The Llama Cloud Admin Python library provides convenient access to the Llama Cloud Admin REST API from any Python 3.9+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.
It is generated with Stainless.
This library's full surface — 30 endpoints across organizations, projects, invites, roles, and the global-admin operator API — is documented in api.md and in the docstring on each generated method. These admin endpoints are not covered by the public product reference at developers.llamaindex.ai, so treat api.md as the reference.
pip install git+https://github.com/run-llama/llamacloud-admin-python.gitAuthenticate with a LLAMA_CLOUD_API_KEY belonging to an organization admin. The client reads
it from the environment by default, or accepts it as the api_key keyword argument.
The client.admin.* methods wrap the /api/v1/admin/* operator API and require a key belonging to
the deployment's global admin; an ordinary organization-admin key gets a 403. (On a self-hosted
or BYOC deployment, admin.get_license_info() and admin.get_llamaextract_features() also accept a
regular BYOC user key.) See
global admin configuration.
The full API of this library can be found in api.md.
import os
from llama_cloud_admin import LlamaCloudAdmin
client = LlamaCloudAdmin(
api_key=os.environ.get("LLAMA_CLOUD_API_KEY"), # This is the default and can be omitted
# Defaults to https://api.cloud.llamaindex.ai. Self-hosted / BYOC deployments should point this
# at their own host, or set the LLAMA_CLOUD_ADMIN_BASE_URL environment variable.
# base_url="https://llamacloud.example.com",
)
organization_members = client.organizations.users.list_members(
"my-organization-id",
)While you can provide an api_key keyword argument,
we recommend using python-dotenv
to add LLAMA_CLOUD_API_KEY="My API Key" to your .env file
so that your API Key is not stored in source control.
Simply import AsyncLlamaCloudAdmin instead of LlamaCloudAdmin and use await with each API call:
import os
import asyncio
from llama_cloud_admin import AsyncLlamaCloudAdmin
client = AsyncLlamaCloudAdmin(
api_key=os.environ.get("LLAMA_CLOUD_API_KEY"), # This is the default and can be omitted
)
async def main() -> None:
organization_members = await client.organizations.users.list_members(
"my-organization-id",
)
asyncio.run(main())Functionality between the synchronous and asynchronous clients is otherwise identical.
By default, the async client uses httpx for HTTP requests. However, for improved concurrency performance you may also use aiohttp as the HTTP backend.
You can enable this by installing aiohttp:
pip install 'llama_cloud_admin[aiohttp] @ git+https://github.com/run-llama/llamacloud-admin-python.git'Then you can enable it by instantiating the client with http_client=DefaultAioHttpClient():
import os
import asyncio
from llama_cloud_admin import DefaultAioHttpClient
from llama_cloud_admin import AsyncLlamaCloudAdmin
async def main() -> None:
async with AsyncLlamaCloudAdmin(
api_key=os.environ.get("LLAMA_CLOUD_API_KEY"), # This is the default and can be omitted
http_client=DefaultAioHttpClient(),
) as client:
organization_members = await client.organizations.users.list_members(
"my-organization-id",
)
asyncio.run(main())Nested request parameters are TypedDicts. Responses are Pydantic models which also provide helper methods for things like:
- Serializing back into JSON,
model.to_json() - Converting to a dictionary,
model.to_dict()
Typed requests and responses provide autocomplete and documentation within your editor. If you would like to see type errors in VS Code to help catch bugs earlier, set python.analysis.typeCheckingMode to basic.
Three methods in this library are paginated: organizations.list(), projects.list(), and
invites.list_mine(). The remaining list-shaped methods — organizations.users.list_members(),
organizations.users.list_projects(), and organizations.roles.list() — return every result in a
single response as a plain list and accept no page_size/page_token.
This library provides auto-paginating iterators with each list response, so you do not have to request successive pages manually:
from llama_cloud_admin import LlamaCloudAdmin
client = LlamaCloudAdmin()
all_organizations = []
# Automatically fetches more pages as needed.
for organization in client.organizations.list(
page_size=20,
):
# Do something with organization here
all_organizations.append(organization)
print(all_organizations)Or, asynchronously:
import asyncio
from llama_cloud_admin import AsyncLlamaCloudAdmin
client = AsyncLlamaCloudAdmin()
async def main() -> None:
all_organizations = []
# Iterate through items across all pages, issuing requests as needed.
async for organization in client.organizations.list(
page_size=20,
):
all_organizations.append(organization)
print(all_organizations)
asyncio.run(main())Alternatively, you can use the .has_next_page(), .next_page_info(), or .get_next_page() methods for more granular control working with pages:
first_page = await client.organizations.list(
page_size=20,
)
if first_page.has_next_page():
print(f"will fetch next page using these details: {first_page.next_page_info()}")
next_page = await first_page.get_next_page()
print(f"number of items we just fetched: {len(next_page.items)}")
# Remove `await` for non-async usage.Or just work directly with the returned data:
first_page = await client.organizations.list(
page_size=20,
)
print(f"next page cursor: {first_page.next_page_token}") # => "next page cursor: ..."
for organization in first_page.items:
print(organization.id)
# Remove `await` for non-async usage.Nested parameters are dictionaries, typed using TypedDict, for example:
from llama_cloud_admin import LlamaCloudAdmin
client = LlamaCloudAdmin()
user_claims = client.admin.users.update_claims(
user_id="user_id",
set_claims={"allowed_org_creation": True, "maximum_org_creation": 5},
)
print(user_claims.claims)When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of llama_cloud_admin.APIConnectionError is raised.
When the API returns a non-success status code (that is, 4xx or 5xx
response), a subclass of llama_cloud_admin.APIStatusError is raised, containing status_code and response properties.
All errors inherit from llama_cloud_admin.APIError.
import llama_cloud_admin
from llama_cloud_admin import LlamaCloudAdmin
client = LlamaCloudAdmin()
try:
client.organizations.list()
except llama_cloud_admin.APIConnectionError as e:
print("The server could not be reached")
print(e.__cause__) # an underlying Exception, likely raised within httpx.
except llama_cloud_admin.RateLimitError as e:
print("A 429 status code was received; we should back off a bit.")
except llama_cloud_admin.APIStatusError as e:
print("Another non-200-range status code was received")
print(e.status_code)
print(e.response)Error codes are as follows:
| Status Code | Error Type |
|---|---|
| 400 | BadRequestError |
| 401 | AuthenticationError |
| 403 | PermissionDeniedError |
| 404 | NotFoundError |
| 422 | UnprocessableEntityError |
| 429 | RateLimitError |
| >=500 | InternalServerError |
| N/A | APIConnectionError |
Certain errors are automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors are all retried by default.
You can use the max_retries option to configure or disable retry settings:
from llama_cloud_admin import LlamaCloudAdmin
# Configure the default for all requests:
client = LlamaCloudAdmin(
# default is 2
max_retries=0,
)
# Or, configure per-request:
client.with_options(max_retries=5).organizations.list()By default requests time out after 1 minute. You can configure this with a timeout option,
which accepts a float or an httpx.Timeout object:
import httpx
from llama_cloud_admin import LlamaCloudAdmin
# Configure the default for all requests:
client = LlamaCloudAdmin(
# 20 seconds (default is 1 minute)
timeout=20.0,
)
# More granular control:
client = LlamaCloudAdmin(
timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
)
# Override per-request:
client.with_options(timeout=5.0).organizations.list()On timeout, an APITimeoutError is thrown.
Note that requests that time out are retried twice by default.
We use the standard library logging module.
You can enable logging by setting the environment variable LLAMA_CLOUD_ADMIN_LOG to info.
$ export LLAMA_CLOUD_ADMIN_LOG=infoOr to debug for more verbose logging.
In an API response, a field may be explicitly null, or missing entirely; in either case, its value is None in this library. You can differentiate the two cases with .model_fields_set:
if response.my_field is None:
if 'my_field' not in response.model_fields_set:
print('Got json like {}, without a "my_field" key present at all.')
else:
print('Got json like {"my_field": null}.')The "raw" Response object can be accessed by prefixing .with_raw_response. to any HTTP method call, e.g.,
from llama_cloud_admin import LlamaCloudAdmin
client = LlamaCloudAdmin()
response = client.organizations.with_raw_response.list()
print(response.headers.get('X-My-Header'))
page = response.parse() # get the object that `organizations.list()` would have returned
print(page.items)These methods return an APIResponse object.
The async client returns an AsyncAPIResponse with the same structure, the only difference being awaitable methods for reading the response content.
The above interface eagerly reads the full response body when you make the request, which may not always be what you want.
To stream the response body, use .with_streaming_response instead, which requires a context manager and only reads the response body once you call .read(), .text(), .json(), .iter_bytes(), .iter_text(), .iter_lines() or .parse(). In the async client, these are async methods.
with client.organizations.with_streaming_response.list() as response:
print(response.headers.get("X-My-Header"))
for line in response.iter_lines():
print(line)The context manager is required so that the response will reliably be closed.
This library is typed for convenient access to the documented API.
If you need to access undocumented endpoints, params, or response properties, the library can still be used.
To make requests to undocumented endpoints, you can make requests using client.get, client.post, and other
http verbs. Options on the client will be respected (such as retries) when making this request.
import httpx
response = client.post(
"/foo",
cast_to=httpx.Response,
body={"my_param": True},
)
print(response.headers.get("x-foo"))If you want to explicitly send an extra param, you can do so with the extra_query, extra_body, and extra_headers request
options.
To access undocumented response properties, you can access the extra fields like response.unknown_prop. You
can also get all the extra fields on the Pydantic model as a dict with
response.model_extra.
You can directly override the httpx client to customize it for your use case, including:
- Support for proxies
- Custom transports
- Additional advanced functionality
import httpx
from llama_cloud_admin import LlamaCloudAdmin, DefaultHttpxClient
client = LlamaCloudAdmin(
# Or use the `LLAMA_CLOUD_ADMIN_BASE_URL` env var
base_url="http://my.test.server.example.com:8083",
http_client=DefaultHttpxClient(
proxy="http://my.test.proxy.example.com",
transport=httpx.HTTPTransport(local_address="0.0.0.0"),
),
)You can also customize the client on a per-request basis by using with_options():
client.with_options(http_client=DefaultHttpxClient(...))By default the library closes underlying HTTP connections whenever the client is garbage collected. You can manually close the client using the .close() method if desired, or with a context manager that closes when exiting.
from llama_cloud_admin import LlamaCloudAdmin
with LlamaCloudAdmin() as client:
# make requests here
...
# HTTP client is now closedThis library is distributed only from this Git repository. It is not published to PyPI and has no
releases, tags, or changelog, so pip install git+https://... always installs the current tip of the
default branch. To pin an exact revision, append a commit SHA:
pip install 'git+https://github.com/run-llama/llamacloud-admin-python.git@<commit-sha>'
Backwards-incompatible changes can land on the default branch, so pin a SHA if you need a stable surface.
We are keen for your feedback; please open an issue with questions, bugs, or suggestions.
llama_cloud_admin.__version__ is a fixed placeholder (0.0.1) and never changes. Because the library
is installed from git, use pip to see which commit you have:
pip freeze | grep llama_cloud_adminPython 3.9 or higher.