update readme

Author: Prasanna721

README.md

@@ -1,238 +1,66 @@
-# 🤖 Chat Agent Starter Kit
+# Supermemory x Pipecat
 
-![npm i agents command](./npm-agents-banner.svg)
-
-<a href="https://deploy.workers.cloudflare.com/?url=https://github.com/cloudflare/agents-starter"><img src="https://deploy.workers.cloudflare.com/button" alt="Deploy to Cloudflare"/></a>
-
-A starter template for building AI-powered chat agents using Cloudflare's Agent platform, powered by [`agents`](https://www.npmjs.com/package/agents). This project provides a foundation for creating interactive chat experiences with AI, complete with a modern UI and tool integration capabilities.
-
-## Features
-
-- 💬 Interactive chat interface with AI
-- 🛠️ Built-in tool system with human-in-the-loop confirmation
-- 📅 Advanced task scheduling (one-time, delayed, and recurring via cron)
-- 🌓 Dark/Light theme support
-- ⚡️ Real-time streaming responses
-- 🔄 State management and chat history
-- 🎨 Modern, responsive UI
-
-## Prerequisites
-
-- Cloudflare account
-- OpenAI API key
+Voice assistant with persistent memory powered by [Supermemory](https://supermemory.ai) and [Pipecat](https://pipecat.ai).
 
 ## Quick Start
 
-1. Create a new project:
-
 ```bash
-npx create-cloudflare@latest --template cloudflare/agents-starter
+bun install && cd backend && pip install -r requirements.txt
 ```
 
-2. Install dependencies:
-
 ```bash
-npm install
-```
-
-3. Set up your environment:
-
-Create a `.dev.vars` file:
-
-```env
-OPENAI_API_KEY=your_openai_api_key
+# backend/.env
+OPENAI_API_KEY=sk-...
+SUPERMEMORY_API_KEY=sm-...
 ```
 
-4. Run locally:
-
 ```bash
-npm start
+bun run start:backend  # Terminal 1
+bun run dev            # Terminal 2
 ```
 
-5. Deploy:
+## Pipecat Memory Integration
 
-```bash
-npm run deploy
-```
+Add persistent memory to your Pipecat voice AI agent. Remember user preferences, past conversations, and context across sessions.
 
-## Project Structure
+Supermemory integrates with Pipecat, providing long-term memory capabilities for voice AI agents. Your Pipecat applications will remember past conversations and provide personalized responses based on user history.
 
-```
-├── src/
-│   ├── app.tsx        # Chat UI implementation
-│   ├── server.ts      # Chat agent logic
-│   ├── tools.ts       # Tool definitions
-│   ├── utils.ts       # Helper functions
-│   └── styles.css     # UI styling
-```
+### Installation
 
-## Customization Guide
-
-### Adding New Tools
-
-Add new tools in `tools.ts` using the tool builder:
-
-```ts
-// Example of a tool that requires confirmation
-const searchDatabase = tool({
-  description: "Search the database for user records",
-  parameters: z.object({
-    query: z.string(),
-    limit: z.number().optional(),
-  }),
-  // No execute function = requires confirmation
-});
-
-// Example of an auto-executing tool
-const getCurrentTime = tool({
-  description: "Get current server time",
-  parameters: z.object({}),
-  execute: async () => new Date().toISOString(),
-});
-
-// Scheduling tool implementation
-const scheduleTask = tool({
-  description:
-    "schedule a task to be executed at a later time. 'when' can be a date, a delay in seconds, or a cron pattern.",
-  parameters: z.object({
-    type: z.enum(["scheduled", "delayed", "cron"]),
-    when: z.union([z.number(), z.string()]),
-    payload: z.string(),
-  }),
-  execute: async ({ type, when, payload }) => {
-    // ... see the implementation in tools.ts
-  },
-});
-```
-
-To handle tool confirmations, add execution functions to the `executions` object:
-
-```typescript
-export const executions = {
-  searchDatabase: async ({
-    query,
-    limit,
-  }: {
-    query: string;
-    limit?: number;
-  }) => {
-    // Implementation for when the tool is confirmed
-    const results = await db.search(query, limit);
-    return results;
-  },
-  // Add more execution handlers for other tools that require confirmation
-};
+```bash
+pip install supermemory-pipecat
 ```
 
-Tools can be configured in two ways:
-
-1. With an `execute` function for automatic execution
-2. Without an `execute` function, requiring confirmation and using the `executions` object to handle the confirmed action. NOTE: The keys in `executions` should match `toolsRequiringConfirmation` in `app.tsx`.
-
-### Use a different AI model provider
+### Configuration
 
-The starting [`server.ts`](https://github.com/cloudflare/agents-starter/blob/main/src/server.ts) implementation uses the [`ai-sdk`](https://sdk.vercel.ai/docs/introduction) and the [OpenAI provider](https://sdk.vercel.ai/providers/ai-sdk-providers/openai), but you can use any AI model provider by:
+```python
+from supermemory_pipecat import SupermemoryPipecatService, InputParams
 
-1. Installing an alternative AI provider for the `ai-sdk`, such as the [`workers-ai-provider`](https://sdk.vercel.ai/providers/community-providers/cloudflare-workers-ai) or [`anthropic`](https://sdk.vercel.ai/providers/ai-sdk-providers/anthropic) provider:
-2. Replacing the AI SDK with the [OpenAI SDK](https://github.com/openai/openai-node)
-3. Using the Cloudflare [Workers AI + AI Gateway](https://developers.cloudflare.com/ai-gateway/providers/workersai/#workers-binding) binding API directly
-
-For example, to use the [`workers-ai-provider`](https://sdk.vercel.ai/providers/community-providers/cloudflare-workers-ai), install the package:
-
-```sh
-npm install workers-ai-provider
+memory = SupermemoryPipecatService(
+    api_key=os.getenv("SUPERMEMORY_API_KEY"),
+    user_id="user_123",
+    params=InputParams(mode="full", search_limit=10),
+)
 ```
 
-Add an `ai` binding to `wrangler.jsonc`:
-
-```jsonc
-// rest of file
-  "ai": {
-    "binding": "AI"
-  }
-// rest of file
+**Modes:** `profile` (user facts) | `query` (search) | `full` (both)
+
+### Pipeline Integration
+
+```python
+pipeline = Pipeline([
+    transport.input(),
+    stt,
+    context_aggregator.user(),
+    memory,  # Supermemory
+    llm,
+    tts,
+    transport.output(),
+    context_aggregator.assistant(),
+])
 ```
 
-Replace the `@ai-sdk/openai` import and usage with the `workers-ai-provider`:
-
-```diff
-// server.ts
-// Change the imports
-- import { openai } from "@ai-sdk/openai";
-+ import { createWorkersAI } from 'workers-ai-provider';
-
-// Create a Workers AI instance
-+ const workersai = createWorkersAI({ binding: env.AI });
-
-// Use it when calling the streamText method (or other methods)
-// from the ai-sdk
-- const model = openai("gpt-5");
-+ const model = workersai("@cf/deepseek-ai/deepseek-r1-distill-qwen-32b")
-```
-
-Commit your changes and then run the `agents-starter` as per the rest of this README.
-
-### Modifying the UI
-
-The chat interface is built with React and can be customized in `app.tsx`:
-
-- Modify the theme colors in `styles.css`
-- Add new UI components in the chat container
-- Customize message rendering and tool confirmation dialogs
-- Add new controls to the header
-
-### Example Use Cases
-
-1. **Customer Support Agent**
-   - Add tools for:
-     - Ticket creation/lookup
-     - Order status checking
-     - Product recommendations
-     - FAQ database search
-
-2. **Development Assistant**
-   - Integrate tools for:
-     - Code linting
-     - Git operations
-     - Documentation search
-     - Dependency checking
-
-3. **Data Analysis Assistant**
-   - Build tools for:
-     - Database querying
-     - Data visualization
-     - Statistical analysis
-     - Report generation
-
-4. **Personal Productivity Assistant**
-   - Implement tools for:
-     - Task scheduling with flexible timing options
-     - One-time, delayed, and recurring task management
-     - Task tracking with reminders
-     - Email drafting
-     - Note taking
-
-5. **Scheduling Assistant**
-   - Build tools for:
-     - One-time event scheduling using specific dates
-     - Delayed task execution (e.g., "remind me in 30 minutes")
-     - Recurring tasks using cron patterns
-     - Task payload management
-     - Flexible scheduling patterns
-
-Each use case can be implemented by:
-
-1. Adding relevant tools in `tools.ts`
-2. Customizing the UI for specific interactions
-3. Extending the agent's capabilities in `server.ts`
-4. Adding any necessary external API integrations
-
-## Learn More
-
-- [`agents`](https://github.com/cloudflare/agents/blob/main/packages/agents/README.md)
-- [Cloudflare Agents Documentation](https://developers.cloudflare.com/agents/)
-- [Cloudflare Workers Documentation](https://developers.cloudflare.com/workers/)
-
-## License
+## Links
 
-MIT
+- [Supermemory Docs](https://supermemory.ai/docs)
+- [Pipecat Docs](https://docs.pipecat.ai)