Update app.py

app.py

@@ -30,7 +30,7 @@ client = AzureOpenAI(
     azure_endpoint = "https://amplifai-openai.openai.azure.com/"
 )
 
-deployment_name='AmplifAI-Chat'
+deployment_name='gpt-4'
 
 DEEPGRAM_API_KEY = os.getenv("DEEPGRAM_API_KEY")
 if not DEEPGRAM_API_KEY:
@@ -50,12 +50,48 @@ class GenerateResponse3(BaseModel):
 class GenerateResponse4(BaseModel):
     text: list
 
+# #Summarize function
+# def summarize_text(text: str):
+#         response = client.chat.completions.create(
+#             model = deployment_name,
+#             #engine="AmplifAI-Chat",
+#             messages="The data is a pre-recorded conversation between a call center agent and a customer. Identify the following: keywords/metrics about the conversation, a summary of the conversation including details. Output should be in the format Keywords/Metrics: ,\n Summary:. \n Data: " + text,
+#             temperature=0.7,
+#             max_tokens=750,
+#             top_p=1.0,
+#             frequency_penalty=0.0,
+#             presence_penalty=0.0
+#         )
+#         if response.choices:
+#             # Extract the text from the response
+#             summary = response.choices[0].text.strip()
+            
+#             # Use regular expressions to find the keywords/metrics and summary sections
+#             keywords_match = re.search(r"Keywords/Metrics:(.*?)(\n|$)", summary, re.S)
+#             summary_match = re.search(r"Summary:(.*?)(\n|$)", summary, re.S)
+            
+#             # Extract the content if matches are found
+#             keywords = keywords_match.group(1).strip() if keywords_match else "No keywords found"
+#             conversation_summary = summary_match.group(1).strip() if summary_match else "No summary found"
+            
+#             # Return a clean version with just the keywords and summary
+#             return GenerateResponse(text=f"Keywords/Metrics: {keywords}\nSummary: {conversation_summary}")
+        
+#         else:
+#             return "No response from the API."
+#         # if response.choices:
+#         #     summary = response.choices[0].text.strip()
+#         #     return GenerateResponse(text=summary)
+#         # else:
+#         #     return "No response from the API."
+
+
 #Summarize function
 def summarize_text(text: str):
         response = client.chat.completions.create(
             model = deployment_name,
             #engine="AmplifAI-Chat",
-            messages="The data is a pre-recorded conversation between a call center agent and a customer. Identify the following: keywords/metrics about the conversation, a summary of the conversation including details. Output should be in the format Keywords/Metrics: ,\n Summary:. \n Data: " + text,
+            messages=["The data is a pre-recorded conversation between a call center agent and a customer. Identify the following: keywords/metrics about the conversation, a summary of the conversation including details. Output should be in the format Keywords/Metrics: ,\n Summary:. \n Data: " + text],
             temperature=0.7,
             max_tokens=750,
             top_p=1.0,
@@ -85,7 +121,6 @@ def summarize_text(text: str):
         # else:
         #     return "No response from the API."
 
-
 # QA Automation function
 def qa_automation(text: str):
     questions = [