AutoBlogs v1.0.0 (`Train Yard`)

AutoBlogs is an AI-assisted content generation tool that can leverage both open-source and/or proprietary Large Language Model (LLM) agents to create high-quality, SEO-optimized content for various needs. The system integrates a human-in-the-loop workflow, ensuring that AI-generated drafts can be reviewed, edited, and refined before publishing.

Project Overview

This project aims to simplify and accelerate the process of writing contents (blog, articles, book, research papers, etc.) by combining AI automation with human editorial control. It provides a flexible framework where multiple LLM providers can be integrated to create and customize contents using a streamlit dashboard.

The contents can then be published online, like in GitHub Pages, substack, etc. and thus starting a technical writing business or freelance job becomes very easy.

Getting Started

The repository uses third-party Python SDKs that provide an API interface to interact with open-source or any proprietary LLM, like OpenAI or Anthropic Claude to generate content.

The package is available on PyPI and can be installed as follows:

pip install autoblogs

The package does not have a hard dependency on a third-party LLM SDK, but requires one based on the type of model you want to use. For example, it either requires the Anthropic SDK for the CLAUDE provider or the OpenAI SDK for all other types of providers.

Release Note(s)

Initial developmental build of AutoBlogs — an AI-assisted, human-in-the-loop content generation toolkit that supports
both a command-line interface and a Streamlit web UI.

Core Library

• autoblogs.model.dataflows — frozen dataclasses AIModel, AIRequest, and AIResponse for typed, immutable data flow across the generation pipeline. AIResponse exposes computed properties total_tokens and word_count.
• autoblogs.config.constants — AIProvider enum (CLAUDE, OPENAI, NVIDIA-NIM, LOCAL) and DraftState lifecycle enum (PENDING, GENERATING, DRAFT, REVIEWING, APPROVED, PUBLISHED, FAILED, RETRACTED, DELETED).
• autoblogs.config.default — module-level defaults available globally.
• autoblogs.error.error — AIClientError for surfacing provider/SDK failures.

Client Layer

• autoblogs.client.anthropic — claudeGenerate function for Claude (Anthropic SDK) using system-prompt + user-message pattern.
• autoblogs.client.openai — generateOpenAI function compatible with OpenAI, NVIDIA-NIM, and local inference servers.
• autoblogs.manager.client.ClientManager — provider-agnostic client factory with lazy, selective SDK imports; raises AIClientError when the required SDK (anthropic / openai) is not installed.

Content & Prompt Layer

• autoblogs.manager.content.ContentManager — Jinja2-based prompt renderer with FileSystemLoader; supports topic, SEO keywords, word-count bounds, sub-section count, and a Claude-specific rendering path.
• Prompt templates shipped with the package under autoblogs/prompts/:
  • base.txt.jinja — base template inherited by all content templates.
  • python.txt.jinja — specialized template for Python-topic blog posts.
• File-write support: ContentManager.writefile() persists generated Markdown content to a configurable output directory.

CLI Tool (autoblogs-cli)

• Interactive terminal workflow: displays ASCII-art banner, collects topic, generation prompt, SEO keywords, and output filename from the user.
• Full .env / environment-variable configuration (LLM_PROVIDER, LLM_MODEL_NAME, LLM_MODEL_APIKEY, LLM_API_BASE_URL, MAX_TOKENS, TEMPERATURE, CONTENT_OUTPUT_DIR, AGENT_PROMPT_CONTEXT).
• Registered as autoblogs-cli entry-point in pyproject.toml.

Streamlit Web UI (autoblogs-ui)

• Multi-page navigation wired via st.navigation with five pages:
  • About — project overview.
  • Dashboard — content dashboard.
  • Create Content — form-driven generation (topic, prompt, SEO keywords); displays word count, token usage, and latency
    metrics on success.
  • Draft Editor — tabbed Edit / Preview interface with a 600-line editable text area and live Markdown preview; separate Save to File and Download tabs for persisting or exporting drafts as .md files.
  • Model Settings — configure provider, model, and API credentials.
• Sidebar heading and info button (links to PyUtility GitHub).
• Custom CSS stylesheet loaded at startup via st.markdown.
• Footer rendered without inline JS (workaround for st.markdown innerHTML restriction).
• Registered as autoblogs-ui entry-point in pyproject.toml.

CI / Automation

• Streamlit Community Cloud CI validation workflow (.github/workflows/streamlit.yml).
• PyPI publish workflow (.github/workflows/publish.yml).
• Dependabot configured to keep GitHub Actions versions up to date.

AutoBlogs v1.0.0.dev0

AutoBlogs is an AI-assisted content generation tool that can leverage both open-source and/or proprietary Large Language Model (LLM) agents to create high-quality, SEO-optimized content for various needs. The system integrates a human-in-the-loop workflow, ensuring that AI-generated drafts can be reviewed, edited, and refined before publishing.

Getting Started

The repository uses third-party Python SDKs that provide an API interface to interact with open-source or any proprietary LLM, like OpenAI or Anthropic Claude to generate content.

The package is available on PyPI and can be installed as follows:

pip install autoblogs

The package does not have a hard dependency on a third-party LLM SDK, but requires one based on the type of model you want to use. For example,

import autoblogs

...

client = autoblogs.client.OpenAIClien(...) # pip install openai
client = autoblogs.client.ClaudeClient(...) # pip install anthropic

Environment Variables

For getting started, you will require the name of the model (LLM_MODEL_NAME) and an API key (if any, LLM_MODEL_APIKEY) to use the module. You can also integrate with external API endpoints or self-hosted/your own company's API endpoints to configure the services as below.

LLM_MODEL_NAME = "awesome-model"
LLM_MODEL_APIKEY = "abc-example.com"
LLM_API_BASE_URL = "https://example.com/api/v1"

Command Line Tools

The package provides distinct command-line tools for different tasks. (I) autoblogs-ui opens a full-fledged UI to create, modify, and finalize content, and (II) autoblogs-cli is the same application available in the terminal.

Preview Release v1.0.0.dev0

This is a preview release of all the functionalities and features that are to be made available in v1. We're excited to provide the best features with ease of use. Looking forward to active collaborators.

Contribution Guidelines

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview of how to contribute can be found in the contributing guidelines. If you run into an issue, please file a new issue for discussion. Create a pull request for a new feature or a fix to an existing issue here.

As contributors and maintainers to this project, you are expected to abide by PyUtility's code of conduct. More information can be found at: Contributor Code of Conduct.

Auto Blogs v0.0.1.dev0

This is a planning release to register the application in PyPI. The tool provides an AI-assisted content generation tool that can leverage both open-source and/or proprietary Large Language Model (LLM) agents to create high-quality, SEO-optimized content for various needs. The system integrates a human-in-the-loop workflow, ensuring that AI-generated drafts can be reviewed, edited, and published.