Update text2generation.py

text2generation.py

@@ -1,29 +1,31 @@
-from transformers import pipeline, set_seed
 import os
-
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-set_seed(42)
+import requests
+import json
 
 def generate_long_answer(question):
-    # Using smaller but capable model (1.5B parameters)
-    generator = pipeline(
-        "text-generation",
-        model="google/flan-t5-large",
-        device_map="auto",
-        torch_dtype="auto"
-    )
-    
-    prompt = f"""Answer this educational question in detail:
-    
-Question: {question}
-Answer:"""
-    
-    result = generator(
-        prompt,
-        max_length=1000,
-        temperature=0.7,
-        top_p=0.9,
-        do_sample=True
-    )
+    """Generate detailed answers using OpenRouter's DeepSeek API"""
+    try:
+        response = requests.post(
+            url="https://openrouter.ai/api/v1/chat/completions",
+            headers={
+                "Authorization": f"Bearer {os.getenv('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')}",
+                "Content-Type": "application/json",
+                "HTTP-Referer": "https://your-huggingface-space-url.hf.space",
+                "X-Title": "Educational AI Assistant"
+            },
+            json={
+                "model": "deepseek/deepseek-chat-v3-0324:free",
+                "messages": [{
+                    "role": "user",
+                    "content": f"Provide a comprehensive educational answer with examples:\n\n{question}"
+                }],
+                "temperature": 0.7,
+                "max_tokens": 2000
+            },
+            timeout=30
+        )
+        response.raise_for_status()
+        return response.json()['choices'][0]['message']['content']
     
-    return result[0]['generated_text'].split("Answer:")[-1].strip()
+    except Exception as e:
+        return f"Error generating answer: {str(e)}"