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| 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 = os.environ.get("GOOGLE_API_KEY") | |
| TITLE = """<h1 align="center">Gemini Movie Editor Assitant (Product Concept)</h1>""" | |
| SUBTITLE = """<h2 align="center">Movie Editing Agent built with Gemini Pro and Gemini Pro Vision API</h2>""" | |
| GETKEY = """ | |
| <div style="text-align: center; display: flex; justify-content: center; align-items: center;"> | |
| <span>Get an API key | |
| <a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>. | |
| </span> | |
| </div> | |
| """ | |
| movie_script = """ | |
| Orion, in his futuristic apartment, discovers a cryptic message about an ancient artifact. | |
| Compelled by curiosity, he embarks on a quest, joined by his skilled friend, Luna. | |
| They navigate through uncharted territories and ancient ruins, solving puzzles and overcoming traps. | |
| Together, they uncover a hidden chamber and retrieve the powerful artifact, | |
| but not without triggering an alarm. In a tense escape, Luna is injured, and Orion uses the artifact to save her. | |
| They return to the city, changed by their journey, with Orion resolved to use the artifact for the greater good, | |
| as they stand looking towards a new future. | |
| """ | |
| AVATAR_IMAGES = ( | |
| None, | |
| "https://media.roboflow.com/spaces/gemini-icon.png" | |
| ) | |
| IMAGE_CACHE_DIRECTORY = "/tmp" | |
| IMAGE_WIDTH = 512 | |
| CHAT_HISTORY = List[Tuple[Optional[Union[Tuple[str], str]], Optional[str]]] | |
| 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': 'model', '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( | |
| google_key: str, | |
| 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 | |
| google_key = google_key if google_key else GOOGLE_API_KEY | |
| if not google_key: | |
| raise ValueError( | |
| "GOOGLE_API_KEY is not set. " | |
| "Please follow the instructions in the README to set it up.") | |
| 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=stop_sequences), | |
| top_k=top_k, | |
| top_p=top_p) | |
| 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-pro-vision') | |
| response = model.generate_content( | |
| text_prompt + image_prompt, | |
| stream=True, | |
| generation_config=generation_config) | |
| else: | |
| messages = preprocess_chat_history(chatbot) | |
| model = genai.GenerativeModel('gemini-pro') | |
| response = model.generate_content( | |
| messages, | |
| stream=True, | |
| generation_config=generation_config) | |
| # streaming effect | |
| 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 | |
| google_key_component = gr.Textbox( | |
| label="GOOGLE API KEY", | |
| value="", | |
| type="password", | |
| placeholder="...", | |
| info="You have to provide your own GOOGLE_API_KEY for this app to function properly", | |
| visible=GOOGLE_API_KEY is None | |
| ) | |
| chatbot_component = gr.Chatbot( | |
| label='Gemini', | |
| bubble_full_width=False, | |
| avatar_images=AVATAR_IMAGES, | |
| scale=2, | |
| height=400 | |
| ) | |
| text_prompt_component = gr.Textbox( | |
| placeholder="Hi there! [press Enter]", 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", | |
| info=( | |
| "Temperature controls the degree of randomness in token selection. Lower " | |
| "temperatures are good for prompts that expect a true or correct response, " | |
| "while higher temperatures can lead to more diverse or unexpected results. " | |
| )) | |
| max_output_tokens_component = gr.Slider( | |
| minimum=1, | |
| maximum=2048, | |
| value=1024, | |
| step=1, | |
| label="Token limit", | |
| info=( | |
| "Token limit determines the maximum amount of text output from one prompt. A " | |
| "token is approximately four characters. The default value is 2048." | |
| )) | |
| stop_sequences_component = gr.Textbox( | |
| label="Add stop sequence", | |
| value="", | |
| type="text", | |
| placeholder="STOP, END", | |
| info=( | |
| "A stop sequence is a series of characters (including spaces) that stops " | |
| "response generation if the model encounters it. The sequence is not included " | |
| "as part of the response. You can add up to five stop sequences." | |
| )) | |
| top_k_component = gr.Slider( | |
| minimum=1, | |
| maximum=40, | |
| value=32, | |
| step=1, | |
| label="Top-K", | |
| info=( | |
| "Top-k changes how the model selects tokens for output. A top-k of 1 means the " | |
| "selected token is the most probable among all tokens in the model’s " | |
| "vocabulary (also called greedy decoding), while a top-k of 3 means that the " | |
| "next token is selected from among the 3 most probable tokens (using " | |
| "temperature)." | |
| )) | |
| top_p_component = gr.Slider( | |
| minimum=0, | |
| maximum=1, | |
| value=1, | |
| step=0.01, | |
| label="Top-P", | |
| info=( | |
| "Top-p changes how the model selects tokens for output. Tokens are selected " | |
| "from most probable to least until the sum of their probabilities equals the " | |
| "top-p value. For example, if tokens A, B, and C have a probability of .3, .2, " | |
| "and .1 and the top-p value is .5, then the model will select either A or B as " | |
| "the next token (using temperature). " | |
| )) | |
| user_inputs = [ | |
| text_prompt_component, | |
| chatbot_component | |
| ] | |
| bot_inputs = [ | |
| google_key_component, | |
| 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: | |
| with gr.Tab("Step 1: Script Writer"): | |
| gr.HTML(TITLE) | |
| gr.HTML("""<a href="https://chat.openai.com/g/g-x1Tr1tOTS-movie-script-maker">Movie Script Maker Custom GPT</a>""") | |
| gr.HTML("""<a href="https://www.linkedin.com/feed/update/urn:li:activity:7143126271470804993/">How This Script Was Made</a>""") | |
| gr.Image(value="resources/step1image.jpg") | |
| with gr.Tab("Step 2: llamaIndex Analyser"): | |
| gr.HTML(TITLE) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Textbox(value = movie_script, label="Movie Script", lines=18, interactive=False ) | |
| with gr.Column(scale=4): | |
| gr.Image(value="resources/imageset.jpg") | |
| with gr.Tab("Setp 3: Gemini Frame Arrranger"): | |
| gr.HTML(TITLE) | |
| gr.HTML(SUBTITLE) | |
| gr.HTML(GETKEY) | |
| with gr.Column(): | |
| google_key_component.render() | |
| 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 | |
| ) | |
| with gr.Tab("Step 4: Movie Maker"): | |
| gr.HTML(TITLE) | |
| with gr.Tab("Step 5: Movie"): | |
| gr.HTML(TITLE) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Textbox(value = movie_script, label="Movie Script", lines=18, interactive=False ) | |
| with gr.Column(scale=4): | |
| gr.Video(value="resources/GPTMovie2.mp4") | |
| with gr.Tab("Step 6: TruEra RAG"): | |
| gr.HTML(TITLE) | |
| gr.HTML("""<a href="https://chat.openai.com/g/g-5WT6q5do0-truera-lesson-creator">TruEra RAG Custom GPT</a>""") | |
| gr.Image(value="resources/trag.jpg") | |
| demo.queue(max_size=99).launch(debug=False, show_error=True) |