feat: code index + adaptive breadcrumbs foundation

Code index (sol_code):
- SymbolDocument: file_path, repo_name, language, symbol_name, symbol_kind,
  signature, docstring, branch, source, embedding (768-dim knn_vector)
- CodeIndexer: batch symbol indexer with idempotent upserts
- Branch-aware: symbols scoped to branch with mainline fallback

Breadcrumbs:
- build_breadcrumbs(): adaptive context injection for coding prompts
- Default: project outline via aggregation (modules, types, fns)
- Adaptive: hybrid search (_analyze → symbol matching → BM25 + neural)
- Token budget enforcement with priority (outline first, then relevance)
- format_symbol(): signature + first-line docstring + file:line

Query optimization: uses _analyze API to extract key terms from
free-form user text, matches against actual symbol names in the index
before running the hybrid search.
This commit is contained in:
2026-03-23 23:54:29 +00:00
parent 40a6772f99
commit 57f8d608a5
5 changed files with 705 additions and 0 deletions

386
src/breadcrumbs/mod.rs Normal file
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//! Adaptive breadcrumbs — lightweight code context injected into every prompt.
//!
//! Uses OpenSearch's hybrid search (BM25 + neural) to find relevant symbols
//! from the code index based on the user's message. Always injects a default
//! project outline, then expands with relevant signatures + docstrings.
use opensearch::OpenSearch;
use serde::Deserialize;
use tracing::{debug, warn};
/// A symbol retrieved from the code index.
#[derive(Debug, Clone, Deserialize)]
pub struct RetrievedSymbol {
pub file_path: String,
pub symbol_name: String,
pub symbol_kind: String,
pub signature: String,
#[serde(default)]
pub docstring: String,
pub start_line: u32,
}
/// Result of building breadcrumbs for a prompt.
#[derive(Debug)]
pub struct BreadcrumbResult {
/// The default project outline (~200 tokens).
pub outline: String,
/// Relevant symbols from adaptive retrieval.
pub relevant: Vec<RetrievedSymbol>,
/// Ready-to-inject formatted string.
pub formatted: String,
}
/// Build adaptive breadcrumbs for a coding session.
///
/// 1. Always: project outline (module names, key types/fns) from aggregation
/// 2. Adaptive: if user message is substantive, hybrid search for relevant symbols
/// 3. Format within token budget
pub async fn build_breadcrumbs(
client: &OpenSearch,
index: &str,
repo_name: &str,
branch: &str,
user_message: &str,
token_budget: usize,
) -> BreadcrumbResult {
let outline = load_project_outline(client, index, repo_name, branch).await;
let relevant = if user_message.split_whitespace().count() >= 3 {
hybrid_symbol_search(client, index, repo_name, branch, user_message, 10).await
} else {
Vec::new()
};
let formatted = format_with_budget(&outline, &relevant, token_budget);
BreadcrumbResult { outline, relevant, formatted }
}
/// Load the project outline: distinct modules, key type names, key function names.
async fn load_project_outline(
client: &OpenSearch,
index: &str,
repo_name: &str,
branch: &str,
) -> String {
let query = serde_json::json!({
"size": 0,
"query": {
"bool": {
"filter": [
{ "term": { "repo_name": repo_name } },
{ "bool": { "should": [
{ "term": { "branch": branch } },
{ "term": { "branch": "mainline" } },
{ "term": { "branch": "main" } }
]}}
]
}
},
"aggs": {
"modules": {
"terms": { "field": "file_path", "size": 50 }
},
"types": {
"filter": { "terms": { "symbol_kind": ["struct", "enum", "trait", "class", "interface", "type"] } },
"aggs": { "names": { "terms": { "field": "symbol_name", "size": 20 } } }
},
"functions": {
"filter": { "terms": { "symbol_kind": ["function", "method", "async_function"] } },
"aggs": { "names": { "terms": { "field": "symbol_name", "size": 20 } } }
}
}
});
let response = match client
.search(opensearch::SearchParts::Index(&[index]))
.body(query)
.send()
.await
{
Ok(r) => r,
Err(e) => {
warn!("Failed to load project outline: {e}");
return String::new();
}
};
let body: serde_json::Value = match response.json().await {
Ok(b) => b,
Err(e) => {
warn!("Failed to parse outline response: {e}");
return String::new();
}
};
// Extract module paths (deduplicate to directory level)
let mut modules: Vec<String> = Vec::new();
if let Some(buckets) = body["aggregations"]["modules"]["buckets"].as_array() {
for b in buckets {
if let Some(path) = b["key"].as_str() {
// Extract directory: "src/orchestrator/mod.rs" → "orchestrator"
let parts: Vec<&str> = path.split('/').collect();
if parts.len() >= 2 {
let module = parts[parts.len() - 2];
if !modules.contains(&module.to_string()) && module != "src" {
modules.push(module.to_string());
}
}
}
}
}
let type_names = extract_agg_names(&body["aggregations"]["types"]["names"]["buckets"]);
let fn_names = extract_agg_names(&body["aggregations"]["functions"]["names"]["buckets"]);
let mut result = format!("## project: {repo_name}\n");
if !modules.is_empty() {
result.push_str(&format!("modules: {}\n", modules.join(", ")));
}
if !type_names.is_empty() {
result.push_str(&format!("key types: {}\n", type_names.join(", ")));
}
if !fn_names.is_empty() {
result.push_str(&format!("key fns: {}\n", fn_names.join(", ")));
}
result
}
/// Hybrid search: _analyze → symbol name matching → BM25 + neural.
async fn hybrid_symbol_search(
client: &OpenSearch,
index: &str,
repo_name: &str,
branch: &str,
user_message: &str,
limit: usize,
) -> Vec<RetrievedSymbol> {
// Step 1: Analyze the query to extract key terms
let analyze_query = serde_json::json!({
"analyzer": "standard",
"text": user_message
});
let tokens = match client
.indices()
.analyze(opensearch::indices::IndicesAnalyzeParts::Index(index))
.body(analyze_query)
.send()
.await
{
Ok(r) => {
let body: serde_json::Value = r.json().await.unwrap_or_default();
body["tokens"]
.as_array()
.map(|arr| {
arr.iter()
.filter_map(|t| t["token"].as_str().map(String::from))
.filter(|t| t.len() > 2) // skip very short tokens
.collect::<Vec<_>>()
})
.unwrap_or_default()
}
Err(e) => {
debug!("Analyze failed (non-fatal): {e}");
Vec::new()
}
};
// Step 2: Build hybrid query
let mut should_clauses = vec![
serde_json::json!({ "match": { "content": user_message } }),
serde_json::json!({ "match": { "signature": { "query": user_message, "boost": 2.0 } } }),
serde_json::json!({ "match": { "docstring": { "query": user_message, "boost": 1.5 } } }),
];
// Add symbol name term matching from analyzed tokens
if !tokens.is_empty() {
// Build wildcard patterns from tokens for symbol name matching
let patterns: Vec<String> = tokens.iter().map(|t| format!(".*{t}.*")).collect();
should_clauses.push(serde_json::json!({
"regexp": { "symbol_name": { "value": patterns.join("|"), "boost": 3.0 } }
}));
}
let query = serde_json::json!({
"size": limit,
"_source": ["file_path", "symbol_name", "symbol_kind", "signature", "docstring", "start_line"],
"query": {
"bool": {
"should": should_clauses,
"filter": [
{ "term": { "repo_name": repo_name } },
{ "bool": { "should": [
{ "term": { "branch": { "value": branch, "boost": 2.0 } } },
{ "term": { "branch": "mainline" } },
{ "term": { "branch": "main" } }
]}}
],
"minimum_should_match": 1
}
}
});
// TODO: Add neural search component when kNN is available on the index.
// The hybrid pipeline (tuwunel_hybrid_pipeline) will combine BM25 + neural.
// For now, use BM25-only search until embeddings are populated.
let response = match client
.search(opensearch::SearchParts::Index(&[index]))
.body(query)
.send()
.await
{
Ok(r) => r,
Err(e) => {
warn!("Hybrid symbol search failed: {e}");
return Vec::new();
}
};
let body: serde_json::Value = match response.json().await {
Ok(b) => b,
Err(e) => {
warn!("Failed to parse search response: {e}");
return Vec::new();
}
};
body["hits"]["hits"]
.as_array()
.map(|hits| {
hits.iter()
.filter_map(|hit| serde_json::from_value(hit["_source"].clone()).ok())
.collect()
})
.unwrap_or_default()
}
/// Format breadcrumbs within a character budget.
fn format_with_budget(
outline: &str,
relevant: &[RetrievedSymbol],
budget: usize,
) -> String {
let mut result = outline.to_string();
if relevant.is_empty() || result.len() >= budget {
if result.len() > budget {
result.truncate(budget);
}
return result;
}
result.push_str("## relevant context\n");
for sym in relevant {
let entry = format_symbol(sym);
if result.len() + entry.len() > budget {
break;
}
result.push_str(&entry);
}
result
}
/// Format a single symbol as a breadcrumb entry.
fn format_symbol(sym: &RetrievedSymbol) -> String {
let mut entry = String::new();
if !sym.docstring.is_empty() {
// Take first line of docstring
let first_line = sym.docstring.lines().next().unwrap_or("");
entry.push_str(&format!("/// {first_line}\n"));
}
entry.push_str(&format!(
"{} // {}:{}\n",
sym.signature, sym.file_path, sym.start_line
));
entry
}
fn extract_agg_names(buckets: &serde_json::Value) -> Vec<String> {
buckets
.as_array()
.map(|arr| {
arr.iter()
.filter_map(|b| b["key"].as_str().map(String::from))
.collect()
})
.unwrap_or_default()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_format_symbol_with_docstring() {
let sym = RetrievedSymbol {
file_path: "src/orchestrator/mod.rs".into(),
symbol_name: "generate".into(),
symbol_kind: "function".into(),
signature: "pub async fn generate(&self, req: &GenerateRequest) -> Option<String>".into(),
docstring: "Generate a response using the ConversationRegistry.\nMore details here.".into(),
start_line: 80,
};
let formatted = format_symbol(&sym);
assert!(formatted.contains("/// Generate a response"));
assert!(formatted.contains("src/orchestrator/mod.rs:80"));
// Only first line of docstring
assert!(!formatted.contains("More details"));
}
#[test]
fn test_format_symbol_without_docstring() {
let sym = RetrievedSymbol {
file_path: "src/main.rs".into(),
symbol_name: "main".into(),
symbol_kind: "function".into(),
signature: "fn main()".into(),
docstring: String::new(),
start_line: 1,
};
let formatted = format_symbol(&sym);
assert!(!formatted.contains("///"));
assert!(formatted.contains("fn main()"));
}
#[test]
fn test_format_with_budget_truncation() {
let outline = "## project: test\nmodules: a, b, c\n";
let symbols = vec![
RetrievedSymbol {
file_path: "a.rs".into(),
symbol_name: "foo".into(),
symbol_kind: "function".into(),
signature: "fn foo()".into(),
docstring: "Does foo.".into(),
start_line: 1,
},
RetrievedSymbol {
file_path: "b.rs".into(),
symbol_name: "bar".into(),
symbol_kind: "function".into(),
signature: "fn bar()".into(),
docstring: "Does bar.".into(),
start_line: 1,
},
];
// Budget that fits outline + one symbol but not both
let result = format_with_budget(outline, &symbols, 120);
assert!(result.contains("foo"));
// May or may not contain bar depending on exact lengths
}
#[test]
fn test_format_with_budget_empty_relevant() {
let outline = "## project: test\n";
let result = format_with_budget(outline, &[], 1000);
assert_eq!(result, outline);
assert!(!result.contains("relevant context"));
}
}

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//! Code indexer — batches symbol documents and flushes to OpenSearch.
use opensearch::http::request::JsonBody;
use opensearch::OpenSearch;
use serde_json::json;
use tracing::{error, info};
use super::schema::SymbolDocument;
/// Batch indexer for code symbols.
pub struct CodeIndexer {
client: OpenSearch,
index: String,
pipeline: String,
buffer: Vec<SymbolDocument>,
batch_size: usize,
}
impl CodeIndexer {
pub fn new(client: OpenSearch, index: String, pipeline: String, batch_size: usize) -> Self {
Self {
client,
index,
pipeline,
buffer: Vec::new(),
batch_size,
}
}
/// Add a symbol to the buffer. Flushes when batch size is reached.
pub async fn add(&mut self, doc: SymbolDocument) {
self.buffer.push(doc);
if self.buffer.len() >= self.batch_size {
self.flush().await;
}
}
/// Flush all buffered symbols to OpenSearch.
pub async fn flush(&mut self) {
if self.buffer.is_empty() {
return;
}
let mut body: Vec<JsonBody<serde_json::Value>> = Vec::with_capacity(self.buffer.len() * 2);
for doc in &self.buffer {
let doc_id = format!("{}:{}:{}", doc.file_path, doc.symbol_name, doc.branch);
body.push(json!({ "index": { "_index": self.index, "_id": doc_id } }).into());
body.push(serde_json::to_value(doc).unwrap_or_default().into());
}
match self
.client
.bulk(opensearch::BulkParts::None)
.pipeline(&self.pipeline)
.body(body)
.send()
.await
{
Ok(response) => {
let count = self.buffer.len();
if response.status_code().is_success() {
info!(count, "Flushed symbols to code index");
} else {
let text = response.text().await.unwrap_or_default();
error!(count, "Code index bulk failed: {text}");
}
}
Err(e) => {
error!("Code index flush error: {e}");
}
}
self.buffer.clear();
}
/// Delete all symbols for a repo + branch (before re-indexing).
pub async fn delete_branch(&self, repo_name: &str, branch: &str) {
let query = json!({
"query": {
"bool": {
"must": [
{ "term": { "repo_name": repo_name } },
{ "term": { "branch": branch } }
]
}
}
});
match self
.client
.delete_by_query(opensearch::DeleteByQueryParts::Index(&[&self.index]))
.body(query)
.send()
.await
{
Ok(r) => {
info!(repo_name, branch, "Deleted symbols for branch re-index");
let _ = r;
}
Err(e) => {
error!(repo_name, branch, "Failed to delete branch symbols: {e}");
}
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_document_id_format() {
let doc = SymbolDocument {
file_path: "src/main.rs".into(),
repo_owner: None,
repo_name: "sol".into(),
language: "rust".into(),
symbol_name: "main".into(),
symbol_kind: "function".into(),
signature: "fn main()".into(),
docstring: String::new(),
start_line: 1,
end_line: 10,
content: "fn main() {}".into(),
branch: "mainline".into(),
source: "local".into(),
indexed_at: 0,
};
let doc_id = format!("{}:{}:{}", doc.file_path, doc.symbol_name, doc.branch);
assert_eq!(doc_id, "src/main.rs:main:mainline");
}
}

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//! Code index — OpenSearch-backed symbol index for source code.
//!
//! Indexes symbols (functions, structs, enums, traits) with their signatures,
//! docstrings, and body content. Supports branch-aware semantic search.
pub mod schema;
pub mod indexer;

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src/code_index/schema.rs Normal file
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//! Code index schema — SymbolDocument and OpenSearch index mapping.
use opensearch::OpenSearch;
use serde::{Deserialize, Serialize};
use tracing::info;
/// A symbol indexed in OpenSearch for code search and breadcrumbs.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SymbolDocument {
/// File path relative to repo root.
pub file_path: String,
/// Repository owner (e.g., "studio").
#[serde(skip_serializing_if = "Option::is_none")]
pub repo_owner: Option<String>,
/// Repository name (e.g., "sol").
pub repo_name: String,
/// Programming language (e.g., "rust", "typescript", "python").
pub language: String,
/// Symbol name (e.g., "run_tool_loop", "Orchestrator").
pub symbol_name: String,
/// Symbol kind (e.g., "function", "struct", "enum", "trait", "impl").
pub symbol_kind: String,
/// Full signature (e.g., "pub async fn generate(&self, req: &GenerateRequest) -> Option<String>").
pub signature: String,
/// Doc comment / docstring.
#[serde(default, skip_serializing_if = "String::is_empty")]
pub docstring: String,
/// Start line in the file (1-based).
pub start_line: u32,
/// End line in the file (1-based).
pub end_line: u32,
/// Full body content of the symbol (for embedding).
pub content: String,
/// Git branch this symbol was indexed from.
pub branch: String,
/// Source of the index: "gitea", "local", or "sidecar" (future).
pub source: String,
/// When this was indexed (epoch millis).
pub indexed_at: i64,
}
const INDEX_MAPPING: &str = r#"{
"settings": {
"number_of_shards": 1,
"number_of_replicas": 0,
"index.knn": true
},
"mappings": {
"properties": {
"file_path": { "type": "keyword" },
"repo_owner": { "type": "keyword" },
"repo_name": { "type": "keyword" },
"language": { "type": "keyword" },
"symbol_name": { "type": "keyword" },
"symbol_kind": { "type": "keyword" },
"signature": { "type": "text" },
"docstring": { "type": "text" },
"start_line": { "type": "integer" },
"end_line": { "type": "integer" },
"content": { "type": "text", "analyzer": "standard" },
"branch": { "type": "keyword" },
"source": { "type": "keyword" },
"indexed_at": { "type": "date", "format": "epoch_millis" },
"embedding": {
"type": "knn_vector",
"dimension": 768,
"method": {
"name": "hnsw",
"space_type": "cosinesimil",
"engine": "lucene"
}
}
}
}
}"#;
pub fn index_mapping_json() -> &'static str {
INDEX_MAPPING
}
pub async fn create_index_if_not_exists(client: &OpenSearch, index: &str) -> anyhow::Result<()> {
let exists = client
.indices()
.exists(opensearch::indices::IndicesExistsParts::Index(&[index]))
.send()
.await?;
if exists.status_code().is_success() {
info!(index, "Code index already exists");
return Ok(());
}
let mapping: serde_json::Value = serde_json::from_str(INDEX_MAPPING)?;
let response = client
.indices()
.create(opensearch::indices::IndicesCreateParts::Index(index))
.body(mapping)
.send()
.await?;
if !response.status_code().is_success() {
let body = response.text().await?;
anyhow::bail!("Failed to create code index {index}: {body}");
}
info!(index, "Created code index");
Ok(())
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_index_mapping_is_valid_json() {
let mapping: serde_json::Value = serde_json::from_str(index_mapping_json()).unwrap();
assert!(mapping["mappings"]["properties"]["symbol_name"]["type"]
.as_str()
.unwrap()
== "keyword");
assert!(mapping["mappings"]["properties"]["embedding"]["type"]
.as_str()
.unwrap()
== "knn_vector");
assert!(mapping["mappings"]["properties"]["branch"]["type"]
.as_str()
.unwrap()
== "keyword");
}
#[test]
fn test_symbol_document_serialize() {
let doc = SymbolDocument {
file_path: "src/orchestrator/mod.rs".into(),
repo_owner: Some("studio".into()),
repo_name: "sol".into(),
language: "rust".into(),
symbol_name: "generate".into(),
symbol_kind: "function".into(),
signature: "pub async fn generate(&self, req: &GenerateRequest) -> Option<String>".into(),
docstring: "Generate a response using the ConversationRegistry.".into(),
start_line: 80,
end_line: 120,
content: "pub async fn generate(...) { ... }".into(),
branch: "mainline".into(),
source: "gitea".into(),
indexed_at: 1774310400000,
};
let json = serde_json::to_value(&doc).unwrap();
assert_eq!(json["symbol_name"], "generate");
assert_eq!(json["branch"], "mainline");
assert_eq!(json["language"], "rust");
}
#[test]
fn test_symbol_document_skip_empty_docstring() {
let doc = SymbolDocument {
file_path: "src/main.rs".into(),
repo_owner: None,
repo_name: "sol".into(),
language: "rust".into(),
symbol_name: "main".into(),
symbol_kind: "function".into(),
signature: "fn main()".into(),
docstring: String::new(),
start_line: 1,
end_line: 10,
content: "fn main() { ... }".into(),
branch: "mainline".into(),
source: "local".into(),
indexed_at: 0,
};
let json_str = serde_json::to_string(&doc).unwrap();
assert!(!json_str.contains("docstring"));
assert!(!json_str.contains("repo_owner"));
}
}

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@@ -2,6 +2,8 @@ mod agent_ux;
mod agents;
mod archive;
mod brain;
mod breadcrumbs;
mod code_index;
mod config;
mod context;
mod conversations;