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import time
import gradio as gr
import openai
from prompt import setup_prompt
from api_keys import gpt_api_key
import utils
import os
openai.api_key = gpt_api_key
messages = []
# system_msg = input("What type of chatbot would you like to create?\n")
messages.append({"role": "system", "content": setup_prompt})
messages.append({"role": "user", "content": "hi, I want to build a 3d model"})
response = openai.ChatCompletion.create(
model="gpt-4",
messages=messages, temperature = 1.2)
reply = response["choices"][0]["message"]["content"]
messages.append({"role": "assistant", "content": reply})
print("\n" + reply + "\n")
meshy_prompt = ""
model_path = "../house_light/model.glb"
cnt = 0
def solve():
global model_path
# time.sleep(3)
extracted_text = utils.extract_text_surrounded_by_backticks(meshy_prompt)
begin = meshy_prompt.find("{")
end = meshy_prompt.find("}")
print(meshy_prompt[begin:end+1])
payload = utils.text_to_3d_gen(meshy_prompt[begin:end+1])
taskid = utils.create_meshy_object(payload)
utils.download_model(taskid)
return os.path.join(os.path.dirname(os.path.abspath(__file__)), f"{taskid}.glb")
def slow_echo(message, history):
global cnt
global messages
global meshy_prompt
global model_path
messages.append({"role": "user", "content": message})
response = openai.ChatCompletion.create(
model="gpt-4",
messages=messages, temperature = 1.2)
reply = response["choices"][0]["message"]["content"]
messages.append({"role": "assistant", "content": reply})
print("\n" + reply + "\n")
if reply[len(reply)-1] == '1' or reply[len(reply)-2] == '1':
print("start generating")
meshy_prompt = reply
reply = "Generating..."
# cnt += 1
# if cnt == 1 :
# model_path = "../house_light/model.glb"
# elif cnt == 2 :
# model_path = "../house_dark/model.glb"
for i in range(len(reply)):
time.sleep(0.02)
yield reply[:i+1]
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
chatbot = gr.ChatInterface(fn = slow_echo, title="SpacialSynergy", examples=["hi, I want to build a 3d model"]).queue()
with gr.Column():
interface = gr.Interface(
fn=solve,
title = "3D Model",
inputs=None,
outputs = ["model3d"],
)
demo.launch(share = False) |