        "default": 5
                    }
                },
                "required": ["query"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "web_extract",
            "description": "Витягнути текстовий контент з веб-сторінки за URL",
            "parameters": {
                "type": "object",
                "properties": {
                    "url": {
                        "type": "string",
                        "description": "URL сторінки для читання"
                    }
                },
                "required": ["url"]
            }
        }
    },
    # PRIORITY 3: Generation tools
    {
        "type": "function",
        "function": {
            "name": "image_generate",
            "description": "🎨 Згенерувати зображення за текстовим описом (FLUX)",
            "parameters": {
                "type": "object",
                "properties": {
                    "prompt": {
                        "type": "string",
                        "description": "Опис зображення для генерації (англійською краще)"
                    },
                    "width": {
                        "type": "integer",
                        "description": "Ширина зображення",
                        "default": 512
                    },
                    "height": {
                        "type": "integer",
                        "description": "Висота зображення",
                        "default": 512
                    }
                },
                "required": ["prompt"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "remember_fact",
            "description": "Запам'ятати важливий факт про користувача або тему",
            "parameters": {
                "type": "object",
                "properties": {
                    "fact": {
                        "type": "string",
                        "description": "Факт для запам'ятовування"
                    },
                    "about": {
                        "type": "string",
                        "description": "Про кого/що цей факт (username або тема)"
                    },
                    "category": {
                        "type": "string",
                        "enum": ["personal", "technical", "preference", "project"],
                        "description": "Категорія факту"
                    }
                },
                "required": ["fact", "about"]
            }
        }
    },
    # PRIORITY 4: Document/Presentation tools
    {
        "type": "function",
        "function": {
            "name": "presentation_create",
            "description": "📊 Створити презентацію PowerPoint. Використовуй коли користувач просить 'створи презентацію', 'зроби презентацію', 'підготуй слайди'.",
            "parameters": {
                "type": "object",
                "properties": {
                    "title": {
                        "type": "string",
                        "description": "Назва презентації"
                    },
                    "slides": {
                        "type": "array",
                        "items": {
                            "type": "object",
                            "properties": {
                                "title": {"type": "string", "description": "Заголовок слайду"},
                                "content": {"type": "string", "description": "Контент слайду (markdown)"}
                            }
                        },
                        "description": "Масив слайдів: [{title, content}]"
                    },
                    "brand_id": {
                        "type": "string",
                        "description": "ID бренду для стилю (energyunion, greenfood, nutra)",
                        "default": "energyunion"
                    },
                    "theme_version": {
                        "type": "string",
                        "description": "Версія теми",
                        "default": "v1.0.0"
                    },
                    "language": {
                        "type": "string",
                        "enum": ["uk", "en", "ru"],
                        "description": "Мова презентації",
                        "default": "uk"
                    }
                },
                "required": ["title", "slides"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "presentation_status",
            "description": "📋 Перевірити статус створення презентації за job_id",
            "parameters": {
                "type": "object",
                "properties": {
                    "job_id": {
                        "type": "string",
                        "description": "ID завдання рендерингу"
                    }
                },
                "required": ["job_id"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "presentation_download",
            "description": "📥 Отримати посилання на готову презентацію за artifact_id",
            "parameters": {
                "type": "object",
                "properties": {
                    "artifact_id": {
                        "type": "string",
                        "description": "ID артефакту презентації"
                    },
                    "format": {
                        "type": "string",
                        "enum": ["pptx", "pdf"],
                        "description": "Формат файлу",
                        "default": "pptx"
                    }
                },
                "required": ["artifact_id"]
            }
        }
    },
    # PRIORITY 5: Web Scraping tools
    {
        "type": "function",
        "function": {
            "name": "crawl4ai_scrape",
            "description": "🕷️ Глибокий скрейпінг веб-сторінки через Crawl4AI. Витягує повний контент, структуровані дані, медіа. Використовуй для детального аналізу сайтів.",
            "parameters": {
                "type": "object",
                "properties": {
                    "url": {
                        "type": "string",
                        "description": "URL сторінки для скрейпінгу"
                    },
                    "extract_links": {
                        "type": "boolean",
                        "description": "Витягувати посилання зі сторінки",
                        "default": True
                    },
                    "extract_images": {
                        "type": "boolean",
                        "description": "Витягувати зображення",
                        "default": False
                    }
                },
                "required": ["url"]
            }
        }
    },
    # PRIORITY 6: TTS tools
    {
        "type": "function",
        "function": {
            "name": "tts_speak",
            "description": "🔊 Перетворити текст на аудіо (Text-to-Speech). Повертає аудіо файл. Використовуй коли користувач просить озвучити текст.",
            "parameters": {
                "type": "object",
                "properties": {
                    "text": {
                        "type": "string",
                        "description": "Текст для озвучення"
                    },
                    "language": {
                        "type": "string",
                        "enum": ["uk", "en", "ru"],
                        "description": "Мова озвучення",
                        "default": "uk"
                    }
                },
                "required": ["text"]
            }
        }
    }
]


@dataclass
class ToolResult:
    """Result of tool execution"""
    success: bool
    result: Any
    error: Optional[str] = None
    image_base64: Optional[str] = None  # For image generation results


class ToolManager:
    """Manages tool execution for the agent"""
    
    def __init__(self, config: Dict[str, Any]):
        self.config = config
        self.http_client = httpx.AsyncClient(timeout=60.0)
        self.swapper_url = os.getenv("SWAPPER_URL", "http://swapper-service:8890")
        self.tools_config = self._load_tools_config()
        
    def _load_tools_config(self) -> Dict[str, Dict]:
        """Load tool endpoints from config"""
        tools = {}
        agent_config = self.config.get("agents", {}).get("helion", {})
        for tool in agent_config.get("tools", []):
            if "endpoint" in tool:
                tools[tool["id"]] = {
                    "endpoint": tool["endpoint"],
                    "method": tool.get("method", "POST")
                }
        return tools
    
    def get_tool_definitions(self, agent_id: str = None) -> List[Dict]:
        """Get tool definitions for function calling, filtered by agent permissions"""
        if not agent_id:
            return TOOL_DEFINITIONS
        
        # Get allowed tools for this agent
        allowed_tools = get_agent_tools(agent_id)
        
        # Filter tool definitions
        filtered = []
        for tool_def in TOOL_DEFINITIONS:
            tool_name = tool_def.get("function", {}).get("name")
            if tool_name in allowed_tools:
                filtered.append(tool_def)
        
        tool_names = [t.get("function", {}).get("name") for t in filtered]
        logger.debug(f"Agent {agent_id} has {len(filtered)} tools: {tool_names}")
        return filtered
    
    async def execute_tool(self, tool_name: str, arguments: Dict[str, Any], agent_id: str = None) -> ToolResult:
        """Execute a tool and return result. Optionally checks agent permissions."""
        logger.info(f"🔧 Executing tool: {tool_name} for agent={agent_id} with args: {arguments}")
        
        # Check agent permission if agent_id provided
        if agent_id and not is_tool_allowed(agent_id, tool_name):
            logger.warning(f"⚠️ Tool {tool_name} not allowed for agent {agent_id}")
            return ToolResult(success=False, result=None, error=f"Tool {tool_name} not available for this agent")
        
        try:
            # Priority 1: Memory/Knowledge tools
            if tool_name == "memory_search":
                return await self._memory_search(arguments, agent_id=agent_id)
            elif tool_name == "graph_query":
                return await self._graph_query(arguments, agent_id=agent_id)
            # Priority 2: Web tools
            elif tool_name == "web_search":
                return await self._web_search(arguments)
            elif tool_name == "web_extract":
                return await self._web_extract(arguments)
            elif tool_name == "image_generate":
                return await self._image_generate(arguments)
            elif tool_name == "remember_fact":
                return await self._remember_fact(arguments)
            # Priority 4: Presentation tools
            elif tool_name == "presentation_create":
                return await self._presentation_create(arguments)
            elif tool_name == "presentation_status":
                return await self._presentation_status(arguments)
            elif tool_name == "presentation_download":
                return await self._presentation_download(arguments)
            # Priority 5: Web scraping tools
            elif tool_name == "crawl4ai_scrape":
                return await self._crawl4ai_scrape(arguments)
            # Priority 6: TTS tools
            elif tool_name == "tts_speak":
                return await self._tts_speak(arguments)
            else:
                return ToolResult(success=False, result=None, error=f"Unknown tool: {tool_name}")
        except Exception as e:
            logger.error(f"Tool execution failed: {e}")
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _memory_search(self, args: Dict, agent_id: str = None) -> ToolResult:
        """Search in Qdrant vector memory using Router's memory_retrieval - PRIORITY 1"""
        query = args.get("query")
        
        try:
            # Use Router's memory_retrieval pipeline directly (has Qdrant connection)
            from memory_retrieval import memory_retrieval
            
            if memory_retrieval and memory_retrieval.qdrant_client:
                results = await memory_retrieval.search_memories(
                    query=query,
                    agent_id=agent_id or helion,
                    limit=5
                )
                
                if results:
                    formatted = []
                    for r in results:
                        text = r.get("text", "")
                        score = r.get("score", 0)
                        mem_type = r.get("type", "memory")
                        if text:
                            formatted.append(f"• [{mem_type}] {text[:200]}... (релевантність: {score:.2f})")
                    if formatted:
                        return ToolResult(success=True, result=f"🧠 Знайдено в пам'яті:\n" + "\n".join(formatted))
                
                return ToolResult(success=True, result="🧠 В моїй пам'яті немає інформації про це.")
            else:
                return ToolResult(success=True, result="🧠 Пам'ять недоступна, спробую web_search.")
        except Exception as e:
            logger.warning(f"Memory search error: {e}")
            return ToolResult(success=True, result="🧠 Не вдалося перевірити пам'ять. Спробую інші джерела.")
    
    async def _web_search(self, args: Dict) -> ToolResult:
        """Execute web search - PRIORITY 2 (use after memory_search)"""
        query = args.get("query")
        max_results = args.get("max_results", 5)
        
        try:
            resp = await self.http_client.post(
                f"{self.swapper_url}/web/search",
                json={"query": query, "max_results": max_results}
            )
            if resp.status_code == 200:
                data = resp.json()
                results = data.get("results", [])
                # Format results for LLM
                formatted = []
                for r in results[:max_results]:
                    formatted.append(f"- {r.get('title', 'No title')}\n  {r.get('snippet', '')}\n  URL: {r.get('url', '')}")
                return ToolResult(success=True, result="\n".join(formatted) if formatted else "Нічого не знайдено")
            else:
                return ToolResult(success=False, result=None, error=f"Search failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _web_extract(self, args: Dict) -> ToolResult:
        """Extract content from URL"""
        url = args.get("url")
        
        try:
            resp = await self.http_client.post(
                f"{self.swapper_url}/web/extract",
                json={"url": url}
            )
            if resp.status_code == 200:
                data = resp.json()
                content = data.get("content", "")
                # Truncate if too long
                if len(content) > 4000:
                    content = content[:4000] + "\n... (текст обрізано)"
                return ToolResult(success=True, result=content)
            else:
                return ToolResult(success=False, result=None, error=f"Extract failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _unload_ollama_models(self):
        """Unload all Ollama models to free VRAM for heavy operations like FLUX"""
        ollama_url = os.getenv("OLLAMA_BASE_URL", "http://172.18.0.1:11434")
        models_to_unload = ["qwen3:8b", "qwen3-vl:8b"]
        
        for model in models_to_unload:
            try:
                await self.http_client.post(
                    f"{ollama_url}/api/generate",
                    json={"model": model, "keep_alive": 0},
                    timeout=5.0
                )
                logger.info(f"🧹 Unloaded Ollama model: {model}")
            except Exception as e:
                logger.debug(f"Could not unload {model}: {e}")
        
        # Give GPU time to release memory
        import asyncio
        await asyncio.sleep(1)
    
    async def _unload_flux(self):
        """Unload FLUX model after image generation to free VRAM"""
        try:
            # Try to unload flux-klein-4b model
            await self.http_client.post(
                f"{self.swapper_url}/image/models/flux-klein-4b/unload",
                timeout=10.0
            )
            logger.info("🧹 Unloaded FLUX model from Swapper")
        except Exception as e:
            logger.debug(f"Could not unload FLUX: {e}")
    
    async def _image_generate(self, args: Dict) -> ToolResult:
        """Generate image with VRAM management"""
        prompt = args.get("prompt")
        # Use smaller sizes to fit in VRAM (20GB GPU shared with LLM)
        width = min(args.get("width", 512), 512)
        height = min(args.get("height", 512), 512)
        
        try:
            # Step 1: Unload Ollama models to free VRAM for FLUX (~15GB needed)
            logger.info("🔄 Preparing VRAM for FLUX image generation...")
            await self._unload_ollama_models()
            
            # Step 2: Generate image
            resp = await self.http_client.post(
                f"{self.swapper_url}/image/generate",
                json={"prompt": prompt, "width": width, "height": height, "num_inference_steps": 8},
                timeout=180.0  # FLUX needs time
            )
            if resp.status_code == 200:
                data = resp.json()
                image_base64 = data.get("image_base64")
                image_url = data.get("image_url") or data.get("url")
                
                # Step 3: Unload FLUX to free VRAM for other models (LLM, Vision)
                logger.info("🔄 Image generated, unloading FLUX to free VRAM...")
                await self._unload_flux()
                
                if image_base64:
                    # Return base64 image for Gateway to send
                    return ToolResult(
                        success=True,
                        result="✅ Зображення згенеровано",
                        image_base64=image_base64
                    )
                elif image_url:
                    return ToolResult(
                        success=True,
                        result=f"✅ Зображення згенеровано: {image_url}",
                        image_base64=None
                    )
                else:
                    return ToolResult(
                        success=True,
                        result="✅ Зображення згенеровано (формат невідомий)",
                        image_base64=None
                    )
            else:
                # Also unload FLUX on failure to free VRAM
                await self._unload_flux()
                return ToolResult(success=False, result=None, error=f"Generation failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _graph_query(self, args: Dict, agent_id: str = None) -> ToolResult:
        """Query knowledge graph"""
        query = args.get("query")
        entity_type = args.get("entity_type")
        
        # Simple natural language to Cypher conversion
        cypher = f"""
        MATCH (n)
        WHERE toLower(n.name) CONTAINS toLower('{query}')
           OR toLower(toString(n)) CONTAINS toLower('{query}')
        RETURN labels(n)[0] as type, n.name as name, n.node_id as id
        LIMIT 10
        """
        
        if entity_type:
            cypher = f"""
            MATCH (n:{entity_type})
            WHERE toLower(n.name) CONTAINS toLower('{query}')
            RETURN n.name as name, n.node_id as id
            LIMIT 10
            """
        
        try:
            # Execute via Router's graph endpoint
            resp = await self.http_client.post(
                "http://localhost:8000/v1/graph/query",
                json={"query": cypher}
            )
            if resp.status_code == 200:
                data = resp.json()
                return ToolResult(success=True, result=json.dumps(data.get("results", []), ensure_ascii=False))
            else:
                return ToolResult(success=False, result=None, error=f"Graph query failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _remember_fact(self, args: Dict) -> ToolResult:
        """Store a fact in memory"""
        fact = args.get("fact")
        about = args.get("about")
        category = args.get("category", "general")
        
        try:
            # Store via Memory Service
            resp = await self.http_client.post(
                "http://memory-service:8000/facts/upsert",
                json={
                    "user_id": about,
                    "fact_key": f"{category}_{hash(fact) % 10000}",
                    "fact_value": fact,
                    "fact_value_json": {"text": fact, "category": category, "about": about}
                }
            )
            if resp.status_code in [200, 201]:
                return ToolResult(success=True, result=f"✅ Запам'ятовано факт про {about}")
            else:
                return ToolResult(success=False, result=None, error=f"Memory store failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _presentation_create(self, args: Dict) -> ToolResult:
        """Create a presentation via Presentation Renderer"""
        title = args.get("title", "Презентація")
        slides = args.get("slides", [])
        brand_id = args.get("brand_id", "energyunion")
        theme_version = args.get("theme_version", "v1.0.0")
        language = args.get("language", "uk")
        
        # Build SlideSpec
        slidespec = {
            "meta": {
                "title": title,
                "brand_id": brand_id,
                "theme_version": theme_version,
                "language": language
            },
            "slides": []
        }
        
        # Add title slide
        slidespec["slides"].append({
            "type": "title",
            "title": title
        })
        
        # Add content slides
        for slide in slides:
            slide_obj = {
                "type": "content",
                "title": slide.get("title", ""),
                "body": slide.get("content", "")
            }
            slidespec["slides"].append(slide_obj)
        
        try:
            renderer_url = os.getenv("PRESENTATION_RENDERER_URL", "http://presentation-renderer:9600")
            resp = await self.http_client.post(
                f"{renderer_url}/present/render",
                json=slidespec,
                timeout=120.0
            )
            if resp.status_code == 200:
                data = resp.json()
                job_id = data.get("job_id")
                artifact_id = data.get("artifact_id")
                return ToolResult(
                    success=True, 
                    result=f"📊 Презентацію створено!\n\n🆔 Job ID: `{job_id}`\n📦 Artifact ID: `{artifact_id}`\n\nЩоб перевірити статус: використай presentation_status\nЩоб завантажити: використай presentation_download"
                )
            else:
                error_text = resp.text[:200] if resp.text else "Unknown error"
                return ToolResult(success=False, result=None, error=f"Render failed ({resp.status_code}): {error_text}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _presentation_status(self, args: Dict) -> ToolResult:
        """Check presentation job status"""
        job_id = args.get("job_id")
        
        try:
            registry_url = os.getenv("ARTIFACT_REGISTRY_URL", "http://artifact-registry:9700")
            resp = await self.http_client.get(
                f"{registry_url}/jobs/{job_id}",
                timeout=10.0
            )
            if resp.status_code == 200:
                data = resp.json()
                status = data.get("status", "unknown")
                artifact_id = data.get("artifact_id")
                error = data.get("error_text", "")
                
                status_emoji = {"queued": "⏳", "running": "🔄", "done": "✅", "failed": "❌"}.get(status, "❓")
                
                result = f"{status_emoji} Статус: **{status}**\n"
                if artifact_id:
                    result += f"📦 Artifact ID: `{artifact_id}`\n"
                if status == "done":
                    result += "\n✅ Презентація готова! Використай presentation_download щоб отримати файл."
                if status == "failed" and error:
                    result += f"\n❌ Помилка: {error[:200]}"
                
                return ToolResult(success=True, result=result)
            elif resp.status_code == 404:
                return ToolResult(success=False, result=None, error="Job not found")
            else:
                return ToolResult(success=False, result=None, error=f"Status check failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    
    async def _presentation_download(self, args: Dict) -> ToolResult:
        """Get download link for presentation"""
        artifact_id = args.get("artifact_id")
        file_format = args.get("format", "pptx")
        
        try:
            registry_url = os.getenv("ARTIFACT_REGISTRY_URL", "http://artifact-registry:9700")
            resp = await self.http_client.get(
                f"{registry_url}/artifacts/{artifact_id}/download?format={file_format}",
                timeout=10.0,
                follow_redirects=False
            )
            
            if resp.status_code in [200, 302, 307]:
                # Check for signed URL in response or Location header
                if resp.status_code in [302, 307]:
                    download_url = resp.headers.get("Location")
                else:
                    data = resp.json() if resp.headers.get("content-type", "").startswith("application/json") else {}
                    download_url = data.get("download_url") or data.get("url")
                
                if download_url:
                    return ToolResult(
                        success=True,
                        result=f"📥 **Посилання для завантаження ({file_format.upper()}):**\n\n{download_url}\n\n⏰ Посилання дійсне 30 хвилин."
                    )
                else:
                    # Direct binary response - artifact available
                    return ToolResult(
                        success=True,
                        result=f"✅ Файл {file_format.upper()} готовий! Завантажити можна через: {registry_url}/artifacts/{artifact_id}/download?format={file_format}"
                    )
            elif resp.status_code == 404:
                return ToolResult(success=False, result=None, error=f"Формат {file_format.upper()} ще не готовий. Спробуй пізніше.")
            else:
                return ToolResult(success=False, result=None, error=f"Download failed: {resp.status_code}")
        except Exception as e:
            return ToolResult(success=False, result=None, error=str(e))
    

    async def _crawl4ai_scrape(self, args: Dict) -> ToolResult:
        """Deep scrape a web page using Crawl4AI - PRIORITY 5"""
        url = args.get("url")
        extract_links = args.get("extract_links", True)
        extract_images = args.get("extract_images", False)
        
        if not url:
            return ToolResult(success=False, result=None, error="URL is required")
        
        try:
            crawl4ai_url = os.getenv("CRAWL4AI_URL", "http://dagi-crawl4ai-node1:11235")
            
            payload = {
                "urls": [url],
                "priority": 5,
                "session_id": f"agent_scrape_{hash(url) % 10000}"
            }
            
            resp = await self.http_client.post(
                f"{crawl4ai_url}/crawl",
                json=payload,
                timeout=60.0
            )
            
            if resp.status_code == 200:
                data = resp.json()
                results = data.get("results", []) if isinstance(data, dict) else []
                if not results and isinstance(data, dict):
                    results = [data]
                
                if results:
                    result = results[0] if isinstance(results, list) else results
                    markdown = result.get("markdown", "") or result.get("cleaned_html", "") or result.get("text", "")
                    title = result.get("title", url)
                    
                    if len(markdown) > 3000:
                        markdown = markdown[:3000] + "... (скорочено)"
                    
                    response_parts = [f"**{title}**", "", markdown]
                    
                    if extract_links:
                        links = result.get("links", [])
                        if links:
                            response_parts.append("")
                            response_parts.append("**Посилання:**")
                            for link in links[:10]:
                                if isinstance(link, dict):
                                    link_url = link.get("href", "")
                                else:
                                    link_url = str(link)
                                if link_url:
                                    response_parts.append(f"- {link_url}")
                    
                    return ToolResult(success=True, result="\n".join(response_parts))
                else:
                    return ToolResult(success=False, result=None, error="No content extracted")
            else:
                return ToolResult(success=False, result=None, error=f"Crawl failed: {resp.status_code}")
        except Exception as e:
            logger.error(f"Crawl4AI scrape failed: {e}")
            return ToolResult(success=False, result=None, error=str(e))

    async def _tts_speak(self, args: Dict) -> ToolResult:
        """Convert text to speech using Swapper TTS - PRIORITY 6"""
        text = args.get("text")
        language = args.get("language", "uk")
        
        if not text:
            return ToolResult(success=False, result=None, error="Text is required")
        
        try:
            if len(text) > 1000:
                text = text[:1000]
            
            resp = await self.http_client.post(
                f"{self.swapper_url}/tts",
                json={"text": text, "language": language},
                timeout=60.0
            )
            
            if resp.status_code == 200:
                data = resp.json()
                audio_url = data.get("audio_url") or data.get("url")
                
                if audio_url:
                    return ToolResult(success=True, result=f"Аудіо: {audio_url}")
                else:
                    return ToolResult(success=True, result="TTS completed")
            else:
                return ToolResult(success=False, result=None, error=f"TTS failed: {resp.status_code}")
        except Exception as e:
            logger.error(f"TTS failed: {e}")
            return ToolResult(success=False, result=None, error=str(e))

    async def close(self):
        await self.http_client.aclose()


def format_tool_calls_for_response(tool_results: List[Dict], fallback_mode: str = "normal") -> str:
    """
    Format tool results in human-friendly way - NOT raw data!
    
    Args:
        tool_results: List of tool execution results
        fallback_mode: "normal" | "dsml_detected" | "empty_response"
    """
    # Special handling for DSML detection - LLM tried to use tools but got confused
    # If we have successful tool results, show them instead of generic fallback
    if fallback_mode == "dsml_detected":
        # Check if any tool succeeded with a useful result
        if tool_results:
            for tr in tool_results:
                if tr.get("success") and tr.get("result"):
                    result = str(tr.get("result", ""))
                    if result and len(result) > 10 and "error" not in result.lower():
                        # We have a useful tool result - use it!
                        if len(result) > 600:
                            return result[:600] + "..."
                        return result
        # No useful tool results - give presence acknowledgment
        return "Я тут. Чим можу допомогти?"
    
    if not tool_results:
        if fallback_mode == "empty_response":
            return "Вибач, щось пішло не так. Спробуй ще раз."
        return "Вибач, не вдалося виконати запит."
    
    # Check what tools were used
    tool_names = [tr.get("name", "") for tr in tool_results]
    
    # Check if ANY tool succeeded
    any_success = any(tr.get("success") for tr in tool_results)
    if not any_success:
        # All tools failed - give helpful message
        errors = [tr.get("error", "unknown") for tr in tool_results if tr.get("error")]
        if errors:
            logger.warning(f"All tools failed: {errors}")
        return "Вибач, виникла технічна проблема. Спробуй ще раз або переформулюй питання."
    
    # Image generation - special handling
    if "image_generate" in tool_names:
        for tr in tool_results:
            if tr.get("name") == "image_generate" and tr.get("success"):
                return "✅ Зображення згенеровано!"
    
    # Web search - show actual results to user
    if "web_search" in tool_names:
        for tr in tool_results:
            if tr.get("name") == "web_search":
                if tr.get("success"):
                    result = tr.get("result", "")
                    if not result:
                        return "🔍 Не знайшов релевантної інформації в інтернеті."
                    
                    # Parse and format results for user
                    lines = result.strip().split("\n")
                    formatted = ["🔍 **Результати пошуку:**\n"]
                    current_title = ""
                    current_url = ""
                    current_snippet = ""
                    count = 0
                    
                    for line in lines:
                        line = line.strip()
                        if line.startswith("- ") and not line.startswith("- URL:"):
                            if current_title and count < 3:  # Show max 3 results
                                formatted.append(f"**{count}. {current_title}**")
                                if current_snippet:
                                    formatted.append(f"   {current_snippet[:150]}...")
                                if current_url:
                                    formatted.append(f"   🔗 {current_url}\n")
                            current_title = line[2:].strip()
                            current_snippet = ""
                            current_url = ""
                            count += 1
                        elif "URL:" in line:
                            current_url = line.split("URL:")[-1].strip()
                        elif line and not line.startswith("-"):
                            current_snippet = line
                    
                    # Add last result
                    if current_title and count <= 3:
                        formatted.append(f"**{count}. {current_title}**")
                        if current_snippet:
                            formatted.append(f"   {current_snippet[:150]}...")
                        if current_url:
                            formatted.append(f"   🔗 {current_url}")
                    
                    if len(formatted) > 1:
                        return "\n".join(formatted)
                    else:
                        return "🔍 Не знайшов релевантної інформації в інтернеті."
                else:
                    return "🔍 Пошук в інтернеті не вдався. Спробуй ще раз."
    
    # Memory search
    if "memory_search" in tool_names:
        for tr in tool_results:
            if tr.get("name") == "memory_search" and tr.get("success"):
                result = tr.get("result", "")
                if "немає інформації" in result.lower() or not result:
                    return "🧠 В моїй пам'яті немає інформації про це."
                # Truncate if too long
                if len(result) > 500:
                    return result[:500] + "..."
                return result
    
    # Graph query
    if "graph_query" in tool_names:
        for tr in tool_results:
            if tr.get("name") == "graph_query" and tr.get("success"):
                result = tr.get("result", "")
                if not result or "не знайдено" in result.lower():
                    return "📊 В базі знань немає інформації про це."
                if len(result) > 500:
                    return result[:500] + "..."
                return result
    
    # Default fallback - check if we have any result to show
    for tr in tool_results:
        if tr.get("success") and tr.get("result"):
            result = str(tr.get("result", ""))
            if result and len(result) > 10:
                # We have something, show it
                if len(result) > 400:
                    return result[:400] + "..."
                return result
    
    # Really nothing useful - be honest
    return "Я обробив твій запит, але не знайшов корисної інформації. Можеш уточнити питання?"