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Malicious npm Packages Impersonate Flashbots SDKs, Targeting Ethereum Wallet Credentials
Four npm packages disguised as cryptographic tools steal developer credentials and send them to attacker-controlled Telegram infrastructure.
bee-agent-framework
Advanced tools
🐝 Bee Agent Framework is an open-source TypeScript library for building production-ready multi-agent systems. Pick from a variety of 🌐 AI Providers, customize the 📜 prompt templates, create 🤖 agents, equip agents with pre-made 🛠️ tools, and orchestrate 🤖🤝🤖 multi-agent workflows! 🪄
For a full changelog, see the releases page.
This example demonstrates how to build a multi-agent workflow using Bee Agent Framework:
import "dotenv/config";
import { UnconstrainedMemory } from "bee-agent-framework/memory/unconstrainedMemory";
import { OpenMeteoTool } from "bee-agent-framework/tools/weather/openMeteo";
import { WikipediaTool } from "bee-agent-framework/tools/search/wikipedia";
import { AgentWorkflow } from "bee-agent-framework/experimental/workflows/agent";
import { Message, Role } from "bee-agent-framework/llms/primitives/message";
import { GroqChatLLM } from "bee-agent-framework/adapters/groq/chat";
const workflow = new AgentWorkflow();
workflow.addAgent({
name: "Researcher",
instructions: "You are a researcher assistant. Respond only if you can provide a useful answer.",
tools: [new WikipediaTool()],
llm: new GroqChatLLM(),
});
workflow.addAgent({
name: "WeatherForecaster",
instructions: "You are a weather assistant. Respond only if you can provide a useful answer.",
tools: [new OpenMeteoTool()],
llm: new GroqChatLLM(),
execution: { maxIterations: 3 },
});
workflow.addAgent({
name: "Solver",
instructions:
"Your task is to provide the most useful final answer based on the assistants' responses which all are relevant. Ignore those where assistant do not know.",
llm: new GroqChatLLM(),
});
const memory = new UnconstrainedMemory();
await memory.add(
Message.of({
role: Role.USER,
text: "What is the capital of France and what is the current weather there?",
meta: { createdAt: new Date() },
}),
);
const { result } = await workflow.run(memory.messages).observe((emitter) => {
emitter.on("success", (data) => {
console.log(`-> ${data.step}`, data.response?.update?.finalAnswer ?? "-");
});
});
console.log(`Agent 🤖`, result.finalAnswer);
[!TIP]
🚀 Would you like a fully set-up TypeScript project with Bee, Code Interpreter, and Observability? Check out our Bee Framework Starter.
[!TIP]
🚀 Would you like to work with Bee in your web browser? See Bee Stack
npm install bee-agent-framework
or
yarn add bee-agent-framework
import { BeeAgent } from "bee-agent-framework/agents/bee/agent";
import { OllamaChatModel } from "bee-agent-framework/adapters/ollama/backend/chat";
import { TokenMemory } from "bee-agent-framework/memory/tokenMemory";
import { DuckDuckGoSearchTool } from "bee-agent-framework/tools/search/duckDuckGoSearch";
import { OpenMeteoTool } from "bee-agent-framework/tools/weather/openMeteo";
const llm = new OllamaChatModel("llama3.1"); // default is llama3.1 (8B), it is recommended to use 70B model
const agent = new BeeAgent({
llm, // for more explore 'bee-agent-framework/adapters'
memory: new TokenMemory(), // for more explore 'bee-agent-framework/memory'
tools: [new DuckDuckGoSearchTool(), new OpenMeteoTool()], // for more explore 'bee-agent-framework/tools'
});
const response = await agent
.run({ prompt: "What's the current weather in Las Vegas?" })
.observe((emitter) => {
emitter.on("update", async ({ data, update, meta }) => {
console.log(`Agent (${update.key}) 🤖 : `, update.value);
});
});
console.log(`Agent 🤖 : `, response.result.text);
➡️ See a more advanced example.
➡️ you can run this example after local installation, using the command yarn start examples/agents/simple.ts
[!TIP]
To run this example, be sure that you have installed ollama with the llama3.1 model downloaded.
[!TIP]
Documentation is available at https://i-am-bee.github.io/bee-agent-framework/
[!NOTE]
yarn
should be installed via Corepack (tutorial)
git clone git@github.com:i-am-bee/bee-agent-framework
.yarn install --immutable && yarn prepare
..env
(from .env.template
) and fill in missing values (if any).yarn run start:bee
(it runs /examples/agents/bee.ts
file).➡️ All examples can be found in the examples directory.
➡️ To run an arbitrary example, use the following command yarn start examples/agents/bee.ts
(just pass the appropriate path to the desired example).
The source directory (src
) provides numerous modules that one can use.
Name | Description |
---|---|
agents | Base classes defining the common interface for agent. |
workflows | Build agentic applications in a declarative way via workflows. |
backend | Functionalities that relates to AI models (chat, embedding, image, tool calling, ...) |
template | Prompt Templating system based on Mustache with various improvements. |
memory | Various types of memories to use with agent. |
tools | Tools that an agent can use. |
cache | Preset of different caching approaches that can be used together with tools. |
errors | Error classes and helpers to catch errors fast. |
logger | Core component for logging all actions within the framework. |
serializer | Core component for the ability to serialize/deserialize modules into the serialized format. |
version | Constants representing the framework (e.g., latest version) |
emitter | Bringing visibility to the system by emitting events. |
internals | Modules used by other modules within the framework. |
To see more in-depth explanation see overview.
The Bee Agent Framework is an open-source project and we ❤️ contributions.
If you'd like to contribute to Bee, please take a look at our contribution guidelines.
We are using GitHub Issues to manage our public bugs. We keep a close eye on this, so before filing a new issue, please check to make sure it hasn't already been logged.
This project and everyone participating in it are governed by the Code of Conduct. By participating, you are expected to uphold this code. Please read the full text so that you can read which actions may or may not be tolerated.
All content in these repositories including code has been provided by IBM under the associated open source software license and IBM is under no obligation to provide enhancements, updates, or support. IBM developers produced this code as an open source project (not as an IBM product), and IBM makes no assertions as to the level of quality nor security, and will not be maintaining this code going forward.
Special thanks to our contributors for helping us improve Bee Agent Framework.
FAQs
Bee - LLM Agent Framework
The npm package bee-agent-framework receives a total of 189 weekly downloads. As such, bee-agent-framework popularity was classified as not popular.
We found that bee-agent-framework demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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