talkpipe-writing-assistant 0.1.4a3

AI-powered writing assistant for structured document generation

TalkPipe Writing Assistant

Making the AI write with you, not for you.

An AI-powered writing assistant that transforms how you create structured documents. This application combines intelligent content generation with intuitive document management, enabling writers to craft professional documents with contextually-aware AI assistance that understands your style, audience, and objectives.

Built on the TalkPipe framework, this tool helps you:

• Break writer's block: Generate initial drafts and ideas for any section
• Maintain consistency: AI understands your document's context, style, and tone across all sections
• Iterate quickly: Multiple generation modes (rewrite, improve, proofread, ideas) let you refine content efficiently
• Stay organized: Structure documents into sections with main points and supporting text
• Work offline: Use local LLMs via Ollama or cloud-based models via OpenAI, Anthropic, and more

Features

• Multi-User Support: JWT-based authentication with per-user document isolation
• Structured Document Creation: Organize your writing into sections with main points and user text
• AI-Powered Generation: Generate contextually-aware paragraph content using advanced language models
• Multiple Generation Modes:
  • Rewrite: Complete rewrite with new ideas and improved clarity
  • Improve: Polish existing text while maintaining structure
  • Proofread: Fix grammar and spelling errors only
  • Ideas: Get specific suggestions for enhancement
• Real-time Editing: Dynamic web interface for seamless writing and editing
• Document Management: Save, load, and manage multiple documents with automatic snapshots
• User Preferences: Per-user AI settings, writing style, and environment variables
• Customizable Metadata: Configure writing style, tone, audience, and generation parameters
• Flexible AI Backend: Support for OpenAI (GPT-4, GPT-4o), Anthropic (Claude 3.5 Sonnet, Claude 3 Opus), and Ollama (llama3, mistral, etc.)
• Database Storage: SQLite database with configurable location for easy backup and deployment
• Async Processing: Efficient queuing system for AI generation requests

Pre-built container (Docker or Podman)

CI publishes images to GitHub Container Registry:

Image	ghcr.io/sandialabs/talkpipe-writing-assistant
Platforms	Linux amd64 and arm64 (release builds). The app runs in a Linux container; on Windows and macOS use Docker Desktop or Podman (they run Linux containers under the hood).

Tags (typical): latest — stable GitHub Release (not marked pre-release); experimental — pushes to the develop branch or a pre-release GitHub Release; branch names (e.g. main) and commit SHAs are also published. Check the package page for the exact tag after a workflow run.

Registry login: This package is public, so you can pull and run without logging in to GHCR. You only need docker login ghcr.io / podman login ghcr.io if the image is private, your organization requires it, or pull fails with an authentication error (use a GitHub Personal Access Token with read:packages as the password).

1. Pull (pick a tag from the package page, e.g. latest):

   docker pull ghcr.io/sandialabs/talkpipe-writing-assistant:latest
   

   With Podman, replace docker with podman (same image reference).

2. Run — persist the database under /app/data (the image supplies defaults, including a JWT secret):

   docker run --rm -p 8001:8001 \
     -v wa_data:/app/data \
     ghcr.io/sandialabs/talkpipe-writing-assistant:latest
   

   Open http://localhost:8001. Use podman run with the same flags if you use Podman.

To build and run from a local clone with Compose (including dev reload), see Using Docker below.

Installation

Prerequisites

• Python 3.11 or higher
• An AI backend: OpenAI, Anthropic, or Ollama (local)

Install from pip (Recommended)

pip install talkpipe-writing-assistant

After installation, you can start the application immediately:

writing-assistant

Then navigate to http://localhost:8001 in your browser. See the Quick Start section below for next steps.

Install from source

git clone https://github.com/sandialabs/talkpipe-writing-assistant.git
cd talkpipe-writing-assistant
pip install -e .

Development Installation

git clone https://github.com/sandialabs/talkpipe-writing-assistant.git
cd talkpipe-writing-assistant
pip install -e .[dev]

Development with uv (reproducible dependency lock)

The repo includes uv.lock so CI and local installs can use the same resolved versions. Install uv, then:

git clone https://github.com/sandialabs/talkpipe-writing-assistant.git
cd talkpipe-writing-assistant
uv sync --frozen --extra dev

Run tests and tools via the project environment, for example uv run pytest, or activate the virtualenv (.venv on Unix: source .venv/bin/activate).

After changing dependencies in pyproject.toml, refresh the lockfile with uv lock and commit uv.lock. To bump versions, use uv lock --upgrade or uv lock --upgrade-package <name>.

Using Docker

Build and run from the repository (as opposed to the pre-built GHCR image above):

# Production deployment
docker-compose up talkpipe-writing-assistant

# Development with live reload
docker-compose --profile dev up talkpipe-writing-assistant-dev

Quick Start

TL;DR: After pip install talkpipe-writing-assistant, just run writing-assistant and open http://localhost:8001 in your browser!

After installing with pip, follow these steps to get started:

1. Start the Server

writing-assistant

The server will start on http://localhost:8001 and display:

🔐 Writing Assistant Server - Multi-User Edition
📝 Access your writing assistant at: http://localhost:8001/
🔑 Register a new account at: http://localhost:8001/register
🔐 Login at: http://localhost:8001/login
📚 API documentation: http://localhost:8001/docs
💾 Database: /home/user/.writing_assistant/writing_assistant.db

2. Create Your Account

1. Open your browser and navigate to http://localhost:8001/register
2. Enter your email address and password
3. Click "Register" to create your account

3. Configure AI Backend

You need to configure one of the supported AI backends:

Option A: OpenAI (Cloud)

1. Get an API key from OpenAI Platform
2. Set your API key:

   export OPENAI_API_KEY="sk-your-api-key-here"
   

3. In the web interface: Settings → AI Settings → Set Source to openai and Model to your model of choice.

Option B: Anthropic (Cloud)

1. Get an API key from Anthropic Console
2. Set your API key:

   export ANTHROPIC_API_KEY="sk-ant-your-api-key-here"
   

3. In the web interface: Settings → AI Settings → Set Source to anthropic and Model to your model of choice.

Option C: Ollama (Local, Free)

1. Install Ollama from ollama.com
2. Pull a model: ollama pull [model name]
3. Start Ollama: ollama serve
4. In the web interface: Settings → AI Settings → Set Source to ollama and Model to [model name]

4. Start Writing!

1. Click "Create New Document"
2. Add a title and sections, leaving a blank line between sections.
3. Click "Generate" on any section to create AI-assisted content
4. Save your work with the "Save Document" button

That's it! You're ready to use the AI writing assistant.

Usage

Starting the Server

# Default: http://localhost:8001
writing-assistant

# Custom port
writing-assistant --port 8080

# Custom host and port
writing-assistant --host 0.0.0.0 --port 8080

# Enable auto-reload for development
writing-assistant --reload

# Custom database location
writing-assistant --db-path /path/to/database.db

# Disable custom environment variables from UI (security)
writing-assistant --disable-custom-env-vars

# Initialize database without starting server
writing-assistant --init-db

# You can also use environment variables
WRITING_ASSISTANT_PORT=8080 writing-assistant
WRITING_ASSISTANT_RELOAD=true writing-assistant
WRITING_ASSISTANT_DB_PATH=/path/to/database.db writing-assistant

When the server starts, it will display:

• The URL to access the application
• Registration and login URLs
• API documentation URL
• Database location

Authentication: The application uses JWT-based multi-user authentication with FastAPI Users. Each user has their own account with secure password storage. New users can register through the web interface at /register, and existing users log in at /login.

Environment Variables

Configure the application with these environment variables:

Variable	Description	Default
WRITING_ASSISTANT_HOST	Server host address	localhost
WRITING_ASSISTANT_PORT	Server port number	8001
WRITING_ASSISTANT_RELOAD	Enable auto-reload (development)	false
WRITING_ASSISTANT_DB_PATH	Database file location	~/.writing_assistant/writing_assistant.db
WRITING_ASSISTANT_SECRET	JWT secret key for authentication	Auto-generated (change in production)
TALKPIPE_OLLAMA_SERVER_URL	Ollama server URL for local models	http://localhost:11434

Security Options:

• --disable-custom-env-vars: Prevents users from configuring environment variables through the browser interface
  • Use this for shared deployments or when you want centralized credential management
  • Environment variables must be set at the server level (via shell environment)
  • The Environment Variables section will be hidden in the UI

Configure document metadata:

• AI Source: openai, anthropic, or ollama
• Model: e.g., gpt-4, claude-3-5-sonnet-20241022, or llama3.1:8b
• Writing style: formal, casual, technical, etc.
• Target audience: general public, experts, students, etc.
• Tone: neutral, persuasive, informative, etc.
• Word limit: approximate words per paragraph

Document Storage

Documents are stored in an SQLite database with multi-user isolation:

Default Location: ~/.writing_assistant/writing_assistant.db

Custom Location: Use --db-path or WRITING_ASSISTANT_DB_PATH to specify an alternative location

Features:

• Per-user document isolation (users only see their own documents)
• Automatic snapshot management (keeps 10 most recent versions)
• User-specific preferences (AI settings, writing style, etc.)
• Cascade deletion (removing a user deletes all their documents)

Backup: Simply copy the database file to create a backup. The database can be moved to a different location using the --db-path option.

Architecture

Package Structure

src/writing_assistant/
├── __init__.py          # Package initialization and version
├── core/                # Core business logic
│   ├── __init__.py
│   ├── callbacks.py     # AI text generation functionality
│   ├── definitions.py   # Data models (Metadata)
│   └── segments.py      # TalkPipe segment registration
└── app/                 # Web application
    ├── __init__.py
    ├── main.py          # FastAPI application and API endpoints
    ├── server.py        # Application entry point
    ├── static/          # CSS and JavaScript assets
    └── templates/       # Jinja2 HTML templates

Core Components

• Metadata: Configuration for writing style, audience, tone, and AI settings
• Section: Individual document sections with async text generation and queuing
• Document: Complete document with sections, metadata, and snapshot management
• Callbacks: AI text generation using TalkPipe with context-aware prompting

Troubleshooting

Application Issues

"Port already in use"

• Change the port: writing-assistant --port 8080
• Or kill the process using the port

"Cannot save document" or "Database error"

• Check write permissions to the database directory (default: ~/.writing_assistant/)
• Ensure the directory exists: mkdir -p ~/.writing_assistant
• Try a different database location: writing-assistant --db-path /tmp/test.db
• Initialize the database manually: writing-assistant --init-db

"Authentication failed" or "Invalid credentials"

• Double-check your email and password
• Register a new account if you haven't already
• The database may have been reset - check the database location

"Cannot connect to database"

• Verify the database file exists and is not corrupted
• Check file permissions on the database file
• Try initializing a new database: writing-assistant --db-path /tmp/new.db --init-db

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

Acknowledgments

Built with TalkPipe, a flexible framework for AI pipeline construction developed at Sandia National Laboratories.