llama-cloud
The official Python library for the llama-cloud API
Decision gist · record as of 2026-08-14
Yes. Active maintenance (released 2 days ago), low install friction, permissive MIT license, no known vulnerabilities, and top-1000 popularity make this a reliable choice for integrating enterprise OCR into Python applications. Install if you need programmatic document parsing via LlamaParse; skip if you don't have a LlamaParse API key or prefer local OCR solutions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a valid LLAMA_CLOUD_API_KEY environment variable to authenticate with the LlamaParse service.
- Low friction install with six common runtime dependencies (anyio, distro, httpx, pydantic, sniffio, typing-extensions).
- Active maintenance: released 2 days ago with recent commits and 57 repository stars.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) allows commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 57 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 29,274,720 downloads/mo, #822 on PyPI
Alternatives
Verify before relying
pip install llama_cloud
import os
from llama_cloud import LlamaCloud
client = LlamaCloud(
api_key=os.environ.get("LLAMA_CLOUD_API_KEY"),
)
job = client.parsing.create(
tier="agentic",
version="latest",
file_id="your-file-id",
)
print(job.id)- Whether the SDK supports all document formats mentioned in the full API documentation beyond the examples shown.
- Specific performance characteristics or throughput limits for batch document processing workflows.
- Whether the MCP Server integration requires additional setup beyond environment variables.
What it is and what it does
llama_cloud is the official Python client for LlamaParse, a cloud-based OCR and document processing platform. It provides synchronous and asynchronous interfaces to upload documents, trigger parsing jobs with configurable tiers (including agentic OCR), and retrieve structured extraction results. The SDK handles authentication, automatic retries (2 times by default on transient failures), pagination for list operations, and detailed error handling with specific exception types for different HTTP status codes.
Typical workflows involve creating a client with an API key, uploading files or referencing existing file IDs, submitting parsing jobs with specified processing tiers, and polling or streaming results. The package supports both simple synchronous usage and async/await patterns for concurrent operations, making it suitable for integration into larger document processing pipelines, data extraction workflows, and AI-assisted document analysis systems.
Use it for
- Extract structured data from PDFs and scanned documents in production applications requiring enterprise-grade OCR.
- Build document processing pipelines that combine file uploads, agentic parsing, and downstream data extraction.
- Integrate document parsing into AI assistant workflows via the MCP Server for interactive document exploration.
- Batch process multiple documents asynchronously to extract text, tables, and metadata at scale.
- Handle error cases and rate limits gracefully in long-running document ingestion systems.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Active maintenance (released 2 days ago), low install friction, permissive MIT license, no known vulnerabilities, and top-1000 popularity make this a reliable choice for integrating enterprise OCR into Python applications. Install if you need programmatic document parsing via LlamaParse; skip if you don't have a LlamaParse API key or prefer local OCR solutions.
Install
llama-cloud on PyPI
Before you install
Low friction install with six common runtime dependencies (anyio, distro, httpx, pydantic, sniffio, typing-extensions). Active maintenance: released 2 days ago with recent commits and 57 repository stars.
Requires a valid LLAMA_CLOUD_API_KEY environment variable to authenticate with the LlamaParse service.
License in practice
MIT license (permissive) allows commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
Quickstart
pip install llama_cloud
import os
from llama_cloud import LlamaCloud
client = LlamaCloud(
api_key=os.environ.get("LLAMA_CLOUD_API_KEY"),
)
job = client.parsing.create(
tier="agentic",
version="latest",
file_id="your-file-id",
)
print(job.id)Verify before relying
- Whether the SDK supports all document formats mentioned in the full API documentation beyond the examples shown.
- Specific performance characteristics or throughput limits for batch document processing workflows.
- Whether the MCP Server integration requires additional setup beyond environment variables.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesanyiodistrohttpxpydanticsniffiotyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 29,274,720 / month, #822 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: OS IndependentOperating System :: POSIXOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries :: Python ModulesTyping :: Typed |
Evidence: llama_cloud-2.14.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “OCR document parsing SDK”
- llama-cloudPython SDK for LlamaParse, an enterprise OCR and document parsing API…
- extend-aiOfficial Python SDK for the Extend document processing API, enabling…
- amazon-textract-response-parserParses JSON responses from Amazon Textract OCR service into typed…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also llama-cloud-services · llama-parse · llama-index-readers-llama-parse · llama-index-indices-managed-llama-cloud · llama-index · unstructured-client · liteparse · pymupdf4llm · reductoai · mineru