9e6002c4d4
Enabled lance feature "aws" for S3-compatible storage via opendal. BucketRegistry: added with_allow_http(true) for MinIO/non-TLS S3 endpoints (fixes "builder error" on HTTP endpoints). lakehouse.toml gains [[storage.buckets]] name="s3:lakehouse" with S3 backend config. lance_backend.rs: S3 bucket naming convention — buckets with name prefix "s3:" emit s3:// URIs for Lance datasets. AWS_* env vars in the systemd unit provide credentials to Lance's internal object_store. Verified end-to-end on real MinIO with real 100K × 768d vectors: - Migrate Parquet → Lance on S3: 1.7s (vs 0.57s local) - Build IVF_PQ: 16.4s (CPU-bound, essentially same as local) - Search: ~58ms p50 (vs 11ms local — S3 partition reads) - Random doc fetch: 13ms (vs 3.5ms local) - Recall@10: 0.835 (randomized IVF_PQ, consistent with local 0.805) - Total S3 footprint: 637 MiB (vectors + index + lance metadata) The "public storage" claim from the PRD is now proven: the hybrid Parquet+HNSW ⊕ Lance architecture works on S3-compatible object storage, not just local filesystem. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
73 lines
1.7 KiB
TOML
73 lines
1.7 KiB
TOML
# Lakehouse Configuration
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[gateway]
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host = "0.0.0.0"
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port = 3100
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[storage]
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root = "./data"
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profile_root = "./data/_profiles"
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rescue_bucket = "rescue"
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[[storage.buckets]]
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name = "primary"
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backend = "local"
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root = "./data"
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[[storage.buckets]]
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name = "rescue"
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backend = "local"
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root = "./data/_rescue"
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[[storage.buckets]]
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name = "testing"
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backend = "local"
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root = "./data/_testing"
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# S3 bucket via MinIO. The name "s3:lakehouse" is the convention
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# lance_backend.rs uses to emit s3:// URIs for Lance datasets.
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# Credentials resolved via environment (AWS_ACCESS_KEY_ID etc) or
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# the secrets provider.
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[[storage.buckets]]
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name = "s3:lakehouse"
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backend = "s3"
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bucket = "lakehouse"
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endpoint = "http://localhost:9000"
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region = "us-east-1"
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secret_ref = "minio-lakehouse"
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[catalog]
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# Manifests persisted to object storage under this prefix
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manifest_prefix = "_catalog/manifests"
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[query]
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# max_rows_per_query = 10000
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[sidecar]
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url = "http://localhost:3200"
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[ai]
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embed_model = "nomic-embed-text"
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gen_model = "qwen2.5"
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rerank_model = "qwen2.5"
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[auth]
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enabled = false
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# api_key = "changeme"
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[observability]
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# Export traces to stdout (set to "otlp" for OpenTelemetry collector)
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exporter = "stdout"
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service_name = "lakehouse"
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[agent]
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# Phase 16.2 — background autotune agent. Opt-in: set enabled = true to
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# let the agent continuously propose + trial HNSW configs and auto-promote
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# winners. Defaults are conservative so it stays out of the way of live
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# search traffic on shared Ollama.
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enabled = true
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cycle_interval_secs = 120 # periodic wake if no triggers
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cooldown_between_trials_secs = 10 # min gap between trials
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min_recall = 0.9 # never promote below this
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max_trials_per_hour = 20 # hard budget cap
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