# --- Connection Settings ---
api:
  base_url: "http://framework.tawny-bellatrix.ts.net:1234"
  api_version: "/v1/"

# --- Model Settings ---
models:
  enrich: "lm_studio/qwen-" # will have an identifier, based on amount of active LLMs see ./load_ingestion_llms.sh
  embedding: "text-embedding-qwen3-embedding-8b"
  retrieval: "lm_studio/qwen/qwen3-30b-a3b-2507"
  expansion: "lm_studio/qwen/qwen3-30b-a3b-2507"

# --- Ingestion Settings ---
ingestion:
  data_dir: "/home/jake/dnd_test/"
  db_path: "./data/"
  db_name: "dmv.db"
  toon_dir: "./data/toon_files"
  active_llms: 2
  parallel_requests_per_llm: 2
  chunk_size: 800
  chunk_overlap: 100
  embedding_batch_size: 32
  time_file_location: "./data/time_file.txt"

# ---- Agent Settings ----
ingestion_agent:
  ingestion_signature: |
    You are an expert Dungeon Master's assistant.
    Analyze the provided notes and extract a concise synopsis and relevant metadata.
    synopsis = A one-sentence summary of the document.
    tags = Relevant tags (NPCs, Locations, Items, Plot Points).
    entities = A list of Key names of people, places, or factions found in the document.
    relationships = A list of object relationships between entities. For each pair of entities that appear together,
                    specify their relationship type (ally, enemy, mentor, servant, family, business_partner, etc.)
                    and connection strength (1-5 based on how often they appear together).
                    Format: [{"entity1": "Name", "entity2": "Name", "type": "relationship_type", "strength": int}, ...]
    Output ONLY the metadata dictionary with these keys.

retrieval_agent:
  retrieval_signature: |
    You are an expert Dungeon Master's assistant.
    Given the context and the question, answer the question.
    Do not make things up, base all of your answers on the context.
    Always site the file location of your source of information.

expansion_agent:
  expansion_signature: |
    You are a query expansion expert, specialised in Dungeons and Dragons.
    Given a user's question, generate 3-5 similar but enhanced search queries that would help find more relevant information.
    Each expanded query should be distinct and add different perspective to the original question.
    Return only the queries as a JSON list with key "queries"."""