├── .gitignore
├── CHANGES.md
├── LICENSE
├── README.md
├── examples
├── GUI
│ ├── README.md
│ └── browser-app.py
├── README.md
└── country-capitals
│ ├── README.md
│ ├── country-capitals.py
│ └── national-capitals.pdf
├── pdf4llm
├── README.md
├── pdf4llm
│ └── __init__.py
└── setup.py
├── pymupdf4llm
├── README.md
├── pymupdf4llm
│ ├── __init__.py
│ ├── helpers
│ │ ├── get_text_lines.py
│ │ ├── multi_column.py
│ │ ├── progress.py
│ │ └── pymupdf_rag.py
│ └── llama
│ │ └── pdf_markdown_reader.py
└── setup.py
└── tests
└── pymupdf4llm
└── llama_index
└── test_pdf_markdown_reader.py
/.gitignore:
--------------------------------------------------------------------------------
1 | _build
2 | build
3 | *.egg-info
4 | __pycache__
5 | .pytest_cache
--------------------------------------------------------------------------------
/CHANGES.md:
--------------------------------------------------------------------------------
1 | # Change Log
2 |
3 | ## Changes in version 0.0.24
4 |
5 | ### Fixes:
6 |
7 | * Fixing "UnboundLocalError"
8 |
9 | ### Other Changes:
10 |
11 |
12 |
13 | ## Changes in version 0.0.23
14 |
15 | ### Fixes:
16 |
17 | * [265](https://github.com/pymupdf/RAG/issues/265) - Code error correction
18 | * [263](https://github.com/pymupdf/RAG/issues/263) - Table Strategy = None raises error
19 | * [261](https://github.com/pymupdf/RAG/issues/261) - wrong markdown in latest pymupdf versions
20 |
21 | ### Other Changes:
22 |
23 | * Highspeed vector graphics count: if `graphics_limit` is specified, drawings are no longer extracted for counting purposes.
24 |
25 |
26 | ## Changes in version 0.0.22
27 |
28 | ### Fixes:
29 |
30 | * [251](https://github.com/pymupdf/RAG/issues/251) - Images a little larger than the page size are being ignored
31 | * [255](https://github.com/pymupdf/RAG/issues/255) - Single-row/column tables are skipped
32 | * [258](https://github.com/pymupdf/RAG/issues/258) - Pymupdf4llm to_markdown crashes on some documents
33 |
34 | ### Other Changes:
35 |
36 | * Added class `TocHeaders` as an alternative way for identifying headers.
37 |
38 |
39 | ## Changes in version 0.0.21
40 |
41 | ### Fixes:
42 |
43 | * [116](https://github.com/pymupdf/RAG/issues/116) - Handling Graphical Images & Superscripts
44 |
45 | ### Other Changes:
46 |
47 |
48 | ## Changes in version 0.0.20
49 |
50 | ### Fixes:
51 |
52 | * [171](https://github.com/pymupdf/RAG/issues/171) - Text rects overlap with tables and images that should be excluded.
53 | * [189](https://github.com/pymupdf/RAG/issues/189) - The position of the extracted image is incorrect
54 | * [238](https://github.com/pymupdf/RAG/issues/238) - When text is laid out around the picture, text extraction is missing.
55 |
56 | ### Other Changes:
57 |
58 | * Added **_new parameter_** `ignore_images`: (bool) optional. `True` will not consider images in any way. May be useful for pages where a plethora of images prevents meaningful layout analysis. Typical examples are PowerPoint slides and derived / similar pages.
59 |
60 | * Added **_new parameter_** `ignore_graphics`: (bool), optional. `True` will not consider graphics except for table detection. May be useful for pages where a plethora of vector graphics prevents meaningful layout analysis. Typical examples are PowerPoint slides and derived / similar pages.
61 |
62 | * Added **_new parameter_** to class `IdentifyHeaders`: Use `max_levels` (integer <= 6) to limit the generation of header tag levels. e.g. `headers = pymupdf4llm.IdentifyHeaders(doc, max_level=3)` ensures that only up to 3 header levels will ever be generated. Any text with a font size less than the value of `###` will be body text. In this case, the markdown generation itself would be coded as `md = pymupdf4llm.to_markdown(doc, hdr_info=headers, ...)`.
63 |
64 | * Changed parameter `table_strategy`: When specifying `None`, no effort to detecting tables will be made. This can be useful when tables are of no interest or known to not exist in a given file. This will speed up processing significantly. Be prepared to see more changes and extensions here.
65 |
66 |
67 | ## Changes in version 0.0.19
68 |
69 | ### Fixes:
70 | The following list includes fixes made in version 0.0.18 already.
71 |
72 | * [158](https://github.com/pymupdf/RAG/issues/158) - Very long titles when converting to markdown.
73 | * [155](https://github.com/pymupdf/RAG/issues/155) - Inconsistent image extraction from image-only PDFs
74 | * [161](https://github.com/pymupdf/RAG/issues/161) - force_text param ignored.
75 | * [162](https://github.com/pymupdf/RAG/issues/162) - to_markdown isn't outputting all the pages but get_text is.
76 | * [173](https://github.com/pymupdf/RAG/issues/173) - First column of table is repeated before the actual table.
77 | * [187](https://github.com/pymupdf/RAG/issues/187) - Unsolicited Text Particles
78 | * [188](https://github.com/pymupdf/RAG/issues/188) - Takes lot of time to convert into markdown.
79 | * [191](https://github.com/pymupdf/RAG/issues/191) - Extraction of text stops in the middle while working fine with PyMuPDF.
80 | * [212](https://github.com/pymupdf/RAG/issues/212) - In pymupdf4llm, if a page has multiple images, only 1 image per-page is extracted.
81 | * [213](https://github.com/pymupdf/RAG/issues/213) - Many ���� after converting when using pymupdf4llm
82 | * [215](https://github.com/pymupdf/RAG/issues/215) - Spending too much time on identifying text bboxes
83 | * [218](https://github.com/pymupdf/RAG/issues/218) - IndexError in get_raw_lines when processing PDFs with formulas
84 | * [225](https://github.com/pymupdf/RAG/issues/225) - Text with background missing from output.
85 | * [229](https://github.com/pymupdf/RAG/issues/229) - Duplicated Table Content on pymuPDF4LLM.
86 |
87 |
88 | ### Other Changes:
89 |
90 | * Added **_new parameter_** `filename`: (str), optional. Overwrites or sets the filename for saved images. Useful when the document is opened from memory.
91 |
92 | * Added **_new parameter_** `use_glyphs`: (bool), optional. Request to use the glyph number (if possible) of a character if the font has no back-translation to the original Unicode value. The default is `False` which causes � symbols to be rendered in these cases.
93 |
94 | * Added **_strike-out support_**: We now detect and render ~~striked-out text.~~
95 |
96 | * Improved **_background color_** detection: We have introduced a simple background color detection mechanism: If a page shows an identical color in all four corners, we assume this to be the background color. Text and vector graphics with this color will be ignored as invisible.
97 |
98 | * Improved **_invisible text detection_**: Text with an alpha value of 0 is now ignored.
99 |
100 | * Improved **_fake-bold_** detection: Text mimicking bold appearance is now treated like standard bold text in most cases.
101 |
102 | * Header handling changes:
103 | - Detection now happens based on the **_largest font size_** of the line.
104 | - Uniformly rendered: All spans of a header line will now be rendered with the same appearance.
105 |
106 | * Changed handling of parameter `graphics_limit`: We previously ignored a page completely if the vector graphics count exceeded the limit. We now only ignore vector graphics if their count **_outside table boundary boxes_** is too large. This should only suppress vector graphics on the page, while keeping images, text and table content extractable.
107 |
108 | * Changed the `margins` default to 0. The previous default `(0, 50, 0, 50)` ignored 50 points at the top and bottom of pages. This has turned out to cause confusion in too many cases.
109 |
110 |
111 | ## Changes in version 0.0.17
112 |
113 | ### Fixes:
114 |
115 |
116 | * [147](https://github.com/pymupdf/RAG/issues/147) - Error when page contains nothing but a table.
117 | * [81](https://github.com/pymupdf/RAG/issues/81) - Issues with bullet points in PDFs.
118 | * [78](https://github.com/pymupdf/RAG/issues/78) - multi column pdf file text extraction.
119 |
120 |
121 | ## Changes in version 0.0.15
122 |
123 | ### Fixes:
124 |
125 |
126 | * [138](https://github.com/pymupdf/RAG/issues/138) - Table is not extracted and some text order was wrong.
127 | * [135](https://github.com/pymupdf/RAG/issues/135) - Problem with multiple columns in simple text.
128 | * [134](https://github.com/pymupdf/RAG/issues/134) - Exclude images based on size threshold parameter.
129 | * [132](https://github.com/pymupdf/RAG/issues/132) - Optionally embed images as base64 string.
130 | * [128](https://github.com/pymupdf/RAG/issues/128) - Enhanced image embedding format.
131 |
132 |
133 | ### Improvements
134 |
135 | * New parameter `embed_images` (bool) **embeds** images and vector graphics in the markdown text as base64-encoded strings. Ignores `write_images` and `image_path` parameters.
136 | * New parameter `image_size_limit` which is a float between 0 and 1, default is 0.05 (5%). Causes images to be ignored if their width or height values are smaller than the corresponding fraction of the page's width or height.
137 | * The algorithm has been improved which determins the sequence of the text rectangles on multi-column pages.
138 | * Change of the header identification algorithm: If more than six header levels are required for a document, then all text with a font size larger than body text is assumed to be a header of level 6 (i.e. HTML "h6" = "###### ").
139 |
140 |
141 | ## Changes in version 0.0.13
142 |
143 |
144 | ### Fixes
145 |
146 | * [112](https://github.com/pymupdf/RAG/issues/112) - Invalid bandwriter header dimensions/setup.
147 |
148 |
149 | ### Improvements
150 |
151 | * New parameter `ignore_code` suppresses special formatting of text in mono-spaced fonts.
152 | * New parameter `extract_words` enforces `page_chunks=True` and adds a "words" list to each page dictionary.
153 |
154 |
155 | ## Changes in version 0.0.11
156 |
157 |
158 | ### Fixes
159 |
160 | * [90](https://github.com/pymupdf/RAG/issues/90) - 'Quad' object has no attribute 'tl'.
161 | * [88](https://github.com/pymupdf/RAG/issues/88) - Bug in `is_significant` function.
162 |
163 |
164 | ### Improvements
165 |
166 | * Extended the list of known bullet point characters.
167 |
168 |
169 | ## Changes in version 0.0.10
170 |
171 |
172 | ### Fixes
173 |
174 | * [73](https://github.com/pymupdf/RAG/issues/73) - bug in `to_markdown` internal function.
175 | * [74](https://github.com/pymupdf/RAG/issues/74) - minimum area for images & vector graphics.
176 | * [75](https://github.com/pymupdf/RAG/issues/75) - Poor Markdown Generation for Particular PDF.
177 | * [76](https://github.com/pymupdf/RAG/issues/76) - suggestion on useful api parameters.
178 |
179 |
180 | ### Improvements
181 |
182 | * Improved recognition of "insignificant" vector graphics. Graphics like text highlights or borders will be ignored.
183 | * The format of saved images can now be controlled via new parameter `image_format`.
184 | * Images can be stored in a specific folder via the new parameter `image_path`.
185 | * Images are **not stored if contained** in another image on same page.
186 | * Images are **not stored if too small:** if width or height are less than 5% of corresponding page dimension.
187 | * All text is always written. If `write_images=True`, text on images / graphics can be suppressed by setting `force_text=False`.
188 |
189 |
190 | ## Changes in version 0.0.9
191 |
192 |
193 | ### Fixes
194 |
195 | * [71](https://github.com/pymupdf/RAG/issues/71) - Unexpected results in pymupdf4llm but pymupdf works.
196 | * [68](https://github.com/pymupdf/RAG/issues/68) - Issue with text extraction near footer of page.
197 |
198 |
199 | ### Improvements
200 |
201 | * Improved identification of scattered text span particles. This should address most issues with out-of-sequence situations.
202 | * We now correctly process rotated pages (see [issue 68](https://github.com/pymupdf/RAG/issues/68)).
203 |
204 |
205 | ## Changes in version 0.0.8
206 |
207 |
208 | ### Fixes
209 |
210 |
211 | * [65](https://github.com/pymupdf/RAG/issues/65) - Fix typo in `pymupdf_rag.py`.
212 |
213 |
214 | ## Changes in version 0.0.7
215 |
216 |
217 | ### Fixes
218 |
219 |
220 | * [54](https://github.com/pymupdf/RAG/issues/54) - Mistakes in orchestrating sentences. Additional fix: text extraction no longer uses the `TEXT_DEHYPHENATE` flag bit.
221 |
222 | ### Improvements
223 |
224 | * Improved the algorithm dealing with vector graphics. Vector graphics are now more reliably classified as irrelevant: We now detect when "strokes" only exist in the neighborhood of the graphics boundary box border itself. This is quite often the case for code snippets.
225 |
226 | ## Changes in version 0.0.6
227 |
228 |
229 | ### Fixes
230 |
231 |
232 | * [55](https://github.com/pymupdf/RAG/issues/55) - Bug in helpers/multi_column.py - IndexError: list index out of range.
233 | * [54](https://github.com/pymupdf/RAG/issues/54) - Mistakes in orchestrating sentences.
234 | * [52](https://github.com/pymupdf/RAG/issues/52) - Chunking of text files.
235 | * Partial fix for [41](https://github.com/pymupdf/RAG/issues/41) / [40](https://github.com/pymupdf/RAG/issues/40) - Improved page column detection, but still no silver bullet for overly complex page layouts.
236 |
237 | ### Improvements
238 |
239 | * New parameter `dpi` to specify the resolution of images.
240 | * New parameters `page_width` / `page_height` for easily processing reflowable documents (Text, Office, e-books).
241 | * New parameter `graphics_limit` to avoid spending runtimes for value-less content.
242 | * New parameter `table_strategy` to directly control the table detection strategy.
243 |
--------------------------------------------------------------------------------
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621 | How to Apply These Terms to Your New Programs
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623 | If you develop a new program, and you want it to be of the greatest
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660 | For more information on this, and how to apply and follow the GNU AGPL, see
661 | .
662 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Using PyMuPDF in an RAG (Retrieval-Augmented Generation) Chatbot Environment
2 |
3 | This repository contains examples showing how PyMuPDF can be used as a data feed for RAG-based chatbots.
4 |
5 | Examples include scripts that start chatbots - either as simple CLI programs in REPL mode or browser-based GUIs.
6 | Chatbot scripts follow this general structure:
7 |
8 | 1. **Extract Text**: Use PyMuPDF to extract text from one or more pages from one or more PDFs. Depending on the specific requirement this may be all text or only text contained in tables, the Table of Contents, etc.
9 | This will generally be implemented as one or more Python functions called by any of the following events - which implement the actual chatbot functionality.
10 | 2. **Indexing the Extracted Text**: Index the extracted text for efficient retrieval. This index will act as the knowledge base for the chatbot.
11 | 3. **Query Processing**: When a user asks a question, process the query to determine the key information needed for a response.
12 | 4. **Retrieving Relevant Information**: Search your indexed knowledge base for the most relevant pieces of information related to the user's query.
13 | 5. **Generating a Response**: Use a generative model to generate a response based on the retrieved information.
14 |
15 | # Installation
16 |
17 | The Python package on PyPI [pymupdf4llm](https://pypi.org/project/pymupdf4llm/) (there also is an alias [pdf4llm](https://pypi.org/project/pdf4llm/)) is capable of converting PDF pages into **_text strings in Markdown format_** (GitHub compatible). This includes **standard text** as well as **table-based text** in a consistent and integrated view - a feature particularly important in RAG settings.
18 |
19 | ```bash
20 | $ pip install -U pymupdf4llm
21 | ```
22 |
23 | > This command will automatically install [PyMuPDF](https://github.com/pymupdf/PyMuPDF) if required.
24 |
25 | Then in your script do
26 |
27 | ```python
28 | import pymupdf4llm
29 |
30 | md_text = pymupdf4llm.to_markdown("input.pdf")
31 |
32 | # now work with the markdown text, e.g. store as a UTF8-encoded file
33 | import pathlib
34 | pathlib.Path("output.md").write_bytes(md_text.encode())
35 | ```
36 |
37 | Instead of the filename string as above, one can also provide a PyMuPDF `Document`. By default, all pages in the PDF will be processed. If desired, the parameter `pages=[...]` can be used to provide a list of zero-based page numbers to consider.
38 |
39 | Markdown text creation now also processes **multi-column pages**.
40 |
41 | To create small **chunks of text** - as opposed to generating one large string for the whole document - the new (v0.0.2) option `page_chunks=True` can be used. The result of `.to_markdown("input.pdf", page_chunks=True)` will be a list of Python dictionaries, one for each page.
42 |
43 | Also new in version 0.0.2 is the optional **extraction of images** and vector graphics: use of parameter `write_images=True`. The will store PNG images in the document's folder, and the Markdown text will appropriately refer to them. The images are named like `"input.pdf-page_number-index.png"`.
44 |
45 | # Documentation and API
46 |
47 | [Documentation](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/index.html)
48 |
49 | [API](https://pymupdf.readthedocs.io/en/latest/pymupdf4llm/api.html#pymupdf4llm-api)
50 |
51 | # Document Support
52 |
53 | While PDF is by far the most important document format worldwide, it is worthwhile mentioning that all examples and helper scripts work in the same way and **_without change_** for [all supported file types](https://pymupdf.readthedocs.io/en/latest/how-to-open-a-file.html#supported-file-types).
54 |
55 | So for an XPS document or an eBook, simply provide the filename for instance as `"input.mobi"` and everything else will work as before.
56 |
57 |
58 | # About PyMuPDF
59 | **PyMuPDF** adds **Python** bindings and abstractions to [MuPDF](https://mupdf.com/), a lightweight **PDF**, **XPS**, and **eBook** viewer, renderer, and toolkit. Both **PyMuPDF** and **MuPDF** are maintained and developed by [Artifex Software, Inc](https://artifex.com).
60 |
61 | PyMuPDF's homepage is located on [GitHub](https://github.com/pymupdf/PyMuPDF).
62 |
63 | # Community
64 | Join us on **Discord** here: [#pymupdf](https://discord.gg/TSpYGBW4eq).
65 |
66 | # License and Copyright
67 | **PyMuPDF** is available under [open-source AGPL](https://www.gnu.org/licenses/agpl-3.0.html) and commercial license agreements. If you determine you cannot meet the requirements of the **AGPL**, please contact [Artifex](https://artifex.com/contact/pymupdf-inquiry.php) for more information regarding a commercial license.
68 |
69 |
--------------------------------------------------------------------------------
/examples/GUI/README.md:
--------------------------------------------------------------------------------
1 | # Example of a Browser Application using Langchain and PyMuPDF
2 |
3 | ## Installation
4 | Please download this folder to your machine.
5 |
6 | Open a terminal and ensure that the required packages are on your system by executing the following commands. We also recommend to always update pip.
7 |
8 | ```bash
9 | pip install -U pip
10 | pip install -U langchain
11 | pip install -U langchain-community
12 | pip install -U langchain-openai
13 | pip install -U gradio
14 | pip install -U PyMuPDF
15 | ```
16 |
17 | ## Launching the Application
18 | Launch the application by executing the following command in a terminal opened in the downloaded folder:
19 |
20 | ```bash
21 | python browser-app.py
22 | ```
23 |
24 | After a few seconds the application will display instructions on how to start a session in your browser.
--------------------------------------------------------------------------------
/examples/GUI/browser-app.py:
--------------------------------------------------------------------------------
1 | """
2 | This code uses the PyMuPDF package.
3 |
4 | PyMuPDF is AGPL licensed, please refer to:
5 | https://pymupdf.readthedocs.io/en/latest/about.html#license-and-copyright
6 | """
7 |
8 | """
9 | Code below is based on an implementation by Sunil Kumar Dash:
10 |
11 | MIT License
12 |
13 | Copyright (c) 2023 Sunil Kumar Dash
14 |
15 | Permission is hereby granted, free of charge, to any person obtaining a copy
16 | of this software and associated documentation files (the "Software"), to deal
17 | in the Software without restriction, including without limitation the rights
18 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
19 | copies of the Software, and to permit persons to whom the Software is
20 | furnished to do so, subject to the following conditions:
21 |
22 | The above copyright notice and this permission notice shall be included in all
23 | copies or substantial portions of the Software.
24 |
25 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
26 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
27 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
28 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
29 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
30 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
31 | SOFTWARE.
32 | """
33 |
34 | from typing import Any
35 | import gradio as gr
36 | from langchain_openai import OpenAIEmbeddings
37 | from langchain_community.vectorstores import Chroma
38 |
39 | from langchain.chains import ConversationalRetrievalChain
40 | from langchain_openai import ChatOpenAI
41 |
42 | from langchain_community.document_loaders import PyMuPDFLoader
43 |
44 | import pymupdf
45 | from PIL import Image
46 | import os
47 | import re
48 | import uuid
49 |
50 | enable_box = gr.Textbox(
51 | value=None, placeholder="Upload your OpenAI API key", interactive=True
52 | )
53 | disable_box = gr.Textbox(value="OpenAI API key is set", interactive=False)
54 |
55 |
56 | def set_apikey(api_key: str):
57 | print("API Key set")
58 | app.OPENAI_API_KEY = api_key
59 | return disable_box
60 |
61 |
62 | def enable_api_box():
63 | return enable_box
64 |
65 |
66 | def add_text(history, text: str):
67 | if not text:
68 | raise gr.Error("enter text")
69 | history = history + [(text, "")]
70 | return history
71 |
72 |
73 | class my_app:
74 | def __init__(self, OPENAI_API_KEY: str = None) -> None:
75 | self.OPENAI_API_KEY: str = OPENAI_API_KEY
76 | self.chain = None
77 | self.chat_history: list = []
78 | self.N: int = 0
79 | self.count: int = 0
80 |
81 | def __call__(self, file: str) -> Any:
82 | if self.count == 0:
83 | self.chain = self.build_chain(file)
84 | self.count += 1
85 | return self.chain
86 |
87 | def process_file(self, file: str):
88 | loader = PyMuPDFLoader(file.name)
89 | documents = loader.load()
90 | pattern = r"/([^/]+)$"
91 | match = re.search(pattern, file.name)
92 | try:
93 | file_name = match.group(1)
94 | except:
95 | file_name = os.path.basename(file)
96 |
97 | return documents, file_name
98 |
99 | def build_chain(self, file: str):
100 | documents, file_name = self.process_file(file)
101 | # Load embeddings model
102 | embeddings = OpenAIEmbeddings(openai_api_key=self.OPENAI_API_KEY)
103 | pdfsearch = Chroma.from_documents(
104 | documents,
105 | embeddings,
106 | collection_name=file_name,
107 | )
108 | chain = ConversationalRetrievalChain.from_llm(
109 | ChatOpenAI(temperature=0.0, openai_api_key=self.OPENAI_API_KEY),
110 | retriever=pdfsearch.as_retriever(search_kwargs={"k": 1}),
111 | return_source_documents=True,
112 | )
113 | return chain
114 |
115 |
116 | def get_response(history, query, file):
117 | if not file:
118 | raise gr.Error(message="Upload a PDF")
119 | chain = app(file)
120 | result = chain(
121 | {"question": query, "chat_history": app.chat_history}, return_only_outputs=True
122 | )
123 | app.chat_history += [(query, result["answer"])]
124 | app.N = list(result["source_documents"][0])[1][1]["page"]
125 | for char in result["answer"]:
126 | history[-1][-1] += char
127 | yield history, ""
128 |
129 |
130 | def render_file(file):
131 | doc = pymupdf.open(file.name)
132 | page = doc[app.N]
133 | # Render the page as a PNG image with a resolution of 150 DPI
134 | pix = page.get_pixmap(dpi=150)
135 | image = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
136 | return image
137 |
138 |
139 | def purge_chat_and_render_first(file):
140 | print("purge_chat_and_render_first")
141 | # Purges the previous chat session so that the bot has no concept of previous documents
142 | app.chat_history = []
143 | app.count = 0
144 |
145 | # Use PyMuPDF to render the first page of the uploaded document
146 | doc = pymupdf.open(file.name)
147 | page = doc[0]
148 | # Render the page as a PNG image with a resolution of 150 DPI
149 | pix = page.get_pixmap(dpi=150)
150 | image = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
151 | return image, []
152 |
153 | app = my_app()
154 |
155 | with gr.Blocks() as demo:
156 | with gr.Column():
157 | with gr.Row():
158 |
159 | with gr.Column(scale=1):
160 | api_key = gr.Textbox(
161 | placeholder="Enter OpenAI API key and hit ",
162 | show_label=False,
163 | interactive=True
164 | )
165 |
166 | with gr.Row():
167 | with gr.Column(scale=2):
168 | with gr.Row():
169 | chatbot = gr.Chatbot(value=[], elem_id="chatbot")
170 | with gr.Row():
171 | txt = gr.Textbox(
172 | show_label=False,
173 | placeholder="Enter text and press submit",
174 | scale=2
175 | )
176 | submit_btn = gr.Button("submit", scale=1)
177 |
178 | with gr.Column(scale=1):
179 | with gr.Row():
180 | show_img = gr.Image(label="Upload PDF")
181 | with gr.Row():
182 | btn = gr.UploadButton("📁 upload a PDF", file_types=[".pdf"])
183 |
184 | api_key.submit(
185 | fn=set_apikey,
186 | inputs=[api_key],
187 | outputs=[
188 | api_key,
189 | ],
190 | )
191 |
192 | btn.upload(
193 | fn=purge_chat_and_render_first,
194 | inputs=[btn],
195 | outputs=[show_img, chatbot],
196 | )
197 |
198 | submit_btn.click(
199 | fn=add_text,
200 | inputs=[chatbot, txt],
201 | outputs=[
202 | chatbot,
203 | ],
204 | queue=False,
205 | ).success(
206 | fn=get_response, inputs=[chatbot, txt, btn], outputs=[chatbot, txt]
207 | ).success(
208 | fn=render_file, inputs=[btn], outputs=[show_img]
209 | )
210 |
211 | demo.queue()
212 | demo.launch()
213 |
--------------------------------------------------------------------------------
/examples/README.md:
--------------------------------------------------------------------------------
1 | # Examples
2 |
3 | These examples are used to support tutorial blog posts as follows:
4 |
5 |
6 | ## country-capitals
7 |
8 | See: [Creating a RAG Chatbot with ChatGPT and PyMuPDF](https://artifex.com/blog/creating-a-rag-chatbot-with-chatgpt-and-pymupdf)
9 |
10 |
11 |
12 | ## GUI
13 |
14 | See: [Building a RAG Chatbot GUI with the ChatGPT API and PyMuPDF](https://artifex.com/blog/building-a-rag-chatbot-gui-with-the-chatgpt-api-and-pymupdf)
15 |
16 |
--------------------------------------------------------------------------------
/examples/country-capitals/README.md:
--------------------------------------------------------------------------------
1 | # Demonstration of an RAG Chatbot Using PyMuPDF
2 |
3 | This script starts an OpenAI RAG (Retrieval Augmented Generation) chatbot.
4 |
5 | The data fed into to chatbot client are tabular data extracted from a 6-page
6 | PDF.
7 |
8 | ## How it Works
9 | The content of the data is a list of almost 200 countries, their capital
10 | cities, city population and its percentage of the country's total
11 | population.
12 |
13 | The script is started like any Python script and without parameters. Upon
14 | start, a function is invoked which calls PyMuPDF to read the PDF, extract the
15 | table data and return a CSV-like string containing the table's content.
16 |
17 | After the chatbot has finished interpreting the data, the user may start asking
18 | questions via Read-Evaluate-Print loop (REPL).
19 |
20 | ## Information Retrieved for Responses
21 | Remarkably, the chatbot "realizes" the geographic and demographic context
22 | established by the PDF's data. This enables it to access the right knowledge
23 | resources on the internet for completing the information required to answer the user
24 | questions.
25 |
26 | For example, it will understand it has to look up **cities** and **countries** when being
27 | asked for words that do not occur in the PDF.
28 |
29 | For instance, the country
30 | **Liechtenstein** is not in the PDF, but asking for it or its capital city,
31 | Vaduz will deliver correct information, including population numbers or
32 | short abstracts of city and country.
33 |
34 | ## Getting Started
35 |
36 | Execute all of the following commands in a terminal:
37 |
38 | ```bash
39 | python pip install -U pip
40 | python pip install -U pymupdf
41 | python pip install -U openai
42 | ```
43 |
44 | Visit https://github.com/openai/openai-cookbook to learn how to register on
45 | OpenAI's website and request an API key.
46 |
47 | Copy this folder to your machine, then edit the script, type in your API key in this line `API_KEY = "your OpenAI API key goes here"` and save. Then open a terminal in the folder and execute the following command:
48 |
49 | ```bash
50 | python country-capitals.py
51 | ```
52 |
53 | After a few seconds, the following should be displayed.
54 |
55 | ## Example Session
56 | Please note how the chatbot searches the internet for information required to answer the question whenever the loaded text is insufficient.
57 |
58 | ```bash
59 | Loaded 204 table rows from file 'national-capitals.pdf'.
60 |
61 | Ready - ask questions or exit with q/Q:
62 | ==> what is the capital of Germany?
63 | Response:
64 |
65 | The capital of Germany is Berlin.
66 | ----------
67 | ==> Berlin's population, absolute and relative?
68 | Response:
69 |
70 | Berlin's population as of 2021 is 3,677,472. This makes up about 4.4% of the total population of Germany.
71 | ----------
72 | ==> is Vaduz part of the text, and if not, do you know about it?
73 | Response:
74 |
75 | No, Vaduz is not part of the text. It is the capital of Liechtenstein.
76 | ----------
77 | ==> the 10 smallest capital cities of the world?
78 | Response:
79 |
80 | 1. Vatican City (Vatican City) - 0.44 km²
81 | 2. Ngerulmud (Palau) - 0.57 km²
82 | 3. San Marino (San Marino) - 7.09 km²
83 | 4. Monaco (Monaco) - 2.02 km²
84 | 5. Gibraltar (Gibraltar) - 6 km²
85 | 6. Tuvalu (Funafuti) - 2.18 km²
86 | 7. Nauru (Yaren) - 21 km²
87 | 8. Malta (Valletta) - 0.8 km²
88 | 9. Andorra la Vella (Andorra) - 12.86 km²
89 | 10.
90 | ----------
91 | ==> the 10 smallest capital cities in terms of population?
92 | Response:
93 |
94 | 1. Vatican City (Vatican City) - 453
95 | 2. Ngerulmud (Palau) - 271
96 | 3. Adamstown (Pitcairn Islands) - 40
97 | 4. Funafuti (Tuvalu) - 6,320
98 | 5. Alofi (Niue) - 597
99 | 6. Yaren (Nauru) - 747
100 | 7. South Tarawa (Kiribati) - 50,182
101 | 8. Stanley (Falkland Islands) - 2,460
102 | 9. Flying Fish Cove (Christmas Island) - 1,599
103 | 10. Roseau (Dominica) - 14,725
104 | ----------
105 | ```
106 |
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/examples/country-capitals/country-capitals.py:
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1 | """
2 | This script implements an RAG chatbot using OpenAI and PyMuPDF.
3 |
4 | It is intended as a simple example for demonstration purposes primarily.
5 |
6 | When the chatbot is started, it will call PyMuPDF to read a PDF that contains
7 | a list of countries, their capital cities and city populations.
8 |
9 | This call to PyMuPDF will happen only once. Thereafter, the user can start
10 | asking questions in a Read-Evaluate-Prompt loop - or end the session.
11 |
12 | Although the data in the PDF are of course limited, the user may ask questions
13 | that require accessing sources present in the internet and may refer to
14 | almost arbitrary geographic or demographic information.
15 |
16 | The chatbot is capable of integrating disparate information sources delivering
17 | a meaningful response.
18 | """
19 |
20 | import pymupdf
21 | import textwrap
22 | from openai import OpenAI
23 |
24 | # Example for reading the OpenAI API key
25 | API_KEY = "your OpenAI API key goes here"
26 |
27 | # create an OpenAI client using the API key
28 | client = OpenAI(api_key=API_KEY)
29 |
30 |
31 | def extract_text_from_pdf(pdf_path):
32 | """Read table content only of all pages in the document.
33 |
34 | Chatbots typically have limitations on the amount of data that can
35 | can be passed in (number of tokens).
36 |
37 | We therefore only extract information on the PDF's pages that are
38 | contained in tables.
39 | As we even know that the PDF actually contains ONE logical table
40 | that has been segmented for reporting purposes, our approach
41 | is the following:
42 | * The cell contents of each table row are joined into one string
43 | separated by ";".
44 | * If table segment on the first page also has an external header row,
45 | join the column names separated by ";". Also ignore any subsequent
46 | table row that equals the header string. This deals with table
47 | header repeat situations.
48 | """
49 | # open document
50 | doc = pymupdf.open(pdf_path)
51 |
52 | text = "" # we will return this string
53 | row_count = 0 # counts table rows
54 | header = "" # overall table header: output this only once!
55 |
56 | # iterate over the pages
57 | for page in doc:
58 | # only read the table rows on each page, ignore other content
59 | tables = page.find_tables() # a "TableFinder" object
60 | for table in tables:
61 |
62 | # on first page extract external column names if present
63 | if page.number == 0 and table.header.external:
64 | # build the overall table header string
65 | # technical note: incomplete / complex tables may have
66 | # "None" in some header cells. Just use empty string then.
67 | header = (
68 | ";".join(
69 | [
70 | name if name is not None else ""
71 | for name in table.header.names
72 | ]
73 | )
74 | + "\n"
75 | )
76 | text += header
77 | row_count += 1 # increase row counter
78 |
79 | # output the table body
80 | for row in table.extract(): # iterate over the table rows
81 |
82 | # again replace any "None" in cells by an empty string
83 | row_text = (
84 | ";".join([cell if cell is not None else "" for cell in row]) + "\n"
85 | )
86 | if row_text != header: # omit duplicates of header row
87 | text += row_text
88 | row_count += 1 # increase row counter
89 | doc.close() # close document
90 | print(f"Loaded {row_count} table rows from file '{doc.name}'.\n")
91 | return text
92 |
93 |
94 | # use model "gpt-3.5-turbo-instruct" for text
95 | def generate_response_with_chatgpt(prompt):
96 | response = client.completions.create(
97 | model="gpt-3.5-turbo-instruct", # Choose appropriate model
98 | prompt=prompt,
99 | max_tokens=150,
100 | n=1,
101 | stop=None,
102 | temperature=0.7,
103 | )
104 | return response.choices[0].text.strip()
105 |
106 |
107 | filename = "national-capitals.pdf"
108 | pdf_text = extract_text_from_pdf(filename)
109 |
110 | print("Ready - ask questions or exit with q/Q:")
111 | while True:
112 | user_query = input("==> ")
113 | if user_query.lower().strip() == "q":
114 | break
115 | prompt = pdf_text + "\n\n" + user_query
116 | response = generate_response_with_chatgpt(prompt)
117 | print("Response:\n")
118 | for line in textwrap.wrap(response, width=70):
119 | print(line)
120 | print("-" * 10)
121 |
--------------------------------------------------------------------------------
/examples/country-capitals/national-capitals.pdf:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/pymupdf/RAG/1c796f4d72c6582491430de321823c63412ddb26/examples/country-capitals/national-capitals.pdf
--------------------------------------------------------------------------------
/pdf4llm/README.md:
--------------------------------------------------------------------------------
1 | # Using PyMuPDF as Data Feeder in LLM / RAG Applications
2 |
3 | This package converts the pages of a PDF to text in Markdown format using [PyMuPDF](https://pypi.org/project/PyMuPDF/).
4 |
5 | Standard text and tables are detected, brought in the right reading sequence and then together converted to GitHub-compatible Markdown text.
6 |
7 | Header lines are identified via the font size and appropriately prefixed with one or more '#' tags.
8 |
9 | Bold, italic, mono-spaced text and code blocks are detected and formatted accordingly. Similar applies to ordered and unordered lists.
10 |
11 | By default, all document pages are processed. If desired, a subset of pages can be specified by providing a list of 0-based page numbers.
12 |
13 |
14 | # Installation
15 |
16 | ```bash
17 | $ pip install -U pdf4llm
18 | ```
19 |
20 | > This command will automatically install [PyMuPDF](https://github.com/pymupdf/PyMuPDF) if required.
21 |
22 | Then in your script do:
23 |
24 | ```python
25 | import pdf4llm
26 |
27 | md_text = pdf4llm.to_markdown("input.pdf")
28 |
29 | # now work with the markdown text, e.g. store as a UTF8-encoded file
30 | import pathlib
31 | pathlib.Path("output.md").write_bytes(md_text.encode())
32 | ```
33 |
34 | Instead of the filename string as above, one can also provide a PyMuPDF `Document`. By default, all pages in the PDF will be processed. If desired, the parameter `pages=[...]` can be used to provide a list of zero-based page numbers to consider.
35 |
36 | **New features as of v0.0.8:**
37 |
38 | * Support for pages with **_multiple text columns_**.
39 | * Support for **_image and vector graphics extraction_**:
40 |
41 | 1. Specify `pdf4llm.to_markdown("input.pdf", write_images=True)`. Default is `False`.
42 | 2. Each image or vector graphic on the page will be extracted and stored as a PNG image named `"input.pdf-pno-index.png"` in the folder of `"input.pdf"`. Where `pno` is the 0-based page number and `index` is some sequence number.
43 | 3. The image files will have width and height equal to the values on the page.
44 | 4. Any text contained in the images or graphics will not be extracted, but become visible as image parts.
45 |
46 | * Support for **page chunks**: Instead of returning one large string for the whole document, a list of dictionaries can be generated: one for each page. Specify `data = pdf4llm.to_markdown("input.pdf", page_chunks=True)`. Then, for instance the first item, `data[0]` will contain a dictionary for the first page with the text and some metadata.
47 |
48 | * As a first example for directly supporting LLM / RAG consumers, this version can output **LlamaIndex documents**:
49 |
50 | ```python
51 | import pdf4llm
52 |
53 | md_read = pdf4llm.LlamaMarkdownReader()
54 | data = md_read.load_data("input.pdf")
55 |
56 | # The result 'data' is of type List[LlamaIndexDocument]
57 | # Every list item contains metadata and the markdown text of 1 page.
58 | ```
59 |
60 | * A LlamaIndex document essentially corresponds to Python dictionary, where the markdown text of the page is one of the dictionary values. For instance the text of the first page is the the value of `data[0].to_dict().["text"]`.
61 | * For details, please consult LlamaIndex documentation.
62 | * Upon creation of the `LlamaMarkdownReader` all necessary LlamaIndex-related imports are executed. Required related package installations must have been done independently and will not be checked during pdf4llm installation.
--------------------------------------------------------------------------------
/pdf4llm/pdf4llm/__init__.py:
--------------------------------------------------------------------------------
1 | import pymupdf4llm
2 | from pymupdf4llm import *
3 |
4 |
5 | __version__ = pymupdf4llm.__version__
6 | version = pymupdf4llm.version
7 | version_tuple = pymupdf4llm.version_tuple
8 |
9 |
10 | def LlamaMarkdownReader(*args, **kwargs):
11 | from pymupdf4llm.llama import pdf_markdown_reader
12 |
13 | return pymupdf4llm.llama.pdf_markdown_reader.PDFMarkdownReader(*args, **kwargs)
14 |
--------------------------------------------------------------------------------
/pdf4llm/setup.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | import setuptools
4 |
5 | setup_py_cwd = os.path.dirname(__file__)
6 | with open(os.path.join(setup_py_cwd, "README.md"), encoding="utf-8") as f:
7 | readme = f.read()
8 |
9 | classifiers = [
10 | "Development Status :: 5 - Production/Stable",
11 | "Environment :: Console",
12 | "Intended Audience :: Developers",
13 | "Programming Language :: Python :: 3",
14 | "Topic :: Utilities",
15 | ]
16 | requires = ["pymupdf4llm==0.0.24"]
17 |
18 | setuptools.setup(
19 | name="pdf4llm",
20 | version="0.0.24",
21 | author="Artifex",
22 | author_email="support@artifex.com",
23 | description="PyMuPDF Utilities for LLM/RAG",
24 | packages=setuptools.find_packages(),
25 | long_description=readme,
26 | long_description_content_type="text/markdown",
27 | install_requires=requires,
28 | license="GNU AFFERO GPL 3.0",
29 | url="https://github.com/pymupdf/RAG",
30 | classifiers=classifiers,
31 | package_data={
32 | "pdf4llm": ["LICENSE"],
33 | },
34 | project_urls={
35 | "Documentation": "https://pymupdf.readthedocs.io/",
36 | "Source": "https://github.com/pymupdf/RAG/tree/main/pdf4llm/pdf4llm",
37 | "Tracker": "https://github.com/pymupdf/RAG/issues",
38 | "Changelog": "https://github.com/pymupdf/RAG/blob/main/CHANGES.md",
39 | },
40 | )
41 |
--------------------------------------------------------------------------------
/pymupdf4llm/README.md:
--------------------------------------------------------------------------------
1 | # Using PyMuPDF as Data Feeder in LLM / RAG Applications
2 |
3 | This package converts the pages of a PDF to text in Markdown format using [PyMuPDF](https://pypi.org/project/PyMuPDF/).
4 |
5 | Standard text and tables are detected, brought in the right reading sequence and then together converted to GitHub-compatible Markdown text.
6 |
7 | Header lines are identified via the font size and appropriately prefixed with one or more '#' tags.
8 |
9 | Bold, italic, mono-spaced text and code blocks are detected and formatted accordingly. Similar applies to ordered and unordered lists.
10 |
11 | By default, all document pages are processed. If desired, a subset of pages can be specified by providing a list of 0-based page numbers.
12 |
13 |
14 | # Installation
15 |
16 | ```bash
17 | $ pip install -U pymupdf4llm
18 | ```
19 |
20 | > This command will automatically install [PyMuPDF](https://github.com/pymupdf/PyMuPDF) if required.
21 |
22 | Then in your script do:
23 |
24 | ```python
25 | import pymupdf4llm
26 |
27 | md_text = pymupdf4llm.to_markdown("input.pdf")
28 |
29 | # now work with the markdown text, e.g. store as a UTF8-encoded file
30 | import pathlib
31 | pathlib.Path("output.md").write_bytes(md_text.encode())
32 | ```
33 |
34 | Instead of the filename string as above, one can also provide a PyMuPDF `Document`. By default, all pages in the PDF will be processed. If desired, the parameter `pages=[...]` can be used to provide a list of zero-based page numbers to consider.
35 |
36 | **Feature Overview:**
37 |
38 | * Support for pages with **_multiple text columns_**.
39 | * Support for **_image and vector graphics extraction_**:
40 |
41 | 1. Specify `pymupdf4llm.to_markdown("input.pdf", write_images=True)`. Default is `False`.
42 | 2. Each image or vector graphic on the page will be extracted and stored as an image named `"input.pdf-pno-index.extension"` in a folder of your choice. The image `extension` can be chosen to represent a PyMuPDF-supported image format (for instance "png" or "jpg"), `pno` is the 0-based page number and `index` is some sequence number.
43 | 3. The image files will have width and height equal to the values on the page. The desired resolution can be chosen via parameter `dpi` (default: `dpi=150`).
44 | 4. Any text contained in the images or graphics will be extracted and **also become visible as part of the generated image**. This behavior can be changed via `force_text=False` (text only apears as part of the image).
45 |
46 | * Support for **page chunks**: Instead of returning one large string for the whole document, a list of dictionaries can be generated: one for each page. Specify `data = pymupdf4llm.to_markdown("input.pdf", page_chunks=True)`. Then, for instance the first item, `data[0]` will contain a dictionary for the first page with the text and some metadata.
47 |
48 | * As a first example for directly supporting LLM / RAG consumers, this version can output **LlamaIndex documents**:
49 |
50 | ```python
51 | import pymupdf4llm
52 |
53 | md_read = pymupdf4llm.LlamaMarkdownReader()
54 | data = md_read.load_data("input.pdf")
55 |
56 | # The result 'data' is of type List[LlamaIndexDocument]
57 | # Every list item contains metadata and the markdown text of 1 page.
58 | ```
59 |
60 | * A LlamaIndex document essentially corresponds to Python dictionary, where the markdown text of the page is one of the dictionary values. For instance the text of the first page is the the value of `data[0].to_dict().["text"]`.
61 | * For details, please consult LlamaIndex documentation.
62 | * Upon creation of the `LlamaMarkdownReader` all necessary LlamaIndex-related imports are executed. Required related package installations must have been done independently and will not be checked during pymupdf4llm installation.
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/__init__.py:
--------------------------------------------------------------------------------
1 | from .helpers.pymupdf_rag import IdentifyHeaders, to_markdown
2 |
3 | __version__ = "0.0.24"
4 | version = __version__
5 | version_tuple = tuple(map(int, version.split(".")))
6 |
7 |
8 | def LlamaMarkdownReader(*args, **kwargs):
9 | from .llama import pdf_markdown_reader
10 |
11 | return pdf_markdown_reader.PDFMarkdownReader(*args, **kwargs)
12 |
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/helpers/get_text_lines.py:
--------------------------------------------------------------------------------
1 | """
2 | This script accepts a PDF document filename and converts it to a text file.
3 |
4 |
5 | Dependencies
6 | -------------
7 | PyMuPDF v1.24.2 or later
8 |
9 | Copyright and License
10 | ----------------------
11 | Copyright 2024 Artifex Software, Inc.
12 | License GNU Affero GPL 3.0
13 | """
14 |
15 | import string
16 | import sys
17 |
18 | import pymupdf
19 |
20 | WHITE = set(string.whitespace)
21 |
22 |
23 | def is_white(text):
24 | return WHITE.issuperset(text)
25 |
26 |
27 | def get_raw_lines(
28 | textpage,
29 | clip=None,
30 | tolerance=3,
31 | ignore_invisible=True,
32 | ):
33 | """Extract the text spans from a TextPage in natural reading sequence.
34 |
35 | All spans roughly on the same line are joined to generate an improved line.
36 | This copes with MuPDF's algorithm that generates new lines also for spans
37 | whose horizontal distance is larger than some threshold.
38 |
39 | Result is a sorted list of line objects that consist of the recomputed line
40 | boundary box and the sorted list of spans in that line.
41 |
42 | This result can then easily be converted e.g. to plain text and other
43 | formats like Markdown or JSON.
44 |
45 | Args:
46 | textpage: (mandatory) TextPage object
47 | clip: (Rect) specifies a sub-rectangle of the textpage rect (which in
48 | turn may be based on a sub-rectangle of the full page).
49 | tolerance: (float) put spans on the same line if their top or bottom
50 | coordinate differ by no more than this value.
51 | ignore_invisible: (bool) if True, invisible text is ignored. This may
52 | have been set to False for pages with OCR text.
53 |
54 | Returns:
55 | A sorted list of items (rect, [spans]), each representing one line. The
56 | spans are sorted left to right. Span dictionaries have been changed:
57 | - "bbox" has been converted to a Rect object
58 | - "line" (new) the line number in TextPage.extractDICT
59 | - "block" (new) the block number in TextPage.extractDICT
60 | This allows to detect where MuPDF has generated line breaks to indicate
61 | large inter-span distances.
62 | """
63 | y_delta = tolerance # allowable vertical coordinate deviation
64 |
65 | def sanitize_spans(line):
66 | """Sort and join the spans in a re-synthesized line.
67 |
68 | The PDF may contain "broken" text with words cut into pieces.
69 | This funtion joins spans representing the particles and sorts them
70 | left to right.
71 |
72 | Arg:
73 | A list of spans - as drived from TextPage.extractDICT()
74 | Returns:
75 | A list of sorted, and potentially cleaned-up spans
76 | """
77 | # sort ascending horizontally
78 | line.sort(key=lambda s: s["bbox"].x0)
79 | # join spans, delete duplicates
80 | for i in range(len(line) - 1, 0, -1): # iterate back to front
81 | s0 = line[i - 1] # preceding span
82 | s1 = line[i] # this span
83 | # "delta" depends on the font size. Spans will be joined if
84 | # no more than 10% of the font size separates them and important
85 | # attributes are the same.
86 | delta = s1["size"] * 0.1
87 | if s0["bbox"].x1 + delta < s1["bbox"].x0 or (
88 | s0["flags"],
89 | s0["char_flags"],
90 | s0["size"],
91 | ) != (s1["flags"], s1["char_flags"], s1["size"]):
92 | continue # no joining
93 | # We need to join bbox and text of two consecutive spans
94 | # On occasion, spans may also be duplicated.
95 | if s0["text"] != s1["text"] or s0["bbox"] != s1["bbox"]:
96 | s0["text"] += s1["text"]
97 | s0["bbox"] |= s1["bbox"] # join boundary boxes
98 | del line[i] # delete the joined-in span
99 | line[i - 1] = s0 # update the span
100 | return line
101 |
102 | if clip is None: # use TextPage rect if not provided
103 | clip = textpage.rect
104 | # extract text blocks - if bbox is not empty
105 | blocks = [
106 | b
107 | for b in textpage.extractDICT()["blocks"]
108 | if b["type"] == 0 and not pymupdf.Rect(b["bbox"]).is_empty
109 | ]
110 | spans = [] # all spans in TextPage here
111 | for bno, b in enumerate(blocks): # the numbered blocks
112 | for lno, line in enumerate(b["lines"]): # the numbered lines
113 | if abs(1 - line["dir"][0]) > 1e-3: # only accept horizontal text
114 | continue
115 | for sno, s in enumerate(line["spans"]): # the numered spans
116 | sbbox = pymupdf.Rect(s["bbox"]) # span bbox as a Rect
117 | if is_white(s["text"]): # ignore white text
118 | continue
119 | # ignore invisible text
120 | if s["alpha"] == 0 and ignore_invisible:
121 | continue
122 | if abs(sbbox & clip) < abs(sbbox) * 0.8: # if not in clip
123 | continue
124 | if s["flags"] & 1 == 1: # if a superscript, modify bbox
125 | # with that of the preceding or following span
126 | i = 1 if sno == 0 else sno - 1
127 | if len(line["spans"]) > i:
128 | neighbor = line["spans"][i]
129 | sbbox.y1 = neighbor["bbox"][3]
130 | s["text"] = f"[{s['text']}]"
131 | s["bbox"] = sbbox # update with the Rect version
132 | # include line/block numbers to facilitate separator insertion
133 | s["line"] = lno
134 | s["block"] = bno
135 | spans.append(s)
136 |
137 | if not spans: # no text at all
138 | return []
139 |
140 | spans.sort(key=lambda s: s["bbox"].y1) # sort spans by bottom coord
141 | nlines = [] # final result
142 | line = [spans[0]] # collects spans with fitting vertical coordinates
143 | lrect = spans[0]["bbox"] # rectangle joined from span rectangles
144 |
145 | for s in spans[1:]: # walk through the spans
146 | sbbox = s["bbox"] # this bbox
147 | sbbox0 = line[-1]["bbox"] # previous bbox
148 | # if any of top or bottom coordinates are close enough, join...
149 | if abs(sbbox.y1 - sbbox0.y1) <= y_delta or abs(sbbox.y0 - sbbox0.y0) <= y_delta:
150 | line.append(s) # append to this line
151 | lrect |= sbbox # extend line rectangle
152 | continue
153 |
154 | # end of current line, sort its spans from left to right
155 | line = sanitize_spans(line)
156 |
157 | # append line rect and its spans to final output
158 | nlines.append([lrect, line])
159 |
160 | line = [s] # start next line
161 | lrect = sbbox # initialize its rectangle
162 |
163 | # need to append last line in the same way
164 | line = sanitize_spans(line)
165 | nlines.append([lrect, line])
166 |
167 | return nlines
168 |
169 |
170 | def get_text_lines(page, *, textpage=None, clip=None, sep="\t", tolerance=3, ocr=False):
171 | """Extract text by line keeping natural reading sequence.
172 |
173 | Notes:
174 | Internally uses "dict" to select lines and their spans.
175 | Returns plain text. If originally separate MuPDF lines in fact have
176 | (approximatly) the same baseline, they are joined into one line using
177 | the 'sep' character(s).
178 | This method can be used to extract text in reading sequence - even in
179 | cases of text replaced by way of redaction annotations.
180 |
181 | Args:
182 | page: (pymupdf.Page)
183 | textpage: (TextPage) if None a temporary one is created.
184 | clip: (rect-like) only consider spans inside this area
185 | sep: (str) use this string when joining multiple MuPDF lines.
186 | Returns:
187 | String of plain text in reading sequence.
188 | """
189 | textflags = pymupdf.TEXT_MEDIABOX_CLIP
190 | page.remove_rotation()
191 | prect = page.rect if not clip else pymupdf.Rect(clip) # area to consider
192 |
193 | xsep = sep if sep == "|" else ""
194 |
195 | # make a TextPage if required
196 | if textpage is None:
197 | if ocr is False:
198 | tp = page.get_textpage(clip=prect, flags=textflags)
199 | else:
200 | tp = page.get_textpage_ocr(dpi=300, full=True)
201 | else:
202 | tp = textpage
203 |
204 | lines = get_raw_lines(tp, clip=prect, tolerance=tolerance)
205 |
206 | if not textpage: # delete temp TextPage
207 | tp = None
208 |
209 | if not lines:
210 | return ""
211 |
212 | # Compose final text
213 | alltext = ""
214 |
215 | if not ocr:
216 | prev_bno = -1 # number of previous text block
217 | for lrect, line in lines: # iterate through lines
218 | # insert extra line break if a different block
219 | bno = line[0]["block"] # block number of this line
220 | if bno != prev_bno:
221 | alltext += "\n"
222 | prev_bno = bno
223 |
224 | line_no = line[0]["line"] # store the line number of previous span
225 | for s in line: # walk over the spans in the line
226 | lno = s["line"]
227 | stext = s["text"]
228 | if line_no == lno:
229 | alltext += stext
230 | else:
231 | alltext += sep + stext
232 | line_no = lno
233 | alltext += "\n" # append line break after a line
234 | alltext += "\n" # append line break at end of block
235 | return alltext
236 |
237 | """
238 | For OCR output, we try a rudimentary table recognition.
239 | """
240 | rows = []
241 | xvalues = []
242 | for lrect, line in lines:
243 | # if only 1 span in line and no columns identified yet...
244 | if len(line) == 1 and not xvalues:
245 | alltext += line[0]["text"] + "\n\n\n"
246 | continue
247 | # multiple spans in line and no columns identified yet
248 | elif not xvalues: # define column borders
249 | xvalues = [s["bbox"].x0 for s in line] + [line[-1]["bbox"].x1]
250 | col_count = len(line) # number of columns
251 | row = [""] * col_count
252 | for r, l in line:
253 | for i in range(len(xvalues) - 1):
254 | x0, x1 = xvalues[i], xvalues[i + 1]
255 | if abs(r.x0 - x0) <= 3 or abs(r.x1 - x1) <= 3:
256 | row[i] = l
257 | rows.append(row)
258 | if rows:
259 | row = "|" + "|".join(rows[0]) + "|\n"
260 | alltext += row
261 | alltext += "|---" * len(rows[0]) + "|\n"
262 | for row in rows[1:]:
263 | alltext += "|" + "|".join(row) + "|\n"
264 | alltext += "\n"
265 | return alltext
266 |
267 |
268 | if __name__ == "__main__":
269 | import pathlib
270 |
271 | filename = sys.argv[1]
272 | doc = pymupdf.open(filename)
273 | text = ""
274 | for page in doc:
275 | text += get_text_lines(page, sep=" ") + "\n" + chr(12) + "\n"
276 | pathlib.Path(f"{doc.name}.txt").write_bytes(text.encode())
277 |
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/helpers/multi_column.py:
--------------------------------------------------------------------------------
1 | """
2 | This is an advanced PyMuPDF utility for detecting multi-column pages.
3 | It can be used in a shell script, or its main function can be imported and
4 | invoked as descript below.
5 |
6 | Features
7 | ---------
8 | - Identify text belonging to (a variable number of) columns on the page.
9 | - Text with different background color is handled separately, allowing for
10 | easier treatment of side remarks, comment boxes, etc.
11 | - Uses text block detection capability to identify text blocks and
12 | uses the block bboxes as primary structuring principle.
13 | - Supports ignoring footers via a footer margin parameter.
14 | - Returns re-created text boundary boxes (integer coordinates), sorted ascending
15 | by the top, then by the left coordinates.
16 |
17 | Restrictions
18 | -------------
19 | - Only supporting horizontal, left-to-right text
20 | - Returns a list of text boundary boxes - not the text itself. The caller is
21 | expected to extract text from within the returned boxes.
22 | - Text written above images is ignored altogether (option).
23 | - This utility works as expected in most cases. The following situation cannot
24 | be handled correctly:
25 | * overlapping (non-disjoint) text blocks
26 | * image captions are not recognized and are handled like normal text
27 |
28 | Usage
29 | ------
30 | - As a CLI shell command use
31 |
32 | python multi_column.py input.pdf footer_margin header_margin
33 |
34 | Where margins are the height of the bottom / top stripes to ignore on each
35 | page.
36 | This code is intended to be modified according to your need.
37 |
38 | - Use in a Python script as follows:
39 |
40 | ----------------------------------------------------------------------------------
41 | from multi_column import column_boxes
42 |
43 | # for each page execute
44 | bboxes = column_boxes(page, footer_margin=50, no_image_text=True)
45 |
46 | bboxes is a list of pymupdf.IRect objects, that are sorted ascending by their
47 | y0, then x0 coordinates. Their text content can be extracted by all PyMuPDF
48 | get_text() variants, like for instance the following:
49 | for rect in bboxes:
50 | print(page.get_text(clip=rect, sort=True))
51 | ----------------------------------------------------------------------------------
52 |
53 | Dependencies
54 | -------------
55 | PyMuPDF v1.24.2 or later
56 |
57 | Copyright and License
58 | ----------------------
59 | Copyright 2024 Artifex Software, Inc.
60 | License GNU Affero GPL 3.0
61 | """
62 |
63 | import string
64 |
65 | import pymupdf
66 |
67 | pymupdf.TOOLS.unset_quad_corrections(True)
68 |
69 |
70 | def column_boxes(
71 | page,
72 | *,
73 | footer_margin=50,
74 | header_margin=50,
75 | no_image_text=True,
76 | textpage=None,
77 | paths=None,
78 | avoid=None,
79 | ignore_images=False,
80 | ):
81 | """Determine bboxes which wrap a column on the page.
82 |
83 | Args:
84 | footer_margin: ignore text if distance from bottom is less
85 | header_margin: ignore text if distance from top is less
86 | no_image_text: ignore text inside image bboxes
87 | textpage: use this textpage instead of creating one
88 | paths: use these drawings instead of extracting here
89 | avoid: ignore text in any of these areas
90 | """
91 | WHITE = set(string.whitespace)
92 |
93 | def is_white(text):
94 | """Check for relevant text."""
95 | return WHITE.issuperset(text)
96 |
97 | def in_bbox(bb, bboxes):
98 | """Return 1-based number if a bbox contains bb, else return 0."""
99 | for i, bbox in enumerate(bboxes, start=1):
100 | if bb in bbox:
101 | return i
102 | return 0
103 |
104 | def in_bbox_using_cache(bb, bboxes, cache):
105 | """Return 1-based number if a bbox contains bb, else return 0."""
106 | """Results are stored in the cache for speedup."""
107 | cache_key = f"{id(bb)}_{id(bboxes)}"
108 | cached = cache.get(cache_key)
109 | if cached is not None:
110 | return cached
111 |
112 | index = 0
113 | for i, bbox in enumerate(bboxes, start=1):
114 | if bb in bbox:
115 | index = i
116 | break
117 |
118 | cache[cache_key] = index
119 | return index
120 |
121 | def intersects_bboxes(bb, bboxes):
122 | """Return True if a bbox touches bb, else return False."""
123 | for bbox in bboxes:
124 | if not (bb & bbox).is_valid:
125 | return True
126 | return False
127 |
128 | def can_extend(temp, bb, bboxlist, vert_bboxes):
129 | """Determines whether rectangle 'temp' can be extended by 'bb'
130 | without intersecting any of the rectangles contained in 'bboxlist'
131 | or 'vert_bboxes'.
132 |
133 | Items of bboxlist may be None if they have been removed.
134 |
135 | Returns:
136 | True if 'temp' has no intersections with items of 'bboxlist'.
137 | """
138 | for b in bboxlist:
139 | if not intersects_bboxes(temp, vert_bboxes) and (
140 | b is None or b == bb or (temp & b).is_empty
141 | ):
142 | continue
143 | return False
144 |
145 | return True
146 |
147 | def clean_nblocks(nblocks):
148 | """Do some elementary cleaning."""
149 |
150 | # 1. remove any duplicate blocks.
151 | blen = len(nblocks)
152 | if blen < 2:
153 | return nblocks
154 | start = blen - 1
155 | for i in range(start, -1, -1):
156 | bb1 = nblocks[i]
157 | bb0 = nblocks[i - 1]
158 | if bb0 == bb1:
159 | del nblocks[i]
160 |
161 | if len(nblocks) == 0:
162 | return nblocks
163 |
164 | # 2. repair sequence in special cases:
165 | # consecutive bboxes with almost same bottom value are sorted ascending
166 | # by x-coordinate.
167 | y1 = nblocks[0].y1 # first bottom coordinate
168 | i0 = 0 # its index
169 | i1 = -1 # index of last bbox with same bottom
170 |
171 | # Iterate over bboxes, identifying segments with approx. same bottom value.
172 | # Replace every segment by its sorted version.
173 | for i in range(1, len(nblocks)):
174 | b1 = nblocks[i]
175 | if abs(b1.y1 - y1) > 3: # different bottom
176 | if i1 > i0: # segment length > 1? Sort it!
177 | nblocks[i0 : i1 + 1] = sorted(
178 | nblocks[i0 : i1 + 1], key=lambda b: b.x0
179 | )
180 | y1 = b1.y1 # store new bottom value
181 | i0 = i # store its start index
182 | i1 = i # store current index
183 | if i1 > i0: # segment waiting to be sorted
184 | nblocks[i0 : i1 + 1] = sorted(nblocks[i0 : i1 + 1], key=lambda b: b.x0)
185 | return nblocks
186 |
187 | def join_rects_phase1(bboxes):
188 | """Postprocess identified text blocks, phase 1.
189 |
190 | Joins any rectangles that "touch" each other.
191 | This means that their intersection is valid (but may be empty).
192 | To prefer vertical joins, we will ignore small gaps.
193 | """
194 | delta = (0, 0, 0, 10) # allow this gap below
195 | prects = bboxes[:]
196 | new_rects = []
197 | while prects:
198 | prect0 = prects[0]
199 | repeat = True
200 | while repeat:
201 | repeat = False
202 | for i in range(len(prects) - 1, 0, -1):
203 | if ((prect0 + delta) & prects[i]).is_valid:
204 | prect0 |= prects[i]
205 | del prects[i]
206 | repeat = True
207 | new_rects.append(prect0)
208 | del prects[0]
209 | return new_rects
210 |
211 | def join_rects_phase2(bboxes):
212 | """Postprocess identified text blocks, phase 2.
213 |
214 | Increase the width of each text block so that small left or right
215 | border differences are removed. Then try to join even more text
216 | rectangles.
217 | """
218 | prects = bboxes[:] # copy of argument list
219 | for i in range(len(prects)):
220 | b = prects[i]
221 | # go left and right somewhat
222 | x0 = min([bb.x0 for bb in prects if abs(bb.x0 - b.x0) <= 3])
223 | x1 = max([bb.x1 for bb in prects if abs(bb.x1 - b.x1) <= 3])
224 | b.x0 = x0 # store new left / right border
225 | b.x1 = x1
226 | prects[i] = b
227 |
228 | # sort by left, top
229 | prects.sort(key=lambda b: (b.x0, b.y0))
230 | new_rects = [prects[0]] # initialize with first item
231 |
232 | # walk through the rest, top to bottom, then left to right
233 | for r in prects[1:]:
234 | r0 = new_rects[-1] # previous bbox
235 |
236 | # join if we have similar borders and are not too far down
237 | if (
238 | abs(r.x0 - r0.x0) <= 3
239 | and abs(r.x1 - r0.x1) <= 3
240 | and abs(r0.y1 - r.y0) <= 10
241 | ):
242 | r0 |= r
243 | new_rects[-1] = r0
244 | continue
245 | # else append this as new text block
246 | new_rects.append(r)
247 | return new_rects
248 |
249 | def join_rects_phase3(bboxes, path_rects, cache):
250 | prects = bboxes[:]
251 | new_rects = []
252 |
253 | while prects:
254 | prect0 = prects[0]
255 | repeat = True
256 | while repeat:
257 | repeat = False
258 | for i in range(len(prects) - 1, 0, -1):
259 | prect1 = prects[i]
260 | # do not join across columns
261 | if prect1.x0 > prect0.x1 or prect1.x1 < prect0.x0:
262 | continue
263 |
264 | # do not join different backgrounds
265 | if in_bbox_using_cache(
266 | prect0, path_rects, cache
267 | ) != in_bbox_using_cache(prect1, path_rects, cache):
268 | continue
269 | temp = prect0 | prect1
270 | test = set(
271 | [tuple(b) for b in prects + new_rects if b.intersects(temp)]
272 | )
273 | if test == set((tuple(prect0), tuple(prect1))):
274 | prect0 |= prect1
275 | prects[0] = prect0
276 | del prects[i]
277 | repeat = True
278 | new_rects.append(prect0)
279 | del prects[0]
280 |
281 | """
282 | Hopefully the most reasonable sorting sequence:
283 | At this point we have finished identifying blocks that wrap text.
284 | We now need to determine the SEQUENCE by which text extraction from
285 | these blocks should take place. This is hardly possible with 100%
286 | certainty. Our sorting approach is guided by the following thought:
287 | 1. Extraction should start with the block whose top-left corner is the
288 | left-most and top-most.
289 | 2. Any blocks further to the right should be extracted later - even if
290 | their top-left corner is higher up on the page.
291 | 3. Sorting the identified rectangles must therefore happen using a
292 | tuple (y, x) as key, where y is not smaller (= higher up) than that
293 | of the left-most block with a non-empty vertical overlap.
294 | 4. To continue "left block" with "next is ...", its sort key must be
295 | Q +---------+ tuple (P.y, Q.x).
296 | | next is |
297 | P +-------+ | this |
298 | | left | | block |
299 | | block | +---------+
300 | +-------+
301 | """
302 | sort_rects = [] # copy of "new_rects" with a computed sort key
303 | for box in new_rects:
304 | # search for the left-most rect that overlaps like "P" above
305 | # candidates must have the same background
306 | background = in_bbox(box, path_rects) # this background
307 | left_rects = sorted(
308 | [
309 | r
310 | for r in new_rects
311 | if r.x1 < box.x0
312 | and (box.y0 <= r.y0 <= box.y1 or box.y0 <= r.y1 <= box.y1)
313 | # and in_bbox(r, path_rects) == background
314 | ],
315 | key=lambda r: r.x1,
316 | )
317 | if left_rects: # if a "P" rectangle was found ...
318 | key = (left_rects[-1].y0, box.x0) # use this key
319 | else:
320 | key = (box.y0, box.x0) # else use the original (Q.y, Q.x).
321 | sort_rects.append((box, key))
322 | sort_rects.sort(key=lambda sr: sr[1]) # by computed key
323 | new_rects = [sr[0] for sr in sort_rects] # extract sorted rectangles
324 |
325 | # move text rects with background color into a separate list
326 | shadow_rects = []
327 | # for i in range(len(new_rects) - 1, 0, -1):
328 | # r = +new_rects[i]
329 | # if in_bbox(r, path_rects): # text with shaded background
330 | # shadow_rects.insert(0, r) # put in front to keep sequence
331 | # del new_rects[i]
332 | return new_rects + shadow_rects
333 |
334 | # compute relevant page area
335 | clip = +page.rect
336 | clip.y1 -= footer_margin # Remove footer area
337 | clip.y0 += header_margin # Remove header area
338 |
339 | if paths is None:
340 | paths = [
341 | p
342 | for p in page.get_drawings()
343 | if p["rect"].width < clip.width and p["rect"].height < clip.height
344 | ]
345 |
346 | if textpage is None:
347 | textpage = page.get_textpage(clip=clip, flags=pymupdf.TEXT_ACCURATE_BBOXES)
348 |
349 | bboxes = []
350 |
351 | # image bboxes
352 | img_bboxes = []
353 | if avoid is not None:
354 | img_bboxes.extend(avoid)
355 |
356 | # non-horizontal text boxes, avoid when expanding other text boxes
357 | vert_bboxes = []
358 |
359 | # path rectangles
360 | path_rects = []
361 | for p in paths:
362 | # give empty path rectangles some small width or height
363 | prect = p["rect"]
364 | lwidth = 0.5 if (_ := p["width"]) is None else _ * 0.5
365 |
366 | if prect.width == 0:
367 | prect.x0 -= lwidth
368 | prect.x1 += lwidth
369 | if prect.height == 0:
370 | prect.y0 -= lwidth
371 | prect.y1 += lwidth
372 | path_rects.append(prect)
373 |
374 | # sort path bboxes by ascending top, then left coordinates
375 | path_rects.sort(key=lambda b: (b.y0, b.x0))
376 |
377 | # bboxes of images on page, no need to sort them
378 | if ignore_images is False:
379 | for item in page.get_images():
380 | img_bboxes.extend(page.get_image_rects(item[0]))
381 |
382 | # blocks of text on page
383 | blocks = textpage.extractDICT()["blocks"]
384 |
385 | # Make block rectangles, ignoring non-horizontal text
386 | for b in blocks:
387 | bbox = pymupdf.Rect(b["bbox"]) # bbox of the block
388 |
389 | # ignore text written upon images
390 | if no_image_text and in_bbox(bbox, img_bboxes):
391 | continue
392 |
393 | # confirm first line to be horizontal
394 | try:
395 | line0 = b["lines"][0] # get first line
396 | except IndexError:
397 | continue
398 |
399 | if abs(1 - line0["dir"][0]) > 1e-3: # only (almost) horizontal text
400 | vert_bboxes.append(bbox) # a block with non-horizontal text
401 | continue
402 |
403 | srect = pymupdf.EMPTY_RECT()
404 | for line in b["lines"]:
405 | lbbox = pymupdf.Rect(line["bbox"])
406 | text = "".join([s["text"] for s in line["spans"]])
407 | if not is_white(text):
408 | srect |= lbbox
409 | bbox = +srect
410 |
411 | if not bbox.is_empty:
412 | bboxes.append(bbox)
413 |
414 | # Sort text bboxes by ascending background, top, then left coordinates
415 | bboxes.sort(key=lambda k: (in_bbox(k, path_rects), k.y0, k.x0))
416 |
417 | # immediately return of no text found
418 | if bboxes == []:
419 | return []
420 | # --------------------------------------------------------------------
421 | # Join bboxes to establish some column structure
422 | # --------------------------------------------------------------------
423 | # the final block bboxes on page
424 | nblocks = [bboxes[0]] # pre-fill with first bbox
425 | bboxes = bboxes[1:] # remaining old bboxes
426 | cache = {}
427 |
428 | for i, bb in enumerate(bboxes): # iterate old bboxes
429 | check = False # indicates unwanted joins
430 |
431 | # check if bb can extend one of the new blocks
432 | for j in range(len(nblocks)):
433 | nbb = nblocks[j] # a new block
434 |
435 | # never join across columns
436 | if bb is None or nbb.x1 < bb.x0 or bb.x1 < nbb.x0:
437 | continue
438 |
439 | # never join across different background colors
440 | if in_bbox_using_cache(nbb, path_rects, cache) != in_bbox_using_cache(
441 | bb, path_rects, cache
442 | ):
443 | continue
444 |
445 | temp = bb | nbb # temporary extension of new block
446 | check = can_extend(temp, nbb, nblocks, vert_bboxes)
447 | if check is True:
448 | break
449 |
450 | if not check: # bb cannot be used to extend any of the new bboxes
451 | nblocks.append(bb) # so add it to the list
452 | j = len(nblocks) - 1 # index of it
453 | temp = nblocks[j] # new bbox added
454 |
455 | # check if some remaining bbox is contained in temp
456 | check = can_extend(temp, bb, bboxes, vert_bboxes)
457 | if check is False:
458 | nblocks.append(bb)
459 | else:
460 | nblocks[j] = temp
461 | bboxes[i] = None
462 |
463 | # do some elementary cleaning
464 | nblocks = clean_nblocks(nblocks)
465 | if len(nblocks) == 0:
466 | return nblocks
467 |
468 | # several phases of rectangle joining
469 | # TODO: disabled for now as too aggressive:
470 | # nblocks = join_rects_phase1(nblocks)
471 | nblocks = join_rects_phase2(nblocks)
472 | nblocks = join_rects_phase3(nblocks, path_rects, cache)
473 |
474 | # return identified text bboxes
475 | return nblocks
476 |
477 |
478 | if __name__ == "__main__":
479 | """Only for debugging purposes, currently.
480 |
481 | Draw red borders around the returned text bboxes and insert
482 | the bbox number.
483 | Then save the file under the name "input-blocks.pdf".
484 | """
485 | import sys
486 |
487 | RED = pymupdf.pdfcolor["red"]
488 | # get the file name
489 | filename = sys.argv[1]
490 |
491 | # check if footer margin is given
492 | if len(sys.argv) > 2:
493 | footer_margin = int(sys.argv[2])
494 | else:
495 | footer_margin = 0
496 |
497 | # check if header margin is given
498 | if len(sys.argv) > 3:
499 | header_margin = int(sys.argv[3])
500 | else:
501 | header_margin = 0
502 |
503 | # open document
504 | doc = pymupdf.open(filename)
505 |
506 | # iterate over the pages
507 | for page in doc:
508 | # get the text bboxes
509 | bboxes = column_boxes(
510 | page, footer_margin=footer_margin, header_margin=header_margin
511 | )
512 |
513 | # prepare a canvas to draw rectangles and text
514 | shape = page.new_shape()
515 |
516 | # iterate over the bboxes
517 | for i, rect in enumerate(bboxes):
518 | shape.draw_rect(rect) # draw a border
519 |
520 | # write sequence number
521 | shape.insert_text(rect.tl + (5, 15), str(i), color=RED)
522 |
523 | # finish drawing / text with color red
524 | shape.finish(color=RED)
525 | shape.commit() # store to the page
526 |
527 | # save document with text bboxes
528 | doc.ez_save(filename.replace(".pdf", "-blocks.pdf"))
529 |
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/helpers/progress.py:
--------------------------------------------------------------------------------
1 | """
2 | This script defines a text-based progress bar to allow watching the advancement
3 | of Markdown conversion of document pages.
4 |
5 | Dependencies
6 | -------------
7 | None
8 |
9 | Copyright and License
10 | ----------------------
11 | Copyright 2024 Artifex Software, Inc.
12 | License GNU Affero GPL 3.0
13 | """
14 |
15 | import sys
16 | from typing import Any, List
17 |
18 |
19 | class _ProgressBar:
20 | def __init__(self, items: List[Any], progress_width: int = 40):
21 | self._len = len(items)
22 | self._iter = iter(items)
23 | self._len_digits = len(str(self._len))
24 | self._progress_width = progress_width
25 | self._progress_bar = 0
26 | self._current_index = 0
27 |
28 | # Calculate the increment for each item based on the list length and the progress width
29 | self._increment = self._progress_width / self._len if self._len else 1
30 |
31 | # Init progress bar
32 | sys.stdout.write(
33 | "[%s] (0/%d)" % (" " * self._progress_width, self._len)
34 | )
35 | sys.stdout.flush()
36 | sys.stdout.write(
37 | "\b" * (self._progress_width + len(str(self._len)) + 6)
38 | )
39 |
40 | def __iter__(self):
41 | return self
42 |
43 | def __next__(self):
44 | try:
45 | result = next(self._iter)
46 | except StopIteration as e:
47 | # End progress on StopIteration
48 | sys.stdout.write("]\n")
49 | raise e
50 |
51 | # Update the current index
52 | self._current_index += 1
53 |
54 | # Add the increment to the progress bar and calculate how many "=" to add
55 | self._progress_bar += self._increment
56 | while self._progress_bar >= 1:
57 | sys.stdout.write("=")
58 | sys.stdout.flush()
59 | self._progress_bar -= 1
60 |
61 | # Update the numerical progress
62 | padded_index = str(self._current_index).rjust(self._len_digits)
63 | progress_info = f" ({padded_index}/{self._len})"
64 | sys.stdout.write(
65 | "\b" * (self._progress_width + len(progress_info) + 1)
66 | )
67 | sys.stdout.write("[")
68 | sys.stdout.write(
69 | "=" * int(self._current_index * self._progress_width / self._len)
70 | )
71 | sys.stdout.write(
72 | " "
73 | * (
74 | self._progress_width
75 | - int(self._current_index * self._progress_width / self._len)
76 | )
77 | )
78 | sys.stdout.write("]" + progress_info)
79 | sys.stdout.flush()
80 | sys.stdout.write(
81 | "\b"
82 | * (
83 | self._progress_width
84 | - int(self._current_index * self._progress_width / self._len)
85 | + len(progress_info)
86 | + 1
87 | )
88 | )
89 |
90 | return result
91 |
92 |
93 | def ProgressBar(list: List[Any], progress_width: int = 40):
94 | return iter(_ProgressBar(list, progress_width))
95 |
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/helpers/pymupdf_rag.py:
--------------------------------------------------------------------------------
1 | """
2 | This script accepts a PDF document filename and converts it to a text file
3 | in Markdown format, compatible with the GitHub standard.
4 |
5 | It must be invoked with the filename like this:
6 |
7 | python pymupdf_rag.py input.pdf [-pages PAGES]
8 |
9 | The "PAGES" parameter is a string (containing no spaces) of comma-separated
10 | page numbers to consider. Each item is either a single page number or a
11 | number range "m-n". Use "N" to address the document's last page number.
12 | Example: "-pages 2-15,40,43-N"
13 |
14 | It will produce a markdown text file called "input.md".
15 |
16 | Text will be sorted in Western reading order. Any table will be included in
17 | the text in markdwn format as well.
18 |
19 | Dependencies
20 | -------------
21 | PyMuPDF v1.25.5 or later
22 |
23 | Copyright and License
24 | ----------------------
25 | Copyright (C) 2024-2025 Artifex Software, Inc.
26 |
27 | PyMuPDF4LLM is free software: you can redistribute it and/or modify it under the
28 | terms of the GNU Affero General Public License as published by the Free
29 | Software Foundation, either version 3 of the License, or (at your option)
30 | any later version.
31 |
32 | Alternative licensing terms are available from the licensor.
33 | For commercial licensing, see or contact
34 | Artifex Software, Inc., 39 Mesa Street, Suite 108A, San Francisco,
35 | CA 94129, USA, for further information.
36 | """
37 |
38 | import os
39 | import string
40 | from binascii import b2a_base64
41 | import pymupdf
42 | from pymupdf import mupdf
43 | from pymupdf4llm.helpers.get_text_lines import get_raw_lines, is_white
44 | from pymupdf4llm.helpers.multi_column import column_boxes
45 | from pymupdf4llm.helpers.progress import ProgressBar
46 | from dataclasses import dataclass
47 | from collections import defaultdict
48 |
49 | pymupdf.TOOLS.unset_quad_corrections(True)
50 |
51 | # Characters recognized as bullets when starting a line.
52 | bullet = tuple(
53 | [
54 | "- ",
55 | "* ",
56 | "> ",
57 | chr(0xB6),
58 | chr(0xB7),
59 | chr(8224),
60 | chr(8225),
61 | chr(8226),
62 | chr(0xF0A7),
63 | chr(0xF0B7),
64 | ]
65 | + list(map(chr, range(9632, 9680)))
66 | )
67 |
68 | GRAPHICS_TEXT = "\n\n"
69 |
70 |
71 | class IdentifyHeaders:
72 | """Compute data for identifying header text.
73 |
74 | All non-white text from all selected pages is extracted and its font size
75 | noted as a rounded value.
76 | The most frequent font size (and all smaller ones) is taken as body text
77 | font size.
78 | Larger font sizes are mapped to strings of multiples of '#', the header
79 | tag in Markdown, which in turn is Markdown's representation of HTML's
80 | header tags to .
81 | Larger font sizes than body text but smaller than the font size are
82 | represented as .
83 | """
84 |
85 | def __init__(
86 | self,
87 | doc: str,
88 | pages: list = None,
89 | body_limit: float = 12, # force this to be body text
90 | max_levels: int = 6, # accept this many header levels
91 | ):
92 | """Read all text and make a dictionary of fontsizes.
93 |
94 | Args:
95 | doc: PDF document or filename
96 | pages: consider these page numbers only
97 | body_limit: treat text with larger font size as a header
98 | """
99 | if not isinstance(max_levels, int) or max_levels not in range(1, 7):
100 | raise ValueError("max_levels must be an integer between 1 and 6")
101 | if isinstance(doc, pymupdf.Document):
102 | mydoc = doc
103 | else:
104 | mydoc = pymupdf.open(doc)
105 |
106 | if pages is None: # use all pages if omitted
107 | pages = range(mydoc.page_count)
108 |
109 | fontsizes = defaultdict(int)
110 | for pno in pages:
111 | page = mydoc.load_page(pno)
112 | blocks = page.get_text("dict", flags=pymupdf.TEXTFLAGS_TEXT)["blocks"]
113 | for span in [ # look at all non-empty horizontal spans
114 | s
115 | for b in blocks
116 | for l in b["lines"]
117 | for s in l["spans"]
118 | if not is_white(s["text"])
119 | ]:
120 | fontsz = round(span["size"]) # # compute rounded fontsize
121 | fontsizes[fontsz] += len(span["text"].strip()) # add character count
122 |
123 | if mydoc != doc:
124 | # if opened here, close it now
125 | mydoc.close()
126 |
127 | # maps a fontsize to a string of multiple # header tag characters
128 | self.header_id = {}
129 |
130 | # If not provided, choose the most frequent font size as body text.
131 | # If no text at all on all pages, just use body_limit.
132 | # In any case all fonts not exceeding
133 | temp = sorted(
134 | [(k, v) for k, v in fontsizes.items()], key=lambda i: (i[1], i[0])
135 | )
136 | if temp:
137 | # most frequent font size
138 | self.body_limit = max(body_limit, temp[-1][0])
139 | else:
140 | self.body_limit = body_limit
141 |
142 | # identify up to 6 font sizes as header candidates
143 | sizes = sorted(
144 | [f for f in fontsizes.keys() if f > self.body_limit],
145 | reverse=True,
146 | )[:max_levels]
147 |
148 | # make the header tag dictionary
149 | for i, size in enumerate(sizes, start=1):
150 | self.header_id[size] = "#" * i + " "
151 | if self.header_id.keys():
152 | self.body_limit = min(self.header_id.keys()) - 1
153 |
154 | def get_header_id(self, span: dict, page=None) -> str:
155 | """Return appropriate markdown header prefix.
156 |
157 | Given a text span from a "dict"/"rawdict" extraction, determine the
158 | markdown header prefix string of 0 to n concatenated '#' characters.
159 | """
160 | fontsize = round(span["size"]) # compute fontsize
161 | if fontsize <= self.body_limit:
162 | return ""
163 | hdr_id = self.header_id.get(fontsize, "")
164 | return hdr_id
165 |
166 |
167 | class TocHeaders:
168 | """Compute data for identifying header text.
169 |
170 | This is an alternative to IdentifyHeaders. Instead of running through the
171 | full document to identify font sizes, it uses the document's Table Of
172 | Contents (TOC) to identify headers on pages.
173 | Like IdentifyHeaders, this also is no guarantee to find headers, but it
174 | is a good change for appropriately build documents. In such cases, this
175 | method can be very much faster and more accurate, because we can use the
176 | hierarchy level of TOC items directly to ientify the header level.
177 | Examples where this approach works very well are the Adobe PDF documents.
178 | """
179 |
180 | def __init__(self, doc: str):
181 | """Read and store the TOC of the document."""
182 | if isinstance(doc, pymupdf.Document):
183 | mydoc = doc
184 | else:
185 | mydoc = pymupdf.open(doc)
186 |
187 | self.TOC = doc.get_toc()
188 | if mydoc != doc:
189 | # if opened here, close it now
190 | mydoc.close()
191 |
192 | def get_header_id(self, span: dict, page=None) -> str:
193 | """Return appropriate markdown header prefix.
194 |
195 | Given a text span from a "dict"/"rawdict" extraction, determine the
196 | markdown header prefix string of 0 to n concatenated '#' characters.
197 | """
198 | if page is None:
199 | return ""
200 | # check if this page has TOC entries with an actual title
201 | my_toc = [t for t in self.TOC if t[1] and t[-1] == page.number + 1]
202 | if not my_toc:
203 | return ""
204 | # check if the span matches a TOC entry
205 | text = span["text"].strip()
206 | for t in my_toc:
207 | title = t[1].strip() # title of TOC entry
208 | lvl = t[0] # level of TOC entry
209 | if text.startswith(title) or title.startswith(text):
210 | # found a match: return the header tag
211 | return "#" * lvl + " "
212 | return ""
213 |
214 |
215 | # store relevant parameters here
216 | @dataclass
217 | class Parameters:
218 | pass
219 |
220 |
221 | def refine_boxes(boxes, enlarge=0):
222 | """Join any rectangles with a pairwise non-empty overlap.
223 |
224 | Accepts and returns a list of Rect items.
225 | Note that rectangles that only "touch" each other (common point or edge)
226 | are not considered as overlapping.
227 | Use a positive "enlarge" parameter to enlarge rectangle by these many
228 | points in every direction.
229 |
230 | TODO: Consider using a sweeping line algorithm for this.
231 | """
232 | delta = (-enlarge, -enlarge, enlarge, enlarge)
233 | new_rects = []
234 | # list of all vector graphic rectangles
235 | prects = boxes[:]
236 |
237 | while prects: # the algorithm will empty this list
238 | r = +prects[0] + delta # copy of first rectangle
239 | repeat = True # initialize condition
240 | while repeat:
241 | repeat = False # set false as default
242 | for i in range(len(prects) - 1, 0, -1): # from back to front
243 | if r.intersects(prects[i].irect): # enlarge first rect with this
244 | r |= prects[i]
245 | del prects[i] # delete this rect
246 | repeat = True # indicate must try again
247 |
248 | # first rect now includes all overlaps
249 | new_rects.append(r)
250 | del prects[0]
251 |
252 | new_rects = sorted(set(new_rects), key=lambda r: (r.x0, r.y0))
253 | return new_rects
254 |
255 |
256 | def is_significant(box, paths):
257 | """Check whether the rectangle "box" contains 'signifiant' drawings.
258 |
259 | This means that some path is contained in the "interior" of box.
260 | To this end, we build a sub-box of 90% of the original box and check
261 | whether this still contains drawing paths.
262 | """
263 | if box.width > box.height:
264 | d = box.width * 0.025
265 | else:
266 | d = box.height * 0.025
267 | nbox = box + (d, d, -d, -d) # nbox covers 90% of box interior
268 | # paths contained in, but not equal to box:
269 | my_paths = [p for p in paths if p["rect"] in box and p["rect"] != box]
270 | for p in my_paths:
271 | rect = p["rect"]
272 | if (
273 | not (rect & nbox).is_empty and not p["rect"].is_empty
274 | ): # intersects interior: significant!
275 | return True
276 | # Remaining case: a horizontal or vertical line
277 | # horizontal line:
278 | if (
279 | 1
280 | and rect.y0 == rect.y1
281 | and nbox.y0 <= rect.y0 <= nbox.y1
282 | and rect.x0 < nbox.x1
283 | and rect.x1 > nbox.x0
284 | ):
285 | pass # return True
286 | # vertical line
287 | if (
288 | 1
289 | and rect.x0 == rect.x1
290 | and nbox.x0 <= rect.x0 <= nbox.x1
291 | and rect.y0 < nbox.y1
292 | and rect.y1 > nbox.y0
293 | ):
294 | pass # return True
295 | return False
296 |
297 |
298 | def to_markdown(
299 | doc,
300 | *,
301 | pages=None,
302 | hdr_info=None,
303 | write_images=False,
304 | embed_images=False,
305 | ignore_images=False,
306 | ignore_graphics=False,
307 | image_path="",
308 | image_format="png",
309 | image_size_limit=0.05,
310 | filename=None,
311 | force_text=True,
312 | page_chunks=False,
313 | margins=0,
314 | dpi=150,
315 | page_width=612,
316 | page_height=None,
317 | table_strategy="lines_strict",
318 | graphics_limit=None,
319 | fontsize_limit=3,
320 | ignore_code=False,
321 | extract_words=False,
322 | show_progress=False,
323 | use_glyphs=False,
324 | ) -> str:
325 | """Process the document and return the text of the selected pages.
326 |
327 | Args:
328 | doc: pymupdf.Document or string.
329 | pages: list of page numbers to consider (0-based).
330 | hdr_info: callable or object having method 'get_hdr_info'.
331 | write_images: (bool) save images / graphics as files.
332 | embed_images: (bool) embed images in markdown text (base64 encoded)
333 | image_path: (str) store images in this folder.
334 | image_format: (str) use this image format. Choose a supported one.
335 | force_text: (bool) output text despite of image background.
336 | page_chunks: (bool) whether to segment output by page.
337 | margins: omit content overlapping margin areas.
338 | dpi: (int) desired resolution for generated images.
339 | page_width: (float) assumption if page layout is variable.
340 | page_height: (float) assumption if page layout is variable.
341 | table_strategy: choose table detection strategy
342 | graphics_limit: (int) if vector graphics count exceeds this, ignore all.
343 | ignore_code: (bool) suppress code-like formatting (mono-space fonts)
344 | extract_words: (bool) include "words"-like output in page chunks
345 | show_progress: (bool) print progress as each page is processed.
346 | use_glyphs: (bool) replace the Invalid Unicode by glyph numbers.
347 |
348 | """
349 | if write_images is False and embed_images is False and force_text is False:
350 | raise ValueError("Image and text on images cannot both be suppressed.")
351 | if embed_images is True:
352 | write_images = False
353 | image_path = ""
354 | if not 0 <= image_size_limit < 1:
355 | raise ValueError("'image_size_limit' must be non-negative and less than 1.")
356 | DPI = dpi
357 | IGNORE_CODE = ignore_code
358 | IMG_EXTENSION = image_format
359 | EXTRACT_WORDS = extract_words
360 | if EXTRACT_WORDS is True:
361 | page_chunks = True
362 | ignore_code = True
363 | IMG_PATH = image_path
364 | if IMG_PATH and write_images is True and not os.path.exists(IMG_PATH):
365 | os.mkdir(IMG_PATH)
366 |
367 | if not isinstance(doc, pymupdf.Document):
368 | doc = pymupdf.open(doc)
369 |
370 | FILENAME = doc.name if filename is None else filename
371 | GRAPHICS_LIMIT = graphics_limit
372 | FONTSIZE_LIMIT = fontsize_limit
373 | IGNORE_IMAGES = ignore_images
374 | IGNORE_GRAPHICS = ignore_graphics
375 |
376 | # for reflowable documents allow making 1 page for the whole document
377 | if doc.is_reflowable:
378 | if hasattr(page_height, "__float__"):
379 | # accept user page dimensions
380 | doc.layout(width=page_width, height=page_height)
381 | else:
382 | # no page height limit given: make 1 page for whole document
383 | doc.layout(width=page_width, height=792)
384 | page_count = doc.page_count
385 | height = 792 * page_count # height that covers full document
386 | doc.layout(width=page_width, height=height)
387 |
388 | if pages is None: # use all pages if no selection given
389 | pages = list(range(doc.page_count))
390 |
391 | if hasattr(margins, "__float__"):
392 | margins = [margins] * 4
393 | if len(margins) == 2:
394 | margins = (0, margins[0], 0, margins[1])
395 | if len(margins) != 4:
396 | raise ValueError("margins must be one, two or four floats")
397 | elif not all([hasattr(m, "__float__") for m in margins]):
398 | raise ValueError("margin values must be floats")
399 |
400 | # If "hdr_info" is not an object with a method "get_header_id", scan the
401 | # document and use font sizes as header level indicators.
402 | if callable(hdr_info):
403 | get_header_id = hdr_info
404 | elif hasattr(hdr_info, "get_header_id") and callable(hdr_info.get_header_id):
405 | get_header_id = hdr_info.get_header_id
406 | elif hdr_info is False:
407 | get_header_id = lambda s, page=None: ""
408 | else:
409 | hdr_info = IdentifyHeaders(doc)
410 | get_header_id = hdr_info.get_header_id
411 |
412 | def max_header_id(spans, page):
413 | hdr_ids = sorted(
414 | [l for l in set([len(get_header_id(s, page=page)) for s in spans]) if l > 0]
415 | )
416 | if not hdr_ids:
417 | return ""
418 | return "#" * (hdr_ids[0] - 1) + " "
419 |
420 | def resolve_links(links, span):
421 | """Accept a span and return a markdown link string.
422 |
423 | Args:
424 | links: a list as returned by page.get_links()
425 | span: a span dictionary as returned by page.get_text("dict")
426 |
427 | Returns:
428 | None or a string representing the link in MD format.
429 | """
430 | bbox = pymupdf.Rect(span["bbox"]) # span bbox
431 | # a link should overlap at least 70% of the span
432 | for link in links:
433 | hot = link["from"] # the hot area of the link
434 | middle = (hot.tl + hot.br) / 2 # middle point of hot area
435 | if not middle in bbox:
436 | continue # does not touch the bbox
437 | text = f'[{span["text"].strip()}]({link["uri"]})'
438 | return text
439 |
440 | def save_image(parms, rect, i):
441 | """Optionally render the rect part of a page.
442 |
443 | We will ignore images that are empty or that have an edge smaller
444 | than x% of the corresponding page edge."""
445 | page = parms.page
446 | if (
447 | rect.width < page.rect.width * image_size_limit
448 | or rect.height < page.rect.height * image_size_limit
449 | ):
450 | return ""
451 | if write_images is True or embed_images is True:
452 | pix = page.get_pixmap(clip=rect, dpi=DPI)
453 | else:
454 | return ""
455 | if pix.height <= 0 or pix.width <= 0:
456 | return ""
457 |
458 | if write_images is True:
459 | filename = os.path.basename(parms.filename).replace(" ", "-")
460 | image_filename = os.path.join(
461 | IMG_PATH, f"{filename}-{page.number}-{i}.{IMG_EXTENSION}"
462 | )
463 | pix.save(image_filename)
464 | return image_filename.replace("\\", "/")
465 | elif embed_images is True:
466 | # make a base64 encoded string of the image
467 | data = b2a_base64(pix.tobytes(IMG_EXTENSION)).decode()
468 | data = f"data:image/{IMG_EXTENSION};base64," + data
469 | return data
470 | return ""
471 |
472 | def write_text(
473 | parms,
474 | clip: pymupdf.Rect,
475 | tables=True,
476 | images=True,
477 | force_text=force_text,
478 | ):
479 | """Output the text found inside the given clip.
480 |
481 | This is an alternative for plain text in that it outputs
482 | text enriched with markdown styling.
483 | The logic is capable of recognizing headers, body text, code blocks,
484 | inline code, bold, italic and bold-italic styling.
485 | There is also some effort for list supported (ordered / unordered) in
486 | that typical characters are replaced by respective markdown characters.
487 |
488 | 'tables'/'images' indicate whether this execution should output these
489 | objects.
490 | """
491 |
492 | if clip is None:
493 | clip = parms.clip
494 | out_string = ""
495 |
496 | # This is a list of tuples (linerect, spanlist)
497 | nlines = get_raw_lines(
498 | parms.textpage,
499 | clip=clip,
500 | tolerance=3,
501 | ignore_invisible=not parms.accept_invisible,
502 | )
503 | nlines = [
504 | l for l in nlines if not intersects_rects(l[0], parms.tab_rects.values())
505 | ]
506 |
507 | parms.line_rects.extend([l[0] for l in nlines]) # store line rectangles
508 |
509 | prev_lrect = None # previous line rectangle
510 | prev_bno = -1 # previous block number of line
511 | code = False # mode indicator: outputting code
512 | prev_hdr_string = None
513 |
514 | for lrect, spans in nlines:
515 | # there may be tables or images inside the text block: skip them
516 | if intersects_rects(lrect, parms.img_rects):
517 | continue
518 |
519 | # ------------------------------------------------------------
520 | # Pick up tables ABOVE this text block
521 | # ------------------------------------------------------------
522 | if tables:
523 | tab_candidates = [
524 | (i, tab_rect)
525 | for i, tab_rect in parms.tab_rects.items()
526 | if tab_rect.y1 <= lrect.y0
527 | and i not in parms.written_tables
528 | and (
529 | 0
530 | or lrect.x0 <= tab_rect.x0 < lrect.x1
531 | or lrect.x0 < tab_rect.x1 <= lrect.x1
532 | or tab_rect.x0 <= lrect.x0 < lrect.x1 <= tab_rect.x1
533 | )
534 | ]
535 | for i, _ in tab_candidates:
536 | out_string += "\n" + parms.tabs[i].to_markdown(clean=False) + "\n"
537 | if EXTRACT_WORDS:
538 | # for "words" extraction, add table cells as line rects
539 | cells = sorted(
540 | set(
541 | [
542 | pymupdf.Rect(c)
543 | for c in parms.tabs[i].header.cells
544 | + parms.tabs[i].cells
545 | if c is not None
546 | ]
547 | ),
548 | key=lambda c: (c.y1, c.x0),
549 | )
550 | parms.line_rects.extend(cells)
551 | parms.written_tables.append(i)
552 |
553 | # ------------------------------------------------------------
554 | # Pick up images / graphics ABOVE this text block
555 | # ------------------------------------------------------------
556 | if images:
557 | for i in range(len(parms.img_rects)):
558 | if i in parms.written_images:
559 | continue
560 | r = parms.img_rects[i]
561 | if r.y1 <= lrect.y0 and (
562 | 0
563 | or lrect.x0 <= r.x0 < lrect.x1
564 | or lrect.x0 < r.x1 <= lrect.x1
565 | or r.x0 <= lrect.x0 < lrect.x1 <= r.x1
566 | ):
567 | pathname = save_image(parms, r, i)
568 | if pathname:
569 | out_string += GRAPHICS_TEXT % pathname
570 |
571 | # recursive invocation
572 | if force_text is True:
573 | img_txt = write_text(
574 | parms,
575 | r,
576 | tables=False,
577 | images=False,
578 | force_text=True,
579 | )
580 |
581 | if not is_white(img_txt):
582 | out_string += img_txt
583 | parms.written_images.append(i)
584 |
585 | parms.line_rects.append(lrect)
586 |
587 | # make text string for the full line
588 | text = " ".join([s["text"] for s in spans])
589 |
590 | # if line is a header, this will return multiple "#" characters,
591 | # otherwise an empty string
592 | hdr_string = max_header_id(spans, page=parms.page) # a header?
593 |
594 | # full line strikeout?
595 | all_strikeout = all([s["char_flags"] & 1 for s in spans])
596 | # full line italic?
597 | all_italic = all([s["flags"] & 2 for s in spans])
598 | # full line bold?
599 | all_bold = all([s["flags"] & 16 or s["char_flags"] & 8 for s in spans])
600 |
601 | # full line mono-spaced?
602 | if not IGNORE_CODE:
603 | all_mono = all([s["flags"] & 8 for s in spans])
604 | else:
605 | all_mono = False
606 |
607 | if all_mono and not hdr_string:
608 | if not code: # if not already in code output mode:
609 | out_string += "```\n" # switch on "code" mode
610 | code = True
611 | # compute approx. distance from left - assuming a width
612 | # of 0.5*fontsize.
613 | delta = int((lrect.x0 - clip.x0) / (spans[0]["size"] * 0.5))
614 | indent = " " * delta
615 |
616 | out_string += indent + text + "\n"
617 | continue # done with this line
618 |
619 | if hdr_string: # if a header line skip the rest
620 | if all_mono:
621 | text = "`" + text + "`"
622 | if all_strikeout:
623 | text = "~~" + text + "~~"
624 | if all_italic:
625 | text = "*" + text + "*"
626 | if all_bold:
627 | text = "**" + text + "**"
628 | if hdr_string != prev_hdr_string:
629 | out_string += hdr_string + text + "\n"
630 | else:
631 | # intercept if header text has been broken in multiple lines
632 | while out_string.endswith("\n"):
633 | out_string = out_string[:-1]
634 | out_string += " " + text + "\n"
635 | prev_hdr_string = hdr_string
636 | continue
637 |
638 | prev_hdr_string = hdr_string
639 |
640 | span0 = spans[0]
641 | bno = span0["block"] # block number of line
642 | if bno != prev_bno:
643 | out_string += "\n"
644 | prev_bno = bno
645 |
646 | if ( # check if we need another line break
647 | prev_lrect
648 | and lrect.y1 - prev_lrect.y1 > lrect.height * 1.5
649 | or span0["text"].startswith("[")
650 | or span0["text"].startswith(bullet)
651 | or span0["flags"] & 1 # superscript?
652 | ):
653 | out_string += "\n"
654 | prev_lrect = lrect
655 |
656 | # this line is not all-mono, so switch off "code" mode
657 | if code: # in code output mode?
658 | out_string += "```\n" # switch of code mode
659 | code = False
660 |
661 | for i, s in enumerate(spans): # iterate spans of the line
662 | # decode font properties
663 | mono = s["flags"] & 8 and IGNORE_CODE is False
664 | bold = s["flags"] & 16 or s["char_flags"] & 8
665 | italic = s["flags"] & 2
666 | strikeout = s["char_flags"] & 1
667 |
668 | if mono:
669 | # this is text in some monospaced font
670 | out_string += f"`{s['text'].strip()}` "
671 | continue
672 |
673 | prefix = ""
674 | suffix = ""
675 | if bold:
676 | prefix = "**" + prefix
677 | suffix += "**"
678 | if italic:
679 | prefix = "*" + prefix
680 | suffix += "*"
681 | if strikeout:
682 | prefix = "~~" + prefix
683 | suffix += "~~"
684 | if mono:
685 | prefix = "`" + prefix
686 | suffix += "`"
687 |
688 | # convert intersecting link to markdown syntax
689 | ltext = resolve_links(parms.links, s)
690 | if ltext:
691 | text = f"{hdr_string}{prefix}{ltext}{suffix} "
692 | else:
693 | text = f"{hdr_string}{prefix}{s['text'].strip()}{suffix} "
694 | if text.startswith(bullet):
695 | text = "- " + text[1:]
696 | text = text.replace(" ", " ")
697 | dist = span0["bbox"][0] - clip.x0
698 | cwidth = (span0["bbox"][2] - span0["bbox"][0]) / len(span0["text"])
699 | if cwidth == 0.0:
700 | cwidth = span0["size"] * 0.5
701 | text = " " * int(round(dist / cwidth)) + text
702 |
703 | out_string += text
704 | if not code:
705 | out_string += "\n"
706 | out_string += "\n"
707 | if code:
708 | out_string += "```\n" # switch of code mode
709 | code = False
710 |
711 | return (
712 | out_string.replace(" \n", "\n").replace(" ", " ").replace("\n\n\n", "\n\n")
713 | )
714 |
715 | def is_in_rects(rect, rect_list):
716 | """Check if rect is contained in a rect of the list."""
717 | for i, r in enumerate(rect_list, start=1):
718 | if rect in r:
719 | return i
720 | return 0
721 |
722 | def intersects_rects(rect, rect_list):
723 | """Check if middle of rect is contained in a rect of the list."""
724 | delta = (-1, -1, 1, 1) # enlarge rect_list members somewhat by this
725 | enlarged = rect + delta
726 | abs_enlarged = abs(enlarged) * 0.5
727 | for i, r in enumerate(rect_list, start=1):
728 | if abs(enlarged & r) > abs_enlarged:
729 | return i
730 | return 0
731 |
732 | def output_tables(parms, text_rect):
733 | """Output tables above given text rectangle."""
734 | this_md = "" # markdown string for table(s) content
735 | if text_rect is not None: # select tables above the text block
736 | for i, trect in sorted(
737 | [j for j in parms.tab_rects.items() if j[1].y1 <= text_rect.y0],
738 | key=lambda j: (j[1].y1, j[1].x0),
739 | ):
740 | if i in parms.written_tables:
741 | continue
742 | this_md += parms.tabs[i].to_markdown(clean=False)
743 | if EXTRACT_WORDS:
744 | # for "words" extraction, add table cells as line rects
745 | cells = sorted(
746 | set(
747 | [
748 | pymupdf.Rect(c)
749 | for c in parms.tabs[i].header.cells
750 | + parms.tabs[i].cells
751 | if c is not None
752 | ]
753 | ),
754 | key=lambda c: (c.y1, c.x0),
755 | )
756 | parms.line_rects.extend(cells)
757 | parms.written_tables.append(i) # do not touch this table twice
758 |
759 | else: # output all remaining tables
760 | for i, trect in parms.tab_rects.items():
761 | if i in parms.written_tables:
762 | continue
763 | this_md += parms.tabs[i].to_markdown(clean=False)
764 | if EXTRACT_WORDS:
765 | # for "words" extraction, add table cells as line rects
766 | cells = sorted(
767 | set(
768 | [
769 | pymupdf.Rect(c)
770 | for c in parms.tabs[i].header.cells
771 | + parms.tabs[i].cells
772 | if c is not None
773 | ]
774 | ),
775 | key=lambda c: (c.y1, c.x0),
776 | )
777 | parms.line_rects.extend(cells)
778 | parms.written_tables.append(i) # do not touch this table twice
779 | return this_md
780 |
781 | def output_images(parms, text_rect, force_text):
782 | """Output images and graphics above text rectangle."""
783 | if not parms.img_rects:
784 | return ""
785 | this_md = "" # markdown string
786 | if text_rect is not None: # select images above the text block
787 | for i, img_rect in enumerate(parms.img_rects):
788 | if img_rect.y0 > text_rect.y0:
789 | continue
790 | if img_rect.x0 >= text_rect.x1 or img_rect.x1 <= text_rect.x0:
791 | continue
792 | if i in parms.written_images:
793 | continue
794 | pathname = save_image(parms, img_rect, i)
795 | parms.written_images.append(i) # do not touch this image twice
796 | if pathname:
797 | this_md += GRAPHICS_TEXT % pathname
798 | if force_text:
799 | img_txt = write_text(
800 | parms,
801 | img_rect,
802 | tables=False, # we have no tables here
803 | images=False, # we have no other images here
804 | force_text=True,
805 | )
806 | if not is_white(img_txt): # was there text at all?
807 | this_md += img_txt
808 | else: # output all remaining images
809 | for i, img_rect in enumerate(parms.img_rects):
810 | if i in parms.written_images:
811 | continue
812 | pathname = save_image(parms, img_rect, i)
813 | parms.written_images.append(i) # do not touch this image twice
814 | if pathname:
815 | this_md += GRAPHICS_TEXT % pathname
816 | if force_text:
817 | img_txt = write_text(
818 | parms,
819 | img_rect,
820 | tables=False, # we have no tables here
821 | images=False, # we have no other images here
822 | force_text=True,
823 | )
824 | if not is_white(img_txt):
825 | this_md += img_txt
826 |
827 | return this_md
828 |
829 | def page_is_ocr(page):
830 | """Check if page exclusivley contains OCR text.
831 |
832 | For this to be true, all text must be written as "ignore-text".
833 | """
834 | text_types = set([b[0] for b in page.get_bboxlog() if "text" in b[0]])
835 | if text_types == {"ignore-text"}:
836 | return True
837 | return False
838 |
839 | def get_bg_color(page):
840 | """Determine the background color of the page.
841 |
842 | The function returns a PDF RGB color triple or None.
843 | We check the color of 10 x 10 pixel areas in the four corners of the
844 | page. If they are unicolor and of the same color, we assume this to
845 | be the background color.
846 | """
847 | pix = page.get_pixmap(
848 | clip=(page.rect.x0, page.rect.y0, page.rect.x0 + 10, page.rect.y0 + 10)
849 | )
850 | if not pix.samples or not pix.is_unicolor:
851 | return None
852 | pixel_ul = pix.pixel(0, 0) # upper left color
853 | pix = page.get_pixmap(
854 | clip=(page.rect.x1 - 10, page.rect.y0, page.rect.x1, page.rect.y0 + 10)
855 | )
856 | if not pix.samples or not pix.is_unicolor:
857 | return None
858 | pixel_ur = pix.pixel(0, 0) # upper right color
859 | if not pixel_ul == pixel_ur:
860 | return None
861 | pix = page.get_pixmap(
862 | clip=(page.rect.x0, page.rect.y1 - 10, page.rect.x0 + 10, page.rect.y1)
863 | )
864 | if not pix.samples or not pix.is_unicolor:
865 | return None
866 | pixel_ll = pix.pixel(0, 0) # lower left color
867 | if not pixel_ul == pixel_ll:
868 | return None
869 | pix = page.get_pixmap(
870 | clip=(page.rect.x1 - 10, page.rect.y1 - 10, page.rect.x1, page.rect.y1)
871 | )
872 | if not pix.samples or not pix.is_unicolor:
873 | return None
874 | pixel_lr = pix.pixel(0, 0) # lower right color
875 | if not pixel_ul == pixel_lr:
876 | return None
877 | return (pixel_ul[0] / 255, pixel_ul[1] / 255, pixel_ul[2] / 255)
878 |
879 | def get_metadata(doc, pno):
880 | meta = doc.metadata.copy()
881 | meta["file_path"] = FILENAME
882 | meta["page_count"] = doc.page_count
883 | meta["page"] = pno + 1
884 | return meta
885 |
886 | def sort_words(words: list) -> list:
887 | """Reorder words in lines.
888 |
889 | The argument list must be presorted by bottom, then left coordinates.
890 |
891 | Words with similar top / bottom coordinates are assumed to belong to
892 | the same line and will be sorted left to right within that line.
893 | """
894 | if not words:
895 | return []
896 | nwords = []
897 | line = [words[0]]
898 | lrect = pymupdf.Rect(words[0][:4])
899 | for w in words[1:]:
900 | if abs(w[1] - lrect.y0) <= 3 or abs(w[3] - lrect.y1) <= 3:
901 | line.append(w)
902 | lrect |= w[:4]
903 | else:
904 | line.sort(key=lambda w: w[0])
905 | nwords.extend(line)
906 | line = [w]
907 | lrect = pymupdf.Rect(w[:4])
908 | line.sort(key=lambda w: w[0])
909 | nwords.extend(line)
910 | return nwords
911 |
912 | def get_page_output(
913 | doc, pno, margins, textflags, FILENAME, IGNORE_IMAGES, IGNORE_GRAPHICS
914 | ):
915 | """Process one page.
916 |
917 | Args:
918 | doc: pymupdf.Document
919 | pno: 0-based page number
920 | textflags: text extraction flag bits
921 |
922 | Returns:
923 | Markdown string of page content and image, table and vector
924 | graphics information.
925 | """
926 | page = doc[pno]
927 | page.remove_rotation() # make sure we work on rotation=0
928 | parms = Parameters() # all page information
929 | parms.page = page
930 | parms.filename = FILENAME
931 | parms.md_string = ""
932 | parms.images = []
933 | parms.tables = []
934 | parms.graphics = []
935 | parms.words = []
936 | parms.line_rects = []
937 | parms.accept_invisible = page_is_ocr(page) # accept invisible text
938 |
939 | # determine background color
940 | parms.bg_color = get_bg_color(page)
941 |
942 | left, top, right, bottom = margins
943 | parms.clip = page.rect + (left, top, -right, -bottom)
944 |
945 | # extract external links on page
946 | parms.links = [l for l in page.get_links() if l["kind"] == pymupdf.LINK_URI]
947 |
948 | # extract annotation rectangles on page
949 | parms.annot_rects = [a.rect for a in page.annots()]
950 |
951 | # make a TextPage for all later extractions
952 | parms.textpage = page.get_textpage(flags=textflags, clip=parms.clip)
953 |
954 | # extract images on page
955 | if not IGNORE_IMAGES:
956 | img_info = page.get_image_info()
957 | else:
958 | img_info = []
959 | for i in range(len(img_info)):
960 | img_info[i]["bbox"] = pymupdf.Rect(img_info[i]["bbox"])
961 | img_info = [
962 | i
963 | for i in img_info
964 | if i["bbox"].width >= image_size_limit * parms.clip.width
965 | and i["bbox"].height >= image_size_limit * parms.clip.height
966 | and i["bbox"].intersects(parms.clip)
967 | and i["bbox"].width > 3
968 | and i["bbox"].height > 3
969 | ]
970 | # sort descending by image area size
971 | img_info.sort(key=lambda i: abs(i["bbox"]), reverse=True)
972 | img_info = img_info[:30] # only accept the largest up to 30 images
973 | # run from back to front (= small to large)
974 | for i in range(len(img_info) - 1, 0, -1):
975 | r = img_info[i]["bbox"]
976 | if r.is_empty:
977 | del img_info[i]
978 | continue
979 | for j in range(i): # image areas larger than r
980 | if r in img_info[j]["bbox"]:
981 | del img_info[i] # contained in some larger image
982 | break
983 | parms.images = img_info
984 |
985 | parms.img_rects = [i["bbox"] for i in parms.images]
986 |
987 | # catch too-many-graphics situation
988 | graphics_count = len([b for b in page.get_bboxlog() if "path" in b[0]])
989 | if GRAPHICS_LIMIT and graphics_count > GRAPHICS_LIMIT:
990 | IGNORE_GRAPHICS = True
991 |
992 | # Locate all tables on page
993 | parms.written_tables = [] # stores already written tables
994 | omitted_table_rects = []
995 | if IGNORE_GRAPHICS or not table_strategy:
996 | # do not try to extract tables
997 | parms.tabs = None
998 | else:
999 | parms.tabs = page.find_tables(clip=parms.clip, strategy=table_strategy)
1000 | # remove tables with too few rows or columns
1001 | for i in range(len(parms.tabs.tables) - 1, -1, -1):
1002 | t = parms.tabs.tables[i]
1003 | if t.row_count < 2 or t.col_count < 2:
1004 | omitted_table_rects.append(pymupdf.Rect(t.bbox))
1005 | del parms.tabs.tables[i]
1006 | parms.tabs.tables.sort(key=lambda t: (t.bbox[0], t.bbox[1]))
1007 |
1008 | # Make a list of table boundary boxes.
1009 | # Must include the header bbox (which may exist outside tab.bbox)
1010 | tab_rects = {}
1011 | if parms.tabs is not None:
1012 | for i, t in enumerate(parms.tabs.tables):
1013 | tab_rects[i] = pymupdf.Rect(t.bbox) | pymupdf.Rect(t.header.bbox)
1014 | tab_dict = {
1015 | "bbox": tuple(tab_rects[i]),
1016 | "rows": t.row_count,
1017 | "columns": t.col_count,
1018 | }
1019 | parms.tables.append(tab_dict)
1020 | parms.tab_rects = tab_rects
1021 | # list of table rectangles
1022 | parms.tab_rects0 = list(tab_rects.values())
1023 |
1024 | # Select paths not intersecting any table.
1025 | # Ignore full page graphics.
1026 | # Ignore fill paths having the background color.
1027 | if not IGNORE_GRAPHICS:
1028 | paths = [
1029 | p
1030 | for p in page.get_drawings()
1031 | if p["rect"] in parms.clip
1032 | and p["rect"].width < parms.clip.width
1033 | and p["rect"].height < parms.clip.height
1034 | and (p["rect"].width > 3 or p["rect"].height > 3)
1035 | and not (p["fill"] == parms.bg_color and p["fill"] != None)
1036 | and not intersects_rects(
1037 | p["rect"], parms.tab_rects0 + omitted_table_rects
1038 | )
1039 | and not intersects_rects(p["rect"], parms.annot_rects)
1040 | ]
1041 | else:
1042 | paths = []
1043 |
1044 | # catch too-many-graphics situation
1045 | if GRAPHICS_LIMIT and len(paths) > GRAPHICS_LIMIT:
1046 | paths = []
1047 |
1048 | # We also ignore vector graphics that only represent
1049 | # "text emphasizing sugar".
1050 | vg_clusters0 = [] # worthwhile vector graphics go here
1051 |
1052 | # walk through all vector graphics outside any table
1053 | clusters = page.cluster_drawings(drawings=paths)
1054 | for bbox in clusters:
1055 | if is_significant(bbox, paths):
1056 | vg_clusters0.append(bbox)
1057 |
1058 | # remove paths that are not in some relevant graphic
1059 | parms.actual_paths = [p for p in paths if is_in_rects(p["rect"], vg_clusters0)]
1060 |
1061 | # also add image rectangles to the list and vice versa
1062 | vg_clusters0.extend(parms.img_rects)
1063 | parms.img_rects.extend(vg_clusters0)
1064 | parms.img_rects = sorted(set(parms.img_rects), key=lambda r: (r.y1, r.x0))
1065 | parms.written_images = []
1066 | # these may no longer be pairwise disjoint:
1067 | # remove area overlaps by joining into larger rects
1068 | parms.vg_clusters0 = refine_boxes(vg_clusters0)
1069 |
1070 | parms.vg_clusters = dict((i, r) for i, r in enumerate(parms.vg_clusters0))
1071 | # identify text bboxes on page, avoiding tables, images and graphics
1072 | text_rects = column_boxes(
1073 | parms.page,
1074 | paths=parms.actual_paths,
1075 | no_image_text=not force_text,
1076 | textpage=parms.textpage,
1077 | avoid=parms.tab_rects0 + parms.vg_clusters0,
1078 | footer_margin=margins[3],
1079 | header_margin=margins[1],
1080 | ignore_images=IGNORE_IMAGES,
1081 | )
1082 |
1083 | """
1084 | ------------------------------------------------------------------
1085 | Extract markdown text iterating over text rectangles.
1086 | We also output any tables. They may live above, below or inside
1087 | the text rectangles.
1088 | ------------------------------------------------------------------
1089 | """
1090 | for text_rect in text_rects:
1091 | # output tables above this rectangle
1092 | parms.md_string += output_tables(parms, text_rect)
1093 | parms.md_string += output_images(parms, text_rect, force_text)
1094 |
1095 | # output text inside this rectangle
1096 | parms.md_string += write_text(
1097 | parms,
1098 | text_rect,
1099 | force_text=force_text,
1100 | images=True,
1101 | tables=True,
1102 | )
1103 |
1104 | parms.md_string = parms.md_string.replace(" ,", ",").replace("-\n", "")
1105 |
1106 | # write any remaining tables and images
1107 | parms.md_string += output_tables(parms, None)
1108 | parms.md_string += output_images(parms, None, force_text)
1109 |
1110 | while parms.md_string.startswith("\n"):
1111 | parms.md_string = parms.md_string[1:]
1112 | parms.md_string = parms.md_string.replace(chr(0), chr(0xFFFD))
1113 |
1114 | if EXTRACT_WORDS is True:
1115 | # output words in sequence compliant with Markdown text
1116 | rawwords = parms.textpage.extractWORDS()
1117 | rawwords.sort(key=lambda w: (w[3], w[0]))
1118 |
1119 | words = []
1120 | for lrect in parms.line_rects:
1121 | lwords = []
1122 | for w in rawwords:
1123 | wrect = pymupdf.Rect(w[:4])
1124 | if wrect in lrect:
1125 | lwords.append(w)
1126 | words.extend(sort_words(lwords))
1127 |
1128 | # remove word duplicates without spoiling the sequence
1129 | # duplicates may occur for multiple reasons
1130 | nwords = [] # words w/o duplicates
1131 | for w in words:
1132 | if w not in nwords:
1133 | nwords.append(w)
1134 | words = nwords
1135 |
1136 | else:
1137 | words = []
1138 | parms.words = words
1139 | return parms
1140 |
1141 | if page_chunks is False:
1142 | document_output = ""
1143 | else:
1144 | document_output = []
1145 |
1146 | # read the Table of Contents
1147 | toc = doc.get_toc()
1148 |
1149 | # Text extraction flags:
1150 | # omit clipped text, collect styles, use accurate bounding boxes
1151 | textflags = (
1152 | 0
1153 | | mupdf.FZ_STEXT_CLIP
1154 | | mupdf.FZ_STEXT_ACCURATE_BBOXES
1155 | | mupdf.FZ_STEXT_IGNORE_ACTUALTEXT
1156 | | 32768 # mupdf.FZ_STEXT_COLLECT_STYLES
1157 | )
1158 | # optionally replace 0xFFFD by glyph number
1159 | if use_glyphs:
1160 | textflags |= mupdf.FZ_STEXT_USE_GID_FOR_UNKNOWN_UNICODE
1161 |
1162 | if show_progress:
1163 | print(f"Processing {FILENAME}...")
1164 | pages = ProgressBar(pages)
1165 | for pno in pages:
1166 | parms = get_page_output(
1167 | doc, pno, margins, textflags, FILENAME, IGNORE_IMAGES, IGNORE_GRAPHICS
1168 | )
1169 | if page_chunks is False:
1170 | document_output += parms.md_string
1171 | else:
1172 | # build subet of TOC for this page
1173 | page_tocs = [t for t in toc if t[-1] == pno + 1]
1174 |
1175 | metadata = get_metadata(doc, pno)
1176 | document_output.append(
1177 | {
1178 | "metadata": metadata,
1179 | "toc_items": page_tocs,
1180 | "tables": parms.tables,
1181 | "images": parms.images,
1182 | "graphics": parms.graphics,
1183 | "text": parms.md_string,
1184 | "words": parms.words,
1185 | }
1186 | )
1187 | del parms
1188 |
1189 | return document_output
1190 |
1191 |
1192 | def extract_images_on_page_simple(page, parms, image_size_limit):
1193 | # extract images on page
1194 | # ignore images contained in some other one (simplified mechanism)
1195 | img_info = page.get_image_info()
1196 | for i in range(len(img_info)):
1197 | item = img_info[i]
1198 | item["bbox"] = pymupdf.Rect(item["bbox"]) & parms.clip
1199 | img_info[i] = item
1200 |
1201 | # sort descending by image area size
1202 | img_info.sort(key=lambda i: abs(i["bbox"]), reverse=True)
1203 | # run from back to front (= small to large)
1204 | for i in range(len(img_info) - 1, 0, -1):
1205 | r = img_info[i]["bbox"]
1206 | if r.is_empty:
1207 | del img_info[i]
1208 | continue
1209 | for j in range(i): # image areas larger than r
1210 | if r in img_info[j]["bbox"]:
1211 | del img_info[i] # contained in some larger image
1212 | break
1213 |
1214 | return img_info
1215 |
1216 |
1217 | def filter_small_images(page, parms, image_size_limit):
1218 | img_info = []
1219 | for item in page.get_image_info():
1220 | r = pymupdf.Rect(item["bbox"]) & parms.clip
1221 | if r.is_empty or (
1222 | max(r.width / page.rect.width, r.height / page.rect.height)
1223 | < image_size_limit
1224 | ):
1225 | continue
1226 | item["bbox"] = r
1227 | img_info.append(item)
1228 | return img_info
1229 |
1230 |
1231 | def extract_images_on_page_simple_drop(page, parms, image_size_limit):
1232 | img_info = filter_small_images(page, parms, image_size_limit)
1233 |
1234 | # sort descending by image area size
1235 | img_info.sort(key=lambda i: abs(i["bbox"]), reverse=True)
1236 | # run from back to front (= small to large)
1237 | for i in range(len(img_info) - 1, 0, -1):
1238 | r = img_info[i]["bbox"]
1239 | if r.is_empty:
1240 | del img_info[i]
1241 | continue
1242 | for j in range(i): # image areas larger than r
1243 | if r in img_info[j]["bbox"]:
1244 | del img_info[i] # contained in some larger image
1245 | break
1246 |
1247 | return img_info
1248 |
1249 |
1250 | if __name__ == "__main__":
1251 | import pathlib
1252 | import sys
1253 | import time
1254 |
1255 | try:
1256 | filename = "sample_document.pdf"
1257 | except IndexError:
1258 | print(f"Usage:\npython {os.path.basename(__file__)} input.pdf")
1259 | sys.exit()
1260 |
1261 | t0 = time.perf_counter() # start a time
1262 |
1263 | doc = pymupdf.open(filename) # open input file
1264 | parms = sys.argv[2:] # contains ["-pages", "PAGES"] or empty list
1265 | pages = range(doc.page_count) # default page range
1266 | if len(parms) == 2 and parms[0] == "-pages": # page sub-selection given
1267 | pages = [] # list of desired page numbers
1268 |
1269 | # replace any variable "N" by page count
1270 | pages_spec = parms[1].replace("N", f"{doc.page_count}")
1271 | for spec in pages_spec.split(","):
1272 | if "-" in spec:
1273 | start, end = map(int, spec.split("-"))
1274 | pages.extend(range(start - 1, end))
1275 | else:
1276 | pages.append(int(spec) - 1)
1277 |
1278 | # make a set of invalid page numbers
1279 | wrong_pages = set([n + 1 for n in pages if n >= doc.page_count][:4])
1280 | if wrong_pages != set(): # if any invalid numbers given, exit.
1281 | sys.exit(f"Page number(s) {wrong_pages} not in '{doc}'.")
1282 |
1283 | # get the markdown string
1284 | md_string = to_markdown(
1285 | doc,
1286 | pages=pages,
1287 | # write_images=True,
1288 | force_text=True,
1289 | ignore_images=True,
1290 | ignore_graphics=True,
1291 | table_strategy=None,
1292 | )
1293 | FILENAME = doc.name
1294 | # output to a text file with extension ".md"
1295 | outname = FILENAME + ".md"
1296 | pathlib.Path(outname).write_bytes(md_string.encode())
1297 | t1 = time.perf_counter() # stop timer
1298 | print(f"Markdown creation time for {FILENAME=} {round(t1-t0,2)} sec.")
1299 |
--------------------------------------------------------------------------------
/pymupdf4llm/pymupdf4llm/llama/pdf_markdown_reader.py:
--------------------------------------------------------------------------------
1 | from pathlib import Path
2 | from typing import Any, Callable, Dict, List, Optional, Union
3 |
4 | import pymupdf
5 | from pymupdf import Document as FitzDocument
6 | from pymupdf4llm import IdentifyHeaders, to_markdown
7 |
8 | try:
9 | from llama_index.core.readers.base import BaseReader
10 | from llama_index.core.schema import Document as LlamaIndexDocument
11 |
12 | print("Successfully imported LlamaIndex")
13 | except ImportError:
14 | raise NotImplementedError("Please install 'llama_index'.")
15 |
16 |
17 | class PDFMarkdownReader(BaseReader):
18 | """Read PDF files using PyMuPDF library."""
19 |
20 | meta_filter: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None
21 |
22 | def __init__(
23 | self,
24 | meta_filter: Optional[
25 | Callable[[Dict[str, Any]], Dict[str, Any]]
26 | ] = None,
27 | ):
28 | self.meta_filter = meta_filter
29 |
30 | def load_data(
31 | self,
32 | file_path: Union[Path, str],
33 | extra_info: Optional[Dict] = None,
34 | **load_kwargs: Any,
35 | ) -> List[LlamaIndexDocument]:
36 | """Loads list of documents from PDF file and also accepts extra information in dict format.
37 |
38 | Args:
39 | file_path (Union[Path, str]): The path to the PDF file.
40 | extra_info (Optional[Dict], optional): A dictionary containing extra information. Defaults to None.
41 | **load_kwargs (Any): Additional keyword arguments to be passed to the load method.
42 |
43 | Returns:
44 | List[LlamaIndexDocument]: A list of LlamaIndexDocument objects.
45 | """
46 | if not isinstance(file_path, str) and not isinstance(file_path, Path):
47 | raise TypeError("file_path must be a string or Path.")
48 |
49 | if not extra_info:
50 | extra_info = {}
51 |
52 | if extra_info and not isinstance(extra_info, dict):
53 | raise TypeError("extra_info must be a dictionary.")
54 |
55 | # extract text header information
56 | hdr_info = IdentifyHeaders(file_path)
57 |
58 | doc: FitzDocument = pymupdf.open(file_path)
59 | docs = []
60 |
61 | for page in doc:
62 | docs.append(
63 | self._process_doc_page(
64 | doc, extra_info, file_path, page.number, hdr_info, **load_kwargs
65 | )
66 | )
67 | return docs
68 |
69 | # Helpers
70 | # ---
71 |
72 | def _process_doc_page(
73 | self,
74 | doc: FitzDocument,
75 | extra_info: Dict[str, Any],
76 | file_path: str,
77 | page_number: int,
78 | hdr_info: IdentifyHeaders,
79 | **load_kwargs: Any,
80 | ):
81 | """Processes a single page of a PDF document."""
82 | extra_info = self._process_doc_meta(
83 | doc, file_path, page_number, extra_info
84 | )
85 |
86 | if self.meta_filter:
87 | extra_info = self.meta_filter(extra_info)
88 |
89 | text = to_markdown(
90 | doc, pages=[page_number],
91 | hdr_info=hdr_info,
92 | **load_kwargs,
93 | )
94 | return LlamaIndexDocument(text=text, extra_info=extra_info)
95 |
96 | def _process_doc_meta(
97 | self,
98 | doc: FitzDocument,
99 | file_path: Union[Path, str],
100 | page_number: int,
101 | extra_info: Optional[Dict] = None,
102 | ):
103 | """Processes metas of a PDF document."""
104 | extra_info.update(doc.metadata)
105 | extra_info["page"] = page_number + 1
106 | extra_info["total_pages"] = len(doc)
107 | extra_info["file_path"] = str(file_path)
108 |
109 | return extra_info
110 |
--------------------------------------------------------------------------------
/pymupdf4llm/setup.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | import setuptools
4 |
5 | setup_py_cwd = os.path.dirname(__file__)
6 | with open(os.path.join(setup_py_cwd, "README.md"), encoding="utf-8") as f:
7 | readme = f.read()
8 |
9 | classifiers = [
10 | "Development Status :: 5 - Production/Stable",
11 | "Environment :: Console",
12 | "Intended Audience :: Developers",
13 | "Programming Language :: Python :: 3",
14 | "Topic :: Utilities",
15 | ]
16 | requires = ["pymupdf>=1.25.5"]
17 |
18 | setuptools.setup(
19 | name="pymupdf4llm",
20 | version="0.0.24",
21 | author="Artifex",
22 | author_email="support@artifex.com",
23 | description="PyMuPDF Utilities for LLM/RAG",
24 | packages=setuptools.find_packages(),
25 | long_description=readme,
26 | long_description_content_type="text/markdown",
27 | install_requires=requires,
28 | license="GNU AFFERO GPL 3.0",
29 | url="https://github.com/pymupdf/RAG",
30 | classifiers=classifiers,
31 | package_data={
32 | "pymupdf4llm": ["LICENSE", "helpers/*.py", "llama/*.py"],
33 | },
34 | project_urls={
35 | "Documentation": "https://pymupdf.readthedocs.io/",
36 | "Source": "https://github.com/pymupdf/RAG/tree/main/pymupdf4llm/pymupdf4llm",
37 | "Tracker": "https://github.com/pymupdf/RAG/issues",
38 | "Changelog": "https://github.com/pymupdf/RAG/blob/main/CHANGES.md",
39 | },
40 | )
41 |
--------------------------------------------------------------------------------
/tests/pymupdf4llm/llama_index/test_pdf_markdown_reader.py:
--------------------------------------------------------------------------------
1 | import os
2 |
3 | import pytest
4 | from llama_index.core.schema import Document as LlamaIndexDocument
5 |
6 | try:
7 | from llama_index.core.readers.base import BaseReader
8 | from llama_index.core.schema import Document as LlamaIndexDocument
9 |
10 | print("All imports are successful.")
11 | except ImportError:
12 | raise NotImplementedError("Please install 'llama_index' is needed.")
13 |
14 |
15 | from pymupdf4llm.pymupdf4llm.llama_index.pdf_markdown_reader import PDFMarkdownReader
16 |
17 | PDF = "input.pdf"
18 |
19 |
20 | def _get_test_file_path(file_name: str, __file__: str = __file__) -> str:
21 | file_path = os.path.join(
22 | os.path.dirname(os.path.abspath(__file__)),
23 | "..",
24 | "..",
25 | ".." "helpers",
26 | file_name,
27 | )
28 | file_path = os.path.normpath(file_path)
29 | return file_path
30 |
31 |
32 | def test_load_data():
33 | # Arrange
34 | # ---
35 | pdf_reader = PDFMarkdownReader()
36 | path = _get_test_file_path(PDF, __file__)
37 | extra_info = {"test_key": "test_value"}
38 |
39 | # Act
40 | # ---
41 | documents = pdf_reader.load_data(path, extra_info)
42 |
43 | # Assert
44 | # ---
45 | assert isinstance(documents, list)
46 | for doc in documents:
47 | assert isinstance(doc, LlamaIndexDocument)
48 |
49 |
50 | def test_load_data_with_invalid_file_path():
51 | # Arrange
52 | # ---
53 | pdf_reader = PDFMarkdownReader()
54 | extra_info = {"test_key": "test_value"}
55 | path = "fake/path"
56 |
57 | # Act & Assert
58 | # ---
59 | with pytest.raises(Exception):
60 | pdf_reader.load_data(path, extra_info)
61 |
62 |
63 | def test_load_data_with_invalid_extra_info():
64 | # Arrange
65 | # ---
66 | pdf_reader = PDFMarkdownReader()
67 | extra_info = "invalid_extra_info"
68 | path = _get_test_file_path(PDF, __file__)
69 |
70 | # Act & Assert
71 | # ---
72 | with pytest.raises(TypeError):
73 | pdf_reader.load_data(path, extra_info)
74 |
75 |
76 | @pytest.mark.asyncio
77 | async def test_aload_data_with_invalid_file_path():
78 | # Arrange
79 | # ---
80 | pdf_reader = PDFMarkdownReader()
81 | extra_info = {"test_key": "test_value"}
82 |
83 | # Act
84 | # ---
85 | path = "Fake/path"
86 |
87 | # Assert
88 | # ---
89 | with pytest.raises(Exception):
90 | await pdf_reader.aload_data(path, extra_info)
91 |
92 |
93 | @pytest.mark.asyncio
94 | async def test_aload_data_with_invalid_extra_info():
95 | # Arrange
96 | # ---
97 | pdf_reader = PDFMarkdownReader()
98 | extra_info = "invalid_extra_info"
99 |
100 | # Act
101 | # ---
102 | path = _get_test_file_path(PDF, __file__)
103 |
104 | # Assert
105 | # ---
106 | with pytest.raises(TypeError):
107 | await pdf_reader.aload_data(path, extra_info)
108 |
--------------------------------------------------------------------------------