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# Copyright (c) Kuaishou.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import base64
import numpy as np
os.system('pip install huggingface_hub gradio openai keye_vl_utils torch torchvision -U')
from argparse import ArgumentParser
from pathlib import Path
import copy
import gradio as gr
import os
import re
import tempfile
from openai import OpenAI
from PIL import Image
from io import BytesIO
from keye_vl_utils import fetch_video, process_vision_info
def _get_args():
parser = ArgumentParser()
parser.add_argument("--share", action="store_true", default=False,
help="Create a publicly shareable link for the interface.")
parser.add_argument("--inbrowser", action="store_true", default=False,
help="Automatically launch the interface in a new tab on the default browser.")
parser.add_argument("--server-port", type=int, default=7860,
help="Demo server port.")
parser.add_argument("--server-name", type=str, default="127.0.0.1",
help="Demo server name.")
args = parser.parse_args()
return args
def _parse_text(text):
lines = text.split("\n")
lines = [line for line in lines if line != ""]
count = 0
for i, line in enumerate(lines):
line = line.replace("<think>", "**ζθθΏη¨εΌε§**οΌ\n")
line = line.replace("</think>", "\n**ζθθΏη¨η»ζ**\n")
line = line.replace("<answer>", "**εηεΌε§**οΌ\n")
line = line.replace("</answer>", "\n**εηη»ζ**\n")
line = line.replace("<analysis>", "**εζεΌε§**οΌ\n")
line = line.replace("</analysis>", "\n**εζη»ζ**\n")
if "```" in line:
count += 1
items = line.split("`")
if count % 2 == 1:
lines[i] = f'<pre><code class="language-{items[-1]}">'
else:
lines[i] = f"<br></code></pre>"
else:
if True or i > 0:
if count % 2 == 1:
line = line.replace("`", r"\`")
line = line.replace("<", "<")
line = line.replace(">", ">")
line = line.replace(" ", " ")
line = line.replace("*", "*")
line = line.replace("_", "_")
line = line.replace("-", "-")
line = line.replace(".", ".")
line = line.replace("!", "!")
line = line.replace("(", "(")
line = line.replace(")", ")")
line = line.replace("$", "$")
lines[i] = "<br>" + line
text = "".join(lines)
return text
def is_video_file(filename):
video_extensions = ['.mp4', '.avi', '.mkv', '.mov', '.wmv', '.flv', '.webm', '.mpeg']
return any(filename.lower().endswith(ext) for ext in video_extensions)
def video_processor(video_path):
video_inputs, video_sample_fps = fetch_video({"video": video_path, "max_frames": 8, "max_pixels": 256*28*28}, return_video_sample_fps=True)
video_input = video_inputs.permute(0, 2, 3, 1).numpy().astype(np.uint8)
# encode image with base64
base64_frames = []
for frame in video_input:
img = Image.fromarray(frame)
output_buffer = BytesIO()
img.save(output_buffer, format="jpeg")
byte_data = output_buffer.getvalue()
base64_str = base64.b64encode(byte_data).decode("utf-8")
base64_frames.append(base64_str)
video_info = {
"type": "video_url",
"video_url": {"url": f"data:video/jpeg;base64,{','.join(base64_frames)}"}
}
return video_info
def _launch_demo(args):
EP_URL = os.getenv("ENDPOINT_URL")
HF_TOKEN = os.getenv("HF_TOKEN")
client = OpenAI(
base_url=f"{EP_URL}/v1/",
api_key=HF_TOKEN
)
def predict(_chatbot, task_history):
chat_query = _chatbot[-1][0]
query = task_history[-1][0]
if len(chat_query) == 0:
_chatbot.pop()
task_history.pop()
return _chatbot
print("User: " + _parse_text(query))
history_cp = copy.deepcopy(task_history)
full_response = ""
messages = []
content = []
for q, a in history_cp:
if isinstance(q, (tuple, list)):
if is_video_file(q[0]):
video_info = video_processor(q[0])
content.append(video_info)
else:
# convert image to base64
with open(q[0], 'rb') as img_file:
img_base64 = base64.b64encode(img_file.read()).decode('utf-8')
content.append({'type': 'image_url', 'image_url': {"url": f"data:image/jpeg;base64,{img_base64}"}})
else:
content.append({'type': 'text', 'text': q})
messages.append({'role': 'user', 'content': content})
messages.append({'role': 'assistant', 'content': [{'type': 'text', 'text': a}]})
content = []
messages.pop()
responses = client.chat.completions.create(
model="Kwai-Keye/Keye-VL-8B-Preview",
messages=messages,
top_p=0.95,
temperature=0.6,
stream=True,
timeout=360
)
response_text = ""
for response in responses:
response = response.choices[0].delta.content
response_text += response
_chatbot[-1] = (chat_query, _parse_text(response_text))
yield _chatbot
response = response_text
_chatbot[-1] = (chat_query, _parse_text(response))
full_response = _parse_text(response)
task_history[-1] = (query, full_response)
print("Kwai-Keye-VL-Chat: " + full_response)
yield _chatbot
def regenerate(_chatbot, task_history):
if not task_history:
return _chatbot
item = task_history[-1]
if item[1] is None:
return _chatbot
task_history[-1] = (item[0], None)
chatbot_item = _chatbot.pop(-1)
if chatbot_item[0] is None:
_chatbot[-1] = (_chatbot[-1][0], None)
else:
_chatbot.append((chatbot_item[0], None))
_chatbot_gen = predict(_chatbot, task_history)
for _chatbot in _chatbot_gen:
yield _chatbot
def add_text(history, task_history, text):
task_text = text
history = history if history is not None else []
task_history = task_history if task_history is not None else []
history = history + [(_parse_text(text), None)]
task_history = task_history + [(task_text, None)]
return history, task_history, ""
def add_file(history, task_history, file):
history = history if history is not None else []
task_history = task_history if task_history is not None else []
history = history + [((file.name,), None)]
task_history = task_history + [((file.name,), None)]
return history, task_history
def reset_user_input():
return gr.update(value="")
def reset_state(task_history):
task_history.clear()
return []
with gr.Blocks() as demo:
gr.Markdown("""<center><font size=3> Kwai-Keye-VL Demo </center>""")
chatbot = gr.Chatbot(label='Kwai-Keye-VL', elem_classes="control-height", height=500)
query = gr.Textbox(lines=2, label='Input')
task_history = gr.State([])
with gr.Row():
addfile_btn = gr.UploadButton("π Upload (δΈδΌ ζδ»Ά)", file_types=["image", "video"])
submit_btn = gr.Button("π Submit (ει)")
regen_btn = gr.Button("π€οΈ Regenerate (ιθ―)")
empty_bin = gr.Button("π§Ή Clear History (ζΈ
ι€εε²)")
submit_btn.click(add_text, [chatbot, task_history, query], [chatbot, task_history]).then(
predict, [chatbot, task_history], [chatbot], show_progress=True
)
submit_btn.click(reset_user_input, [], [query])
empty_bin.click(reset_state, [task_history], [chatbot], show_progress=True)
regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True)
addfile_btn.upload(add_file, [chatbot, task_history, addfile_btn], [chatbot, task_history], show_progress=True)
demo.queue(default_concurrency_limit=40).launch(
share=args.share,
)
def main():
args = _get_args()
_launch_demo(args)
if __name__ == '__main__':
main() |