Skip to main content

A Python package for experimental usage of Langchain and Human-in-the-Loop

Project description

oLCa

oLCa is a Python package that provides a CLI tool for Experimenting Langchain with OpenAI wrapper around interacting thru the human-in-the-loop tool.

Features

Installation

To install the package, you can use pip:

pip install olca

Quick Start

  1. Install the package:
    pip install olca
    
  2. Initialize configuration:
    olca init
    
  3. Run the CLI with tracing:
    olca -T
    

Environment Variables

Set LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, and LANGFUSE_HOST for tracing with Langfuse.
Set LANGCHAIN_API_KEY for LangSmith tracing.
Optionally, set OPENAI_API_KEY for OpenAI usage.

Usage

CLI Tool

Help

To see the available commands and options, use the --help flag:

olca2 --help

fusewill

The fusewill command is a CLI tool that provides functionalities for interacting with Langfuse, including tracing, dataset management, and prompt operations.

Help

To see the available commands and options for fusewill, use the --help flag:


IMPORTED README from olca1

Olca

The olca.py script is designed to function as a command-line interface (CLI) agent. It performs various tasks based on given inputs and files present in the directory. The agent is capable of creating directories, producing reports, and writing instructions for self-learning. It operates within a GitHub repository environment and can commit and push changes if provided with an issue ID. The script ensures that it logs its internal actions and follows specific guidelines for handling tasks and reporting, without modifying certain configuration files or checking out branches unless explicitly instructed.

Tracing

Olca now supports tracing functionality to help monitor and debug its operations. You can enable tracing by using the -T or --tracing flag when running the script. Ensure that the LANGCHAIN_API_KEY environment variable is set for tracing to work.

Initialization

To initialize olca, you need to create a configuration file named olca.yml. This file contains various settings that olca will use to perform its tasks. Below is an example of the olca.yml file:

api_keyname: OPENAI_API_KEY__o450olca241128
human: true
model_name: gpt-4o-mini #or bellow:
model_name: ollama://llama3.1:latest #or with host
model_name: ollama://llama3.1:latest@mymachine.mydomain.com:11434
recursion_limit: 300
system_instructions: You focus on interacting with human and do what they ask.  Make sure you dont quit the program.
temperature: 0.0
tracing: true
tracing_providers:
- langsmith
- langfuse
user_input: Look in the file 3act.md and in ./story, we have created a story point by point and we need you to generate the next iteration of the book in the folder ./book.  You use what you find in ./story to start the work.  Give me your plan to correct or accept.

Usage

To run olca, use the following command:

olca -T

This command will enable tracing and start the agent. You can also use the --trace flag to achieve the same result.

Configuration

The olca.yml file allows you to configure various aspects of olca, such as the API key (so you can know how much your experimetation cost you), model name, recursion limit, system instructions, temperature, and user input. You can customize these settings to suit your needs and preferences.

Command-Line Interface (CLI)

The olca script provides a user-friendly CLI that allows you to interact with the agent and perform various tasks. You can use flags and options to control the agent's behavior and provide input for its operations. The CLI also includes error handling mechanisms to notify you of any issues or missing configuration settings.

GitHub Integration

olca is designed to integrate seamlessly with GitHub workflows and issue management. You can provide an issue ID to the agent, and it will commit and push changes directly to the specified issue. This feature streamlines the development process and reduces the need for manual intervention. Additionally, olca maintains detailed logs of its actions and updates, ensuring transparency and traceability in its operations.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

olca-0.2.78.tar.gz (37.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

olca-0.2.78-py3-none-any.whl (36.2 kB view details)

Uploaded Python 3

File details

Details for the file olca-0.2.78.tar.gz.

File metadata

  • Download URL: olca-0.2.78.tar.gz
  • Upload date:
  • Size: 37.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.15

File hashes

Hashes for olca-0.2.78.tar.gz
Algorithm Hash digest
SHA256 0b66b35f872d9c6912a5ded8fac432a85bc86216968765c726a68338e953b8e9
MD5 c248a471022f96287fe2c31f91a785b8
BLAKE2b-256 ebbc65bfe9e0dca3141ecc96ab519e4030e9706b1ca5db9aaa66009ebc02b62d

See more details on using hashes here.

File details

Details for the file olca-0.2.78-py3-none-any.whl.

File metadata

  • Download URL: olca-0.2.78-py3-none-any.whl
  • Upload date:
  • Size: 36.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.15

File hashes

Hashes for olca-0.2.78-py3-none-any.whl
Algorithm Hash digest
SHA256 a370b99d617e6ab3bda14fb8a7410230caea972f4a8318589a0f491aa6f681f2
MD5 daa4e323ea23f8442b0343d2218900ba
BLAKE2b-256 11bdac1a890d0502f2bf5ac7133f8380851c4f3b6f9e0995a735503410106a70

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page