Create hf_integration.py

hf_integration.py

@@ -0,0 +1,47 @@
+import os
+import requests
+import streamlit as st
+
+class HuggingFaceIntegration:
+    def __init__(self):
+        self.api_key = st.secrets.get("HF_API_KEY", os.getenv("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"))
+        self.base_url = "https://api-inference.huggingface.co/models"
+        self.model_map = {
+            "english": "google/flan-t5-xxl",
+            "math": "EleutherAI/gpt-neo-2.7B",
+            "science": "google/gemma-7b"
+        }
+
+    def generate_questions(self, subject, difficulty="medium"):
+        try:
+            headers = {"Authorization": f"Bearer {self.api_key}"}
+            prompt = (
+                f"Generate a {difficulty} difficulty {subject} question for IELTS preparation "
+                f"with 4 multiple choice options in this exact format: "
+                "Question: [question]\nA) [option1]\nB) [option2]\nC) [option3]\nD) [option4]"
+            )
+            
+            response = requests.post(
+                f"{self.base_url}/{self.model_map[subject]}",
+                headers=headers,
+                json={"inputs": prompt, "parameters": {"max_new_tokens": 200}}
+            )
+            
+            return response.json()
+        except Exception as e:
+            return {"error": str(e)}
+
+    def evaluate_writing(self, text):
+        try:
+            headers = {"Authorization": f"Bearer {self.api_key}"}
+            response = requests.post(
+                f"{self.base_url}/openai-community/gpt2",
+                headers=headers,
+                json={
+                    "inputs": f"Evaluate this IELTS essay for grammar, vocabulary, coherence, and task achievement:\n\n{text}",
+                    "parameters": {"temperature": 0.7, "max_length": 500}
+                }
+            )
+            return response.json()
+        except Exception as e:
+            return {"error": str(e)}  # Added missing return statement