app.py

import gradio as gr
from anthropic import Anthropic
from openai import OpenAI
import openai
import json
import uuid
import os

default_urls = ["https://api.anthropic.com", "https://api.openai.com/v1"]

# List of available Claude models
claude_models = ["claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307"]

# List of available OpenAI models
openai_models = ["gpt-4", "gpt-4-32k", "gpt-3.5-turbo", "gpt-4-0125-preview", "gpt-4-turbo-preview", "gpt-4-1106-preview", "gpt-4-0613"]

both_models = claude_models + openai_models

def generate_response(endpoint, api_key, model, user_prompt):
    print(endpoint)
    if endpoint in default_urls:
        #check api keys as normal
        if api_key.startswith("sk-ant-"):
            client = Anthropic(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "json.txt")
        elif api_key.startswith("sk-"):
            client = OpenAI(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "json.txt")
        else:
            print("Invalid API key")
            return "Invalid API key", "Invalid API key", None
    else:
        if model in claude_models:
            # Set the Anthropic API key
            client = Anthropic(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "json.txt")
        else:
            # Set the OpenAI API key
            client = OpenAI(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "json.txt")

    # Read the system prompt from a text file
    with open(system_prompt_path, "r") as file:
        system_prompt = file.read()

    if model in claude_models:
        # Generate a response using the selected Anthropic model
        try:
            response = client.messages.create(
                system=system_prompt,
                messages=[{"role": "user", "content": user_prompt}],
                model=model,
                max_tokens=4096
            )
            response_text = response.content[0].text
        except Exception as e:
            print(e)
            response_text = "An error occurred while generating the response. Check that your API key is correct!"
    else:
        try:
            # Generate a response using the selected OpenAI model
            response = client.chat.completions.create(
                model=model,
                messages=[
                    {"role": "system", "content": system_prompt},
                    {"role": "user", "content": user_prompt}
                ],
                max_tokens=4096
            )
            response_text = response.choices[0].message.content
        except Exception as e:
            print(e)
            response_text = "An error occurred while generating the response. Check that your API key is correct!"

    json_string, json_json = extract_json(response_text)
    json_file = json_string if json_string else None
    create_unique_id = str(uuid.uuid4())

    json_folder = __file__.replace("app.py", f"outputs/")
    if not os.path.exists(json_folder):
        os.makedirs(json_folder)
    path = None
    if json_string:
        with open(f"{json_folder}{json_json['name']}_{create_unique_id}.json", "w") as file:
            file.write(json_file)
        path = f"{json_folder}{json_json['name']}_{create_unique_id}.json"
    else:
        json_string = "No JSON data was found, or the JSON data was incomplete."
    return response_text, json_string or "", path

def extract_json(generated_output):
    try:
        generated_output = generated_output.replace("```json", "").replace("```", "").strip()
        # Find the JSON string in the generated output
        json_start = generated_output.find("{")
        json_end = generated_output.rfind("}") + 1
        json_string = generated_output[json_start:json_end]
        print(json_string)

        # Parse the JSON string
        json_data = json.loads(json_string)
        json_data['name'] = json_data['char_name']
        json_data['personality'] = json_data['char_persona']
        json_data['scenario'] = json_data['world_scenario']
        json_data['first_mes'] = json_data['char_greeting']
        # Check if all the required keys are present
        required_keys = ["char_name", "char_persona", "world_scenario", "char_greeting", "example_dialogue", "description"]
        if all(key in json_data for key in required_keys):
            return json.dumps(json_data), json_data
        else:
            return None, None
    except Exception as e:
        print(e)
        return None, None

def generate_second_response(endpoint, api_key, model, generated_output):
    if endpoint in default_urls:
        #check api keys as normal
        if api_key.startswith("sk-ant-"):
            client = Anthropic(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "diffusion.txt")
        elif api_key.startswith("sk-"):
            client = OpenAI(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "diffusion.txt")
        else:
            print("Invalid API key")
            return "Invalid API key", "Invalid API key", None
    else:
        if model in claude_models:
            # Set the Anthropic API key
            client = Anthropic(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "diffusion.txt")
        else:
            # Set the OpenAI API key
            client = OpenAI(api_key=api_key, base_url=endpoint)
            system_prompt_path = __file__.replace("app.py", "diffusion.txt")

    # Read the system prompt from a text file
    with open(system_prompt_path, "r") as file:
        system_prompt = file.read()

    if model in claude_models:
        try:
            # Generate a second response using the selected Anthropic model and the previously generated output
            response = client.messages.create(
                system=system_prompt,
                messages=[{"role": "user", "content": generated_output}],
                model=model,
                max_tokens=4096
            )
            response_text = response.content[0].text
        except Exception as e:
            print(e)
            response_text = "An error occurred while generating the response. Check that your API key is correct!"
    else:
        try:
            # Generate a response using the selected OpenAI model
            response = client.chat.completions.create(
                model=model,
                messages=[
                    {"role": "system", "content": system_prompt},
                    {"role": "user", "content": generated_output}
                ],
                max_tokens=4096
            )
            response_text = response.choices[0].message.content
        except Exception as e:
            print(e)
            response_text = "An error occurred while generating the response. Check that your API key is correct!"

    return response_text

# Set up the Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# SillyTavern Character Generator")

    #Text explaining that you can use the API key from the Anthropic API or the OpenAI API
    gr.Markdown("You can use the API key from the Anthropic API or the OpenAI API. The API key should start with 'sk-ant-' for Anthropic or 'sk-' for OpenAI.")

    with gr.Row():
        with gr.Column():
            endpoint = gr.Textbox(label="Endpoint", value="https://api.anthropic.com")
            api_key = gr.Textbox(label="API Key", type="password", placeholder="sk-ant-api03-... or sk-...")
            model_dropdown = gr.Dropdown(choices=[], label="Select a model")
            user_prompt = gr.Textbox(label="User Prompt", value="Make me a card for a panther made of translucent pastel colored goo. Its color never changes once it exists but each 'copy' has a different color. The creature comes out of a small jar, seemingly defying physics with its size. It is the size of a real panther, and as strong as one too. By default its female but is able to change gender. It can even split into multiple copies of itself if needed with no change in its own size or mass. Its outside is normally lightly squishy but solid, but on command it can become viscous like non-newtonian fluids. Be descriptive when describing this character, and make sure to describe all of its features in char_persona just like you do in description. Make sure to describe commonly used features in detail (visual, smell, taste, touch, etc).")
            generate_button = gr.Button("Generate JSON")

        with gr.Column():
            generated_output = gr.Textbox(label="Generated Output")
            json_output = gr.Textbox(label="JSON Output")
            json_download = gr.File(label="Download JSON")

    with gr.Row():
        with gr.Column():
            generate_button_2 = gr.Button("Generate SDXL Prompt")

        with gr.Column():
            generated_output_2 = gr.Textbox(label="Generated SDXL Prompt")

    def update_models(api_key):
        if api_key.startswith("sk-ant-"):
            return gr.Dropdown(choices=claude_models), gr.Textbox(label="Endpoint", value="https://api.anthropic.com")
        elif api_key.startswith("sk-"):
            return gr.Dropdown(choices=openai_models), gr.Textbox(label="Endpoint", value="https://api.openai.com/v1")
        else:
            return gr.Dropdown(choices=both_models), gr.Textbox(label="Endpoint", value="https://api.anthropic.com")

    api_key.change(update_models, inputs=api_key, outputs=[model_dropdown, endpoint])

    generate_button.click(generate_response, inputs=[endpoint, api_key, model_dropdown, user_prompt], outputs=[generated_output, json_output, json_download])
    generate_button_2.click(generate_second_response, inputs=[endpoint, api_key, model_dropdown, generated_output], outputs=generated_output_2)

demo.launch()