Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, tamper-evident SHA-256 chain with RFC 3161 anchoring, 20 MCP tools.
关键参数与规格
关键参数与规格
参数
值
语言
TypeScript
类别
AI Engineering
子类别
Build agent workflow (SDK)
星标数
1,438
分叉数
172
贡献者
6
创建日期
2023-04-10
更新日期
2026-10-15
1 天星标数
0
7 天星标数
1
排名
10,324
上次排名
5,689
排名变化
-4,635
7 天星标排名
9,842
上次 7 天星标排名
9,906
7 天星标排名变化
64
总星标排名
8,365
上次总星标排名
8,354
总星标排名变化
-11
README 摘录
AI Legion: an LLM-powered autonomous agent platform A framework for autonomous agents who can work together to accomplish tasks. Rename the file at the root of the project to and add your secrets to it: You'll also need to enable the Google Custom Search API for your Google Cloud account, e. Running Start the program: Interact with the agents through the console. Anything you type will be sent as a message to all agents currently. Action errors After spinning
up a new agent, you will often see them make some mistakes which generate errors: Trying to use an action before they've asked for on it to know what its parameters are Trying to just use a raw text response instead of a correctly-formatted action (or raw text wrapping a code block which contains a valid action) Trying to use a multi-line parameter value without wrapping it in the multiline delimiter ( ) This is a normal period of adjustment
as they learn to operate themselves. They generally will learn from these mistakes and recover, although agents sometimes devolve into endless error loops and can't figure out what the problem is. It's highly advised never to leave an agent unattended, since such infinite loops can eat through your tokens quickly (especially if they're stuck on a high-token-count action such as ). Agent state Each agent stores its state under the directory. Agent 1, for example, has You can simply
delete any of these things, or the whole agent folder (or the whole ) to selectively wipe whatever state you want between runs. Otherwise, agents will pick up where you left off on restart. A nice aspect of this is that when you want to debug a problem you ran into with a particular agent, you can delete the events in their memory subsequent to the point where the problem occurred, make changes to the code, and restart them to effectively
replay that moment until you've fixed the bug. You can also ask an agent to implement a feature, and once they've done so you can restart, tell them that you've loaded the feature, and ask them to try it out.
常见问题
记录了多少星标和分叉？
eumemic/ai-legion 有 1,438 个星标和 172 个分叉。
仓库排名是多少？
eumemic/ai-legion 排名第 10,324。
记录的语言和类别是什么？
eumemic/ai-legion 有 1,438 个星标，语言为 TypeScript，类别为 AI Engineering。
AI Legion: an LLM-powered autonomous agent platform
A framework for autonomous agents who can work together to accomplish tasks.
Setup
You will need at least Node 10.
npm install
Rename the .env.template file at the root of the project to .env and add your secrets to it:
OPENAI_API_KEY=... # obtain from https://platform.openai.com/account/api-keys
# the following are needed for the agent to be able to search the web:
GOOGLE_SEARCH_ENGINE_ID=... # create a custom search engine at https://cse.google.com/cse/all
GOOGLE_API_KEY=... # obtain from https://console.cloud.google.com/apis/credentials
AGENT_DELAY=... # optionally, a delay in milliseconds following every agent action
You'll also need to enable the Google Custom Search API for your Google Cloud account, e.g.
Running
Start the program:
npm run start [# of agents] [gpt-3.5-turbo|gpt-4]
Interact with the agents through the console. Anything you type will be sent as a message to all agents currently.
Action errors
After spinning up a new agent, you will often see them make some mistakes which generate errors:
Trying to use an action before they've asked for help on it to know what its parameters are
Trying to just use a raw text response instead of a correctly-formatted action (or raw text wrapping a code block which contains a valid action)
Trying to use a multi-line parameter value without wrapping it in the multiline delimiter (% ff9d7713-0bb0-40d4-823c-5a66de48761b)
This is a normal period of adjustment as they learn to operate themselves. They generally will learn from these mistakes and recover, although gpt-3.5-turbo agents sometimes devolve into endless error loops and can't figure out what the problem is. It's highly advised never to leave an agent unattended, since such infinite loops can eat through your tokens quickly (especially if they're stuck on a high-token-count action such as writeFile).
Agent state
Each agent stores its state under the .store directory. Agent 1, for example, has
.store/1/memory
.store/1/goals
.store/1/notes
You can simply delete any of these things, or the whole agent folder (or the whole .store) to selectively wipe whatever state you want between runs. Otherwise, agents will pick up where you left off on restart.
A nice aspect of this is that when you want to debug a problem you ran into with a particular agent, you can delete the events in their memory subsequent to the point where the problem occurred, make changes to the code, and restart them to effectively replay that moment until you've fixed the bug. You can also ask an agent to implement a feature, and once they've done so you can restart, tell them that you've loaded the feature, and ask them to try it out.