feat: Initialize AutoForm AI project structure

Sets up the basic project structure for AutoForm AI, including:
- Vite for build tooling and development server.
- React and ReactDOM for the UI.
- TypeScript for static typing.
- Essential dependencies for PDF manipulation (jspdf, pdf-lib) and AI integration (@google/genai).
- Basic HTML structure and styling.
- Component definitions and service interfaces for future development.
- A README with local development instructions.

services/geminiService.ts

@@ -0,0 +1,161 @@
+import { GoogleGenAI, Type, Schema } from "@google/genai";
+import { FileData, FormResponse } from "../types";
+import { PdfFieldInfo } from "./pdfService";
+
+const ai = new GoogleGenAI({ apiKey: process.env.API_KEY });
+
+const responseSchema: Schema = {
+  type: Type.OBJECT,
+  properties: {
+    summary: {
+      type: Type.STRING,
+      description: "A brief summary of what document was processed."
+    },
+    fields: {
+      type: Type.ARRAY,
+      items: {
+        type: Type.OBJECT,
+        properties: {
+          key: {
+            type: Type.STRING,
+            description: "The PDF field name (if available)."
+          },
+          label: {
+            type: Type.STRING,
+            description: "A human-readable label for the field."
+          },
+          value: {
+            type: Type.STRING,
+            description: "The value to fill. For checkboxes, use 'true'/'false' or 'X'."
+          },
+          sourceContext: {
+            type: Type.STRING,
+            description: "The exact snippet of text from the source document used to derive this value. Used for user verification."
+          },
+          coordinates: {
+            type: Type.OBJECT,
+            description: "REQUIRED if no specific PDF field names are provided. Visual location to draw text.",
+            properties: {
+              pageIndex: { type: Type.INTEGER, description: "0-based page index" },
+              x: { type: Type.INTEGER, description: "Horizontal position (0-1000) from Left" },
+              y: { type: Type.INTEGER, description: "Vertical position (0-1000) from Top" }
+            },
+            required: ["pageIndex", "x", "y"]
+          },
+          validation: {
+             type: Type.OBJECT,
+             properties: {
+                status: {
+                  type: Type.STRING,
+                  description: "VALID, WARNING, or INVALID."
+                },
+                message: {
+                  type: Type.STRING,
+                  description: "Validation message explaining any issues or uncertainty."
+                },
+                suggestion: {
+                  type: Type.STRING,
+                  description: "Alternative value suggestion if the extracted value is uncertain."
+                }
+             },
+             required: ["status"]
+          }
+        },
+        required: ["label", "value", "validation"]
+      }
+    }
+  },
+  required: ["fields", "summary"]
+};
+
+export const processDocuments = async (
+  blankForm: FileData,
+  sourceDocument: FileData,
+  pdfFields: PdfFieldInfo[] = []
+): Promise<FormResponse> => {
+  
+  const formPart = {
+    inlineData: {
+      data: blankForm.base64,
+      mimeType: blankForm.type,
+    },
+  };
+
+  const sourcePart = {
+    inlineData: {
+      data: sourceDocument.base64,
+      mimeType: sourceDocument.type,
+    },
+  };
+
+  let systemPrompt = `
+    ROLE: Intelligent Document Processing AI (Verification Expert).
+    TASK: Extract data from the SOURCE DOCUMENT and map it to the BLANK TARGET FORM.
+    
+    CRITICAL INSTRUCTION: You must verify every extraction. If a value is ambiguous, plausibility is low, or you are guessing, set validation.status to 'WARNING' and explain why in validation.message.
+  `;
+
+  if (pdfFields.length > 0) {
+    const fieldList = pdfFields.map(f => `"${f.name}" (${f.type})`).join(", ");
+    systemPrompt += `
+      MODE: FILLABLE PDF (AcroForm).
+      The target form has specific embedded fields.
+      Map extracted data to these exact field IDs: [${fieldList}].
+      Return the 'key' property matching the field ID.
+    `;
+  } else {
+    systemPrompt += `
+      MODE: VISUAL FILLING (Flat/XFA/Scan).
+      The target form DOES NOT have accessible digital fields.
+      You must VISUALLY locate where the text should be written.
+      
+      For every field you identify on the TARGET FORM:
+      1. Extract the corresponding value from the SOURCE DOCUMENT.
+      2. Estimate the VISUAL COORDINATES [pageIndex, x, y] where the text should start.
+         - 'x' and 'y' are on a scale of 0 to 1000.
+         - (0,0) is the top-left corner of the page.
+         - (1000,1000) is the bottom-right corner.
+         - Align text slightly above lines or inside boxes.
+      
+      For checkboxes: If true/yes, the value should be "X" placed inside the box.
+    `;
+  }
+
+  systemPrompt += `
+    VALIDATION RULES:
+    1. Dates: Ensure format matches the form (e.g. DD.MM.YYYY).
+    2. Checkboxes: Only mark if explicitly supported by source.
+    3. Missing Data: If a field is not found in source, leave 'value' empty and set status 'VALID'. Do not hallucinate.
+    4. Source Context: Always populate 'sourceContext' with the exact text snippet from the source document that justifies your extraction.
+  `;
+
+  try {
+    const modelId = "gemini-3-flash-preview";
+
+    const response = await ai.models.generateContent({
+      model: modelId,
+      contents: {
+        parts: [
+          formPart, 
+          { text: "This is the BLANK TARGET FORM." },
+          sourcePart,
+          { text: "This is the SOURCE DOCUMENT." },
+        ]
+      },
+      config: {
+        responseMimeType: "application/json",
+        responseSchema: responseSchema,
+        systemInstruction: systemPrompt
+      }
+    });
+
+    const text = response.text;
+    if (!text) throw new Error("No response from Gemini");
+
+    return JSON.parse(text) as FormResponse;
+
+  } catch (error) {
+    console.error("Gemini API Error:", error);
+    throw error;
+  }
+};