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feat(agent-runner): add plugin runner host integration

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This commit is contained in:
huanghuoguoguo
2026-06-20 10:18:52 +08:00
parent d22fa82d7c
commit cede35b31b
129 changed files with 26980 additions and 6209 deletions
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tests/unit_tests/provider/test_requester_base.py
+108
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@@ -302,6 +302,59 @@ async def test_runtime_provider_invoke_llm_delegates(runtime_provider, runtime_l
assert result.role == 'assistant'
@pytest.mark.asyncio
async def test_runtime_provider_invoke_llm_stashes_usage(runtime_provider, runtime_llm_model):
"""RuntimeProvider preserves requester usage for upstream action handlers."""
provider = runtime_provider
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
query = pipeline_query.Query.model_construct(
query_id='test-query-usage',
launcher_type='person',
launcher_id=12345,
sender_id=12345,
message_chain=None,
message_event=None,
adapter=None,
pipeline_uuid='pipeline-uuid',
bot_uuid='bot-uuid',
pipeline_config={'ai': {}, 'output': {}, 'trigger': {}},
session=None,
prompt=None,
messages=[],
user_message=None,
use_funcs=[],
use_llm_model_uuid=None,
variables={},
resp_messages=[],
resp_message_chain=None,
current_stage_name=None,
)
usage = {
'prompt_tokens': 11,
'completion_tokens': 7,
'total_tokens': 18,
'prompt_tokens_details': {'cached_tokens': 3},
}
provider.requester.invoke_llm = AsyncMock(
return_value=(
provider_message.Message(role='assistant', content='ok'),
usage,
)
)
result = await provider.invoke_llm(
query,
runtime_llm_model,
[provider_message.Message(role='user', content='Hello')],
)
assert result.content == 'ok'
assert query.variables[requester.LLM_USAGE_QUERY_VARIABLE] == usage
@pytest.mark.asyncio
async def test_runtime_provider_invoke_llm_stream_yields_chunks(runtime_provider, runtime_llm_model):
"""Test RuntimeProvider.invoke_llm_stream yields chunks from requester."""
@@ -345,6 +398,61 @@ async def test_runtime_provider_invoke_llm_stream_yields_chunks(runtime_provider
assert chunks[0].role == 'assistant'
@pytest.mark.asyncio
async def test_runtime_provider_invoke_llm_stream_stashes_usage(runtime_provider, runtime_llm_model):
"""RuntimeProvider transfers captured stream usage to the public query usage key."""
provider = runtime_provider
import langbot_plugin.api.entities.builtin.provider.message as provider_message
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
query = pipeline_query.Query.model_construct(
query_id='test-stream-usage',
launcher_type='person',
launcher_id=12345,
sender_id=12345,
message_chain=None,
message_event=None,
adapter=None,
pipeline_uuid='pipeline-uuid',
bot_uuid='bot-uuid',
pipeline_config={'ai': {}, 'output': {}, 'trigger': {}},
session=None,
prompt=None,
messages=[],
user_message=None,
use_funcs=[],
use_llm_model_uuid=None,
variables={},
resp_messages=[],
resp_message_chain=None,
current_stage_name=None,
)
usage = {
'prompt_tokens': 13,
'completion_tokens': 2,
'total_tokens': 15,
}
async def fake_stream(**kwargs):
kwargs['query'].variables[requester.LLM_USAGE_QUERY_VARIABLE] = usage
yield provider_message.MessageChunk(role='assistant', content='ok')
provider.requester.invoke_llm_stream = fake_stream
chunks = [
chunk
async for chunk in provider.invoke_llm_stream(
query,
runtime_llm_model,
[provider_message.Message(role='user', content='Hello')],
)
]
assert len(chunks) == 1
assert query.variables[requester.LLM_USAGE_QUERY_VARIABLE] == usage
@pytest.mark.asyncio
async def test_runtime_provider_invoke_embedding_returns_vectors(runtime_provider, runtime_embedding_model):
"""Test RuntimeProvider.invoke_embedding returns embedding vectors."""