Agus Zubiaga
1bd34e0db0
Retrieval stats will now use polars to build a big data frame for references with the cartesian product of LSP declarations and retrieved declaration candidates (with all their score components) and rebuilds the stats summary on top of it. This data frame is written to a `.parquet` file, which we can load into advanced analytics tools (such as Metabase), so we can explore our scoring distributions and find ways to improve retrieval, and then train the decision tree. Release Notes: - N/A
57 lines
1.4 KiB
TOML
57 lines
1.4 KiB
TOML
[package]
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name = "zeta_cli"
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version = "0.1.0"
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edition.workspace = true
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publish.workspace = true
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license = "GPL-3.0-or-later"
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[lints]
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workspace = true
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[[bin]]
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name = "zeta"
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path = "src/main.rs"
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[dependencies]
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anyhow.workspace = true
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chrono.workspace = true
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clap.workspace = true
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client.workspace = true
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cloud_llm_client.workspace= true
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cloud_zeta2_prompt.workspace= true
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collections.workspace = true
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debug_adapter_extension.workspace = true
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edit_prediction_context.workspace = true
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extension.workspace = true
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fs.workspace = true
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futures.workspace = true
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gpui.workspace = true
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gpui_tokio.workspace = true
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language.workspace = true
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language_extension.workspace = true
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language_model.workspace = true
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language_models.workspace = true
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languages = { workspace = true, features = ["load-grammars"] }
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log.workspace = true
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node_runtime.workspace = true
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ordered-float.workspace = true
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paths.workspace = true
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polars = { version = "0.51", features = ["lazy", "dtype-struct", "parquet"] }
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project.workspace = true
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prompt_store.workspace = true
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release_channel.workspace = true
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reqwest_client.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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settings.workspace = true
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shellexpand.workspace = true
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smol.workspace = true
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soa-rs = "0.8.1"
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terminal_view.workspace = true
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util.workspace = true
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watch.workspace = true
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workspace-hack.workspace = true
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zeta.workspace = true
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zeta2.workspace = true
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zlog.workspace = true
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