Upload app.py

app.py

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+import PIL.Image
+import gradio as gr
+import base64
+import time
+import os
+import google.generativeai as genai
+
+import pathlib
+
+txt_model = genai.GenerativeModel('gemini-pro')
+vis_model = genai.GenerativeModel('gemini-pro-vision')
+
+txt_prompt_1 = """The image contains the contents of a letter. I'd like to follow the request mentioned in the letter. Please provide 3 actionable items to assist me. When responding, use the following format:
+
+# Sender and Subject #
+1- Action 1 (no more than 20 words)
+2- Action 2 (no more than 20 words)
+3- Action 3 (no more than 20 words)
+
+For example:
+# From Richard regarding 'Shipping to Customer ABC' #
+1- Pack Product A
+2- Ship before 3:00 PM today
+3- Notify Richard after shipment
+"""
+
+txt_display_1 = 'content of email'
+
+import os
+
+GOOGLE_API_KEY=os.getenv('GOOGLE_API_KEY')
+
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# 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 app2_query(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 app2_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
+
+# Function that takes User Inputs and displays it on ChatUI
+
+def app1_query(img):
+    if not img:
+        return txt_prompt_1
+    base64 = image_to_base64(img)
+    data_url = f"data:image/jpeg;base64,{base64}"
+    outputText = [(f"{txt_display_1} ![]({data_url})", None)]
+    return outputText
+
+# Function that takes User Inputs, generates Response and displays on Chat UI
+def app1_response(img):
+    if not img:
+        response = txt_model.generate_content(txt_prompt_1)
+        return response
+
+    else:
+        img = PIL.Image.open(img)
+        response = vis_model.generate_content([txt_prompt_1,img])
+        return response.txt
+
+        
+# Interface Code- Selector method
+
+def sentence_builder(animal, place):
+    return f"""how many {animal}s from the {place} are shown in the picture?"""
+
+# gradio block
+    
+with gr.Blocks(theme='snehilsanyal/scikit-learn') as app1:
+    with gr.Column():    
+        outputbox = gr.Textbox(label="here are the plans...")
+        image_box = gr.Image(type="filepath")
+        
+    btn = gr.Button("Make a Plan")
+    clicked = btn.click(app1_query,
+                        [image_box],
+                        outputbox
+                        ).then(app1_response,
+                                [image_box],
+                                outputbox
+                                )
+    gr.Markdown("""
+    # Make a Plan #
+    
+    	- screen capture (Win + shift + S)
+        - click **Make a Plan** to upload
+        - await LLM Bot (Gemini, in this case) response
+        - receive THREE actionable items
+    
+
+    [demo](https://youtu.be/lJ4jIAEVRNY)
+
+    """)
+
+with gr.Blocks(theme='snehilsanyal/scikit-learn') as app2:
+    gr.Markdown("check the image...")
+    with gr.Row():
+        image_box = gr.Image(type="filepath")
+    
+        chatbot = gr.Chatbot(
+            scale = 2,
+            height=750
+        )
+    text_box = gr.Dropdown(
+                ["what is in the image", 
+                 "provide alternative title for the image", 
+                 "how many parts can be seen in the picture?",
+                  "check ID and expiration date"], 
+                 label="Select--", 
+                 info="ask Bot"
+            )
+
+    btn = gr.Button("Submit")
+    clicked = btn.click(app2_query,
+                        [chatbot,text_box,image_box],
+                        chatbot
+                        ).then(app2_response,
+                                [chatbot,text_box],
+                                chatbot
+                                )
+with gr.Blocks(theme='snehilsanyal/scikit-learn') as demo:
+    gr.Markdown("## Workflow Bot ##")
+    gr.TabbedInterface([app1, app2], ["Make a Plan!", "Check This!"])
+
+demo.queue()
+demo.launch()