multipurpose_chatbot/configs.py

import os

# ! UI Markdown information

MODEL_TITLE = """
<img src="file/seal_logo.png" style="
    max-width: 10em;
    max-height: 5%;
    height: 3em;
    width: 3em;
">
<div class="text" style="
loat: left;
padding-bottom: 2%;
">
SeaLLMs - Large Language Models for Southeast Asia
</div>
"""

# <a href='https://huggingface.co/spaces/SeaLLMs/SeaLMMM-7b'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> 
# <a href='https://huggingface.co/SeaLLMs/SeaLLM-7B-v2'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> 
# 
MODEL_DESC = f"""
<div style='display:flex; gap: 0.25rem; '>
<a href='https://github.com/damo-nlp-sg/seallms'><img src='https://img.shields.io/badge/Github-Code-success'></a>
<a href='https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> 
<a href='https://huggingface.co/SeaLLMs/SeaLMMM-7B-early'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> 
</div>
<span style="font-size: larger">
<a href="https://huggingface.co/SeaLLMs/SeaLMMM-7B-early" target="_blank">SeaLMMM-7B-early</a> - multilingual multimodal assistant for Southeast Asia. It handles <b>both</b> text-only (<a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2" target="_blank">LLMs</a> and vision instructions (LVMs). <span style="color: red">SeaLMMM-7B has not finished training.</span>
</span>
<br>
<span>
<span style="color: red">The chatbot may produce false and harmful content!</span>
By using our service, you are required to agree to our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE" target="_blank" style="color: red">Terms Of Use</a>
</span>

""".strip()

MODEL_DESC = f"""
<div style='display:flex; gap: 0.25rem; '>
<a href='https://github.com/damo-nlp-sg/seallms'><img src='https://img.shields.io/badge/Github-Code-success'></a>
<a href='https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B-v2.5'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> 
<a href='https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> 
<a href='https://arxiv.org/pdf/2312.00738.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a>
</div>
<span style="font-size: larger">
<a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5" target="_blank">SeaLLM-7B-v2.5</a> - a helpful assistant for Southeast Asian Languages 🇬🇧 🇻🇳 🇮🇩 🇹🇭 🇲🇾 🇰🇭 🇱🇦 🇵🇭 🇲🇲.
Explore <a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B" target="_blank">SeaLMMM-7B</a> - our multi-modal version of SeaLLMs.
</span>
<br>
<span>
<span style="color: red">The chatbot may produce false and harmful content!</span>
By using our service, you are required to agree to our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE" target="_blank" style="color: red">Terms Of Use</a>
</span>
""".strip()
# <span>
# <span style="color: red">NOTE: The chatbot may produce false and harmful content and does not have up-to-date knowledge.</span> 
# By using our service, you are required to agree to our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE" target="_blank" style="color: red">Terms Of Use</a>, which includes 
# not to use our service to generate any harmful, inappropriate or illegal content. 
# The service collects user dialogue data for testing and improvement under 
# <a href="https://creativecommons.org/licenses/by/4.0/">(CC-BY)</a> or similar license. So do not enter any personal information!
# </span>

"""
By using our service, you are required to agree to our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE" target="_blank" style="color: red">Terms Of Use</a>, which includes 
not to use our service to generate any harmful, inappropriate or illegal content. 
The service collects user dialogue data for testing and improvement under 
<a href="https://creativecommons.org/licenses/by/4.0/">(CC-BY)</a> or similar license. So do not enter any personal information!

"""
MODEL_DESC = ""


# MODEL_INFO = """
# <h4 style="display: hidden;">Model Name: {model_path}</h4>
# """
MODEL_INFO = ""

CITE_MARKDOWN = """
## Citation
If you find our project useful, hope you can star our repo and cite our paper as follows:
```
@article{damonlpsg2023seallm,
  author = {Xuan-Phi Nguyen*, Wenxuan Zhang*, Xin Li*, Mahani Aljunied*, Zhiqiang Hu, Chenhui Shen^, Yew Ken Chia^, Xingxuan Li, Jianyu Wang, Qingyu Tan, Liying Cheng, Guanzheng Chen, Yue Deng, Sen Yang, Chaoqun Liu, Hang Zhang, Lidong Bing},
  title = {SeaLLMs - Large Language Models for Southeast Asia},
  year = 2023,
}
```

"""
CITE_MARKDOWN = ""
USE_PANEL = bool(int(os.environ.get("USE_PANEL", "1")))
CHATBOT_HEIGHT = int(os.environ.get("CHATBOT_HEIGHT", "500"))

ALLOWED_PATHS = ["seal_logo.png"]


DEMOS = os.environ.get("DEMOS", "")

DEMOS = DEMOS.split(",") if DEMOS.strip() != "" else [
    "DocChatInterfaceDemo",
    "ChatInterfaceDemo",
    "TextCompletionDemo",
    # "RagChatInterfaceDemo",
    # "VisionChatInterfaceDemo",
    # "VisionDocChatInterfaceDemo",
]

# DEMOS=DocChatInterfaceDemo,ChatInterfaceDemo,RagChatInterfaceDemo,TextCompletionDemo



# ! server info

DELETE_FOLDER = os.environ.get("DELETE_FOLDER", "")
PORT = int(os.environ.get("PORT", "7860"))
PROXY = os.environ.get("PROXY", "").strip()

# ! backend info

BACKEND = os.environ.get("BACKEND", "debug")

# ! model information
# for RAG
RAG_EMBED_MODEL_NAME = os.environ.get("RAG_EMBED_MODEL_NAME", "sentence-transformers/all-MiniLM-L6-v2")
CHUNK_SIZE = int(os.environ.get("CHUNK_SIZE", "1024"))
CHUNK_OVERLAP = int(os.environ.get("CHUNK_SIZE", "50"))


SYSTEM_PROMPT = os.environ.get("SYSTEM_PROMPT", """You are a helpful, respectful, honest and safe AI assistant.""")

MAX_TOKENS = int(os.environ.get("MAX_TOKENS", "2048"))
TEMPERATURE = float(os.environ.get("TEMPERATURE", "0.1"))
# ! these values currently not used
FREQUENCE_PENALTY = float(os.environ.get("FREQUENCE_PENALTY", "0.0"))
PRESENCE_PENALTY = float(os.environ.get("PRESENCE_PENALTY", "0.0"))


# Transformers or vllm
MODEL_PATH = os.environ.get("MODEL_PATH", "mistralai/Mistral-7B-Instruct-v0.2")
MODEL_NAME = os.environ.get("MODEL_NAME", "Cool-Chatbot")
DTYPE = os.environ.get("DTYPE", "bfloat16")
DEVICE = os.environ.get("DEVICE", "cuda")

# VLLM
GPU_MEMORY_UTILIZATION = float(os.environ.get("GPU_MEMORY_UTILIZATION", "0.9"))
TENSOR_PARALLEL = int(os.environ.get("TENSOR_PARALLEL", "1"))
QUANTIZATION = str(os.environ.get("QUANTIZATION", ""))
STREAM_YIELD_MULTIPLE = int(os.environ.get("STREAM_YIELD_MULTIPLE", "1"))
# how many iterations to perform safety check on response
STREAM_CHECK_MULTIPLE = int(os.environ.get("STREAM_CHECK_MULTIPLE", "0"))

# llama.cpp
DEFAULT_CHAT_TEMPLATE = os.environ.get("DEFAULT_CHAT_TEMPLATE", "chatml")
N_CTX = int(os.environ.get("N_CTX", "4096"))
N_GPU_LAYERS = int(os.environ.get("N_GPU_LAYERS", "-1"))

# llava.llama.cpp


# Multimodal
IMAGE_TOKEN = os.environ.get("IMAGE_TOKEN", "[IMAGE]<|image|>[/IMAGE]")
IMAGE_TOKEN_INTERACTIVE = bool(int(os.environ.get("IMAGE_TOKEN_INTERACTIVE", "0")))
IMAGE_TOKEN_LENGTH = int(os.environ.get("IMAGE_TOKEN_LENGTH", "576"))
MAX_PACHES = int(os.environ.get("MAX_PACHES", "1"))