Spaces:
Runtime error
Runtime error
| import warnings | |
| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| warnings.filterwarnings('ignore') | |
| # Initialize the language model | |
| generator = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
| def generate_script(host_name, listener_location, causes_climate_change, co2_level, effects_climate_change, | |
| sea_level_rise, warming_rate, potential_solutions, individual_role, call_to_action, | |
| TOPIC, DESCRIPTION): | |
| try: | |
| # Variables and template definitions... | |
| introduction_template = f"{host_name}, good morning! This is {listener_location}'s local radio station. Today we're talking about an issue that affects us all - {TOPIC}. It's a pressing issue that requires our immediate attention..." | |
| causes_template = f"The causes of {TOPIC} are {causes_climate_change}. Today, the level of CO2 in our atmosphere is {co2_level}, which is concerning..." | |
| effects_template = f"These activities result in {effects_climate_change}, leading to drastic changes in our environment. For instance, sea levels are rising at a rate of {sea_level_rise} per year, and global temperatures are increasing at a rate of {warming_rate} per decade..." | |
| solutions_template = f"But don't worry, there are solutions. {potential_solutions} are all steps we can take to mitigate these effects..." | |
| role_template = f"Each one of us plays a role in combating {TOPIC}. Even small actions can make a big difference. In fact, our location, {listener_location}, is particularly vulnerable to {TOPIC} due to its geographical features..." | |
| action_template = f"So, {listener_location}, why wait? Start taking steps today towards a greener future. Support local businesses that prioritize sustainability, reduce your carbon footprint, and voice your opinion to policy makers..." | |
| summary_template = f"In conclusion, {TOPIC} is a serious issue that requires our immediate attention. But by understanding its causes, effects, and potential solutions, we can all play a part in mitigating its impact. Thank you for joining us today, and remember, every small action counts!" | |
| # Combine templates based on the DESCRIPTION | |
| prompt_template = f"""{introduction_template} {causes_template} {effects_template} {solutions_template} {role_template} {action_template} {summary_template} | |
| TOPIC: {TOPIC}. DESCRIPTION: {DESCRIPTION}""" | |
| # Generate the script using the language model | |
| script = generator.text_generation(prompt_template)[0]['generated_text'] | |
| if isinstance(response, list): | |
| script = response[0].get('generated_text', '') | |
| else: | |
| script = response.get('generated_text', '') | |
| # Split the script into sections | |
| sections = script.split("\n") | |
| # Calculate the word count for each section | |
| word_counts = [len(section.split()) for section in sections] | |
| # Check if any section exceeds the target word count | |
| for i, count in enumerate(word_counts): | |
| if count > 200: | |
| return f"Warning: Section {i + 1} exceeds the target word count. You may need to shorten this section." | |
| return script | |
| except Exception as e: | |
| error_message = f"Error: {e}" | |
| # Save error log to a file | |
| with open("./error_log.txt", "a") as log_file: | |
| log_file.write(error_message + "\n") | |
| return error_message | |
| # Gradio interface setup... | |
| iface = gr.Interface(fn=generate_script, | |
| inputs=[gr.Textbox(label="Host Name", value="John"), | |
| gr.Textbox(label="Listener Location", value="City"), | |
| gr.Textbox(label="Causes Climate Change", value="human activities"), | |
| gr.Number(label="CO2 Level", value=400), | |
| gr.Textbox(label="Effects Climate Change", value="rising temperatures"), | |
| gr.Number(label="Sea Level Rise", value=0.1), | |
| gr.Number(label="Warming Rate", value=0.2), | |
| gr.Textbox(label="Potential Solutions", value="renewable energy"), | |
| gr.Textbox(label="Individual Role", value="reduce carbon footprint"), | |
| gr.Textbox(label="Call To Action", value="act now")], | |
| outputs="text") | |
| # Launch the interface | |
| iface.launch(debug=True) | |