pip install uv

irm https://astral.sh/uv/install.ps1 | iex

git clone https://github.com/mannaandpoem/OpenManus.git
cd OpenManus

uv venv
#Unix/macOS返回
source .venv/bin/activate

#Windows返回:
.venv\Scripts\activate

uv pip install -r requirements.txt

C:\OpenManus\OpenManus-main>uv pip install -r requirements.txt
Resolved 133 packages in 2m 36s
      Built english-words==2.0.1
      Built html2text==2024.2.26
Prepared 132 packages in 2m 50s
Installed 133 packages in 10.19s
 + aiofiles==24.1.0
 + aiohappyeyeballs==2.5.0
 + aiohttp==3.11.13
 + aiolimiter==1.2.1
 + aiosignal==1.3.2
 + annotated-types==0.7.0
 + anthropic==0.49.0
 + anyio==4.8.0
 + attrs==25.1.0
 + backoff==2.2.1
 + beartype==0.12.0
 + beautifulsoup4==4.13.3
 + blinker==1.9.0
 + browser-use==0.1.40
 + browsergym==0.13.3
 + browsergym-assistantbench==0.13.3
 + browsergym-core==0.13.3
 + browsergym-experiments==0.13.3
 + browsergym-miniwob==0.13.3
 + browsergym-visualwebarena==0.13.3
 + browsergym-webarena==0.13.3
 + browsergym-workarena==0.4.1
 + certifi==2025.1.31
 + charset-normalizer==3.4.1
 + click==8.1.8
 + cloudpickle==3.1.1
 + colorama==0.4.6
 + dataclasses-json==0.6.7
 + datasets==3.2.0
 + defusedxml==0.7.1
 + dill==0.3.8
 + distro==1.9.0
 + english-words==2.0.1
 + evaluate==0.4.3
 + faker==37.0.0
 + farama-notifications==0.0.4
 + filelock==3.17.0
 + flask==3.1.0
 + frozenlist==1.5.0
 + fsspec==2024.9.0
 + googlesearch-python==1.3.0
 + greenlet==3.1.1
 + gymnasium==1.0.0
 + h11==0.14.0
 + html2text==2024.2.26
 + httpcore==1.0.7
 + httpx==0.28.1
 + huggingface-hub==0.29.2
 + idna==3.10
 + imageio==2.37.0
 + itsdangerous==2.2.0
 + jinja2==3.1.6
 + jiter==0.8.2
 + joblib==1.4.2
 + jsonpatch==1.33
 + jsonpointer==3.0.0
 + langchain-anthropic==0.3.3
 + langchain-core==0.3.43
 + langchain-ollama==0.2.2
 + langchain-openai==0.3.1
 + langsmith==0.3.13
 + lazy-loader==0.4
 + libvisualwebarena==0.0.15
 + libwebarena==0.0.4
 + loguru==0.7.3
 + lxml==5.3.1
 + markdownify==0.14.1
 + markupsafe==3.0.2
 + marshmallow==3.26.1
 + monotonic==1.6
 + mpmath==1.3.0
 + multidict==6.1.0
 + multiprocess==0.70.16
 + mypy-extensions==1.0.0
 + networkx==3.4.2
 + nltk==3.9.1
 + numpy==2.2.3
 + ollama==0.4.7
 + openai==1.58.1
 + orjson==3.10.15
 + packaging==24.2
 + pandas==2.2.3
 + pillow==10.4.0
 + playwright==1.49.1
 + portalocker==3.1.1
 + posthog==3.19.0
 + propcache==0.3.0
 + pyarrow==19.0.1
 + pydantic==2.10.6
 + pydantic-core==2.27.2
 + pyee==12.0.0
 + pyparsing==3.2.1
 + python-dateutil==2.9.0.post0
 + python-dotenv==1.0.1
 + pytz==2025.1
 + pywin32==309
 + pyyaml==6.0.2
 + regex==2024.11.6
 + requests==2.32.3
 + requests-toolbelt==1.0.0
 + sacrebleu==2.5.1
 + safetensors==0.5.3
 + scikit-image==0.25.2
 + scipy==1.15.2
 + setuptools==76.0.0
 + six==1.17.0
 + sniffio==1.3.1
 + soupsieve==2.6
 + sympy==1.13.1
 + tabulate==0.9.0
 + tenacity==9.0.0
 + text-generation==0.7.0
 + tifffile==2025.2.18
 + tiktoken==0.9.0
 + tokenizers==0.21.0
 + torch==2.6.0
 + tqdm==4.67.1
 + transformers==4.49.0
 + types-requests==2.32.0.20250306
 + types-tqdm==4.67.0.20250301
 + typing-extensions==4.12.2
 + typing-inspect==0.9.0
 + tzdata==2025.1
 + unidiff==0.7.5
 + urllib3==2.3.0
 + uvicorn==0.34.0
 + weblinx==0.3.2
 + weblinx-browsergym==0.0.1.dev14
 + werkzeug==3.1.3
 + win32-setctime==1.2.0
 + xxhash==3.5.0
 + yarl==1.18.3
 + zstandard==0.23.0

# DeepSeek V3配置（國內(nèi)最佳選擇）
[llm]
model = "deepseek-v3"
base_url = "https://api.deepseek.com/v1"
api_key = "你的API密鑰"  # 替換為你的實(shí)際密鑰
max_tokens = 8192
temperature = 0.0

# 通義千問配置（國產(chǎn)模型備選）
[llm]
model = "qwen-turbo"
base_url = "https://dashscope.aliyuncs.com/api/v1"
api_key = "你的阿里云API密鑰"
max_tokens = 4096
temperature = 0.0

# Claude配置（國外用戶推薦）
[llm]
model = "claude-3-5-sonnet"
base_url = "https://api.anthropic.com"
api_key = "你的Anthropic API密鑰"
max_tokens = 4096
temperature = 0.0

# 分步安裝能解決大部分依賴問題
pip install --no-deps -r requirements.txt

# 對于playwright，使用這個(gè)方法成功解決了問題
pip install playwright==1.40.0 --no-build-isolation
playwright install chromium

# 如果仍然遇到問題，嘗試手動安裝核心依賴
pip install pydantic==2.5.2 langchain==0.1.6 beautifulsoup4==4.12.3

# 在Windows中處理路徑時(shí)使用了這種方式統(tǒng)一處理
import os
def normalize_path(path):
    """統(tǒng)一處理Windows和Linux路徑"""
    return os.path.normpath(path).replace('\\', '/')

# 修改了app/llm.py，增加了更詳細(xì)的錯(cuò)誤處理
def call_api_with_detailed_error(self, *args, **kwargs):
    try:
        return self._call_api(*args, **kwargs)
    except Exception as e:
        error_msg = str(e)
        if "400" in error_msg:
            # 檢查請求參數(shù)
            print("API 400錯(cuò)誤排查清單:")
            print("1. 檢查API密鑰格式是否正確")
            print("2. 檢查模型名稱是否正確")
            print("3. 檢查請求參數(shù)格式")
            print("4. 原始錯(cuò)誤信息:", error_msg)
        elif "401" in error_msg:
            print("認(rèn)證失敗，請檢查API密鑰")
        elif "429" in error_msg:
            print("請求頻率過高，請降低請求速度或升級API配額")
        raise e

# 實(shí)現(xiàn)了一個(gè)上下文管理器，大大提高了長任務(wù)的完成率
def manage_context_length(context, max_length=6000, summarize_threshold=7500):
    """智能管理上下文長度"""
    if len(context) < summarize_threshold:
        return context
    
    # 將上下文分為三部分處理
    intro = context[:1500]  # 保留初始指令
    recent = context[-3000:]  # 保留最近交互
    middle = context[1500:-3000]  # 中間部分需要壓縮
    
    # 對中間部分進(jìn)行摘要
    from app.llm import LLM
    llm = LLM()
    summary_prompt = f"請將以下對話歷史壓縮為簡短摘要，保留關(guān)鍵信息：\n\n{middle}"
    summary = llm.generate(summary_prompt, max_tokens=1500)
    
    # 組合處理后的上下文
    new_context = intro + "\n\n[歷史摘要]: " + summary + "\n\n" + recent
    return new_context

# app/tool/bing_search.py
from typing import Dict, List, Optional
import os
import requests
from pydantic import Field
from app.logger import logger
from app.tool.base import BaseTool

class BingSearch(BaseTool):
    """使用必應(yīng)搜索引擎進(jìn)行網(wǎng)絡(luò)搜索"""
    
    name: str = "bing_search"
    description: str = "使用必應(yīng)搜索查詢信息，對于需要最新信息的查詢特別有用"
    
    def __init__(self):
        super().__init__()
        # 從環(huán)境變量或配置文件獲取API密鑰
        self.subscription_key = os.environ.get("BING_API_KEY", "你的Bing搜索API密鑰")
        self.search_url = "https://api.bing.microsoft.com/v7.0/search"
    
    def _call(self, query: str, num_results: int = 10) -> Dict:
        """執(zhí)行必應(yīng)搜索"""
        headers = {"Ocp-Apim-Subscription-Key": self.subscription_key}
        params = {
            "q": query, 
            "count": num_results, 
            "textDecorations": True, 
            "textFormat": "HTML",
            "mkt": "zh-CN"  # 設(shè)置為中文市場，結(jié)果更符合國內(nèi)用戶習(xí)慣
        }
        
        try:
            response = requests.get(self.search_url, headers=headers, params=params)
            response.raise_for_status()
            search_results = response.json()
            
            # 提取有用的搜索結(jié)果
            results = []
            if "webPages" in search_results and "value" in search_results["webPages"]:
                for result in search_results["webPages"]["value"]:
                    results.append({
                        "title": result["name"],
                        "link": result["url"],
                        "snippet": result["snippet"],
                        "dateLastCrawled": result.get("dateLastCrawled", "")
                    })
            
            # 添加新聞結(jié)果
            if "news" in search_results and "value" in search_results["news"]:
                for news in search_results["news"]["value"][:3]:  # 取前3條新聞
                    results.append({
                        "title": "[新聞] " + news["name"],
                        "link": news["url"],
                        "snippet": news["description"],
                        "datePublished": news.get("datePublished", "")
                    })
            
            return {
                "query": query,
                "results": results,
                "total_results": len(results)
            }
            
        except Exception as e:
            logger.error(f"必應(yīng)搜索出錯(cuò): {str(e)}")
            return {
                "query": query,
                "results": [],
                "total_results": 0,
                "error": str(e)
            }

# app/tool/baidu_search.py
import requests
from bs4 import BeautifulSoup
from pydantic import Field
from app.tool.base import BaseTool
from app.logger import logger

class BaiduSearch(BaseTool):
    """使用百度搜索引擎進(jìn)行網(wǎng)絡(luò)搜索"""
    
    name: str = "baidu_search"
    description: str = "使用百度搜索獲取信息，適合中文搜索"
    
    def _call(self, query: str, num_results: int = 10) -> dict:
        """執(zhí)行百度搜索并解析結(jié)果"""
        headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
            "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8"
        }
        
        search_url = f"https://www.baidu.com/s?wd={query}&rn={num_results}"
        
        try:
            response = requests.get(search_url, headers=headers, timeout=10)
            response.raise_for_status()
            response.encoding = 'utf-8'
            
            soup = BeautifulSoup(response.text, 'html.parser')
            search_results = soup.select('.result.c-container')
            
            results = []
            for result in search_results[:num_results]:
                title_elem = result.select_one('.t')
                link_elem = title_elem.select_one('a') if title_elem else None
                abstract_elem = result.select_one('.c-abstract')
                
                if title_elem and link_elem:
                    title = title_elem.get_text(strip=True)
                    link = link_elem.get('href', '')
                    abstract = abstract_elem.get_text(strip=True) if abstract_elem else "無描述"
                    
                    results.append({
                        "title": title,
                        "link": link,
                        "snippet": abstract
                    })
            
            return {
                "query": query,
                "results": results,
                "total_results": len(results)
            }
            
        except Exception as e:
            logger.error(f"百度搜索出錯(cuò): {str(e)}")
            return {
                "query": query,
                "results": [],
                "total_results": 0,
                "error": str(e)
            }

# 修改app/agent/manus.py文件
from app.tool.bing_search import BingSearch
from app.tool.baidu_search import BaiduSearch

# 找到available_tools部分并替換
available_tools: ToolCollection = Field(
    default_factory=lambda: ToolCollection(
        PythonExecute(), 
        BaiduSearch(),  # 國內(nèi)用戶首選
        BingSearch(),   # 備選搜索工具
        BrowserUseTool(), 
        FileSaver(), 
        Terminate()
    )
)

# 在app/agent/base.py中添加了循環(huán)檢測功能
def is_in_loop(self, actions_history, threshold=3, similarity_threshold=0.85):
    """檢測是否陷入執(zhí)行循環(huán)"""
    if len(actions_history) < threshold * 2:
        return False
    
    recent_actions = actions_history[-threshold:]
    previous_actions = actions_history[-(threshold*2):-threshold]
    
    # 計(jì)算最近動作與前一批動作的相似度
    similarity_count = 0
    for i in range(threshold):
        # 使用簡單字符串相似度
        current = recent_actions[i]
        previous = previous_actions[i]
        
        # 如果動作類型、參數(shù)等關(guān)鍵信息相似
        if current['tool'] == previous['tool'] and \
           self._params_similarity(current['params'], previous['params']) > similarity_threshold:
            similarity_count += 1
    
    # 如果超過一定比例的動作重復(fù)，判定為循環(huán)
    return similarity_count / threshold > 0.7

def _params_similarity(self, params1, params2):
    """計(jì)算兩組參數(shù)的相似度"""
    # 簡化實(shí)現(xiàn)，實(shí)際使用中可以采用更復(fù)雜的相似度算法
    if params1 == params2:
        return 1.0
    
    common_keys = set(params1.keys()) & set(params2.keys())
    if not common_keys:
        return 0.0
    
    similarity = 0
    for key in common_keys:
        if params1[key] == params2[key]:
            similarity += 1
    
    return similarity / len(common_keys)

# 在執(zhí)行流程中使用循環(huán)檢測
def run(self, prompt):
    actions_history = []
    
    for step in range(self.max_steps):
        action = self.plan_next_action(prompt)
        actions_history.append(action)
        
        # 檢測是否陷入循環(huán)
        if len(actions_history) > 6 and self.is_in_loop(actions_history):
            logger.warning("檢測到執(zhí)行循環(huán)，嘗試重新規(guī)劃...")
            # 添加特殊提示，幫助模型跳出循環(huán)
            prompt += "\n\n[系統(tǒng)提示]: 檢測到可能的執(zhí)行循環(huán)，請嘗試不同的解決方案或工具。"
            continue
        
        result = self.execute_action(action)
        
        if self.is_task_complete():
            return result
    
    return "達(dá)到最大步驟數(shù)，任務(wù)未完成"

# 改進(jìn)的FileSaver工具實(shí)現(xiàn)
def save_file_with_verification(self, content, file_path, overwrite=False):
    """保存文件并驗(yàn)證成功與否"""
    # 規(guī)范化路徑
    file_path = os.path.abspath(file_path)
    
    # 檢查目錄是否存在，不存在則創(chuàng)建
    dir_path = os.path.dirname(file_path)
    if not os.path.exists(dir_path):
        try:
            os.makedirs(dir_path, exist_ok=True)
        except Exception as e:
            return f"創(chuàng)建目錄失敗: {dir_path}, 錯(cuò)誤: {str(e)}"
    
    # 檢查文件是否已存在
    if os.path.exists(file_path) and not overwrite:
        return f"文件已存在且未設(shè)置覆蓋: {file_path}"
    
    # 保存文件
    try:
        if isinstance(content, str):
            with open(file_path, 'w', encoding='utf-8') as f:
                f.write(content)
        else:
            with open(file_path, 'wb') as f:
                f.write(content)
        
        # 驗(yàn)證文件是否成功保存
        if os.path.exists(file_path) and os.path.getsize(file_path) > 0:
            return f"文件成功保存到: {file_path}"
        else:
            return f"文件保存失敗，雖然沒有報(bào)錯(cuò)但文件為空: {file_path}"
    except Exception as e:
        return f"保存文件出錯(cuò): {str(e)}"