supermemory/apps/docs/memory-api/sdks/openai-plugins.mdx

---
title: "OpenAI SDK Plugins"
description: "Memory tools for OpenAI function calling with Supermemory integration"
---

Add memory capabilities to the official OpenAI SDKs using Supermemory's function calling tools. These plugins provide seamless integration with OpenAI's chat completions and function calling features.

<CardGroup>
<Card title="Supermemory tools on npm" icon="npm" href="https://www.npmjs.com/package/@supermemory/tools">
    Check out the NPM page for more details
</Card>
<Card title="Supermemory AI SDK" icon="python" href="https://pypi.org/project/supermemory-openai-sdk/">
    Check out the PyPI page for more details
</Card>
</CardGroup>

## Installation

<CodeGroup>

```bash Python
# Using uv (recommended)
uv add supermemory-openai-sdk

# Or with pip
pip install supermemory-openai-sdk
```

```bash JavaScript/TypeScript
npm install @supermemory/tools
```

</CodeGroup>

## Quick Start

<CodeGroup>

```python Python SDK
import asyncio
import openai
from supermemory_openai import SupermemoryTools, execute_memory_tool_calls

async def main():
    # Initialize OpenAI client
    client = openai.AsyncOpenAI(api_key="your-openai-api-key")

    # Initialize Supermemory tools
    tools = SupermemoryTools(
        api_key="your-supermemory-api-key",
        config={"project_id": "my-project"}
    )

    # Chat with memory tools
    response = await client.chat.completions.create(
        model="gpt-5",
        messages=[
            {
                "role": "system",
                "content": "You are a helpful assistant with access to user memories."
            },
            {
                "role": "user",
                "content": "Remember that I prefer tea over coffee"
            }
        ],
        tools=tools.get_tool_definitions()
    )

    # Handle tool calls if present
    if response.choices[0].message.tool_calls:
        tool_results = await execute_memory_tool_calls(
            api_key="your-supermemory-api-key",
            tool_calls=response.choices[0].message.tool_calls,
            config={"project_id": "my-project"}
        )
        print("Tool results:", tool_results)

    print(response.choices[0].message.content)

asyncio.run(main())
```

```typescript JavaScript/TypeScript SDK
import { supermemoryTools, getToolDefinitions, createToolCallExecutor } from "@supermemory/tools/openai"
import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY!,
})

// Get tool definitions for OpenAI
const toolDefinitions = getToolDefinitions()

// Create tool executor
const executeToolCall = createToolCallExecutor(process.env.SUPERMEMORY_API_KEY!, {
  projectId: "your-project-id",
})

// Use with OpenAI Chat Completions
const completion = await client.chat.completions.create({
  model: "gpt-5",
  messages: [
    {
      role: "user",
      content: "What do you remember about my preferences?",
    },
  ],
  tools: toolDefinitions,
})

// Execute tool calls if any
if (completion.choices[0]?.message.tool_calls) {
  for (const toolCall of completion.choices[0].message.tool_calls) {
    const result = await executeToolCall(toolCall)
    console.log(result)
  }
}
```

</CodeGroup>

## Configuration

### Memory Tools Configuration

<CodeGroup>

```python Python Configuration
from supermemory_openai import SupermemoryTools

tools = SupermemoryTools(
    api_key="your-supermemory-api-key",
    config={
        "project_id": "my-project",  # or use container_tags
        "base_url": "https://custom-endpoint.com",  # optional
    }
)
```

```typescript JavaScript Configuration
import { supermemoryTools } from "@supermemory/tools/openai"

const tools = supermemoryTools(process.env.SUPERMEMORY_API_KEY!, {
  containerTags: ["your-user-id"],
  baseUrl: "https://custom-endpoint.com", // optional
})
```

</CodeGroup>

## Available Tools

### Search Memories

Search through user memories using semantic search:

<CodeGroup>

```python Python
# Search memories
result = await tools.search_memories(
    information_to_get="user preferences",
    limit=10,
    include_full_docs=True
)
print(f"Found {len(result.memories)} memories")
```

```typescript JavaScript
// Search memories
const searchResult = await tools.searchMemories({
  informationToGet: "user preferences",
  limit: 10,
})
console.log(`Found ${searchResult.memories.length} memories`)
```

</CodeGroup>

### Add Memory

Store new information in memory:

<CodeGroup>

```python Python
# Add memory
result = await tools.add_memory(
    memory="User prefers tea over coffee"
)
print(f"Added memory with ID: {result.memory.id}")
```

```typescript JavaScript
// Add memory
const addResult = await tools.addMemory({
  memory: "User prefers dark roast coffee",
})
console.log(`Added memory with ID: ${addResult.memory.id}`)
```

</CodeGroup>

### Fetch Memory

Retrieve specific memory by ID:

<CodeGroup>

```python Python
# Fetch specific memory
result = await tools.fetch_memory(
    memory_id="memory-id-here"
)
print(f"Memory content: {result.memory.content}")
```

```typescript JavaScript
// Fetch specific memory
const fetchResult = await tools.fetchMemory({
  memoryId: "memory-id-here"
})
console.log(`Memory content: ${fetchResult.memory.content}`)
```

</CodeGroup>

## Individual Tools

Use tools separately for more granular control:

<CodeGroup>

```python Python Individual Tools
from supermemory_openai import (
    create_search_memories_tool,
    create_add_memory_tool,
    create_fetch_memory_tool
)

search_tool = create_search_memories_tool("your-api-key")
add_tool = create_add_memory_tool("your-api-key")
fetch_tool = create_fetch_memory_tool("your-api-key")

# Use individual tools in OpenAI function calling
tools_list = [search_tool, add_tool, fetch_tool]
```

```typescript JavaScript Individual Tools
import {
  createSearchMemoriesTool,
  createAddMemoryTool,
  createFetchMemoryTool
} from "@supermemory/tools/openai"

const searchTool = createSearchMemoriesTool(process.env.SUPERMEMORY_API_KEY!)
const addTool = createAddMemoryTool(process.env.SUPERMEMORY_API_KEY!)
const fetchTool = createFetchMemoryTool(process.env.SUPERMEMORY_API_KEY!)

// Use individual tools
const toolDefinitions = [searchTool, addTool, fetchTool]
```

</CodeGroup>

## Complete Chat Example

Here's a complete example showing a multi-turn conversation with memory:

<CodeGroup>

```python Complete Python Example
import asyncio
import openai
from supermemory_openai import SupermemoryTools, execute_memory_tool_calls

async def chat_with_memory():
    client = openai.AsyncOpenAI()
    tools = SupermemoryTools(
        api_key="your-supermemory-api-key",
        config={"project_id": "chat-example"}
    )

    messages = [
        {
            "role": "system",
            "content": """You are a helpful assistant with memory capabilities.
            When users share personal information, remember it using addMemory.
            When they ask questions, search your memories to provide personalized responses."""
        }
    ]

    while True:
        user_input = input("You: ")
        if user_input.lower() == 'quit':
            break

        messages.append({"role": "user", "content": user_input})

        # Get AI response with tools
        response = await client.chat.completions.create(
            model="gpt-5",
            messages=messages,
            tools=tools.get_tool_definitions()
        )

        # Handle tool calls
        if response.choices[0].message.tool_calls:
            messages.append(response.choices[0].message)

            tool_results = await execute_memory_tool_calls(
                api_key="your-supermemory-api-key",
                tool_calls=response.choices[0].message.tool_calls,
                config={"project_id": "chat-example"}
            )

            messages.extend(tool_results)

            # Get final response after tool execution
            final_response = await client.chat.completions.create(
                model="gpt-5",
                messages=messages
            )

            assistant_message = final_response.choices[0].message.content
        else:
            assistant_message = response.choices[0].message.content
            messages.append({"role": "assistant", "content": assistant_message})

        print(f"Assistant: {assistant_message}")

# Run the chat
asyncio.run(chat_with_memory())
```

```typescript Complete JavaScript Example
import OpenAI from "openai"
import { getToolDefinitions, createToolCallExecutor } from "@supermemory/tools/openai"
import readline from 'readline'

const client = new OpenAI()
const executeToolCall = createToolCallExecutor(process.env.SUPERMEMORY_API_KEY!, {
  projectId: "chat-example",
})

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
})

async function chatWithMemory() {
  const messages: OpenAI.Chat.ChatCompletionMessageParam[] = [
    {
      role: "system",
      content: `You are a helpful assistant with memory capabilities.
      When users share personal information, remember it using addMemory.
      When they ask questions, search your memories to provide personalized responses.`
    }
  ]

  const askQuestion = () => {
    rl.question("You: ", async (userInput) => {
      if (userInput.toLowerCase() === 'quit') {
        rl.close()
        return
      }

      messages.push({ role: "user", content: userInput })

      // Get AI response with tools
      const response = await client.chat.completions.create({
        model: "gpt-5",
        messages,
        tools: getToolDefinitions(),
      })

      const choice = response.choices[0]
      if (choice?.message.tool_calls) {
        messages.push(choice.message)

        // Execute tool calls
        for (const toolCall of choice.message.tool_calls) {
          const result = await executeToolCall(toolCall)
          messages.push({
            role: "tool",
            tool_call_id: toolCall.id,
            content: JSON.stringify(result),
          })
        }

        // Get final response after tool execution
        const finalResponse = await client.chat.completions.create({
          model: "gpt-5",
          messages,
        })

        const assistantMessage = finalResponse.choices[0]?.message.content || "No response"
        console.log(`Assistant: ${assistantMessage}`)
        messages.push({ role: "assistant", content: assistantMessage })
      } else {
        const assistantMessage = choice?.message.content || "No response"
        console.log(`Assistant: ${assistantMessage}`)
        messages.push({ role: "assistant", content: assistantMessage })
      }

      askQuestion()
    })
  }

  console.log("Chat with memory started. Type 'quit' to exit.")
  askQuestion()
}

chatWithMemory()
```

</CodeGroup>

## Error Handling

Handle errors gracefully in your applications:

<CodeGroup>

```python Python Error Handling
from supermemory_openai import SupermemoryTools
import openai

async def safe_chat():
    try:
        client = openai.AsyncOpenAI()
        tools = SupermemoryTools(api_key="your-api-key")

        response = await client.chat.completions.create(
            model="gpt-5",
            messages=[{"role": "user", "content": "Hello"}],
            tools=tools.get_tool_definitions()
        )

    except openai.APIError as e:
        print(f"OpenAI API error: {e}")
    except Exception as e:
        print(f"Unexpected error: {e}")
```

```typescript JavaScript Error Handling
import OpenAI from "openai"
import { getToolDefinitions } from "@supermemory/tools/openai"

async function safeChat() {
  try {
    const client = new OpenAI()

    const response = await client.chat.completions.create({
      model: "gpt-5",
      messages: [{ role: "user", content: "Hello" }],
      tools: getToolDefinitions(),
    })

  } catch (error) {
    if (error instanceof OpenAI.APIError) {
      console.error("OpenAI API error:", error.message)
    } else {
      console.error("Unexpected error:", error)
    }
  }
}
```

</CodeGroup>

## API Reference

### Python SDK

#### `SupermemoryTools`

**Constructor**
```python
SupermemoryTools(
    api_key: str,
    config: Optional[SupermemoryToolsConfig] = None
)
```

**Methods**
- `get_tool_definitions()` - Get OpenAI function definitions
- `search_memories(information_to_get, limit, include_full_docs)` - Search user memories
- `add_memory(memory)` - Add new memory
- `fetch_memory(memory_id)` - Fetch specific memory by ID
- `execute_tool_call(tool_call)` - Execute individual tool call

#### `execute_memory_tool_calls`

```python
execute_memory_tool_calls(
    api_key: str,
    tool_calls: List[ToolCall],
    config: Optional[SupermemoryToolsConfig] = None
) -> List[dict]
```

### JavaScript SDK

#### `supermemoryTools`

```typescript
supermemoryTools(
  apiKey: string,
  config?: { projectId?: string; baseUrl?: string }
)
```

#### `createToolCallExecutor`

```typescript
createToolCallExecutor(
  apiKey: string,
  config?: { projectId?: string; baseUrl?: string }
) -> (toolCall: OpenAI.Chat.ChatCompletionMessageToolCall) => Promise<any>
```

## Environment Variables

Set these environment variables:

```bash
SUPERMEMORY_API_KEY=your_supermemory_key
OPENAI_API_KEY=your_openai_key
SUPERMEMORY_BASE_URL=https://custom-endpoint.com  # optional
```

## Development

### Python Setup

```bash
# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Setup project
git clone <repository-url>
cd packages/openai-sdk-python
uv sync --dev

# Run tests
uv run pytest

# Type checking
uv run mypy src/supermemory_openai

# Formatting
uv run black src/ tests/
uv run isort src/ tests/
```

### JavaScript Setup

```bash
# Install dependencies
npm install

# Run tests
npm test

# Type checking
npm run type-check

# Linting
npm run lint
```

## Next Steps

<CardGroup cols={2}>
  <Card title="AI SDK Integration" icon="triangle" href="/ai-sdk/overview">
    Use with Vercel AI SDK for streamlined development
  </Card>

  <Card title="Memory API" icon="database" href="/memory-api/overview">
    Direct API access for advanced memory management
  </Card>
</CardGroup>