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Update app.py

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  1. app.py +31 -48
app.py CHANGED
@@ -1,54 +1,37 @@
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- import os
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  import gradio as gr
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- import google.generativeai as genai
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- # Configure the Google Generative AI
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- genai.configure(api_key=os.environ["GEMINI_API_KEY"])
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # Create the model
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- generation_config = {
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- "temperature": 1,
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- "top_p": 0.95,
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- "top_k": 64,
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- "max_output_tokens": 8192,
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- "response_mime_type": "text/plain",
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- }
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-
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- model = genai.GenerativeModel(
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- model_name="gemini-1.5-flash",
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- generation_config=generation_config,
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- )
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-
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- # Initialize a chat session
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- chat_session = model.start_chat(
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- history=[
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- {
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- "role": "user",
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- "parts": [
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- "tell me a story about me",
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- ],
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- },
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- {
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- "role": "model",
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- "parts": [
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- "Please tell me a little bit about yourself! I need some information to write a story about you. For example:\n\n* **What are your hobbies and interests?** \n* **What are some of your favorite things?** \n* **What kind of story do you want to hear?** (Adventure, romance, mystery, etc.)\n* **Is there anything unique or interesting about you that you'd like to see in the story?**\n\nOnce I know more about you, I can write a fun and engaging story just for you! 😊 \n",
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- ],
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- },
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- ]
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- )
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-
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- def generate_story(user_input):
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- response = chat_session.send_message(user_input)
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- return response.text
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-
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- # Create a Gradio Interface
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  iface = gr.Interface(
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- fn=generate_story,
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- inputs=gr.Textbox(lines=4, placeholder="Enter some information about yourself..."),
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- outputs="text",
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- title="AI Story Generator",
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- description="Enter some details about yourself, and the AI will generate a personalized story for you!"
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  )
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- # Launch the interface
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- iface.launch()
 
 
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  import gradio as gr
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+ import requests
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+ # Define the function to interact with the API
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+ def generate_content(text):
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+ url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent?key=AIzaSyAflU5a8T3dCuIrkql737ZQtqWdrPmo0ts'
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+ headers = {'Content-Type': 'application/json'}
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+ data = {
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+ "contents": [
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+ {
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+ "parts": [
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+ {
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+ "text": text
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+ }
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+ ]
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+ }
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+ ]
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+ }
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+
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+ response = requests.post(url, headers=headers, json=data)
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+
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+ if response.status_code == 200:
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+ return response.json() # You can customize this to return specific parts of the response
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+ else:
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+ return f"Error: {response.status_code} - {response.text}"
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+ # Create a Gradio interface
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  iface = gr.Interface(
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+ fn=generate_content,
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+ inputs="text",
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+ outputs="json",
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+ title="AI Content Generator",
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+ description="Enter a prompt to generate content using the Google Gemini API."
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  )
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+ # Launch the Gradio app
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+ iface.launch()