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Lines changed: 60 additions & 54 deletions

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‎docs/notebooks/tutorials/110_openrouter_sample_annotation.ipynb‎

Lines changed: 47 additions & 44 deletions
Original file line numberDiff line numberDiff line change
@@ -2,6 +2,7 @@
22
"cells": [
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{
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"cell_type": "markdown",
5+
"id": "0b7b320c",
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"metadata": {},
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"source": [
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"# OpenRouter sample annotation with Leiden clusters\n",
@@ -13,25 +14,23 @@
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"- annotate clusters across samples with `CellAnnotator`.\n",
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"\n",
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"It follows the same high-level workflow as `100_heart_atlas.ipynb`, but is parameterized for OpenRouter."
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],
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"id": "0b7b320c"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "add3858e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import scanpy as sc\n",
24-
"import pandas as pd\n",
25-
"from cell_annotator import CellAnnotator\n",
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"\n",
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"print(\"scanpy:\", sc.__version__)"
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],
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"execution_count": null,
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"outputs": [],
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"id": "add3858e"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a2337a8d",
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"metadata": {},
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"source": [
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"## Configure your run\n",
@@ -41,12 +40,14 @@
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"- `OPENROUTER_MODEL`: an OpenRouter model ID (for example: `openai/gpt-4o-mini`)\n",
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"- `LEIDEN_KEY`: the Leiden column in `adata.obs`\n",
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"- `SAMPLE_KEY`: sample/batch column in `adata.obs` (or `None` for a single-sample dataset)"
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],
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"id": "a2337a8d"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "70164ce3",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Required\n",
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"OPENROUTER_API_KEY = \"\" # e.g. sk-or-v1-...\n",
@@ -66,14 +67,14 @@
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" raise ValueError(\"Set OPENROUTER_API_KEY before continuing.\")\n",
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"if not OPENROUTER_MODEL:\n",
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" raise ValueError(\"Set OPENROUTER_MODEL before continuing.\")"
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],
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"execution_count": null,
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"outputs": [],
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"id": "70164ce3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2428de31",
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"metadata": {},
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"outputs": [],
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"source": [
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"adata = sc.read_h5ad(ADATA_PATH)\n",
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"\n",
@@ -86,34 +87,34 @@
8687
"print(adata)\n",
8788
"print(\"Leiden key:\", LEIDEN_KEY)\n",
8889
"print(\"Sample key:\", SAMPLE_KEY)"
89-
],
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"execution_count": null,
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"outputs": [],
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"id": "2428de31"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ffe7a22b-8d3c-4ad2-9dfd-13bc01cb7f6a",
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"metadata": {},
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"outputs": [],
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"source": [
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"adata.obs"
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],
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"execution_count": null,
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"outputs": [],
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"id": "ffe7a22b-8d3c-4ad2-9dfd-13bc01cb7f6a"
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]
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},
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{
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"cell_type": "code",
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"metadata": {},
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"source": [
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"adata.obsm['spatial']"
109-
],
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"execution_count": null,
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"id": "bd6282fc-2140-4e9f-a81c-1bc0f4200261",
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"metadata": {},
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"outputs": [],
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"id": "bd6282fc-2140-4e9f-a81c-1bc0f4200261"
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"source": [
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"adata.obsm[\"spatial\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6245b49a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# 1) Ask the model for expected cell types and marker genes\n",
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"cell_ann.get_expected_cell_type_markers()\n",
@@ -123,14 +124,14 @@
123124
"\n",
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"# 3) Annotate clusters and write predictions to adata.obs\n",
125126
"cell_ann.annotate_clusters(key_added=\"cell_type_predicted\")"
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],
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"execution_count": null,
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"outputs": [],
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"id": "6245b49a"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "df316877",
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"metadata": {},
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"outputs": [],
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"source": [
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"if \"X_umap\" in adata.obsm:\n",
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" sc.pl.umap(adata, color=[LEIDEN_KEY, \"cell_type_predicted\"], wspace=0.35)\n",
@@ -140,30 +141,32 @@
140141
"output_path = ADATA_PATH.replace(\".h5ad\", \"_annotated.h5ad\")\n",
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"adata.write(output_path)\n",
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"print(f\"Saved annotated object to: {output_path}\")"
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],
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"execution_count": null,
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"outputs": [],
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"id": "df316877"
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]
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},
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{
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"cell_type": "code",
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"metadata": {},
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"source": [
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"fig = sc.pl.embedding(adata, basis='X_umap_drvi', color='cell_type_predicted', title='s', )"
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],
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"execution_count": null,
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"id": "294208db-4c90-4855-b875-2841b23b8a20",
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"metadata": {},
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"outputs": [],
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"id": "294208db-4c90-4855-b875-2841b23b8a20"
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"source": [
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"fig = sc.pl.embedding(\n",
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" adata,\n",
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" basis=\"X_umap_drvi\",\n",
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" color=\"cell_type_predicted\",\n",
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" title=\"s\",\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a9e74b69-ca17-44c4-a010-6cf149cccb73",
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"metadata": {},
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"outputs": [],
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"source": [
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"fig"
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],
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"execution_count": null,
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"outputs": [],
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"id": "a9e74b69-ca17-44c4-a010-6cf149cccb73"
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]
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}
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],
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"metadata": {

‎src/cell_annotator/model/_providers.py‎

Lines changed: 10 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
"""LLM provider abstraction layer."""
22

3-
from abc import ABC, abstractmethod
43
import json
4+
from abc import ABC, abstractmethod
55

66
from dotenv import load_dotenv
77

@@ -188,7 +188,9 @@ def query(
188188
logger.warning(failure_reason)
189189
return response_format.default_failure(failure_reason=failure_reason)
190190
except openai.OpenAIError as e:
191-
logger.debug("Structured parse failed for model '%s'. Falling back to JSON-mode query. Error: %s", model, str(e))
191+
logger.debug(
192+
"Structured parse failed for model '%s'. Falling back to JSON-mode query. Error: %s", model, str(e)
193+
)
192194
return self._query_with_json_fallback(
193195
model=model,
194196
response_format=response_format,
@@ -197,7 +199,9 @@ def query(
197199
fallback_error=str(e),
198200
)
199201
except Exception as e: # noqa: BLE001
200-
logger.debug("Non-OpenAI parse failure for model '%s'. Falling back to JSON-mode query. Error: %s", model, str(e))
202+
logger.debug(
203+
"Non-OpenAI parse failure for model '%s'. Falling back to JSON-mode query. Error: %s", model, str(e)
204+
)
201205
return self._query_with_json_fallback(
202206
model=model,
203207
response_format=response_format,
@@ -254,8 +258,7 @@ def _query_with_json_fallback(
254258
if not text:
255259
return response_format.default_failure(
256260
failure_reason=(
257-
"Model returned empty content during JSON fallback. "
258-
f"Original parse error: {fallback_error}"
261+
f"Model returned empty content during JSON fallback. Original parse error: {fallback_error}"
259262
)
260263
)
261264

@@ -378,10 +381,7 @@ def __repr__(self) -> str:
378381
model_preview = ", ".join(models)
379382
if len(self.list_available_models()) > 5:
380383
model_preview += ", ..."
381-
return (
382-
f"OpenRouterProvider(models: {model_preview}). "
383-
"Call .list_available_models() for complete list."
384-
)
384+
return f"OpenRouterProvider(models: {model_preview}). Call .list_available_models() for complete list."
385385
else:
386386
return "OpenRouterProvider(models: none available). Call .list_available_models() for complete list."
387387
except Exception: # noqa: BLE001
@@ -405,6 +405,7 @@ def _list_models_impl(self) -> list[str]:
405405

406406
return sorted(filtered_models)
407407

408+
408409
class GeminiProvider(LLMProvider):
409410
"""Google Gemini provider implementation."""
410411

‎tests/model/test_providers.py‎

Lines changed: 3 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -291,7 +291,9 @@ def test_provider_factory_pattern(self):
291291

292292
@flaky
293293
@pytest.mark.skipif(
294-
not any(os.getenv(key) for key in ["OPENAI_API_KEY", "GEMINI_API_KEY", "ANTHROPIC_API_KEY", "OPENROUTER_API_KEY"]),
294+
not any(
295+
os.getenv(key) for key in ["OPENAI_API_KEY", "GEMINI_API_KEY", "ANTHROPIC_API_KEY", "OPENROUTER_API_KEY"]
296+
),
295297
reason="No API keys available for testing",
296298
)
297299
@pytest.mark.real_llm_query()

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