Skip to main content

Xberg

crewai-xberg

CrewAI tools backed by Xberg. Give an agent document intelligence: extract text, metadata, keywords, entities, and summaries from 98 file formats — PDF, DOCX, XLSX, HTML, images with OCR, and more. Extraction is async at the core; the batch tool routes many files through Xberg's extract_batch in a single native call.

Install

pip install crewai-xberg

Requires Python 3.10+.

Tools

Tool Input Returns
XbergExtractTool file_path Extracted text, plus any requested rich results.
XbergExtractBatchTool file_paths One section per document via extract_batch, then errors.
XbergExtractMetadataTool file_path Title, authors, dates, page/table/image counts, format info.

Use

from crewai import Agent
from crewai_xberg import XbergExtractTool, XbergExtractBatchTool, XbergExtractMetadataTool

agent = Agent(
    role="Document Analyst",
    goal="Extract and analyze document content",
    backstory="You process documents of any format.",
    tools=[XbergExtractTool(), XbergExtractBatchTool(), XbergExtractMetadataTool()],
)

Call a tool directly to see its output:

tool = XbergExtractTool()

# Plain extraction
text = tool.run(file_path="report.pdf")

# Force OCR and surface keywords, entities, and a summary
enriched = tool.run(
    file_path="scan.pdf",
    output_format="markdown",
    force_ocr=True,
    extract_keywords=True,
    extract_entities=True,
    summarize=True,
)

# Many files in one batched extraction
combined = XbergExtractBatchTool().run(file_paths=["report.pdf", "notes.docx", "sheet.xlsx"])

Options

Both extraction tools accept the same options. Each toggles an Xberg ExtractionConfig capability:

Option Default Effect
output_format "markdown" plain, markdown, or html.
force_ocr False Run OCR on every page, even with a text layer.
chunk False Split into semantic chunks; report the chunk count.
extract_keywords False Append a keyword list.
extract_entities False Append named entities (people, orgs, locations).
summarize False Append a short summary.

Detected languages and tables are surfaced automatically when present.

Async

The tools are async at the core. Inside an event loop, await tool.arun(...); the synchronous run bridges to it and must not be called from a running loop.

Errors

A missing file raises from Xberg directly. In batch mode, per-file failures land in ExtractionResult.errors and are reported in a trailing Errors section instead of aborting the batch.

For the full API, see the Xberg documentation.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

crewai_xberg-1.0.5.tar.gz (9.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

crewai_xberg-1.0.5-py3-none-any.whl (8.0 kB view details)

Uploaded Python 3

File details

Details for the file crewai_xberg-1.0.5.tar.gz.

File metadata

  • Download URL: crewai_xberg-1.0.5.tar.gz
  • Upload date:
  • Size: 9.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.12.0 {"installer":{"name":"uv","version":"0.12.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for crewai_xberg-1.0.5.tar.gz
Algorithm Hash digest
SHA256 f7b90382e79b286d2fbe142d08f856509f6489359f0e5eb525f433977f76bf44
MD5 d86adcb944adad4cad23bb3da02b41c9
BLAKE2b-256 29b6fac989baff449ff0553c30906ab18bbb79583b31ad6fa244fb5017735bd8

See more details on using hashes here.

File details

Details for the file crewai_xberg-1.0.5-py3-none-any.whl.

File metadata

  • Download URL: crewai_xberg-1.0.5-py3-none-any.whl
  • Upload date:
  • Size: 8.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.12.0 {"installer":{"name":"uv","version":"0.12.0","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for crewai_xberg-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 5319ecd40cfbb1193e99b2cfbd3c96215bc100e0e0401d5d17133437d386798f
MD5 cae99f37ff1247fed98d3ec51cc61a77
BLAKE2b-256 673258d651a0b6fed44f32d9f00e47c8f6b0427eb35ee30f2b782e01e2913042

See more details on using hashes here.

Release history Release notifications | RSS feed

1.2.1

2 files

1.1.5

2 files

1.1.3

2 files

1.1.2

2 files

1.1.1

2 files

1.1.0

2 files

1.0.14

2 files

1.0.12

2 files

1.0.11

2 files

1.0.10

2 files

1.0.9

2 files

1.0.8

2 files

1.0.7

2 files

This release

1.0.5 This release

2 files

1.0.3

2 files

1.0.1

2 files

1.0.0

2 files

0.0.1

1 file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page