If you’ve ever worked with Power BI in an enterprise environment, you’ve faced the same frustrating challenge that has plagued data professionals for years: comprehensive documentation. You spend weeks building sophisticated reports with complex DAX measures, intricate data models, and carefully crafted visualizations, only to realize that documenting everything properly will take nearly as long as building the solution itself.
The documentation dilemma is a real and costly issue. Teams often skip it due to time constraints, resulting in knowledge silos when developers leave the organization. Stakeholders struggle to understand the report’s logic without proper documentation. Compliance requirements go unmet. New team members take months to understand existing models. Manual documentation becomes outdated the moment a model changes.
What if there were a way to generate comprehensive, professional Power BI documentation automatically, in minutes rather than hours? What if you could chat with an AI assistant about your report’s structure, ask questions about specific DAX measures, and get detailed explanations about table relationships—all based on your actual model data?
Enter AutoDoc—the AI-powered solution that finally solves Power BI’s documentation problem once and for all.
What is AutoDoc?
AutoDoc is a revolutionary documentation generator specifically designed for Power BI. It harnesses the power of artificial intelligence to create comprehensive, professional documentation automatically. Think of it as having a dedicated documentation specialist who never sleeps, never misses details, and can analyze your entire Power BI model in minutes.
AutoDoc is an open-source tool that offers complete flexibility for implementation, both in the cloud and locally, through the repository available on GitHub. The solution allows secure execution in a local environment, including with local LLM models via Ollama, or can be securely hosted on platforms such as Microsoft Azure AI Foundry or Amazon Bedrock.
The Multi-AI Advantage
What sets AutoDoc apart from other documentation tools is its integration with multiple leading AI providers, giving you the flexibility to choose the language model that best fits your needs and budget:
- OpenAI GPT-4.1 models (nano and mini variants)
- Azure OpenAI GPT-41 nano for enterprise environments
- Anthropic Claude 3.7 Sonnet for advanced reasoning
- Google Gemini 2.5 Pro for comprehensive analysis
- Llama 4 for open-source flexibility
Core Capabilities
Intelligent File Processing: AutoDoc supports both .pbit (Power BI Template) and .zip files, automatically extracting and analyzing all components of your Power BI model regardless of complexity.
Comprehensive Analysis: The tool meticulously documents every aspect of your Power BI solution, including tables, columns, measures, calculated fields, data sources, relationships, and Power Query transformations.
Professional Output Formats: Generate documentation in both Excel and Word formats, ensuring compatibility with your organization’s documentation standards and workflows.
Interactive AI Chat: Perhaps the most groundbreaking feature is AutoDoc’s intelligent chat system that allows you to have conversations about your Power BI model, asking specific questions about DAX logic, table relationships, or data transformations.
Multi-Language: You can create Power BI documentation in multiple languages, including English, Portuguese, and Spanish.
How to Use AutoDoc
Using AutoDoc is remarkably straightforward, designed with busy data professionals in mind who need results quickly without a steep learning curve.
Getting Started
Step 1: Access AutoDoc. Visit https://autodoc.lawrence.eti.br/ to access the web-based version, or set up a local installation for enhanced security and control.
Step 2: Select Your AI Engine. Choose from the available AI models based on your specific requirements. Each model offers distinct strengths: GPT-4.1 for general use, Claude for complex reasoning, and Gemini for comprehensive analysis.
Step 3: Provide Your Power BI Model. You have two flexible options for getting your model into AutoDoc:
Option A: Direct Upload
- Save your Power BI file as a
.pbittemplate or export as.zip - Upload directly to the AutoDoc interface
- The system automatically processes and analyzes your model
Option B: API Integration. For direct integration with Power BI Service:
- Input your App ID in the sidebar
- Provide your Tenant ID
- Enter your Secret Value
- AutoDoc connects directly to your Power BI workspace
Step 4: Review Interactive Preview. Before generating final documentation, AutoDoc provides an interactive visualization of your data model, allowing you to:
- Verify the accuracy of the extracted information
- Review table structures and relationships
- Confirm DAX measures and calculations
- Check data source connections
Step 5: Generate Documentation. Select your preferred output format (Excel or Word) and download professional documentation that includes:
- Complete table inventory with column details
- All DAX measures with expressions
- Data source documentation
- Relationship mappings
- Power Query transformation logic
Step 6: Leverage AI Chat. After documentation generation, click the “💬 Chat” button to access the intelligent assistant. Ask questions like:
- “Explain the logic behind the ‘Total Sales’ measure.”
- “What relationships exist between the Customer and Orders tables?”
- “Which columns in the Product table are calculated?”
- “Show me all measures that reference the Date table.”
Token Configuration in AutoDoc
Depending on the size of your Power BI report, AutoDoc allows you to adjust the maximum number of input and output tokens to optimize processing.
What are tokens? Tokens are basic processing units of LLM models – they can be words, parts of words, or characters.
Input Tokens represent the amount of information the LLM model can process at once, including your report content and system instructions. This configuration allows you to:
- Increase the value: Process more content simultaneously, reducing the number of required interactions
- Decrease the value: Useful when the report is too large and exceeds model limits, forcing processing in smaller parts with more interactions.
Output Tokens: Define the maximum size of the response the model can generate. This configuration varies according to each LLM model’s capabilities and directly influences:
- The length of the generated documentation
- The completeness of the produced analyses
- Processing time
Important: Each LLM model has specific token limitations. Refer to the documentation on this website to determine the exact limits and adjust these settings accordingly if necessary.
Free OpenAI & every-LLM API Pricing Calculator | Updated jun. 2025
How to Implement AutoDoc Locally
For organizations requiring enhanced security, compliance, or customization, AutoDoc offers complete local deployment capabilities. I created this open-source project, and you can find my GitHub repository here: https://github.com/LawrenceTeixeira/PBIAutoDoc
System Requirements
Operating System: Windows, macOS, or Linux Python Version: 3.10 or higher Network: Internet connection for AI model access API Access: Valid API keys for chosen AI providers
Installation Process
1. Repository Setup
git clone https://github.com/LawrenceTeixeira/PBIAutoDoc.git
cd AutoDoc2. Environment Configuration
# Create isolated Python environment
python -m venv .venv
# Activate environment
# Windows
.venv\Scripts\activate
# macOS/Linux
source .venv/bin/activate3. Dependency Installation
# Install core requirements
pip install -r requirements.txt
# Install additional AI processing library
pip install --no-cache-dir chunkipy4. Environment Variables Setup: Create a .env file in your project root:
# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key
# Groq Configuration
GROQ_API_KEY=your_groq_api_key
# Azure OpenAI Configuration
AZURE_API_KEY=your_azure_api_key
AZURE_API_BASE=https://<your-alias>.openai.azure.com
AZURE_API_VERSION=2024-02-15-preview
# Google Gemini Configuration
GEMINI_API_KEY=your_gemini_api_key
# Anthropic Claude Configuration
ANTHROPIC_API_KEY=your_anthropic_api_key5. Application Launch
# Standard launch
streamlit run app.py --server.fileWatcherType none
# Alternative for specific environments
python -X utf8 -m streamlit run app.py --server.fileWatcherType noneCloud Deployment Option
For scalable cloud deployment, AutoDoc supports Fly.io hosting:
# Install Fly CLI
curl -L https://fly.io/install.sh | sh
export PATH=/home/codespace/.fly/bin
# Authentication and deployment
flyctl auth login
flyctl launch
flyctl deployWhat Are the Benefits?
AutoDoc delivers transformative benefits that address every central pain point in Power BI documentation:
Dramatic Time Savings
What traditionally takes hours or days now happens in minutes. Data professionals report saving 15-20 hours per week on documentation tasks, allowing them to focus on analysis and insights rather than administrative work.
Unmatched Accuracy and Completeness
Human documentation inevitably misses details or becomes outdated. AutoDoc captures every table, column, measure, and relationship automatically, ensuring nothing is overlooked and documentation remains current.
Professional Consistency
Every documentation output follows the same professional format and standard, regardless of who generates it or when. This consistency is crucial for enterprise environments and compliance requirements.
Enhanced Knowledge Transfer
The AI chat feature transforms documentation from static text into an interactive knowledge base. Team members can ask specific questions and get detailed explanations, dramatically reducing onboarding time for new staff.
Compliance and Audit Support
For heavily regulated industries, AutoDoc provides the comprehensive documentation required for compliance audits, with detailed tracking of data lineage, transformations, and business logic.
Improved Collaboration
Non-technical stakeholders can better understand Power BI solutions through clear, comprehensive documentation. The chat feature allows business users to ask questions about data definitions and calculations without requiring technical expertise.
Cost Efficiency
By automating documentation processes, organizations reduce the human resources required for documentation maintenance while improving quality and coverage.
Conclusion
AutoDoc represents more than just another documentation tool—it’s a paradigm shift that finally makes comprehensive Power BI documentation practical and sustainable. By combining cutting-edge AI technology with a deep understanding of Power BI architecture, AutoDoc solves the fundamental challenges that have made documentation a persistent pain point for data teams worldwide.
The tool’s multi-AI approach ensures flexibility and future-proofing, while its interactive chat capability transforms static documentation into a dynamic knowledge resource. Whether you’re a solo analyst struggling to document complex models or an enterprise data team managing hundreds of reports, AutoDoc adapts to your needs and scales with your organization.
The choice is clear: continue struggling with manual documentation processes that consume valuable time and often go incomplete, or embrace the AI-powered solution that makes comprehensive Power BI documentation effortless and automatic.
AutoDoc doesn’t just solve Power BI’s documentation problem—it eliminates it. The question isn’t whether you can afford to implement AutoDoc; it’s whether you can afford not to.
Should you have any questions or need assistance with AutoDoc, please don’t hesitate to contact me using the provided link: https://lawrence.eti.br/contact/
That´s it for Today!
