Update app.py

app.py

@@ -2,9 +2,11 @@ import os
 
 import gradio as gr
 import openai
+import google.generativeai as palm
 
 #from dotenv import load_dotenv
 
+
 #load_dotenv()
 
 llm_api_options = ["OpenAI API","Azure OpenAI API","Google PaLM API", "Llama 2"]
@@ -13,8 +15,12 @@ openai_models = ["gpt-4", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-
                      "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "text-davinci-003", 
                      "text-davinci-002", "text-curie-001", "text-babbage-001", "text-ada-001"]
 
+google_palm_models = ["models/text-bison-001"]
+
 azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
 azure_deployment_name = os.getenv("AZURE_OPENAI_DEPLOYMENT_NAME")
+google_palm_key = os.getenv("GOOGLE_PALM_AI_API_KEY")
+
 
 def openai_text_completion(prompt: str, model: str):
     try:
@@ -74,16 +80,46 @@ def azure_openai_text_completion(prompt: str, model: str):
         return f" {optionSelection} test_handler Error - {exception}", ""
 
 
-def test_handler(optionSelection, prompt: str = TEST_MESSAGE, model: str ="gpt-4"):
+def palm_text_completion(prompt: str, model: str):
+    try:
+        temperature = 0.7
+        candidate_count = 1
+        top_k = 40
+        top_p = 0.95
+        max_output_tokens = 1024
+        palm.configure(api_key=google_palm_key)
+        defaults = {
+                  'model': model,
+                  'temperature': temperature,
+                  'candidate_count': candidate_count,
+                  'top_k': top_k,
+                  'top_p': top_p,
+                  'max_output_tokens': max_output_tokens,
+                  'stop_sequences': [],
+                  'safety_settings': [{"category":"HARM_CATEGORY_DEROGATORY","threshold":1},{"category":"HARM_CATEGORY_TOXICITY","threshold":1},{"category":"HARM_CATEGORY_VIOLENCE","threshold":2},{"category":"HARM_CATEGORY_SEXUAL","threshold":2},{"category":"HARM_CATEGORY_MEDICAL","threshold":2},{"category":"HARM_CATEGORY_DANGEROUS","threshold":2}],
+                }
+        
+        response = palm.generate_text(
+          **defaults,
+          prompt=prompt
+        )
+        return "", response.result
+    except openai.error.ServiceUnavailableError:
+        print(f"Exception Name: {type(exception).__name__}")
+        print(exception)
+        return f" {optionSelection} test_handler Error - {exception}", ""
+
+def test_handler(optionSelection, prompt: str = TEST_MESSAGE, openai_model_name: str ="gpt-4", google_model_name: str ="models/text-bison-001"):
     match optionSelection:
         case  "OpenAI API":
-            message, response = openai_text_completion(prompt,model)
+            message, response = openai_text_completion(prompt,openai_model_name)
             return message, response
         case  "Azure OpenAI API":
-            message, response = azure_openai_text_completion(prompt,model)
+            message, response = azure_openai_text_completion(prompt,openai_model_name)
             return message, response
         case  "Google PaLM API":
-            return "", ""
+            message, response = palm_text_completion(prompt,google_model_name)
+            return message, response
         case  "Llama 2":
             return "", ""
         case _:
@@ -97,7 +133,9 @@ with gr.Blocks() as LLMDemoTabbedScreen:
         llm_options = gr.Radio(llm_api_options, label="Select one", info="Which service do you want to use?", value="OpenAI API")
         with gr.Tab("Open AI"):
             openai_model = gr.Dropdown(openai_models, value="gpt-4", label="Model", info="Select one, for Natural language")
-
+        with gr.Tab("Google PaLM API"):
+            google_model_name = gr.Dropdown(google_palm_models, 
+                                                   value="models/text-bison-001", label="Model", info="Select one, for Natural language") 
         with gr.Row():
             with gr.Column(): 
                 test_string = gr.Textbox(label="Try String", value=TEST_MESSAGE, lines=2)
@@ -108,7 +146,7 @@ with gr.Blocks() as LLMDemoTabbedScreen:
 
     test_button.click(
             fn=test_handler,
-            inputs=[llm_options, test_string, openai_model],
+            inputs=[llm_options, test_string, openai_model, google_model_name],
             outputs=[test_string_output_info, test_string_response]
     )