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Refactor/react agent (#3355)

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Yeuoly
2024-04-11 18:34:17 +08:00
committed by GitHub
parent 509c640a80
commit cea107b165
9 changed files with 589 additions and 511 deletions
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81
api/core/app/apps/agent_chat/app_runner.py
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@@ -1,7 +1,8 @@
import logging
from typing import cast
from core.agent.cot_agent_runner import CotAgentRunner
from core.agent.cot_chat_agent_runner import CotChatAgentRunner
from core.agent.cot_completion_agent_runner import CotCompletionAgentRunner
from core.agent.entities import AgentEntity
from core.agent.fc_agent_runner import FunctionCallAgentRunner
from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
@@ -11,8 +12,8 @@ from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, Mo
from core.app.entities.queue_entities import QueueAnnotationReplyEvent
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance
from core.model_runtime.entities.llm_entities import LLMUsage
from core.model_runtime.entities.model_entities import ModelFeature
from core.model_runtime.entities.llm_entities import LLMMode, LLMUsage
from core.model_runtime.entities.model_entities import ModelFeature, ModelPropertyKey
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
from core.moderation.base import ModerationException
from core.tools.entities.tool_entities import ToolRuntimeVariablePool
@@ -207,48 +208,40 @@ class AgentChatAppRunner(AppRunner):
# start agent runner
if agent_entity.strategy == AgentEntity.Strategy.CHAIN_OF_THOUGHT:
assistant_cot_runner = CotAgentRunner(
tenant_id=app_config.tenant_id,
application_generate_entity=application_generate_entity,
conversation=conversation,
app_config=app_config,
model_config=application_generate_entity.model_config,
config=agent_entity,
queue_manager=queue_manager,
message=message,
user_id=application_generate_entity.user_id,
memory=memory,
prompt_messages=prompt_message,
variables_pool=tool_variables,
db_variables=tool_conversation_variables,
model_instance=model_instance
)
invoke_result = assistant_cot_runner.run(
message=message,
query=query,
inputs=inputs,
)
# check LLM mode
if model_schema.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value:
runner_cls = CotChatAgentRunner
elif model_schema.model_properties.get(ModelPropertyKey.MODE) == LLMMode.COMPLETION.value:
runner_cls = CotCompletionAgentRunner
else:
raise ValueError(f"Invalid LLM mode: {model_schema.model_properties.get(ModelPropertyKey.MODE)}")
elif agent_entity.strategy == AgentEntity.Strategy.FUNCTION_CALLING:
assistant_fc_runner = FunctionCallAgentRunner(
tenant_id=app_config.tenant_id,
application_generate_entity=application_generate_entity,
conversation=conversation,
app_config=app_config,
model_config=application_generate_entity.model_config,
config=agent_entity,
queue_manager=queue_manager,
message=message,
user_id=application_generate_entity.user_id,
memory=memory,
prompt_messages=prompt_message,
variables_pool=tool_variables,
db_variables=tool_conversation_variables,
model_instance=model_instance
)
invoke_result = assistant_fc_runner.run(
message=message,
query=query,
)
runner_cls = FunctionCallAgentRunner
else:
raise ValueError(f"Invalid agent strategy: {agent_entity.strategy}")
runner = runner_cls(
tenant_id=app_config.tenant_id,
application_generate_entity=application_generate_entity,
conversation=conversation,
app_config=app_config,
model_config=application_generate_entity.model_config,
config=agent_entity,
queue_manager=queue_manager,
message=message,
user_id=application_generate_entity.user_id,
memory=memory,
prompt_messages=prompt_message,
variables_pool=tool_variables,
db_variables=tool_conversation_variables,
model_instance=model_instance
)
invoke_result = runner.run(
message=message,
query=query,
inputs=inputs,
)
# handle invoke result
self._handle_invoke_result(