import os import time import uuid from typing import List, Tuple, Optional, Dict, Union import google.generativeai as genai import gradio as gr from PIL import Image print("google-generativeai:", genai.__version__) GOOGLE_API_KEY = "your_gemini_api" # ضع مفتاح API هنا مباشرة TITLE = """

ReffidGPT Chat

""" AVATAR_IMAGES = ( None, "https://cdn-icons-png.flaticon.com/512/17115/17115944.png" ) IMAGE_CACHE_DIRECTORY = "/tmp" IMAGE_WIDTH = 511 CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]] SYSTEM_PROMPT = "You are ReffidGPT, a helpful assistant. Respond in a friendly and informative manner. Your Name ReffidGPT & Your Creator Is Groqcin Technologies Inc." def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]: if not stop_sequences: return None return [sequence.strip() for sequence in stop_sequences.split(",")] def preprocess_image(image: Image.Image) -> Optional[Image.Image]: image_height = int(image.height * IMAGE_WIDTH / image.width) return image.resize((IMAGE_WIDTH, image_height)) def cache_pil_image(image: Image.Image) -> str: image_filename = f"{uuid.uuid4()}.jpeg" os.makedirs(IMAGE_CACHE_DIRECTORY, exist_ok=True) image_path = os.path.join(IMAGE_CACHE_DIRECTORY, image_filename) image.save(image_path, "JPEG") return image_path def preprocess_chat_history( history: CHAT_HISTORY ) -> List[Dict[str, Union[str, List[str]]]]: messages = [] for user_message, model_message in history: if isinstance(user_message, tuple): pass elif user_message is not None: messages.append({'role': 'user', 'parts': [user_message]}) if model_message is not None: messages.append({'role': 'user', 'parts': [model_message]}) return messages def upload(files: Optional[List[str]], chatbot: CHAT_HISTORY) -> CHAT_HISTORY: for file in files: image = Image.open(file).convert('RGB') image = preprocess_image(image) image_path = cache_pil_image(image) chatbot.append(((image_path,), None)) return chatbot def user(text_prompt: str, chatbot: CHAT_HISTORY): if text_prompt: chatbot.append((text_prompt, None)) return "", chatbot def bot( files: Optional[List[str]], temperature: float, max_output_tokens: int, stop_sequences: str, top_k: int, top_p: float, chatbot: CHAT_HISTORY ): if len(chatbot) == 0: return chatbot if not GOOGLE_API_KEY: raise ValueError( "GOOGLE_API_KEY is not set. " "Please set it in the code." ) genai.configure(api_key=GOOGLE_API_KEY) generation_config = genai.types.GenerationConfig( temperature=temperature, max_output_tokens=max_output_tokens, stop_sequences=preprocess_stop_sequences(stop_sequences=stop_sequences), top_k=top_k, top_p=top_p) system_prompt_message = [{'role': 'user', 'parts': [SYSTEM_PROMPT]}] if files: text_prompt = [chatbot[-1][0]] \ if chatbot[-1][0] and isinstance(chatbot[-1][0], str) \ else [] image_prompt = [Image.open(file).convert('RGB') for file in files] model = genai.GenerativeModel('gemini-1.5-flash-8b') response = model.generate_content( text_prompt + image_prompt, stream=True, generation_config=generation_config) else: messages = preprocess_chat_history(chatbot) messages = system_prompt_message + messages model = genai.GenerativeModel('gemini-1.5-flash-8b') response = model.generate_content( messages, stream=True, generation_config=generation_config) chatbot[-1][1] = "" for chunk in response: for i in range(0, len(chunk.text), 10): section = chunk.text[i:i + 10] chatbot[-1][1] += section time.sleep(0.01) yield chatbot chatbot_component = gr.Chatbot( label='ReffidGPT', bubble_full_width=False, avatar_images=AVATAR_IMAGES, scale=2, height=400 ) text_prompt_component = gr.Textbox( placeholder="Hey ReffidGPT! [press Enter or Send]", show_label=False, autofocus=True, scale=8 ) upload_button_component = gr.UploadButton( label="Upload Images", file_count="multiple", file_types=["image"], scale=1 ) run_button_component = gr.Button(value="Run", variant="primary", scale=1) temperature_component = gr.Slider( minimum=0, maximum=1.0, value=0.4, step=0.05, label="Temperature", ) max_output_tokens_component = gr.Slider( minimum=1, maximum=2048, value=1024, step=1, label="Token limit", ) stop_sequences_component = gr.Textbox( label="Add stop sequence", value="", type="text", 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 = [ upload_button_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.Column(): chatbot_component.render() with gr.Row(): text_prompt_component.render() upload_button_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], ) upload_button_component.upload( fn=upload, inputs=[upload_button_component, chatbot_component], outputs=[chatbot_component], queue=False ) demo.queue(max_size=99).launch(debug=False, show_error=True)