> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlayer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Create a project

> Learn how to create a project using the UI, REST API, or CLI

The Openlayer workspace is organized around **projects**. Each project represents an AI
initiative within your organization and provides a structured space to evaluate, observe, and govern
your AI efforts.

This guide walks you through creating a project using both the UI and programmatically.

<Info>
  **Prerequisite**: you need an [Openlayer account](https://app.openlayer.com/)
  to follow this guide.
</Info>

<img width="700" style={{ borderRadius: "0.5rem" }} src="https://mintcdn.com/openlayer-44/jN8MTVdaEnRVD4sY/images/how-to-guides/create_new_project.png?fit=max&auto=format&n=jN8MTVdaEnRVD4sY&q=85&s=f8d319191d02743c4195ca387dd0463c" alt="Create new project" data-path="images/how-to-guides/create_new_project.png" />

## Create a project in the UI

The UI is the quickest way to set up a new project.

1. Log into your [Openlayer account](https://app.openlayer.com/)
2. Navigate to the workspace home page.
3. Click the **"Create"** button on the top right.
4. Follow the onboarding prompts to set the project name, type, and mode, and review suggested tests for your use case.

[After the project is created](#next-steps), you are ready to start using it to evaluate your AI system.

## Create a project using the REST API or CLI

You can also create projects using our [REST API](/api-reference/rest/overview) or [CLI tool](/api-reference/cli/overview).
This is particularly useful for automation workflows or CI/CD integration.

To authenticate, you need to [create an API key](/workspace-and-projects/find-your-api-key).

<Tabs>
  <Tab title="REST API">
    You can create a project by making a POST request to the `/projects` endpoint. Refer
    to the [Create project API reference page](/api-reference/rest/projects/create-project) for details.

    <CodeGroup>
      ```bash cURL theme={null}
      curl --request POST \
        --url https://api.openlayer.com/v1/projects \
        --header 'Authorization: Bearer <YOUR_API_KEY>' \
        --header 'Content-Type: application/json' \
        --data '{
          "name": "My Project",
          "description": "My project description.",
          "taskType": "llm-base"
        }'
      ```

      ```python Python theme={null}
      from openlayer import Openlayer

      client = Openlayer()
      project = client.projects.create(
        name="My Project",
        description="My project description.",
        taskType="llm-base"
      )
      ```

      ```typescript TypeScript theme={null}
      import Openlayer from 'openlayer';

      const openlayer = new Openlayer();
      const project = await openlayer.projects.create({
        name: 'My Project',
        description: 'My project description.',
        taskType: 'llm-base'
      });
      ```

      ```java Java theme={null}
      import com.openlayer.api.client.OpenlayerClient;
      import com.openlayer.api.client.okhttp.OpenlayerOkHttpClient;
      import com.openlayer.api.models.ProjectCreateParams;
      import com.openlayer.api.models.ProjectCreateResponse;

      OpenlayerClient client = OpenlayerOkHttpClient.fromEnv();

      ProjectCreateParams params = ProjectCreateParams.builder()
          .name("My Project")
          .description("My project description.")
          .taskType(ProjectCreateParams.TaskType.LLM_BASE)
          .build();

      ProjectCreateResponse project = client.projects().create(params);
      ```

      ```go Go theme={null}
      package main

      import (
        "context"
        "github.com/openlayer-ai/openlayer-go"
        "github.com/openlayer-ai/openlayer-go/option"
      )

      client := openlayer.NewClient()
      project, err := client.Projects.New(context.TODO(), openlayer.ProjectNewParams{
        Name: openlayer.F("My Project"),
        TaskType: openlayer.F(openlayer.ProjectNewParamsTaskTypeLlmBase),
      })
      if err != nil {
        panic(err.Error())
      }
      ```
    </CodeGroup>
  </Tab>

  <Tab title="CLI">
    First, make sure you have the [CLI installed](/api-reference/cli/overview#installing-the-openlayer-cli).

    Then, run the [openlayer login](/api-reference/cli/commands/login) command and use your API key when prompted to authenticate:

    ```bash theme={null}
    openlayer login
    ```

    Finally, run the [openlayer link](/api-reference/cli/commands/link) command to create (or connect to) a project:

    ```bash theme={null}
    openlayer link
    ```
  </Tab>
</Tabs>

## Next steps

Once you have created a project, you can immediately start evaluating your AI system. Common
paths are:

* [Monitoring mode overview](/monitoring/overview), to learn how to start observing and testing your live AI system.
* [Development mode overview](/development/overview), to learn how to incorporate Openlayer tests into your CI/CD pipeline.

## FAQ

<AccordionGroup>
  <Accordion title="Can I control which users have access to a project?">
    Yes, Openlayer supports **role-based access control** (RBAC) at the project level.

    You can create access groups with different roles, such as "Admin," "Member," "Viewer," and others. Refer to
    the [Access groups page](/security/access-groups) for details.
  </Accordion>

  <Accordion title="What are the project modes?">
    A project on Openlayer has different modes, such as "Development" and "Monitoring."
    Each mode has a particular purpose in the AI lifecycle:

    * [**Development mode**](/development/overview) is used pre-production and helps you iterate on your AI system, test each version, and track improvements across them.
    * [**Monitoring mode**](/monitoring/overview) is used in production and helps you observe and test an AI system that is serving live requests.
  </Accordion>
</AccordionGroup>