cargo-self
| Crates.io | cargo-self |
| lib.rs | cargo-self |
| version | 0.1.7 |
| source | src |
| created_at | 2023-09-30 06:20:00.085481 |
| updated_at | 2023-10-23 21:02:24.039071 |
| description | A tool to build and install a package using cargo enhanced with LLM models. |
| homepage | |
| repository | |
| max_upload_size | |
| id | 988424 |
| size | 245,375 |
Bregy Malpartida (bregydoc)
documentation
README
Cargo Self
This software is a modular and extensible computation framework designed to manage, process, and execute computational plans. It provides features such as computation planning, dynamic chat completion using OpenAI's GPT, JSON persistence for storing and retrieving computation state, and a CLI tool for interacting with the engine and executing plans. The software also supports constitution-based processing, allowing users to define constitutions to guide the computation process and retrieve system and input data. With a modular design and clear separation of concerns, this software offers flexibility and customization for various computational needs.
Features
- Computation Planning: Define and manage computational plans with a specified root path and persistence mechanism.
- Dynamic Chat Completion: Utilize OpenAI's GPT-3.5-turbo to generate chat completions based on structured input.
- JSON Persistence: Store and retrieve the state of the computation in a JSON format.
- Modular Design: Extensible architecture with clear separation of concerns among different modules such as planning, state management, and JSON persistence.
- CLI Tool: A command-line interface for interacting with the computation engine and executing plans.
- Constitution-based Processing: Define a constitution to guide the computation process, with the ability to retrieve system and input data for constitution-based processing.
Modules
- src/engine: Core engine modules handling state management, JSON persistence, planning, and constitution-based processing.
- src/cli: Command-line interface for interacting with the computation engine.
- src/lib.rs: Library root, tying together the CLI and engine modules.
- src/main.rs: Entry point for initializing and executing the computation engine.
Dependencies
- async-openai, cargo, clap, dotenv, handlebars, ignore, serde, serde_json, sha2, tokio, walkdir, and others.
Usage
Refer to the README.md for detailed instructions on how to use this software, including setting up, configuring, and executing computational plans.
Contribution
Feel free to fork this repository, submit issues, or open pull requests to improve the project.