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77cf56e54a
* Embeddings plugin hook + OpenAI implementation * llm.get_embedding_model(name) function * llm embed command, for returning embeddings or saving them to SQLite * Tests using an EmbedDemo embedding model * llm embed-models list and emeb-models default commands * llm embed-db path and llm embed-db collections commands
81 lines
1.8 KiB
Python
81 lines
1.8 KiB
Python
import pytest
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import llm
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from llm.plugins import pm
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def pytest_configure(config):
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import sys
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sys._called_from_test = True
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@pytest.fixture
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def user_path(tmpdir):
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dir = tmpdir / "llm.datasette.io"
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dir.mkdir()
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return dir
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@pytest.fixture
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def templates_path(user_path):
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dir = user_path / "templates"
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dir.mkdir()
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return dir
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@pytest.fixture(autouse=True)
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def env_setup(monkeypatch, user_path):
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monkeypatch.setenv("LLM_USER_PATH", str(user_path))
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class EmbedDemo(llm.EmbeddingModel):
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model_id = "embed-demo"
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def embed(self, text):
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words = text.split()[:16]
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embedding = [len(word) for word in words]
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# Pad with 0 up to 16 words
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embedding += [0] * (16 - len(embedding))
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return embedding
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@pytest.fixture(autouse=True)
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def register_embed_demo_model():
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class EmbedDemoPlugin:
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__name__ = "EmbedDemoPlugin"
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@llm.hookimpl
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def register_embedding_models(self, register):
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register(EmbedDemo())
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pm.register(EmbedDemoPlugin(), name="undo-embed-demo-plugin")
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try:
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yield
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finally:
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pm.unregister(name="undo-embed-demo-plugin")
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@pytest.fixture
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def mocked_openai(requests_mock):
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return requests_mock.post(
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"https://api.openai.com/v1/chat/completions",
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json={
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"model": "gpt-3.5-turbo",
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"usage": {},
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"choices": [{"message": {"content": "Bob, Alice, Eve"}}],
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},
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headers={"Content-Type": "application/json"},
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)
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@pytest.fixture
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def mocked_localai(requests_mock):
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return requests_mock.post(
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"http://localai.localhost/chat/completions",
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json={
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"model": "orca",
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"usage": {},
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"choices": [{"message": {"content": "Bob, Alice, Eve"}}],
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},
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headers={"Content-Type": "application/json"},
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)
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