BeeAI Framework for TypeScript 
**Build production-ready multi-agent systems. Also available in
Python.**
[](https://github.com/i-am-bee/beeai-framework?tab=Apache-2.0-1-ov-file#readme)
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## Modules
The source directory (`src`) contains the available modules:
| Name | Description |
| --------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| [**agents**](/typescript/docs/agents.md) | Base classes defining the common interface for agent. |
| [**backend**](/typescript/docs/backend.md) | Functionalities that relates to AI models (chat, embedding, image, tool calling, ...) |
| [**template**](/typescript/docs/templates.md) | Prompt Templating system based on `Mustache` with various improvements. |
| [**memory**](/typescript/docs/memory.md) | Various types of memories to use with agent. |
| [**tools**](/typescript/docs/tools.md) | Tools that an agent can use. |
| [**cache**](/typescript/docs/cache.md) | Preset of different caching approaches that can be used together with tools. |
| [**errors**](/typescript/docs/errors.md) | Base framework error classes used by each module. |
| [**logger**](/typescript/docs/logger.md) | Core component for logging all actions within the framework. |
| [**serializer**](/typescript/docs/serialization.md) | Core component for the ability to serialize/deserialize modules into the serialized format. |
| [**version**](/typescript/docs/version.md) | Constants representing the framework (e.g., the latest version) |
| [**emitter**](/typescript/docs/emitter.md) | Bringing visibility to the system by emitting events. |
## External modules
Use these packages to extend the base BeeAI framework functionality:
| Name | Description |
| -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------- |
| [**instrumentation**](https://github.com/Arize-ai/openinference/tree/main/js/packages/openinference-instrumentation-beeai) | Integrate monitoring tools into your application. |
## Installation
Install the framework using npm:
```shell
npm install beeai-framework
```
or yarn:
```shell
yarn add beeai-framework
```
## Quick example
The following example demonstrates how to build a multi-agent workflow using the BeeAI Framework:
```ts
import "dotenv/config";
import { OpenMeteoTool } from "beeai-framework/tools/weather/openMeteo";
import { WikipediaTool } from "beeai-framework/tools/search/wikipedia";
import { AgentWorkflow } from "beeai-framework/workflows/agent";
import { OllamaChatModel } from "beeai-framework/adapters/ollama/backend/chat";
const workflow = new AgentWorkflow();
workflow.addAgent({
name: "Researcher",
role: "A diligent researcher",
instructions: "You look up and provide information about a specific topic.",
tools: [new WikipediaTool()],
llm: new OllamaChatModel("llama3.1"),
});
workflow.addAgent({
name: "WeatherForecaster",
role: "A weather reporter",
instructions: "You provide detailed weather reports.",
tools: [new OpenMeteoTool()],
llm: new OllamaChatModel("llama3.1"),
});
workflow.addAgent({
name: "DataSynthesizer",
role: "A meticulous and creative data synthesizer",
instructions: "You can combine disparate information into a final coherent summary.",
llm: new OllamaChatModel("llama3.1"),
});
const location = "Saint-Tropez";
await workflow
.run([
{
prompt: `Provide a short history of ${location}.`,
},
{
prompt: `Provide a comprehensive weather summary for ${location} today.`,
expectedOutput:
"Essential weather details such as chance of rain, temperature and wind. Only report information that is available.",
},
{
prompt: `Summarize the historical and weather data for ${location}.`,
expectedOutput: `A paragraph that describes the history of ${location}, followed by the current weather conditions.`,
},
])
.observe((emitter) => {
emitter.on("success", (data) => {
console.log(
`-> ${data.step} has been completed with the following outcome\n`,
data?.state.finalAnswer ?? "-",
);
});
});
```
### Running the example
> [!Note]
>
> To run this example, be sure that you have installed [groq](/typescript/docs/backend.md) and the appropriate .env files set up.
To run projects, use:
```shell
yarn start [project_name].ts
```
Using npm:
```shell
npm run start [project_name].ts
```
➡️ Explore more in our [examples library](/typescript/examples).
## Contribution guidelines
The BeeAI Framework is an open-source project and we ❤️ contributions.