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Refactor LLM instantiation across agents and orchestrator

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- Replaced direct instantiation of ChatOpenAI with a centralized get_llm function in CheckpointAgent, NoteAgent, ProjectAgent, and TaskAgent.
- Introduced a new llm.py module to handle LLM model instantiation and API key management.
- Updated settings.py to include LLM_MODEL and LLM_ROUTER_MODEL configurations.
- Modified orchestrator.py to use get_router_llm for intent classification.
- Updated requirements.txt to include litellm for LLM management.
- Adjusted tests to mock get_llm instead of ChatOpenAI directly.
This commit is contained in:
roberto
2026-03-03 15:46:44 +01:00
parent 480e7ac5bd
commit 8bfce9da00
11 changed files with 830 additions and 50 deletions
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40
tests/test_orchestrator.py
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@@ -87,21 +87,21 @@ def reg() -> AgentRegistry:
class TestClassifyIntent:
@pytest.mark.asyncio
async def test_routes_to_known_agent(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
result = await classify_intent("add a task", {}, reg)
assert result == "task_agent"
@pytest.mark.asyncio
async def test_routes_to_calendar_agent(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("calendar_agent")
result = await classify_intent("schedule a meeting", {}, reg)
assert result == "calendar_agent"
@pytest.mark.asyncio
async def test_falls_back_on_unknown_name(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("nonexistent_agent")
result = await classify_intent("do something", {}, reg)
assert result == "task_agent"
@@ -110,14 +110,14 @@ class TestClassifyIntent:
async def test_empty_registry_returns_fallback_without_llm_call(self) -> None:
empty_reg = AgentRegistry()
# No LLM should be instantiated — early return path
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
result = await classify_intent("anything", {}, empty_reg)
mock_cls.assert_not_called()
assert result == "task_agent"
@pytest.mark.asyncio
async def test_whitespace_stripped_from_response(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm(" task_agent \n")
result = await classify_intent("create task", {}, reg)
assert result == "task_agent"
@@ -154,7 +154,7 @@ class TestRouteSingle:
class TestRoutePipeline:
@pytest.mark.asyncio
async def test_returns_chat_response(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("synthesized result")
result = await route_pipeline(
["task_agent", "calendar_agent"], "plan my week", {}, reg
@@ -163,7 +163,7 @@ class TestRoutePipeline:
@pytest.mark.asyncio
async def test_response_is_synthesis_output(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("synthesized result")
result = await route_pipeline(
["task_agent", "calendar_agent"], "plan my week", {}, reg
@@ -193,7 +193,7 @@ class TestRoutePipeline:
reg.register(_CapturingAgent)
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("done")
await route_pipeline(["task_agent", "capture"], "hi", {}, reg)
@@ -204,7 +204,7 @@ class TestRoutePipeline:
@pytest.mark.asyncio
async def test_single_agent_pipeline(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("single result")
result = await route_pipeline(["task_agent"], "one agent", {}, reg)
assert result.response == "single result"
@@ -218,7 +218,7 @@ class TestOrchestrate:
async def test_direct_mode_returns_chat_response(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="add a task", execution_mode="direct")
result = await orchestrate(request, reg)
@@ -226,7 +226,7 @@ class TestOrchestrate:
@pytest.mark.asyncio
async def test_direct_mode_response_content(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="add a task", execution_mode="direct")
result = await orchestrate(request, reg)
@@ -237,7 +237,7 @@ class TestOrchestrate:
async def test_plan_mode_returns_execution_plan(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="plan my tasks", execution_mode="plan")
result = await orchestrate(request, reg)
@@ -247,7 +247,7 @@ class TestOrchestrate:
async def test_plan_mode_agent_matches_classified(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("calendar_agent")
request = ChatRequest(
message="schedule something", execution_mode="plan"
@@ -258,7 +258,7 @@ class TestOrchestrate:
@pytest.mark.asyncio
async def test_plan_mode_has_steps(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="plan tasks", execution_mode="plan")
result = await orchestrate(request, reg)
@@ -269,7 +269,7 @@ class TestOrchestrate:
async def test_plan_mode_template_id_contains_agent_name(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="plan tasks", execution_mode="plan")
result = await orchestrate(request, reg)
@@ -281,7 +281,7 @@ class TestOrchestrate:
async def test_default_execution_mode_is_direct(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
# execution_mode defaults to "direct"
request = ChatRequest(message="help me")
@@ -295,7 +295,7 @@ class TestOrchestrate:
class TestOrchestrateStream:
@pytest.mark.asyncio
async def test_yields_at_least_one_chunk(self, reg: AgentRegistry) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="add a task", execution_mode="direct")
chunks = [chunk async for chunk in orchestrate_stream(request, reg)]
@@ -305,7 +305,7 @@ class TestOrchestrateStream:
async def test_last_chunk_is_final_json_frame(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="add a task", execution_mode="direct")
chunks = [chunk async for chunk in orchestrate_stream(request, reg)]
@@ -319,7 +319,7 @@ class TestOrchestrateStream:
async def test_final_frame_response_matches_agent_output(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(message="create a task", execution_mode="direct")
chunks = [chunk async for chunk in orchestrate_stream(request, reg)]
@@ -331,7 +331,7 @@ class TestOrchestrateStream:
async def test_text_chunks_before_final_frame(
self, reg: AgentRegistry
) -> None:
with patch("app.core.orchestrator.ChatOpenAI") as mock_cls:
with patch("app.core.orchestrator._make_llm") as mock_cls:
mock_cls.return_value = _mock_llm("task_agent")
request = ChatRequest(
message="x" * 200, execution_mode="direct"