Update utils.py

utils.py

@@ -13,15 +13,15 @@ from groq import Groq
 import time 
 from openai import OpenAI
 
-#openai_key = "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"
-#client = OpenAI(api_key = openai_key)
+openai_key = "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"
+client = OpenAI(api_key = openai_key)
 desc = pd.read_excel('Descriptor.xlsx',header = None)
 desc_list  = desc.iloc[:,0].to_list()
 
 def callAzure(prompt,text):
     
-    url = "https://Mistral-large-tmhcg-serverless.eastus2.inference.ai.azure.com"
-    api_key = "LB0ha1R4k3pNpHl68P3VtUZ3sMLr3wT7"
+    url = "https://Meta-Llama-3-70B-Instruct-fkqip-serverless.eastus2.inference.ai.azure.com"
+    api_key = "o5yaLhTIvg0s5zuYVInBpyneEZO8oonY"
     client = OpenAI(base_url=url, api_key=api_key)
     msg = "{} {}".format(prompt, text)
     
@@ -33,7 +33,7 @@ def callAzure(prompt,text):
             }
         ],
         model="azureai",
-        max_tokens = 20000
+        max_tokens = 1000
         ) 
     
     return response.choices[0].message.content
@@ -78,7 +78,9 @@ def summary(input_json):
 
     id = desc_list.index(input_json['Descriptor'])
     long_text = filtering_results[1]
-
+    long_text = long_text.lstrip()
+    long_text = long_text.rstrip()
+    
     url = 'https://www.bseindia.com/xml-data/corpfiling/AttachLive/'+ input_json['FileURL'].split('Pname=')[-1]
 
     output["Link to BSE website"] = url
@@ -90,14 +92,11 @@ def summary(input_json):
     answer = "You are an financial expert" + callAzure(promptShort[id], long_text)
     output['Short Summary'] = answer
 
-    answer = "You are an financial expert" + callAzure(promptLong[id] + " The Summary should be around 2000 characters. Please make sure it is not smaller than that. Do not truncate the final answers", long_text)
-    output['Long summary'] = answer
-
-    prompt = "Answer in 1 word only. Financial SEO tag for this news article"
+    prompt = "Answer in 1 word only. Financial SEO tag for this news article. Nothing more than that"
     answer = callAzure(prompt, output['Short Summary'])
     output['Tag'] = answer
 
-    prompt = "Give a single headline for this News Article"
+    prompt = "Answer in single sentence. A headline for this News Article. Nothing more than that"
     answer = callAzure(prompt, output['Short Summary'])
     output['Headline'] = answer
 
@@ -111,7 +110,15 @@ def summary(input_json):
     prompt = "Answer in one word the sentiment of this News out of Positive, Negative or Neutral {}"
     output['Sentiment'] = callAzure(prompt, output['Short Summary'])
 
-    #time.sleep(60)
+    completion = client.chat.completions.create(
+    model="gpt-4-turbo-preview",
+    messages=[
+    {"role": "system", "content": "You are a financial expert. Help the client with summarizing the financial newsletter"},
+    {"role": "user", "content": "{} {}".format(promptLong[id], long_text)}
+    ]
+    )
+
+    output['Long summary'] = completion.choices[0].message
     # response = client.images.generate(
     # model="dall-e-3",
     # prompt=headline.text,