API Use Cases

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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "openai/gpt-5-mini",
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    messages: [
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      {
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        role: "system",
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        content: "You are a helpful support agent for Acme Corp. " +
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          "Answer questions about our products, pricing, and policies. " +
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          "If you can't help, offer to connect the user to a human agent."
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      },
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      { role: "user", content: customerMessage }
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    ],
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    temperature: 0.3,
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  }),
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});
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const data = await response.json();
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console.log(data.choices[0].message.content);

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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "openai/gpt-5",
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    messages: [
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      {
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        role: "system",
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        content: "You are an expert content writer. Write SEO-optimized " +
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          "blog posts with proper heading structure (H2, H3), meta " +
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          "descriptions, and natural keyword placement."
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      },
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      {
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        role: "user",
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        content: `Write a 1500-word blog post about "${topic}".
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Target keyword: ${keyword}
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Tone: professional but approachable
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Include: introduction, 4 sections with H2 headings, conclusion, meta description`
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      }
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    ],
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    temperature: 0.7,
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    max_tokens: 4000,
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  }),
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});
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const article = (await response.json()).choices[0].message.content;

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const response = await fetch("https://api.vincony.com/v1/generate-image", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    prompt: "A sleek wireless headphone on a marble surface, " +
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      "soft studio lighting, product photography, 4K, minimalist",
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    width: 1024,
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    height: 1024,
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    model: "flux-pro",
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  }),
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});
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const { image_url } = await response.json();
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console.log("Generated image:", image_url);

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const response = await fetch("https://api.vincony.com/v1/generate-video", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    prompt: "A smooth camera orbit around a luxury watch on a " +
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      "dark velvet surface, cinematic lighting, 5 seconds",
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  }),
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});
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const { video_url, status } = await response.json();
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// Poll for completion if status === "processing"
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console.log("Video:", video_url);

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const response = await fetch("https://api.vincony.com/v1/text-to-speech", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    text: "Welcome back! You have 3 new notifications today.",
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    voice: "nova",  // alloy, echo, fable, onyx, nova, shimmer
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  }),
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});
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const { audio_url } = await response.json();
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// Play audio or download
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const audio = new Audio(audio_url);
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audio.play();

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const response = await fetch("https://api.vincony.com/v1/extract-data", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    url: "https://example.com/product/wireless-earbuds",
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    schema: {
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      product_name: "string",
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      price: "number",
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      currency: "string",
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      rating: "number",
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      features: "string[]",
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      in_stock: "boolean",
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    },
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  }),
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});
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const structured = await response.json();
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// { product_name: "Pro Earbuds X3", price: 79.99, ... }

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const response = await fetch("https://api.vincony.com/v1/ai-search", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    query: "Best practices for React Server Components in 2026",
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  }),
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});
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const { answer, sources } = await response.json();
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console.log("Answer:", answer);
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console.log("Sources:", sources.map(s => s.url));

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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "openai/gpt-5-mini",
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    messages: [{
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      role: "user",
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      content: `Generate an Amazon product listing for:
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Product: ${productName}
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Features: ${features.join(", ")}
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Target audience: ${audience}
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Return JSON with: title, bullet_points (5), description, search_terms`
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    }],
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    temperature: 0.6,
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  }),
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});
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const listing = (await response.json()).choices[0].message.content;

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// Batch personalize emails for a list of prospects
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const emails = await Promise.all(
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  prospects.map(async (prospect) => {
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    const response = await fetch("https://api.vincony.com/v1/chat", {
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      method: "POST",
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      headers: {
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        "Authorization": "Bearer YOUR_API_KEY",
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        "Content-Type": "application/json",
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      },
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      body: JSON.stringify({
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        model: "openai/gpt-5-mini",
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        messages: [{
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          role: "user",
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          content: `Write a personalized sales email.
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Recipient: ${prospect.name}, ${prospect.title} at ${prospect.company}
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Our product: ${productDescription}
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Tone: professional, concise, no more than 150 words
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Include a specific pain point relevant to their industry: ${prospect.industry}`
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        }],
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        temperature: 0.8,
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      }),
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    });
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    return {
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      to: prospect.email,
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      body: (await response.json()).choices[0].message.content,
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    };
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  })
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);

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const analyticsData = await getWeeklyMetrics(); // your data source
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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "openai/gpt-5",
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    messages: [
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      {
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        role: "system",
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        content: "You are a senior data analyst. Summarize metrics " +
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          "into an executive brief with: key highlights, trends, " +
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          "anomalies, and 3 actionable recommendations."
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      },
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      {
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        role: "user",
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        content: `Weekly metrics (JSON):\n${JSON.stringify(analyticsData, null, 2)}
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                  \nPrevious week for comparison:\n${JSON.stringify(prevWeek, null, 2)}`
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      }
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    ],
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    temperature: 0.4,
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  }),
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});
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const summary = (await response.json()).choices[0].message.content;
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// Send via Slack, email, or dashboard widget

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// In your CI pipeline or GitHub Action
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const diff = await getGitDiff(); // git diff output
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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "openai/gpt-5",
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    messages: [
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      {
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        role: "system",
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        content: "You are a senior code reviewer. Analyze the diff " +
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          "and provide: 1) Critical issues (bugs, security) " +
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          "2) Suggestions (performance, readability) " +
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          "3) Positive observations. Be specific with line references."
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      },
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      {
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        role: "user",
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        content: `Review this PR diff:\n\`\`\`diff\n${diff}\n\`\`\``
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      }
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    ],
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    temperature: 0.2,
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  }),
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});
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const review = (await response.json()).choices[0].message.content;
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await postGitHubComment(prNumber, review);

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// Step 1: Search your vector DB for relevant chunks
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const relevantDocs = await vectorSearch(userQuestion, { topK: 5 });
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// Step 2: Send to AI with context
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const response = await fetch("https://api.vincony.com/v1/chat", {
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  method: "POST",
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  headers: {
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    "Authorization": "Bearer YOUR_API_KEY",
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    "Content-Type": "application/json",
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  },
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  body: JSON.stringify({
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    model: "google/gemini-2.5-flash",
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    messages: [
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      {
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        role: "system",
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        content: "Answer questions using ONLY the provided context. " +
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          "Cite sources with [1], [2], etc. If the answer isn't in " +
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          "the context, say so honestly."
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      },
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      {
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        role: "user",
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        content: `Context:\n${relevantDocs.map((d, i) =>
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          `[${i+1}] ${d.content}`).join("\n\n")}
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          \n\nQuestion: ${userQuestion}`
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      }
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    ],
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    temperature: 0.2,
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  }),
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});
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const answer = (await response.json()).choices[0].message.content;