Project

Object-centric interface for Galileo projects. This class provides an intuitive way to work with Galileo projects, encapsulating project management operations and providing seamless integration with log stream management. Examples

Create a new project locally, then persist

project = Project(name=“My AI Project”).create()

Get an existing project

project = Project.get(name=“My AI Project”)

List all projects

projects = Project.list()

Create a log stream for the project

log_stream = project.create_log_stream(name=“Production Logs”)

List log streams for the project

log_streams = project.list_log_streams() for log_stream in project.logstreams: print(log_stream.name) for experiment in project.experiments: print(experiment.name) for dataset in project.datasets: print(dataset.name) for prompt in project.prompts: print(prompt.name)

Or use the explicit list methods

datasets = project.list_datasets() prompts = project.list_prompts()

Manage collaborators

for collab in project.collaborators: print(f”: “)

Add a collaborator

project.add_collaborator(user_id=“user-123”, role=CollaboratorRole.EDITOR)

Update a collaborator’s role

project.update_collaborator(user_id=“user-123”, role=CollaboratorRole.VIEWER)

Remove a collaborator

project.remove_collaborator(user_id=“user-123”)

Delete a project (WARNING: cannot be undone!)

old_project = Project.get(name=“Old Project”) old_project.delete()

add_collaborator

def add_collaborator(self,
                     user_id: str,
                     role: CollaboratorRole=CollaboratorRole.VIEWER) -> Collaborator

Add a collaborator to this project. Shares the project with a user, granting them access with the specified role. Arguments

user_id: The ID of the user to add as a collaborator.
role: The role to assign. One of CollaboratorRole.OWNER, EDITOR, VIEWER, or ANNOTATOR. Defaults to VIEWER.

collaborators

def collaborators(self) -> builtins.list[Collaborator]

Property to access collaborators for this project. Returns users who have access to this project. Each Collaborator object has update() and remove() methods for modifying access. You can also use add_collaborator() on the project to add new collaborators. .. note:: This property makes an API call on every access and is not cached. Examples project = Project.get(name=“My AI Project”) for collab in project.collaborators: print(f”: “)

Filter by role

editors = [c for c in project.collaborators if c.role == CollaboratorRole.EDITOR]

Update or remove directly on the collaborator object

collab.update(role=CollaboratorRole.EDITOR) collab.remove()

create

def create(self) -> Project

Persist this project to the API. Examples project = Project(name=“My AI Project”).create() assert project.is_synced()

create_log_stream

def create_log_stream(self, name: str) -> LogStream

Create a new log stream for this project. Arguments

name (str): The name of the log stream to create.

datasets

def datasets(self) -> builtins.list[Dataset]

Property to access datasets used in this project. This is a read-only property that returns the datasets associated with this project. Examples project = Project.get(name=“My AI Project”) for dataset in project.datasets: print(dataset.name)

delete

def delete(self) -> None

Delete this project. This is a destructive operation that permanently removes the project and all associated data (experiments, log streams, datasets, traces, etc.) from the API. WARNING: This operation cannot be undone! After successful deletion, the object state is set to DELETED. The local object still exists in memory but no longer represents a remote resource. Examples

Delete a project

project = Project.get(name=“Old Project”) project.delete() assert project.is_deleted()

After deletion, the project no longer exists remotely

The local object is marked as DELETED

print(project.sync_state) # SyncState.DELETED

experiments

def experiments(self) -> builtins.list[Experiment]

Property to access experiments for this project. This is a read-only property that returns the current list of experiments. Examples project = Project.get(name=“My AI Project”) for exp in project.experiments: print(exp.name)

get

def get(cls, *, id: str | None=None, name: str | None=None) -> Project | None

Get an existing project by ID or name. Arguments

id (Optional[str]): The project ID.
name (Optional[str]): The project name.

list

def list(cls) -> builtins.list[Project]

List all available projects. Examples projects = Project.list() for project in projects:

Process each project

pass

list_collaborators

def list_collaborators(self) -> builtins.list[Collaborator]

List all collaborators for this project. Returns a list of Collaborator objects representing users who have access to this project, along with their roles and permissions. Examples project = Project.get(name=“My AI Project”) collaborators = project.list_collaborators() for collab in collaborators: print(f”: “)

list_datasets

def list_datasets(self) -> builtins.list[Dataset]

List all datasets used in this project. Examples project = Project.get(name=“My AI Project”) datasets = project.list_datasets() for dataset in datasets:

Process each dataset

pass

list_experiments

def list_experiments(self) -> builtins.list[Experiment]

List all experiments for this project. Examples project = Project.get(name=“My AI Project”) experiments = project.list_experiments() for exp in experiments:

Process each experiment

pass

list_log_streams

def list_log_streams(self,
                     *,
                     limit: Unset | int=100,
                     starting_token: Unset | int=0) -> builtins.list[LogStream]

List log streams for this project. Returns a single page of results. Use starting_token (from next_starting_token on a prior response) to fetch subsequent pages. Arguments

limit (Union[Unset, int]): Maximum number of log streams to return per page. Defaults to 100.
starting_token (Union[Unset, int]): Pagination token to start from. Defaults to 0 (first page).

list_prompts

def list_prompts(self) -> builtins.list[Prompt]

List all prompts used in this project. Examples project = Project.get(name=“My AI Project”) prompts = project.list_prompts() for prompt in prompts:

Process each prompt

pass

logstreams

def logstreams(self) -> builtins.list[LogStream]

Property to access log streams for this project. This is a read-only property that returns the current list of log streams. To create new log streams, use create_log_stream(). Examples project = Project.get(name=“My AI Project”) for stream in project.logstreams: print(stream.name)

prompts

def prompts(self) -> builtins.list[Prompt]

Property to access prompts used in this project. This is a read-only property that returns the prompts associated with this project. Examples project = Project.get(name=“My AI Project”) for prompt in project.prompts: print(prompt.name)

refresh

def refresh(self) -> None

Refresh this project’s state from the API. Updates all attributes with the latest values from the remote API and sets the state to SYNCED. Examples project.refresh() assert project.is_synced()

remove_collaborator

def remove_collaborator(self, user_id: str) -> None

Remove a collaborator from this project. Revokes a user’s access to this project. The user will no longer be able to view or interact with the project. Arguments

user_id: The ID of the user to remove.

save

def save(self) -> Project

Save changes to this project. Persists any local changes (name, type) to the remote API. If the project is LOCAL_ONLY, delegates to create(). If SYNCED, returns immediately as a no-op. Raises ValueError for DELETED or FAILED_SYNC states. .. note:: ProjectUpdate also supports description, labels, and created_by, but these are not exposed as tracked attributes on the domain object because the read endpoints (get/list) do not return them consistently. created_by is server-managed. If the project is in FAILED_SYNC state (from a prior failed operation), this method raises ValueError. Call :meth:refresh first to re-sync, then retry. Examples

Create a new project

project = Project(name=“My Project”) project.save()

Update an existing project’s name via dirty-tracking

project = Project.get(name=“My Project”) project.name = “Renamed Project” # automatically marks DIRTY project.save()

update_collaborator

def update_collaborator(self, user_id: str, role: CollaboratorRole) -> Collaborator

Update a collaborator’s role on this project. Changes the role of an existing collaborator. The user must already have access to the project. Arguments

user_id: The ID of the user whose role to update.
role: The new role to assign. One of CollaboratorRole.OWNER, EDITOR, VIEWER, or ANNOTATOR.

​Project

​Create a new project locally, then persist

​Get an existing project

​List all projects

​Create a log stream for the project

​List log streams for the project

​Access related resources via properties

​Or use the explicit list methods

​Manage collaborators

​Add a collaborator

​Update a collaborator’s role

​Remove a collaborator

​Delete a project (WARNING: cannot be undone!)

​add_collaborator

​collaborators

​Filter by role

​Update or remove directly on the collaborator object

​create

​create_log_stream

​datasets

​delete

​Delete a project

​After deletion, the project no longer exists remotely

​The local object is marked as DELETED

​experiments

​get

​list

​Process each project

​list_collaborators

​list_datasets

​Process each dataset

​list_experiments

​Process each experiment

​list_log_streams

​list_prompts

​Process each prompt

​logstreams

​prompts

​refresh

​remove_collaborator

​save

​Create a new project

​Update an existing project’s name via dirty-tracking

​update_collaborator

Project

Create a new project locally, then persist

Get an existing project

List all projects

Create a log stream for the project

List log streams for the project

Access related resources via properties

Or use the explicit list methods

Manage collaborators

Add a collaborator

Update a collaborator’s role

Remove a collaborator

Delete a project (WARNING: cannot be undone!)

add_collaborator

collaborators

Filter by role

Update or remove directly on the collaborator object

create

create_log_stream

datasets

delete

Delete a project

After deletion, the project no longer exists remotely

The local object is marked as DELETED

experiments

get

list

Process each project

list_collaborators

list_datasets

Process each dataset

list_experiments

Process each experiment

list_log_streams

list_prompts

Process each prompt

logstreams

prompts

refresh

remove_collaborator

save

Create a new project

Update an existing project’s name via dirty-tracking

update_collaborator