feat: frigate-notify v2 (modular app, CLIP recognition) + clip-service

Splits the single main.py into config/database/models/routes/vision/recognition/
ollama_client/cleanup modules, adds a web UI, and introduces clip-service for
CLIP (ViT-L-14) embeddings.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

compose/hf-pdocker-01/frigate-notify/app/ollama_client.py

@@ -0,0 +1,132 @@
+"""Ollama vision LLM client for frigate-notify v2."""
+
+import base64
+import logging
+
+import aiohttp
+
+logger = logging.getLogger(__name__)
+
+
+class OllamaClient:
+    """Client for Ollama vision models (e.g., llava)."""
+
+    def __init__(self, base_url: str, model: str):
+        self.base_url = base_url.rstrip("/")
+        self.model = model
+
+    async def analyze_image(self, image_bytes: bytes, prompt: str) -> str | None:
+        """Send an image to Ollama for analysis.
+
+        Args:
+            image_bytes: Raw image bytes (JPEG).
+            prompt: Text prompt for the vision model.
+
+        Returns:
+            Response text or None on failure.
+        """
+        b64 = base64.b64encode(image_bytes).decode("utf-8")
+        payload = {
+            "model": self.model,
+            "prompt": prompt,
+            "images": [b64],
+            "stream": False,
+            "options": {"num_predict": 200},
+        }
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    f"{self.base_url}/api/generate",
+                    json=payload,
+                    timeout=aiohttp.ClientTimeout(total=30),
+                ) as resp:
+                    if resp.status == 200:
+                        data = await resp.json()
+                        text = data.get("response", "").strip()
+                        logger.info(
+                            "Ollama analysis complete: %d chars", len(text)
+                        )
+                        return text if text else None
+                    body = await resp.text()
+                    logger.error(
+                        "Ollama analyze_image failed %s: %s", resp.status, body
+                    )
+        except Exception:
+            logger.exception("Ollama analyze_image request failed")
+        return None
+
+    async def compare_images(
+        self,
+        image_bytes: bytes,
+        reference_bytes: bytes,
+        object_name: str,
+    ) -> bool | None:
+        """Compare two images to determine if they show the same object/person.
+
+        Args:
+            image_bytes: The new event image bytes.
+            reference_bytes: The reference (known) image bytes.
+            object_name: Name of the known object for context.
+
+        Returns:
+            True if same, False if different, None on failure/inconclusive.
+        """
+        b64_new = base64.b64encode(image_bytes).decode("utf-8")
+        b64_ref = base64.b64encode(reference_bytes).decode("utf-8")
+        prompt = (
+            f"Look at these two images. The first image is from a security camera. "
+            f"The second image is a reference photo of '{object_name}'. "
+            f"Are these the same person/vehicle/animal? "
+            f"Answer with ONLY 'yes' or 'no'."
+        )
+        payload = {
+            "model": self.model,
+            "prompt": prompt,
+            "images": [b64_new, b64_ref],
+            "stream": False,
+            "options": {"num_predict": 200},
+        }
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    f"{self.base_url}/api/generate",
+                    json=payload,
+                    timeout=aiohttp.ClientTimeout(total=30),
+                ) as resp:
+                    if resp.status == 200:
+                        data = await resp.json()
+                        text = data.get("response", "").strip().lower()
+                        logger.info("Ollama compare result: %s", text)
+                        if "yes" in text.split()[:3]:
+                            return True
+                        if "no" in text.split()[:3]:
+                            return False
+                        logger.warning(
+                            "Ollama compare inconclusive: %s", text
+                        )
+                        return None
+                    body = await resp.text()
+                    logger.error(
+                        "Ollama compare_images failed %s: %s",
+                        resp.status,
+                        body,
+                    )
+        except Exception:
+            logger.exception("Ollama compare_images request failed")
+        return None
+
+    async def is_available(self) -> bool:
+        """Check if Ollama is reachable and responding.
+
+        Returns:
+            True if Ollama responds with HTTP 200, False otherwise.
+        """
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.get(
+                    f"{self.base_url}/api/tags",
+                    timeout=aiohttp.ClientTimeout(total=3),
+                ) as resp:
+                    return resp.status == 200
+        except Exception:
+            return False