把这份指南发给你的 OpenClaw,它会引导你选择最适合的多 Agent 架构。
当用户把这份文档发给你时,请按照以下流程引导他们选择合适的多 Agent 架构配置。
I wrote an in-depth research prompt to conduct a GPT-Deep-Research on the Manus topic, seeking to replicate it with currently available open source tools. This is the result:
Manus is an autonomous AI agent built as a wrapper around foundation models (primarily Claude 3.5/3.7 and Alibaba's Qwen). It operates in a cloud-based virtual computing environment with full access to tools like web browsers, shell commands, and code execution. The system's key innovation is using executable Python code as its action mechanism ("CodeAct" approach), allowing it to perform complex operations autonomously. The architecture consists of an iterative agent loop (analyze → plan → execute → observe), with specialized modules for planning, knowledge retrieval, and memory management. Manus uses file-based memory to track progress and store information across operations. The system can be replicated using open-source components including CodeActAgent (a fine-tuned Mistral model), Docker for sandbox
AntiGraviti tools parsed based on reverse engineering and ParseToolArgs structs found in the binary. We need strings, the juice is in the DATA block and not in the code.
I have used the following commands on my MacOS:
1. Extract strings to file for faster iterations
# strings /Applications/Antigravity.app/Contents/Resources/app/extensions/antigravity/bin/language_server_macos_arm > ~/Downloads/language_server_macos_arm_strings.txt
2. Search tools| You are Manus, an AI agent created by the Manus team. | |
| You excel at the following tasks: | |
| 1. Information gathering, fact-checking, and documentation | |
| 2. Data processing, analysis, and visualization | |
| 3. Writing multi-chapter articles and in-depth research reports | |
| 4. Creating websites, applications, and tools | |
| 5. Using programming to solve various problems beyond development | |
| 6. Various tasks that can be accomplished using computers and the internet |
| package main | |
| import ( | |
| "fmt" | |
| "runtime" | |
| "testing" | |
| "unsafe" | |
| ) | |
| func toBytes(s string) []byte { |
| #include <bcc/proto.h> | |
| #include <uapi/linux/ip.h> | |
| #include <uapi/linux/ipv6.h> | |
| #include <uapi/linux/icmp.h> | |
| #include <uapi/linux/tcp.h> | |
| #include <uapi/linux/udp.h> | |
| #include <uapi/linux/icmpv6.h> | |
| #include <net/inet_sock.h> | |
| #include <linux/netfilter/x_tables.h> |
| 000000 Officially Xerox | |
| 000001 SuperLAN-2U | |
| 000002 BBN (was internal usage only, no longer used) | |
| 000003 XEROX CORPORATION | |
| 000004 XEROX CORPORATION | |
| 000005 XEROX CORPORATION | |
| 000006 XEROX CORPORATION | |
| 000007 XEROX CORPORATION | |
| 000008 XEROX CORPORATION | |
| 000009 powerpipes? |
| package main | |
| import ( | |
| "fmt" | |
| "strings" | |
| "time" | |
| ) | |
| func handleEventError(tokenName string, line, pos int) error { | |
| err := fmt.Errorf("error at line %d, pos %d: %s", line, pos, tokenName) |