* refactor(ai): use responses API for OpenAI/Azure, create 'other' provider for completion endpoint - Created new 'other.rs' provider using the OpenAI-compatible completion endpoint - Refactored 'openai.rs' to use the Responses API for both text and image output - Updated query_builder to route OpenAI/AzureOpenAI to OpenAIQueryBuilder - All other providers (Mistral, DeepSeek, Groq, etc.) now use OtherQueryBuilder - Updated OpenRouter to delegate to OtherQueryBuilder instead of OpenAIQueryBuilder This prepares the codebase for adding websearch tool support using the Responses API. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * feat(ai): add websearch as AI agent tool type - Added WebsearchToolValue to ToolValue enum in flows.rs - Updated all pattern matches to handle websearch tool type - Added has_websearch parameter to run_agent function - Websearch tools don't require additional configuration This prepares the backend for provider-specific websearch implementations. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * feat(frontend): add websearch as tool option in AI agent UI - Added WebsearchTool type and utility functions to agentToolUtils.ts - Added "Web Search" option in tool insertion menu (InsertModuleInner) - Updated NewAIToolNode to handle pickWebsearchTool event - Updated AIToolNode to render websearch tools properly - Updated FlowModuleSchemaMap to create websearch tools Users can now add websearch tools to AI agents through the UI. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * feat(ai): implement websearch for OpenAI provider - Added has_websearch parameter to BuildRequestArgs - OpenAI provider now adds web_search tool to requests when enabled - Uses OpenAI Responses API web_search tool type - Websearch tool is added before other custom tools in the request Implements websearch functionality for OpenAI and Azure OpenAI providers. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * feat(ai): implement websearch for Anthropic provider - Created anthropic.rs provider with native Anthropic API format - Added web_search tool to Anthropic requests when enabled - Anthropic uses /messages endpoint with x-api-key authentication - Updated query_builder to route Anthropic to new provider Implements websearch functionality for Anthropic Claude models. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * feat(ai): implement websearch for Gemini/GoogleAI provider - GoogleAI now uses completion endpoint (other.rs) for text instead of responses API - Added Google Search grounding when websearch is enabled - Uses google_search_retrieval tool in request when has_websearch is true - Updated parse methods to use OtherQueryBuilder for completion endpoint Implements websearch functionality for Google Gemini models. Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> * fix frontend * fix anthropic and openai * better for gemini * structured output * cleaning * fix validate tool * fixes * cleaning * cleaning * fix for openai * no responses api for azure * fixes * fix * add tests for ai agent * avoid panic * better tests * test user images * fix tool choice * always use streaming backend side * big cleaning * show annotations plus agent action for open ai websearch use * show annotations plus agent action for anthropic websearch use * show annotations plus agent action for google websearch use * nit forntend * rm * fix * add test for image ouptut * fix for azure * add in openflow * fix * fix * nit tests * fixes --------- Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com> Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com> Co-authored-by: centdix <farhadg110@gmail.com>
181 lines
5.9 KiB
Python
181 lines
5.9 KiB
Python
"""
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Streaming tests for AI agents.
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Tests that AI agents correctly handle streaming responses:
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- Streaming enabled returns wm_stream with valid events
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- Streaming with tools includes tool-related events
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- Streaming disabled does not return wm_stream
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"""
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import json
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import pytest
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from .conftest import AIAgentTestClient, create_ai_agent_flow, create_rawscript_tool
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from .providers import ALL_PROVIDERS
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def get_provider_ids(providers: list) -> list[str]:
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"""Get provider names for pytest parametrization IDs."""
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return [p["name"] for p in providers]
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# Inline script for sum tool (Bun/TypeScript)
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ADD_NUMBERS_SCRIPT = """
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export function main(a: number, b: number): number {
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return a + b;
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}
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"""
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def parse_streaming_events(wm_stream: str) -> list[dict]:
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"""Parse newline-delimited JSON events from wm_stream."""
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events = []
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for line in wm_stream.strip().split("\n"):
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if line:
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events.append(json.loads(line))
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return events
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class TestStreaming:
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"""Test AI agent streaming functionality."""
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@pytest.mark.parametrize(
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"provider_config",
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ALL_PROVIDERS,
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ids=get_provider_ids(ALL_PROVIDERS),
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)
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def test_streaming_enabled(
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self,
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client: AIAgentTestClient,
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setup_providers,
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provider_config,
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):
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"""
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Test that streaming enabled returns wm_stream with valid events.
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"""
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flow_value = create_ai_agent_flow(
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provider_input_transform=provider_config["input_transform"],
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system_prompt="You are a helpful assistant. Answer concisely.",
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streaming=True,
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)
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result = client.run_preview_flow(
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flow_value=flow_value,
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args={"user_message": "What is 2 + 2? Just say the number."},
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)
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assert result is not None
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assert "wm_stream" in result, f"Expected 'wm_stream' in result: {result}"
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wm_stream = result["wm_stream"]
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assert wm_stream is not None and wm_stream != "", "wm_stream should not be empty"
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# Parse and validate events
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events = parse_streaming_events(wm_stream)
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assert len(events) > 0, "Expected at least one streaming event"
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# Check that events have valid types (snake_case format)
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valid_types = {"token_delta", "tool_call", "tool_call_arguments", "tool_execution", "tool_result"}
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for event in events:
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assert "type" in event, f"Event missing 'type' field: {event}"
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assert event["type"] in valid_types, f"Invalid event type: {event['type']}"
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# For a simple response without tools, we expect token_delta events
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token_events = [e for e in events if e["type"] == "token_delta"]
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assert len(token_events) > 0, "Expected at least one TokenDelta event"
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print(f"Streaming result from {provider_config['name']}: {len(events)} events")
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@pytest.mark.parametrize(
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"provider_config",
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ALL_PROVIDERS,
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ids=get_provider_ids(ALL_PROVIDERS),
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)
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def test_streaming_with_tool(
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self,
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client: AIAgentTestClient,
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setup_providers,
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provider_config,
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):
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"""
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Test that streaming with a tool includes tool-related events.
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"""
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tools = [
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create_rawscript_tool(
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tool_id="add_numbers",
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content=ADD_NUMBERS_SCRIPT,
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params=["a", "b"],
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language="bun",
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)
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]
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flow_value = create_ai_agent_flow(
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provider_input_transform=provider_config["input_transform"],
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system_prompt="You are a helpful assistant. Use the add_numbers tool to perform arithmetic.",
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tools=tools,
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streaming=True,
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)
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result = client.run_preview_flow(
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flow_value=flow_value,
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args={"user_message": "What is 5 + 7? Use the add_numbers tool."},
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)
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assert result is not None
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assert "wm_stream" in result, f"Expected 'wm_stream' in result: {result}"
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wm_stream = result["wm_stream"]
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assert wm_stream is not None and wm_stream != "", "wm_stream should not be empty"
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# Parse and validate events
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events = parse_streaming_events(wm_stream)
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assert len(events) > 0, "Expected at least one streaming event"
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# With a tool call, we expect tool-related events
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event_types = {e["type"] for e in events}
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# Should have at least some of the tool events (snake_case format)
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tool_event_types = {"tool_call", "tool_call_arguments", "tool_execution", "tool_result"}
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has_tool_events = bool(event_types & tool_event_types)
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assert has_tool_events, f"Expected tool events, got: {event_types}"
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print(f"Streaming with tool result from {provider_config['name']}: {event_types}")
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@pytest.mark.parametrize(
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"provider_config",
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ALL_PROVIDERS,
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ids=get_provider_ids(ALL_PROVIDERS),
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)
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def test_streaming_disabled(
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self,
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client: AIAgentTestClient,
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setup_providers,
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provider_config,
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):
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"""
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Test that streaming disabled does not return wm_stream.
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"""
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flow_value = create_ai_agent_flow(
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provider_input_transform=provider_config["input_transform"],
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system_prompt="You are a helpful assistant. Answer concisely.",
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streaming=False,
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)
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result = client.run_preview_flow(
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flow_value=flow_value,
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args={"user_message": "What is 2 + 2? Just say the number."},
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)
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assert result is not None
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# wm_stream should not be present or should be empty/null
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wm_stream = result.get("wm_stream")
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assert wm_stream is None, f"Expected no wm_stream when disabled"
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print(f"Non-streaming result from {provider_config['name']}: no wm_stream (as expected)")
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if __name__ == "__main__":
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pytest.main([__file__, "-v", "-s"])
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