Conversant is a Python framework for building customizable dialogue agents powered by Cohere's large language models. Maintained by the Cohere ConvAI Team until March 1, 2023, the library enables developers to create chatbots with distinct personas that can engage in natural conversations with users. The project is distributed via PyPI and requires Python 3.8 or higher along with Cohere 2.8.0 or later.
The framework provides several pre-built personas out of the box, including a client support agent, a watch sales agent, a math teacher, and a fantasy wizard character. Users can also create entirely custom personas by providing a description and example conversations. The library handles the underlying complexity of managing chat history and context, allowing developers to focus on defining persona characteristics and conversation examples rather than implementing dialogue management logic themselves.
Conversant operates using prompt completion techniques, where a persona is defined through a description and few-shot examples that are sent to Cohere's generate endpoint. Each user message and chatbot response is appended to a chat history, ensuring that future responses remain contextually grounded in the ongoing dialogue. The framework is designed to be modular, flexible, and extensible, enabling creation of diverse chatbot types without requiring deep expertise in conversational AI systems.
The repository includes a Streamlit demo application that allows users to interact with different personas without installation. The demo is available at conversant.streamlit.app and provides an interactive interface for testing chatbots. Users can also run their own local Streamlit instance by setting up a Cohere API key and executing the provided demo application. The Streamlit integration enables both testing existing personas and editing them directly within the web interface.
Creating custom personas involves defining a configuration file in JSON format that specifies chatbot parameters, client settings for the language model, and chat prompt configuration. The config structure includes fields for maximum context examples, avatar selection, generation parameters, persona description, example separators, conversation headers, and few-shot examples. The framework automatically incorporates new personas into the Streamlit dropdown menu once they are properly configured in the designated personas directory.
The library is part of Cohere's Sandbox initiative, an experimental open-source program for conversational AI tooling. The project maintains active testing infrastructure with automated test workflows and is licensed under the MIT License. Documentation is available through the project's GitHub Pages site, and community support is provided via the Cohere Discord server.
GitGenius activity data indicates this repository has overlapping contributors with the astral-sh/ruff project, suggesting cross-pollination between the Cohere conversational AI efforts and the broader Python development tools ecosystem. The repository is classified across multiple domains including machine learning models, dialogue systems, semantic understanding, chatbot development, and natural language processing, reflecting its comprehensive approach to conversational AI implementation.
