# parameters.py
# All tunable values live here.

# ---------- LLM settings ----------
MODEL = "mistral-small-latest"
TEMPERATURE = 0.3
MAX_TOKENS = 1024
MAX_AGENT_STEPS = 5

# ---------- Embeddings (sentence-transformers) ----------
# Local model used for both the supervised classifier and the unsupervised
# clusterer. Downloaded once (~90MB) and cached. Change to any other model
# from https://huggingface.co/sentence-transformers if you want different
# speed/quality trade-offs.
EMBEDDING_MODEL = "all-MiniLM-L6-v2"

# ---------- Supervised training settings ----------
TRAIN_TEST_SPLIT = 0.8                  # fraction of data used for training

# ---------- Unsupervised clustering settings ----------
# Only Hierarchical Agglomerative Clustering is used (semantic embeddings +
# cosine distance + average linkage). The single tunable is the number of
# clusters, exposed as a slider in the UI. This value is the default slider
# position.
CLUSTER_DEFAULT_N_CLUSTERS = 6