Initial Code Commit

Project/app/api/buildings/route.ts

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+// @ts-nocheck
+import { NextResponse } from 'next/server';
+import { CosmosClient } from "@azure/cosmos";
+
+const cosmosClient = new CosmosClient({
+    endpoint: process.env.COSMOS_ENDPOINT!,
+    key: process.env.COSMOS_KEY!
+});
+
+const database = cosmosClient.database(process.env.COSMOS_DATABASE_ID!);
+const container = database.container(process.env.COSMOS_CONTAINER_ID!);
+
+export async function GET(request: Request) {
+    const { searchParams } = new URL(request.url);
+    const id = searchParams.get('id');
+
+    console.log("Received GET request with id:", id);
+
+    try {
+        if (id) {
+            // Get a single building
+            console.log("Attempting to get building with id:", id);
+
+            const querySpec = {
+                query: "SELECT * FROM c WHERE c.id = @id",
+                parameters: [{ name: "@id", value: id }]
+            };
+
+            const { resources } = await container.items.query(querySpec).fetchAll();
+            console.log("Query result:", resources);
+
+            if (resources && resources.length > 0) {
+                console.log("Returning resource for id:", id);
+                return NextResponse.json(resources[0]);
+            } else {
+                console.log("Building not found for id:", id);
+                return NextResponse.json({ message: "Building not found" }, { status: 404 });
+            }
+        } else {
+            // Get all buildings
+            console.log("Attempting to get all buildings");
+            const { resources } = await container.items.readAll().fetchAll();
+            console.log("Number of buildings retrieved:", resources.length);
+
+            return NextResponse.json(resources);
+        }
+    } catch (error) {
+        console.error("Error in GET request:", error);
+        return NextResponse.json({ message: "Error fetching data", error }, { status: 500 });
+    }
+}
+
+// function deepMerge(target: any, source: any) {
+//     for (const key in source) {
+//         if (Array.isArray(source[key])) {
+//             if (!target[key]) target[key] = [];
+//             target[key] = [...target[key], ...source[key]];
+//         } else if (source[key] instanceof Object && key in target) {
+//             deepMerge(target[key], source[key]);
+//         } else {
+//             target[key] = source[key];
+//         }
+//     }
+//     return target;
+// }
+
+export async function PATCH(request: Request) {
+    try {
+        const { id, operation, ...data } = await request.json();
+
+        // Query for the existing item
+        const querySpec = {
+            query: "SELECT * FROM c WHERE c.id = @id",
+            parameters: [{ name: "@id", value: id }]
+        };
+
+        const { resources } = await container.items.query(querySpec).fetchAll();
+
+        let existingItem = resources[0] || { id };
+
+        if (operation === 'deleteWasteEntry') {
+            // Remove the waste entry at the specified index
+            const index = data.index;
+            existingItem.wasteGeneration.splice(index, 1);
+        } else {
+            // Deep merge the existing data with the new data
+            existingItem = { ...existingItem, ...data };
+        }
+
+
+        // Upsert the item
+        const { resource: result } = await container.items.upsert(existingItem);
+
+        console.log("Update successful. Result:", result);
+
+        return NextResponse.json({ message: "Building updated successfully", result });
+    } catch (error) {
+        return NextResponse.json({ message: "Error updating data", error }, { status: 500 });
+    }
+}

Project/app/api/chat/route.ts

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+import { NextResponse } from 'next/server';
+
+export async function POST(request: Request) {
+    try {
+        const { imageURL, type } = await request.json();
+
+        if (!imageURL) {
+            return NextResponse.json({ error: "No image URL provided" }, { status: 400 });
+        }
+
+        const payload = {
+            messages: [
+                {
+                    role: "user",
+                    content: [
+                        {
+                            type: "text",
+                            text: ` Analyze the following ${type} bill image and extract the following information:
+                                        1. Multiple data points of usage, each with a date and ${type === 'gas' ? 'therms' : 'kWh'} used
+                                        2. Any other relevant usage data
+
+                                    Format the output as a JSON object with an array of data points and any additional data.
+                                    You must output valid JSON in the following format, or an empty array if no data is found:
+                                    {
+                                        "dataPoints": [
+                                            {
+                                                "date": "<ISO 8601 date string>",
+                                                "usage": <number>
+                                            },
+                                            // ... more data points
+                                        ]
+                                    }
+                            `
+                        },
+                        {
+                            type: "image_url",
+                            image_url: {
+                                url: imageURL
+                            }
+                        }
+                    ]
+                }
+            ],
+            temperature: 0.4,
+            top_p: 0.95,
+            max_tokens: 1000
+        };
+
+        const response = await fetch(process.env.AZURE_OPENAI_ENDPOINT as string, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+                'api-key': process.env.AZURE_OPENAI_KEY as string,
+            },
+            body: JSON.stringify(payload),
+        });
+
+        console.log('CHAT RESPONSE', response);
+
+        if (!response.ok) {
+            throw new Error('Failed to generate description: ' + response.status + " " + response.statusText);
+        }
+
+        const data = await response.json();
+        const description = data.choices[0].message.content;
+
+        console.log("CHAT DESCRIPTION", description);
+        return NextResponse.json({ response: description });
+    } catch (error) {
+        console.error('Error processing chat:', error);
+        return NextResponse.json({ error: (error as Error).message }, { status: 500 });
+    }
+}
+

Project/app/api/pdf-to-image/route.ts

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+// @ts-nocheck
+
+import { NextRequest, NextResponse } from 'next/server';
+
+import { toBase64 } from 'openai/core';
+
+export async function POST(request: NextRequest) {
+    try {
+        const formData = await request.formData();
+
+        let res = await fetch(process.env.PDF_URI, {
+            method: 'POST',
+            body: formData
+        });
+        res = await res.json();
+
+        const pdfBuffer = await res[0];
+
+        let b64 = await toBase64(pdfBuffer);
+        console.log(b64);
+        console.log(request);
+
+        // Step 2: Use the image with the chat route
+        const chatResponse = await fetch(process.env.PROD_URL + '/api/chat', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                imageURL: `data:image/png;base64,${b64}`,
+                type: formData.get('type'),
+            }),
+        });
+
+        const chatData = await chatResponse.json();
+        console.log("CHAT RESPONSE", chatData);
+
+        return NextResponse.json({ message: 'PDF converted successfully', response: chatData });
+    } catch (error) {
+        console.error('Error processing PDF:', error);
+        return NextResponse.json({ error: 'Failed to process PDF' }, { status: 500 });
+    }
+}