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import gradio as gr
import os
import time
import torch
from transformers import pipeline
pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device_map="auto")
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate",
},
# {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
]
def greet(name):
return "Hello " + name + "!!"
#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
#iface.launch()
# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.
def print_like_dislike(x: gr.LikeData):
print(x.index, x.value, x.liked)
def add_ia_text(history, text):
messages.append({"role": "user", "content": text})
print(messages)
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
print("prompt")
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print("output")
response = (outputs[0]["generated_text"])# type: ignore
print(response)
history = history + [response, None]
def add_text(history, text):
history = history + [(text, None)]
add_ia_text(history, text)
return history, gr.Textbox(value="", interactive=False)
def add_file(history, file):
history = history + [((file.name,), None)]
return history
def bot(history):
response = "**That's cool!**"
history[-1][1] = ""
for character in response:
history[-1][1] += character
time.sleep(0.05)
yield history
with gr.Blocks() as demo:
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
bubble_full_width=False,
avatar_images=(None, (os.path.join(os.path.dirname(__file__), "avatar.png"))),
)
with gr.Row():
txt = gr.Textbox(
scale=4,
show_label=False,
placeholder="Enter text and press enter, or upload an image",
container=False,
)
btn = gr.UploadButton("📁", file_types=["image", "video", "audio"])
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, chatbot, chatbot, api_name="bot_response"
)
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
file_msg = btn.upload(add_file, [chatbot, btn], [chatbot], queue=False).then(
bot, chatbot, chatbot
)
chatbot.like(print_like_dislike, None, None)
demo.queue()
if __name__ == "__main__":
demo.launch()
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