1use crate::errors::AppError;
34use serde::Deserialize;
35use std::process::Stdio;
36use std::sync::Arc;
37use tokio::io::AsyncWriteExt;
38use tokio::process::Command;
39
40const DEFAULT_EMBED_TIMEOUT_SECS: u64 = 300;
44
45fn embed_timeout() -> std::time::Duration {
46 let secs = std::env::var("SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS")
47 .ok()
48 .and_then(|v| v.parse::<u64>().ok())
49 .filter(|&n| (10..=3_600).contains(&n))
50 .unwrap_or(DEFAULT_EMBED_TIMEOUT_SECS);
51 std::time::Duration::from_secs(secs)
52}
53
54fn build_single_schema(dim: usize) -> String {
56 format!(
57 r#"{{"type":"object","properties":{{"embedding":{{"type":"array","items":{{"type":"number"}},"minItems":{dim},"maxItems":{dim}}}}},"required":["embedding"],"additionalProperties":false}}"#
58 )
59}
60
61fn build_batch_schema(dim: usize) -> String {
65 format!(
66 r#"{{"type":"object","properties":{{"items":{{"type":"array","items":{{"type":"object","properties":{{"i":{{"type":"integer"}},"v":{{"type":"array","items":{{"type":"number"}},"minItems":{dim},"maxItems":{dim}}}}},"required":["i","v"],"additionalProperties":false}}}}}},"required":["items"],"additionalProperties":false}}"#
67 )
68}
69
70#[derive(Clone, Debug)]
71pub struct LlmEmbedding {
72 flavour: EmbeddingFlavour,
74 binary: std::path::PathBuf,
76 model: String,
78 codex_schemas: Arc<parking_lot::Mutex<CodexSchemaFiles>>,
82}
83
84#[derive(Debug, Default)]
85struct CodexSchemaFiles {
86 single: Option<(usize, Arc<tempfile::NamedTempFile>)>,
87 batch: Option<(usize, Arc<tempfile::NamedTempFile>)>,
88}
89
90#[derive(Clone, Copy, Debug, PartialEq, Eq, Deserialize)]
91pub enum EmbeddingFlavour {
92 Claude,
93 Codex,
94}
95
96impl EmbeddingFlavour {
97 pub fn as_str(self) -> &'static str {
98 match self {
99 Self::Claude => "claude",
100 Self::Codex => "codex",
101 }
102 }
103}
104
105#[derive(Debug, Deserialize)]
106struct EmbeddingResponse {
107 embedding: Vec<f32>,
108}
109
110#[derive(Debug, Deserialize)]
111struct BatchEmbeddingResponse {
112 items: Vec<BatchEmbeddingItem>,
113}
114
115#[derive(Debug, Deserialize)]
116struct BatchEmbeddingItem {
117 i: usize,
118 v: Vec<f32>,
119}
120
121pub fn resolve_real_binary(path: &std::path::Path) -> std::path::PathBuf {
125 if let Ok(canonical) = std::fs::canonicalize(path) {
126 if is_elf_binary(&canonical) {
127 return canonical;
128 }
129 if let Some(exec_target) = extract_exec_target_from_shim(&canonical) {
130 if exec_target.exists() && is_elf_binary(&exec_target) {
131 return exec_target;
132 }
133 }
134 return canonical;
135 }
136 path.to_path_buf()
137}
138
139fn is_elf_binary(path: &std::path::Path) -> bool {
140 std::fs::read(path)
141 .map(|bytes| bytes.len() >= 4 && bytes[..4] == [0x7f, b'E', b'L', b'F'])
142 .unwrap_or(false)
143}
144
145fn extract_exec_target_from_shim(path: &std::path::Path) -> Option<std::path::PathBuf> {
146 let content = std::fs::read_to_string(path).ok()?;
147 if !content.starts_with("#!") {
148 return None;
149 }
150 for line in content.lines().rev() {
151 let trimmed = line.trim();
152 if trimmed.starts_with("exec ") {
153 let after_exec = trimmed.strip_prefix("exec ")?;
154 let binary = after_exec.split_whitespace().next()?;
155 return Some(std::path::PathBuf::from(binary));
156 }
157 }
158 None
159}
160
161fn claude_embed_model() -> String {
164 std::env::var("SQLITE_GRAPHRAG_CLAUDE_EMBED_MODEL")
165 .unwrap_or_else(|_| "claude-sonnet-4-6".to_string())
166}
167
168fn codex_embed_model() -> String {
169 std::env::var("SQLITE_GRAPHRAG_CODEX_EMBED_MODEL").unwrap_or_else(|_| "gpt-5.5".to_string())
170}
171
172impl LlmEmbedding {
173 pub fn detect_available() -> Result<Self, AppError> {
185 Self::oauth_only_enforce()?;
186
187 if let Ok(path) = which::which("codex") {
188 return Ok(Self {
189 flavour: EmbeddingFlavour::Codex,
190 binary: resolve_real_binary(&path),
191 model: codex_embed_model(),
192 codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
193 });
194 }
195 if let Ok(path) = which::which("claude") {
196 return Ok(Self {
197 flavour: EmbeddingFlavour::Claude,
198 binary: resolve_real_binary(&path),
199 model: claude_embed_model(),
200 codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
201 });
202 }
203 Err(AppError::Embedding(
204 "no LLM CLI found on PATH: install `codex` (0.130+) or `claude` (Claude Code 2.1+)"
205 .to_string(),
206 ))
207 }
208
209 pub fn with_codex() -> Result<Self, AppError> {
210 Self::oauth_only_enforce()?;
211 let path = which::which("codex")
212 .map_err(|_| AppError::Embedding("`codex` not found on PATH".to_string()))?;
213 Ok(Self {
214 flavour: EmbeddingFlavour::Codex,
215 binary: resolve_real_binary(&path),
216 model: codex_embed_model(),
217 codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
218 })
219 }
220
221 pub fn with_claude() -> Result<Self, AppError> {
222 Self::oauth_only_enforce()?;
223 let path = which::which("claude")
224 .map_err(|_| AppError::Embedding("`claude` not found on PATH".to_string()))?;
225 Ok(Self {
226 flavour: EmbeddingFlavour::Claude,
227 binary: resolve_real_binary(&path),
228 model: claude_embed_model(),
229 codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
230 })
231 }
232
233 fn oauth_only_enforce() -> Result<(), AppError> {
238 if std::env::var("ANTHROPIC_API_KEY").is_ok() {
239 return Err(AppError::Validation(
240 "ANTHROPIC_API_KEY is set; v1.0.76 requires OAuth. \
241 unset it and use `claude login` instead."
242 .into(),
243 ));
244 }
245 if std::env::var("OPENAI_API_KEY").is_ok() {
246 return Err(AppError::Validation(
247 "OPENAI_API_KEY is set; v1.0.76 requires OAuth. \
248 unset it and use `codex login` instead."
249 .into(),
250 ));
251 }
252 Ok(())
253 }
254
255 pub fn embed_passage(&self, text: &str) -> Result<Vec<f32>, AppError> {
258 self.invoke_with_prefix(crate::constants::PASSAGE_PREFIX, text)
259 }
260
261 pub fn embed_query(&self, text: &str) -> Result<Vec<f32>, AppError> {
264 self.invoke_with_prefix(crate::constants::QUERY_PREFIX, text)
265 }
266
267 pub async fn embed_batch_async(
277 &self,
278 prefix: &str,
279 batch: &[(usize, String)],
280 ) -> Result<Vec<(usize, Vec<f32>)>, AppError> {
281 let dim = crate::constants::embedding_dim();
282 if batch.is_empty() {
283 return Ok(Vec::new());
284 }
285 if batch.len() == 1 {
286 let (idx, text) = (&batch[0].0, &batch[0].1);
287 let v = self.invoke_single_async(prefix, text, dim).await?;
288 return Ok(vec![(*idx, v)]);
289 }
290
291 let mut prompt = format!(
292 "Generate {dim}-dimensional semantic embedding vectors for each numbered text below.\n\
293 Return a JSON object with an \"items\" array containing EXACTLY {n} items.\n\
294 Each item has \"i\" (the 1-based index) and \"v\" (the {dim}-float vector, values between -1 and 1).\n\n",
295 n = batch.len()
296 );
297 for (pos, (_, text)) in batch.iter().enumerate() {
298 prompt.push_str(&format!("{}: {prefix}{text}\n", pos + 1));
299 }
300
301 let stdout = match self.flavour {
302 EmbeddingFlavour::Claude => {
303 self.invoke_claude(&prompt, &build_batch_schema(dim))
304 .await?
305 }
306 EmbeddingFlavour::Codex => {
307 let schema = self.codex_schema_file(dim, true)?;
308 self.invoke_codex(&prompt, schema.path()).await?
309 }
310 };
311
312 let parsed: BatchEmbeddingResponse = parse_llm_json(&stdout).map_err(|e| {
313 AppError::Embedding(format!(
314 "LLM batch embedding response parse failed: {e}; raw={stdout}"
315 ))
316 })?;
317 if parsed.items.len() != batch.len() {
318 return Err(AppError::Embedding(format!(
319 "LLM batch returned {} items, expected {} (G42/S2 coverage check)",
320 parsed.items.len(),
321 batch.len()
322 )));
323 }
324 let mut out: Vec<Option<Vec<f32>>> = vec![None; batch.len()];
325 for item in parsed.items {
326 if item.i == 0 || item.i > batch.len() {
327 return Err(AppError::Embedding(format!(
328 "LLM batch item index {} out of range 1..={}",
329 item.i,
330 batch.len()
331 )));
332 }
333 if item.v.len() != dim {
334 return Err(AppError::Embedding(format!(
335 "LLM batch item {} returned {} dims, expected {dim}; \
336 refusing to truncate or pad silently (G42/C5)",
337 item.i,
338 item.v.len()
339 )));
340 }
341 out[item.i - 1] = Some(item.v);
342 }
343 let mut result = Vec::with_capacity(batch.len());
344 for (pos, slot) in out.into_iter().enumerate() {
345 let v = slot.ok_or_else(|| {
346 AppError::Embedding(format!(
347 "LLM batch response is missing item index {} (G42/S2 coverage check)",
348 pos + 1
349 ))
350 })?;
351 result.push((batch[pos].0, v));
352 }
353 Ok(result)
354 }
355
356 fn invoke_with_prefix(&self, prefix: &str, text: &str) -> Result<Vec<f32>, AppError> {
357 let dim = crate::constants::embedding_dim();
358 let inner = self.invoke_single_async(prefix, text, dim);
359 match tokio::runtime::Handle::try_current() {
364 Ok(handle) => tokio::task::block_in_place(|| handle.block_on(inner)),
365 Err(_) => crate::embedder::shared_runtime()?.block_on(inner),
366 }
367 }
368
369 async fn invoke_single_async(
370 &self,
371 prefix: &str,
372 text: &str,
373 dim: usize,
374 ) -> Result<Vec<f32>, AppError> {
375 let prompt = format!("{prefix}{text}");
376 let stdout = match self.flavour {
377 EmbeddingFlavour::Claude => {
378 self.invoke_claude(&prompt, &build_single_schema(dim))
379 .await?
380 }
381 EmbeddingFlavour::Codex => {
382 let schema = self.codex_schema_file(dim, false)?;
383 self.invoke_codex(&prompt, schema.path()).await?
384 }
385 };
386 let parsed: EmbeddingResponse = parse_llm_json(&stdout).map_err(|e| {
387 AppError::Embedding(format!(
388 "LLM embedding response parse failed: {e}; raw={stdout}"
389 ))
390 })?;
391 if parsed.embedding.len() != dim {
392 return Err(AppError::Embedding(format!(
393 "LLM returned {} dims, expected {dim}; \
394 refusing to truncate or pad silently (G42/C5)",
395 parsed.embedding.len()
396 )));
397 }
398 Ok(parsed.embedding)
399 }
400
401 fn codex_schema_file(
406 &self,
407 dim: usize,
408 batch: bool,
409 ) -> Result<Arc<tempfile::NamedTempFile>, AppError> {
410 let mut guard = self.codex_schemas.lock();
411 let slot = if batch {
412 &mut guard.batch
413 } else {
414 &mut guard.single
415 };
416 if let Some((cached_dim, file)) = slot {
417 if *cached_dim == dim {
418 return Ok(Arc::clone(file));
419 }
420 }
421 let content = if batch {
422 build_batch_schema(dim)
423 } else {
424 build_single_schema(dim)
425 };
426 let file = tempfile::Builder::new()
427 .prefix("sqlite-graphrag-embed-schema-")
428 .suffix(".json")
429 .tempfile()
430 .map_err(|e| AppError::Embedding(format!("schema tempfile create failed: {e}")))?;
431 std::fs::write(file.path(), content)
432 .map_err(|e| AppError::Embedding(format!("schema tempfile write failed: {e}")))?;
433 let file = Arc::new(file);
434 *slot = Some((dim, Arc::clone(&file)));
435 Ok(file)
436 }
437
438 async fn invoke_claude(&self, prompt: &str, schema: &str) -> Result<String, AppError> {
439 let mut cmd = Command::new(&self.binary);
452 cmd.arg("-p")
453 .arg(prompt)
454 .arg("--model")
455 .arg(&self.model)
456 .arg("--json-schema")
457 .arg(schema)
458 .arg("--output-format")
459 .arg("json")
460 .arg("--strict-mcp-config")
461 .arg("--mcp-config")
462 .arg(r#"{"mcpServers":{}}"#)
463 .arg("--settings")
464 .arg(r#"{"hooks":{}}"#)
465 .arg("--dangerously-skip-permissions")
466 .env_clear()
467 .env("PATH", std::env::var("PATH").unwrap_or_default())
468 .env("HOME", std::env::var("HOME").unwrap_or_default())
469 .stdin(Stdio::null())
470 .stdout(Stdio::piped())
471 .stderr(Stdio::piped())
472 .kill_on_drop(true);
474 if let Some(config_dir) = claude_embedding_config_dir() {
475 cmd.env("CLAUDE_CONFIG_DIR", &config_dir);
476 }
477 let output = tokio::time::timeout(embed_timeout(), cmd.output())
478 .await
479 .map_err(|_| {
480 AppError::Embedding(format!(
481 "claude embedding call timed out after {}s \
482 (override via SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS)",
483 embed_timeout().as_secs()
484 ))
485 })?
486 .map_err(|e| AppError::Embedding(format!("claude spawn failed: {e}")))?;
487 if !output.status.success() {
488 return Err(AppError::Embedding(format!(
489 "claude exited with {}: stderr={}",
490 output.status,
491 String::from_utf8_lossy(&output.stderr)
492 )));
493 }
494 Ok(String::from_utf8_lossy(&output.stdout).into_owned())
495 }
496
497 async fn invoke_codex(
498 &self,
499 prompt: &str,
500 schema_path: &std::path::Path,
501 ) -> Result<String, AppError> {
502 let mut child = build_codex_embedding_command(&self.binary, &self.model, schema_path)
503 .spawn()
504 .map_err(|e| AppError::Embedding(format!("codex spawn failed: {e}")))?;
505 if let Some(mut stdin) = child.stdin.take() {
506 stdin
507 .write_all(prompt.as_bytes())
508 .await
509 .map_err(|e| AppError::Embedding(format!("codex stdin write failed: {e}")))?;
510 }
511 let output = tokio::time::timeout(embed_timeout(), child.wait_with_output())
512 .await
513 .map_err(|_| {
514 AppError::Embedding(format!(
515 "codex embedding call timed out after {}s \
516 (override via SQLITE_GRAPHRAG_EMBED_TIMEOUT_SECS)",
517 embed_timeout().as_secs()
518 ))
519 })?
520 .map_err(|e| AppError::Embedding(format!("codex wait failed: {e}")))?;
521 if !output.status.success() {
522 let stderr = String::from_utf8_lossy(&output.stderr);
523 if stderr.contains("request_user_input") {
527 return Err(AppError::Embedding(format!(
528 "codex requested interactive input in a headless embedding call \
529 (exit {}). This codex build ignores the non-interactive flags; \
530 upgrade codex (>= 0.134) or switch the embedding backend to \
531 claude by removing `codex` from PATH or installing `claude`. \
532 stderr={stderr}",
533 output.status
534 )));
535 }
536 return Err(AppError::Embedding(format!(
537 "codex exited with {}: stderr={stderr}",
538 output.status
539 )));
540 }
541 Ok(String::from_utf8_lossy(&output.stdout).into_owned())
542 }
543}
544
545fn claude_embedding_config_dir() -> Option<std::path::PathBuf> {
559 if let Ok(dir) = std::env::var("SQLITE_GRAPHRAG_CLAUDE_EMPTY_CONFIG_DIR") {
560 let path = std::path::PathBuf::from(dir);
561 if path.is_dir() {
562 return Some(path);
563 }
564 tracing::warn!(
565 target: "embedding",
566 path = %path.display(),
567 "SQLITE_GRAPHRAG_CLAUDE_EMPTY_CONFIG_DIR is set but not a directory; \
568 falling back to the managed empty config dir"
569 );
570 }
571 let home = std::env::var("HOME").ok()?;
572 let dir = std::path::Path::new(&home)
573 .join(".local/state/sqlite-graphrag")
574 .join("claude-empty-config");
575 if std::fs::create_dir_all(&dir).is_err() {
576 return None;
577 }
578 #[cfg(unix)]
579 {
580 use std::os::unix::fs::PermissionsExt;
581 let _ = std::fs::set_permissions(&dir, std::fs::Permissions::from_mode(0o700));
582 }
583 let creds = std::path::Path::new(&home).join(".claude/.credentials.json");
586 if creds.exists() {
587 let target = dir.join(".credentials.json");
588 if !target.exists() {
589 let _ = std::fs::copy(&creds, &target);
590 }
591 }
592 Some(dir)
593}
594
595fn build_codex_embedding_command(
596 binary: &std::path::Path,
597 model: &str,
598 schema_path: &std::path::Path,
599) -> Command {
600 let mut cmd = Command::new(binary);
601 cmd.arg("exec")
605 .arg("-c")
606 .arg("sandbox_mode='read-only'")
607 .arg("-c")
608 .arg("approval_policy='never'")
609 .arg("--json")
610 .arg("--output-schema")
611 .arg(schema_path)
612 .arg("--ephemeral")
613 .arg("--skip-git-repo-check")
614 .arg("--sandbox")
615 .arg("read-only")
616 .arg("--ignore-user-config")
617 .arg("--ignore-rules");
618 if crate::extract::codex_compat::codex_supports_ask_for_approval() {
619 cmd.arg("--ask-for-approval").arg("never");
620 }
621 let codex_home = prepare_isolated_codex_home();
624 cmd.arg("--model")
625 .arg(model)
626 .arg("-")
627 .env_clear()
628 .env("PATH", std::env::var("PATH").unwrap_or_default())
629 .env("HOME", std::env::var("HOME").unwrap_or_default());
630 if let Some(ref ch) = codex_home {
631 cmd.env("CODEX_HOME", ch);
632 }
633 cmd.stdin(Stdio::piped())
634 .stdout(Stdio::piped())
635 .stderr(Stdio::piped())
636 .kill_on_drop(true);
638 cmd
639}
640
641fn prepare_isolated_codex_home() -> Option<std::path::PathBuf> {
642 let home = std::env::var("HOME").ok()?;
643 let real_auth = std::path::Path::new(&home).join(".codex/auth.json");
644 if !real_auth.exists() {
645 return None;
646 }
647 let base = std::path::Path::new(&home).join(".local/share/sqlite-graphrag");
648 let isolated = base.join(format!("codex-home-{}", std::process::id()));
649 let _ = std::fs::create_dir_all(&isolated);
650 let target = isolated.join("auth.json");
651 if !target.exists() {
652 let _ = std::fs::copy(&real_auth, &target);
653 }
654 Some(isolated)
655}
656
657fn parse_llm_json<T: serde::de::DeserializeOwned>(stdout: &str) -> Result<T, String> {
666 if let Ok(parsed) = serde_json::from_str::<T>(stdout) {
668 return Ok(parsed);
669 }
670 let mut last_agent_text: Option<String> = None;
673 for line in stdout.lines() {
674 let line = line.trim();
675 if line.is_empty() {
676 continue;
677 }
678 let Ok(event) = serde_json::from_str::<serde_json::Value>(line) else {
679 continue;
680 };
681 if event.get("type").and_then(|t| t.as_str()) != Some("item.completed") {
682 continue;
683 }
684 let item = match event.get("item") {
685 Some(i) => i,
686 None => continue,
687 };
688 if item.get("type").and_then(|t| t.as_str()) != Some("agent_message") {
689 continue;
690 }
691 if let Some(text) = item.get("text").and_then(|t| t.as_str()) {
692 last_agent_text = Some(text.to_string());
693 }
694 }
695 let text = last_agent_text
696 .ok_or_else(|| "no agent_message found in codex JSONL output".to_string())?;
697 serde_json::from_str::<T>(&text)
698 .map_err(|e| format!("codex agent_message text does not match schema: {e}; raw={text}"))
699}
700
701#[cfg(test)]
702mod tests {
703 use super::*;
704
705 fn test_client(flavour: EmbeddingFlavour, binary: std::path::PathBuf) -> LlmEmbedding {
706 LlmEmbedding {
707 flavour,
708 binary,
709 model: "gpt-5.4".to_string(),
710 codex_schemas: Arc::new(parking_lot::Mutex::new(CodexSchemaFiles::default())),
711 }
712 }
713
714 #[test]
715 #[serial_test::serial(env)]
716 fn oauth_only_enforce_blocks_api_keys() {
717 unsafe {
720 std::env::set_var("ANTHROPIC_API_KEY", "test");
721 assert!(LlmEmbedding::oauth_only_enforce().is_err());
722 std::env::remove_var("ANTHROPIC_API_KEY");
723
724 std::env::set_var("OPENAI_API_KEY", "test");
725 assert!(LlmEmbedding::oauth_only_enforce().is_err());
726 std::env::remove_var("OPENAI_API_KEY");
727 }
728 assert!(LlmEmbedding::oauth_only_enforce().is_ok());
729 }
730
731 #[test]
732 fn flavour_as_str_is_stable() {
733 assert_eq!(EmbeddingFlavour::Claude.as_str(), "claude");
734 assert_eq!(EmbeddingFlavour::Codex.as_str(), "codex");
735 }
736
737 #[test]
738 fn single_schema_embeds_active_dim() {
739 let schema = build_single_schema(64);
740 assert!(schema.contains(r#""minItems":64"#));
741 assert!(schema.contains(r#""maxItems":64"#));
742 let parsed: serde_json::Value =
743 serde_json::from_str(&schema).expect("single schema must be valid JSON");
744 assert_eq!(parsed["properties"]["embedding"]["minItems"], 64);
745 }
746
747 #[test]
748 fn batch_schema_is_valid_json_and_unbounded_items() {
749 let schema = build_batch_schema(64);
750 let parsed: serde_json::Value =
751 serde_json::from_str(&schema).expect("batch schema must be valid JSON");
752 assert!(parsed["properties"]["items"].get("minItems").is_none());
755 assert_eq!(
756 parsed["properties"]["items"]["items"]["properties"]["v"]["minItems"],
757 64
758 );
759 }
760
761 #[test]
762 fn parse_llm_json_accepts_claude_json() {
763 let stdout = r#"{"embedding":[0.0,1.0,2.0]}"#;
764
765 let parsed: EmbeddingResponse = parse_llm_json(stdout).expect("claude JSON must parse");
766
767 assert_eq!(parsed.embedding, vec![0.0, 1.0, 2.0]);
768 }
769
770 #[test]
771 fn parse_llm_json_accepts_codex_jsonl() {
772 let stdout = r#"{"type":"thread.started","thread_id":"mock-thread-0"}
773{"type":"item.completed","item":{"type":"agent_message","text":"{\"embedding\":[0.0,1.0,2.0]}"}}
774{"type":"turn.completed","usage":{"input_tokens":1,"output_tokens":1}}"#;
775
776 let parsed: EmbeddingResponse = parse_llm_json(stdout).expect("codex JSONL must parse");
777
778 assert_eq!(parsed.embedding, vec![0.0, 1.0, 2.0]);
779 }
780
781 #[test]
782 fn parse_llm_json_rejects_jsonl_without_agent_message() {
783 let stdout = r#"{"type":"thread.started","thread_id":"mock-thread-0"}"#;
784
785 let err = parse_llm_json::<EmbeddingResponse>(stdout)
786 .expect_err("missing agent_message must fail");
787
788 assert!(err.contains("no agent_message"));
789 }
790
791 #[test]
792 fn parse_llm_json_accepts_batch_response() {
793 let stdout = r#"{"items":[{"i":1,"v":[0.0,1.0]},{"i":2,"v":[2.0,3.0]}]}"#;
794
795 let parsed: BatchEmbeddingResponse = parse_llm_json(stdout).expect("batch JSON must parse");
796
797 assert_eq!(parsed.items.len(), 2);
798 assert_eq!(parsed.items[0].i, 1);
799 assert_eq!(parsed.items[1].v, vec![2.0, 3.0]);
800 }
801
802 #[test]
803 fn codex_schema_file_is_created_once_and_reused() {
804 let client = test_client(
805 EmbeddingFlavour::Codex,
806 std::path::PathBuf::from("/bin/true"),
807 );
808 let first = client
809 .codex_schema_file(64, false)
810 .expect("schema file must be created");
811 let second = client
812 .codex_schema_file(64, false)
813 .expect("schema file must be reused");
814 assert_eq!(first.path(), second.path(), "same dim must reuse the file");
815
816 let batch = client
817 .codex_schema_file(64, true)
818 .expect("batch schema file must be created");
819 assert_ne!(
820 first.path(),
821 batch.path(),
822 "single and batch schemas are distinct files"
823 );
824
825 let content = std::fs::read_to_string(first.path()).expect("schema file must be readable");
826 assert!(content.contains(r#""minItems":64"#));
827 }
828
829 #[test]
830 fn codex_embedding_command_reads_prompt_from_stdin() {
831 let schema_path = std::env::temp_dir().join("sqlite-graphrag-embed-schema-test.json");
832 let cmd = build_codex_embedding_command(
833 std::path::Path::new("/bin/true"),
834 "gpt-5.4",
835 &schema_path,
836 );
837 let argv: Vec<String> = cmd
838 .as_std()
839 .get_args()
840 .filter_map(|arg| arg.to_str().map(|s| s.to_string()))
841 .collect();
842
843 assert!(
844 argv.iter().any(|arg| arg == "-"),
845 "codex embedding command must read prompt from stdin: {argv:?}"
846 );
847 assert!(
848 !argv.iter().any(|arg| arg.starts_with("passage: ")),
849 "prompt text must not be passed as argv: {argv:?}"
850 );
851 for required in &[
852 "exec",
853 "-c",
854 "sandbox_mode='read-only'",
855 "approval_policy='never'",
856 "--json",
857 "--output-schema",
858 "--ephemeral",
859 "--skip-git-repo-check",
860 "--sandbox",
861 "read-only",
862 "--ignore-user-config",
863 "--ignore-rules",
864 "--model",
865 "gpt-5.4",
866 ] {
867 assert!(
868 argv.iter().any(|arg| arg == required),
869 "missing flag {required} in {argv:?}"
870 );
871 }
872 }
873
874 #[cfg(unix)]
875 #[test]
876 #[serial_test::serial(env)]
877 fn embed_passage_sends_prompt_to_codex_stdin() {
878 use std::os::unix::fs::PermissionsExt;
879
880 unsafe {
884 std::env::set_var("SQLITE_GRAPHRAG_EMBEDDING_DIM", "64");
885 }
886
887 let temp = tempfile::tempdir().expect("tempdir must exist");
888 let binary = temp.path().join("codex-stdin-check");
889 let script = r#"#!/usr/bin/env bash
890set -euo pipefail
891
892prompt="$(cat)"
893if [[ "$prompt" != "passage: codex-cli" ]]; then
894 echo "unexpected stdin: $prompt" >&2
895 exit 41
896fi
897
898vals="0.0"
899for _ in $(seq 2 64); do
900 vals="$vals,0.0"
901done
902payload="{\"embedding\":[$vals]}"
903escaped="${payload//\"/\\\"}"
904echo "{\"type\":\"item.completed\",\"item\":{\"type\":\"agent_message\",\"text\":\"$escaped\"}}"
905"#;
906 std::fs::write(&binary, script).expect("mock codex script must be written");
907 let mut perms = std::fs::metadata(&binary)
908 .expect("mock codex metadata must exist")
909 .permissions();
910 perms.set_mode(0o755);
911 std::fs::set_permissions(&binary, perms).expect("mock codex must be executable");
912
913 let embedding = test_client(EmbeddingFlavour::Codex, binary);
914
915 let vector = embedding
916 .embed_passage("codex-cli")
917 .expect("stdin-backed codex embedding must succeed");
918
919 unsafe {
921 std::env::remove_var("SQLITE_GRAPHRAG_EMBEDDING_DIM");
922 }
923
924 assert_eq!(vector.len(), 64);
925 assert!(vector.iter().all(|value| *value == 0.0));
926 }
927}