Update inference.py

inference.py

@@ -16,28 +16,52 @@ evo_model.eval()
 # --- Load Tokenizer ---
 tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
 
-# --- EvoRAG+ Inference ---
+# --- EvoRAG+ with Rich Reasoning ---
 def evo_rag_response(query):
-    # Step 1: get document context (from uploaded file)
+    # Step 1: Get context from RAG (doc) + web
     rag_context = retrieve(query)
-
-    # Step 2: get online info (search/web)
     web_context = web_search(query)
 
-    # Step 3: combine all into one input
+    # Step 2: Combine for inference
     combined = query + "\n\n" + rag_context + "\n\n" + web_context
     inputs = tokenizer(combined, return_tensors="pt", truncation=True, padding="max_length", max_length=128)
     input_ids = inputs["input_ids"].to(device)
 
-    # Step 4: Evo prediction
+    # Step 3: Evo decision
     with torch.no_grad():
         logits = evo_model(input_ids)
         pred = int(torch.sigmoid(logits).item() > 0.5)
 
-    return f"Evo suggests: Option {pred + 1}"
+    # Step 4: Extract Option Texts if available
+    option_text = ""
+    if "Option 1:" in query and "Option 2:" in query:
+        try:
+            opt1 = query.split("Option 1:")[1].split("Option 2:")[0].strip()
+            opt2 = query.split("Option 2:")[1].strip()
+            option_text = opt1 if pred == 0 else opt2
+        except:
+            pass
+
+    # Step 5: Format output
+    output = f"🧠 Evo suggests: Option {pred + 1}"
+    if option_text:
+        output += f"\n➡️ {option_text}"
+
+    output += "\n\n📌 Reasoning:\n"
+    if rag_context:
+        first_line = rag_context.strip().splitlines()[0][:250]
+        output += f"- {first_line}...\n"
+    else:
+        output += "- No document insight available.\n"
+
+    output += "\n📂 Context used:\n" + (rag_context[:400] if rag_context else "[None]")
+
+    output += "\n\n🌐 Web insight:\n" + (web_context[:400] if web_context else "[None]")
+
+    return output
 
-# --- GPT-3.5 Inference (OpenAI >= 1.0.0) ---
-openai_api_key = os.environ.get("OPENAI_API_KEY", "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")  # Replace or use HF secret
+# --- GPT-3.5 (OpenAI >= 1.0.0) ---
+openai_api_key = os.environ.get("OPENAI_API_KEY", "sk-...")  # Replace or set via HF secrets
 client = OpenAI(api_key=openai_api_key)
 
 def get_gpt_response(query, context):