src/services/huggingface.js

// This service calls the Hugging Face Inference API.
// It's best for models fine-tuned for JSON output, like Llama 3.

export const callHuggingFaceAPI = async (prompt, apiKey, maxTokens = 2000) => {
  if (!apiKey) {
    throw new Error("Hugging Face API Key is required.");
  }

  // Recommended model: Meta's Llama 3 is excellent at following instructions.
  const API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct";

  const headers = {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  };

  const payload = {
    inputs: prompt,
    parameters: {
      max_new_tokens: maxTokens,
      return_full_text: false, // Important: only return the generated text
      temperature: 0.6, // A bit of creativity but still factual
      top_p: 0.9,
    }
  };

  try {
    const response = await fetch(API_URL, {
      method: "POST",
      headers: headers,
      body: JSON.stringify(payload),
    });

    if (!response.ok) {
      const errorText = await response.text();
      throw new Error(`Hugging Face API request failed: ${response.status} - ${errorText}`);
    }

    const data = await response.json();
    // The response is an array, we take the first element's generated text.
    if (data && data[0] && data[0].generated_text) {
      return data[0].generated_text;
    } else {
      throw new Error("Invalid response structure from Hugging Face API.");
    }
  } catch (error) {
    console.error("Hugging Face API Error:", error);
    throw error;
  }
};