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31 changes: 24 additions & 7 deletions README.md
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Use agentic AI on Runloop to create a (fake) tax preparation service.

**⚠️ IMPORTANT: This is a demonstration system only. Do not use for actual tax preparation or filing. Do not upload real personal or tax information.**
**⚠️ IMPORTANT: This is a demonstration system only. Do not use for actual tax preparation or filing. Do not upload real personal or tax information. ⚠️**

## Overview

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- Runloop account and API key (as described in the [Runloop Quickstart](https://docs.runloop.ai/docs/tutorials/quickstart))
- (Optional) Weights & Biases account for LLM tracing with Weave

### Setting up
### Setup & Configuration

1. **Install dependencies**

```bash
pnpm install
```

2. **Set up environment variables**
2. **Configure your environment**

Set up your Runloop API key in your local environment:
Set up your API keys in your local environment and configure a .env file.

First, visit the [https://platform.runloop.ai/settings](settings) page on Runloop.

a. Create a Runloop API key in the [https://platform.runloop.ai/settings](settings) page.

b. Generate an OpenAI API key using the [https://platform.openai.com/settings/organization/api-keys](OpenAI console).

c. Create a Secret for the OpenAI key you just generated in the [https://platform.runloop.ai/settings](settings) page. Name the secret name `OPENAI_API_KEY` and paste the key value from the OpenAI site.

d. Now configure your environment:

```bash
export RUNLOOP_API_KEY=<your_runloop_api_key_here>
cp packages/tax-processing/.env.example packages/tax-processing/.env
```

Open the `.env` file and update values where prompted.

e. Launch the environment to test the setup:

```bash
pnpm dev
```

And add your OPENAI_API_KEY as a Runloop secret.
TODO: point to the docs on how to do this
TODO: specify the name needed
Then open your browser and go to the [http://localhost:3000/](demo site).

3. **(Optional) Enable Weave Tracing**

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2 changes: 1 addition & 1 deletion packages/scripts/src/step1-runloop-setup.ts
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console.log(` ✓ Base blueprint created: ${baseBlueprint.id}`);

let baseBlueprintInfo = await baseBlueprint.getInfo();
const baseBlueprintInfo = await baseBlueprint.getInfo();
if (baseBlueprintInfo.status === 'build_complete') {
console.log(` ✓ Base blueprint build completed successfully! \n`);
} else {
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