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Feat/assistant app (#2086)

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Co-authored-by: chenhe <guchenhe@gmail.com>
Co-authored-by: Pascal M <11357019+perzeuss@users.noreply.github.com>
This commit is contained in:
Yeuoly
2024-01-23 19:58:23 +08:00
committed by GitHub
parent 7bbe12b2bd
commit 86286e1ac8
175 changed files with 11619 additions and 1235 deletions
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180
api/core/application_manager.py
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@@ -4,7 +4,7 @@ import threading
import uuid
from typing import Any, Generator, Optional, Tuple, Union, cast
from core.app_runner.agent_app_runner import AgentApplicationRunner
from core.app_runner.assistant_app_runner import AssistantApplicationRunner
from core.app_runner.basic_app_runner import BasicApplicationRunner
from core.app_runner.generate_task_pipeline import GenerateTaskPipeline
from core.application_queue_manager import ApplicationQueueManager, ConversationTaskStoppedException, PublishFrom
@@ -13,7 +13,7 @@ from core.entities.application_entities import (AdvancedChatPromptTemplateEntity
ApplicationGenerateEntity, AppOrchestrationConfigEntity, DatasetEntity,
DatasetRetrieveConfigEntity, ExternalDataVariableEntity,
FileUploadEntity, InvokeFrom, ModelConfigEntity, PromptTemplateEntity,
SensitiveWordAvoidanceEntity)
SensitiveWordAvoidanceEntity, AgentPromptEntity)
from core.entities.model_entities import ModelStatus
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
from core.file.file_obj import FileObj
@@ -23,6 +23,7 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeErr
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
from core.prompt.prompt_template import PromptTemplateParser
from core.provider_manager import ProviderManager
from core.tools.prompt.template import REACT_PROMPT_TEMPLATES
from extensions.ext_database import db
from flask import Flask, current_app
from models.account import Account
@@ -93,6 +94,9 @@ class ApplicationManager:
extras=extras
)
if not stream and application_generate_entity.app_orchestration_config_entity.agent:
raise ValueError("Agent app is not supported in blocking mode.")
# init generate records
(
conversation,
@@ -151,7 +155,7 @@ class ApplicationManager:
if application_generate_entity.app_orchestration_config_entity.agent:
# agent app
runner = AgentApplicationRunner()
runner = AssistantApplicationRunner()
runner.run(
application_generate_entity=application_generate_entity,
queue_manager=queue_manager,
@@ -354,6 +358,8 @@ class ApplicationManager:
# external data variables
properties['external_data_variables'] = []
# old external_data_tools
external_data_tools = copy_app_model_config_dict.get('external_data_tools', [])
for external_data_tool in external_data_tools:
if 'enabled' not in external_data_tool or not external_data_tool['enabled']:
@@ -366,6 +372,19 @@ class ApplicationManager:
config=external_data_tool['config']
)
)
# current external_data_tools
for variable in copy_app_model_config_dict.get('user_input_form', []):
typ = list(variable.keys())[0]
if typ == 'external_data_tool':
val = variable[typ]
properties['external_data_variables'].append(
ExternalDataVariableEntity(
variable=val['variable'],
type=val['type'],
config=val['config']
)
)
# show retrieve source
show_retrieve_source = False
@@ -375,15 +394,64 @@ class ApplicationManager:
show_retrieve_source = True
properties['show_retrieve_source'] = show_retrieve_source
dataset_ids = []
if 'datasets' in copy_app_model_config_dict.get('dataset_configs', {}):
datasets = copy_app_model_config_dict.get('dataset_configs', {}).get('datasets', {
'strategy': 'router',
'datasets': []
})
for dataset in datasets.get('datasets', []):
keys = list(dataset.keys())
if len(keys) == 0 or keys[0] != 'dataset':
continue
dataset = dataset['dataset']
if 'enabled' not in dataset or not dataset['enabled']:
continue
dataset_id = dataset.get('id', None)
if dataset_id:
dataset_ids.append(dataset_id)
else:
datasets = {'strategy': 'router', 'datasets': []}
if 'agent_mode' in copy_app_model_config_dict and copy_app_model_config_dict['agent_mode'] \
and 'enabled' in copy_app_model_config_dict['agent_mode'] and copy_app_model_config_dict['agent_mode'][
'enabled']:
agent_dict = copy_app_model_config_dict.get('agent_mode')
agent_strategy = agent_dict.get('strategy', 'router')
if agent_strategy in ['router', 'react_router']:
dataset_ids = []
for tool in agent_dict.get('tools', []):
agent_dict = copy_app_model_config_dict.get('agent_mode', {})
agent_strategy = agent_dict.get('strategy', 'cot')
if agent_strategy == 'function_call':
strategy = AgentEntity.Strategy.FUNCTION_CALLING
elif agent_strategy == 'cot' or agent_strategy == 'react':
strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
else:
# old configs, try to detect default strategy
if copy_app_model_config_dict['model']['provider'] == 'openai':
strategy = AgentEntity.Strategy.FUNCTION_CALLING
else:
strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
agent_tools = []
for tool in agent_dict.get('tools', []):
keys = tool.keys()
if len(keys) >= 4:
if "enabled" not in tool or not tool["enabled"]:
continue
agent_tool_properties = {
'provider_type': tool['provider_type'],
'provider_id': tool['provider_id'],
'tool_name': tool['tool_name'],
'tool_parameters': tool['tool_parameters'] if 'tool_parameters' in tool else {}
}
agent_tools.append(AgentToolEntity(**agent_tool_properties))
elif len(keys) == 1:
# old standard
key = list(tool.keys())[0]
if key != 'dataset':
@@ -397,58 +465,57 @@ class ApplicationManager:
dataset_id = tool_item['id']
dataset_ids.append(dataset_id)
dataset_configs = copy_app_model_config_dict.get('dataset_configs', {'retrieval_model': 'single'})
query_variable = copy_app_model_config_dict.get('dataset_query_variable')
if dataset_configs['retrieval_model'] == 'single':
properties['dataset'] = DatasetEntity(
dataset_ids=dataset_ids,
retrieve_config=DatasetRetrieveConfigEntity(
query_variable=query_variable,
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
dataset_configs['retrieval_model']
),
single_strategy=agent_strategy
)
)
else:
properties['dataset'] = DatasetEntity(
dataset_ids=dataset_ids,
retrieve_config=DatasetRetrieveConfigEntity(
query_variable=query_variable,
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
dataset_configs['retrieval_model']
),
top_k=dataset_configs.get('top_k'),
score_threshold=dataset_configs.get('score_threshold'),
reranking_model=dataset_configs.get('reranking_model')
)
)
agent_prompt = agent_dict.get('prompt', None) or {}
# check model mode
model_mode = copy_app_model_config_dict.get('model', {}).get('mode', 'completion')
if model_mode == 'completion':
agent_prompt_entity = AgentPromptEntity(
first_prompt=agent_prompt.get('first_prompt', REACT_PROMPT_TEMPLATES['english']['completion']['prompt']),
next_iteration=agent_prompt.get('next_iteration', REACT_PROMPT_TEMPLATES['english']['completion']['agent_scratchpad']),
)
else:
if agent_strategy == 'react':
strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
else:
strategy = AgentEntity.Strategy.FUNCTION_CALLING
agent_prompt_entity = AgentPromptEntity(
first_prompt=agent_prompt.get('first_prompt', REACT_PROMPT_TEMPLATES['english']['chat']['prompt']),
next_iteration=agent_prompt.get('next_iteration', REACT_PROMPT_TEMPLATES['english']['chat']['agent_scratchpad']),
)
agent_tools = []
for tool in agent_dict.get('tools', []):
key = list(tool.keys())[0]
tool_item = tool[key]
properties['agent'] = AgentEntity(
provider=properties['model_config'].provider,
model=properties['model_config'].model,
strategy=strategy,
prompt=agent_prompt_entity,
tools=agent_tools,
max_iteration=agent_dict.get('max_iteration', 5)
)
agent_tool_properties = {
"tool_id": key
}
if len(dataset_ids) > 0:
# dataset configs
dataset_configs = copy_app_model_config_dict.get('dataset_configs', {'retrieval_model': 'single'})
query_variable = copy_app_model_config_dict.get('dataset_query_variable')
if "enabled" not in tool_item or not tool_item["enabled"]:
continue
agent_tool_properties["config"] = tool_item
agent_tools.append(AgentToolEntity(**agent_tool_properties))
properties['agent'] = AgentEntity(
provider=properties['model_config'].provider,
model=properties['model_config'].model,
strategy=strategy,
tools=agent_tools
if dataset_configs['retrieval_model'] == 'single':
properties['dataset'] = DatasetEntity(
dataset_ids=dataset_ids,
retrieve_config=DatasetRetrieveConfigEntity(
query_variable=query_variable,
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
dataset_configs['retrieval_model']
),
single_strategy=datasets.get('strategy', 'router')
)
)
else:
properties['dataset'] = DatasetEntity(
dataset_ids=dataset_ids,
retrieve_config=DatasetRetrieveConfigEntity(
query_variable=query_variable,
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
dataset_configs['retrieval_model']
),
top_k=dataset_configs.get('top_k'),
score_threshold=dataset_configs.get('score_threshold'),
reranking_model=dataset_configs.get('reranking_model')
)
)
# file upload
@@ -601,6 +668,7 @@ class ApplicationManager:
message_id=message.id,
type=file.type.value,
transfer_method=file.transfer_method.value,
belongs_to='user',
url=file.url,
upload_file_id=file.upload_file_id,
created_by_role=('account' if account_id else 'end_user'),