A local-first conversational AI tool featuring persistent memory. Return to your chat history at any time or seamlessly switch models while retaining full context of your previous conversations.
OverviewKey FeaturesPrerequisitesInstallationUsageSwitching ModelsCreditsContactsBuy Me a Coffee
abah_chat is designed to eliminate session loss during local LLM interactions. It stores conversation histories across sessions in persistent storage, allowing you to:
- Resume conversations exactly where you left off.
- Switch between different local models without losing chat context.
- Query the LLM about past discussions and saved history.
Persistent Chat History: Conversations are saved locally across restarts.Model Interoperability: Swap the underlying LLM at any point and continue referencing prior context.Context Querying: Prompt the LLM directly to summarize or recall where you left off in past sessions.100% Local & Private: Powered locally through Ollama.
Python:3.12.13
(or Python3.12+
)Ollama: Installed and running locally
Clone the repository and navigate to the project root:
git clone https://github.com/john-abah/ABAH_CHAT.git
cd ABAH_CHAT
Install the package in editable mode:
pip install -e .
Pull the model in Ollama:
ollama pull gemma4:12b
Start the Ollama background service:
ollama serve
Launch the chat assistant in your CLI:
abah_chat
Interact with the assistant:- Type your messages normally to chat.
- Ask contextual questions such as "Where did we leave off last time?"or"Summarize our previous conversation".
If you wish to use a different model pulled from Ollama:
- Pull your desired model:
ollama pull <your-model-name>
- Open
abahchat.py
and update:self.model_client
to your new model name.model_info
to match the specifications of the newly pulled model.
- If the program is currently running, exit the session and run
abah_chat
again for the changes to take effect.
Author: John Abah
Email:john.abah@stud.hshl.de** LinkedIn:**John Abah
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