Knob Registry

Max code snippet length in semantic chunk_summaries

Directories to skip when building chunk_summaries

Keywords that, when present in code, skip the chunk

File patterns/extensions to skip

Max API routes to include per chunk_summary

Max symbols to include per chunk_summary

Max length for purpose field in chunk_summaries

Quick tips shown in chunk_summaries builder UI

Overlap lines for AST chunking

Overlap between chunks

Target chunk size (non-whitespace chars)

Chunking strategy

Target size for greedy chunking

Maximum tokens per chunk - chunks exceeding this are split recursively

Max file size to index (bytes) - files larger than this are skipped

Minimum chunk size

Include imports in chunks

Port for dev backend (Uvicorn)

Port for dev frontend (Vite)

Timeout for dev stack restart operations (seconds)

Timeout for Docker container actions (start/stop/restart)

Timeout for Docker container list (seconds)

Docker socket URL (e.g., unix:///var/run/docker.sock). Leave empty for auto-detection.

Timeout for Docker infrastructure down command (seconds)

Timeout for Docker infrastructure up command (seconds)

Default number of log lines to tail from containers

Include timestamps in Docker logs (1=yes, 0=no)

Timeout for Docker status check (seconds)

Batch size for embedding generation

Enable embedding cache

Embedding dimensions

Max tokens per embedding chunk

OpenAI embedding model

Local SentenceTransformer model

Max retries for embedding API

Embedding API timeout (seconds)

Embedding provider (dynamic - validated against models.json at runtime)

Voyage embedding model

Enable chunk_summary enrichment by default

Max chunk_summaries to generate

Enable chunk enrichment

Max chars for enrichment prompt

Min chars for enrichment

Enrichment timeout (seconds)

Baseline results path

Evaluation dataset path

Multi-query variants for evaluation

K used for ndcg_at_10 metric (default 10).

K used for precision_at_5 metric (default 5).

K used for recall_at_10 metric (default 10).

K used for recall_at_20 metric (default 20).

K used for recall_at_5 metric (default 5).

Weight for graph search results (Neo4j)

Fusion method: 'rrf' (Reciprocal Rank Fusion) or 'weighted' (score-based)

Normalize scores to [0,1] before fusion

RRF smoothing constant (higher = more weight to top ranks)

Weight for sparse BM25/FTS search results

Weight for vector search results (pgvector)

Enrichment backend

Disable code enrichment

Model for code enrichment

Ollama enrichment model

Max tokens for generation

Primary generation model

CLI generation model

HTTP transport generation model override

MCP transport generation model override

Ollama generation model

Max retries for generation

Generation temperature

Generation timeout (seconds)

Nucleus sampling threshold

Context window for Ollama

Maximum total time to wait for a local (Ollama) generation request to complete (seconds)

Maximum idle time allowed between streamed chunks from local (Ollama) during generation (seconds)

Ollama API URL

OpenAI API base URL override (for proxies)

Edge weight for AST call relationships (function->callee).

Edge weight for AST containment relationships (module->class/function, class->method).

Edge weight for AST import relationships (module->imported_module).

Edge weight for AST inheritance relationships (class->base).

Build lexical graph (Document/Chunk nodes + NEXT_CHUNK relationships)

Chunk node property that stores the embedding vector

Neo4j vector index name for Chunk embeddings (mode='chunk')

Enable graph building during indexing (Neo4j)

Build semantic knowledge graph (concept entities + relations) linked to chunks during indexing

LLM model name for semantic KG extraction when semantic_kg_mode='llm' (empty = use generation.enrich_model)

Timeout (seconds) for semantic KG LLM extraction per chunk

Maximum chunks to process for semantic KG extraction per indexing run (0 = disabled)

Maximum semantic concepts to extract per chunk

Maximum semantic relations to create per chunk (heuristic mode)

Minimum length for semantic concept tokens

Semantic KG extraction mode. 'heuristic' is deterministic and test-friendly; 'llm' uses an LLM to extract entities + relations.

Edge weight for semantic concept relations in heuristic fallback mode.

Edge weight for semantic concept relations in LLM mode.

Store chunk embeddings on Chunk nodes for Neo4j vector search (requires dense embeddings)

Timeout waiting for Neo4j vector index ONLINE (seconds)

Neo4j vector similarity function

Wait for the Neo4j vector index to come ONLINE after (re)creating it

When mode='chunk', expand from seed chunks via Entity graph (IN_CHUNK links) to find related chunks

Blend weight for entity-expansion scores relative to seed chunk scores (mode='chunk')

When mode='chunk', include up to N adjacent chunks (NEXT_CHUNK) around each seed hit

When mode='chunk' and Neo4j uses a shared database, overfetch seed hits before filtering by corpus_id

Enable graph search in tri-brid retrieval

Include community-based expansion in graph search

Maximum graph traversal hops

Graph retrieval mode. 'chunk' uses lexical chunk nodes + Neo4j vector index; 'entity' uses the legacy code-entity graph.

Number of results to retrieve from graph search

Community detection algorithm

Entity types to extract and store in graph

Number of results from graph traversal

Include community detection in graph analysis

Maximum traversal hops for graph search

Automatically create per-corpus Neo4j databases when missing (Enterprise).

Neo4j database name

Database isolation mode: 'shared' uses a single Neo4j database (Community-compatible), 'per_corpus' uses a separate Neo4j database per corpus (Enterprise multi-database).

Prefix for per-corpus Neo4j database names when neo4j_database_mode='per_corpus'.

Neo4j password (recommend using environment variable)

Neo4j connection URI (bolt:// or neo4j://)

Neo4j username

Relationship types to extract

Max characters to hydrate

Context hydration mode

Stemmer language

Stopwords language code

BM25 tokenizer type

Collection suffix for multi-index scenarios

Excluded file extensions (comma-separated)

Max file size to index (MB)

Batch size for indexing

Parallel workers for indexing

Base output directory

PostgreSQL connection string (DSN) for pgvector + FTS storage

Override for OUT_DIR_BASE if specified

Fallback repository path if not found in repos.json

Repository configuration file

Skip dense vector indexing

pgvector table name template

Auto-generate keywords

Score boost for keyword matches

Max discriminative keywords per repo

Min frequency for keyword

Hours between keyword refresh

Bonus for recently modified files

Bonus for GUI/front-end layers

Bonus for indexing/ingestion layers

Intent-to-layer bonus matrix. Keys are query intents, values are layer->multiplier maps.

Bonus for retrieval/API layers

Penalty for vendor/third-party code (negative values apply a penalty)

Allowed Host header values for MCP HTTP (supports wildcard ':*').

Allowed Origin header values for MCP HTTP (supports wildcard ':*').

Default retrieval mode for MCP search/answer tools when not provided.

Default top_k for MCP search/answer tools when not provided.

Enable DNS rebinding protection for MCP HTTP (recommended).

Enable the embedded MCP Streamable HTTP server.

Prefer JSON responses for MCP Streamable HTTP (recommended).

Mount path for the MCP Streamable HTTP endpoint (e.g. /mcp).

Require `Authorization: Bearer $MCP_API_KEY` for MCP HTTP access.

Run MCP Streamable HTTP in stateless mode (recommended).

Snippet chars for reranking input

Cloud reranker model name when mode=cloud (Cohere: rerank-v3.5)

Cloud reranker provider when mode=cloud (cohere, voyage, jina)

Number of candidates to rerank (cloud mode)

Local HuggingFace cross-encoder model when mode=local

Reranker mode: 'cloud' (Cohere/Voyage API), 'local' (HuggingFace cross-encoder), 'learning' (TRIBRID cross-encoder-tribrid), 'none' (disabled)

Reranker API timeout (seconds)

Allow transformers remote code for HF rerankers that require it

Blend weight for reranker scores

Reranker batch size

Max token length for reranker

Hot-reload on model change

Reload check period (seconds)

Number of candidates to rerank (local/learning mode)

BM25 length normalization (0=no penalty, 1=full penalty, 0.3-0.5 recommended for code)

BM25 term frequency saturation parameter (higher = more weight to term frequency)

Weight for BM25 in hybrid search

Enable chunk_summary-based retrieval

Minimum confidence threshold

Confidence threshold for avg top-5

Confidence threshold for top-1

Top-k for evaluation runs

Enable multi-query in eval

Confidence threshold for fallback retrieval strategies

Default top-k for search results

Max characters for result hydration

Result hydration mode

Number of final results to return in LangGraph pipeline

Maximum number of query rewrites for LangGraph pipeline

Maximum number of query rewrites for multi-query expansion

Query variants for multi-query

Enable synonym expansion

RRF rank smoothing constant (higher = more weight to top ranks)

Top-K for dense vector search

Top-K for sparse BM25 search

Custom path to semantic_synonyms.json (default: data/semantic_synonyms.json)

Enable semantic synonym expansion

Weight for vector search

Bonus score for chunks matched via chunk_summary-based retrieval

Score multiplier when filename exactly matches query terms

Score multiplier when path components match query terms

Comma-separated path prefixes to boost

Vendor code preference

BM25 length normalization (0 = no penalty, 1 = full penalty)

BM25 term frequency saturation (higher = more weight to term frequency)

Enable sparse BM25 search in tri-brid retrieval

Number of results to retrieve from sparse search

Extract metadata from code chunks during indexing

Analyze eval regressions with skeptical approach - avoid false explanations

Lightweight chunk_summary generation prompt for faster indexing

Main conversational AI system prompt for answering codebase questions

Generate query variants for better recall in hybrid search

Optimize user query for code search - expand CamelCase, include API nouns

Generate JSON summaries for code chunks during indexing

Prompt for LLM-assisted semantic KG extraction (concepts + relations)

Include resolved alerts

Alert severities to notify

Alert webhook timeout (seconds)

LangChain/LangSmith API endpoint

LangChain project name

Enable LangChain v2 tracing

LangTrace API host

LangTrace project ID

Logging level

Enable metrics collection

Prometheus metrics port

Auto-enable LangSmith tracing

Number of traces to retain

Trace sampling rate (0.0-1.0)

Enable distributed tracing

Tracing backend mode

Query log file path

Training batch size

Training epochs for reranker

Learning rate

Warmup steps ratio

Triplet mining mode

Reset triplets file before mining

Reranker model path

Training triplets file path

Min triplets for training

Triplet mining mode

Default model for chat if not specified in request

Max chat history messages

Show citations list on chat answers

Show confidence badge on chat answers

Show dev/debug footer under chat answers

Show routing trace panel by default

Include reasoning/thinking in streamed responses when supported by model

Streaming response timeout in seconds

Enable streaming responses

Max thinking tokens for Anthropic extended thinking

Editor bind mode

Enable editor embedding

Enable embedded editor

Editor Docker image

Embedded editor port

Grafana authentication mode

Grafana base URL

Grafana dashboard slug

Default Grafana dashboard UID

Enable Grafana embedding

Grafana kiosk mode

Grafana organization ID

Grafana refresh interval

Auto-open browser on start

Runtime environment mode (development uses localhost, production uses deployed URLs)

UI theme mode

Enable vector search in tri-brid retrieval

Minimum similarity score threshold (0 = no threshold)

Number of results to retrieve from vector search