Story Crater Bot
33eaf1b4f8
- Add database schema with pgvector extension (L0/L1/L2 memories) - Implement pgvector-backed vector store with similarity search - Add Ollama embeddings client for 768-dim nomic embeddings - Implement ingest worker to process records into L0/L1 memory - Implement query worker with semantic search across memory tiers - Rewrite HTTP server with database connection pooling - Wire all endpoints to actual backend (ingest, query, projects, skills) - Update main.rs to use DATABASE_URL from environment - All code compiles, ready for Docker build and deployment
38 lines
913 B
TOML
38 lines
913 B
TOML
[package]
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name = "mem-cli"
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version = "0.1.0"
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edition = "2021"
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[lib]
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name = "mem_cli"
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path = "src/lib.rs"
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[[bin]]
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name = "mem"
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path = "src/main.rs"
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[dependencies]
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mem-core = { path = "../mem-core" }
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mem-chunk = { path = "../mem-chunk" }
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mem-llm = { path = "../mem-llm" }
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mem-ingest = { path = "../mem-ingest" }
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mem-store = { path = "../mem-store" }
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tokio = { workspace = true }
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futures = { workspace = true }
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serde = { workspace = true }
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serde_json = { workspace = true }
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serde_yaml = { workspace = true }
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anyhow = { workspace = true }
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thiserror = { workspace = true }
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clap = { workspace = true }
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tracing = { workspace = true }
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tracing-subscriber = { workspace = true }
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time = { workspace = true }
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actix-web = { workspace = true }
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actix-rt = { workspace = true }
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uuid = { workspace = true }
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chrono = { workspace = true }
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sqlx = { workspace = true }
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pgvector = { workspace = true }
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base64 = { workspace = true }
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