From 874cd05082839b254d8e1b2d425c5aea6d48204f Mon Sep 17 00:00:00 2001 From: tqtensor Date: Tue, 6 May 2025 15:09:52 +0000 Subject: [PATCH 1/2] chore: apply pre-commit --- .github/CODEOWNERS | 2 +- .github/ISSUE_TEMPLATE/bug_report.yml | 2 +- .github/ISSUE_TEMPLATE/feature_request.yml | 2 +- .github/PULL_REQUEST_TEMPLATE.md | 2 +- .github/workflows/ci.yml | 2 +- .github/workflows/codeql.yml | 2 +- .github/workflows/release.yml | 2 +- .gitignore | 20 +- .pre-commit-config.yaml | 33 + CITATION.cff | 2 +- CONTRIBUTING.md | 2 +- Dockerfile | 2 +- Makefile | 2 +- benchmarks/benchmark_results.md | 1 - benchmarks/ground_truth.md | 42 +- benchmarks/scoring.py | 8 +- docker-compose.yml | 12 +- docs/examples/deepseek_demo.ipynb | 130 +- docs/examples/gemini_demo.ipynb | 256 +-- docs/examples/gradio_app.py | 1 + docs/examples/ollama_demo.ipynb | 212 +-- docs/examples/openai_demo.ipynb | 232 +-- docs/examples/streamlit_app.py | 5 +- docs/faq.md | 2 +- docs/ollama_setup.md | 2 +- pyproject.toml | 111 +- src/vision_parse/__init__.py | 7 +- src/vision_parse/image_analysis.j2 | 17 +- src/vision_parse/llm.py | 18 +- src/vision_parse/markdown_prompt.j2 | 16 +- src/vision_parse/parser.py | 20 +- src/vision_parse/utils.py | 13 +- tests/conftest.py | 4 +- tests/test_llm.py | 10 +- tests/test_parser.py | 10 +- uv.lock | 1903 +++++++++++--------- 36 files changed, 1679 insertions(+), 1428 deletions(-) create mode 100644 .pre-commit-config.yaml diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index 2a5c47a..c5c820a 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -1 +1 @@ -* @iamarunbrahma \ No newline at end of file +* @iamarunbrahma diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml index 9bc35fe..b24692a 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.yml +++ b/.github/ISSUE_TEMPLATE/bug_report.yml @@ -43,4 +43,4 @@ body: id: expected attributes: label: Expected Behavior - description: What did you expect to happen? \ No newline at end of file + description: What did you expect to happen? diff --git a/.github/ISSUE_TEMPLATE/feature_request.yml b/.github/ISSUE_TEMPLATE/feature_request.yml index 7d6ac13..934953b 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.yml +++ b/.github/ISSUE_TEMPLATE/feature_request.yml @@ -36,4 +36,4 @@ body: - label: This feature would be useful to other users required: true - label: I'm willing to help implement this feature - required: false \ No newline at end of file + required: false diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md index b0dbd06..813e2e5 100644 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -11,4 +11,4 @@ In short, provide a summary of what this PR does and why. Usually, the relevant - [ ] Ran make lint and make format to handle lint / formatting issues. - [ ] Ran make test to run relevant tests scripts. - [ ] Read the [contributor guidelines](https://github.com/iamarunbrahma/vision-parse/blob/main/CONTRIBUTING.md). -- [ ] Wrote necessary unit or integration tests. \ No newline at end of file +- [ ] Wrote necessary unit or integration tests. diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index b6852da..22e9785 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -36,4 +36,4 @@ jobs: run: | source .venv/bin/activate ruff check . - black . --check \ No newline at end of file + black . --check diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml index 6cc1587..a420357 100644 --- a/.github/workflows/codeql.yml +++ b/.github/workflows/codeql.yml @@ -34,4 +34,4 @@ jobs: - name: Perform CodeQL Analysis uses: github/codeql-action/analyze@v3 with: - category: "/language:${{matrix.language}}" \ No newline at end of file + category: "/language:${{matrix.language}}" diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 91f16e4..124eccb 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -48,4 +48,4 @@ jobs: TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }} run: | source .venv/bin/activate - twine upload dist/* \ No newline at end of file + twine upload dist/* diff --git a/.gitignore b/.gitignore index a105853..4a21278 100644 --- a/.gitignore +++ b/.gitignore @@ -1,17 +1,17 @@ +# Environment variables +.env +.env.* +.DS_Store + # Python-generated files -__pycache__/ +*.egg-info *.py[oc] +__pycache__/ +.pytest_cache/ +.ruff_cache/ build/ dist/ wheels/ -*.egg-info -.ruff_cache/ -.pytest_cache/ -.DS_Store - -# Environment variables -.env -.env.* # Virtual environments -.venv \ No newline at end of file +.venv diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..225765c --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,33 @@ +repos: + - repo: https://github.com/ambv/black + rev: 23.3.0 + hooks: + - id: black + language_version: python3 + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.4.0 + hooks: + - id: check-json + exclude: '(^.vscode/)' + - id: pretty-format-json + exclude: '(^.vscode/)' + args: + - --autofix + - --indent + - '2' + - id: end-of-file-fixer + - id: trailing-whitespace + - repo: https://github.com/pycqa/isort + rev: 5.11.5 + hooks: + - id: isort + args: ['--profile', 'black'] + - repo: local + hooks: + - id: flake8 + name: flake8 + entry: uv run flake8 src + language: system + pass_filenames: false + always_run: true + args: ['--ignore=E203,E501,W503'] diff --git a/CITATION.cff b/CITATION.cff index a0b4644..582bf9d 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -5,4 +5,4 @@ authors: given-names: "Arun" title: "Vision-Parse: Parse PDFs into markdown using Vision LLMs" date-released: 2024-12-31 -url: "https://github.com/iamarunbrahma/vision-parse" \ No newline at end of file +url: "https://github.com/iamarunbrahma/vision-parse" diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 374b24b..abf4c55 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -75,4 +75,4 @@ By participating in this project, you agree to abide by our Code of Conduct: 2. **Create Pull Request** - Go to your fork on GitHub and click "New Pull Request" - Select your feature branch - - Fill in the PR template by describing your changes, and referencing related issue. \ No newline at end of file + - Fill in the PR template by describing your changes, and referencing related issue. diff --git a/Dockerfile b/Dockerfile index 2fc97e4..1f08d16 100644 --- a/Dockerfile +++ b/Dockerfile @@ -40,4 +40,4 @@ esac\n\ exec "$@"' > /start.sh && chmod +x /start.sh ENTRYPOINT ["/start.sh"] -CMD ["tail", "-f", "/dev/null"] \ No newline at end of file +CMD ["tail", "-f", "/dev/null"] diff --git a/Makefile b/Makefile index a64b207..2713090 100644 --- a/Makefile +++ b/Makefile @@ -23,4 +23,4 @@ tag: release: build tag @echo "Release workflow will be triggered by the tag push" - @echo "Distribution files are available in ./dist directory" \ No newline at end of file + @echo "Distribution files are available in ./dist directory" diff --git a/benchmarks/benchmark_results.md b/benchmarks/benchmark_results.md index dcd1f39..e931f58 100644 --- a/benchmarks/benchmark_results.md +++ b/benchmarks/benchmark_results.md @@ -20,4 +20,3 @@ Generated on: 2025-01-03 16:15:01 - Number of runs: 3 - Individual accuracy scores: 0.52, 0.52, 0.52 - diff --git a/benchmarks/ground_truth.md b/benchmarks/ground_truth.md index ad0a2ba..3928d91 100644 --- a/benchmarks/ground_truth.md +++ b/benchmarks/ground_truth.md @@ -7,10 +7,10 @@ Quantum Computing is a revolutionary paradigm that leverages the principles of q ## Key Concepts in Quantum Computing --- -### 1. *Quantum Mechanics Basics* -Quantum computing is built on the principles of: -- **Superposition**: A qubit can represent both 0 and 1 simultaneously. -- **Entanglement**: Qubits can become interconnected, influencing each other regardless of distance. +### 1. *Quantum Mechanics Basics* +Quantum computing is built on the principles of: +- **Superposition**: A qubit can represent both 0 and 1 simultaneously. +- **Entanglement**: Qubits can become interconnected, influencing each other regardless of distance. - **Quantum Interference**: Amplifies correct solutions and suppresses incorrect ones. ### 2. *Classical vs Quantum Computing* @@ -26,42 +26,42 @@ Quantum computing is built on the principles of: ## Applications of Quantum Computing --- -1. **Cryptography** - - Breaking traditional encryption systems (e.g., RSA). +1. **Cryptography** + - Breaking traditional encryption systems (e.g., RSA). - Building unbreakable quantum encryption. -2. **Healthcare** - - Drug discovery through quantum simulations. +2. **Healthcare** + - Drug discovery through quantum simulations. - Optimizing protein folding patterns. -3. **Artificial Intelligence (AI)** - - Enhancing machine learning algorithms. +3. **Artificial Intelligence (AI)** + - Enhancing machine learning algorithms. - Faster data processing and pattern recognition. ### Advantages and Challenges -**Advantages** -1. Exponential computational power. -2. Solves problems intractable for classical computers. +**Advantages** +1. Exponential computational power. +2. Solves problems intractable for classical computers. -**Challenges** -1. **Hardware stability**: Qubits are fragile and error-prone. -2. **Scalability**: Building large quantum systems is expensive. +**Challenges** +1. **Hardware stability**: Qubits are fragile and error-prone. +2. **Scalability**: Building large quantum systems is expensive. 3. **Software development**: Limited programming frameworks. ### Key Players in Quantum Computing --- -Some organizations leading the quantum revolution include: -- [IBM Quantum](https://www.ibm.com/quantum-computing) -- [Google Quantum AI](https://quantumai.google) -- [Microsoft Azure Quantum](https://azure.microsoft.com/en-us/services/quantum/) +Some organizations leading the quantum revolution include: +- [IBM Quantum](https://www.ibm.com/quantum-computing) +- [Google Quantum AI](https://quantumai.google) +- [Microsoft Azure Quantum](https://azure.microsoft.com/en-us/services/quantum/) - [D-Wave](https://www.dwavesys.com) ## Conclusion --- -Quantum computing is still in its infancy but holds immense promise to redefine technology. As research progresses, it has the potential to solve problems deemed insurmountable by classical computing systems. \ No newline at end of file +Quantum computing is still in its infancy but holds immense promise to redefine technology. As research progresses, it has the potential to solve problems deemed insurmountable by classical computing systems. diff --git a/benchmarks/scoring.py b/benchmarks/scoring.py index d971312..b44509c 100644 --- a/benchmarks/scoring.py +++ b/benchmarks/scoring.py @@ -1,12 +1,14 @@ import os +import statistics +from datetime import datetime from pathlib import Path + import nltk -from nltk.translate.bleu_score import sentence_bleu from Levenshtein import distance from markitdown import MarkItDown +from nltk.translate.bleu_score import sentence_bleu + from vision_parse import VisionParser -import statistics -from datetime import datetime # Download required NLTK data nltk.download("punkt") diff --git a/docker-compose.yml b/docker-compose.yml index 617635e..72028d6 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -9,24 +9,24 @@ services: - MODEL_NAME=${MODEL_NAME:?MODEL_NAME is required} environment: - MODEL_NAME=${MODEL_NAME:?MODEL_NAME is required} - - OPENAI_API_KEY=${OPENAI_API_KEY:-} # Optional: For OpenAI models - - GEMINI_API_KEY=${GEMINI_API_KEY:-} # Optional: For Gemini models + - OPENAI_API_KEY=${OPENAI_API_KEY:-} # Optional: For OpenAI models + - GEMINI_API_KEY=${GEMINI_API_KEY:-} # Optional: For Gemini models volumes: - .:/app working_dir: /app tty: true stdin_open: true ports: - - "11434:11434" # Expose Ollama port + - '11434:11434' # Expose Ollama port deploy: resources: limits: - memory: 16G # Set memory limit to 16GB + memory: 16G # Set memory limit to 16GB reservations: - memory: 8G # Guarantee at least 8GB + memory: 8G # Guarantee at least 8GB # Uncomment below lines if you have NVIDIA GPU available # devices: # - driver: nvidia # count: all # capabilities: [gpu] - command: tail -f /dev/null # Keep container running + command: tail -f /dev/null # Keep container running diff --git a/docs/examples/deepseek_demo.ipynb b/docs/examples/deepseek_demo.ipynb index db09bb5..69b89c2 100644 --- a/docs/examples/deepseek_demo.ipynb +++ b/docs/examples/deepseek_demo.ipynb @@ -1,68 +1,68 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Using Vision Parse with DeepSeek" - ] + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Vision Parse with DeepSeek" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook demonstrates how to use Vision Parse with DeepSeek." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install 'vision-parse[openai]' -Uqq # install the vision-parse package with openai" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from vision_parse import VisionParser\n", + "import os\n", + "\n", + "# Initialize parser\n", + "parser = VisionParser(\n", + " model_name=\"deepseek-chat\",\n", + " api_key=os.getenv(\"DEEPSEEK_API_KEY\"),\n", + " temperature=0.9,\n", + " top_p=0.4,\n", + " image_mode=None,\n", + " detailed_extraction=True,\n", + " enable_concurrency=True,\n", + ")\n", + "\n", + "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", + "markdown_pages = parser.convert_pdf(pdf_path)\n", + "\n", + "# Print the markdown pages\n", + "for i, page_content in enumerate(markdown_pages):\n", + " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "personal", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.10.9" + } }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook demonstrates how to use Vision Parse with DeepSeek." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install 'vision-parse[openai]' -Uqq # install the vision-parse package with openai" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from vision_parse import VisionParser\n", - "import os\n", - "\n", - "# Initialize parser\n", - "parser = VisionParser(\n", - " model_name=\"deepseek-chat\",\n", - " api_key=os.getenv(\"DEEPSEEK_API_KEY\"),\n", - " temperature=0.9,\n", - " top_p=0.4,\n", - " image_mode=None,\n", - " detailed_extraction=True,\n", - " enable_concurrency=True,\n", - ")\n", - "\n", - "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", - "markdown_pages = parser.convert_pdf(pdf_path)\n", - "\n", - "# Print the markdown pages\n", - "for i, page_content in enumerate(markdown_pages):\n", - " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "personal", - "language": "python", - "name": "python3" - }, - "language_info": { - "name": "python", - "version": "3.10.9" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/docs/examples/gemini_demo.ipynb b/docs/examples/gemini_demo.ipynb index 92c98b7..4fee681 100644 --- a/docs/examples/gemini_demo.ipynb +++ b/docs/examples/gemini_demo.ipynb @@ -1,137 +1,137 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Using Vision Parse with Google Gemini" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook demonstrates how to use Vision Parse with Google Gemini." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install 'vision-parse[gemini]' -Uqq # install the vision-parse package with gemini" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/arunbrahma/anaconda3/envs/mp/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n", - "Converting pages in PDF file into markdown format: 100%|██████████| 1/1 [00:15<00:00, 15.82s/it]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Vision Parse with Google Gemini" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Page 1 ---\n", - "# TEXAS A&M\n", - "# AGRILIFE\n", - "# EXTENSION\n", - "\n", - "March 3, 2020\n", - "\n", - "TO: JR Sprague, TCAAA D1 Chairman\n", - "\n", - "FROM: Andy Holloway, CEA ANR Hemphill County\n", - "\n", - "Regarding the three chairmanships appointed to me none have any action\n", - "needed at this time except for the rules to be submitted to be posted on the\n", - "TCAAA website for the Texas Holdem Tournament. Please note the following:\n", - "\n", - "# Texas Hold'em Basic Poker Rules\n", - "\n", - "Texas Hold'em is played with a standard deck of 52 cards. The object of the game is to make the best\n", - "possible five-card poker hand using any combination of the two card's in a player's hand (known as\n", - "the \"hole cards\") and the five community cards that the dealer places in the middle of the table, which\n", - "can be used by all players. The standard hand rankings are used, as follows (from best to worst):\n", - "\n", - "* Straight Flush: Any five cards of the same suit and consecutive rank; the best of these hands,\n", - "AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, aces may be\n", - "played as high or low cards.\n", - "* Four of a Kind: Any four cards of the same rank.\n", - "* Full House: Any three cards from a single rank combined with a pair from a different rank (i.e.,\n", - "TT55).\n", - "* Flush: Any five cards of the same suit.\n", - "* Straight: Any five cards of consecutive ranks (i.e., 34567).\n", - "* Three of a Kind: Any three cards of the same rank.\n", - "* Two Pair: Any two pairs of cards from the same ranks (ie, 5599A).\n", - "* One Pair: Any two cards of the same rank.\n", - "* High Card: Hands that do not fit any of the above categories are ranked based on the highest card\n", - "in their hand (aces are high), then by the second highest card, and so on.\n", - "\n", - "\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook demonstrates how to use Vision Parse with Google Gemini." + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install 'vision-parse[gemini]' -Uqq # install the vision-parse package with gemini" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/arunbrahma/anaconda3/envs/mp/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n", + "Converting pages in PDF file into markdown format: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:15<00:00, 15.82s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "--- Page 1 ---\n", + "# TEXAS A&M\n", + "# AGRILIFE\n", + "# EXTENSION\n", + "\n", + "March 3, 2020\n", + "\n", + "TO: JR Sprague, TCAAA D1 Chairman\n", + "\n", + "FROM: Andy Holloway, CEA ANR Hemphill County\n", + "\n", + "Regarding the three chairmanships appointed to me none have any action\n", + "needed at this time except for the rules to be submitted to be posted on the\n", + "TCAAA website for the Texas Holdem Tournament. Please note the following:\n", + "\n", + "# Texas Hold'em Basic Poker Rules\n", + "\n", + "Texas Hold'em is played with a standard deck of 52 cards. The object of the game is to make the best\n", + "possible five-card poker hand using any combination of the two card's in a player's hand (known as\n", + "the \"hole cards\") and the five community cards that the dealer places in the middle of the table, which\n", + "can be used by all players. The standard hand rankings are used, as follows (from best to worst):\n", + "\n", + "* Straight Flush: Any five cards of the same suit and consecutive rank; the best of these hands,\n", + "AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, aces may be\n", + "played as high or low cards.\n", + "* Four of a Kind: Any four cards of the same rank.\n", + "* Full House: Any three cards from a single rank combined with a pair from a different rank (i.e.,\n", + "TT55).\n", + "* Flush: Any five cards of the same suit.\n", + "* Straight: Any five cards of consecutive ranks (i.e., 34567).\n", + "* Three of a Kind: Any three cards of the same rank.\n", + "* Two Pair: Any two pairs of cards from the same ranks (ie, 5599A).\n", + "* One Pair: Any two cards of the same rank.\n", + "* High Card: Hands that do not fit any of the above categories are ranked based on the highest card\n", + "in their hand (aces are high), then by the second highest card, and so on.\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from vision_parse import VisionParser\n", + "import os\n", + "\n", + "# Initialize parser\n", + "parser = VisionParser(\n", + " model_name=\"gemini-1.5-flash\",\n", + " api_key=os.getenv(\"GEMINI_API_KEY\"),\n", + " temperature=0.9,\n", + " top_p=0.4,\n", + " max_output_tokens=2048,\n", + " image_mode=\"url\",\n", + " detailed_extraction=True,\n", + ")\n", + "\n", + "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", + "markdown_pages = parser.convert_pdf(pdf_path)\n", + "\n", + "# Print the markdown pages\n", + "for i, page_content in enumerate(markdown_pages):\n", + " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.1" } - ], - "source": [ - "from vision_parse import VisionParser\n", - "import os\n", - "\n", - "# Initialize parser\n", - "parser = VisionParser(\n", - " model_name=\"gemini-1.5-flash\",\n", - " api_key=os.getenv(\"GEMINI_API_KEY\"),\n", - " temperature=0.9,\n", - " top_p=0.4,\n", - " max_output_tokens=2048,\n", - " image_mode=\"url\",\n", - " detailed_extraction=True,\n", - ")\n", - "\n", - "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", - "markdown_pages = parser.convert_pdf(pdf_path)\n", - "\n", - "# Print the markdown pages\n", - "for i, page_content in enumerate(markdown_pages):\n", - " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mp", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/docs/examples/gradio_app.py b/docs/examples/gradio_app.py index e06d058..46b6757 100644 --- a/docs/examples/gradio_app.py +++ b/docs/examples/gradio_app.py @@ -1,4 +1,5 @@ import os + import gradio as gr from dotenv import load_dotenv diff --git a/docs/examples/ollama_demo.ipynb b/docs/examples/ollama_demo.ipynb index 9cf3d40..1fcddf7 100644 --- a/docs/examples/ollama_demo.ipynb +++ b/docs/examples/ollama_demo.ipynb @@ -1,115 +1,115 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Using Vision Parse with Ollama" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook demonstrates how to use Vision Parse with Ollama." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install vision-parse -Uqq # install the vision-parse package with ollama" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "Converting pages in PDF file into markdown format: 100%|██████████| 1/1 [00:48<00:00, 48.24s/it]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Vision Parse with Ollama" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Page 1 ---\n", - "**Extracted Text**\n", - "\n", - "* **TO:** JR Sprague, TCAAA D1 Chairman\n", - " * FROM: Andy Holloway, CEA ANR Hemphill County\n", - " * Regarding the three chairmanships appointed to me none have any action needed at this time except for the rules to be submitted to be posted on the TCAAA website for the Texas Holdem Tournament. Please note the following:\n", - "* **Texas Hold'em Basic Poker Rules**\n", - " * Straight Flush: Any five cards of the same suit and consecutive rank; the best of these hands, AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, Aces may be played as high or low cards.\n", - " * Four of a Kind: Any four cards of the same rank.\n", - " * Full House: Any three cards from a single rank combined with a pair from a different rank (i.e., TTT55).\n", - " * Flush: Any five cards of the same suit.\n", - " * Straight: Any five cards of consecutive ranks (i.e., 34567).\n", - " * Three of a Kind: Any three cards of the same rank.\n", - " * Two Pair: Any two pairs of cards from the same ranks (i.e., 5599A).\n", - " * One Pair: Any two cards of the same rank.\n", - " * High Card: Hands that do not fit any of the above categories are ranked based on the highest card in their hand (aces are high), then by the second highest card, and so on.\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook demonstrates how to use Vision Parse with Ollama." + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install vision-parse -Uqq # install the vision-parse package with ollama" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Converting pages in PDF file into markdown format: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:48<00:00, 48.24s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "--- Page 1 ---\n", + "**Extracted Text**\n", + "\n", + "* **TO:** JR Sprague, TCAAA D1 Chairman\n", + " * FROM: Andy Holloway, CEA ANR Hemphill County\n", + " * Regarding the three chairmanships appointed to me none have any action needed at this time except for the rules to be submitted to be posted on the TCAAA website for the Texas Holdem Tournament. Please note the following:\n", + "* **Texas Hold'em Basic Poker Rules**\n", + " * Straight Flush: Any five cards of the same suit and consecutive rank; the best of these hands, AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, Aces may be played as high or low cards.\n", + " * Four of a Kind: Any four cards of the same rank.\n", + " * Full House: Any three cards from a single rank combined with a pair from a different rank (i.e., TTT55).\n", + " * Flush: Any five cards of the same suit.\n", + " * Straight: Any five cards of consecutive ranks (i.e., 34567).\n", + " * Three of a Kind: Any three cards of the same rank.\n", + " * Two Pair: Any two pairs of cards from the same ranks (i.e., 5599A).\n", + " * One Pair: Any two cards of the same rank.\n", + " * High Card: Hands that do not fit any of the above categories are ranked based on the highest card in their hand (aces are high), then by the second highest card, and so on.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from vision_parse import VisionParser\n", + "\n", + "parser = VisionParser(\n", + " model_name=\"llama3.2-vision:11b\",\n", + " temperature=0.7,\n", + " top_p=0.4,\n", + " num_ctx=4096,\n", + " num_predict=4096,\n", + " ollama_config={\n", + " \"OLLAMA_NUM_PARALLEL\": \"10\",\n", + " },\n", + " image_mode=\"base64\",\n", + " detailed_extraction=True,\n", + " enable_concurrency=True,\n", + ")\n", + "\n", + "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", + "markdown_pages = parser.convert_pdf(pdf_path)\n", + "\n", + "for i, page_content in enumerate(markdown_pages):\n", + " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.0" } - ], - "source": [ - "from vision_parse import VisionParser\n", - "\n", - "parser = VisionParser(\n", - " model_name=\"llama3.2-vision:11b\",\n", - " temperature=0.7,\n", - " top_p=0.4,\n", - " num_ctx=4096,\n", - " num_predict=4096,\n", - " ollama_config={\n", - " \"OLLAMA_NUM_PARALLEL\": \"10\",\n", - " },\n", - " image_mode=\"base64\",\n", - " detailed_extraction=True,\n", - " enable_concurrency=True,\n", - ")\n", - "\n", - "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", - "markdown_pages = parser.convert_pdf(pdf_path)\n", - "\n", - "for i, page_content in enumerate(markdown_pages):\n", - " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mp", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/docs/examples/openai_demo.ipynb b/docs/examples/openai_demo.ipynb index 0aae981..edeb13b 100644 --- a/docs/examples/openai_demo.ipynb +++ b/docs/examples/openai_demo.ipynb @@ -1,125 +1,125 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Using Vision Parse with OpenAI" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook demonstrates how to use Vision Parse with OpenAI." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "!pip install 'vision-parse[openai]' -Uqq # install the vision-parse package with openai" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "Converting pages in PDF file into markdown format: 100%|██████████| 1/1 [00:25<00:00, 25.21s/it]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Vision Parse with OpenAI" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Page 1 ---\n", - "# TEXAS A&M \n", - "AGRILIFE \n", - "EXTENSION\n", - "\n", - "March 3, 2020\n", - "\n", - "TO: JR Sprague, TCAAA D1 Chairman \n", - "FROM: Andy Holloway, CEA ANR Hemphill County\n", - "\n", - "Regarding the three chairmanships appointed to me none have any action needed at this time except for the rules to be submitted to be posted on the TCAAA website for the Texas Holdem Tournament. Please note the following:\n", - "\n", - "## Texas Hold'em Basic Poker Rules\n", - "\n", - "Texas Hold'em is played with a standard deck of 52 cards. The object of the game is to make the best possible five-card poker hand using any combination of the two card's in a player's hand (known as the \"hole cards\") and the five community cards that the dealer places in the middle of the table, which can be used by all players. The standard hand rankings are used, as follows (from best to worst):\n", - "\n", - "- **Straight Flush**: Any five cards of the same suit and consecutive rank; the best of these hands, AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, aces may be played as high or low cards.\n", - "- **Four of a Kind**: Any four cards of the same rank.\n", - "- **Full House**: Any three cards from a single rank combined with a pair from a different rank (i.e., TTT55).\n", - "- **Flush**: Any five cards of the same suit.\n", - "- **Straight**: Any five cards of consecutive ranks (i.e., 34567).\n", - "- **Three of a Kind**: Any three cards of the same rank.\n", - "- **Two Pair**: Any two pairs of cards from the same ranks (ie, 5599A).\n", - "- **One Pair**: Any two cards of the same rank.\n", - "- **High Card**: Hands that do not fit any of the above categories are ranked based on the highest card in their hand (aces are high), then by the second highest card, and so on.\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook demonstrates how to use Vision Parse with OpenAI." + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install 'vision-parse[openai]' -Uqq # install the vision-parse package with openai" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Converting pages in PDF file into markdown format: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:25<00:00, 25.21s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "--- Page 1 ---\n", + "# TEXAS A&M \n", + "AGRILIFE \n", + "EXTENSION\n", + "\n", + "March 3, 2020\n", + "\n", + "TO: JR Sprague, TCAAA D1 Chairman \n", + "FROM: Andy Holloway, CEA ANR Hemphill County\n", + "\n", + "Regarding the three chairmanships appointed to me none have any action needed at this time except for the rules to be submitted to be posted on the TCAAA website for the Texas Holdem Tournament. Please note the following:\n", + "\n", + "## Texas Hold'em Basic Poker Rules\n", + "\n", + "Texas Hold'em is played with a standard deck of 52 cards. The object of the game is to make the best possible five-card poker hand using any combination of the two card's in a player's hand (known as the \"hole cards\") and the five community cards that the dealer places in the middle of the table, which can be used by all players. The standard hand rankings are used, as follows (from best to worst):\n", + "\n", + "- **Straight Flush**: Any five cards of the same suit and consecutive rank; the best of these hands, AKQJT of a single suit, is known as a Royal Flush. For these and regular straights, aces may be played as high or low cards.\n", + "- **Four of a Kind**: Any four cards of the same rank.\n", + "- **Full House**: Any three cards from a single rank combined with a pair from a different rank (i.e., TTT55).\n", + "- **Flush**: Any five cards of the same suit.\n", + "- **Straight**: Any five cards of consecutive ranks (i.e., 34567).\n", + "- **Three of a Kind**: Any three cards of the same rank.\n", + "- **Two Pair**: Any two pairs of cards from the same ranks (ie, 5599A).\n", + "- **One Pair**: Any two cards of the same rank.\n", + "- **High Card**: Hands that do not fit any of the above categories are ranked based on the highest card in their hand (aces are high), then by the second highest card, and so on.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from vision_parse import VisionParser\n", + "import os\n", + "\n", + "# Initialize parser\n", + "parser = VisionParser(\n", + " model_name=\"gpt-4o\",\n", + " api_key=os.getenv(\"OPENAI_API_KEY\"),\n", + " temperature=0.9,\n", + " top_p=0.4,\n", + " max_tokens=4096,\n", + " frequency_penalty=0.3,\n", + " image_mode=None,\n", + " detailed_extraction=True,\n", + " enable_concurrency=True,\n", + ")\n", + "\n", + "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", + "markdown_pages = parser.convert_pdf(pdf_path)\n", + "\n", + "# Print the markdown pages\n", + "for i, page_content in enumerate(markdown_pages):\n", + " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.0" } - ], - "source": [ - "from vision_parse import VisionParser\n", - "import os\n", - "\n", - "# Initialize parser\n", - "parser = VisionParser(\n", - " model_name=\"gpt-4o\",\n", - " api_key=os.getenv(\"OPENAI_API_KEY\"),\n", - " temperature=0.9,\n", - " top_p=0.4,\n", - " max_tokens=4096,\n", - " frequency_penalty=0.3,\n", - " image_mode=None,\n", - " detailed_extraction=True,\n", - " enable_concurrency=True,\n", - ")\n", - "\n", - "pdf_path = \"../tests/Texas-Holdem-Rules.pdf\"\n", - "markdown_pages = parser.convert_pdf(pdf_path)\n", - "\n", - "# Print the markdown pages\n", - "for i, page_content in enumerate(markdown_pages):\n", - " print(f\"\\n--- Page {i+1} ---\\n{page_content}\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "mp", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/docs/examples/streamlit_app.py b/docs/examples/streamlit_app.py index 45b6185..74e69db 100644 --- a/docs/examples/streamlit_app.py +++ b/docs/examples/streamlit_app.py @@ -1,7 +1,8 @@ -from pathlib import Path -from typing import Optional, Union, List import gc import os +from pathlib import Path +from typing import List, Optional, Union + import pyperclip import streamlit as st from dotenv import load_dotenv diff --git a/docs/faq.md b/docs/faq.md index 5156427..e6b1543 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -15,7 +15,7 @@ 3. **The llama3.2-vision:11b model was hallucinating and unable to extract content accurately from the PDF document. How can I improve the extraction accuracy of locally hosted vision models?** To improve extraction accuracy with the llama3.2-vision:11b model: - + - **Adjust Model Parameters**: Lower the `temperature` and `top_p` for more deterministic outputs and to reduce hallucinations. - **Define Custom Prompts**: By defining custom prompts according to your document structure, you can guide the model to extract content more accurately. - **Enable Detailed Extraction**: Enabling `detailed_extraction` will help the Vision LLM detect the presence of images, LaTeX equations, structured, and semi-structured tables, and then extract them with high accuracy. diff --git a/docs/ollama_setup.md b/docs/ollama_setup.md index 8bce640..e3df5c3 100644 --- a/docs/ollama_setup.md +++ b/docs/ollama_setup.md @@ -24,4 +24,4 @@ 3. **Verify** server status: ```bash curl http://localhost:11434/api/version - ``` \ No newline at end of file + ``` diff --git a/pyproject.toml b/pyproject.toml index d8f4fe0..799a5d1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,85 +1,88 @@ [build-system] -requires = ["hatchling", "hatch-vcs"] build-backend = "hatchling.build" +requires = ["hatchling", "hatch-vcs"] [project] -name = "vision-parse" -dynamic = ["version"] -description = "Parse PDF documents into markdown formatted content using Vision LLMs" -readme = "README.md" -requires-python = ">=3.9" -license = "MIT" authors = [ - { name = "Arun Brahma", email = "mithubrahma@gmail.com" } -] -keywords = [ - "pdf", - "markdown", - "pdf to markdown", - "vision llm", - "document parser", - "ocr", + {name = "Arun Brahma", email = "mithubrahma@gmail.com"} ] classifiers = [ - "Development Status :: 3 - Alpha", - "Intended Audience :: Developers", - "License :: OSI Approved :: MIT License", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.9", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", + "Development Status :: 3 - Alpha", + "Intended Audience :: Developers", + "License :: OSI Approved :: MIT License", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13" ] dependencies = [ - "jinja2>=3.0.0", - "nest-asyncio>=1.6.0", - "numpy>=2.0.0", - "ollama>=0.4.4", - "opencv-python>=4.10.0.84", - "pydantic>=2.0.0", - "pymupdf>=1.22.0", - "tenacity>=9.0.0", - "tqdm>=4.65.0", + "jinja2>=3.0.0", + "nest-asyncio>=1.6.0", + "numpy>=2.0.0", + "ollama>=0.4.4", + "opencv-python>=4.10.0.84", + "pydantic>=2.0.0", + "pymupdf>=1.22.0", + "tenacity>=9.0.0", + "tqdm>=4.65.0" ] +description = "Parse PDF documents into markdown formatted content using Vision LLMs" +dynamic = ["version"] +keywords = [ + "pdf", + "markdown", + "pdf to markdown", + "vision llm", + "document parser", + "ocr" +] +license = "MIT" +name = "vision-parse" +readme = "README.md" +requires-python = ">=3.9" [project.urls] Homepage = "https://github.com/iamarunbrahma/vision-parse" Repository = "https://github.com/iamarunbrahma/vision-parse.git" [project.optional-dependencies] +all = [ + "google-generativeai==0.8.3", + "openai==1.59.8" +] dev = [ - "black>=24.4.1", - "black[jupyter]>=24.8.0", - "build>=1.2.2", - "pytest>=8.3.4", - "pytest-asyncio>=0.23.5", - "ruff>=0.8.3", - "twine>=6.0.1", + "black>=24.4.1", + "black[jupyter]>=24.8.0", + "build>=1.2.2", + "flake8>=7.2.0", + "pre-commit>=4.2.0", + "pytest>=8.3.4", + "pytest-asyncio>=0.23.5", + "ruff>=0.8.3", + "toml-sort>=0.24.2", + "twine>=6.0.1" ] gemini = [ - "google-generativeai==0.8.3", + "google-generativeai==0.8.3" ] openai = [ - "openai==1.59.8", -] -all = [ - "google-generativeai==0.8.3", - "openai==1.59.8", + "openai==1.59.8" ] [tool.hatch.build.targets.wheel] packages = ["src/vision_parse"] +[tool.hatch.build.targets.wheel.force-include] +"src/vision_parse/image_analysis.j2" = "vision_parse/image_analysis.j2" +"src/vision_parse/markdown_prompt.j2" = "vision_parse/markdown_prompt.j2" + [tool.hatch.build.targets.sdist] include = [ - "/src/vision_parse", - "/tests", + "/src/vision_parse", + "/tests" ] -[tool.hatch.build.targets.wheel.force-include] -"src/vision_parse/markdown_prompt.j2" = "vision_parse/markdown_prompt.j2" -"src/vision_parse/image_analysis.j2" = "vision_parse/image_analysis.j2" - [tool.hatch.version] -source = "vcs" \ No newline at end of file +source = "vcs" diff --git a/src/vision_parse/__init__.py b/src/vision_parse/__init__.py index 5d1ab8f..9f59a73 100644 --- a/src/vision_parse/__init__.py +++ b/src/vision_parse/__init__.py @@ -1,8 +1,9 @@ -from .parser import VisionParser, PDFPageConfig, VisionParserError, UnsupportedFileError +from importlib.metadata import PackageNotFoundError, version + +from .constants import SUPPORTED_MODELS from .llm import LLMError, UnsupportedModelError +from .parser import PDFPageConfig, UnsupportedFileError, VisionParser, VisionParserError from .utils import ImageExtractionError -from importlib.metadata import version, PackageNotFoundError -from .constants import SUPPORTED_MODELS try: __version__ = version("vision-parse") diff --git a/src/vision_parse/image_analysis.j2 b/src/vision_parse/image_analysis.j2 index 0627747..856c133 100644 --- a/src/vision_parse/image_analysis.j2 +++ b/src/vision_parse/image_analysis.j2 @@ -1,18 +1,19 @@ {% autoescape true %} - Analyze this image and return a detailed JSON description including any text detected, images detected, tables detected, latex equations detected, extracted text and confidence score for the extracted text. + - Confidence score for the extracted text should be a float value between 0 and 1. If you cannot determine certain details, leave those fields empty or zero. - Ensure markdown text formatting for extracted text is applied properly by analyzing the image. - Please ensure that the JSON object is valid and all the fields are present in the response as below: ```json { - "text_detected": "Yes" | "No", - "images_detected": "Yes" | "No", - "tables_detected": "Yes" | "No", - "latex_equations_detected": "Yes" | "No", - "extracted_text": "Extracted text from the image", - "confidence_score_text": "Confidence score for the extracted text" + "text_detected": "Yes" | "No", + "images_detected": "Yes" | "No", + "tables_detected": "Yes" | "No", + "latex_equations_detected": "Yes" | "No", + "extracted_text": "Extracted text from the image", + "confidence_score_text": "Confidence score for the extracted text" } ``` -{% endautoescape %} \ No newline at end of file + +{% endautoescape %} diff --git a/src/vision_parse/llm.py b/src/vision_parse/llm.py index 703e4c3..27b230b 100644 --- a/src/vision_parse/llm.py +++ b/src/vision_parse/llm.py @@ -1,14 +1,16 @@ -from typing import Literal, Dict, Any, Union -from pydantic import BaseModel -from jinja2 import Template +import logging +import os import re +from typing import Any, Dict, Literal, Union + import fitz -import os -from tqdm import tqdm -from .utils import ImageData +from jinja2 import Template +from pydantic import BaseModel from tenacity import retry, stop_after_attempt, wait_exponential +from tqdm import tqdm + from .constants import SUPPORTED_MODELS -import logging +from .utils import ImageData logger = logging.getLogger(__name__) @@ -188,7 +190,7 @@ def _init_llm(self) -> None: ): try: import openai - from openai import AzureOpenAI, AsyncAzureOpenAI + from openai import AsyncAzureOpenAI, AzureOpenAI except ImportError: raise ImportError( "OpenAI is not installed. Please install it using pip install 'vision-parse[openai]'." diff --git a/src/vision_parse/markdown_prompt.j2 b/src/vision_parse/markdown_prompt.j2 index ced85ee..72e172d 100644 --- a/src/vision_parse/markdown_prompt.j2 +++ b/src/vision_parse/markdown_prompt.j2 @@ -4,27 +4,29 @@ Your task is to analyze the given image and extract textual content in markdown {% if confidence_score_text is defined and confidence_score_text|float > 0.6 %} - Compare if the extracted text matches with the image content:\n\n```markdown\n{{ extracted_text|escape|trim }}\n```\n\n -- Strictly do not change any content in the original extracted text while applying markdown formatting and do not repeat the extracted text. +- Strictly do not change any content in the original extracted text while applying markdown formatting. {% else %} - Analyze this image carefully and extract all the content from the provided image in markdown format. - Ensure markdown text formatting for extracted text is applied properly by analyzing the image. -- Strictly do not change any content in the original extracted text while applying markdown formatting and do not repeat the extracted text. +- Strictly do not change any content in the original extracted text while applying markdown formatting. {% endif %} {% if tables_detected is defined and tables_detected|string == "Yes" %} - If tables are detected, preserve the tabular structure in markdown format using | for columns and - for the header row separator. - Ensure that the cell values are properly aligned within the table columns and the tabular data is not distorted. -- Maintain the original positioning of the table within the scanned document. Strictly do not include any additional explanations or comments. +- Maintain the original positioning of the table within the scanned document. +- Strictly do not include any additional explanations or comments about tables. {% endif %} {% if latex_equations_detected is defined and latex_equations_detected|string == "Yes" %} - If latex equations are detected, preserve the inline math equations and block math equations in LaTeX format using math symbols, superscripts, subscripts, and other LaTeX formatting. -- If inline equations are detected, strictly enclose them in single dollar signs i.e. $...$ and if block equations are detected, strictly enclose them in double dollar signs i.e. $$...$$. -- Strictly ensure that the LaTeX formatting is valid. Strictly do not include any additional explanations or comments. +- If inline equations are detected, strictly enclose them in single dollar signs i.e. $...$ and if block equations are detected, strictly enclose them in double dollar signs i.e. $$...$$ +- Strictly ensure that the LaTeX formatting is valid. +- Strictly do not include any additional explanations or comments about equations. {% endif %} - Strictly preserve markdown text formatting if present such as horizontal lines, header levels, footers, bullet points, links/urls, or other markdown elements. -- Strictly, do not omit any textual content from the markdown formatted extracted text. +- Strictly do not omit any textual content from the markdown formatted extracted text. - Strictly do not include any additional explanations or comments in the markdown formatted extracted text. - Strictly do not generate code fences or backticks like ``` or ```markdown. @@ -32,4 +34,4 @@ Your task is to analyze the given image and extract textual content in markdown {{ custom_prompt|string }} {% endif %} -{% endautoescape %} \ No newline at end of file +{% endautoescape %} diff --git a/src/vision_parse/parser.py b/src/vision_parse/parser.py index 6bc9b49..f72d301 100644 --- a/src/vision_parse/parser.py +++ b/src/vision_parse/parser.py @@ -1,15 +1,17 @@ -import fitz # PyMuPDF library for PDF processing -from pathlib import Path -from typing import Optional, List, Dict, Union, Literal, Any -from tqdm import tqdm -import base64 -from pydantic import BaseModel import asyncio -from .utils import get_device_config -from .llm import LLM -import nest_asyncio +import base64 import logging import warnings +from pathlib import Path +from typing import Any, Dict, List, Literal, Optional, Union + +import fitz # PyMuPDF library for PDF processing +import nest_asyncio +from pydantic import BaseModel +from tqdm import tqdm + +from .llm import LLM +from .utils import get_device_config logger = logging.getLogger(__name__) nest_asyncio.apply() diff --git a/src/vision_parse/utils.py b/src/vision_parse/utils.py index c8f5139..bb296f0 100644 --- a/src/vision_parse/utils.py +++ b/src/vision_parse/utils.py @@ -1,11 +1,12 @@ -import fitz -import numpy as np -import cv2 import base64 -from typing import List, Tuple, Literal, ClassVar +import logging from dataclasses import dataclass from threading import Lock -import logging +from typing import ClassVar, List, Literal, Tuple + +import cv2 +import fitz +import numpy as np logger = logging.getLogger(__name__) @@ -145,9 +146,9 @@ def extract_images( def get_device_config() -> Tuple[Literal["cuda", "mps", "cpu"], int]: """Get optimal number of worker processes based on device.""" + import os import platform import subprocess - import os try: nvidia_smi = subprocess.run( diff --git a/tests/conftest.py b/tests/conftest.py index 5d05d72..afa55af 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,6 +1,8 @@ -import pytest from pathlib import Path + import fitz # PyMuPDF library for PDF handling +import pytest + from vision_parse.parser import PDFPageConfig, VisionParser diff --git a/tests/test_llm.py b/tests/test_llm.py index 5b38e2c..3a3f233 100644 --- a/tests/test_llm.py +++ b/tests/test_llm.py @@ -1,8 +1,10 @@ -import pytest -from unittest.mock import patch, MagicMock, AsyncMock -import json import base64 -from vision_parse.llm import LLM, UnsupportedModelError, LLMError +import json +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + +from vision_parse.llm import LLM, LLMError, UnsupportedModelError @pytest.fixture diff --git a/tests/test_parser.py b/tests/test_parser.py index 36b0f2e..f69b29e 100644 --- a/tests/test_parser.py +++ b/tests/test_parser.py @@ -1,11 +1,13 @@ -import pytest -from unittest.mock import patch, MagicMock, AsyncMock import json +from unittest.mock import AsyncMock, MagicMock, patch + +import pytest + from vision_parse import ( - VisionParserError, + PDFPageConfig, UnsupportedFileError, VisionParser, - PDFPageConfig, + VisionParserError, ) diff --git a/uv.lock b/uv.lock index a8b6c6e..fc6e30f 100644 --- a/uv.lock +++ b/uv.lock @@ -1,30 +1,31 @@ version = 1 +revision = 2 requires-python = ">=3.9" resolution-markers = [ - "python_full_version == '3.10.*' and platform_system == 'Darwin'", - "python_full_version == '3.10.*' and platform_machine == 'aarch64' and platform_system == 'Linux'", - "(python_full_version == '3.10.*' and platform_machine != 'aarch64' and platform_system == 'Linux') or (python_full_version == '3.10.*' and platform_system != 'Darwin' and platform_system != 'Linux')", - "python_full_version < '3.10' and platform_machine == 'arm64' and platform_system == 'Darwin'", - "python_full_version < '3.10' and platform_machine == 'aarch64' and platform_system == 'Linux'", - "(python_full_version < '3.10' and platform_machine != 'arm64' and platform_system == 'Darwin') or (python_full_version < '3.10' and platform_machine != 'aarch64' and platform_system == 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'git+https://github.com/tqtensor/vision-parse.git#egg=vision-parse[all]' ``` ### Setting up Ollama (Optional) @@ -180,34 +180,34 @@ parser = VisionParser( This package supports the following Vision LLM models: -| **Model Name** | **Provider Name** | -|:------------:|:----------:| -| gpt-4o | OpenAI | -| gpt-4o-mini | OpenAI | -| gemini-1.5-flash | Google | -| gemini-2.0-flash-exp | Google | -| gemini-1.5-pro | Google | -| llava:13b | Ollama | -| llava:34b | Ollama | -| llama3.2-vision:11b | Ollama | -| llama3.2-vision:70b | Ollama | -| deepseek-r1:32b | Ollama | -| deepseek-chat | DeepSeek | +| **Model Name** | **Provider Name** | +| :------------------: | :---------------: | +| gpt-4o | OpenAI | +| gpt-4o-mini | OpenAI | +| gemini-1.5-flash | Google | +| gemini-2.0-flash-exp | Google | +| gemini-1.5-pro | Google | +| llava:13b | Ollama | +| llava:34b | Ollama | +| llama3.2-vision:11b | Ollama | +| llama3.2-vision:70b | Ollama | +| deepseek-r1:32b | Ollama | +| deepseek-chat | DeepSeek | ## 🔧 Customization Parameters Vision Parse offers several customization parameters to enhance document processing: -| **Parameter** | **Description** | **Value Type** | -|:---------:|:-----------:|:-------------:| -| model_name | Name of the Vision LLM model to use | str | -| custom_prompt | Define custom prompt for the model and it will be used as a suffix to the default prompt | str | -| ollama_config | Specify custom configuration for Ollama client initialization | dict | -| openai_config | Specify custom configuration for OpenAI, Azure OpenAI or DeepSeek client initialization | dict | -| gemini_config | Specify custom configuration for Gemini client initialization | dict | -| image_mode | Sets the image output format for the model i.e. if you want image url in markdown content or base64 encoded image | str | -| detailed_extraction | Enable advanced content extraction to extract complex information such as LaTeX equations, tables, images, etc. | bool | -| enable_concurrency | Enable parallel processing of multiple pages in a PDF document in a single request | bool | +| **Parameter** | **Description** | **Value Type** | +| :-----------------: | :---------------------------------------------------------------------------------------------------------------: | :------------: | +| model_name | Name of the Vision LLM model to use | str | +| custom_prompt | Define custom prompt for the model and it will be used as a suffix to the default prompt | str | +| ollama_config | Specify custom configuration for Ollama client initialization | dict | +| openai_config | Specify custom configuration for OpenAI, Azure OpenAI or DeepSeek client initialization | dict | +| gemini_config | Specify custom configuration for Gemini client initialization | dict | +| image_mode | Sets the image output format for the model i.e. if you want image url in markdown content or base64 encoded image | str | +| detailed_extraction | Enable advanced content extraction to extract complex information such as LaTeX equations, tables, images, etc. | bool | +| enable_concurrency | Enable parallel processing of multiple pages in a PDF document in a single request | bool | > [!TIP] > For more details on custom model configuration i.e. `openai_config`, `gemini_config`, and `ollama_config`; please refer to [Model Configuration](docs/model_config.md). @@ -220,11 +220,11 @@ Since there are no other ground truth data available for this task, I relied on ### Results -| Parser | Accuracy Score | -|:-------:|:---------------:| -| Vision Parse | 92% | -| MarkItDown | 67% | -| Nougat | 79% | +| Parser | Accuracy Score | +| :----------: | :------------: | +| Vision Parse | 92% | +| MarkItDown | 67% | +| Nougat | 79% | > [!NOTE] > I used gpt-4o model for Vision Parse to extract markdown content from the pdf documents. I have used model parameter settings as in `scoring.py` script. The above results may vary depending on the model you choose for Vision Parse and the model parameter settings. diff --git a/src/vision_parse/constants.py b/src/vision_parse/constants.py index 9ddee2e..1819833 100644 --- a/src/vision_parse/constants.py +++ b/src/vision_parse/constants.py @@ -8,6 +8,7 @@ "deepseek-r1:32b": "ollama", "gpt-4o": "openai", "gpt-4o-mini": "openai", + "litellm/*": "openai", "gemini-1.5-flash": "gemini", "gemini-2.0-flash-exp": "gemini", "gemini-1.5-pro": "gemini", diff --git a/src/vision_parse/llm.py b/src/vision_parse/llm.py index 27b230b..9446e98 100644 --- a/src/vision_parse/llm.py +++ b/src/vision_parse/llm.py @@ -292,7 +292,9 @@ def _init_llm(self) -> None: def _get_provider_name(self, model_name: str) -> str: """Get the provider name for a given model name.""" try: - return SUPPORTED_MODELS[model_name] + return SUPPORTED_MODELS[ + "litellm/*" if "litellm" in model_name else model_name + ] except KeyError: supported_models = ", ".join( f"'{model}' from {provider}"