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https://github.com/open-jarvis/OpenJarvis.git
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Jon Saad-FalconandClaude Opus 4.6
301e9cd2d4
Complete implementation across six development phases (v0.1 through v1.0): - Core: Registry system, config, event bus, types (Phase 0) - Intelligence + Inference: Model routing, Ollama/vLLM/llama.cpp/Cloud engines (Phase 1) - Memory: SQLite/FAISS/ColBERT/BM25/Hybrid backends, document ingest, context injection (Phase 2) - Agents: Simple/Orchestrator/Custom/OpenClaw agents, tool system (Phase 3) - Learning: HeuristicRouter, reward functions, GRPO stub, telemetry aggregation (Phase 4) - SDK: Jarvis class, OpenClaw protocol/transport, benchmarks, Docker deployment (Phase 5) 520 tests passing, 8 skipped (optional deps). Ruff lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
74 lines
2.0 KiB
Python
74 lines
2.0 KiB
Python
"""Tests for the embeddings abstraction layer."""
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from __future__ import annotations
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import pytest
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st = pytest.importorskip("sentence_transformers")
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from openjarvis.memory.embeddings import ( # noqa: E402
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Embedder,
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SentenceTransformerEmbedder,
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)
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@pytest.fixture()
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def embedder() -> SentenceTransformerEmbedder:
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return SentenceTransformerEmbedder()
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def test_produces_vectors(embedder: SentenceTransformerEmbedder):
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"""embed() returns a numpy array with one row per input."""
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import numpy as np
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vecs = embedder.embed(["hello world"])
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assert isinstance(vecs, np.ndarray)
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assert vecs.shape[0] == 1
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def test_correct_dimension(
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embedder: SentenceTransformerEmbedder,
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):
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"""Embedding dimension matches the declared dim()."""
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vecs = embedder.embed(["test"])
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assert vecs.shape[1] == embedder.dim()
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def test_batch(embedder: SentenceTransformerEmbedder):
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"""Batch of texts produces matching number of vectors."""
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texts = ["one", "two", "three"]
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vecs = embedder.embed(texts)
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assert vecs.shape[0] == 3
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assert vecs.shape[1] == embedder.dim()
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def test_empty_input(embedder: SentenceTransformerEmbedder):
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"""Empty list produces an empty array."""
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import numpy as np
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vecs = embedder.embed([])
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assert isinstance(vecs, np.ndarray)
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assert vecs.shape[0] == 0
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def test_missing_dep(monkeypatch: pytest.MonkeyPatch):
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"""Import error is raised with a helpful message."""
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import builtins
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real_import = builtins.__import__
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def _block_st(name, *args, **kwargs): # type: ignore[no-untyped-def]
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if name == "sentence_transformers":
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raise ImportError("mocked")
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return real_import(name, *args, **kwargs)
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monkeypatch.setattr(builtins, "__import__", _block_st)
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with pytest.raises(ImportError, match="sentence-transformers"):
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SentenceTransformerEmbedder()
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def test_embedder_abc_cannot_instantiate():
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"""Embedder ABC cannot be instantiated directly."""
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with pytest.raises(TypeError):
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Embedder() # type: ignore[abstract]
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