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"""
This is a Hugging Face Spaces demo for Fin-RWKV-1B5 attention free financial expert modal.
Author: Umut (Hope) YILDIRIM <[email protected]>
"""
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
from threading import Thread
import torch
# from openbb import obb
# Login to OpenBB
# obb.account.login()
tokenizer = AutoTokenizer.from_pretrained("umuthopeyildirim/fin-rwkv-1b5")
model = AutoModelForCausalLM.from_pretrained("umuthopeyildirim/fin-rwkv-1b5")
products = [
{"name": "Red Bull", "description": "Energy Drink", "symbol": "ALI",
"image": "https://i.pinimg.com/originals/f9/68/e3/f968e3a1d474e1c19a91b508231a88c8.png"},
{"name": "iPhone 15", "description": "Latest Apple Smartphone", "symbol": "PL",
"image": "https://www.apple.com/newsroom/images/2023/09/apple-unveils-iphone-15-pro-and-iphone-15-pro-max/tile/Apple-iPhone-15-Pro-lineup-hero-230912.jpg.news_app_ed.jpg"},
{"name": "Pencil", "description": "Wooden Writing Tool", "symbol": "CL",
"image": "https://m.media-amazon.com/images/I/41IQfWzTojL._AC_UF1000,1000_QL80_.jpg"},
{"name": "LG Monitor", "description": "High-Resolution Computer Monitor", "symbol": "NG",
"image": "https://media.us.lg.com/transform/ecomm-PDPGallery-1100x730/a330bb92-bc33-435a-aa1b-07795eedbc10/md08003490-DZ-03"},
]
examples_openbb = [
"x,Aluminum Futures\n 2024-01-02T00:00:00,2278.75\n 2024-01-03T00:00:00,2251\n 2024-01-04T00:00:00,2218.25\n 2024-01-05T00:00:00,2203\n 2024-01-08T00:00:00,2168.5\n 2024-01-09T00:00:00,2182.5\n 2024-01-10T00:00:00,2178.5\n 2024-01-11T00:00:00,2179.75\n 2024-01-12T00:00:00,2167.5\n 2024-01-16T00:00:00,2161.75\n 2024-01-17T00:00:00,2148.75\n 2024-01-18T00:00:00,2136.5\n 2024-01-19T00:00:00,2127.5\n 2024-01-22T00:00:00,2127.5\n 2024-01-23T00:00:00,2184.25\n 2024-01-24T00:00:00,2186.25\n 2024-01-25T00:00:00,2194.5\n 2024-01-26T00:00:00,2246.25\n Here is the historical data for Aluminum Futures. Did it appreciated over time or depreciated?\n",
"x,Platinum Futures\n 2024-01-02T00:00:00,985.5\n 2024-01-03T00:00:00,974.4000244140624\n 2024-01-04T00:00:00,953.9000244140624\n 2024-01-05T00:00:00,959.2999877929688\n 2024-01-08T00:00:00,946.7000122070312\n 2024-01-09T00:00:00,931\n 2024-01-10T00:00:00,918.7999877929688\n 2024-01-11T00:00:00,909\n 2024-01-12T00:00:00,910.0999755859376\n 2024-01-16T00:00:00,895.0999755859375\n 2024-01-17T00:00:00,882.7999877929688\n 2024-01-18T00:00:00,903.2999877929688\n 2024-01-19T00:00:00,897.2999877929688\n 2024-01-22T00:00:00,894.4000244140625\n 2024-01-23T00:00:00,896.2000122070312\n 2024-01-24T00:00:00,905.5999755859376\n 2024-01-25T00:00:00,887.4000244140625\n 2024-01-26T00:00:00,921.7000122070312\n Here is the historical data for Platinum Futures. Did it appreciated over time or depreciated?\n",
"x,Natural Gas Futures\n 2024-01-02T00:00:00,2.568000078201294\n 2024-01-03T00:00:00,2.6679999828338623\n 2024-01-04T00:00:00,2.821000099182129\n 2024-01-05T00:00:00,2.8929998874664307\n 2024-01-08T00:00:00,2.9800000190734863\n 2024-01-09T00:00:00,3.190000057220459\n 2024-01-10T00:00:00,3.0390000343322754\n 2024-01-11T00:00:00,3.0969998836517334\n 2024-01-12T00:00:00,3.312999963760376\n 2024-01-15T00:00:00,3.1059999465942383\n 2024-01-16T00:00:00,2.9000000953674316\n 2024-01-17T00:00:00,2.869999885559082\n 2024-01-18T00:00:00,2.697000026702881\n 2024-01-19T00:00:00,2.5190000534057617\n 2024-01-22T00:00:00,2.4189999103546143\n 2024-01-23T00:00:00,2.450000047683716\n 2024-01-24T00:00:00,2.6410000324249268\n 2024-01-25T00:00:00,2.571000099182129\n 2024-01-26T00:00:00,2.7190001010894775 Here is the historical data for Natural Gas Futures. Did it appreciated over time or depreciated?\n",
"x,WTI Crude Oil Futures\n 2024-01-02T00:00:00,70.37999725341797\n 2024-01-03T00:00:00,72.69999694824219\n 2024-01-04T00:00:00,72.19000244140625\n 2024-01-05T00:00:00,73.80999755859375\n 2024-01-08T00:00:00,70.7699966430664\n 2024-01-09T00:00:00,72.23999786376953\n 2024-01-10T00:00:00,71.37000274658203\n 2024-01-11T00:00:00,72.0199966430664\n 2024-01-12T00:00:00,72.68000030517578\n 2024-01-15T00:00:00,72.5\n 2024-01-16T00:00:00,72.4000015258789\n 2024-01-17T00:00:00,72.55999755859375\n 2024-01-18T00:00:00,74.08000183105469\n 2024-01-19T00:00:00,73.41000366210938\n 2024-01-22T00:00:00,75.19000244140625\n 2024-01-23T00:00:00,74.37000274658203\n 2024-01-24T00:00:00,75.08999633789062\n 2024-01-25T00:00:00,77.36000061035156\n 2024-01-26T00:00:00,78.2300033569336 Here is the historical data for WTI Crude Oil Futures. Did it appreciated over time or depreciated?\n",
]
openbb_inputbox = ""
openbb_chatbox = ""
class StopOnTokens(StoppingCriteria):
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool:
stop_ids = [29, 0]
for stop_id in stop_ids:
if input_ids[0][-1] == stop_id:
return True
return False
def predict(message, history):
history_transformer_format = history + [[message, ""]]
stop = StopOnTokens()
messages = "".join(["".join(["\nuser :"+item[0], "\nbot:"+item[1]]) # curr_system_message +
for item in history_transformer_format])
print(messages)
model_inputs = tokenizer([messages], return_tensors="pt")
streamer = TextIteratorStreamer(
tokenizer, timeout=10., skip_prompt=True, skip_special_tokens=True)
generate_kwargs = dict(
model_inputs,
streamer=streamer,
max_new_tokens=1024,
do_sample=True,
top_p=0.95,
top_k=1000,
temperature=0.5,
num_beams=1,
stopping_criteria=StoppingCriteriaList([stop])
)
t = Thread(target=model.generate, kwargs=generate_kwargs)
t.start()
partial_message = ""
for new_token in streamer:
if new_token != '<':
partial_message += new_token
yield partial_message
def predict2(message, history):
history_transformer_format = history + [[message, ""]]
stop = StopOnTokens()
messages = "".join(["".join(["\nuser :"+item[0], "\nbot:"+item[1]]) # curr_system_message +
for item in history_transformer_format])
print(messages)
model_inputs = tokenizer([messages], return_tensors="pt")
streamer = TextIteratorStreamer(
tokenizer, timeout=10., skip_prompt=True, skip_special_tokens=True)
generate_kwargs = dict(
model_inputs,
streamer=streamer,
max_new_tokens=1024,
do_sample=True,
top_p=0.95,
top_k=1000,
temperature=0.5,
num_beams=1,
stopping_criteria=StoppingCriteriaList([stop])
)
t = Thread(target=model.generate, kwargs=generate_kwargs)
t.start()
partial_message = ""
for new_token in streamer:
if new_token != '<':
partial_message += new_token
yield partial_message
def generate_text(prompt, tokenizer, model):
# Tokenize the input
input_ids = tokenizer.encode(prompt, return_tensors="pt")
# Generate a response
output = model.generate(input_ids, max_length=333, num_return_sequences=1)
# Decode the output
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
return generated_text
# def fetch_historical_data(symbol):
# # Replace with actual OpenBB method to fetch historical data
# data = obb.derivatives.futures.historical(
# symbol,
# start_date="2024-01-01",
# interval="1wk",
# ).to_df()["close"].rename(symbol)
# return data
title = "# Fin-RWKV: Attention Free Financial Expert (WIP)"
description = """Demo for **Fin-RWKV: Attention Free Financial Expert (WIP)**.
To download the model, please visit [Fin-RWKV: Attention Free Financial Expert (WIP)](https://huggingface.co/umuthopeyildirim/fin-rwkv-1b5). [Google Presentation](https://docs.google.com/presentation/d/1vNQ8Y5wwR0WXlO60fsXjkru5R9I0ZgykTmgag0B3Ato/edit?usp=sharing)"""
css = """
#img-display-container {
max-height: 100vh;
}
#img-display-input {
max-height: 80vh;
}
#img-display-output {
max-height: 80vh;
}
"""
with gr.Blocks(css=css) as demo:
gr.Markdown(title)
gr.Markdown(description)
with gr.Tab("Chatbot"):
gr.ChatInterface(predict)
# with gr.Tab("E-Commerce"):
# e_commerce_interface()
with gr.Tab("OpenBB"):
gr.ChatInterface(predict2, examples=[
examples_openbb[0], examples_openbb[1], examples_openbb[2], examples_openbb[3]])
if __name__ == '__main__':
demo.queue().launch(share=False)
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