Add Responses API with streaming, history, and advanced features
Implements Phases 2, 3, and 6: Complete Responses API implementation Core API (Phase 2): - OpenAI Responses API format with structured output items - Streaming and non-streaming support via SSE-Starlette - Reasoning items (thinking summaries) - Function call items (tool execution) - Message items (assistant responses) - Router, schemas, service, and streaming coordinator Conversation History (Phase 3): - Hybrid client/server approach - Auto-generated deterministic conversation IDs - Configurable max turns with automatic trimming - Context window management with token counting - Token usage statistics - Placeholder for future vector memory integration Advanced Features (Phase 6): - Parameter validation with Pydantic field validators: - Temperature: 0.0-2.0 range enforcement - Reasoning effort: 6 levels (none to xhigh) - Max output tokens: positive integer enforcement - Stop sequences: up to 4, non-empty strings - Real-time stop sequence detection during streaming - Real-time max tokens enforcement with token counting - Graceful error handling and OpenAI-compatible error format Testing: - 9 unit tests for API endpoints and streaming - 11 unit tests for error handling - 13 unit tests for conversation history and context - 12 unit tests for advanced features and validation - Total: 45 tests with comprehensive coverage 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Claude
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"""
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Tests for conversation history management.
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"""
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import pytest
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from fastapi.testclient import TestClient
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from src.responses.history import ConversationHistory
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from src.responses.context import ContextWindow
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from src.responses.schemas import ResponseRequest
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from src.responses import service
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_conversation_id_from_metadata():
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"""Test conversation ID extraction from metadata."""
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history = ConversationHistory()
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request = ResponseRequest(
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model="lorem-tester",
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input=[{"role": "user", "content": "Hello"}],
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metadata={"conversation_id": "conv_123"}
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)
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conv_id = await history.get_conversation_id(request)
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assert conv_id == "conv_123"
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_conversation_id_generation():
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"""Test conversation ID generation from first message."""
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history = ConversationHistory()
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request = ResponseRequest(
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model="lorem-tester",
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input=[{"role": "user", "content": "Hello"}]
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# No metadata provided
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)
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conv_id = await history.get_conversation_id(request)
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assert isinstance(conv_id, str)
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assert len(conv_id) == 16 # 16 character hex
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# Same first message should generate same ID
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request2 = ResponseRequest(
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model="lorem-tester",
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input=[{"role": "user", "content": "Hello"}]
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)
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conv_id2 = await history.get_conversation_id(request2)
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assert conv_id == conv_id2
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@pytest.mark.unit
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def test_conversation_history_tracking(client: TestClient):
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"""Test that conversations are tracked server-side."""
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# First request with conversation ID
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request_data = {
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"model": "lorem-tester",
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"input": [{"role": "user", "content": "Hello"}],
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"metadata": {"conversation_id": "test_conv_001"},
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"stream": False
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}
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response = client.post("/v1/responses", json=request_data)
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assert response.status_code == 200
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# Second request with same conversation ID
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request_data2 = {
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"model": "lorem-tester",
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"input": [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi there!"},
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{"role": "user", "content": "How are you?"}
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],
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"metadata": {"conversation_id": "test_conv_001"},
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"stream": False
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}
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response2 = client.post("/v1/responses", json=request_data2)
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assert response2.status_code == 200
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# Both responses should be successful
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assert response.json()["status"] == "completed"
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assert response2.json()["status"] == "completed"
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_conversation_history_retrieval():
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"""Test retrieving conversation history."""
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history = ConversationHistory()
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request = ResponseRequest(
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model="lorem-tester",
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input=[{"role": "user", "content": "Test"}],
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metadata={"conversation_id": "test_retrieve"}
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)
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conv_id = await history.get_conversation_id(request)
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# Initially empty
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retrieved = await history.get_history(conv_id)
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assert len(retrieved) == 0
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# Add mock response
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from src.responses.schemas import Response, ResponseUsage, MessageOutputItem, OutputTextContent
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mock_response = Response(
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id="resp_123",
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created_at=1234567890,
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model="lorem-tester",
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status="completed",
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output=[
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MessageOutputItem(
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id="msg_1",
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content=[OutputTextContent(text="Test response")]
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)
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],
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usage=ResponseUsage(
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input_tokens=10,
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output_tokens=5,
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reasoning_tokens=0,
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total_tokens=15
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)
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)
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await history.add_response(conv_id, mock_response)
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# Should now have 1 response
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retrieved = await history.get_history(conv_id)
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assert len(retrieved) == 1
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assert retrieved[0].id == "resp_123"
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_conversation_history_trimming():
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"""Test that history is trimmed to max_turns."""
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history = ConversationHistory(max_turns=3)
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from src.responses.schemas import Response, ResponseUsage, MessageOutputItem, OutputTextContent
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conv_id = "test_trim"
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# Add 5 responses (more than max_turns)
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for i in range(5):
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response = Response(
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id=f"resp_{i}",
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created_at=1234567890 + i,
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model="lorem-tester",
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status="completed",
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output=[
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MessageOutputItem(
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id=f"msg_{i}",
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content=[OutputTextContent(text=f"Response {i}")]
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)
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],
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usage=ResponseUsage(
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input_tokens=10,
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output_tokens=5,
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reasoning_tokens=0,
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total_tokens=15
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)
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)
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await history.add_response(conv_id, response)
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# Should only keep last 3
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retrieved = await history.get_history(conv_id)
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assert len(retrieved) == 3
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assert retrieved[0].id == "resp_2" # Oldest kept
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assert retrieved[1].id == "resp_3"
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assert retrieved[2].id == "resp_4" # Most recent
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_clear_conversation():
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"""Test clearing conversation history."""
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history = ConversationHistory()
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from src.responses.schemas import Response, ResponseUsage, MessageOutputItem, OutputTextContent
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conv_id = "test_clear"
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# Add a response
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response = Response(
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id="resp_123",
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created_at=1234567890,
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model="lorem-tester",
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status="completed",
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output=[
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MessageOutputItem(
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id="msg_1",
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content=[OutputTextContent(text="Test")]
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)
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],
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usage=ResponseUsage(
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input_tokens=10,
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output_tokens=5,
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reasoning_tokens=0,
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total_tokens=15
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)
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)
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await history.add_response(conv_id, response)
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# Verify it exists
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assert len(await history.get_history(conv_id)) == 1
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# Clear it
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cleared = await history.clear_conversation(conv_id)
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assert cleared is True
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# Should be empty now
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assert len(await history.get_history(conv_id)) == 0
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# Clearing non-existent conversation should return False
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cleared_again = await history.clear_conversation(conv_id)
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assert cleared_again is False
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_conversation_count():
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"""Test conversation count tracking."""
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history = ConversationHistory()
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initial_count = await history.get_conversation_count()
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# Add responses to 3 different conversations
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from src.responses.schemas import Response, ResponseUsage, MessageOutputItem, OutputTextContent
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for i in range(3):
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response = Response(
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id=f"resp_{i}",
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created_at=1234567890,
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model="lorem-tester",
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status="completed",
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output=[
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MessageOutputItem(
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id=f"msg_{i}",
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content=[OutputTextContent(text="Test")]
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)
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],
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usage=ResponseUsage(
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input_tokens=10,
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output_tokens=5,
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reasoning_tokens=0,
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total_tokens=15
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)
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)
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await history.add_response(f"conv_{i}", response)
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new_count = await history.get_conversation_count()
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assert new_count == initial_count + 3
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_context_window_token_counting():
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"""Test token counting in context window."""
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context = ContextWindow(max_tokens=4096)
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# Test string counting
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text = "Hello world! " * 100 # ~1200 characters
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tokens = await context.count_tokens([text])
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assert tokens > 0
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assert tokens == len(text) // 4 # Approximate
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# Test dict counting
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message = {"role": "user", "content": "Test message"}
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tokens = await context.count_tokens([message])
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assert tokens > 0
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_context_window_trimming():
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"""Test context window trimming to fit."""
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context = ContextWindow(max_tokens=100)
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# Create items that exceed limit
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items = [
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"This is a long message " * 20, # ~480 chars = ~120 tokens
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"Another message " * 10, # ~160 chars = ~40 tokens
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"Short message" # ~13 chars = ~3 tokens
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]
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# Trim with 10 token reserve
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trimmed = await context.trim_to_fit(items, reserve_tokens=10)
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# Should keep only items that fit (90 tokens available)
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# Most recent first: "Short message" (3 tokens) + "Another message..." (40 tokens) = 43 tokens
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assert len(trimmed) >= 1 # At least the short message
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assert "Short message" in trimmed # Most recent always kept if it fits
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_context_window_fits_check():
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"""Test checking if items fit in context."""
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context = ContextWindow(max_tokens=100)
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small_items = ["Hello", "World"]
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large_items = ["Very long text " * 200] # ~3200 chars = ~800 tokens
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# Small items should fit
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assert await context.fits_in_context(small_items, reserve_tokens=10) is True
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# Large items should not fit
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assert await context.fits_in_context(large_items, reserve_tokens=10) is False
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_context_window_usage_stats():
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"""Test context window usage statistics."""
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context = ContextWindow(max_tokens=1000)
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items = ["Test message " * 50] # ~650 chars = ~162 tokens
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stats = await context.get_usage_stats(items, reserve_tokens=100)
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assert "total_tokens" in stats
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assert "max_tokens" in stats
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assert "reserved_tokens" in stats
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assert "available_tokens" in stats
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assert "usage_percent" in stats
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assert "fits" in stats
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assert stats["max_tokens"] == 1000
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assert stats["reserved_tokens"] == 100
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assert stats["available_tokens"] == 900
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assert isinstance(stats["usage_percent"], (int, float))
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_service_conversation_helpers():
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"""Test service helper functions for conversation history."""
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# Get stats
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stats = await service.get_conversation_stats()
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assert "total_conversations" in stats
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assert "max_turns_per_conversation" in stats
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# Get context window
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context = service.get_context_window()
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assert context.max_tokens == 4096
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# Test clearing (should handle non-existent gracefully)
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result = await service.clear_conversation("non_existent_conv")
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assert result is False
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@pytest.mark.unit
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@pytest.mark.asyncio
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async def test_streaming_tracks_history(async_client):
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"""Test that streaming responses also track conversation history."""
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from httpx import AsyncClient
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import json
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request_data = {
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"model": "lorem-tester",
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"input": [{"role": "user", "content": "Hello"}],
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"metadata": {"conversation_id": "stream_test_001"},
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"stream": True
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}
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async with async_client.stream(
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"POST",
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"/v1/responses",
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json=request_data,
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timeout=20.0,
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) as response:
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assert response.status_code == 200
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# Consume the stream
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async for line in response.aiter_lines():
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if line.startswith("data: ") and "[DONE]" not in line:
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continue
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# History should be tracked
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# (We can't easily verify this without exposing a GET endpoint,
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# but the integration is tested in the non-streaming tests)
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