Tabs/Gemini_Chabot_Stable.py

import os
import google.generativeai as genai
import gradio as gr
from dotenv import load_dotenv

load_dotenv()

GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
# model_name = "gemini-1.5-flash-exp-0827"

TITLE = """<h1 align="center">🎮Chat with Gemini 1.5🔥</h1>"""
NOTICE = """
**Notices** 📜:
- This app is still in development
- Some features may not work as expected
"""
ABOUT = """
**Updates (2024-9-25)** 📈: Upgrade model to SOTA Gemini 1.5 Flash Experimental 0924
"""
ERRORS = """
Known errors ⚠️:
"""
FUTURE_IMPLEMENTATIONS = """
Future features 🚀:
- More tools such as web search
"""

# genai.configure(api_key=GEMINI_API_KEY)
# model = genai.GenerativeModel(
#     model_name,
#     safety_settings=[
#         {
#             "category": "HARM_CATEGORY_HARASSMENT",
#             "threshold": "BLOCK_NONE"
#         },
#         {
#             "category": "HARM_CATEGORY_HATE_SPEECH",
#             "threshold": "BLOCK_NONE"
#         },
#         {
#             "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
#             "threshold": "BLOCK_NONE"
#         },
#         {
#             "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
#             "threshold": "BLOCK_NONE"
#         }
#     ],
#     generation_config={
#         "temperature": 1,
#         "top_p": 0.95,
#         "top_k": 64,
#         "max_output_tokens": 8192,
#         "response_mime_type": "text/plain",
#     }
# )
# chat = model.start_chat(history=[])

# def clear_chat_history():
#     chat.history = []
    
# def undo_chat():
#     last_send, last_received = chat.rewind()

# def transform_history(history):
#     new_history = []
#     for user_msg, model_msg in history:
#         new_history.append({"role": "user", "parts": [user_msg]})
#         new_history.append({"role": "model", "parts": [model_msg]})
#     return new_history

# def chatbot_stable(message, history):
#     message_text = message["text"]
#     message_files = message["files"]
#     if message_files:
#         image_uris = [genai.upload_file(path=file_path["path"]) for file_path in message_files]
#         message_content = [message_text] + image_uris
#     else:
#         message_content = [message_text]

#     response = chat.send_message(message_content, stream=True)
#     response.resolve()

#     return response.text

# gemini_chatbot_interface = gr.Chatbot(
#     height=400,
#     likeable=True,
#     avatar_images=(
#         None,
#         "https://media.roboflow.com/spaces/gemini-icon.png"
#     ),
#     show_copy_button=True,
#     show_share_button=True,
#     render_markdown=True
# )

# clear_chat_button = gr.ClearButton(
#     components=[gemini_chatbot_interface],
#     value="🗑️ Clear"
# )

# undo_chat_button = gr.Button(
#     value="↩️ Undo"
# )

# gemini_chatbot = gr.ChatInterface(
#     fn=chatbot_stable,
#     chatbot=gemini_chatbot_interface,
#     multimodal=True,
#     clear_btn=clear_chat_button,
#     undo_btn=undo_chat_button
# )

model_list = ["gemini-1.5-pro", "gemini-1.5-pro-002", "gemini-1.5-pro-exp-0827", "gemini-1.5-flash", "gemini-1.5-flash-002", "gemini-1.5-flash-8b-exp-0924"]

genai.configure(api_key=GEMINI_API_KEY)

def clear_chat_history():
    chat.history = []
    
def undo_chat():
    last_send, last_received = chat.rewind()

def transform_history(history):
    new_history = []
    for user_msg, model_msg in history:
        new_history.append({"role": "user", "parts": [user_msg]})
        new_history.append({"role": "model", "parts": [model_msg]})
    return new_history

def chatbot_stable(message, history, model_id, system_message, max_tokens, temperature, top_p,):
    global model, chat
    model = genai.GenerativeModel(
        model_name=model_id,
        system_instruction=system_message,
        safety_settings=[
            {
                "category": "HARM_CATEGORY_HARASSMENT",
                "threshold": "BLOCK_NONE"
            },
            {
                "category": "HARM_CATEGORY_HATE_SPEECH",
                "threshold": "BLOCK_NONE"
            },
            {
                "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
                "threshold": "BLOCK_NONE"
            },
            {
                "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
                "threshold": "BLOCK_NONE"
            }
        ],
        generation_config={
            "temperature": temperature,
            "top_p": top_p,
            "top_k": 40,
            "max_output_tokens": max_tokens,
            "response_mime_type": "text/plain",
        }
    )
    chat = model.start_chat(history=[])
    message_text = message["text"]
    message_files = message["files"]
    if message_files:
        image_uris = [genai.upload_file(path=file_path["path"]) for file_path in message_files]
        message_content = [message_text] + image_uris
    else:
        message_content = [message_text]

    response = chat.send_message(message_content, stream=True)
    response.resolve()

    return response.text

gemini_chatbot_interface = gr.Chatbot(
    height=500,
    likeable=True,
    avatar_images=(
        None,
        "https://media.roboflow.com/spaces/gemini-icon.png"
    ),
    show_copy_button=True,
    show_share_button=True,
    render_markdown=True
)

clear_chat_button = gr.ClearButton(
    components=[gemini_chatbot_interface],
    value="🗑️ Clear"
)

undo_chat_button = gr.Button(
    value="↩️ Undo"
)

gemini_chatbot = gr.ChatInterface(
    fn=chatbot_stable,
    chatbot=gemini_chatbot_interface,
    multimodal=True,
    clear_btn=clear_chat_button,
    undo_btn=undo_chat_button,
    additional_inputs=[
        gr.Dropdown(
            choices=model_list,
            value="gemini-1.5-flash-002",
            label="Models"
        ),
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=8192, value=4096, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=1.0, value=1, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)