chore(docs): bring AMP doc refresh from release/v1.0.0 into main (#3637)
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* WIP: v1 docs (#3626)

(cherry picked from commit d46e20fa09bcd2f5916282f5553ddeb7183bd92c)

* docs: parity for all translations

* docs: full name of acronym AMP

* docs: fix lingering unused code

* docs: expand contextual options in docs.json

* docs: add contextual action to request feature on GitHub

* chore: tidy docs formatting
This commit is contained in:
Tony Kipkemboi
2025-10-02 11:36:04 -04:00
committed by GitHub
parent f47e0c82c4
commit bf9e0423f2
242 changed files with 8999 additions and 3637 deletions

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---
title: OCR Tool
description: The `OCRTool` extracts text from local images or image URLs using an LLM with vision.
icon: image
mode: "wide"
---
# `OCRTool`
## Description
Extract text from images (local path or URL). Uses a visioncapable LLM via CrewAIs LLM interface.
## Installation
No extra install beyond `crewai-tools`. Ensure your selected LLM supports vision.
## Parameters
### Run Parameters
- `image_path_url` (str, required): Local image path or HTTP(S) URL.
## Examples
### Direct usage
```python Code
from crewai_tools import OCRTool
print(OCRTool().run(image_path_url="/tmp/receipt.png"))
```
### With an agent
```python Code
from crewai import Agent, Task, Crew
from crewai_tools import OCRTool
ocr = OCRTool()
agent = Agent(
role="OCR",
goal="Extract text",
tools=[ocr],
)
task = Task(
description="Extract text from https://example.com/invoice.jpg",
expected_output="All detected text in plain text",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
```
## Notes
- Ensure the selected LLM supports image inputs.
- For large images, consider downscaling to reduce token usage.
- You can pass a specific LLM instance to the tool (e.g., `LLM(model="gpt-4o")`) if needed, matching the README guidance.
## Example
```python Code
from crewai import Agent, Task, Crew
from crewai_tools import OCRTool
tool = OCRTool()
agent = Agent(
role="OCR Specialist",
goal="Extract text from images",
backstory="Visionenabled analyst",
tools=[tool],
verbose=True,
)
task = Task(
description="Extract text from https://example.com/receipt.png",
expected_output="All detected text in plain text",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
```

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---
title: PDF Text Writing Tool
description: The `PDFTextWritingTool` writes text to specific positions in a PDF, supporting custom fonts.
icon: file-pdf
mode: "wide"
---
# `PDFTextWritingTool`
## Description
Write text at precise coordinates on a PDF page, optionally embedding a custom TrueType font.
## Parameters
### Run Parameters
- `pdf_path` (str, required): Path to the input PDF.
- `text` (str, required): Text to add.
- `position` (tuple[int, int], required): `(x, y)` coordinates.
- `font_size` (int, default `12`)
- `font_color` (str, default `"0 0 0 rg"`)
- `font_name` (str, default `"F1"`)
- `font_file` (str, optional): Path to `.ttf` file.
- `page_number` (int, default `0`)
## Example
```python Code
from crewai import Agent, Task, Crew
from crewai_tools import PDFTextWritingTool
tool = PDFTextWritingTool()
agent = Agent(
role="PDF Editor",
goal="Annotate PDFs",
backstory="Documentation specialist",
tools=[tool],
verbose=True,
)
task = Task(
description="Write 'CONFIDENTIAL' at (72, 720) on page 1 of ./sample.pdf",
expected_output="Confirmation message",
agent=agent,
)
crew = Crew(
agents=[agent],
tasks=[task],
verbose=True,
)
result = crew.kickoff()
```
### Direct usage
```python Code
from crewai_tools import PDFTextWritingTool
PDFTextWritingTool().run(
pdf_path="./input.pdf",
text="CONFIDENTIAL",
position=(72, 720),
font_size=18,
page_number=0,
)
```
## Tips
- Coordinate origin is the bottomleft corner.
- If using a custom font (`font_file`), ensure it is a valid `.ttf`.