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+"""Tests for the Embedder factories (embeddings/embedder.py).
+
+`from_callable` and `from_endpoint` are exercised with no optional
+dependencies: the endpoint factory is tested against a stdlib mock HTTP
+server. The `from_sentence_transformers` factory pulls in the optional
+`sentence-transformers` extra, so its test is skipped when that extra is not
+installed, keeping the core CI matrix fast.
+"""
+
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from pathlib import Path
+
+import numpy as np
+import pytest
+import sys
+
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))
+
+from tracer.embeddings.embedder import Embedder
+
+
+# ── from_callable ─────────────────────────────────────────────────────────────
+
+def test_from_callable_shapes_and_dtype():
+    def fn(texts):
+        return [[float(len(t)), 1.0] for t in texts]
+
+    emb = Embedder.from_callable(fn)
+    out = emb.embed(["a", "bbb"])
+    assert out.shape == (2, 2)
+    assert out.dtype == np.float32
+    np.testing.assert_allclose(out[:, 0], [1.0, 3.0])
+
+
+def test_embed_one_returns_1d():
+    emb = Embedder.from_callable(lambda texts: [[1.0, 2.0, 3.0] for _ in texts])
+    one = emb.embed_one("hello")
+    assert one.shape == (3,)
+    assert one.dtype == np.float32
+
+
+def test_from_callable_repr():
+    emb = Embedder.from_callable(lambda texts: [[0.0] for _ in texts])
+    assert "callable" in repr(emb)
+
+
+# ── from_endpoint (mock HTTP server) ───────────────────────────────────────────
+
+class _EmbedHandler(BaseHTTPRequestHandler):
+    """Echoes a deterministic embedding derived from input length.
+
+    Single mode:  {"input": "ab"}            -> {"embedding": [2.0]}
+    Batch mode:   {"inputs": ["a", "bb"]}    -> {"embeddings": [[1.0], [2.0]]}
+    """
+
+    def do_POST(self):
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length))
+        self.server.request_count += 1
+        self.server.last_auth = self.headers.get("Authorization")
+
+        if "inputs" in body:
+            payload = {"embeddings": [[float(len(t))] for t in body["inputs"]]}
+        else:
+            payload = {"embedding": [float(len(body["input"]))]}
+
+        raw = json.dumps(payload).encode()
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(raw)))
+        self.end_headers()
+        self.wfile.write(raw)
+
+    def log_message(self, *args):
+        pass
+
+
+@pytest.fixture
+def mock_endpoint():
+    httpd = HTTPServer(("127.0.0.1", 0), _EmbedHandler)
+    httpd.request_count = 0
+    httpd.last_auth = None
+    thread = threading.Thread(target=httpd.serve_forever, daemon=True)
+    thread.start()
+    port = httpd.server_address[1]
+    yield httpd, f"http://127.0.0.1:{port}"
+    httpd.shutdown()
+    thread.join(timeout=5)
+    httpd.server_close()
+
+
+def test_from_endpoint_single_mode(mock_endpoint):
+    httpd, url = mock_endpoint
+    emb = Embedder.from_endpoint(url)
+    out = emb.embed(["a", "bb", "ccc"])
+    assert out.shape == (3, 1)
+    assert out.dtype == np.float32
+    np.testing.assert_allclose(out[:, 0], [1.0, 2.0, 3.0])
+    # One HTTP request per text in single mode.
+    assert httpd.request_count == 3
+
+
+def test_from_endpoint_batch_mode(mock_endpoint):
+    httpd, url = mock_endpoint
+    emb = Embedder.from_endpoint(url, batch_key="inputs",
+                                 batch_output_key="embeddings")
+    out = emb.embed(["a", "bb"])
+    assert out.shape == (2, 1)
+    np.testing.assert_allclose(out[:, 0], [1.0, 2.0])
+    # The whole batch goes in a single request.
+    assert httpd.request_count == 1
+
+
+def test_from_endpoint_passes_headers(mock_endpoint):
+    httpd, url = mock_endpoint
+    emb = Embedder.from_endpoint(url, headers={"Authorization": "Bearer xyz"})
+    emb.embed(["a"])
+    assert httpd.last_auth == "Bearer xyz"
+
+
+def test_from_endpoint_repr(mock_endpoint):
+    _, url = mock_endpoint
+    emb = Embedder.from_endpoint(url)
+    assert "endpoint" in repr(emb)
+
+
+# ── from_sentence_transformers (optional extra) ────────────────────────────────
+
+def test_from_sentence_transformers_smoke():
+    # Skipped unless the optional `sentence-transformers` extra is installed,
+    # so the core CI matrix stays fast.
+    pytest.importorskip("sentence_transformers")
+    emb = Embedder.from_sentence_transformers("all-MiniLM-L6-v2")
+    out = emb.embed(["hello world", "another sentence"])
+    assert out.ndim == 2
+    assert out.shape[0] == 2
+    assert out.dtype == np.float32
+    assert "sentence-transformers" in repr(emb)