### Get Repository Details using Python SDK

Source: https://docs.relace.ai/api-reference/repos/get

This example illustrates how to retrieve repository details using the Relace AI Python SDK. It involves initializing the client with an API key and then using the `repo.get` method with the repository ID.

```python
from relace import Relace

client = Relace(api_key = "YOUR_API_KEY")

repo_id = "123e4567-e89b-12d3-a456-426614174000"
data = client.repo.get(repo_id)
print(data)
```

--------------------------------

### Handle SSE Event Streams

Source: https://docs.relace.ai/api-reference/agents/analysis-agent

Example of the Server-Sent Events (SSE) format used to stream real-time updates from the agent execution, such as the 'started' event.

```text
event: started
data: {"prompt_id": "prompt_123e4567-e89b-12d3-a456-426614174000"}

event: agent
```

--------------------------------

### Analyze Agent Tool Usage and Response Stream (SSE)

Source: https://docs.relace.ai/api-reference/agents/fast-agentic-search

This example shows a Server-Sent Events (SSE) stream representing the output from a Relace AI agent. It includes various event types like 'started', 'agent' (with content and reasoning), and 'tool' (detailing commands executed and their results). This stream allows for real-time monitoring of the agent's execution flow and decision-making process.

```text
event: started
data: {"prompt_id":"123e4567-e89b-12d3-a456-426614174000"}

event: agent
data: {"name":"relace-search","content":"I'll explore the codebase to understand where global styles and UI components are defined. Let me first get an overview of the project structure to identify relevant directories and files.\n\n"}

event: tool
data: {"name":"view_directory","path":"/repo"}

event: tool
data: {"name":"bash","command":"find /repo -type f -name \"*.css\" -o -name \"*.scss\" -o -name \"*.sass\" -o -name \"*.less\" | head -20"}

event: tool
data: {"name":"bash","command":"find /repo -type f -name \"*component*\" -o -name \"*ui*\" -o -name \"*style*\" | head -20"}

event: tool
data: {"name":"bash","command":"grep -r \"global.*style\|style.*global\" /repo --include=\"*.js\" --include=\"*.ts\" --include=\"*.jsx\" --include=\"*.tsx\" | head -10"}

event: tool
data: {"name":"bash","command":"grep -r \"ThemeProvider\|GlobalStyle\|styled\." /repo --include=\"*.js\" --include=\"*.ts\" --include=\"*.jsx\" --include=\"*.tsx\" | head -10"}

event: agent
data: {"name":"relace-search","content":"Based on the initial exploration, I can see this appears to be a React project with a structured component system. Let me dive deeper into the key areas that would contain global styles and UI components.\n\n"}

event: tool
data: {"name":"view_directory","path":"/repo/src/components"}

event: tool
data: {"name":"view_file","path":"/repo/src/index.css"}

event: tool
data: {"name":"view_directory","path":"/repo/src/components/ui"}

event: tool
data: {"name":"view_file","path":"/repo/src/main.tsx"}

event: tool
data: {"name":"bash","command":"find /repo/src -name \"*.css\" -o -name \"*.scss\" -o -name \"*.sass\" | xargs ls -la"}

event: agent
```

--------------------------------

### POST /v1/repo

Source: https://docs.relace.ai/docs/data-analysis/quickstart

Creates a new repository from a specified template source to serve as the foundation for your project.

```APIDOC
## POST /v1/repo

### Description
Initializes a new repository based on a provided git template URL.

### Method
POST

### Endpoint
https://api.relace.run/v1/repo

### Request Body
- **source** (object) - Required - Contains repository source details
  - **type** (string) - Required - Source type (e.g., "git")
  - **url** (string) - Required - Repository URL
  - **branch** (string) - Required - Target branch

### Request Example
{
  "source": {
    "type": "git",
    "url": "https://github.com/squack-io/tailwind-vite-base",
    "branch": "main"
  }
}

### Response
#### Success Response (200)
- **repo_id** (string) - The unique identifier for the created repository

#### Response Example
{
  "repo_id": "abc-123-xyz"
}
```

--------------------------------

### Initialize and Clone Relace Repo in Sandbox

Source: https://docs.relace.ai/docs/repos/sandbox

Demonstrates how to provision a sandbox environment, configure git credentials, and clone a Relace repository using an API key. The examples cover both Python with Modal and TypeScript with E2B.

```python
import modal

app = modal.App.lookup("Sandbox-Example", create_if_missing=True)

repo_id = "REPO_ID"
relace_api_key = "RELACE_API_TOKEN"

# Configure the sandbox image with git
image = (
    modal.Image.debian_slim(python_version="3.13")
    .apt_install("git", "curl")
    .run_commands(
        "git config --global user.name 'Relace'",
        "git config --global user.email 'noreply@relace.ai'",
    )
    .workdir("/repo")
)

# Create the sandbox
sandbox = modal.Sandbox.create(image=image, app=app)

clone_url = f"https://token:{relace_api_key}@api.relace.run/v1/repo/{repo_id}.git"

# Run git clone inside the sandbox
clone_proc = sandbox.exec("git", "clone", clone_url, ".")
if clone_proc.wait() != 0:
    print("Clone failed:", clone_proc.stderr.read())
    raise Exception("Clone failed")

# Example command to list files in the cloned repo
ls_proc = sandbox.exec("ls", "-la")
print(ls_proc.stdout.read())

sandbox.terminate()
```

```typescript
import { Sandbox } from "@e2b/code-interpreter";

// Create the sandbox
const sandbox = await Sandbox.create();

// Configure git
await sandbox.commands.run(`git config --global user.name 'Relace'`);
await sandbox.commands.run(`git config --global user.email 'noreply@relace.ai'`);

const token = "RELACE_API_KEY";
const repoId = "REPO_ID";
const repoDir = "./repo";

// Clone Relace repo inside the sandbox
const cloneResult = await sandbox.commands.run(
    `git clone https://token:${token}@api.relace.run/v1/repo/${repoId}.git ${repoDir}`
);

// Check for clone failure
if (cloneResult.exitCode !== 0) {
    console.error("Clone failed:", cloneResult.stderr);
    throw new Error(`Failed to clone repository: ${cloneResult.stderr}`);
}

// Example command to list files in the cloned repo
const files = await sandbox.commands.run(`ls -la ${repoDir}`);
console.log(files.stdout);
```

--------------------------------

### List Repositories (cURL)

Source: https://docs.relace.ai/api-reference/repos/list

Example of fetching a paginated list of repositories using cURL. This demonstrates a direct API call with an authorization header and query parameters for pagination.

```bash
curl -X GET "https://api.relace.run/v1/repo?page_size=10" \
    -H "Authorization: Bearer YOUR_API_KEY"
```

--------------------------------

### POST /repo

Source: https://docs.relace.ai/docs/fast-agentic-search/quickstart

Creates a new repository in Relace, either from a Git source or from uploaded files. This is the first step to enabling Fast Agentic Search.

```APIDOC
## POST /repo

### Description
Creates a new repository in Relace, allowing you to transfer your source code for analysis and search.

### Method
POST

### Endpoint
/repo

### Parameters
#### Request Body
- **source** (object) - Required - The source of the repository.
  - **type** (string) - Required - The type of source ('git' or 'files').
  - **url** (string) - Optional (if type is 'git') - The URL of the Git repository.
  - **branch** (string) - Optional (if type is 'git') - The branch to clone from.
  - **files** (array) - Optional (if type is 'files') - An array of file objects.
    - **filename** (string) - Required - The name of the file.
    - **content** (string) - Required - The content of the file.
- **auto_index** (boolean) - Optional - Whether to automatically index the repository for semantic search. Defaults to false.
- **metadata** (object) - Optional - Custom metadata to associate with the repository.

### Request Example
```json
{
  "source": {
    "type": "git",
    "url": "https://github.com/relace-ai/vite-template",
    "branch": "main"
  },
  "auto_index": true,
  "metadata": {}
}
```

### Response
#### Success Response (200)
- **repo_id** (string) - The unique identifier for the created repository.

#### Response Example
```json
{
  "repo_id": "repo_12345"
}
```
```

--------------------------------

### Create Repository with Relace SDK

Source: https://docs.relace.ai/docs/fast-agentic-search/quickstart

Initializes a repository in Relace using either a Git URL or direct file content. Requires an API key and supports auto-indexing for semantic search capabilities.

```typescript
import { Relace } from '@relace-ai/relace';

const client = new Relace({ apiKey: 'YOUR_API_KEY' });

const repo = await client.repo.create({
  source: {
    type: 'git',
    url: 'https://github.com/relace-ai/vite-template',
    branch: 'main',
  },
  auto_index: true,
  metadata: {},
});

console.log(`Repository created with ID: ${repo.repo_id}`);
```

```typescript
import { Relace } from '@relace-ai/relace';

const client = new Relace({ apiKey: 'YOUR_API_KEY' });

const repo = await client.repo.create({
  source: {
    type: 'files',
    files: [
      {
        filename: 'src/main.py',
        content: "def main():\n    print('Hello from my existing project!')\n\nif __name__ == '__main__':\n    main()",
      }
    ],
  },
  auto_index: true,
  metadata: {},
});

console.log(`Repository created with ID: ${repo.repo_id}`);
```

--------------------------------

### Initiate Agent Search with Relace TypeScript SDK

Source: https://docs.relace.ai/api-reference/agents/fast-agentic-search

This TypeScript code example shows how to use the Relace SDK to search within a repository. It initializes the Relace client with an API key and then calls the `repo.search` method with a repository ID and a search query. The results are streamed as events, which are then logged to the console.

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const repoId = "123e4567-e89b-12d3-a456-426614174000";
const results = client.repo.search(repoId, {
  query: "Where in the project are global styles and UI components defined?",
});

for await (const event of results) {
  console.log(event);
}
```

--------------------------------

### Configure VS Code MCP Server

Source: https://docs.relace.ai/docs/fast-agentic-search/mcp-installation

Specific JSON configuration format required for the VS Code MCP user configuration file.

```json
{
  "servers": {
    "Relace": {
      "command": "uvx",
      "args": ["relace-mcp-server"],
      "env": {
        "RELACE_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}
```

--------------------------------

### Get Repository Details using TypeScript SDK

Source: https://docs.relace.ai/api-reference/repos/get

This code snippet shows how to fetch repository details using the Relace AI TypeScript SDK. It initializes the client with an API key and calls the `get` method with the repository ID.

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const repoId = "123e4567-e89b-12d3-a456-426614174000";
const data = await client.repo.get(repoId);
console.log(data);
```

--------------------------------

### POST /v1/code/embed

Source: https://docs.relace.ai/docs/embeddings/quickstart

Generates vector embeddings for a list of input strings using the Relace embedding model.

```APIDOC
## POST /v1/code/embed

### Description
Sends code snippets or text to the Relace embeddings endpoint to retrieve high-dimensional vector representations.

### Method
POST

### Endpoint
https://embeddings.endpoint.relace.run/v1/code/embed

### Parameters
#### Request Body
- **model** (string) - Required - The model identifier, e.g., "relace-embed-v1"
- **input** (array) - Required - A list of strings to be embedded
- **output_dtype** (string) - Optional - The data type of the output, e.g., "float" or "binary"

### Request Example
{
  "model": "relace-embed-v1",
  "input": ["def add(a, b): return a + b", "class User: pass"]
}

### Response
#### Success Response (200)
- **results** (array) - List of objects containing index and embedding vector
- **usage** (object) - Token usage statistics

#### Response Example
{
  "results": [
    { "index": 0, "embedding": [0.123, 0.456, 0.789] },
    { "index": 1, "embedding": [0.234, 0.567, 0.89] }
  ],
  "usage": {
    "total_tokens": 8
  }
}
```

--------------------------------

### Store Embeddings in Pinecone (TypeScript)

Source: https://docs.relace.ai/docs/embeddings/quickstart

An example of how to store generated embeddings in Pinecone, a popular vector database. This involves initializing the Pinecone client, preparing vectors with IDs and metadata, and then upserting them to an index.

```typescript
import { Pinecone } from '@pinecone-database/pinecone';

// Initialize Pinecone (example)
const pinecone = new Pinecone({ apiKey: "[PINECONE_API_KEY]" });
const index = pinecone.index("my-embeddings-index");

// Prepare vectors for upsert
const vectors = embeddings.results.map(r => ({
  id: `code-${r.index}`,
  values: r.embedding,
  metadata: { source: inputs[r.index] }
}));

// Upsert to Pinecone
await index.upsert(vectors);
```

--------------------------------

### Get Repository Details using cURL

Source: https://docs.relace.ai/api-reference/repos/get

This snippet demonstrates how to retrieve details for a specific repository using a cURL command. It requires the repository ID and an API key for authentication.

```bash
curl -X GET https://api.relace.run/v1/repo/123e4567-e89b-12d3-a456-426614174000 \
    -H "Authorization: Bearer YOUR_API_KEY"
```

--------------------------------

### Create Relace Repository from Template

Source: https://docs.relace.ai/docs/data-analysis/quickstart

Initializes a new Relace repository using a public template. This process requires an API key and establishes the base environment for subsequent data analysis tasks.

```python
import requests

# Create a new repository from the base template
url = "https://api.relace.run/v1/repo"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

data = {
    "source": {
        "type": "git",
        "url": "https://github.com/squack-io/tailwind-vite-base",
        "branch": "main"
    }
}

response = requests.post(url, headers=headers, json=data)
repo = response.json()
repo_id = repo['repo_id']

print(f"Repository created with ID: {repo_id}")
```

--------------------------------

### List Repositories (Python SDK)

Source: https://docs.relace.ai/api-reference/repos/list

Example of fetching a paginated list of repositories using the Relace AI Python SDK. This provides a Pythonic way to interact with the API, handling request formatting and response parsing.

```python
from relace import Relace

client = Relace(api_key="YOUR_API_KEY")

data = client.repo.list(page_size=10)
print(data)
```

--------------------------------

### List Repositories (TypeScript SDK)

Source: https://docs.relace.ai/api-reference/repos/list

Example of fetching a paginated list of repositories using the Relace AI TypeScript SDK. This method abstracts the HTTP request and provides a type-safe interface for interacting with the API.

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const data = await client.repo.list({
    page_size: 10
});
console.log(data);
```

--------------------------------

### Codebase Exploration Commands

Source: https://docs.relace.ai/docs/fast-agentic-search/quickstart

Common bash commands used within the agent environment to locate specific architectural patterns such as global styles and theme providers.

```bash
find /repo/src -name "*.css" -o -name "*.scss" | xargs ls -la
find /repo -name "*theme*" -type f
grep -r "ThemeProvider" /repo/src --include="*.tsx"
```

--------------------------------

### Prepare Code Snippets for Embedding (TypeScript)

Source: https://docs.relace.ai/docs/embeddings/quickstart

Prepare an array of code snippets or text strings that you want to convert into vector embeddings. This array will be sent to the Relace AI embeddings endpoint.

```typescript
const inputs = [
  "def add(a, b): return a + b",
  "class User: pass",
  // ... more code or text
];
```

--------------------------------

### POST /repos

Source: https://docs.relace.ai/api-reference/repos/create

Creates a new repository by initializing it from files, a GitHub URL, or an existing Relace repository.

```APIDOC
## POST /repos

### Description
Create a new repository from various sources. This endpoint allows for flexible initialization including file uploads, git cloning, or cloning existing Relace repositories.

### Method
POST

### Endpoint
/repos

### Parameters
#### Request Body
- **source** (object) - Optional - Configuration for initializing the repo.
  - **type** (string) - Required - The source type: "files", "git", or "relace".
  - **files** (array) - Required (if type=files) - Array of objects with "filename" and "content".
  - **url** (string) - Required (if type=git) - Git repository URL.
  - **branch** (string) - Optional (if type=git) - Specific branch to clone.
  - **shallow** (boolean) - Optional - Whether to perform a shallow clone (default: true).
  - **repo_id** (string) - Required (if type=relace) - ID of the template repository.
- **metadata** (object) - Optional - Custom key-value pairs for repository metadata.
- **auto_index** (boolean) - Optional - Enable automatic code indexing (default: false).

### Request Example
{
  "source": {
    "type": "git",
    "url": "https://github.com/user/repo.git",
    "branch": "main"
  },
  "auto_index": true
}

### Response
#### Success Response (200)
- **id** (string) - The unique identifier of the created repository.
- **status** (string) - Current status of the repository creation process.

#### Response Example
{
  "id": "repo_12345",
  "status": "created"
}
```

--------------------------------

### Add Relace MCP to Claude Code

Source: https://docs.relace.ai/docs/fast-agentic-search/mcp-installation

Command-line instruction to add the Relace MCP server to the Claude Code environment.

```bash
claude mcp add Relace --scope user --env RELACE_API_KEY=YOUR_API_KEY_HERE -- uvx relace-mcp-server
```

--------------------------------

### Create a new repository

Source: https://docs.relace.ai/api-reference/repos/create

Initializes a new repository by providing a source object containing file contents and repository metadata. The operation returns a unique repository identifier and the current commit hash.

```bash
curl -X POST https://api.relace.run/v1/repo \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
    -d '{
    "source": {
      "type": "files",
      "files": [
        {
          "filename": "src/search.ts",
          "content": "function findItem(array: Item[], targetId: string): Item | undefined {\n  for (let i = 0; i < array.length; i++) {\n    const item = array[i];\n    if (item.id === targetId) {\n      return item;\n    }\n  }\n  return undefined;\n}"
        },
        {
          "filename": "src/types.ts",
          "content": "interface Item {\n  id: string;\n  value: string;\n  metadata?: Record<string, unknown>;\n}"
        }
      ]
    },
    "metadata": {
      "name": "my-codebase",
      "id": "my-internal-id"
    }
  }'
```

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const result = await client.repo.create({
    source: {
        type: "files",
        files: [
            {
                filename: "src/search.ts",
                content: "function findItem(array: Item[], targetId: string): Item | undefined {\n  for (let i = 0; i < array.length; i++) {\n    const item = array[i];\n    if (item.id === targetId) {\n      return item;\n    }\n  }\n  return undefined;\n}"
            },
            {
                filename: "src/types.ts",
                content: "interface Item {\n  id: string;\n  value: string;\n  metadata?: Record<string, unknown>;\n}"
            }
        ]
    },
    metadata: {
        name: "my-codebase",
        id: "my-internal-id"
    }
});

console.log(result);
```

```python
from relace import Relace

client = Relace(api_key="YOUR_API_KEY")

result = client.repo.create(
    source={
        "type": "files",
        "files": [
            {
                "filename": "src/search.ts",
                "content": (
                    "function findItem(array: Item[], targetId: string): Item | undefined {\n"
                    "  for (let i = 0; i < array.length; i++) {\n"
                    "    const item = array[i];\n"
                    "    if (item.id === targetId) {\n"
                    "      return item;\n"
                    "    }\n"
                    "  }\n"
                    "  return undefined;\n"
                    "}"
                ),
            },
            {
                "filename": "src/types.ts",
                "content": (
                    "interface Item {\n"
                    "  id: string;\n"
                    "  value: string;\n"
                    "  metadata?: Record<string, unknown>;\n"
                    "}"
                ),
            },
        ],
    },
    metadata={
        "name": "my-codebase",
        "id": "my-internal-id",
    },
)

print(result)
```

--------------------------------

### Get Repo Token Details using cURL, TypeScript, and Python

Source: https://docs.relace.ai/api-reference/repo_tokens/get

This snippet demonstrates how to retrieve details for a specific repository token. It includes examples for making the request via cURL, using the Relace TypeScript SDK, and the Relace Python SDK. The token string is required as a path parameter.

```bash
curl -X GET https://api.relace.run/v1/repo_token/rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12
```

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({apiKey: "YOUR_API_KEY"});

const token = "rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12";
const data = await client.repoToken.get(token);
console.log(data);
```

```python
from relace import Relace

client = Relace(api_key = "YOUR_API_KEY")

token = "rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12"
data = client.repo_token.get(token)
print(data)
```

--------------------------------

### Pull Latest Repository Changes

Source: https://docs.relace.ai/docs/repos/git-commands

Updates the local repository with the latest changes from the remote Relace repository. Essential for maintaining consistency before starting new work.

```typescript
import { Relace } from '@relace-ai/relace';

const client = new Relace({ apiKey: 'YOUR_API_KEY' });

// Pull the latest changes before continuing work
await client.git('./repo_path').pull();
```

```bash
git pull
```

--------------------------------

### Perform Agent Search with Relace Python SDK

Source: https://docs.relace.ai/api-reference/agents/fast-agentic-search

This Python code snippet demonstrates how to perform a repository search using the Relace SDK. It initializes the Relace client with an API key and then uses the `client.repo.search` method, providing the repository ID and the search query. The results are iterated over and printed to the console.

```python
from relace import Relace

client = Relace(api_key="YOUR_API_KEY")

repo_id = "123e4567-e89b-12d3-a456-426614174000"
results = client.repo.search(repo_id, query="Where in the project are global styles and UI components defined?")
for event in results:
    print(event)
```

--------------------------------

### Configure Relace MCP Server

Source: https://docs.relace.ai/docs/fast-agentic-search/mcp-installation

JSON configuration for integrating the Relace MCP server into compatible coding agents. Requires the uv package manager and a valid Relace API key.

```json
{
  "mcpServers": {
    "Relace": {
      "command": "uvx",
      "args": ["relace-mcp-server"],
      "env": {
        "RELACE_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}
```

--------------------------------

### Get Repo Token Details

Source: https://docs.relace.ai/api-reference/repo_tokens/get

Retrieve details about a specific repo token using its token string.

```APIDOC
## GET /v1/repo_token/{token}

### Description
Retrieve details about a specific repo token.

### Method
GET

### Endpoint
/v1/repo_token/{token}

### Parameters
#### Path Parameters
- **token** (string) - Required - The repo token string to retrieve details for

### Request Example
```bash cURL
curl -X GET https://api.relace.run/v1/repo_token/rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12
```

```typescript TypeScript SDK
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const token = "rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12";
const data = await client.repoToken.get(token);
console.log(data);
```

```python Python SDK
from relace import Relace

client = Relace(api_key = "YOUR_API_KEY")

token = "rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12"
data = client.repo_token.get(token)
print(data)
```

### Response
#### Success Response (200)
- **name** (string) - The name of the repo token
- **repo_ids** (array) - Array of repository UUIDs this token has access to

#### Response Example
```json Response
{
  "name": "my-token",
  "repo_ids": [
    "123e4567-e89b-12d3-a456-426614174000",
    "987fcdeb-51a2-43f7-b123-456789abcdef"
  ]
}
```
```

--------------------------------

### GET /v1/repo/{repo_id}

Source: https://docs.relace.ai/api-reference/repos/get

Retrieves comprehensive details about a specific repository by its unique identifier, including creation timestamps, metadata, and indexing configuration.

```APIDOC
## GET /v1/repo/{repo_id}

### Description
Retrieve details about a specific repository using its UUID. This endpoint returns the repository's configuration, metadata, and status.

### Method
GET

### Endpoint
https://api.relace.run/v1/repo/{repo_id}

### Parameters
#### Path Parameters
- **repo_id** (string) - Required - UUID of the repo to retrieve

### Request Example
```bash
curl -X GET https://api.relace.run/v1/repo/123e4567-e89b-12d3-a456-426614174000 \
  -H "Authorization: Bearer YOUR_API_KEY"
```

### Response
#### Success Response (200)
- **repo_id** (string) - Unique identifier for the repo
- **created_at** (string) - Time when the repo was originally created (ISO 8601 timestamp)
- **updated_at** (string) - Time when the repo was last modified (ISO 8601 timestamp)
- **metadata** (object) - Custom key/value pairs associated with the repo
- **auto_index** (boolean) - Whether the repo is configured to index source files for semantic retrieval

#### Response Example
{
  "repo_id": "123e4567-e89b-12d3-a456-426614174000",
  "created_at": "2024-01-15T10:30:00Z",
  "updated_at": "2024-01-15T11:15:00Z",
  "metadata": {
    "name": "my-project",
    "description": "A sample project"
  },
  "auto_index": true
}
```

--------------------------------

### Initialize OpenAI Client for Relace Search

Source: https://docs.relace.ai/docs/fast-agentic-search/agent

Demonstrates how to initialize an OpenAI client to interact with the Relace AI search endpoint. It requires an API key and specifies the base URL for the search service. The client is then used to create chat completions, specifying the model, user messages, and tool definitions.

```typescript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.RELACE_API_KEY,
  baseUrl: 'https://search.endpoint.relace.run/v1/search',
});

const response = await client.chat.completions.create({
  model: 'relace-search',
  messages: [{ role: 'user', content: 'Find authentication logic in /repo' }],
  tools: [
    /* tool definitions below */
  ],
});
```

--------------------------------

### GET /v1/repo/{repo_id}/clone

Source: https://docs.relace.ai/api-reference/repos/clone

Downloads all files and content from a specified repository.

```APIDOC
## GET /v1/repo/{repo_id}/clone

### Description
Downloads all files and content from a specified repository.

### Method
GET

### Endpoint
/v1/repo/{repo_id}/clone

### Parameters
#### Path Parameters
- **repo_id** (string) - Required - Repo ID

### Request Example
```bash cURL
curl -X GET https://api.relace.run/v1/repo/123e4567-e89b-12d3-a456-426614174000/clone \
  -H "Authorization: Bearer YOUR_API_KEY"
```

```typescript TypeScript SDK
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const repoId = "123e4567-e89b-12d3-a456-426614174000";
const data = await client.repo.clone(repoId);
console.log(data);
```

```python Python SDK
from relace import Relace

client = Relace(api_key = "YOUR_API_KEY")

repo_id = "123e4567-e89b-12d3-a456-426614174000"
data = client.repo.clone(repo_id)
print(data)
```

### Response
#### Success Response (200)
- **files** (array) - Array of all files in the repository with their complete content
  - **filename** (string) - Path to the file within the repo
  - **content** (string) - Full content of the file

#### Response Example
```json Response
{
  "files": [
    {
      "filename": "src/main.py",
      "content": "def main():\n    print('Hello World!')\n\nif __name__ == '__main__':\n    main()"
    },
    {
      "filename": "README.md",
      "content": "# My Project\n\nThis is a sample project."
    },
    {
      "filename": "requirements.txt",
      "content": "requests==2.28.1\nflask==2.2.2"
    }
  ]
}
```
```

--------------------------------

### Perform Semantic Search with User Query (TypeScript)

Source: https://docs.relace.ai/docs/embeddings/quickstart

Demonstrates how to perform a semantic search using a user query. The query is first embedded using the same Relace AI API, and then the resulting embedding is used to query a vector database like Pinecone for similar code snippets.

```typescript
// Embed the user query
const query = "How do I add two numbers?";
const queryData = {
  model: "relace-embed-v1",
  input: [query]
};

const queryResponse = await fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(queryData)
});

const queryResult = await queryResponse.json();
const queryEmbedding = queryResult.results[0].embedding;

// Query Pinecone for similar code
const results = await index.query({
  vector: queryEmbedding,
  topK: 5,
  includeMetadata: true
});

for (const match of results.matches) {
  console.log(`Score: ${match.score}, Source: ${match.metadata.source}`);
}
```

--------------------------------

### API Response Structure

Source: https://docs.relace.ai/api-reference/repos/retrieve

Example of the JSON response returned by the retrieval endpoint, containing the list of relevant files, their content, relevance scores, and repository metadata.

```json
{
  "results": [
    {
      "filename": "src/auth.py",
      "content": "def authenticate_user(username, password):\n    \"\"\"Authenticate user credentials against the database.\"\"\"\n    user = User.query.filter_by(username=username).first()\n    if user and bcrypt.check_password_hash(user.password_hash, password):\n        return user\n    return None",
      "score": 0.94
    },
    {
      "filename": "src/models/user.py",
      "content": "class User(db.Model):\n    id = db.Column(db.Integer, primary_key=True)\n    username = db.Column(db.String(80), unique=True, nullable=False)\n    password_hash = db.Column(db.String(128), nullable=False)",
      "score": 0.87
    }
  ],
  "hash": "a3f82c1d4e9b6f028571d3a2c8e4b96f7d2e5a18",
  "pending_embeddings": 0
}
```

--------------------------------

### OpenAI Compatible API

Source: https://docs.relace.ai/docs/instant-apply/quickstart

This section details how to use the Relace Instant Apply service with an OpenAI-compatible client, allowing for integration with existing OpenAI workflows.

```APIDOC
## OpenAI Compatible API

### Description
Integrates with the Relace Instant Apply service using an OpenAI-compatible client. This allows developers to leverage the Instant Apply functionality within their existing OpenAI API workflows.

### Method
POST (via OpenAI client)

### Endpoint
https://instantapply.endpoint.relace.run/v1/apply

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body (as part of OpenAI message content)
- **initial_code** (string) - Encapsulated within `<code>` tags. The original code content.
- **edit_snippet** (string) - Encapsulated within `<update>` tags. The snippet containing the desired edits.

### Request Example
```typescript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "YOUR_API_KEY",
  baseURL: "https://instantapply.endpoint.relace.run/v1/apply"
});

const initialCode = "// ... existing code ...\nfunction oldFunction() {\n  // ...\n}\n// ... rest of code ...";
const editSnippet = "// ... keep existing code ...\nfunction newFunction() {\n  // ... new logic ...\n}\n// ... rest of code ...";

const userMessage = `
<code>${initialCode}</code>
<update>${editSnippet}</update>
`;

const response = await client.chat.completions.create({
  model: "auto", // Or a specific model if applicable
  messages: [
    {
      role: "user",
      content: userMessage
    }
  ]
});

// The response object will contain the merged code and usage details.
console.log(response.choices[0].message.content);
```

### Response
#### Success Response (200)
The response structure will be similar to the standard OpenAI chat completion response, with the merged code typically found within the message content. The exact format may vary, but it should include the final merged code.

#### Response Example (Conceptual)
```json
{
  "id": "chatcmpl-xxxxxxxxxxxxxxxxx",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-3.5-turbo-0613",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "{\n  \"mergedCode\": \"// ... existing code ...\nfunction newFunction() {\n  // ... new logic ...\n}\n// ... rest of code ...\",\n  \"usage\": {\n    \"prompt_tokens\": 150,\n    \"completion_tokens\": 50,\n    \"total_tokens\": 200\n  }\n}"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 150,
    "completion_tokens": 50,
    "total_tokens": 200
  }
}
```
```

--------------------------------

### POST /v1/repo/{repo_id}/agent

Source: https://docs.relace.ai/docs/data-analysis/quickstart

Triggers an analysis agent to process data and generate an interactive dashboard.

```APIDOC
## POST /v1/repo/{repo_id}/agent

### Description
Executes an analysis agent with a custom query and system prompt, returning an SSE stream of execution events.

### Method
POST

### Endpoint
https://api.relace.run/v1/repo/{repo_id}/agent

### Parameters
#### Path Parameters
- **repo_id** (string) - Required - The ID of the repository

### Request Body
- **agent_name** (string) - Required - Name of the agent to run
- **agent_inputs** (object) - Required - Input parameters for the agent
  - **query** (string) - Required - The analysis task
  - **system_prompt** (string) - Required - Instructions for the agent

### Request Example
{
  "agent_name": "analysis-agent",
  "agent_inputs": {
    "query": "Analyze trends",
    "system_prompt": "You are a data expert."
  }
}

### Response
#### Success Response (200)
- **stream** (SSE) - Returns execution events and tool calls
```

--------------------------------

### PUT /v1/repo/{repo_id}/file/{path}

Source: https://docs.relace.ai/docs/data-analysis/quickstart

Uploads structured data files to a specific path within the repository.

```APIDOC
## PUT /v1/repo/{repo_id}/file/{path}

### Description
Uploads a file to the public directory of the specified repository.

### Method
PUT

### Endpoint
https://api.relace.run/v1/repo/{repo_id}/file/{path}

### Parameters
#### Path Parameters
- **repo_id** (string) - Required - The ID of the repository
- **path** (string) - Required - The destination path (e.g., "public/data.csv")

### Request Body
- **binary** (blob) - Required - The raw file content

### Response
#### Success Response (200/201)
- **status** (string) - Confirmation of successful upload
```

--------------------------------

### POST /v1/repo

Source: https://docs.relace.ai/api-reference/repos/create

Creates a new repository with the provided source code files and metadata. This endpoint is used to upload and initialize a new codebase within the Relace platform.

```APIDOC
## POST /v1/repo

### Description
Creates a new repository with the provided source code files and metadata. This endpoint is used to upload and initialize a new codebase within the Relace platform.

### Method
POST

### Endpoint
/v1/repo

### Parameters
#### Request Body
- **source** (object) - Required - The source code of the repository.
  - **type** (string) - Required - The type of source, e.g., "files".
  - **files** (array) - Required - An array of file objects.
    - **filename** (string) - Required - The name of the file.
    - **content** (string) - Required - The content of the file.
- **metadata** (object) - Optional - Metadata for the repository.
  - **name** (string) - Optional - The name of the repository.
  - **id** (string) - Optional - A unique identifier for the repository.

### Request Example
```json
{
  "source": {
    "type": "files",
    "files": [
      {
        "filename": "src/search.ts",
        "content": "function findItem(array: Item[], targetId: string): Item | undefined {\n  for (let i = 0; i < array.length; i++) {\n    const item = array[i];\n    if (item.id === targetId) {\n      return item;\n    }\n  }\n  return undefined;\n}"
      },
      {
        "filename": "src/types.ts",
        "content": "interface Item {\n  id: string;\n  value: string;\n  metadata?: Record<string, unknown>;\n}"
      }
      // ... more files
    ]
  },
  "metadata": {
    "name": "my-codebase",
    "id": "my-internal-id"
  }
}
```

### Response
#### Success Response (200)
- **repo_id** (string) - Unique identifier for the newly created repo.
- **repo_head** (string) - Commit hash for the current repo head.

#### Response Example
```json
{
  "repo_id": "123e4567-e89b-12d3-a456-426614174000",
  "repo_head": "a1b2c3d4e5f6789012345678901234567890abcdef"
}
```
```

--------------------------------

### Example Reranker Output (JSON)

Source: https://docs.relace.ai/docs/code-reranker/workflow

The code reranker returns a list of objects, each containing a filename and its relevance score. This output format is used to determine which code segments are most relevant for further processing.

```json
[
  {
    "filename": "src/components/UserProfile.tsx",
    "relevance_score": 0.9598
  },
  {
    "filename": "src/types/user.ts",
    "relevance_score": 0.0321
  },
  {
    "filename": "src/components/Header.tsx",
    "relevance_score": 0.0014
  }
]
```

--------------------------------

### Apply Code Snippets using OpenAI Client

Source: https://docs.relace.ai/api-reference/instant-apply/apply

This snippet demonstrates how to use the OpenAI client to interact with the Relace Apply API. It constructs a user message with instructions, initial code, and an edit snippet, then sends it to the 'auto' model for processing. Ensure you replace 'YOUR_API_KEY' with your actual API key and provide the correct instruction, initial_code, and edit_snippet.

```typescript
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://instantapply.endpoint.relace.run/v1/apply',
});

const userMessage = `
<instruction>{instruction}</instruction>
<code>{initial_code}</code>
<update>{edit_snippet}</update>
`;

const response = await client.chat.completions.create({
  model: 'auto',
  messages: [
    {
      role: 'user',
      content: userMessage,
    },
  ],
});
```

--------------------------------

### Create a Relace Template Repository

Source: https://docs.relace.ai/docs/repos/relace-templates

Initializes a new template repository in Relace using either a remote Git URL or a local file structure. Setting auto_index to true is required to enable semantic search capabilities for the repository.

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const templateRepo = await client.repo.create({
    source: {
        type: "git",
        url: "https://github.com/relace-ai/vite-template",
        branch: "main"
    },
    auto_index: true // Required for semantic search
});

const templateRepoId = templateRepo.repo_id;
console.log(`Template repository created with ID: ${templateRepoId}`);
```

```typescript
import { Relace } from "@relace-ai/relace";

const client = new Relace({ apiKey: "YOUR_API_KEY" });

const templateRepo = await client.repo.create({
    source: {
        type: "files",
        files: [
            {
                filename: "src/agent.py",
                content: "class Agent:\n    def __init__(self):\n        self.name = 'BaseAgent'\n    \n    def process(self, input_data):\n        # Base processing logic\n        return input_data"
            }
        ]
    },
    auto_index: true // Required for semantic search
});

const templateRepoId = templateRepo.repo_id;
console.log(`Template repository created with ID: ${templateRepoId}`);
```

--------------------------------

### Using Repo Tokens

Source: https://docs.relace.ai/api-reference/repo_tokens/create

Demonstrates how to use the generated repo tokens for authentication on repository-specific endpoints.

```APIDOC
## Using Repo Tokens

Once created, repo tokens can be used as bearer tokens for authentication on any `/repo/{repo_id}` endpoint that they are scoped for.

### Example Usage
```bash
curl -X POST https://api.relace.run/v1/repo/123e4567-e89b-12d3-a456-426614174000/search \
  -H "Authorization: Bearer rlcr-a1b2c3d4e5f67890abcdef1234567890abcdef12" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "authentication logic"
  }'
```
```