feat: Add Telegram bot integration and .env configuration
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# ai-pipelines
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# AI Pipelines with Telegram Bot
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To install dependencies:
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This project provides a framework for creating and executing AI-powered pipelines, with a Telegram bot interface for easy interaction.
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## Features
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- Execute AI-powered pipelines using OpenAI's models
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- Integration with Model Context Protocol (MCP) tools
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- Telegram bot interface for easy interaction
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- Support for dynamic prompts and variables
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## Prerequisites
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- Node.js and Bun installed
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- OpenAI API key
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- Telegram Bot Token (get it from [@BotFather](https://t.me/botfather))
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## Setup
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1. Clone the repository
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2. Install dependencies:
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```bash
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bun install
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```
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To run:
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3. Copy `.env.example` to `.env` and fill in your credentials:
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```bash
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bun run index.ts
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cp .env.example .env
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```
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This project was created using `bun init` in bun v1.2.14. [Bun](https://bun.sh) is a fast all-in-one JavaScript runtime.
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4. Edit the `.env` file and add your:
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- `OPENAI_API_KEY` - Your OpenAI API key
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- `TELEGRAM_BOT_TOKEN` - Your Telegram bot token from @BotFather
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- `MCP_SERVER_URL` - (Optional) MCP server URL (defaults to Santiment's MCP server)
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## Running the Bot
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Start the bot with:
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```bash
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bun start
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```
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Or in development mode with auto-reload:
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```bash
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bun --watch src/main.ts
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```
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## Using the Bot
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1. Find your bot on Telegram using the username you set with @BotFather
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2. Start a chat with the bot
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3. Send any message to the bot, and it will process it through the AI pipeline
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4. The bot will respond with the AI's analysis or action
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## Project Structure
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- `src/bot/` - Telegram bot implementation
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- `src/models/` - Data models and interfaces
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- `src/pipelines/` - Pipeline execution logic
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- `src/services/` - External service integrations
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- `src/main.ts` - Application entry point
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## Development
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- Run linter: `bun run lint`
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- Run type checking: `bun run ts:check`
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- Run both: `bun run check`
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## License
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MIT
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