Refactor to v3.0.0: Modular architecture, advanced tools (Filesystem, Web, Python, Media), and professional REPL

src/ollama_cli/tools/media.py

@@ -0,0 +1,111 @@
+import subprocess
+import os
+import sys
+import requests
+import json
+import random
+from .base import tool
+from ..core.config import load_config
+
+@tool(
+    name="generate_image",
+    description="Generate an image using the local Stable Diffusion workflow (ComfyUI)",
+    parameters={
+        "prompt": {"type": "string", "description": "The image description"}
+    }
+)
+def generate_image(prompt: str) -> str:
+    """Invokes the ComfyUI API directly with a predefined workflow"""
+    config = load_config()
+    comfy_url = config.get("comfy_url", "http://127.0.0.1:8188").rstrip("/")
+    
+    try:
+        # Check if ComfyUI is running
+        try:
+            requests.get(comfy_url, timeout=2)
+        except:
+            return f"Error: ComfyUI server ({comfy_url}) appears to be down. Please start it first or configure the URL with '/config comfy <url>'."
+
+        # Define the workflow directly
+        # Based on the user's previous generate_image.py, but using the configured URL
+        workflow = {
+            "1": {
+                "inputs": {"ckpt_name": "dreamshaper_8.safetensors"},
+                "class_type": "CheckpointLoaderSimple"
+            },
+            "2": {
+                "inputs": {
+                    "text": f"masterpiece, best quality, highly detailed, {prompt}",
+                    "clip": ["1", 1]
+                },
+                "class_type": "CLIPTextEncode"
+            },
+            "3": {
+                "inputs": {
+                    "text": "blurry, low quality, distorted, watermark, nsfw",
+                    "clip": ["1", 1]
+                },
+                "class_type": "CLIPTextEncode"
+            },
+            "4": {
+                "inputs": {"width": 512, "height": 512, "batch_size": 1},
+                "class_type": "EmptyLatentImage"
+            },
+            "5": {
+                "inputs": {
+                    "seed": random.randint(1, 1000000000), "steps": 20, "cfg": 7.0,
+                    "sampler_name": "dpmpp_2m", "scheduler": "karras",
+                    "denoise": 1.0, "model": ["1", 0],
+                    "positive": ["2", 0], "negative": ["3", 0],
+                    "latent_image": ["4", 0]
+                },
+                "class_type": "KSampler"
+            },
+            "6": {
+                "inputs": {"samples": ["5", 0], "vae": ["1", 2]},
+                "class_type": "VAEDecode"
+            },
+            "7": {
+                "inputs": {
+                    "filename_prefix": "ollama_cli_",
+                    "images": ["6", 0]
+                },
+                "class_type": "SaveImage"
+            }
+        }
+        
+        payload = {"prompt": workflow}
+        response = requests.post(f"{comfy_url}/prompt", json=payload, timeout=10)
+        
+        if response.status_code == 200:
+            data = response.json()
+            prompt_id = data.get('prompt_id', 'unknown')
+            return f"Image generation queued successfully on {comfy_url}.\nPrompt ID: {prompt_id}\nCheck your ComfyUI output folder for 'ollama_cli_' prefixed files."
+        else:
+            return f"Error form ComfyUI: {response.status_code} - {response.text}"
+            
+    except Exception as e:
+        return f"Error generating image: {str(e)}"
+
+@tool(
+    name="speak_text",
+    description="Convert text to speech using Piper TTS",
+    parameters={
+        "text": {"type": "string", "description": "Text to speak"},
+        "output_file": {"type": "string", "description": "Output filename", "default": "output.wav"}
+    }
+)
+def speak_text(text: str, output_file: str = "output.wav") -> str:
+    """Uses local Piper installation if available"""
+    piper_bin = os.path.expanduser("~/piper/piper")
+    model_path = os.path.expanduser("~/piper/models/en_US-lessac-medium.onnx") # Guessing model path based on common setup
+    
+    # Fallback to simple 'say' command on macOS if piper is tricky to locate without scanning
+    if sys.platform == "darwin":
+        try:
+            subprocess.run(["say", "-o", output_file, text], check=True)
+            return f"Audio saved to {output_file} (using macOS 'say')"
+        except Exception as e:
+            return f"Error using 'say': {e}"
+            
+    return "TTS not configured for this platform yet."