Update app.py

app.py

@@ -3,7 +3,7 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline, AutoMod
 import torch
 import fitz  # PyMuPDF
 from docx import Document
-import openai
+from openai import OpenAI
 
 # Load models and tokenizers
 summarizer_model_name = "facebook/bart-large-cnn"
@@ -101,24 +101,20 @@ if uploaded_file is not None:
                     "average_predictions": avg_predictions.tolist()  # Convert tensor to list for JSON serialization
                 }
 
-                openai.api_key = openai_key
+                client = OpenAI(api_key=openai_key)
 
                 decision_prompt = f"""
                 Analyze the following legal document analysis data and provide a decision and reasoning:
-
                 Summary of the Document:
                 {full_summary}
-
                 Classification Result:
                 {classification_result}
-
                 Average Predictions:
                 {avg_predictions.tolist()}
-
                 Based on the above analysis, provide the judge's decision and reasoning in a detailed manner.
                 """
 
-                response = openai.ChatCompletion.create(
+                response = client.chat.completions.create(
                     model="gpt-4",
                     messages=[
                         {"role": "system", "content": "You are a legal expert analyzing the case."},
@@ -127,10 +123,10 @@ if uploaded_file is not None:
                     max_tokens=500
                 )
 
-                decision_and_reasoning = response['choices'][0]['message']['content'].strip()
+                decision_and_reasoning = response.choices[0].message.content.strip()
                 st.write(decision_and_reasoning)
                 
             else:
                 st.write("Please input a legal document for analysis.")
         else:
-            st.write("Please enter your OpenAI API key.")
+            st.write("Please enter your OpenAI API key.")