feat: add index persistence

README.md

@@ -63,6 +63,20 @@ semble search "save_pretrained" ./my-project
 semble search "save model to disk" ./my-project --top-k 10
 ​```
 
+If you anticipate doing more than one search, use `semble index` to create an index.
+
+​```bash
+semble index ./my-project -o my_index
+​```
+
+You can then reuse this index later on:
+
+​```bash
+semble search "save_pretrained" --index my_index
+​```
+
+An index is not automatically updated, so if the code changes significantly, reindex. If you notice stale results while resolving searches to files, reindex.
+
 Use `--content docs` to search documentation and prose, `--content config` for config files (yaml, toml, etc.), or `--content all` to search code, docs, and config:
 
 ​```bash
@@ -77,17 +91,20 @@ Use `semble find-related` to discover code similar to a known location (pass `fi
 semble find-related src/auth.py 42 ./my-project
 ​```
 
+Like search, `find-related` also accepts an `--index` argument.
+
 `path` defaults to the current directory when omitted; git URLs are accepted.
 
 If `semble` is not on `$PATH`, use `uvx --from "semble[mcp]" semble` in its place.
 
 ### Workflow
 
-1. Start with `semble search` to find relevant chunks.
-2. Use `--content docs` for documentation, `--content config` for config files, or `--content all` for everything.
-3. Inspect full files only when the returned chunk is not enough context.
-4. Optionally use `semble find-related` with a promising result's `file_path` and `line` to discover related implementations.
-5. Use grep only when you need exhaustive literal matches or quick confirmation of an exact string.
+1. Index the repo using `semble index -o cached_index`.
+2. Start with `semble search` to find relevant chunks. Pass the index to achieve results faster.
+3. Use `--content docs` for documentation, `--content config` for config files, or `--content all` for everything.
+4. Inspect full files only when the returned chunk does not give enough context.
+5. Optionally use `semble find-related` with a promising result's `file_path` and `line` to discover related implementations.
+6. Use grep only when you need exhaustive literal matches or quick confirmation of an exact string.
 ```
 
 </details>
@@ -318,6 +335,20 @@ semble search "save_pretrained" ./my-project
 semble search "save model to disk" ./my-project --top-k 10
 ​```
 
+If you anticipate doing more than one search, use `semble index` to create an index.
+
+​```bash
+semble index ./my-project -o my_index
+​```
+
+You can then reuse this index later on:
+
+​```bash
+semble search "save_pretrained" --index my_index
+​```
+
+An index is not automatically updated, so if the code changes significantly, reindex. If you notice stale results while resolving searches to files, reindex.
+
 Use `--content docs` to search documentation and prose, `--content config` for config files (yaml, toml, etc.), or `--content all` to search code, docs, and config:
 
 ​```bash
@@ -332,17 +363,20 @@ Use `semble find-related` to discover code similar to a known location (pass `fi
 semble find-related src/auth.py 42 ./my-project
 ​```
 
+Like search, `find-related` also accepts an `--index` argument.
+
 `path` defaults to the current directory when omitted; git URLs are accepted.
 
 If `semble` is not on `$PATH`, use `uvx --from "semble[mcp]" semble` in its place.
 
-## Workflow
+### Workflow
 
-1. Start with `semble search` to find relevant chunks.
-2. Use `--content docs` for documentation, `--content config` for config files, or `--content all` for everything.
-3. Inspect full files only when the returned chunk is not enough context.
-4. Optionally use `semble find-related` with a promising result's `file_path` and `line` to discover related implementations.
-5. Use grep only when you need exhaustive literal matches or quick confirmation of an exact string.
+1. Index the repo using `semble index -o cached_index`.
+2. Start with `semble search` to find relevant chunks. Pass the index to achieve results faster.
+3. Use `--content docs` for documentation, `--content config` for config files, or `--content all` for everything.
+4. Inspect full files only when the returned chunk does not give enough context.
+5. Optionally use `semble find-related` with a promising result's `file_path` and `line` to discover related implementations.
+6. Use grep only when you need exhaustive literal matches or quick confirmation of an exact string.
 ```
 
 ### Sub-agent setup
@@ -365,8 +399,14 @@ If semble is not on `$PATH`, prefix the command with `uvx --from "semble[mcp]"`.
 Semble also ships as a standalone CLI. This is useful in scripts or anywhere you want search results without an MCP session.
 
 ```bash
+# Index a local repository
+semble index ./my-project -o my-index
+
 # Search a local repo
 semble search "authentication flow" ./my-project
+# Or with index (significantly faster)
+# the index flag applies to all commands below.
+semble search "authentication flow" --index my-index
 
 # Search for a symbol or identifier
 semble search "save_pretrained" ./my-project

benchmarks/baselines/ablations.py

@@ -5,7 +5,6 @@
 from dataclasses import asdict
 
 import numpy as np
-from model2vec import StaticModel
 
 from benchmarks.data import (
     RepoSpec,
@@ -38,8 +37,6 @@
 def _bench(
     repo_tasks: dict[str, list[Task]],
     specs: dict[str, RepoSpec],
-    model: StaticModel,
-    modes: list[str],
     *,
     verbose: bool = False,
 ) -> list[RepoResult]:
@@ -62,7 +59,7 @@ def _bench(
             print(f"\n--- {repo} ---", file=sys.stderr)
 
         started = time.perf_counter()
-        index = SembleIndex.from_path(spec.benchmark_dir, model=model)
+        index = SembleIndex.from_path(spec.benchmark_dir)
         index_ms = (time.perf_counter() - started) * 1000
 
         for mode, (alpha, rerank) in sorted(_MODE_PARAMS.items()):
@@ -98,30 +95,26 @@ def _bench(
 def _parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description="semble ablation benchmarks.")
     add_filter_args(parser, verbose=True)
-    parser.add_argument(
-        "--mode", action="append", default=[], choices=sorted(_MODE_PARAMS), help="Mode(s) to evaluate (default: all)."
-    )
     return parser.parse_args()
 
 
 def main() -> None:
     """Run the semble ablation benchmarks."""
     args = _parse_args()
-    modes = args.mode or sorted(_MODE_PARAMS)
 
     repo_specs, tasks = load_filtered_tasks(args.repo or None, args.language or None)
 
     print("Loading model...", file=sys.stderr)
     started = time.perf_counter()
-    model = StaticModel.from_pretrained(_DEFAULT_MODEL_NAME)
     print(f"Loaded in {(time.perf_counter() - started) * 1000:.0f}ms", file=sys.stderr)
     print(file=sys.stderr)
 
-    results = _bench(grouped_tasks(tasks), repo_specs, model, modes, verbose=args.verbose)
+    results = _bench(grouped_tasks(tasks), repo_specs, verbose=args.verbose)
 
     if not results:
         return
 
+    modes = sorted(_MODE_PARAMS)
     print(file=sys.stderr)
     for mode in modes:
         mode_results = [r for r in results if r.mode == mode]

benchmarks/baselines/coderankembed.py

@@ -63,7 +63,6 @@ class RepoResult:
 def _evaluate(
     index: SembleIndex,
     tasks: list[Task],
-    mode: str,
     *,
     verbose: bool = False,
 ) -> tuple[float, float, list[float], dict[str, float]]:
@@ -78,7 +77,7 @@ def _evaluate(
         results: list[SearchResult] = []
         for _ in range(_LATENCY_RUNS):
             started = time.perf_counter()
-            results = index.search(task.query, top_k=_TOP_K, mode=mode)
+            results = index.search(task.query, top_k=_TOP_K)
             query_latencies.append((time.perf_counter() - started) * 1000)
         latencies.append(float(np.median(query_latencies)))
 
@@ -176,12 +175,12 @@ def _bench(
             print(f"\n--- {repo} ---", file=sys.stderr)
 
         started = time.perf_counter()
-        index = SembleIndex.from_path(spec.benchmark_dir, model=model)
+        index = SembleIndex.from_path(spec.benchmark_dir)
         index_ms = (time.perf_counter() - started) * 1000
 
         repo_results: list[RepoResult] = []
         for mode in modes:
-            ndcg5, ndcg10, latencies, by_category = _evaluate(index, tasks, mode, verbose=verbose)
+            ndcg5, ndcg10, latencies, by_category = _evaluate(index, tasks, verbose=verbose)
             p50, p90 = np.percentile(latencies, [50, 90]).tolist()
             result = RepoResult(
                 repo=repo,