Sophia — AI Assistant
A conversational AI research playground for memory, tool-use and multi-step planning.

Overview
Sophia, a conversational AI prototype exploring tool-calling, contextual memory over structured JSON state, and multi-step task planning with citations and recall.
- Role
- Solo builder · AI Engineer
- Year
- 2025
- Live link
- Source on GitHub
Goals
- Test whether an LLM can hold multi-turn task state reliably.
- Give the assistant tools rather than only text output.
- Keep memory inspectable instead of hidden in an embedding blob.
- Build the agentic patterns later reused in J.A.R.V.I.S — NIX.
Approach & architecture
- 1
Prompt orchestration
Structured system prompts and templates separate role, tools and task state so behaviour stays predictable.
- 2
Tool calling
The model returns structured calls into a small tool set instead of free-form instructions.
- 3
Lightweight memory
Context is stored as structured JSON state, which is readable and diffable rather than opaque.
- 4
Planning loop
Multi-step tasks are decomposed, executed and re-checked against the original request.

Tech stack

Results
task flow with recall and citations
inspectable memory state instead of opaque embeddings
patterns carried into J.A.R.V.I.S — NIX
Frequently asked questions
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J.A.R.V.I.S — NIX
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