restructure cli (#656)

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Adil Hafeez 2025-12-25 14:55:29 -08:00 committed by GitHub
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45 changed files with 153 additions and 115 deletions

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@ -0,0 +1,475 @@
import json
import pytest
from unittest import mock
import sys
from planoai.config_generator import validate_and_render_schema
# Patch sys.path to allow import from cli/
import os
sys.path.insert(
0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "cli"))
)
@pytest.fixture(autouse=True)
def cleanup_env(monkeypatch):
# Clean up environment variables and mocks after each test
yield
monkeypatch.undo()
def test_validate_and_render_happy_path(monkeypatch):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: openai/gpt-4o-mini
access_key: $OPENAI_API_KEY
default: true
- model: openai/gpt-4o
access_key: $OPENAI_API_KEY
routing_preferences:
- name: code understanding
description: understand and explain existing code snippets, functions, or libraries
- model: openai/gpt-4.1
access_key: $OPENAI_API_KEY
routing_preferences:
- name: code generation
description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
tracing:
random_sampling: 100
"""
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
# Removed empty read - was causing validation failures
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):
validate_and_render_schema()
def test_validate_and_render_happy_path_agent_config(monkeypatch):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = """
version: v0.3.0
agents:
- id: query_rewriter
url: http://localhost:10500
- id: context_builder
url: http://localhost:10501
- id: response_generator
url: http://localhost:10502
- id: research_agent
url: http://localhost:10500
- id: input_guard_rails
url: http://localhost:10503
listeners:
- name: tmobile
type: agent
router: plano_orchestrator_v1
agents:
- name: simple_tmobile_rag_agent
description: t-mobile virtual assistant for device contracts.
filter_chain:
- query_rewriter
- context_builder
- response_generator
- name: research_agent
description: agent to research and gather information from various sources.
filter_chain:
- research_agent
- response_generator
port: 8000
- name: llm_provider
type: model
description: llm provider configuration
port: 12000
llm_providers:
- access_key: ${OPENAI_API_KEY}
model: openai/gpt-4o
"""
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
# Removed empty read - was causing validation failures
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):
validate_and_render_schema()
arch_config_test_cases = [
{
"id": "duplicate_provider_name",
"expected_error": "Duplicate model_provider name",
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- name: test1
model: openai/gpt-4o
access_key: $OPENAI_API_KEY
- name: test1
model: openai/gpt-4o
access_key: $OPENAI_API_KEY
""",
},
{
"id": "provider_interface_with_model_id",
"expected_error": "Please provide provider interface as part of model name",
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: openai/gpt-4o
access_key: $OPENAI_API_KEY
provider_interface: openai
""",
},
{
"id": "duplicate_model_id",
"expected_error": "Duplicate model_id",
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: openai/gpt-4o
access_key: $OPENAI_API_KEY
- model: mistral/gpt-4o
""",
},
{
"id": "custom_provider_base_url",
"expected_error": "Must provide base_url and provider_interface",
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: custom/gpt-4o
""",
},
{
"id": "base_url_with_path_prefix",
"expected_error": None,
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: custom/gpt-4o
base_url: "http://custom.com/api/v2"
provider_interface: openai
""",
},
{
"id": "duplicate_routeing_preference_name",
"expected_error": "Duplicate routing preference name",
"arch_config": """
version: v0.1.0
listeners:
egress_traffic:
address: 0.0.0.0
port: 12000
message_format: openai
timeout: 30s
llm_providers:
- model: openai/gpt-4o-mini
access_key: $OPENAI_API_KEY
default: true
- model: openai/gpt-4o
access_key: $OPENAI_API_KEY
routing_preferences:
- name: code understanding
description: understand and explain existing code snippets, functions, or libraries
- model: openai/gpt-4.1
access_key: $OPENAI_API_KEY
routing_preferences:
- name: code understanding
description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
tracing:
random_sampling: 100
""",
},
]
@pytest.mark.parametrize(
"arch_config_test_case",
arch_config_test_cases,
ids=[case["id"] for case in arch_config_test_cases],
)
def test_validate_and_render_schema_tests(monkeypatch, arch_config_test_case):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = arch_config_test_case["arch_config"]
expected_error = arch_config_test_case.get("expected_error")
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
mock.mock_open(
read_data=arch_config
).return_value, # validate_prompt_config: ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # validate_prompt_config: ARCH_CONFIG_SCHEMA_FILE
mock.mock_open(
read_data=arch_config
).return_value, # validate_and_render_schema: ARCH_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # validate_and_render_schema: ARCH_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):
if expected_error:
# Test expects an error
with pytest.raises(Exception) as excinfo:
validate_and_render_schema()
assert expected_error in str(excinfo.value)
else:
# Test expects success - no exception should be raised
validate_and_render_schema()
def test_convert_legacy_llm_providers():
from planoai.utils import convert_legacy_listeners
listeners = {
"ingress_traffic": {
"address": "0.0.0.0",
"port": 10000,
"timeout": "30s",
},
"egress_traffic": {
"address": "0.0.0.0",
"port": 12000,
"timeout": "30s",
},
}
llm_providers = [
{
"model": "openai/gpt-4o",
"access_key": "test_key",
}
]
updated_providers, llm_gateway, prompt_gateway = convert_legacy_listeners(
listeners, llm_providers
)
assert isinstance(updated_providers, list)
assert llm_gateway is not None
assert prompt_gateway is not None
print(json.dumps(updated_providers))
assert updated_providers == [
{
"name": "egress_traffic",
"type": "model_listener",
"port": 12000,
"address": "0.0.0.0",
"timeout": "30s",
"model_providers": [{"model": "openai/gpt-4o", "access_key": "test_key"}],
},
{
"name": "ingress_traffic",
"type": "prompt_listener",
"port": 10000,
"address": "0.0.0.0",
"timeout": "30s",
},
]
assert llm_gateway == {
"address": "0.0.0.0",
"model_providers": [
{
"access_key": "test_key",
"model": "openai/gpt-4o",
},
],
"name": "egress_traffic",
"type": "model_listener",
"port": 12000,
"timeout": "30s",
}
assert prompt_gateway == {
"address": "0.0.0.0",
"name": "ingress_traffic",
"port": 10000,
"timeout": "30s",
"type": "prompt_listener",
}
def test_convert_legacy_llm_providers_no_prompt_gateway():
from planoai.utils import convert_legacy_listeners
listeners = {
"egress_traffic": {
"address": "0.0.0.0",
"port": 12000,
"timeout": "30s",
}
}
llm_providers = [
{
"model": "openai/gpt-4o",
"access_key": "test_key",
}
]
updated_providers, llm_gateway, prompt_gateway = convert_legacy_listeners(
listeners, llm_providers
)
assert isinstance(updated_providers, list)
assert llm_gateway is not None
assert prompt_gateway is not None
assert updated_providers == [
{
"address": "0.0.0.0",
"model_providers": [
{
"access_key": "test_key",
"model": "openai/gpt-4o",
},
],
"name": "egress_traffic",
"port": 12000,
"timeout": "30s",
"type": "model_listener",
}
]
assert llm_gateway == {
"address": "0.0.0.0",
"model_providers": [
{
"access_key": "test_key",
"model": "openai/gpt-4o",
},
],
"name": "egress_traffic",
"type": "model_listener",
"port": 12000,
"timeout": "30s",
}