Update app.py

app.py

@@ -1,83 +1,13 @@
-import PIL.Image
-import gradio as gr
-import base64
-import time
-import os
 import google.generativeai as genai
-
-# Set Google API key 
-genai.configure(api_key = os.environ['GOOGLE_PALM_KEY'])
-
-# Create the Model
-txt_model = genai.GenerativeModel('gemini-pro')
-vis_model = genai.GenerativeModel('gemini-pro-vision')
-
-# Image to Base 64 Converter
-def image_to_base64(image_path):
-    with open(image_path, 'rb') as img:
-        encoded_string = base64.b64encode(img.read())
-    return encoded_string.decode('utf-8')
-
-# Function that takes User Inputs and displays it on ChatUI
-def query_message(history,txt,img):
-    if not img:
-        history += [(txt,None)]
-        return history
-    base64 = image_to_base64(img)
-    data_url = f"data:image/jpeg;base64,{base64}"
-    history += [(f"{txt} ![]({data_url})", None)]
-    return history
-
-# Function that takes User Inputs, generates Response and displays on Chat UI
-def llm_response(history,text,img):
-    if not img:
-        response = txt_model.generate_content(text)
-        history += [(None,response.text)]
-        return history
-
-    else:
-        img = PIL.Image.open(img)
-        response = vis_model.generate_content([text,img])
-        history += [(None,response.text)]
-        return history
-
-# Interface Code
-with gr.Blocks() as app:
-    with gr.Row():
-        chatbot = gr.Chatbot(
-            scale = 2,
-            height=750
-        )
-    text_box = gr.Textbox(
-            placeholder="Enter text and press enter, or upload an image",
-            container=False,
-        )
-
-    btn = gr.Button("Submit")
-    clicked = btn.click(query_message,
-                        [chatbot,text_box],
-                        chatbot
-                        ).then(llm_response,
-                                [chatbot,text_box],
-                                chatbot
-                                )
-app.queue()
-app.launch(debug=True)
-
-
-
-''''import google.generativeai as genai
 import gradio as gr
 import os
 
-genai.configure(api_key=os.getenv("GOOGLE_PALM_KEY"))
-
 # Set up the model
 generation_config = {
   "temperature": 0.9,
   "top_p": 1,
   "top_k": 1,
-  "max_output_tokens": 4096,
+  "max_output_tokens": 2048,
 }
 
 safety_settings = [
@@ -99,6 +29,8 @@ safety_settings = [
   },
 ]
 
+genai.configure(api_key=os.getenv("GOOGLE_PALM_KEY"))
+
 model = genai.GenerativeModel(model_name="gemini-pro",
                               generation_config=generation_config,
                               safety_settings=safety_settings)
@@ -178,21 +110,94 @@ convo = model.start_chat(history=[
   },
 ])
 
-#response = convo.send_message(
-#       messages=messages)
-#    return response.last.text
 
-def generate(messages):
-    model = genai.GenerativeModel('gemini-pro')
-    response = model.generate_content(
-        messages,
-        stream=True,
-        generation_config=generation_config)   
+def gemini_chat(prompt, history):
+    response = chat.send_message(message)
+    return response.text
+
 
 gr.ChatInterface(
-    fn=generate,
+    fn=gemini_chat,
     chatbot=gr.Chatbot(show_label=False, avatar_images=(None, 'palm-logo.png'), show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
     title="PaLM-2",
     description="This is unofficial demo of ```PaLM-2``` based on ```Google API```. ```History/context``` memory does not work in this demo.",
     concurrency_limit=20,
-).launch(show_api=False)'''
+).launch(show_api=False)
+
+
+convo.send_message("YOUR_USER_INPUT")
+print(convo.last.text)
+
+
+
+
+
+
+
+
+
+"""import PIL.Image
+import gradio as gr
+import base64
+import time
+import os
+import google.generativeai as genai
+
+# Set Google API key 
+genai.configure(api_key = os.environ['GOOGLE_PALM_KEY'])
+
+# Create the Model
+txt_model = genai.GenerativeModel('gemini-pro')
+vis_model = genai.GenerativeModel('gemini-pro-vision')
+
+# Image to Base 64 Converter
+def image_to_base64(image_path):
+    with open(image_path, 'rb') as img:
+        encoded_string = base64.b64encode(img.read())
+    return encoded_string.decode('utf-8')
+
+# Function that takes User Inputs and displays it on ChatUI
+def query_message(history,txt,img):
+    if not img:
+        history += [(txt,None)]
+        return history
+    base64 = image_to_base64(img)
+    data_url = f"data:image/jpeg;base64,{base64}"
+    history += [(f"{txt} ![]({data_url})", None)]
+    return history
+
+# Function that takes User Inputs, generates Response and displays on Chat UI
+def llm_response(history,text,img):
+    if not img:
+        response = txt_model.generate_content(text)
+        history += [(None,response.text)]
+        return history
+
+    else:
+        img = PIL.Image.open(img)
+        response = vis_model.generate_content([text,img])
+        history += [(None,response.text)]
+        return history
+
+# Interface Code
+with gr.Blocks() as app:
+    with gr.Row():
+        chatbot = gr.Chatbot(
+            scale = 2,
+            height=750
+        )
+    text_box = gr.Textbox(
+            placeholder="Enter text and press enter, or upload an image",
+            container=False,
+        )
+
+    btn = gr.Button("Submit")
+    clicked = btn.click(query_message,
+                        [chatbot,text_box],
+                        chatbot
+                        ).then(llm_response,
+                                [chatbot,text_box],
+                                chatbot
+                                )
+app.queue()
+app.launch(debug=True)"""