Create src/services/huggingface.js

src/services/huggingface.js

@@ -0,0 +1,50 @@
+// 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;
+  }
+};