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import gradio as gr
import requests
# GPT-J-6B API
API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B"
headers = {"Authorization": "Bearer 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"}
prompt = """
me: I'm Twimbly Twombly. I live in California. I'm a robot."""
prev_chat = """
you: Hello. How are you?
me: I'm fine"""
examples = [["how are you?"], ["hello"]]
def chat_generate(word):
# print(f"**current reply")
global prev_chat
p = prompt + prev_chat + "\n" + "you: " + word.lower() + "\n" + "me: "
print(f"*****Inside chat_generate - Prompt is :{p}")
json_ = {"inputs": p,
"parameters":
{
"top_p": 0.9,
"temperature": 1.1,
"max_new_tokens": 50,
"return_full_text": False
}}
response = requests.post(API_URL, headers=headers, json=json_)
output = response.json()
output_tmp = output[0]['generated_text']
reply = output_tmp.split("you:")[0] # +"."
print(f"Chat Response being returned is: {reply}")
prev_chat = "you: " + word.lower() + "\n" + "me: " + reply
return reply
def text_to_image(reply):
print("*****Inside Text_to_image")
reply = " ".join(reply.split('\n'))
reply = reply + " oil on canvas."
steps, width, height, images, diversity = '50','256','256','1',15
img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(reply, steps, width, height, images, diversity)[0]
return img
demo = gr.Blocks()
with demo:
gr.Markdown("<h1><center>Twimbly Twombly</center></h1>")
gr.Markdown(
"<div>Hi I'm Twimbly Twombly ready to talk to you.</div>"
)
input_word = gr.Textbox(placeholder="Enter a word here to chat..")
chat_txt = gr.Textbox(lines=1)
# output_image = gr.Image(type="filepath", shape=(256,256))
b1 = gr.Button("Send")
#b2 = gr.Button("Imagine")
b1.click(chat_generate, input_word, chat_txt)
#b2.click(text_to_image, chat_txt, output_image)
#examples=examples
demo.launch(enable_queue=True, debug=True) |