apunkt/trustgraph
1
0
Fork 0
mirror of https://github.com/trustgraph-ai/trustgraph.git synced 2026-04-28 18:06:21 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions 1

Streaming LLM part 2 (#567)

Browse source 
* Updates for agent API with streaming support

* Added tg-dump-queues tool to dump Pulsar queues to a log

* Updated tg-invoke-agent, incremental output

* Queue dumper CLI - might be useful for debug

* Updating for tests
This commit is contained in:
cybermaggedon 2025-11-26 15:16:17 +00:00 • committed by GitHub
parent 310a2deb06
commit b1cc724f7d
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
8 changed files with 609 additions and 51 deletions
Download patch file Download diff file Expand all files Collapse all files

16
tests/integration/test_agent_manager_integration.py
View file

@ -135,10 +135,10 @@ Args: {
# Verify prompt client was called correctly
prompt_client = mock_flow_context("prompt-request")
prompt_client.agent_react.assert_called_once()
# Verify the prompt variables passed to agent_react
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
assert variables["question"] == question
assert len(variables["tools"]) == 3 # knowledge_query, text_completion, web_search
assert variables["context"] == "You are a helpful AI assistant with access to knowledge and tools."
@ -237,7 +237,7 @@ Final Answer: Machine learning is a branch of artificial intelligence."""
# Verify history was included in prompt variables
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
assert len(variables["history"]) == 1
assert variables["history"][0]["thought"] == "I need to search for information about machine learning"
assert variables["history"][0]["action"] == "knowledge_query"
@ -337,7 +337,7 @@ Args: {
# Verify tool information was passed to prompt
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
# Should have all 3 tools available
tool_names = [tool["name"] for tool in variables["tools"]]
@ -408,7 +408,7 @@ Args: {args_json}"""
# Assert
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
assert variables["context"] == "You are an expert in machine learning research."
assert variables["question"] == question
@ -427,7 +427,7 @@ Args: {args_json}"""
# Assert
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
assert len(variables["tools"]) == 0
assert variables["tool_names"] == ""
@ -682,7 +682,7 @@ Final Answer: {
# Verify history was processed correctly
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
assert len(variables["history"]) == 50
@pytest.mark.asyncio
@ -709,7 +709,7 @@ Final Answer: {
# Verify JSON was properly serialized in prompt
prompt_client = mock_flow_context("prompt-request")
call_args = prompt_client.agent_react.call_args
variables = call_args[0][0]
variables = call_args.kwargs['variables']
# Should not raise JSON serialization errors
json_str = json.dumps(variables, indent=4)