# --- Preset selection (models.yaml is the source of truth) ---
ACTIVE_MODEL=minicpm5-1b
# Dev: enable dropdown in Gradio. Space: leave false to pin one model for visitors.
ALLOW_MODEL_SWITCH=false
# MODEL_PRESETS_PATH=./models.yaml

# --- Agent outputs ---
# AGENT_OUTPUTS_DIR=/tmp/agent_outputs
# AGENT_TRACES_DIR=outputs/traces
# SKILLS_DIR=./skills

# --- ResearchMind (MemRAG + scraper) ---
# RESEARCHMIND_DATA_DIR=outputs/researchmind
# RESEARCHMIND_EMBED_MODEL=all-MiniLM-L6-v2
# RESEARCHMIND_AUTO_SEARCH=false
# RESEARCHMIND_TOP_K=5
# RESEARCHMIND_CHUNK_SIZE=512
# RESEARCHMIND_CHUNK_OVERLAP=128

# --- Legacy single-model overrides (optional; applied to ACTIVE_MODEL only) ---
# INFERENCE_BACKEND=transformers
# MODEL_ID=openbmb/MiniCPM5-1B
# TRUST_REMOTE_CODE=true

# --- llama.cpp presets (optional) ---
# ACTIVE_MODEL=qwen3b-gguf
# INFERENCE_BACKEND=llama_cpp
# MODEL_REPO=Qwen/Qwen2.5-3B-Instruct-GGUF
# MODEL_FILE=qwen2.5-3b-instruct-q4_k_m.gguf
# N_CTX=4096
# N_GPU_LAYERS=0

# Optional: local GGUF path instead of Hub download
# MODEL_PATH=./models/qwen2.5-3b-instruct-q4_k_m.gguf

# Optional: local fine-tuned merged weights
# ACTIVE_MODEL=gemma-merged-local
# MODEL_ID=./gemma_merged_model

# --- Fine-tuning (research/finetune.py) ---
# FINETUNE_PRESET=minicpm5-1b
# FINETUNE_MODEL=openbmb/MiniCPM5-1B
# FINETUNE_DATASET=./research/data/education-lesson-chat.jsonl
# FINETUNE_DATASET=tatsu-lab/alpaca
# FINETUNE_DATASET_CONFIG=
# FINETUNE_DATASET_SPLIT=train
# FINETUNE_MAX_SAMPLES=500
# FINETUNE_OUT=./models/finetuned/minicpm5-1b-lora
# FINETUNE_FORMAT=chat
# After training, point Gradio at the adapter preset:
# ACTIVE_MODEL=minicpm5-1b-lesson-lora

# --- Ensemble research (research/ensemble/) ---
# Base LLM resolution (first match wins): ENSEMBLE_LLM, LLM_PATH, BASE, MODEL_ID, ACTIVE_MODEL
# LLM_PATH=./models/finetuned/minicpm5-1b-lora-merged
# ENSEMBLE_LLM=Qwen/Qwen2.5-0.5B-Instruct
# ENSEMBLE_PRESET=minicpm5-1b
# ENSEMBLE_OUT=./models/ensemble/minicpm5-1b-jepa-pretrain
# ENSEMBLE_QA=./research/data/benchmark-qa.jsonl
# ENSEMBLE_KB=./research/data/benchmark-kb.jsonl
# ENSEMBLE_CKPT=./models/ensemble/jepa-lesson-pretrain

BASE=openbmb/MiniCPM5-1B