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2024.01.27_chat.guanjihuan.com/使用 Transformer 软件包调用开源模型 InternLM/InternLM.py

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+"""
+This code is supported by the website: https://www.guanjihuan.com
+The newest version of this code is on the web page: https://www.guanjihuan.com/archives/38502
+"""
+
+import streamlit as st
+st.set_page_config(
+    page_title="Chat",
+    layout='wide'
+)
+
+@st.cache_resource
+def load_model_internlm_7B():
+    # internlm（需要 7G 显存）
+    import torch
+    from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+    nf4_config = BitsAndBytesConfig(
+        load_in_4bit=True,
+        bnb_4bit_quant_type="nf4",
+    )
+    model = AutoModelForCausalLM.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True, quantization_config=nf4_config)
+    tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-chat-7b", trust_remote_code=True, torch_dtype=torch.bfloat16)
+    model = model.eval()
+    return model, tokenizer
+model_internlm_7B, tokenizer_internlm_7B = load_model_internlm_7B()
+
+with st.sidebar:
+    with st.expander('参数', expanded=True):
+        max_length = 409600
+        top_p = st.slider('top_p', 0.01, 1.0, step=0.01, value=0.8, key='top_p_session')
+        temperature = st.slider('temperature', 0.51, 1.0, step=0.01, value=0.8, key='temperature_session') 
+        def reset_parameter():
+            st.session_state['top_p_session'] = 0.8
+            st.session_state['temperature_session'] = 0.8
+        reset_parameter_button = st.button('重置', on_click=reset_parameter)
+
+prompt = st.chat_input("在这里输入您的命令")
+
+from tools.transformers.interface import GenerationConfig, generate_interactive
+
+def prepare_generation_config():
+    generation_config = GenerationConfig(max_length=max_length, top_p=top_p, temperature=temperature)
+    return generation_config
+
+def combine_history(prompt, messages):
+    total_prompt = ""
+    for message in messages:
+        cur_content = message["content"]
+        if message["role"] == "user":
+            cur_prompt = user_prompt.replace("{user}", cur_content)
+        elif message["role"] == "robot":
+            cur_prompt = robot_prompt.replace("{robot}", cur_content)
+        else:
+            raise RuntimeError
+        total_prompt += cur_prompt
+    total_prompt = total_prompt + cur_query_prompt.replace("{user}", prompt)
+    return total_prompt
+
+user_prompt = "<|User|>:{user}<eoh>\n"
+robot_prompt = "<|Bot|>:{robot}<eoa>\n"
+cur_query_prompt = "<|User|>:{user}<eoh>\n<|Bot|>:"
+generation_config = prepare_generation_config()
+
+if "messages_internlm_7B" not in st.session_state:
+    st.session_state.messages_internlm_7B = []
+
+from dataclasses import asdict
+
+def chat_response_internlm_7B(prompt):
+    real_prompt = combine_history(prompt, messages = st.session_state.messages_internlm_7B)
+    st.session_state.messages_internlm_7B.append({"role": "user", "content": prompt, "avatar": 'user'})
+    for cur_response in generate_interactive(
+        model=model_internlm_7B,
+        tokenizer=tokenizer_internlm_7B,
+        prompt=real_prompt,
+        additional_eos_token_id=103028,
+        **asdict(generation_config),
+    ):
+        message_placeholder_internlm_7B.markdown(cur_response + "▌")
+        if stop_button:
+            break
+    message_placeholder_internlm_7B.markdown(cur_response)
+    st.session_state.messages_internlm_7B.append({"role": "robot", "content": cur_response, "avatar": "assistant"})
+    st.session_state.ai_response.append({"role": "robot", "content": cur_response, "avatar": "assistant"})
+    return cur_response
+
+
+def clear_all():
+    st.session_state.messages_internlm_7B = []
+    st.session_state.ai_response = []
+
+if 'messages_internlm_7B' not in st.session_state:
+    st.session_state.messages_internlm_7B = []
+if 'ai_response' not in st.session_state:
+    st.session_state.ai_response = []
+
+for ai_response in st.session_state.ai_response:
+    with st.chat_message(ai_response["role"], avatar=ai_response.get("avatar")):
+        st.markdown(ai_response["content"])
+
+prompt_placeholder = st.chat_message("user", avatar='user')
+with st.chat_message("robot", avatar="assistant"):
+    message_placeholder_internlm_7B = st.empty()
+
+if prompt:
+    prompt_placeholder.markdown(prompt)
+    st.session_state.ai_response.append({"role": "user", "content": prompt, "avatar": 'user'})
+    stop = st.empty()
+    stop_button = stop.button('停止', key='break_response')
+    chat_response_internlm_7B(prompt)
+    stop.empty()
+button_clear = st.button("清空", on_click=clear_all, key='clear')