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#!/usr/bin/env python | |
import os | |
from threading import Thread | |
from typing import Iterator | |
import gradio as gr | |
import spaces | |
import torch | |
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer | |
from peft import PeftModel, PeftConfig | |
DESCRIPTION = "# MergeLlama-7b\nThis is a conversational interface powered by the MergeLlama-7b model, a finetune of CodeLlama-7b designed to assist developers in resolving merge conflicts in their code. " | |
DESCRIPTION += "It leverages the capabilities of deep learning to provide suggestions for reconciling code differences, presenting potential resolutions for highlighted changes\n" | |
DESCRIPTION += "The feedback from this space will help develop future versions including more powerful 13b and 34b versions." | |
DESCRIPTION += "\n# How to use: \n" | |
DESCRIPTION += "1. Input your merge conflict in the chat in the following format:\n```\n<<<<<<<\n[Current change]\n=======\n[Incoming change]\n>>>>>>>\n```\n" | |
DESCRIPTION += "The model will generate the merge resolution. Context can be added before the conflict and multiple conflicts/resolutions can be chained together for context.\n" | |
DESCRIPTION += "**Additional Information:**\n" | |
DESCRIPTION += "- The model behind this tool is based on the MergeLlama dataset, which can be found [here](https://huggingface.co/datasets/codys12/MergeLlama).\n" | |
DESCRIPTION += "- For more information about the MergeLlama-7b model, visit [here](https://huggingface.co/codys12/MergeLlama-7b).\n" | |
DESCRIPTION += "- If you are interested in supporting the larger versions of this model, such as the 13b and 34b variants, you can check them out [here](https://www.dreamcatcher.co/ProjectPage?projectId=uibaxk4sfzetpkg7ch71ui).\n" | |
DESCRIPTION += "- This model was trained on [DreamcatcherAI](https://www.dreamcatcher.co/Discover)\n" | |
if not torch.cuda.is_available(): | |
DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>" | |
MAX_MAX_NEW_TOKENS = 2048 | |
DEFAULT_MAX_NEW_TOKENS = 256 | |
MAX_INPUT_TOKEN_LENGTH = 4096 | |
if torch.cuda.is_available(): | |
model_id = "codys12/MergeLlama-7b" | |
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float16, device_map=0, cache_dir="/data") | |
tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-7b-hf", trust_remote_code=True) | |
tokenizer.pad_token = tokenizer.eos_token | |
tokenizer.padding_side = "right" | |
def generate( | |
message: str, | |
chat_history: list[tuple[str, str]], | |
max_new_tokens: int = 1024, | |
#temperature: float = 0.6, | |
#top_p: float = 0.9, | |
#top_k: int = 50, | |
#repetition_penalty: float = 1.2, | |
) -> Iterator[str]: | |
conversation = [] | |
current_input = "" | |
for user, assistant in chat_history: | |
current_input += user | |
current_input += assistant | |
history = current_input | |
current_input += message | |
current_input += "\n" | |
device = "cuda:0" | |
input_ids = tokenizer(current_input, return_tensors="pt").input_ids.to(device) | |
if len(input_ids) > MAX_INPUT_TOKEN_LENGTH: | |
input_ids = input_ids[-MAX_INPUT_TOKEN_LENGTH:] | |
gr.Warning("Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.") | |
streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True) | |
generate_kwargs = dict( | |
{"input_ids": input_ids}, | |
streamer=streamer, | |
max_new_tokens=max_new_tokens, | |
#do_sample=True, | |
#top_p=top_p, | |
#top_k=top_k, | |
#temperature=temperature, | |
#num_beams=1, | |
#repetition_penalty=repetition_penalty, | |
) | |
t = Thread(target=model.generate, kwargs=generate_kwargs) | |
t.start() | |
outputs = [] | |
for text in streamer: | |
outputs.append(text) | |
combined_text = "".join(outputs) | |
if "<<<<<<<" in combined_text: | |
combined_text = combined_text.replace("<<<<<<<", "") # Remove the unwanted string | |
yield combined_text | |
break | |
else: | |
yield combined_text | |
chat_interface = gr.ChatInterface( | |
fn=generate, | |
additional_inputs=[ | |
gr.Slider( | |
label="Max new tokens", | |
minimum=1, | |
maximum=MAX_MAX_NEW_TOKENS, | |
step=1, | |
value=DEFAULT_MAX_NEW_TOKENS, | |
), | |
# gr.Slider( | |
# label="Temperature", | |
# minimum=0.1, | |
# maximum=4.0, | |
# step=0.1, | |
# value=0.6, | |
# ), | |
# gr.Slider( | |
# label="Top-p (nucleus sampling)", | |
# minimum=0.05, | |
# maximum=1.0, | |
# step=0.05, | |
# value=0.9, | |
# ), | |
# gr.Slider( | |
# label="Top-k", | |
# minimum=1, | |
# maximum=1000, | |
# step=1, | |
# value=50, | |
# ), | |
# gr.Slider( | |
# label="Repetition penalty", | |
# minimum=0.1, | |
# maximum=2.0, | |
# step=0.05, | |
# value=1.2, | |
# ), | |
], | |
stop_btn=None, | |
examples=[ | |
["<<<<<<<\nlet x = max(y, 11)\n=======\nvar x = max(y, 12, z)\n>>>>>>>"], | |
["<<<<<<<\nclass Calculator { \nadd(a, b) {\n return a + b;\n }\n}\n=======\nclass Calculator {\n subtract(a, b) {\n return a - b;\n }\n}\n>>>>>>>"], | |
["<<<<<<<\nfunction greet(name) {\n return `Hello, ${name}! Have a good day.`;\n}\n=======\nfunction greet(name, time) {\n return `Good ${time}, ${name}!`;\n}\n>>>>>>>"], | |
["<<<<<<<\nconst user = {\n name: 'John',\n age: 30\n}\n=======\nconst user = {\n name: 'John',\n email: '[email protected]'\n}\n>>>>>>>"], | |
["<<<<<<<\n.btn {\n background-color: blue;\n padding: 10px 20px;\n}\n=======\n.btn {\n border: 1px solid black;\n font-size: 16px;\n}\n>>>>>>>"], | |
["<<<<<<<\n var visibleSets = beatmapSets.Where(s => !s.Filtered).ToList();\n if (!visibleSets.Any())\n return;\n\n=======\n\n var visible = beatmapSets.Where(s => !s.Filtered).ToList();\n if (!visible.Any())\n return false;\n\n>>>>>>>"], | |
], | |
) | |
with gr.Blocks(css="style.css") as demo: | |
gr.Markdown(DESCRIPTION) | |
gr.DuplicateButton( | |
value="Duplicate Space for private use", | |
elem_id="duplicate-button", | |
visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1", | |
) | |
chat_interface.render() | |
if __name__ == "__main__": | |
demo.queue(max_size=20).launch() | |