fix(avatar): batch knowledge embedding requests

digital-avatar-app/backend/embeddings.py

@@ -51,7 +51,14 @@ def embed(texts):
     if api_url:
         api_key = os.getenv("EMBEDDING_API_KEY", "")
         model = os.getenv("EMBEDDING_MODEL", "text-embedding-3-small")
-        payload = json.dumps({"input": texts, "model": model}).encode("utf-8")
+        try:
+            batch_size = max(1, int(os.getenv("EMBEDDING_BATCH_SIZE", "10")))
+        except ValueError:
+            batch_size = 10
+        embeddings = []
+        for start in range(0, len(texts), batch_size):
+            batch = texts[start:start + batch_size]
+            payload = json.dumps({"input": batch, "model": model}).encode("utf-8")
             req = urllib.request.Request(
                 api_url,
                 data=payload,
@@ -66,7 +73,10 @@ def embed(texts):
             items = data["data"]
             if items and "index" in items[0]:
                 items = sorted(items, key=lambda x: x["index"])
-        return [item["embedding"] for item in items]
+            if len(items) != len(batch):
+                raise ValueError("embedding response count does not match request")
+            embeddings.extend(item["embedding"] for item in items)
+        return embeddings
     return _hash_embedding(texts)
 
 

digital-avatar-app/backend/tests/test_embeddings.py

@@ -1,10 +1,26 @@
+import json
 import os
 import tempfile
 import unittest
+from unittest.mock import patch
 
 import embeddings
 
 
+class FakeResponse:
+    def __init__(self, payload):
+        self.payload = payload
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *_):
+        return None
+
+    def read(self):
+        return json.dumps(self.payload).encode("utf-8")
+
+
 class TextExtractionTests(unittest.TestCase):
     def write_text(self, suffix, content):
         handle = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
@@ -28,5 +44,33 @@ class TextExtractionTests(unittest.TestCase):
             embeddings.extract_text(path, ".csv")
 
 
+class RemoteEmbeddingTests(unittest.TestCase):
+    def test_large_input_is_split_into_provider_safe_batches(self):
+        texts = [f"chunk-{index}" for index in range(14)]
+        batch_sizes = []
+
+        def fake_urlopen(request, timeout):
+            self.assertEqual(timeout, 30)
+            payload = json.loads(request.data.decode("utf-8"))
+            batch_sizes.append(len(payload["input"]))
+            return FakeResponse({
+                "data": [
+                    {"index": index, "embedding": [float(text.split("-")[1])]}
+                    for index, text in enumerate(payload["input"])
+                ]
+            })
+
+        with patch.dict(os.environ, {
+            "EMBEDDING_API_URL": "https://embedding.example/v1/embeddings",
+            "EMBEDDING_API_KEY": "test-key",
+            "EMBEDDING_MODEL": "text-embedding-v4",
+            "EMBEDDING_BATCH_SIZE": "10",
+        }), patch("embeddings.urllib.request.urlopen", side_effect=fake_urlopen):
+            result = embeddings.embed(texts)
+
+        self.assertEqual(batch_sizes, [10, 4])
+        self.assertEqual(result, [[float(index)] for index in range(14)])
+
+
 if __name__ == "__main__":
     unittest.main()