Update app.py

app.py

@@ -1,4 +1,5 @@
-import openai
+os.system("pip install langchain-openai")
+from langchain_openai import AzureChatOpenAI
 import os
 import pdfplumber
 from langchain.chains.mapreduce import MapReduceChain
@@ -44,7 +45,11 @@ class KeyValueExtractor:
             pdf_file_path (str): The path to the input PDF file.
         """
         self.model = "facebook/bart-large-mnli"
-        self.client = OpenAI()
+        self.client = AzureOpenAI(api_key=os.getenv("AZURE_OPENAI_KEY"),  
+                            api_version="2023-07-01-preview",
+                            azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+                             )
+            
         
         
     def get_url(self,keyword):
@@ -100,7 +105,7 @@ class KeyValueExtractor:
 
       # Load the summarization chain using the ChatOpenAI language model
       chain = load_summarize_chain(
-          llm = ChatOpenAI(temperature=0),
+          llm = AzureChatOpenAI(azure_deployment = "ChatGPT"),
           chain_type="refine",
           question_prompt=prompt,
           refine_prompt=refine_prompt,
@@ -116,6 +121,7 @@ class KeyValueExtractor:
       return result["output_text"]
 
     def one_day_summary(self,content) -> None:
+        
         conversation = [
             {"role": "system", "content": "You are a helpful assistant."},
             {"role": "user", "content": f"i want detailed Summary from given finance details. i want information like what happen today comparing last day good or bad Bullish or Bearish like these details i want summary. content in backticks.```{content}```."}
@@ -123,7 +129,7 @@ class KeyValueExtractor:
         
         # Call OpenAI GPT-3.5-turbo
         chat_completion = self.client.chat.completions.create(
-            model = "gpt-3.5-turbo",
+            model = "ChatGPT",
             messages = conversation,
             max_tokens=1000,
             temperature=0
@@ -322,7 +328,7 @@ class KeyValueExtractor:
 
         # Load the summarization chain using the ChatOpenAI language model
         chain = load_summarize_chain(
-            llm = ChatOpenAI(temperature=0),
+            llm = AzureChatOpenAI(azure_deployment = "ChatGPT"),
             chain_type="refine",
             question_prompt=prompt,
             refine_prompt=refine_prompt,