""" References: - https://medium.com/@turna.fardousi/building-a-multimodal-chatbot-with-gemini-api-8015bfbee538 """ import os import time from typing import List, Tuple, Optional import google.generativeai as genai import gradio as gr from PIL import Image from dotenv import load_dotenv load_dotenv() GEMINI_API_KEY = os.getenv("GEMINI_API_KEY") genai.configure(api_key=GEMINI_API_KEY) TITLE = """

๐ŸŽฎChat with Gemini 1.5๐Ÿ”ฅ -- Beta Preview

""" NOTICE = """ Notices ๐Ÿ“œ: - This app is still in development - Some features may not work as expected """ ABOUT = """ Updates (2024-8-12): Created the App Info: - Model: Gemini 1.5 Flash - Features: - Langchain integration - Google search """ ERRORS = """ Known errors โš ๏ธ: """ FUTURE_IMPLEMENTATIONS = """ To be implemented ๐Ÿš€: - Select other Gemini / Gemma models - Upload files - More tools other than web search """ IMAGE_WIDTH = 512 def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]: return [seq.strip() for seq in stop_sequences.split(",")] if stop_sequences else None def preprocess_image(image: Image.Image) -> Image.Image: image_height = int(image.height * IMAGE_WIDTH / image.width) return image.resize((IMAGE_WIDTH, image_height)) def user(text_prompt: str, chatbot: List[Tuple[str, str]]): return "", chatbot + [[text_prompt, None]] def bot( google_key: str, image_prompt: Optional[Image.Image], temperature: float, max_output_tokens: int, stop_sequences: str, top_k: int, top_p: float, chatbot: List[Tuple[str, str]] ): google_key = google_key or GEMINI_API_KEY if not google_key: raise ValueError("GOOGLE_API_KEY is not set. Please set it up.") text_prompt = chatbot[-1][0] genai.configure(api_key=google_key) generation_config = genai.types.GenerationConfig( temperature=temperature, max_output_tokens=max_output_tokens, stop_sequences=preprocess_stop_sequences(stop_sequences), top_k=top_k, top_p=top_p, ) model_name = "gemini-1.5-flash" # if image_prompt is None else "gemini-pro-vision" model = genai.GenerativeModel(model_name) inputs = [text_prompt] if image_prompt is None else [text_prompt, preprocess_image(image_prompt)] response = model.generate_content(inputs, stream=True, generation_config=generation_config) response.resolve() chatbot[-1][1] = "" for chunk in response: for i in range(0, len(chunk.text), 10): chatbot[-1][1] += chunk.text[i:i + 10] time.sleep(0.01) yield chatbot google_key_component = gr.Textbox( label = "GOOGLE API KEY", type = "password", placeholder = "...", visible = GEMINI_API_KEY is None ) image_prompt_component = gr.Image( type = "pil", label = "Image" ) chatbot_component = gr.Chatbot( # label = 'Gemini', bubble_full_width = False ) text_prompt_component = gr.Textbox( placeholder = "Chat with Gemini", label = "Ask me anything and press Enter" ) run_button_component = gr.Button( "Run" ) temperature_component = gr.Slider( minimum = 0, maximum = 1.0, value = 0.5, step = 0.05, label = "Temperature" ) max_output_tokens_component = gr.Slider( minimum = 1, maximum = 8192, value = 4096, step = 1, label = "Max Output Tokens" ) stop_sequences_component = gr.Textbox( label = "Add stop sequence", placeholder = "STOP, END" ) top_k_component = gr.Slider( minimum = 1, maximum = 40, value = 32, step = 1, label = "Top-K" ) top_p_component = gr.Slider( minimum = 0, maximum = 1, value = 1, step = 0.01, label = "Top-P" ) user_inputs = [ text_prompt_component, chatbot_component ] bot_inputs = [ google_key_component, image_prompt_component, temperature_component, max_output_tokens_component, stop_sequences_component, top_k_component, top_p_component, chatbot_component ] with gr.Blocks() as demo: gr.HTML(TITLE) with gr.Row(): gr.Markdown(NOTICE) gr.Markdown(ABOUT) gr.Markdown(ERRORS) gr.Markdown(FUTURE_IMPLEMENTATIONS) with gr.Column(): google_key_component.render() with gr.Row(): image_prompt_component.render() chatbot_component.render() text_prompt_component.render() run_button_component.render() with gr.Accordion("Parameters", open=False): temperature_component.render() max_output_tokens_component.render() stop_sequences_component.render() with gr.Accordion("Advanced", open=False): top_k_component.render() top_p_component.render() run_button_component.click( fn = user, inputs = user_inputs, outputs = [ text_prompt_component, chatbot_component ], queue = False ).then( fn = bot, inputs = bot_inputs, outputs = [ chatbot_component ] ) text_prompt_component.submit( fn = user, inputs = user_inputs, outputs = [ text_prompt_component, chatbot_component ], queue = False ).then( fn = bot, inputs = bot_inputs, outputs = [ chatbot_component ] ) demo.launch()