import re import json import g4f import openai from typing import Tuple, List from termcolor import colored from dotenv import load_dotenv import os import google.generativeai as genai # Load environment variables load_dotenv("../.env") # Set environment variables OPENAI_API_KEY = os.getenv('OPENAI_API_KEY') openai.api_key = OPENAI_API_KEY GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY') genai.configure(api_key=GOOGLE_API_KEY) def generate_response(prompt: str, ai_model: str) -> str: """ Generate a script for a video, depending on the subject of the video. Args: video_subject (str): The subject of the video. ai_model (str): The AI model to use for generation. Returns: str: The response from the AI model. """ if ai_model == 'g4f': response = g4f.ChatCompletion.create( model=g4f.models.gpt_35_turbo_16k_0613, messages=[{"role": "user", "content": prompt}], ) elif ai_model in ["gpt3.5-turbo", "gpt4"]: model_name = "gpt-3.5-turbo" if ai_model == "gpt3.5-turbo" else "gpt-4-1106-preview" response = openai.chat.completions.create( model=model_name, messages=[{"role": "user", "content": prompt}], ).choices[0].message.content elif ai_model == 'gemmini': model = genai.GenerativeModel('gemini-pro') response_model = model.generate_content(prompt) response = response_model.text else: raise ValueError("Invalid AI model selected.") return response def generate_script(video_subject: str, paragraph_number: int, ai_model: str, voice: str, customPrompt: str) -> str: """ Generate a script for a video, depending on the subject of the video, the number of paragraphs, and the AI model. Args: video_subject (str): The subject of the video. paragraph_number (int): The number of paragraphs to generate. ai_model (str): The AI model to use for generation. Returns: str: The script for the video. """ # Build prompt if customPrompt: prompt = customPrompt else: prompt = """ Generate a script for a video, depending on the subject of the video. The script is to be returned as a string with the specified number of paragraphs. Here is an example of a string: "This is an example string." Do not under any circumstance reference this prompt in your response. Get straight to the point, don't start with unnecessary things like, "welcome to this video". Obviously, the script should be related to the subject of the video. YOU MUST NOT INCLUDE ANY TYPE OF MARKDOWN OR FORMATTING IN THE SCRIPT, NEVER USE A TITLE. YOU MUST WRITE THE SCRIPT IN THE LANGUAGE SPECIFIED IN [LANGUAGE]. ONLY RETURN THE RAW CONTENT OF THE SCRIPT. DO NOT INCLUDE "VOICEOVER", "NARRATOR" OR SIMILAR INDICATORS OF WHAT SHOULD BE SPOKEN AT THE BEGINNING OF EACH PARAGRAPH OR LINE. YOU MUST NOT MENTION THE PROMPT, OR ANYTHING ABOUT THE SCRIPT ITSELF. ALSO, NEVER TALK ABOUT THE AMOUNT OF PARAGRAPHS OR LINES. JUST WRITE THE SCRIPT. """ prompt += f""" Subject: {video_subject} Number of paragraphs: {paragraph_number} Language: {voice} """ # Generate script response = generate_response(prompt, ai_model) print(colored(response, "cyan")) # Return the generated script if response: # Clean the script # Remove asterisks, hashes response = response.replace("*", "") response = response.replace("#", "") # Remove markdown syntax response = re.sub(r"\[.*\]", "", response) response = re.sub(r"\(.*\)", "", response) # Split the script into paragraphs paragraphs = response.split("\n\n") # Select the specified number of paragraphs selected_paragraphs = paragraphs[:paragraph_number] # Join the selected paragraphs into a single string final_script = "\n\n".join(selected_paragraphs) # Print to console the number of paragraphs used print(colored(f"Number of paragraphs used: {len(selected_paragraphs)}", "green")) return final_script else: print(colored("[-] GPT returned an empty response.", "red")) return None def get_search_terms(video_subject: str, amount: int, script: str, ai_model: str) -> List[str]: """ Generate a JSON-Array of search terms for stock videos, depending on the subject of a video. Args: video_subject (str): The subject of the video. amount (int): The amount of search terms to generate. script (str): The script of the video. ai_model (str): The AI model to use for generation. Returns: List[str]: The search terms for the video subject. """ # Build prompt prompt = f""" Generate {amount} search terms for stock videos, depending on the subject of a video. Subject: {video_subject} The search terms are to be returned as a JSON-Array of strings. Each search term should consist of 1-3 words, always add the main subject of the video. YOU MUST ONLY RETURN THE JSON-ARRAY OF STRINGS. YOU MUST NOT RETURN ANYTHING ELSE. YOU MUST NOT RETURN THE SCRIPT. The search terms must be related to the subject of the video. Here is an example of a JSON-Array of strings: ["search term 1", "search term 2", "search term 3"] For context, here is the full text: {script} """ # Generate search terms response = generate_response(prompt, ai_model) # Parse response into a list of search terms search_terms = [] try: search_terms = json.loads(response) if not isinstance(search_terms, list) or not all(isinstance(term, str) for term in search_terms): raise ValueError("Response is not a list of strings.") except (json.JSONDecodeError, ValueError): print(colored("[*] GPT returned an unformatted response. Attempting to clean...", "yellow")) # Attempt to extract list-like string and convert to list match = re.search(r'\["(?:[^"\\]|\\.)*"(?:,\s*"[^"\\]*")*\]', response) if match: try: search_terms = json.loads(match.group()) except json.JSONDecodeError: print(colored("[-] Could not parse response.", "red")) return [] # Let user know print(colored(f"\nGenerated {len(search_terms)} search terms: {', '.join(search_terms)}", "cyan")) # Return search terms return search_terms def generate_metadata(video_subject: str, script: str, ai_model: str) -> Tuple[str, str, List[str]]: """ Generate metadata for a YouTube video, including the title, description, and keywords. Args: video_subject (str): The subject of the video. script (str): The script of the video. ai_model (str): The AI model to use for generation. Returns: Tuple[str, str, List[str]]: The title, description, and keywords for the video. """ # Build prompt for title title_prompt = f""" Generate a catchy and SEO-friendly title for a YouTube shorts video about {video_subject}. """ # Generate title title = generate_response(title_prompt, ai_model).strip() # Build prompt for description description_prompt = f""" Write a brief and engaging description for a YouTube shorts video about {video_subject}. The video is based on the following script: {script} """ # Generate description description = generate_response(description_prompt, ai_model).strip() # Generate keywords keywords = get_search_terms(video_subject, 6, script, ai_model) return title, description, keywords