Initial commit

hooks/post_tool_use_elevenlabs.py

@@ -0,0 +1,207 @@
+#!/usr/bin/env -S uv run --script
+# /// script
+# requires-python = ">=3.11"
+# dependencies = [
+#     "python-dotenv",
+#     "openai",
+# ]
+# ///
+
+import json
+import sys
+import subprocess
+import os
+from pathlib import Path
+from datetime import datetime
+
+try:
+    from dotenv import load_dotenv
+    load_dotenv()
+except ImportError:
+    pass
+
+def get_simple_summary(tool_name, tool_input, tool_response):
+    """
+    Create a simple summary without LLM first
+    """
+    if tool_name == "Task":
+        # Extract task description
+        task_desc = ""
+        if "prompt" in tool_input:
+            task_desc = tool_input['prompt']
+        elif "description" in tool_input:
+            task_desc = tool_input['description']
+        
+        # Extract agent name if present
+        if ':' in task_desc:
+            parts = task_desc.split(':', 1)
+            agent_name = parts[0].strip()
+            task_detail = parts[1].strip() if len(parts) > 1 else ""
+            # Shorten task detail
+            if len(task_detail) > 30:
+                task_detail = task_detail[:30] + "..."
+            return f"{agent_name} completed {task_detail}"
+        return "Agent task completed"
+    
+    elif tool_name == "Write":
+        file_path = tool_input.get("file_path", "")
+        if file_path:
+            file_name = Path(file_path).name
+            return f"Created {file_name}"
+        return "File created"
+    
+    elif tool_name in ["Edit", "MultiEdit"]:
+        file_path = tool_input.get("file_path", "")
+        if file_path:
+            file_name = Path(file_path).name
+            return f"Updated {file_name}"
+        return "File updated"
+    
+    return f"{tool_name} completed"
+
+def get_ai_summary(tool_name, tool_input, tool_response):
+    """
+    Use OpenAI to create a better summary
+    """
+    api_key = os.getenv("OPENAI_API_KEY")
+    if not api_key:
+        return None
+    
+    try:
+        from openai import OpenAI
+        client = OpenAI(api_key=api_key)
+        
+        # Build context
+        context = f"Tool: {tool_name}\n"
+        
+        if tool_name == "Task":
+            task_desc = tool_input.get("prompt", tool_input.get("description", ""))
+            context += f"Task: {task_desc}\n"
+            if tool_response and "output" in tool_response:
+                # Truncate output if too long
+                output = str(tool_response["output"])[:200]
+                context += f"Result: {output}\n"
+        
+        elif tool_name == "Write":
+            file_path = tool_input.get("file_path", "")
+            context += f"File: {file_path}\n"
+            context += "Action: Created new file\n"
+        
+        elif tool_name in ["Edit", "MultiEdit"]:
+            file_path = tool_input.get("file_path", "")
+            context += f"File: {file_path}\n"
+            context += "Action: Modified existing file\n"
+        
+        prompt = f"""Create a 3-7 word summary of this tool completion for voice announcement.
+Be specific about what was accomplished.
+
+{context}
+
+Examples of good summaries:
+- "Created user authentication module"
+- "Updated API endpoints"
+- "Documentation generator built"
+- "Fixed validation errors"
+- "Database schema created"
+
+Summary:"""
+        
+        response = client.chat.completions.create(
+            model="gpt-5-nano",
+            messages=[{"role": "user", "content": prompt}],
+            max_completion_tokens=15,
+        )
+        
+        summary = response.choices[0].message.content.strip()
+        # Remove quotes if present
+        summary = summary.strip('"').strip("'")
+        return summary
+        
+    except Exception as e:
+        print(f"AI summary error: {e}", file=sys.stderr)
+        return None
+
+def announce_with_tts(summary):
+    """
+    Use ElevenLabs Sarah voice for all announcements (high quality, consistent)
+    Falls back to macOS say if ElevenLabs fails.
+    """
+    script_dir = Path(__file__).parent
+    tts_dir = script_dir / "utils" / "tts"
+    elevenlabs_script = tts_dir / "elevenlabs_tts.py"
+
+    try:
+        result = subprocess.run(
+            ["uv", "run", str(elevenlabs_script), summary],
+            capture_output=True,
+            timeout=10
+        )
+        if result.returncode == 0:
+            return "elevenlabs"
+        else:
+            # ElevenLabs failed, use macOS fallback
+            subprocess.run(["say", summary], timeout=5)
+            return "macos-fallback"
+    except:
+        # Last resort fallback
+        try:
+            subprocess.run(["say", summary], timeout=5)
+            return "macos-fallback"
+        except:
+            return "none"
+
+def main():
+    try:
+        # Read input
+        input_data = json.load(sys.stdin)
+        tool_name = input_data.get("tool_name", "")
+        tool_input = input_data.get("tool_input", {})
+        tool_response = input_data.get("tool_response", {})
+        
+        # Skip certain tools
+        if tool_name in ["TodoWrite", "Grep", "LS", "Bash", "Read", "Glob", "WebFetch", "WebSearch"]:
+            sys.exit(0)
+        
+        # Try AI summary first, fall back to simple summary
+        summary = get_ai_summary(tool_name, tool_input, tool_response)
+        if not summary:
+            summary = get_simple_summary(tool_name, tool_input, tool_response)
+        
+        # Announce with TTS (ElevenLabs or local)
+        tts_method = announce_with_tts(summary)
+        
+        # Log what we announced
+        log_dir = os.path.join(os.getcwd(), "logs")
+        if os.path.exists(log_dir):
+            log_path = os.path.join(log_dir, "voice_announcements.json")
+            logs = []
+            if os.path.exists(log_path):
+                try:
+                    with open(log_path, 'r') as f:
+                        logs = json.load(f)
+                except:
+                    logs = []
+            
+            logs.append({
+                "timestamp": datetime.now().isoformat(),
+                "tool": tool_name,
+                "summary": summary,
+                "ai_generated": bool(get_ai_summary(tool_name, tool_input, tool_response)),
+                "tts_method": tts_method
+            })
+            
+            # Keep last 50
+            logs = logs[-50:]
+            
+            with open(log_path, 'w') as f:
+                json.dump(logs, f, indent=2)
+        
+        print(f"Announced via {tts_method}: {summary}")
+        sys.exit(0)
+        
+    except Exception as e:
+        print(f"Hook error: {e}", file=sys.stderr)
+        sys.exit(0)
+
+if __name__ == "__main__":
+    main()