fabricatio 0.31.2.dev3

A LLM multi-agent framework.

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Overview

Fabricatio is a streamlined Python library for building LLM applications using an event-based agent structure. It leverages Rust for performance-critical tasks, Handlebars for templating, and PyO3 for Python bindings.

Features

• Event-Driven Architecture: Robust task management through an EventEmitter pattern.
• LLM Integration & Templating: Seamlessly interact with large language models and dynamic content generation.
• Async & Extensible: Fully asynchronous execution with easy extension via custom actions and workflows.

TODO

• Add api support.
  • Define API types + REST route handlers + wire into axum server
  • Add CORS/error middleware + Python binding for server config
  • Integration tests + API docs
• Run as mcp server.
  • Feature flag + McpServer struct + tool registry + tools/list
  • stdio + HTTP transports + tools/call dispatch
  • Register Fabricatio tools as MCP tools + Python binding + tests
• Finalize the webui.
  • Chat interface + API client + WebSocket/SSE streaming
  • Config panel + agent status dashboard
  • Error handling + loading states + UX polish
• Add ComfyUI integration.
  • Package skeleton + ComfyUIClient for prompt queue, progress polling, image retrieval
  • Workflow template system with dynamic parameter injection
  • ComfyUIAction + Python bindings + integration tests
  • WebSocket real-time progress tracking
  • End-to-end integration test with running ComfyUI instance
• Novel scene image generation with ComfyUI.
  • Scene extraction from novel content + prompt engineering for image generation
  • SceneImageAction in fabricatio-novel calling fabricatio-comfyui to generate scene illustrations
  • Image embedding into novel output (EPUB/Typst) + configurable style/template selection
  • Per-chapter image caching + regeneration on content changes
• Add Plugin system.
  • Plugin protocol + registry + lifecycle (load/unload)
  • Hook points in core lifecycle + entry-point discovery
  • Plugin config support + validation + tests
• Replace litellm with native rust impl
  • Port deprecated mock utils to thryd impl
  • Port tests to new mock utils
  • Sync documentations
  • Router cache support ttl and eviction
• Add worktree-based isolated development subpackage
• Add level-based context compression subpackage
  • Package skeleton + CompressionLevel enum + compression strategies
  • Async compression + Python bindings + tests
• TreeSetter-based ACE
  • tree-sitter dep + AST node types + tree edit operations (insert/replace/delete/move)
  • TreeSetter orchestrator + Python bindings + multi-language round-trip tests
• Self-Extensible Agent
  • Capability protocol + runtime registry + dynamic method injection on Role
  • Config-based discovery + hot-reload + tests
• Add more examples
• Write missing examples (Structured Output, Extract, Improve)
• Document undocumented examples + cross-link use-cases.rst + examples index
• ToolExecuter exec results feedback to llm
  • Surface errors via ApplicationError + ResultCollector.error() + last_error template param
• Use stubgen feat and cfg_attr to make the stub generation as an opt-in for all mixed packages.
• Use Thryd impl to move some requests to rust side
  • All core LLM operations already routed through rust.router_usage
• Add Texts-based skill system, as a subpackage
  • Skill YAML/JSON schema + loader + directory scanner
  • Wire into Role + validation + example skill file + tests
• Port build workflow to Justfile
• thryd::Router use concurrent safe impl
• Extract Router from fabricatio-core into standalone fabricatio-router crate
• Replace parser with native rust impl
• Better memory impl
• RAG package refactor, move rerank and embedding to thryd
  • Add Reranker support in thryd
  • TEI as Provider in thryd (RerankerModel for OpenAI-compat: wontfix — OpenAI doesn't support rerankers)
  • Wire rerank() into Router Python class + add UseReranker capability
• Add embedding and rerank mock support to fabricatio-mock
  • Add add_or_update_dummy_embedding_model and add_or_update_dummy_reranker_model to Router
  • Add setup_dummy_embeddings / setup_dummy_reranks + response builders in fabricatio-mock
  • Tests for embedding and rerank mock paths
• Replace UseLLM with native rust impl
  • Fix the mock utils that is break by the replacement.
  • router support no_cache
• Diff use Hashline impl instead of StringGrep
  • Integrate rho-hashline crate + hash-based line anchoring in Rust
  • Add compute_hash, format_hashes, parse_hashline_anchor, apply_* functions
• Add Diff.format_with_hashes() method + Python exports + 22 tests
• Add high-level HashlineDiff wrapper for hashline API
  • Diff dataclass with anchor and line-number fields
  • from_anchors() and from_line_range() factory methods
  • apply() with line_range and pattern matching modes + tests
• Placeholder based multiple-agents edits
• Convert fabricatio-rag to a pure python package
  • Extract lancedb impl into a seperate package
• fabricatio-novel support rag
• Lancedb integration refactor
  • Refactor fabricatio-typst
• Milvus integration refactor
• Novel generation fix
• Embedding fail without any debug info fix
• sparse cache for embedding
• Thryd router support retry

Installation

# install fabricatio with full capabilities.
pip install fabricatio[full]

# or with uv

uv add fabricatio[full]


# install fabricatio with only rag and rule capabilities.
pip install fabricatio[rag,rule]

# or with uv

uv add fabricatio[rag,rule]

You can download the templates from the github release manually and extract them to the work directory.

curl -L https://github.com/Whth/fabricatio/releases/download/v0.19.1/templates.tar.gz | tar -xz

Or you can use the cli tdown bundled with fabricatio to achieve the same result.

tdown download --verbose -o ./

Note: fabricatio performs template discovery across multiple sources with filename-based identification. Template resolution follows a priority hierarchy where working directory templates override templates located in <ROAMING>/fabricatio/templates.

Usage

Basic Example

"""Example of a simple hello world program using fabricatio."""

from typing import Any

# Import necessary classes from the namespace package.
from fabricatio import Action, Event, Role, Task, WorkFlow, logger


# Create an action.
class Hello(Action):
    """Action that says hello."""

    output_key: str = "task_output"

    async def _execute(self, **_) -> Any:
        ret = "Hello fabricatio!"
        logger.info("executing talk action")
        return ret


# Create the role and register the workflow.
(Role()
 .subscribe(Event.quick_instantiate("talk"), WorkFlow(name="talk", steps=(Hello,)))
 .dispatch())

# Make a task and delegate it to the workflow registered above.
assert Task(name="say hello").delegate_blocking("talk") == "Hello fabricatio!"

Examples

For various usage scenarios, refer to the following examples:

• Simple Chat
• Structured Output
• Extraction
• Content Improvement
• Retrieval-Augmented Generation (RAG)
• Article Extraction
• Propose Task
• Code Review
• Write Outline

(For full example details, see Examples)

Configuration

Fabricatio supports flexible configuration through multiple sources, with the following priority order: Call Arguments > ./.env > Environment Variables > ./fabricatio.toml > ./pyproject.toml > <ROMANING>/fabricatio/fabricatio.toml > Builtin Defaults.

Below is a unified view of the same configuration expressed in different formats:

Environment variables or dotenv file

FABRICATIO_LLM__SEND_TO=openai/gpt-3.5-turbo
FABRICATIO_LLM__TEMPERATURE=1.0
FABRICATIO_LLM__TOP_P=0.35
FABRICATIO_LLM__STREAM=false
FABRICATIO_LLM__MAX_COMPLETION_TOKENS=8192
FABRICATIO_DEBUG__LOG_LEVEL=INFO

fabricatio.toml file

[debug]
log_level = "DEBUG"


[llm]
send_to = "base" # send req to `base` group by default
max_completion_tokens = 32000
stream = false
temperature = 1.0
top_p = 0.35


[routing]
providers = [
    { ptype = "OpenAICompatible", key = "sk-...", name = "mm", base_url = "https://api.example.com/v1/" }
]

completion_deployments = [
    { id = "mm/a-completion-model", group = 'base', tpm = 100_000, rpm = 1000 }
]
cache_database_path = "path/to/.cache.db"

pyproject.toml file

[tool.fabricatio.debug]
log_level = "DEBUG"


[tool.fabricatio.llm]
send_to = "base" # send req to `base` group by default
max_completion_tokens = 32000
stream = false
temperature = 1.0
top_p = 0.35


[tool.fabricatio.routing]
providers = [
    { ptype = "OpenAICompatible", key = "sk-...", name = "mm", base_url = "https://api.example.com/v1/" }
]

completion_deployments = [
    { id = "mm/a-completion-model", group = 'base', tpm = 100_000, rpm = 1000 }
]
cache_database_path = "path/to/.cache.db"

Contributing

We welcome contributions from everyone! Before contributing, please read our Contributing Guide and Code of Conduct.

License

Fabricatio is licensed under the MIT License. See LICENSE for details.

Acknowledgments

Special thanks to the contributors and maintainers of:

• PyO3
• Maturin
• Handlebars.rs