Ubuntu 22.04 安装 Openclaw 详细教程：配置 AI 员工与多模型接入

重启服务：openclaw-cn gateway restart

配置钉钉

访问 https://open-dev.dingtalk.com 获取 Client ID (AppKey) 和 Client Secret (AppSecret)。 在权限管理中添加：

• Card.Instance.Write
• Card.Streaming.Write
• im:message

安装钉钉插件（默认无内置）：

openclaw-cn plugins install https://github.com/soimy/clawdbot-channel-dingtalk.git

在 GLM-4.7-Flash 基础上加入 DeepSeek

当 GLM-4.7 Flash 免费 token 不足时，可自动切换到 DeepSeek。需在 openclaw.json 中加入 DeepSeek API Key 配置，然后重启服务：openclaw-cn gateway restart

加入 MiniMax 和豆包模型

1. MiniMax M2.5: 访问 https://api.minimax.chat/ 获取 API Key。
2. Seedance 2.0: 访问 https://console.volcengine.com/ark 开通火山方舟服务并创建 API Key。
3. 配置 openclaw.json 即可接入多个大模型。

配置 Web 搜索

使用 Exa.ai (https://exa.ai/) 进行网络搜索。

1. 注册并获取 API Key。
2. 告知 Openclaw 配置："我注册了 Exa.ai，并得到 apikey：xxx，请帮我配置 exa.ai，代替 Brave Search 进行网络搜索。"
3. 重启服务：openclaw-cn gateway restart

.env File

EXA_API_KEY=YOUR_API_KEY

🔌 Exa MCP Server for OpenAI Codex

给 OpenAI Codex 提供实时 Web 搜索、代码上下文和公司研究功能。

运行命令：

codex mcp add exa --url https://mcp.exa.ai/mcp?exaApiKey=YOUR_API_KEY

启用特定工具：

https://mcp.exa.ai/mcp?exaApiKey=YOUR_API_KEY&tools=web_search_exa,get_code_context_exa,people_search_exa

启用所有工具：

https://mcp.exa.ai/mcp?exaApiKey=YOUR_API_KEY&tools=web_search_exa,web_search_advanced_exa,get_code_context_exa,crawling_exa,company_research_exa,people_search_exa,deep_researcher_start,deep_researcher_check

Quick Start

cURL:

curl -X POST 'https://api.exa.ai/search' \
-H 'x-api-key: YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{ "query": "latest developments in AI safety research", "type": "auto", "num_results": 10, "contents": { "text": { "max_characters": 20000 } } }'

Function Calling / Tool Use

Function calling 允许 AI 代理根据对话上下文动态决定何时搜索网络。

OpenAI Function Calling:

import json
from openai import OpenAI
from exa_py import Exa

openai = OpenAI()
exa = Exa()

tools = [{"type":"function","function":{"name":"exa_search","description":"Search the web for current information.","parameters":{"type":"object","properties":{"query":{"type":"string","description":"Search query"}},"required":["query"]}}}]

def exa_search(query:str)->str:
    results = exa.search_and_contents(query,type="auto", num_results=10, text={"max_characters":20000})
    return "\n".join([f"{r.title}: {r.url}" for r in results.results])

messages = [{"role":"user","content":"What's the latest in AI safety?"}]
response = openai.chat.completions.create(model="gpt-4o", messages=messages, tools=tools)
if response.choices[0].message.tool_calls:
    tool_call = response.choices[0].message.tool_calls[0]
    search_results = exa_search(json.loads(tool_call.function.arguments)["query"])
    messages.append(response.choices[0].message)
    messages.append({"role":"tool","tool_call_id": tool_call.id,"content": search_results})
final = openai.chat.completions.create(model="gpt-4o", messages=messages)
print(final.choices[0].message.content)

Anthropic Tool Use:

import anthropic
from exa_py import Exa

client = anthropic.Anthropic()
exa = Exa()

tools = [{"name":"exa_search","description":"Search the web for current information.","input_schema":{"type":"object","properties":{"query":{"type":"string","description":"Search query"}},"required":["query"]}}]

def exa_search(query:str)->str:
    results = exa.search_and_contents(query,type="auto", num_results=10, text={"max_characters":20000})
    return "\n".join([f"{r.title}: {r.url}" for r in results.results])

messages = [{"role":"user","content":"Latest quantum computing developments?"}]
response = client.messages.create(model="claude-sonnet-4-20250514", max_tokens=4096, tools=tools, messages=messages)
if response.stop_reason == "tool_use":
    tool_use = next(b for b in response.content if b.type=="tool_use")
    tool_result = exa_search(tool_use.input["query"])
    messages.append({"role":"assistant","content": response.content})
    messages.append({"role":"user","content":[{"type":"tool_result","tool_use_id": tool_use.id,"content": tool_result}]})
final = client.messages.create(model="claude-sonnet-4-20250514", max_tokens=4096, tools=tools, messages=messages)
print(final.content[0].text)

Search Type Reference

Tip: type="auto" works well for most queries.

Content Configuration

Choose ONE content type per request:

Warning: Using text: true can significantly increase token count.

Domain Filtering (Optional)

Example:

{"includeDomains":["arxiv.org","github.com"],"excludeDomains":["pinterest.com"]}

Web Search Tool

{"query":"latest developments in AI safety research","num_results":10,"contents":{"text":{"max_characters":20000}}}

Category Examples

Use category filters to search dedicated indexes.

• People Search (category: "people"): Find people by role, expertise.
• Company Search (category: "company"): Find companies by industry.
• News Search (category: "news"): News articles.
• Research Papers (category: "research paper"): Academic papers.
• Tweet Search (category: "tweet"): Twitter/X posts.

Content Freshness (maxAgeHours)

Sets maximum acceptable age for cached content.

Other Endpoints

Troubleshooting

• Results not relevant? Try type: "auto" or type: "deep". Refine query.
• Need structured data? Use type: "deep" with outputSchema.
• Results too slow? Use type: "fast" or reduce num_results.
• No results? Remove filters, simplify query.

Resources

• Docs: https://exa.ai/docs
• Dashboard: https://dashboard.exa.ai
• API Status: https://status.exa.ai