class MyCustomEngine(BaseEngine): def __init__(self, model_path): super().__init__() self.model = load_my_fancy_transformer(model_path)
What It Is Starsessions NN is a lightweight, open‑source framework for building and running neural‑network‑driven “session” experiences . Think of it as a toolkit that lets developers create interactive, AI‑enhanced sessions—whether they’re chat‑bots, tutoring modules, or creative‑writing assistants—while keeping the focus on star‑themed or high‑visibility use‑cases (hence the “Star” prefix). starsessions nn
Give it a spin, and let your users “reach for the stars” in every conversation! 🚀✨ 🚀✨ # 3️⃣ Run the demo session python
# 3️⃣ Run the demo session python examples/run_demo.py You’ll see a minimal web UI at http://localhost:8000 where you can type messages and watch the NN generate responses while the star‑progress bar fills. | Concept | One‑Line Definition | |---------|----------------------| | Session | A self‑contained conversation or interaction that retains state across turns. | | Context Buffer | Stores the last N tokens (default = 512) to give the model the necessary history. | | Star‑Score | A normalized confidence metric (0–5★) displayed as a star rating; useful for quick human review. | | Persistence Layer | Optional SQLite/Redis store that lets you resume a session after a server restart. | Extending the NN Engine from starsessions.nn import BaseEngine | | Star‑Score | A normalized confidence metric
# 2️⃣ Install dependencies (Python 3.10+) pip install -r requirements.txt
def generate(self, prompt, context): # Combine prompt + context, feed into the model return self.model.generate(prompt + context, max_length=150) Swap the engine in the config: