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import {generateObject, LanguageModel, tool} from "npm:ai"
import {openai} from "npm:@ai-sdk/openai"
import {google} from "npm:@ai-sdk/google"
import {
  constructor(provider?: AIProvider) {
    const envProvider = Deno.env.get("AI_PROVIDER") as AIProvider | undefined
    this.provider = provider || envProvider || "openai"
    if (this.provider === "openai") {
      if (!Deno.env.get("OPENAI_API_KEY")) {
        console.warn("OPENAI_API_KEY environment variable not set. OpenAI calls may fail.")
      }
      this.model = openai("gpt-4o") as LanguageModel
    } else if (this.provider === "gemini") {
      if (!Deno.env.get("GOOGLE_GENERATIVE_AI_API_KEY") && !Deno.env.get("GOOGLE_API_KEY")) {

    "npm:@ai-sdk/google@*": "0.0.23_zod@3.23.8",
    "npm:@ai-sdk/google@0.0.23": "0.0.23_zod@3.23.8",
    "npm:@ai-sdk/openai@*": "0.0.36_zod@3.23.8",
    "npm:@ai-sdk/openai@0.0.36": "0.0.36_zod@3.23.8",
    "npm:@libsql/client@*": "0.15.6",
    "npm:@types/node@*": "22.12.0",
      ]
    },
    "@ai-sdk/openai@0.0.36_zod@3.23.8": {
      "integrity": "sha512-6IcvR35UMuuQEQPkVjzUtqDAuz6vy+PMCEL0PAS2ufHXdPPm81OTKVetqjgOPjebsikhVP0soK1pKPEe2cztAQ==",
      "dependencies": [

import { Hono } from "https://esm.sh/hono@3.11.7";
import { cors } from "https://esm.sh/hono@3.11.7/middleware";
import { OpenAI } from "https://esm.town/v/std/openai";
import { readFile, serveFile } from "https://esm.town/v/std/utils@85-main/index.ts";
    }
    const openai = new OpenAI();
    
    try {
      const completion = await openai.chat.completions.create({
        model: "gpt-4o-mini",
        messages: [
        enhancedPrompt 
      });
    } catch (openaiError) {
      console.error("OpenAI API error:", openaiError);
      return c.json({ 
        error: "OpenAI service error", 
        message: "There was an issue with the AI service. Please try again later." 
      }, 503);

- Simple, clean interface for entering prompts
- AI-powered enhancement using OpenAI
- Before/after comparison
- Copy-to-clipboard functionality
1. Enter your basic prompt in the input area
2. Click "Enhance Prompt" 
3. The application uses OpenAI to analyze and improve your prompt
4. View the enhanced version and copy it for use with your preferred AI system
- Frontend: HTML, JavaScript with Tailwind CSS for styling
- Backend: TypeScript API using Hono framework and OpenAI integration
- Deployed on Val Town

import { Hono } from "https://esm.sh/hono@3.11.7";
import { OpenAI } from "https://esm.town/v/std/openai";
import { readFile, serveFile } from "https://esm.town/v/std/utils@85-main/index.ts";
import { parseProject } from "https://esm.town/v/std/utils@85-main/index.ts";
    }
    const openai = new OpenAI();
    // Create different prompts based on the content type
    }
    const completion = await openai.chat.completions.create({
      messages: [
        {

import { OpenAI } from "https://esm.town/v/std/openai";
import { readFile } from "https://esm.town/v/std/utils@85-main/index.ts";
import { LicenseInfo, ScanResponse } from "../shared/types.ts";
      const dataURI = `data:${imageFile.type};base64,${base64Image}`;
      
      // Process with OpenAI
      const licenseInfo = await extractLicenseInfo(dataURI);
      
/**
 * Extracts license information from an image using OpenAI's Vision capabilities
 */
async function extractLicenseInfo(imageDataUri: string): Promise<LicenseInfo> {
  const openai = new OpenAI();
  
  const response = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [
    return JSON.parse(jsonString) as LicenseInfo;
  } catch (error) {
    console.error("Error parsing OpenAI response:", error);
    return { rawText: content };
  }

    
    <footer class="mt-12 text-center text-sm text-gray-500">
      <p>This application processes images using OpenAI's API. Images are not stored permanently.</p>
      <p class="mt-1">
        <a 

1. Upload an image of a driver's license
2. The application uses OpenAI's Vision capabilities to analyze the image
3. The extracted information is returned in a structured JSON format
## Privacy Notice
This application processes images using OpenAI's API. Images are not stored permanently but are transmitted to OpenAI for processing. Please ensure you have appropriate consent before uploading any personal identification documents.

import { OpenAI } from "https://esm.town/v/std/openai";
import { readFile } from "https://esm.town/v/std/utils@85-main/index.ts";
// Initialize OpenAI client
const openai = new OpenAI();
// Medical analysis prompt to guide the AI
    const dataURI = `data:${imageFile.type};base64,${base64Image}`;
    // Send the image to OpenAI for analysis
    const response = await openai.chat.completions.create({
      model: "gpt-4-vision-preview",
      messages: [
    });
    // Extract the analysis from OpenAI's response
    const analysis = response.choices[0]?.message?.content || "Analysis failed";

1. Users upload a medical image through the web interface
2. The image is sent to OpenAI's Vision API with specific medical analysis prompts
3. The AI analyzes the image and provides potential diagnoses or observations
4. Results are displayed to the user
- Frontend: HTML, JavaScript, and TailwindCSS for styling
- Backend: TypeScript with Val Town's HTTP trigger
- AI: OpenAI's Vision API for image analysis
## Limitations