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app.py

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+import streamlit as st
+import torch
+import time
+from threading import Thread
+from transformers import (
+ AutoTokenizer,
+ AutoModelForCausalLM,
+ TextIteratorStreamer
+)
+
+
+# App title
+st.set_page_config(page_title="😶‍🌫️ FuseChat Model")
+
+root_path = "FuseAI"
+
+@st.cache_resource
+def load_model(model_name):
+ tokenizer = AutoTokenizer.from_pretrained(
+ f"{root_path}/{model_name}",
+ trust_remote_code=True,
+ )
+
+ if tokenizer.pad_token_id is None:
+ if tokenizer.eos_token_id is not None:
+ tokenizer.pad_token_id = tokenizer.eos_token_id
+ else:
+ tokenizer.pad_token_id = 0
+
+ model = AutoModelForCausalLM.from_pretrained(
+ f"{root_path}/{model_name}",
+ device_map="auto",
+ torch_dtype=torch.bfloat16,
+ load_in_4bit=True,
+ trust_remote_code=True,
+ )
+
+ model.eval()
+ return model, tokenizer
+
+
+with st.sidebar:
+ st.title('😶‍🌫️ FuseChat')
+ st.write('This chatbot is created using FuseChat, a model developed by FuseAI')
+ st.subheader('Models and parameters')
+ selected_model = st.sidebar.selectbox('Choose a FuseChat model', ['FuseChat-7B-VaRM', 'FuseChat-7B-Slerp', 'FuseChat-7B-TA'], key='selected_model')
+ temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.1, step=0.01)
+ top_p = st.sidebar.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01)
+ top_k = st.sidebar.slider('top_k', min_value=1, max_value=1000, value=50, step=1)
+ repetition_penalty = st.sidebar.slider('repetition penalty', min_value=1., max_value=2., value=1.2, step=0.05)
+ max_length = st.sidebar.slider('max new tokens', min_value=32, max_value=2000, value=240, step=8)
+
+with st.spinner('loading model..'):
+ model, tokenizer = load_model(selected_model)
+
+# Store LLM generated responses
+if "messages" not in st.session_state.keys():
+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+
+# Display or clear chat messages
+for message in st.session_state.messages:
+ with st.chat_message(message["role"]):
+ st.write(message["content"])
+
+def clear_chat_history():
+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
+
+
+def generate_fusechat_response():
+ string_dialogue = "You are a helpful and harmless assistant."
+ for dict_message in st.session_state.messages:
+ if dict_message["role"] == "user":
+ string_dialogue += "GPT4 Correct User: " + dict_message["content"] + "<|end_of_turn|>"
+ else:
+ string_dialogue += "GPT4 Correct Assistant: " + dict_message["content"] + "<|end_of_turn|>"
+
+ input_ids = tokenizer(f"{string_dialogue}GPT4 Correct Assistant: ", return_tensors="pt").input_ids
+ 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_length,
+ 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)
+ return "".join(outputs)
+
+# User-provided prompt
+if prompt := st.chat_input("Hello there! How are you doing?"):
+ st.session_state.messages.append({"role": "user", "content": prompt})
+ with st.chat_message("user"):
+ st.write(prompt)
+
+# Generate a new response if last message is not from assistant
+if st.session_state.messages[-1]["role"] != "assistant":
+ with st.chat_message("assistant"):
+ with st.spinner("Thinking..."):
+ response = generate_fusechat_response()
+ placeholder = st.empty()
+ full_response = ''
+ for item in response:
+ full_response += item
+ time.sleep(0.05)
+ placeholder.markdown(full_response + "▌")
+ placeholder.markdown(full_response)
+ message = {"role": "assistant", "content": full_response}
+ st.session_state.messages.append(message)

requirements.txt

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+streamlit==1.29.0
+bitsandbytes==0.42.0
+accelerate==0.25.0
+transformers==4.34.0
+torch==2.1.2
+protobuf==4.25.1
+scipy==1.11.4
+sentencepiece==0.1.99