contexting/context.toml.example at main · ktappdev/contexting · GitHub

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[common]
output = ".ctxt/ctx_index.json"
synonym_cache = ".ctxt/ctx_cache.json"
llm_model = "meta-llama/llama-3.1-8b-instruct"  # any OpenAI-compatible model name
batch_size = 15             # names per batch; 15 works well for 8B models
synonyms_min = 4            # min synonyms per name
synonyms_max = 8            # max synonyms per name
ignore = [".git", ".venv", "site-packages", "__pycache__", "node_modules", "vendor", "dist", "migrations", "pb_migrations", "alembic", "flyway"]
# Extra dot files to keep (merged with built-in defaults like .prettierrc, .editorconfig, etc.)
dot_whitelist = []
verbose = true

[llm]
# LLM provider name shown in logs (cosmetic)
provider = "openrouter"
# API endpoint - OpenAI-compatible
endpoint = "https://openrouter.ai/api/v1/chat/completions"
# Model to use
model = "meta-llama/llama-3.1-8b-instruct"
# API key (not needed if using env var)
api_key = ""
# Environment variable containing API key
api_key_env = "OPENROUTER_API_KEY"
# Sampling parameters
temperature = 0.3
max_tokens = 0
# Concurrent LLM requests (1 = sequential, 2+ = parallel batches)
parallel_requests = 4

[init]
root = "."

[watch]
root = "."
debounce = "750ms"
llm = true
persist = "shutdown"
persist_interval = "45s"
search_log = true
search_log_query_max = 120
max_batch_size = 0

[search]
index = "ctx_index.json"
limit = 5
min_score = 1
type = "all"
dir_summary = false
dir_limit = 5
drill_limit = 3
memory = true
runtime_file = "ctx_runtime.json"
explain = false
json = false
show_tokens = false

[eval]
index = "ctx_index.json"
cases = "ctx_cases.json"
limit = 5
min_score = 1
type = "all"
explain = false
json = false