Adjust folder structure for HACS

.gitignore

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+__pycache__

custom_components/README.md

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+# hass_ollama_image_analysis
+Image analysis with Ollama (AI models) from within Home Assistant

custom_components/__init__.py

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+"""Ollama (local AI models) image analysis integration"""
+
+import voluptuous as vol
+
+from homeassistant.core import (
+    Config,
+    HomeAssistant,
+    ServiceCall,
+    SupportsResponse,
+    ServiceResponse,
+)
+
+from homeassistant.config_entries import ConfigEntry
+
+from ollama import AsyncClient
+
+import pybase64
+import aiofiles
+
+DOMAIN = "ollama_image_analysis"
+
+OLLAMA_IMAGE_ANALYSIS_SERVICE_NAME = "ollama_image_analysis"
+OLLAMA_IMAGE_ANALYSIS_SCHEMA = vol.Schema(
+    {
+        vol.Required("prompt"): str,
+        vol.Required("model"): str,
+        vol.Required("image_path"): str,
+    }
+)
+
+
+async def read_binary_file(file_name):
+    try:
+        async with aiofiles.open(file_name, "r") as f:
+            return await f.read()
+    except FileNotFoundError:
+        print(f"The file {file_name} was not found.")
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+
+async def async_setup_entry(hass: HomeAssistant, config: ConfigEntry) -> bool:
+    """Setup up a config entry."""
+
+    async def ollama_image_analysis(call: ServiceCall) -> ServiceResponse:
+        config_dict = config.as_dict()
+
+        # load the call parameters
+        prompt = call.data["prompt"]
+        image_path = call.data["image_path"]
+        model = call.data.get("model", "llava")
+
+        host = config_dict["data"]["host"]
+
+        client = AsyncClient(host=host)
+
+        binary_image = await read_binary_file("/workspaces/hass_core" + image_path)
+
+        # b64encoded_binary_image = await pybase64.b64encode(binary_image)
+
+        # make the call to ollama
+        response = await client.chat(
+            model=model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": prompt,
+                    "image": binary_image,
+                },
+            ],
+        )
+
+        print("Rückmeldung von Modell: ", response["message"]["content"])
+
+        return {
+            "items": [
+                {
+                    "result": response["message"]["content"],
+                }
+            ],
+        }
+
+    hass.services.async_register(
+        DOMAIN,
+        OLLAMA_IMAGE_ANALYSIS_SERVICE_NAME,
+        ollama_image_analysis,
+        schema=OLLAMA_IMAGE_ANALYSIS_SCHEMA,
+        supports_response=SupportsResponse.ONLY,
+    )
+
+    return True

custom_components/config_flow.py

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+"""Config flow for Ollama (local AI models) image analysis integration."""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+import re
+
+import voluptuous as vol
+
+from homeassistant.config_entries import ConfigFlow, ConfigFlowResult
+from homeassistant.const import CONF_HOST
+from homeassistant.core import HomeAssistant, HomeAssistantError
+
+from .const import DOMAIN
+
+_LOGGER = logging.getLogger(__name__)
+
+STEP_USER_DATA_SCHEMA = vol.Schema({vol.Required(CONF_HOST): str})
+
+
+async def validate_input(hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]:
+    """Validate the user input allows us to connect.
+
+    Data has the keys from STEP_USER_DATA_SCHEMA with values provided by the user.
+    """
+
+    # If your PyPI package is not built with async, pass your methods
+    # to the executor:
+    # await hass.async_add_executor_job(
+    #     your_validate_func, data[CONF_USERNAME], data[CONF_PASSWORD]
+    # )
+
+    p = "(?:http.*://)(?P<host>[^:/ ]+).?(?P<port>[0-9]*).*"
+
+    result = re.match(p, data[CONF_HOST])
+
+    if not result:
+        raise InvalidUrlScheme
+
+    # Return info that you want to store in the config entry.
+    return {"host": data[CONF_HOST]}
+
+
+class ConfigFlow(ConfigFlow, domain=DOMAIN):
+    """Handle a config flow for Ollama (local AI models) image analysis."""
+
+    VERSION = 1
+
+    async def async_step_user(
+        self, user_input: dict[str, Any] | None = None
+    ) -> ConfigFlowResult:
+        """Handle the initial step."""
+        errors: dict[str, str] = {}
+        if user_input is not None:
+            try:
+                await validate_input(self.hass, user_input)
+            except InvalidUrlScheme:
+                errors["base"] = "invalid_url_scheme"
+            except Exception:
+                _LOGGER.exception("Unexpected exception")
+                errors["base"] = "unknown"
+            else:
+                return self.async_create_entry(
+                    title="Ollama (local AI models) image analysis", data=user_input
+                )
+
+        return self.async_show_form(
+            step_id="user", data_schema=STEP_USER_DATA_SCHEMA, errors=errors
+        )
+
+
+class InvalidUrlScheme(HomeAssistantError):
+    """Error to indicate we cannot connect."""

custom_components/const.py

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+"""Constants for the Ollama (local AI models) image analysis integration."""
+
+DOMAIN = "ollama_image_analysis"

custom_components/icons.json

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+{
+    "services": {
+        "ollama_image_analysis": "mdi:image-auto-adjust"
+    }
+}

custom_components/manifest.json

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+{
+  "domain": "ollama_image_analysis",
+  "name": "Ollama (local AI models) image analysis",
+  "version": "0.1.0",
+  "codeowners": [
+    "@the-smart-home-maker"
+  ],
+  "config_flow": true,
+  "single_config_entry": true,
+  "dependencies": [],
+  "documentation": "https://github.com/the-smart-home-maker/hass_ollama_image_analysis",
+  "issue_tracker": "https://github.com/the-smart-home-maker/hass_ollama_image_analysis/issues",
+  "homekit": {},
+  "iot_class": "local_polling",
+  "integration_type": "service",
+  "requirements": [
+    "ollama==0.2.1",
+    "pybase64==1.3.2",
+    "aiofiles"
+  ],
+  "ssdp": [],
+  "zeroconf": []
+}

custom_components/services.yaml

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+ollama_image_analysis:
+  name: Analyze camera image with local AI based upon Ollama
+  description: Analyze a camera image with a local AI model (e.g. llava) based upon Ollama
+  fields:
+    prompt:
+      description: The prompt describing how to analyze the image
+      example: |
+        You are a security agent and analyze the following camera image. Your focus is to identify irregularities. Please list all irregularities.
+      required: true
+      selector:
+        text:
+          multiline: true
+    image_path:
+      description: This should be the path to a snapshot image taken from your camera which shall be analyzed.
+      example: /x/y/camera_image.jpg
+      required: true
+      selector:
+        text:
+    model:
+      description: Choose which model to use. Defaults to llava.
+      example: llava
+      default: llava
+      required: false
+      selector:
+        text:

custom_components/strings.json

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+{
+  "config": {
+    "step": {
+      "user": {
+        "data": {
+          "host": "[%key:common::config_flow::data::host%]",
+          "username": "[%key:common::config_flow::data::username%]",
+          "password": "[%key:common::config_flow::data::password%]"
+        }
+      }
+    },
+    "error": {
+      "cannot_connect": "[%key:common::config_flow::error::cannot_connect%]",
+      "invalid_auth": "[%key:common::config_flow::error::invalid_auth%]",
+      "unknown": "[%key:common::config_flow::error::unknown%]"
+    },
+    "abort": {
+      "already_configured": "[%key:common::config_flow::abort::already_configured_device%]"
+    }
+  }
+}

custom_components/translations/en.json

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+{
+    "config": {
+        "abort": {
+            "already_configured": "Device is already configured"
+        },
+        "error": {
+            "unknown": "Unexpected error",
+            "invalid_url_scheme": "Invalid URL scheme"
+        },
+        "step": {
+            "user": {
+                "data": {
+                    "host": "Host"
+                }
+            }
+        }
+    }
+}