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src/lib/image-describer.ts

@@ -0,0 +1,66 @@
+import fs from 'fs';
+import path from 'path';
+import dotenv from 'dotenv';
+import { logger } from './logger';
+
+dotenv.config();
+
+const LLM_BASE_URL = process.env.LLM_BASE_URL;
+
+async function describeImage(imagePath: string, prompt: string): Promise<any> {
+    if (!LLM_BASE_URL) {
+        throw new Error('LLM_BASE_URL is not defined in the .env file');
+    }
+
+    const imageBuffer = fs.readFileSync(imagePath);
+    const base64Image = imageBuffer.toString('base64');
+
+    for (let i = 0; i < 10; i++) {
+        let llmResponse = "";
+
+        try {
+            const requestUrl = new URL('v1/chat/completions', LLM_BASE_URL);
+            const response = await fetch(requestUrl, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({
+                    model: 'local-model',
+                    messages: [
+                        {
+                            role: 'user',
+                            content: [
+                                { type: 'image_url', image_url: { url: `data:image/jpeg;base64,${base64Image}` } },
+                                { type: 'text', text: prompt },
+                            ],
+                        },
+                    ],
+                    temperature: 0.7,
+                }),
+            });
+
+            const data = await response.json();
+            if (data.choices && data.choices.length > 0) {
+                const content = data.choices[0].message.content;
+                llmResponse = content;
+                const jsonMatch = content.match(/\{[\s\S]*\}/);
+                if (jsonMatch) {
+                    return JSON.parse(jsonMatch[0]);
+                }
+            } else {
+                logger.error('Unexpected API response:', data);
+            }
+        } catch (error) {
+            logger.error(`Attempt ${i + 1} failed:`, error);
+            if (error instanceof TypeError && error.message.includes('fetch failed')) {
+                logger.error('Could not connect to the LM Studio server. Please ensure the server is running and accessible at the specified LLM_BASE_URL.');
+            }
+            logger.debug(`LLM response: ${llmResponse}`)
+        }
+    }
+
+    throw new Error('Failed to describe image after 10 attempts');
+}
+
+export { describeImage };