Create app.py

app.py

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+from azure.ai.textanalytics import TextAnalyticsClient
+from azure.core.credentials import AzureKeyCredential
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+# Azure Text Analytics setup
+azure_endpoint = "https://t6langservice.cognitiveservices.azure.com/"
+azure_api_key = "3CU1gpUszvl7pLb90Ivdp1Kd5WZc56savzdXOK5GV40JHebnxnxoJQQJ99BAACYeBjFXJ3w3AAAaACOGkRT5"
+
+# Authenticate client
+text_analytics_client = TextAnalyticsClient(endpoint=azure_endpoint, credential=AzureKeyCredential(azure_api_key))
+
+
+# Load Hugging Face chatbot model
+model_name = "microsoft/DialoGPT-medium"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Chatbot logic
+def chatbot_response(input_text):
+    # Hugging Face response
+    input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors="pt")
+    chat_output = model.generate(input_ids, max_length=50, pad_token_id=tokenizer.eos_token_id)
+    hf_response = tokenizer.decode(chat_output[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
+
+    # Azure Text Analytics: Analyze sentiment of user input
+    try:
+        response = text_analytics_client.analyze_sentiment([input_text])[0]
+        sentiment = response.sentiment
+        azure_analysis = f"The sentiment of your input is: {sentiment}."
+    except Exception as e:
+        azure_analysis = f"Error analyzing sentiment: {str(e)}"
+
+    # Combine responses
+    return f"Hugging Face response: {hf_response}\nAzure analysis: {azure_analysis}"
+
+# Chat loop
+while True:
+    user_input = input("You: ")
+    if user_input.lower() in ["exit", "quit"]:
+        print("Exiting chatbot. Goodbye!")
+        break
+    print(chatbot_response(user_input))
+