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| import gradio as gr | |
| from gradio.inputs import Textbox, Slider | |
| import requests | |
| # Template | |
| title = "A conversation with some NPC in a Tavern 🍻" | |
| description = "" | |
| article = """ | |
| <p> If you liked don't forget to 💖 the project 🥰 </p> | |
| <h2> Parameters: </h2> | |
| <ul> | |
| <li><i>message</i>: what you want to say to the NPC.</li> | |
| <li><i>npc_name</i>: name of the NPC.</li> | |
| <li><i>npc_prompt</i>: prompt of the NPC, we can modify it to see if results are better.</li> | |
| <li><i>top_p</i>: control how deterministic the model is in generating a response.</li> | |
| <li><i>temperature</i>: (sampling temperature) higher values means the model will take more risks.</li> | |
| <li><i>max_new_tokens</i>: Max number of tokens in generation.</li> | |
| </ul> | |
| <img src='http://www.simoninithomas.com/test/gandalf.jpg', alt="Gandalf"/>""" | |
| theme="huggingface" | |
| # Builds the prompt from what previously happened | |
| def build_prompt(conversation, context, interlocutor_names): | |
| prompt = context + "\n" | |
| for player_msg, npc_msg in conversation: | |
| line = "\n- " + interlocutor_names[0] + ":" + player_msg | |
| prompt += line | |
| line = "\n- " + interlocutor_names[1] + ":" + npc_msg | |
| prompt += line | |
| prompt += "" | |
| return prompt | |
| # Recognize what the model said, if it used the correct format | |
| def clean_chat_output(txt, prompt, interlocutor_names): | |
| delimiter = "\n- "+interlocutor_names[0] | |
| output = txt.replace(prompt, '') | |
| output = output[:output.find(delimiter)] | |
| return output | |
| # GPT-J-6B API | |
| API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B" | |
| def query(payload): | |
| response = requests.post(API_URL, json=payload) | |
| return response.json() | |
| def chat(message, npc_name, initial_prompt, top_p, temperature, max_new_tokens, history=[]): | |
| interlocutor_names = ["Player", npc_name] | |
| print("message", message) | |
| print("npc_name", npc_name) | |
| print("initial_prompt", initial_prompt) | |
| print("top_p", top_p) | |
| print("temperature", temperature) | |
| print("max_new_tokens", max_new_tokens) | |
| print("history", history) | |
| response = "Test" | |
| history.append((message, "")) | |
| conversation = history | |
| # Build the prompt | |
| prompt = build_prompt(conversation, initial_prompt, interlocutor_names) | |
| # Build JSON | |
| json_req = {"inputs": prompt, | |
| "parameters": | |
| { | |
| "top_p": top_p, | |
| "temperature": temperature, | |
| "max_new_tokens": max_new_tokens, | |
| "return_full_text": False | |
| }} | |
| # Get the output | |
| output = query(json_req) | |
| output = output[0]['generated_text'] | |
| print("output", output) | |
| answer = clean_chat_output(output, prompt, interlocutor_names) | |
| response = answer | |
| print("response", answer) | |
| history[-1] = (message, response) | |
| return history, history | |
| #io = gr.Interface.load("huggingface/EleutherAI/gpt-j-6B") | |
| iface = gr.Interface(fn=chat, | |
| inputs=[Textbox(label="message", placeholder="Hello!"), | |
| Textbox(label="npc_name", placeholder="Antoine"), | |
| Textbox(label="initial_prompt", placeholder="The following is a conversation with Antoine, a guard for Northfall that's drinking in the Tavern."), | |
| Slider(minimum=0.5, maximum=1, step=0.05, default=0.9, label="top_p"), | |
| Slider(minimum=0.5, maximum=1.5, step=0.1, default=1.1, label="temperature"), | |
| Slider(minimum=20, maximum=250, step=10, default=50, label="max_new_tokens"), | |
| "state"], | |
| outputs=["chatbot","state"], | |
| #examples = [["Hello!", "", , 0.9, 1.1, 50, iface.state]], | |
| allow_screenshot=True, | |
| allow_flagging=True, | |
| title=title, | |
| article=article, | |
| theme=theme) | |
| if __name__ == "__main__": | |
| iface.launch() |