Update app.py

app.py

@@ -9,17 +9,17 @@ from keybert import KeyBERT
 # Option 1: High-level helper pipeline for chat-like generation
 pipe = pipeline(
     "text-generation",
-    model="deepseek-ai/DeepSeek-R1",
+    model="deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
     trust_remote_code=True
 )
 
 # Option 2: Direct model & tokenizer instantiation (alternative)
 # tokenizer_ds = AutoTokenizer.from_pretrained(
-#     "deepseek-ai/DeepSeek-R1",
+#     "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
 #     trust_remote_code=True
 # )
 # model_ds = AutoModelForCausalLM.from_pretrained(
-#     "deepseek-ai/DeepSeek-R1",
+#     "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
 #     trust_remote_code=True
 # )
 
@@ -50,7 +50,6 @@ LABEL_MAP = {
     "LABEL_4": "Very Positive"
 }
 
-
 def main():
     st.title("📊 Amazon Review Analyzer")
 
@@ -111,7 +110,7 @@ def main():
     progress.text("Generating insights...")
     prompt = f"""
 You are an analytical amazon feedback expert.
-Review: \"{review}\"
+Review: "{review}"
 Sentiment Scores: {sentiment_results}
 Top Keywords: {[kw for kw, _ in keywords]}
 Tasks:
@@ -137,4 +136,4 @@ Tasks:
     progress.text("Done!")
 
 if __name__ == "__main__":
-    main()
+    main()