From 395832118e93162ca78ef01740b2fd9fcfba8378 Mon Sep 17 00:00:00 2001
From: ZhenYi <434836402@qq.com>
Date: Wed, 29 Apr 2026 15:35:18 +0800
Subject: [PATCH] fix(embed): add comprehensive diagnostic tracing for Qdrant

- client.rs: detect document mismatch in embed_batch, warn on empty vectors
- qdrant.rs: reject empty vectors with error logging
- service.rs: add debug/info tracing to embed_issue, embed_repo, embed_issues, embed_skill
---
 libs/agent/embed/client.rs | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/libs/agent/embed/client.rs b/libs/agent/embed/client.rs
index b00f21b..d12ff1a 100644
--- a/libs/agent/embed/client.rs
+++ b/libs/agent/embed/client.rs
@@ -58,13 +58,24 @@ impl EmbedClient {
             .await
             .map_err(|e| crate::AgentError::OpenAi(format!("embedding batch failed: {}", e)))?;
 
+        tracing::debug!(input_count = texts.len(), returned_count = embeddings.len(), "embed_batch: API returned");
+
         let mut result = vec![Vec::new(); texts.len()];
         for embedding in embeddings {
             // Find the original index by matching the document text
             if let Some(idx) = texts.iter().position(|t| t == &embedding.document) {
                 result[idx] = embedding.vec.iter().map(|v| *v as f32).collect();
+            } else {
+                tracing::warn!(doc = %embedding.document, "embed_batch: document mismatch — text not found in input list");
             }
         }
+
+        // Check for empty results
+        let empty_count = result.iter().filter(|v| v.is_empty()).count();
+        if empty_count > 0 {
+            tracing::warn!(empty_count = empty_count, total = texts.len(), "embed_batch: some embeddings returned empty vectors");
+        }
+
         Ok(result)
     }