Added LiteLLM to the stack
This commit is contained in:
@@ -0,0 +1,229 @@
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import json
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import os
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import sys
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from unittest.mock import AsyncMock, MagicMock, patch
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import httpx
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import pytest
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sys.path.insert(
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0, os.path.abspath("../../../../..")
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) # Adds the parent directory to the system path
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from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig
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from litellm.types.llms.openai import OpenAIRealtimeStreamSessionEvents
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def test_gemini_realtime_transformation_session_created():
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config = GeminiRealtimeConfig()
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assert config is not None
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session_configuration_request = {
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"model": "gemini-1.5-flash",
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"generationConfig": {"responseModalities": ["TEXT"]},
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}
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session_configuration_request_str = json.dumps(session_configuration_request)
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session_created_message = {"setupComplete": {}}
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session_created_message_str = json.dumps(session_created_message)
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logging_obj = MagicMock()
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logging_obj.litellm_trace_id = "123"
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transformed_message = config.transform_realtime_response(
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session_created_message_str,
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"gemini-1.5-flash",
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logging_obj,
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realtime_response_transform_input={
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"session_configuration_request": session_configuration_request_str,
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"current_output_item_id": None,
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"current_response_id": None,
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"current_conversation_id": None,
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"current_delta_chunks": [],
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"current_item_chunks": [],
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"current_delta_type": None,
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},
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)
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print(transformed_message)
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assert transformed_message["response"][0]["type"] == "session.created"
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def test_gemini_realtime_transformation_content_delta():
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config = GeminiRealtimeConfig()
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assert config is not None
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session_configuration_request = {
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"model": "gemini-1.5-flash",
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"generationConfig": {"responseModalities": ["TEXT"]},
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}
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session_configuration_request_str = json.dumps(session_configuration_request)
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session_created_message = {
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"serverContent": {
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"modelTurn": {
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"parts": [
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{"text": "Hello, world!"},
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{"text": "How are you?"},
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]
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}
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}
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}
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session_created_message_str = json.dumps(session_created_message)
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logging_obj = MagicMock()
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logging_obj.litellm_trace_id.return_value = "123"
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returned_object = config.transform_realtime_response(
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session_created_message_str,
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"gemini-1.5-flash",
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logging_obj,
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realtime_response_transform_input={
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"session_configuration_request": session_configuration_request_str,
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"current_output_item_id": None,
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"current_response_id": None,
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"current_conversation_id": None,
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"current_delta_chunks": [],
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"current_item_chunks": [],
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"current_delta_type": None,
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},
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)
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transformed_message = returned_object["response"]
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assert isinstance(transformed_message, list)
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print(transformed_message)
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transformed_message_str = json.dumps(transformed_message)
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assert "Hello, world" in transformed_message_str
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assert "How are you?" in transformed_message_str
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print(transformed_message)
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## assert all instances of 'event_id' are unique
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event_ids = [
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event["event_id"] for event in transformed_message if "event_id" in event
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]
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assert len(event_ids) == len(set(event_ids))
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## assert all instances of 'response_id' are the same
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response_ids = [
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event["response_id"] for event in transformed_message if "response_id" in event
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]
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assert len(set(response_ids)) == 1
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## assert all instances of 'output_item_id' are the same
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output_item_ids = [
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event["item_id"] for event in transformed_message if "item_id" in event
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]
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assert len(set(output_item_ids)) == 1
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def test_gemini_model_turn_event_mapping():
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from litellm.types.llms.openai import OpenAIRealtimeEventTypes
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config = GeminiRealtimeConfig()
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assert config is not None
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model_turn_event = {"parts": [{"text": "Hello, world!"}]}
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openai_event = config.map_model_turn_event(model_turn_event)
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assert openai_event == OpenAIRealtimeEventTypes.RESPONSE_TEXT_DELTA
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model_turn_event = {
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"parts": [{"inlineData": {"mimeType": "audio/pcm", "data": "..."}}]
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}
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openai_event = config.map_model_turn_event(model_turn_event)
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assert openai_event == OpenAIRealtimeEventTypes.RESPONSE_AUDIO_DELTA
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model_turn_event = {
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"parts": [
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{
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"text": "Hello, world!",
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"inlineData": {"mimeType": "audio/pcm", "data": "..."},
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}
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]
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}
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openai_event = config.map_model_turn_event(model_turn_event)
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assert openai_event == OpenAIRealtimeEventTypes.RESPONSE_TEXT_DELTA
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def test_gemini_realtime_transformation_audio_delta():
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from litellm.types.llms.openai import OpenAIRealtimeEventTypes
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config = GeminiRealtimeConfig()
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assert config is not None
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session_configuration_request = {
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"model": "gemini-1.5-flash",
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"generationConfig": {"responseModalities": ["AUDIO"]},
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}
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session_configuration_request_str = json.dumps(session_configuration_request)
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audio_delta_event = {
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"serverContent": {
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"modelTurn": {
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"parts": [
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{"inlineData": {"mimeType": "audio/pcm", "data": "my-audio-data"}}
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]
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}
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}
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}
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result = config.transform_realtime_response(
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json.dumps(audio_delta_event),
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"gemini-1.5-flash",
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MagicMock(),
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realtime_response_transform_input={
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"session_configuration_request": session_configuration_request_str,
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"current_output_item_id": None,
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"current_response_id": None,
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"current_conversation_id": None,
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"current_delta_chunks": [],
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"current_item_chunks": [],
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"current_delta_type": None,
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},
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)
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print(result)
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responses = result["response"]
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contains_audio_delta = False
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for response in responses:
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if response["type"] == OpenAIRealtimeEventTypes.RESPONSE_AUDIO_DELTA.value:
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contains_audio_delta = True
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break
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assert contains_audio_delta, "Expected audio delta event"
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def test_gemini_realtime_transformation_generation_complete():
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from litellm.types.llms.openai import OpenAIRealtimeEventTypes
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config = GeminiRealtimeConfig()
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assert config is not None
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session_configuration_request = {
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"model": "gemini-1.5-flash",
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"generationConfig": {"responseModalities": ["AUDIO"]},
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}
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session_configuration_request_str = json.dumps(session_configuration_request)
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audio_delta_event = {"serverContent": {"generationComplete": True}}
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result = config.transform_realtime_response(
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json.dumps(audio_delta_event),
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"gemini-1.5-flash",
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MagicMock(),
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realtime_response_transform_input={
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"session_configuration_request": session_configuration_request_str,
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"current_output_item_id": "my-output-item-id",
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"current_response_id": "my-response-id",
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"current_conversation_id": None,
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"current_delta_chunks": [],
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"current_item_chunks": [],
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"current_delta_type": "audio",
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},
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)
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print(result)
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responses = result["response"]
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contains_audio_done_event = False
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for response in responses:
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if response["type"] == OpenAIRealtimeEventTypes.RESPONSE_AUDIO_DONE.value:
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contains_audio_delta = True
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break
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assert contains_audio_delta, "Expected audio delta event"
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@@ -0,0 +1,101 @@
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import pytest
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import litellm
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import os
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from unittest.mock import patch, Mock
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from litellm import completion
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@pytest.fixture(autouse=True)
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def mock_gemini_api_key(monkeypatch):
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monkeypatch.setenv("GOOGLE_API_KEY", "fake-gemini-key-for-testing")
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def test_gemini_completion():
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response = completion(
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model="gemini/gemini-2.0-flash-exp-image-generation",
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messages=[{"role": "user", "content": "Test message"}],
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mock_response="Test Message",
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)
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assert response.choices[0].message.content is not None
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def test_gemini_completion_no_api_key():
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"""Test Gemini completion fails gracefully when no API key is provided."""
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with patch.dict(os.environ, {}, clear=True):
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# Remove all API keys
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for key in ["GOOGLE_API_KEY", "GEMINI_API_KEY"]:
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if key in os.environ:
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del os.environ[key]
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# Test without mock_response to ensure actual API key validation
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with pytest.raises(Exception) as exc_info:
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completion(
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model="gemini/gemini-1.5-flash",
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messages=[{"role": "user", "content": "Test message"}],
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)
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# Check that the exception message contains API key related text
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error_message = str(exc_info.value).lower()
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assert any(
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keyword in error_message
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for keyword in [
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"api key",
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"authentication",
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"unauthorized",
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"invalid",
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"missing",
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"credential",
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]
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)
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def test_gemini_completion_no_api_key_with_mock():
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"""Alternative test that properly mocks the API key validation."""
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with patch.dict(os.environ, {}, clear=True):
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# Remove all API keys
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for key in ["GOOGLE_API_KEY", "GEMINI_API_KEY"]:
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if key in os.environ:
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del os.environ[key]
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with patch("litellm.get_secret") as mock_get_secret:
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mock_get_secret.return_value = None
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with pytest.raises(Exception) as exc_info:
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completion(
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model="gemini/gemini-1.5-flash",
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messages=[{"role": "user", "content": "Test message"}],
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)
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error_message = str(exc_info.value).lower()
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assert any(
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keyword in error_message
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for keyword in [
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"api key",
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"authentication",
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"unauthorized",
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"invalid",
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"missing",
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"credential",
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]
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)
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@pytest.mark.parametrize("api_key_env", ["GOOGLE_API_KEY", "GEMINI_API_KEY"])
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def test_gemini_completion_both_env_vars(monkeypatch, api_key_env):
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"""Test Gemini completion works with both environment variable names."""
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# Clear all API keys first
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monkeypatch.delenv("GOOGLE_API_KEY", raising=False)
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monkeypatch.delenv("GEMINI_API_KEY", raising=False)
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# Set the specific API key being tested
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monkeypatch.setenv(api_key_env, f"fake-{api_key_env.lower()}-for-testing")
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response = completion(
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model="gemini/gemini-1.5-flash",
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messages=[{"role": "user", "content": f"Test with {api_key_env}"}],
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mock_response=f"Mocked response using {api_key_env}",
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)
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assert (
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response["choices"][0]["message"]["content"]
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== f"Mocked response using {api_key_env}"
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)
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@@ -0,0 +1,160 @@
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from unittest.mock import AsyncMock, patch
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import pytest
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from litellm.llms.gemini.common_utils import GeminiModelInfo, GoogleAIStudioTokenCounter
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class TestGeminiModelInfo:
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"""Test suite for GeminiModelInfo class"""
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def test_process_model_name_normal_cases(self):
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"""Test process_model_name with normal model names"""
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gemini_model_info = GeminiModelInfo()
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# Test with normal model names
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models = [
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{"name": "models/gemini-1.5-flash"},
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{"name": "models/gemini-1.5-pro"},
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{"name": "models/gemini-2.0-flash-exp"},
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]
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result = gemini_model_info.process_model_name(models)
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expected = [
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"gemini/gemini-1.5-flash",
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"gemini/gemini-1.5-pro",
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"gemini/gemini-2.0-flash-exp",
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]
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assert result == expected
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def test_process_model_name_edge_cases(self):
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"""Test process_model_name with edge cases that could be affected by strip() vs replace()"""
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gemini_model_info = GeminiModelInfo()
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# Test edge cases where model names end with characters from "models/"
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# These would be incorrectly processed if using strip("models/") instead of replace("models/", "")
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models = [
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{
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"name": "models/gemini-1.5-pro"
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}, # ends with 'o' - would become "gemini-1.5-pr" with strip()
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{
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"name": "models/test-model"
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}, # ends with 'l' - would become "gemini/test-mode" with strip()
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{
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"name": "models/custom-models"
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}, # ends with 's' - would become "gemini/custom-model" with strip()
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{
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"name": "models/demo"
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}, # ends with 'o' - would become "gemini/dem" with strip()
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]
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result = gemini_model_info.process_model_name(models)
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expected = [
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"gemini/gemini-1.5-pro", # 'o' should be preserved
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"gemini/test-model", # 'l' should be preserved
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"gemini/custom-models", # 's' should be preserved
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"gemini/demo", # 'o' should be preserved
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]
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assert result == expected
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def test_process_model_name_empty_list(self):
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"""Test process_model_name with empty list"""
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gemini_model_info = GeminiModelInfo()
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result = gemini_model_info.process_model_name([])
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assert result == []
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def test_process_model_name_no_models_prefix(self):
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"""Test process_model_name with model names that don't have 'models/' prefix"""
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gemini_model_info = GeminiModelInfo()
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models = [
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{"name": "gemini-1.5-flash"}, # No "models/" prefix
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{"name": "custom-model"},
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]
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result = gemini_model_info.process_model_name(models)
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expected = [
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"gemini/gemini-1.5-flash",
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"gemini/custom-model",
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]
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assert result == expected
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class TestGoogleAIStudioTokenCounter:
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"""Test suite for GoogleAIStudioTokenCounter class"""
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def test_should_use_token_counting_api(self):
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"""Test should_use_token_counting_api method with different provider values"""
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from litellm.types.utils import LlmProviders
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token_counter = GoogleAIStudioTokenCounter()
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# Test with gemini provider - should return True
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assert token_counter.should_use_token_counting_api(LlmProviders.GEMINI.value) is True
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# Test with other providers - should return False
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assert token_counter.should_use_token_counting_api(LlmProviders.OPENAI.value) is False
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assert token_counter.should_use_token_counting_api("anthropic") is False
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assert token_counter.should_use_token_counting_api("vertex_ai") is False
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# Test with None - should return False
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assert token_counter.should_use_token_counting_api(None) is False
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@pytest.mark.asyncio
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async def test_count_tokens(self):
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"""Test count_tokens method with mocked API response"""
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from litellm.types.utils import TokenCountResponse
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token_counter = GoogleAIStudioTokenCounter()
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# Mock the GoogleAIStudioTokenCounter from handler module
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mock_response = {
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"totalTokens": 31,
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"totalBillableCharacters": 96,
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"promptTokensDetails": [
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{
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"modality": "TEXT",
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"tokenCount": 31
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}
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]
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}
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with patch('litellm.llms.gemini.count_tokens.handler.GoogleAIStudioTokenCounter.acount_tokens',
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new_callable=AsyncMock) as mock_acount_tokens:
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mock_acount_tokens.return_value = mock_response
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# Test data
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model_to_use = "gemini-1.5-flash"
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contents = [{"parts": [{"text": "Hello world"}]}]
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request_model = "gemini/gemini-1.5-flash"
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# Call the method
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result = await token_counter.count_tokens(
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model_to_use=model_to_use,
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messages=None,
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contents=contents,
|
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deployment=None,
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request_model=request_model
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)
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||||
# Verify the result
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||||
assert result is not None
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||||
assert isinstance(result, TokenCountResponse)
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assert result.total_tokens == 31
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assert result.request_model == request_model
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assert result.model_used == model_to_use
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assert result.original_response == mock_response
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# Verify the mock was called correctly
|
||||
mock_acount_tokens.assert_called_once_with(
|
||||
model=model_to_use,
|
||||
contents=contents
|
||||
)
|
||||
@@ -0,0 +1,221 @@
|
||||
"""
|
||||
Test Gemini TTS (Text-to-Speech) functionality
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import pytest
|
||||
from unittest.mock import patch, MagicMock
|
||||
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../../../..")
|
||||
) # Adds the parent directory to the system path
|
||||
|
||||
import litellm
|
||||
from litellm.llms.gemini.chat.transformation import GoogleAIStudioGeminiConfig
|
||||
from litellm.utils import get_supported_openai_params
|
||||
|
||||
|
||||
class TestGeminiTTSTransformation:
|
||||
"""Test Gemini TTS transformation functionality"""
|
||||
|
||||
def test_gemini_tts_model_detection(self):
|
||||
"""Test that TTS models are correctly identified"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
# Test TTS models
|
||||
assert config.is_model_gemini_audio_model("gemini-2.5-flash-preview-tts") == True
|
||||
assert config.is_model_gemini_audio_model("gemini-2.5-pro-preview-tts") == True
|
||||
|
||||
# Test non-TTS models
|
||||
assert config.is_model_gemini_audio_model("gemini-2.5-flash") == False
|
||||
assert config.is_model_gemini_audio_model("gemini-2.5-pro") == False
|
||||
assert config.is_model_gemini_audio_model("gpt-4o-audio-preview") == False
|
||||
|
||||
def test_gemini_tts_supported_params(self):
|
||||
"""Test that audio parameter is included for TTS models"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
# Test TTS model
|
||||
params = config.get_supported_openai_params("gemini-2.5-flash-preview-tts")
|
||||
assert "audio" in params
|
||||
|
||||
# Test that other standard params are still included
|
||||
assert "temperature" in params
|
||||
assert "max_tokens" in params
|
||||
assert "modalities" in params
|
||||
|
||||
# Test non-TTS model
|
||||
params_non_tts = config.get_supported_openai_params("gemini-2.5-flash")
|
||||
assert "audio" not in params_non_tts
|
||||
|
||||
def test_gemini_tts_audio_parameter_mapping(self):
|
||||
"""Test audio parameter mapping for TTS models"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
non_default_params = {
|
||||
"audio": {
|
||||
"voice": "Kore",
|
||||
"format": "pcm16"
|
||||
}
|
||||
}
|
||||
optional_params = {}
|
||||
|
||||
result = config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
# Check speech config is created
|
||||
assert "speechConfig" in result
|
||||
assert "voiceConfig" in result["speechConfig"]
|
||||
assert "prebuiltVoiceConfig" in result["speechConfig"]["voiceConfig"]
|
||||
assert result["speechConfig"]["voiceConfig"]["prebuiltVoiceConfig"]["voiceName"] == "Kore"
|
||||
|
||||
# Check response modalities
|
||||
assert "responseModalities" in result
|
||||
assert "AUDIO" in result["responseModalities"]
|
||||
|
||||
def test_gemini_tts_audio_parameter_with_existing_modalities(self):
|
||||
"""Test audio parameter mapping when modalities already exist"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
non_default_params = {
|
||||
"audio": {
|
||||
"voice": "Puck",
|
||||
"format": "pcm16"
|
||||
}
|
||||
}
|
||||
optional_params = {
|
||||
"responseModalities": ["TEXT"]
|
||||
}
|
||||
|
||||
result = config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
# Check that AUDIO is added to existing modalities
|
||||
assert "responseModalities" in result
|
||||
assert "TEXT" in result["responseModalities"]
|
||||
assert "AUDIO" in result["responseModalities"]
|
||||
|
||||
def test_gemini_tts_no_audio_parameter(self):
|
||||
"""Test that non-audio parameters are handled normally"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
non_default_params = {
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 100
|
||||
}
|
||||
optional_params = {}
|
||||
|
||||
result = config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
# Should not have speech config
|
||||
assert "speechConfig" not in result
|
||||
# Should not automatically add audio modalities
|
||||
assert "responseModalities" not in result
|
||||
|
||||
def test_gemini_tts_invalid_audio_parameter(self):
|
||||
"""Test handling of invalid audio parameter"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
non_default_params = {
|
||||
"audio": "invalid_string" # Should be dict
|
||||
}
|
||||
optional_params = {}
|
||||
|
||||
result = config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
# Should not create speech config for invalid audio param
|
||||
assert "speechConfig" not in result
|
||||
|
||||
def test_gemini_tts_empty_audio_parameter(self):
|
||||
"""Test handling of empty audio parameter"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
non_default_params = {
|
||||
"audio": {}
|
||||
}
|
||||
optional_params = {}
|
||||
|
||||
result = config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
# Should still set response modalities even with empty audio config
|
||||
assert "responseModalities" in result
|
||||
assert "AUDIO" in result["responseModalities"]
|
||||
|
||||
def test_gemini_tts_audio_format_validation(self):
|
||||
"""Test audio format validation for TTS models"""
|
||||
config = GoogleAIStudioGeminiConfig()
|
||||
|
||||
# Test invalid format
|
||||
non_default_params = {
|
||||
"audio": {
|
||||
"voice": "Kore",
|
||||
"format": "wav" # Invalid format
|
||||
}
|
||||
}
|
||||
optional_params = {}
|
||||
|
||||
with pytest.raises(ValueError, match="Unsupported audio format for Gemini TTS models"):
|
||||
config.map_openai_params(
|
||||
non_default_params=non_default_params,
|
||||
optional_params=optional_params,
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
drop_params=False
|
||||
)
|
||||
|
||||
def test_gemini_tts_utils_integration(self):
|
||||
"""Test integration with LiteLLM utils functions"""
|
||||
# Test that get_supported_openai_params works with TTS models
|
||||
params = get_supported_openai_params("gemini-2.5-flash-preview-tts", "gemini")
|
||||
assert "audio" in params
|
||||
|
||||
# Test non-TTS model
|
||||
params_non_tts = get_supported_openai_params("gemini-2.5-flash", "gemini")
|
||||
assert "audio" not in params_non_tts
|
||||
|
||||
|
||||
def test_gemini_tts_completion_mock():
|
||||
"""Test Gemini TTS completion with mocked response"""
|
||||
with patch('litellm.completion') as mock_completion:
|
||||
# Mock a successful TTS response
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = "Generated audio response"
|
||||
mock_completion.return_value = mock_response
|
||||
|
||||
# Test completion call with audio parameter
|
||||
response = litellm.completion(
|
||||
model="gemini-2.5-flash-preview-tts",
|
||||
messages=[{"role": "user", "content": "Say hello"}],
|
||||
audio={"voice": "Kore", "format": "pcm16"}
|
||||
)
|
||||
|
||||
assert response is not None
|
||||
assert response.choices[0].message.content is not None
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__])
|
||||
Reference in New Issue
Block a user