dw112/PocketLLM

1import random2import re3import json4import os5import base646from threading import Thread7from datetime import datetime8 9import torch10import numpy as np11import streamlit as st12from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer13 14st.set_page_config(page_title="PocketLLM", initial_sidebar_state="expanded", layout="wide")15 16# ================= 本地图片转 Base64 =================17def get_image_base64(filename):18    img_dir = "/app/images"19    path = os.path.join(img_dir, filename)20    if os.path.exists(path):21        with open(path, "rb") as f:22            return f"data:image/png;base64,{base64.b64encode(f.read()).decode()}"23    # 占位透明图24    return "data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"25 26logo_b64 = get_image_base64("logo.png")27banner_b64 = get_image_base64("顶部横幅.png")28avatar_b64 = get_image_base64("助手头像.png")29# =================================================30 31st.markdown("""32    <style>33        /* 全局字体 (Gemini 风格) */34        @import url('https://fonts.googleapis.com/css2?family=Google+Sans:wght@400;500;700&display=swap');35        html, body, [class*="css"] {36            font-family: 'Google Sans', 'Noto Sans SC', sans-serif !important;37            color: #1f1f1f;38        }39        .stMainBlockContainer {40            padding-top: 1rem !important;41            padding-bottom: 5rem !important;42        }43        /* 历史对话按钮模拟 */44        .history-btn {45            background: transparent;46            border: none;47            color: #444;48            padding: 10px 15px;49            width: 100%;50            text-align: left;51            border-radius: 8px;52            cursor: pointer;53            font-size: 14px;54            margin-bottom: 5px;55            transition: background 0.2s;56        }57        .history-btn:hover {58            background: #f0f4f9;59        }60        /* 滚动条 */61        ::-webkit-scrollbar { width: 6px; height: 6px; }62        ::-webkit-scrollbar-thumb { background: #d1d5db; border-radius: 3px; }63        ::-webkit-scrollbar-track { background: transparent; }64    </style>65""", unsafe_allow_html=True)66 67device = "cuda" if torch.cuda.is_available() else "cpu"68 69# ================= 多语言文本 =================70LANG_TEXTS = {71    'zh': {72        'settings': '模型设定调整',73        'history_rounds': '历史对话轮次',74        'max_length': '最大生成长度',75        'temperature': '温度',76        'thinking': '✨ 开启深度思考',77        'tools': '工具选择 (最多4个)',78        'language': '语言',79        'send': '给 PocketLLM 发送消息...',80        'disclaimer': 'AI 生成内容可能存在错误，请仔细核实',81        'think_tip': '自适应思考，多轮对话或Tool Call时可能不稳定',82    },83    'en': {84        'settings': 'Model Settings',85        'history_rounds': 'History Rounds',86        'max_length': 'Max Length',87        'temperature': 'Temperature',88        'thinking': '✨ Enable Deep Thinking',89        'tools': 'Tool Selection (max 4)',90        'language': 'Language',91        'send': 'Message PocketLLM...',92        'disclaimer': 'AI-generated content may be inaccurate, please verify',93        'think_tip': 'Adaptive thinking; may be unstable with multi-turn or Tool Call',94    }95}96 97def get_text(key):98    lang = st.session_state.get('lang', 'zh')99    return LANG_TEXTS.get(lang, {}).get(key, LANG_TEXTS['zh'].get(key, key))100 101# ================= 工具定义 & 执行 (完全保持原版) =================102TOOLS = [103    {"type": "function", "function": {"name": "calculate_math", "description": "计算数学表达式", "parameters": {"type": "object", "properties": {"expression": {"type": "string", "description": "数学表达式"}}, "required": ["expression"]}}},104    {"type": "function", "function": {"name": "get_current_time", "description": "获取当前时间", "parameters": {"type": "object", "properties": {"timezone": {"type": "string", "default": "Asia/Shanghai"}}, "required": []}}},105    {"type": "function", "function": {"name": "random_number", "description": "生成随机数", "parameters": {"type": "object", "properties": {"min": {"type": "integer"}, "max": {"type": "integer"}}, "required": ["min", "max"]}}},106    {"type": "function", "function": {"name": "text_length", "description": "计算文本长度", "parameters": {"type": "object", "properties": {"text": {"type": "string"}}, "required": ["text"]}}},107    {"type": "function", "function": {"name": "unit_converter", "description": "单位转换", "parameters": {"type": "object", "properties": {"value": {"type": "number"}, "from_unit": {"type": "string"}, "to_unit": {"type": "string"}}, "required": ["value", "from_unit", "to_unit"]}}},108    {"type": "function", "function": {"name": "get_current_weather", "description": "获取天气", "parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}}},109    {"type": "function", "function": {"name": "get_exchange_rate", "description": "获取汇率", "parameters": {"type": "object", "properties": {"from_currency": {"type": "string"}, "to_currency": {"type": "string"}}, "required": ["from_currency", "to_currency"]}}},110    {"type": "function", "function": {"name": "translate_text", "description": "翻译文本", "parameters": {"type": "object", "properties": {"text": {"type": "string"}, "target_lang": {"type": "string"}}, "required": ["text", "target_lang"]}}},111]112 113TOOL_SHORT_NAMES = {114    'calculate_math': '数学', 'get_current_time': '时间', 'random_number': '随机',115    'text_length': '字数', 'unit_converter': '单位', 'get_current_weather': '天气',116    'get_exchange_rate': '汇率', 'translate_text': '翻译'117}118 119def execute_tool(tool_name, args):120    import datetime121    try:122        if tool_name == 'calculate_math':123            return {"result": eval(args.get('expression', '0'))}124        elif tool_name == 'get_current_time':125            return {"result": datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}126        elif tool_name == 'random_number':127            return {"result": random.randint(args.get('min', 0), args.get('max', 100))}128        elif tool_name == 'text_length':129            return {"result": len(args.get('text', ''))}130        elif tool_name == 'unit_converter':131            return {"result": f"{args.get('value', 0)} {args.get('from_unit', '')} = ? {args.get('to_unit', '')}"}132        elif tool_name == 'get_current_weather':133            return {"result": f"{args.get('city', 'Unknown')}: 晴, 7~10°C"}134        elif tool_name == 'get_exchange_rate':135            return {"result": f"1 {args.get('from_currency', 'USD')} = 7.2 {args.get('to_currency', 'CNY')}"}136        elif tool_name == 'translate_text':137            return {"result": f"[翻译结果]: hello world"}138        return {"result": "Unknown tool"}139    except Exception as e:140        return {"error": str(e)}141 142# ================= 原版 process_assistant_content (完全保持副本逻辑) =================143def process_assistant_content(content, is_streaming=False):144    # 处理tool_call标签，格式化显示145    if '<tool_call>' in content:146        def format_tool_call(match):147            try:148                tc = json.loads(match.group(1))149                name = tc.get('name', 'unknown')150                args = tc.get('arguments', {})151                return f'<div style="background: rgba(80, 110, 150, 0.20); border: 1px solid rgba(140, 170, 210, 0.30); padding: 10px 12px; border-radius: 12px; margin: 6px 0;"><div style="font-size:12px;opacity:.75;display:block;margin:0 0 6px 0;line-height:1;">ToolCalling</div><div><b>{name}</b>: {json.dumps(args, ensure_ascii=False)}</div></div>'152            except:153                return match.group(0)154        content = re.sub(r'<tool_call>(.*?)</tool_call>', format_tool_call, content, flags=re.DOTALL)155    156    # 流式生成且开启思考时，一开始就放到折叠里157    if is_streaming and st.session_state.get('enable_thinking', False) and '</think>' not in content and '<think>' not in content:158        m = re.search(r'(\n\n(?:我是|您好|你好)[^\n]*)', content)159        if m and m.start(1) > 5:160            i = m.start(1)161            think_part = content[:i]162            answer_part = content[i:]163            return f'<details open style="border-left: 2px solid #666; padding-left: 12px; margin: 8px 0;"><summary style="cursor: pointer; color: #888;">已思考</summary><div style="color: #aaa; font-size: 0.95em; margin-top: 8px; max-height: 100px; overflow-y: auto;">{think_part.strip()}</div></details>{answer_part}'164        elif len(content) > 5:165            return f'<details open style="border-left: 2px solid #666; padding-left: 12px; margin: 8px 0;"><summary style="cursor: pointer; color: #888;">思考中...</summary><div style="color: #aaa; font-size: 0.95em; margin-top: 8px; max-height: 100px; overflow-y: auto; display: flex; flex-direction: column-reverse;"><div style="margin-bottom: auto;">{content.strip().replace(chr(10), "<br>")}</div></div></details>'166 167    if '<think>' in content and '</think>' in content:168        def format_think(match):169            think_content = match.group(2)170            if think_content.replace('\n', '').strip():171                return f'<details open style="border-left: 2px solid #666; padding-left: 12px; margin: 8px 0;"><summary style="cursor: pointer; color: #888;">已思考</summary><div style="color: #aaa; font-size: 0.95em; margin-top: 8px; max-height: 100px; overflow-y: auto;">{think_content.strip()}</div></details>'172            return ''173        content = re.sub(r'(<think>)(.*?)(</think>)', format_think, content, flags=re.DOTALL)174 175    if '<think>' in content and '</think>' not in content:176        def format_think_in_progress(match):177            tc = match.group(1)178            return f'<details open style="border-left: 2px solid #666; padding-left: 12px; margin: 8px 0;"><summary style="cursor: pointer; color: #888;">思考中...</summary><div style="color: #aaa; font-size: 0.95em; margin-top: 8px; max-height: 100px; overflow-y: auto; display: flex; flex-direction: column-reverse;"><div style="margin-bottom: auto;">{tc.strip().replace(chr(10), "<br>")}</div></div></details>'179        content = re.sub(r'<think>(.*?)$', format_think_in_progress, content, flags=re.DOTALL)180 181    if '<think>' not in content and '</think>' in content:182        def format_think_no_start(match):183            think_content = match.group(1)184            if think_content.replace('\n', '').strip():185                return f'<details open style="border-left: 2px solid #666; padding-left: 12px; margin: 8px 0;"><summary style="cursor: pointer; color: #888;">已思考</summary><div style="color: #aaa; font-size: 0.95em; margin-top: 8px; max-height: 100px; overflow-y: auto;">{think_content.strip()}</div></details>'186            return ''187        content = re.sub(r'(.*?)</think>', format_think_no_start, content, flags=re.DOTALL)188 189    return content190 191# ================= 模型加载 =================192@st.cache_resource193def load_model_tokenizer(model_path):194    model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code=True)195    tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)196    model = model.half().eval().to(device)197    return model, tokenizer198 199def clear_chat_messages():200    # 保存当前对话到历史（非空时）201    save_current_conversation()202    st.session_state.messages = []203    st.session_state.chat_messages = []204 205def save_current_conversation():206    """保存当前对话到历史记录列表中"""207    if "messages" not in st.session_state or not st.session_state.messages:208        return209    # 避免重复保存空对话210    if len(st.session_state.messages) == 0:211        return212    # 获取最后一条消息时间作为标题213    timestamp = datetime.now().strftime("%m-%d %H:%M")214    # 取用户的第一条消息作为预览215    preview = ""216    for msg in st.session_state.messages:217        if msg["role"] == "user":218            preview = msg["content"][:30]219            break220    title = f"{timestamp} - {preview}" if preview else timestamp221    222    # 保存到历史列表（最多20条）223    if "conversation_history" not in st.session_state:224        st.session_state.conversation_history = []225    # 避免与最后一条完全相同226    if st.session_state.conversation_history and st.session_state.conversation_history[-1]["messages"] == st.session_state.messages:227        return228    st.session_state.conversation_history.append({229        "title": title,230        "messages": st.session_state.messages.copy(),231        "chat_messages": st.session_state.chat_messages.copy()232    })233    # 保留最近20条234    if len(st.session_state.conversation_history) > 20:235        st.session_state.conversation_history = st.session_state.conversation_history[-20:]236 237def load_conversation(index):238    """加载指定索引的历史对话"""239    if 0 <= index < len(st.session_state.conversation_history):240        conv = st.session_state.conversation_history[index]241        st.session_state.messages = conv["messages"].copy()242        st.session_state.chat_messages = conv["chat_messages"].copy()243        st.rerun()244 245MODEL_PATHS = {246    "PocketLLM": ["/app/pout", "PocketLLM"]247}248 249# 动态扫描模型目录250# script_dir = os.path.dirname(os.path.abspath(__file__))251# MODEL_PATHS = {}252# for d in sorted(os.listdir(script_dir), reverse=True):253#     full_path = os.path.join(script_dir, d)254#     if os.path.isdir(full_path) and not d.startswith('.') and not d.startswith('_'):255#         if any(f.endswith(('.bin', '.safetensors', '.pt')) or os.path.exists(os.path.join(full_path, 'model.safetensors.index.json')) for f in os.listdir(full_path) if os.path.isfile(os.path.join(full_path, f))):256#             MODEL_PATHS[d] = [d, d]257# if not MODEL_PATHS:258#     MODEL_PATHS = {"No models found": ["", "No models"]}259 260# ================= 侧边栏 UI (Logo 放大 + 深度思考独立开关) =================261with st.sidebar:262    # 侧边栏顶部：大 Logo + 标题263    st.markdown(f'<div style="text-align: center; margin-bottom: 20px;"><img src="{logo_b64}" style="width: 100px; border-radius: 12px;"></div>', unsafe_allow_html=True)264    st.markdown("<h2 style='text-align: center; margin-top: -10px; margin-bottom: 20px;'>PocketLLM</h2>", unsafe_allow_html=True)265    266    # 新建对话按钮267    if st.button("➕ 新建对话", use_container_width=True, type="primary"):268        clear_chat_messages()269        st.rerun()270    271    st.markdown("<div style='margin-top: 24px; font-size: 13px; color: #5f6368; font-weight: 500; margin-bottom: 8px;'>历史对话</div>", unsafe_allow_html=True)272    273    # 动态显示所有已保存的历史对话列表（不再显示独立的“之前的讨论...”按钮）274    if "conversation_history" in st.session_state and st.session_state.conversation_history:275        for idx, conv in enumerate(reversed(st.session_state.conversation_history)):276            # 倒序显示，最新的在上277            if st.button(f"📝 {conv['title']}", key=f"hist_{idx}", use_container_width=True):278                load_conversation(len(st.session_state.conversation_history) - 1 - idx)279    else:280        st.caption("暂无历史对话，新建对话后会自动保存")281    282    st.markdown("<hr style='margin: 20px 0;'>", unsafe_allow_html=True)283    284    # 深度思考开关作为独立显眼组件285    st.session_state.enable_thinking = st.toggle(get_text('thinking'), value=st.session_state.get('enable_thinking', False), help=get_text('think_tip'))286    287    st.markdown("<hr style='margin: 20px 0 12px 0;'>", unsafe_allow_html=True)288    289    # 设置收纳在 Popover290    with st.popover("⚙️ 设置", use_container_width=True):291        selected_model = st.selectbox('模型 (Model)', list(MODEL_PATHS.keys()), index=0)292        lang_options = {'中文': 'zh', 'English': 'en'}293        current_lang = st.session_state.get('lang', 'zh')294        lang_index = 0 if current_lang == 'zh' else 1295        lang_label = st.radio('语言 (Language)', list(lang_options.keys()), index=lang_index, horizontal=True)296        if lang_options[lang_label] != current_lang:297            st.session_state.lang = lang_options[lang_label]298            st.rerun()299        300        st.divider()301        st.session_state.history_chat_num = st.slider(get_text('history_rounds'), 0, 8, 0, step=2)302        st.session_state.max_new_tokens = st.slider(get_text('max_length'), 256, 8192, 8192, step=1)303        st.session_state.temperature = st.slider(get_text('temperature'), 0.6, 1.2, 0.90, step=0.01)304        305        st.divider()306        st.caption(get_text('tools'))307        st.session_state.selected_tools = []308        selected_count = sum(1 for tool in TOOLS if st.session_state.get(f"tool_{tool['function']['name']}", False))309        t_col1, t_col2 = st.columns(2)310        for i, tool in enumerate(TOOLS):311            name = tool['function']['name']312            short_name = TOOL_SHORT_NAMES.get(name, name)313            col = t_col1 if i % 2 == 0 else t_col2314            with col:315                checked = st.checkbox(short_name, key=f"tool_{name}", disabled=(selected_count >= 4 and not st.session_state.get(f"tool_{name}", False)))316                if checked and len(st.session_state.selected_tools) < 4:317                    st.session_state.selected_tools.append(name)318 319model_path = MODEL_PATHS[selected_model][0]320slogan = f"我是 {MODEL_PATHS[selected_model][1]}，有什么可以帮你的？" if st.session_state.get('lang', 'zh') == 'zh' else f"I am {MODEL_PATHS[selected_model][1]}, how can I help you?"321 322 323def render_user_msg(text):324    return f'<div style="display: flex; justify-content: flex-end; margin: 16px 0;"><div style="background-color: #f0f4f9; color: #1f1f1f; padding: 12px 20px; border-radius: 24px; font-size: 15px; max-width: 80%; line-height: 1.6;">{text}</div></div>'325 326def render_bot_msg(html_content):327    return f'<div style="display: flex; gap: 16px; margin: 20px 0;"><img src="{avatar_b64}" style="width: 34px; height: 34px; border-radius: 50%; object-fit: cover; border: 1px solid #eee;"><div style="color: #1f1f1f; font-size: 15px; padding-top: 4px; line-height: 1.7; flex: 1; overflow-x: auto;">{html_content}</div></div>'328 329def setup_seed(seed):330    random.seed(seed)331    np.random.seed(seed)332    torch.manual_seed(seed)333    torch.cuda.manual_seed(seed)334    torch.cuda.manual_seed_all(seed)335    torch.backends.cudnn.deterministic = True336    torch.backends.cudnn.benchmark = False337 338# ================= Main =================339# def main():340 341 342#     st.write("当前工作目录:", os.getcwd())343 344#     st.write("/app 内容:", os.listdir("/app"))345 346#     if os.path.exists("/app/src"):347#         st.write("/app/src 内容:", os.listdir("/app/src"))348 349#     if os.path.exists("/app/pout"):350#         st.write("/app/pout 内容:", os.listdir("/app/pout"))351 352#     model, tokenizer = load_model_tokenizer("../pout")353def main():354    # model, tokenizer = load_model_tokenizer("/app/pout")355    model, tokenizer = load_model_tokenizer(model_path)356 357    if "messages" not in st.session_state:358        st.session_state.messages = []359        st.session_state.chat_messages = []360    if "conversation_history" not in st.session_state:361        st.session_state.conversation_history = []362 363    messages = st.session_state.messages364 365    # 主界面顶部：横幅图片（修复截断问题：使用 contain 确保完整显示）366    if banner_b64 and not banner_b64.endswith("R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"):367        st.markdown(368            f'<div style="display: flex; justify-content: center; overflow: visible; padding-top: 18px;">'369            f'<img src="{banner_b64}" style="width: auto; max-width: 500px; max-height: 150px; height: auto; object-fit: contain; border-radius: 12px; margin-bottom: 20px;">'370            f'</div>',371            unsafe_allow_html=True372        )373 374    # 欢迎界面 (无历史消息时)375    if not messages:376        st.markdown(377            f'<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; text-align: center; margin-top: 2rem;">'378            f'<h1 style="font-size: 28px; color: #202124; margin-bottom: 8px;">{slogan}</h1>'379            f'<p style="color: #5f6368; font-size: 14px;">{get_text("disclaimer")}</p>'380            '</div>',381            unsafe_allow_html=True382        )383 384    # 渲染历史消息 (带左侧头像)385    for message in messages:386        if message["role"] == "assistant":387            st.markdown(render_bot_msg(process_assistant_content(message["content"])), unsafe_allow_html=True)388        else:389            st.markdown(render_user_msg(message["content"]), unsafe_allow_html=True)390 391    392    prompt = st.chat_input(key="input", placeholder=get_text('send'))393 394    if prompt:395        396        st.markdown(render_user_msg(prompt), unsafe_allow_html=True)397        messages.append({"role": "user", "content": prompt[-st.session_state.max_new_tokens:]})398        st.session_state.chat_messages.append({"role": "user", "content": prompt[-st.session_state.max_new_tokens:]})399 400        placeholder = st.empty()  # 用于流式输出401 402        random_seed = random.randint(0, 2 ** 32 - 1)403        setup_seed(random_seed)404 405 406        tools = [t for t in TOOLS if t['function']['name'] in st.session_state.get('selected_tools', [])] or None407        sys_prompt = [] if tools else [{"role": "system", "content": "你是PocketLLM，一个乐于助人、知识渊博的AI助手。请用完整且友好的方式回答用户问题。"}]408        st.session_state.chat_messages = sys_prompt + st.session_state.chat_messages[-(st.session_state.history_chat_num + 1):]409 410        template_kwargs = {"tokenize": False, "add_generation_prompt": True}411        if st.session_state.get('enable_thinking', False):412            template_kwargs["open_thinking"] = True413        if tools:414            template_kwargs["tools"] = tools415 416        new_prompt = tokenizer.apply_chat_template(st.session_state.chat_messages, **template_kwargs)417        inputs = tokenizer(new_prompt, return_tensors="pt", truncation=True).to(device)418 419        # 流式生成420        streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)421        generation_kwargs = {422            "input_ids": inputs.input_ids,423            "max_length": inputs.input_ids.shape[1] + st.session_state.max_new_tokens,424            "num_return_sequences": 1,425            "do_sample": True,426            "attention_mask": inputs.attention_mask,427            "pad_token_id": tokenizer.pad_token_id,428            "eos_token_id": tokenizer.eos_token_id,429            "temperature": st.session_state.temperature,430            "top_p": 0.85,431            "streamer": streamer,432        }433 434        Thread(target=model.generate, kwargs=generation_kwargs).start()435 436        answer = ""437        for new_text in streamer:438            answer += new_text439            placeholder.markdown(process_assistant_content(answer, is_streaming=True), unsafe_allow_html=True)440 441        full_answer = answer442 443       444        for _ in range(16):445            tool_calls = re.findall(r'<tool_call>(.*?)</tool_call>', answer, re.DOTALL)446            if not tool_calls:447                break448            st.session_state.chat_messages.append({"role": "assistant", "content": answer})449            tool_results = []450            for tc_str in tool_calls:451                try:452                    tc = json.loads(tc_str.strip())453                    result = execute_tool(tc.get('name', ''), tc.get('arguments', {}))454                    st.session_state.chat_messages.append({"role": "tool", "content": json.dumps(result, ensure_ascii=False)})455                    tool_results.append(f'<div style="background: rgba(90, 130, 110, 0.20); border: 1px solid rgba(150, 200, 170, 0.30); padding: 10px 12px; border-radius: 12px; margin: 6px 0;"><div style="font-size:12px;opacity:.75;display:block;margin:0 0 6px 0;line-height:1;">ToolCalled</div><div><b>{tc.get("name", "")}</b>: {json.dumps(result, ensure_ascii=False)}</div></div>')456                except:457                    pass458            full_answer += "\n" + "\n".join(tool_results) + "\n"459            placeholder.markdown(process_assistant_content(full_answer, is_streaming=True), unsafe_allow_html=True)460 461            new_prompt = tokenizer.apply_chat_template(st.session_state.chat_messages, **template_kwargs)462            inputs = tokenizer(new_prompt, return_tensors="pt", truncation=True).to(device)463            streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)464            generation_kwargs["input_ids"] = inputs.input_ids465            generation_kwargs["attention_mask"] = inputs.attention_mask466            generation_kwargs["max_length"] = inputs.input_ids.shape[1] + st.session_state.max_new_tokens467            generation_kwargs["streamer"] = streamer468 469            Thread(target=model.generate, kwargs=generation_kwargs).start()470            answer = ""471            for new_text in streamer:472                answer += new_text473                placeholder.markdown(process_assistant_content(full_answer + answer, is_streaming=True), unsafe_allow_html=True)474            full_answer += answer475 476        answer = full_answer477        messages.append({"role": "assistant", "content": answer})478        st.session_state.chat_messages.append({"role": "assistant", "content": answer})479        480      481 482if __name__ == "__main__":483    main()