From a1b715656c8ef15e965184f4b7a19ec4de774ec6 Mon Sep 17 00:00:00 2001 From: wangyijunlyy <1157637345@qq.com> Date: Sun, 26 Nov 2023 10:38:34 +0800 Subject: [PATCH 1/5] update --- modelscope_agent/tools/openapi_tool.py | 88 +++++---- tests/tools/test_openapi_tool.py | 259 +++++++------------------ 2 files changed, 126 insertions(+), 221 deletions(-) diff --git a/modelscope_agent/tools/openapi_tool.py b/modelscope_agent/tools/openapi_tool.py index 72a2cf405..82398f3f9 100644 --- a/modelscope_agent/tools/openapi_tool.py +++ b/modelscope_agent/tools/openapi_tool.py @@ -1,21 +1,28 @@ from typing import List, Optional + import json import requests from jsonschema import RefResolver from pydantic import BaseModel, ValidationError from requests.exceptions import RequestException, Timeout + from .tool import Tool + MAX_RETRY_TIMES = 3 + + class ParametersSchema(BaseModel): name: str description: str required: Optional[bool] = True + class ToolSchema(BaseModel): name: str description: str parameters: List[ParametersSchema] + class OpenAPISchemaTool(Tool): """ openapi schema tool @@ -55,7 +62,8 @@ def _remote_call(self, *args, **kwargs): f"Could not use remote call for {self.name} since this tool doesn't have a remote endpoint" ) - remote_parsed_input = json.dumps(self._remote_parse_input(*args, **kwargs)) + remote_parsed_input = json.dumps( + self._remote_parse_input(*args, **kwargs)) origin_result = None if self.method == 'POST': retry_times = MAX_RETRY_TIMES @@ -65,12 +73,13 @@ def _remote_call(self, *args, **kwargs): response = requests.request( 'POST', url=self.url, - headers= self.header, + headers=self.header, data=remote_parsed_input) - + if response.status_code != requests.codes.ok: response.raise_for_status() - origin_result = json.loads(response.content.decode('utf-8')) + origin_result = json.loads( + response.content.decode('utf-8')) final_result = self._parse_output( origin_result, remote=True) @@ -90,7 +99,7 @@ def _remote_call(self, *args, **kwargs): while retry_times: retry_times -= 1 try: - print("GET:",self.url) + print('GET:', self.url) response = requests.request( 'GET', url=self.url, @@ -99,7 +108,8 @@ def _remote_call(self, *args, **kwargs): if response.status_code != requests.codes.ok: response.raise_for_status() - origin_result = json.loads(response.content.decode('utf-8')) + origin_result = json.loads( + response.content.decode('utf-8')) final_result = self._parse_output( origin_result, remote=True) @@ -139,11 +149,11 @@ def _remote_parse_input(self, *args, **kwargs): # f the key does not contain ".", directly store the key-value pair into restored_dict restored_dict[key] = value kwargs = restored_dict - print("传给tool的参数:",kwargs) + print('传给tool的参数:', kwargs) return kwargs -#openapi_schema_convert,register to tool_config.json +# openapi_schema_convert,register to tool_config.json def extract_references(schema_content): references = [] if isinstance(schema_content, dict): @@ -166,7 +176,8 @@ def parse_nested_parameters(param_name, param_info, parameters_list, content): if param_type == 'object': properties = param_info.get('properties') if properties: - # If the argument type is an object and has a non-empty "properties" field, its internal properties are parsed recursively + # If the argument type is an object and has a non-empty "properties" field, + # its internal properties are parsed recursively for inner_param_name, inner_param_info in properties.items(): param_type = inner_param_info['type'] param_description = inner_param_info.get( @@ -205,7 +216,8 @@ def parse_responses_parameters(param_name, param_info, parameters_list): if param_type == 'object': properties = param_info.get('properties') if properties: - # If the argument type is an object and has a non-empty "properties" field, its internal properties are parsed recursively + # If the argument type is an object and has a non-empty "properties" field, + # its internal properties are parsed recursively for inner_param_name, inner_param_info in properties.items(): param_type = inner_param_info['type'] param_description = inner_param_info.get( @@ -227,8 +239,9 @@ def parse_responses_parameters(param_name, param_info, parameters_list): raise ValueError(f'{e}:schema结构出错') -#YOUR_API_TOKEN = os.getenv('YOUR_API_TOKEN') ## get token from gradio -#schema is json data +# YOUR_API_TOKEN = os.getenv('YOUR_API_TOKEN') +# get token from gradio +# schema is json data def openapi_schema_convert(schema, YOUR_API_TOKEN): resolver = RefResolver.from_schema(schema) servers = schema.get('servers', []) @@ -244,7 +257,7 @@ def openapi_schema_convert(schema, YOUR_API_TOKEN): # Iterate over each endpoint and its contents for endpoint_path, methods in endpoints.items(): for method, details in methods.items(): - summary = details.get('summary', 'No summary').replace(" ", "_") + summary = details.get('summary', 'No summary').replace(' ', '_') name = details.get('operationId', 'No operationId') url = f'{servers_url}{endpoint_path}' security = details.get('security', [{}]) @@ -271,36 +284,37 @@ def openapi_schema_convert(schema, YOUR_API_TOKEN): parse_nested_parameters( param_name, param_info, parameters_list, content) - X_DashScope_Async = requestBody.get('X-DashScope-Async','') + X_DashScope_Async = requestBody.get( + 'X-DashScope-Async', '') if X_DashScope_Async == '': config_entry = { - 'name': name, - 'description': description, - 'is_active': True, - 'is_remote_tool': True, - 'url': url, - 'method': method.upper(), - 'parameters': parameters_list, - 'header': { - 'Content-Type': content_type, - 'Authorization': authorization + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': parameters_list, + 'header': { + 'Content-Type': content_type, + 'Authorization': authorization + } } - } else: config_entry = { - 'name': name, - 'description': description, - 'is_active': True, - 'is_remote_tool': True, - 'url': url, - 'method': method.upper(), - 'parameters': parameters_list, - 'header': { - 'Content-Type': content_type, - 'Authorization': authorization, - "X-DashScope-Async": "enable" + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': parameters_list, + 'header': { + 'Content-Type': content_type, + 'Authorization': authorization, + 'X-DashScope-Async': 'enable' + } } - } else: config_entry = { 'name': name, diff --git a/tests/tools/test_openapi_tool.py b/tests/tools/test_openapi_tool.py index 6b85a9bc1..43a668fae 100644 --- a/tests/tools/test_openapi_tool.py +++ b/tests/tools/test_openapi_tool.py @@ -1,14 +1,19 @@ -import sys -sys.path.append("../../") import os +import sys import time + import json import yaml -from modelscope_agent.tools.openapi_tool import openapi_schema_convert -from modelscope_agent.tools.openapi_tool import OpenAPISchemaTool +from modelscope_agent.tools.openapi_tool import (OpenAPISchemaTool, + openapi_schema_convert) + from modelscope.utils.config import Config -#make sure YOUR_API_TOKEN + +sys.path.append('../../') + file_path = '../../apps/agentfabric/config/additional_tool_config.json' + + def is_json(data): try: json.loads(data) @@ -16,14 +21,17 @@ def is_json(data): except ValueError: return False + def is_yaml(data): try: yaml.safe_load(data) return True except yaml.YAMLError: return False + + def test_openapi_schema_convert(token): - + schema = """ { "openapi": "3.1.0", @@ -88,7 +96,7 @@ def test_openapi_schema_convert(token): "BearerAuth": [] } ] - + } } }, @@ -154,148 +162,28 @@ def test_openapi_schema_convert(token): } } """ - - # schema = ''' - # { - # "openapi": "3.1.0", - # "info": { - # "title": "Combined API Services", - # "description": "API services for file uploading and face detection and face training in images.", - # "version": "v1.0.0" - # }, - # "servers": [ - # { - # "url": "https://dashscope.aliyuncs.com" - # } - # ], - # "paths": { - # "/api/v1/services/vision/facedetection/detect": { - # "post": { - # "summary": "Detect Faces in Images", - # "operationId": "detectFaces", - # "tags": [ - # "Face Detection" - # ], - # "requestBody": { - # "required": true, - # "content": { - # "application/json": { - # "schema": { - # "$ref": "#/components/schemas/FaceDetectionRequest" - # } - # } - # } - # }, - # "responses": { - # "200": { - # "description": "Successful Response", - # "content": { - # "application/json": { - # "schema": { - # "$ref": "#/components/schemas/FaceDetectionResponse" - # } - # } - # } - # } - # }, - # "security": [ - # { - # "BearerAuth": [] - # } - # ] - # } - # } - # }, - # "components": { - # "schemas": { - # "FaceDetectionRequest": { - # "type": "object", - # "properties": { - # "model": { - # "type": "string", - # "enum": [ - # "facechain-facedetect" - # ] - # }, - # "input": { - # "type": "object", - # "properties": { - # "images": { - # "type": "array", - # "items": { - # "type": "string", - # "format": "url" - # } - # } - # } - # }, - # "parameters": { - # "type": "object" - # } - # }, - # "required": [ - # "model", - # "input" - # ] - # }, - # "FaceDetectionResponse": { - # "type": "object", - # "properties": { - # "output": { - # "type": "object", - # "properties": { - # "is_face": { - # "type": "array", - # "items": { - # "type": "boolean", - # "description": "List of results corresponding to the submitted images.", - # "example": [true, true, false, false] - # } - # } - # } - # }, - # "request_id": { - # "type": "string", - # "description": "Unique code for the request.", - # "example": "7574ee8f-38a3-4b1e-9280-11c33ab46e51" - # } - # } - # } - # }, - # "securitySchemes": { - # "BearerAuth": { - # "type": "http", - # "scheme": "bearer", - # "bearerFormat": "JWT" - # } - # } - # } - # } - - # ''' - if is_json(schema): - print("输入字符串schema是JSON") + print('输入字符串schema是JSON') elif is_yaml(schema): - print("输入字符串schema是YAML") - yaml_dict = yaml.safe_load(schema) - # 将YAML数据转换为JSON数据 - schema = json.dumps(yaml_dict, indent=2) + print('输入字符串schema是YAML') + yaml_dict = yaml.safe_load(schema) + # 将YAML数据转换为JSON数据 + schema = json.dumps(yaml_dict, indent=2) else: - raise("输入字符串schema既不是JSON也不是YAML") + raise ('输入字符串schema既不是JSON也不是YAML') schema_data = json.loads(schema) - config_data = openapi_schema_convert(schema_data,token) + config_data = openapi_schema_convert(schema_data, token) # 检查文件是否存在 if os.path.exists(file_path): - # 检查文件是否为空 - if os.path.getsize(file_path) > 0: - # 如果文件不为空,读取原有的 JSON 数据 - existing_data = {} - with open(file_path, 'r', encoding='utf-8') as config_file: - existing_data = json.load(config_file) - else: - # 如果文件为空,创建一个空的字典作为原有数据 - existing_data = {} + # 检查文件是否为空 + if os.path.getsize(file_path) > 0: + # 如果文件不为空,读取原有的 JSON 数据 + existing_data = {} + with open(file_path, 'r', encoding='utf-8') as config_file: + existing_data = json.load(config_file) + else: + # 如果文件为空,创建一个空的字典作为原有数据 + existing_data = {} else: # 如果文件不存在,创建一个空的字典作为原有数据 existing_data = {} @@ -303,30 +191,30 @@ def test_openapi_schema_convert(token): existing_data.update(config_data) with open(file_path, 'w', encoding='utf-8') as config_file: json.dump(existing_data, config_file, ensure_ascii=False, indent=4) - + def test_openapi_tool_remote_call(): DEFAULT_TOOL_CONFIG_FILE = '../../apps/agentfabric/config/additional_tool_config.json' tool_cfg_file = os.getenv('TOOL_CONFIG_FILE', DEFAULT_TOOL_CONFIG_FILE) tool_cfg = Config.from_file(tool_cfg_file) - tool = OpenAPISchemaTool(cfg=tool_cfg,name='Generate_WordArt_Semantically') + tool = OpenAPISchemaTool( + cfg=tool_cfg, name='Generate_WordArt_Semantically') mock_kwargs = { 'input.text': '文字创意', 'input.prompt': '水果,蔬菜,温暖的色彩空间', 'parameters.steps': 80, 'parameters.n': 2 } - - + # 调用远程请求,并传递模拟的 kwargs try: result = tool(remote=True, **mock_kwargs) print(result) result_data = json.loads(json.dumps(result['result'])) - if "task_id" in result_data['output']: + if 'task_id' in result_data['output']: task_id = result_data['output']['task_id'] - print("www",task_id) - #从前端重新读取schema字符串 + print('www', task_id) + # 从前端重新读取schema字符串 schema = """ { "openapi": "3.1.0", @@ -391,7 +279,7 @@ def test_openapi_tool_remote_call(): "BearerAuth": [] } ] - + } } }, @@ -457,48 +345,50 @@ def test_openapi_tool_remote_call(): } } """ - schema = schema.replace("{task_id}",task_id) + schema = schema.replace('{task_id}', task_id) schema_data = json.loads(schema) existing_data = {} - #从前端get token - config_data = openapi_schema_convert(schema_data,'sk-daee58a99bb44a94bddca4ebb5f6544f') + # 从前端get token + config_data = openapi_schema_convert( + schema_data, 'sk-daee58a99bb44a94bddca4ebb5f6544f') with open(file_path, 'r', encoding='utf-8') as config_file: - existing_data = json.load(config_file) + existing_data = json.load(config_file) existing_data.update(config_data) print(existing_data) with open(file_path, 'w', encoding='utf-8') as config_file: - json.dump(existing_data, config_file, ensure_ascii=False, indent=4) + json.dump( + existing_data, config_file, ensure_ascii=False, indent=4) except Exception as e: - print("Error:", str(e)) + print('Error:', str(e)) DEFAULT_TOOL_CONFIG_FILE = '../../apps/agentfabric/config/additional_tool_config.json' tool_cfg_file = os.getenv('TOOL_CONFIG_FILE', DEFAULT_TOOL_CONFIG_FILE) tool_cfg = Config.from_file(tool_cfg_file) - tool = OpenAPISchemaTool(cfg=tool_cfg,name='Get_WordArt_Result') + tool = OpenAPISchemaTool(cfg=tool_cfg, name='Get_WordArt_Result') mock_kwargs = {} # 调用远程请求,并传递模拟的 kwargs try: result = tool(remote=True, **mock_kwargs) print(result) while True: - result_data = result.get('result', {}) - output = result_data.get('output', {}) - task_status = output.get('task_status', '') + result_data = result.get('result', {}) + output = result_data.get('output', {}) + task_status = output.get('task_status', '') - if task_status == 'SUCCEEDED': - print("任务已完成") - break - elif task_status == 'FAILED': - print("任务失败") - break + if task_status == 'SUCCEEDED': + print('任务已完成') + break + elif task_status == 'FAILED': + print('任务失败') + break - # 继续轮询,等待一段时间后再次调用 - time.sleep(5) # 等待 5 秒钟 - result = tool(remote=True, **mock_kwargs) - print(result) - if "task_id" in result_data['output'] and "task_id" in schema: + # 继续轮询,等待一段时间后再次调用 + time.sleep(5) # 等待 5 秒钟 + result = tool(remote=True, **mock_kwargs) + print(result) + if 'task_id' in result_data['output'] and 'task_id' in schema: task_id = result_data['output']['task_id'] - print("www",task_id) - #从前端重新读取schema字符串 + print('www', task_id) + # 从前端重新读取schema字符串 schema = """ { "openapi": "3.1.0", @@ -563,7 +453,7 @@ def test_openapi_tool_remote_call(): "BearerAuth": [] } ] - + } } }, @@ -629,22 +519,23 @@ def test_openapi_tool_remote_call(): } } """ - schema = schema.replace("{task_id}",task_id) + schema = schema.replace('{task_id}', task_id) schema_data = json.loads(schema) existing_data = {} - #从前端get token - config_data = openapi_schema_convert(schema_data,'sk-daee58a99bb44a94bddca4ebb5f6544f') + # 从前端get token + config_data = openapi_schema_convert( + schema_data, 'sk-daee58a99bb44a94bddca4ebb5f6544f') with open(file_path, 'r', encoding='utf-8') as config_file: - existing_data = json.load(config_file) + existing_data = json.load(config_file) existing_data.update(config_data) with open(file_path, 'w', encoding='utf-8') as config_file: - json.dump(existing_data, config_file, ensure_ascii=False, indent=4) + json.dump( + existing_data, config_file, ensure_ascii=False, indent=4) except Exception as e: - print("Error:", str(e)) - + print('Error:', str(e)) -if __name__ == "__main__": - #从环境获取token,如果这个api不需要token,从前端判断,设置为'' +if __name__ == '__main__': + # 从环境获取token,如果这个api不需要token,从前端判断,设置为'' test_openapi_schema_convert(token='xxxxxxxxxxx') test_openapi_tool_remote_call() From e5255933cfda8068528be77bb6d14b8c5fb8f5c9 Mon Sep 17 00:00:00 2001 From: wangyijunlyy <1157637345@qq.com> Date: Mon, 27 Nov 2023 19:46:07 +0800 Subject: [PATCH 2/5] update openapi_plugin name --- apps/agentfabric/README.md | 6 +- apps/agentfabric/README_CN.md | 6 +- apps/agentfabric/app.py | 183 +++++++++++++----- apps/agentfabric/appBot.py | 10 +- apps/agentfabric/builder_core.py | 76 +++++++- apps/agentfabric/config/builder_config.json | 2 +- .../config/builder_config_template.json | 2 +- apps/agentfabric/config/custom_bot_avatar.png | Bin 958983 -> 1469511 bytes apps/agentfabric/config/tool_config.json | 4 + apps/agentfabric/config_utils.py | 102 ++++++++-- apps/agentfabric/custom_prompt.py | 119 ++++++++---- apps/agentfabric/gradio_utils.py | 6 +- apps/agentfabric/help_tools.py | 15 +- apps/agentfabric/publish_util.py | 118 +++++++++++ apps/agentfabric/user_core.py | 37 +++- 15 files changed, 550 insertions(+), 136 deletions(-) create mode 100644 apps/agentfabric/publish_util.py diff --git a/apps/agentfabric/README.md b/apps/agentfabric/README.md index f112afac6..a0f020105 100644 --- a/apps/agentfabric/README.md +++ b/apps/agentfabric/README.md @@ -40,9 +40,9 @@ python app.py ## 🚀 Roadmap - [x] Allow customizable agent-building via configurations. - [x] Agent-building through interactive conversations with LLMs. -- [ ] Support multi-user preview on ModelScope space. -- [ ] Optimize knowledge retrival. -- [ ] Allow publication and sharing of agent. +- [x] Support multi-user preview on ModelScope space. [link](https://modelscope.cn/studios/wenmengzhou/AgentFabric/summary) +- [ ] Optimize knowledge retrival. (ing) +- [ ] Allow publication and sharing of agent. (ing) - [ ] Support more pluggable LLMs via API or ModelScope interface. - [ ] Improve long context via memory. - [ ] Improve logging and profiling. diff --git a/apps/agentfabric/README_CN.md b/apps/agentfabric/README_CN.md index f7b95f6e8..f9dbe51aa 100644 --- a/apps/agentfabric/README_CN.md +++ b/apps/agentfabric/README_CN.md @@ -42,9 +42,9 @@ python app.py ## 🚀 发展路线规划 - [x] 支持人工配置构建智能体 - [x] 基于LLM对话构建智能体 -- [ ] 支持在ModelScope创空间上使用 -- [ ] 知识库检索效果优化 -- [ ] 支持智能体发布和分享 +- [x] 支持在ModelScope创空间上使用 [link](https://modelscope.cn/studios/wenmengzhou/AgentFabric/summary) +- [ ] 知识库检索效果优化 (ing) +- [ ] 支持智能体发布和分享 (ing) - [ ] 支持其他多种LLM模型API和ModelScope模型 - [ ] 处理长文本输入到内存 - [ ] 生产级支持:日志和性能分析 diff --git a/apps/agentfabric/app.py b/apps/agentfabric/app.py index fcd2cb81a..c839bc5b0 100644 --- a/apps/agentfabric/app.py +++ b/apps/agentfabric/app.py @@ -1,19 +1,27 @@ +import os import random +import shutil import sys import traceback import gradio as gr +import json from builder_core import init_builder_chatbot_agent -from config_utils import (Config, get_avatar_image, parse_configuration, - save_avatar_image, save_builder_configuration) +from config_utils import (Config, get_avatar_image, get_user_cfg_file, + get_user_dir, parse_configuration, save_avatar_image, + save_builder_configuration, + save_plugin_configuration) from gradio_utils import ChatBot, format_cover_html +from publish_util import prepare_agent_zip from user_core import init_user_chatbot_agent +sys.path.append('../../') -def init_user(state): + +def init_user(uuid_str, state): try: seed = state.get('session_seed', random.randint(0, 1000000000)) - user_agent = init_user_chatbot_agent() + user_agent = init_user_chatbot_agent(uuid_str) user_agent.seed = seed state['user_agent'] = user_agent except Exception as e: @@ -22,9 +30,10 @@ def init_user(state): return state -def init_builder(state): +def init_builder(uuid_str, state): + try: - builder_agent = init_builder_chatbot_agent() + builder_agent = init_builder_chatbot_agent(uuid_str) state['builder_agent'] = builder_agent except Exception as e: error = traceback.format_exc() @@ -32,7 +41,21 @@ def init_builder(state): return state -def init_ui_config(state, builder_cfg, model_cfg, tool_cfg): +def update_builder(uuid_str, state): + builder_agent = state['builder_agent'] + + try: + builder_cfg_file = get_user_cfg_file(uuid_str=uuid_str) + with open(builder_cfg_file, 'r') as f: + config = json.load(f) + builder_agent.update_config_to_history(config) + except Exception as e: + error = traceback.format_exc() + print(f'Error:{e}, with detail: {error}') + return state + + +def init_ui_config(uuid_str, state, builder_cfg, model_cfg, tool_cfg): print('builder_cfg:', builder_cfg) # available models models = list(model_cfg.keys()) @@ -42,8 +65,8 @@ def init_ui_config(state, builder_cfg, model_cfg, tool_cfg): state['model_cfg'] = model_cfg state['tool_cfg'] = tool_cfg state['capabilities'] = capabilities - bot_avatar = get_avatar_image(builder_cfg.get('avatar', ''))[1] - suggests = builder_cfg.get('conversation_starters', []) + bot_avatar = get_avatar_image(builder_cfg.get('avatar', ''), uuid_str)[1] + suggests = builder_cfg.get('prompt_recommend', []) return [ state, # config form @@ -68,30 +91,54 @@ def init_ui_config(state, builder_cfg, model_cfg, tool_cfg): ] -def init_all(state): - builder_cfg, model_cfg, tool_cfg, available_tool_list = parse_configuration( - ) - ret = init_ui_config(state, builder_cfg, model_cfg, tool_cfg) +def init_all(uuid_str, state): + uuid_str = check_uuid(uuid_str) + builder_cfg, model_cfg, tool_cfg, available_tool_list, _, _ = parse_configuration( + uuid_str) + ret = init_ui_config(uuid_str, state, builder_cfg, model_cfg, tool_cfg) yield ret - init_user(state) - init_builder(state) + init_user(uuid_str, state) + init_builder(uuid_str, state) yield ret -def process_configuration(bot_avatar, name, description, instructions, model, - suggestions, files, capabilities_checkboxes, state): +def check_uuid(uuid_str): + if not uuid_str or uuid_str == '': + if os.getenv('MODELSCOPE_ENVIRONMENT') == 'studio': + raise gr.Error('请登陆后使用! (Please login first)') + else: + uuid_str = 'local_user' + return uuid_str + + +def process_configuration(uuid_str, bot_avatar, name, description, + instructions, model, suggestions, knowledge_files, + capabilities_checkboxes, openapi_schema, + openapi_auth, openapi_privacy_policy, state): + uuid_str = check_uuid(uuid_str) tool_cfg = state['tool_cfg'] capabilities = state['capabilities'] - - bot_avatar, bot_avatar_path = save_avatar_image(bot_avatar) + bot_avatar, bot_avatar_path = save_avatar_image(bot_avatar, uuid_str) suggestions_filtered = [row for row in suggestions if row[0]] + user_dir = get_user_dir(uuid_str) + if knowledge_files is not None: + new_knowledge_files = [ + os.path.join(user_dir, os.path.basename((f.name))) + for f in knowledge_files + ] + for src_file, dst_file in zip(knowledge_files, new_knowledge_files): + if not os.path.exists(dst_file): + shutil.copy(src_file.name, dst_file) + else: + new_knowledge_files = [] + builder_cfg = { 'name': name, 'avatar': bot_avatar, 'description': description, 'instruction': instructions, - 'conversation_starters': [row[0] for row in suggestions_filtered], - 'knowledge': list(map(lambda file: file.name, files or [])), + 'prompt_recommend': [row[0] for row in suggestions_filtered], + 'knowledge': new_knowledge_files, 'tools': { capability: dict( name=tool_cfg[capability]['name'], @@ -102,14 +149,28 @@ def process_configuration(bot_avatar, name, description, instructions, model, 'model': model, } - save_builder_configuration(builder_cfg) - init_user(state) + try: + schema_dict = json.loads(openapi_schema) + openapi_plugin_cfg = { + 'schema': schema_dict, + 'auth': openapi_auth, + 'privacy_policy': openapi_privacy_policy + } + save_plugin_configuration(openapi_plugin_cfg, uuid_str) + except Exception as e: + error = traceback.format_exc() + print(f'Error:{e}, with detail: {error}') + + save_builder_configuration(builder_cfg, uuid_str) + update_builder(uuid_str, state) + init_user(uuid_str, state) return [ gr.HTML.update( visible=True, value=format_cover_html(builder_cfg, bot_avatar_path)), gr.Chatbot.update( - visible=False, avatar_images=get_avatar_image(bot_avatar)), + visible=False, + avatar_images=get_avatar_image(bot_avatar, uuid_str)), gr.Dataset.update(samples=suggestions_filtered), gr.DataFrame.update(value=suggestions_filtered) ] @@ -118,6 +179,7 @@ def process_configuration(bot_avatar, name, description, instructions, model, # 创建 Gradio 界面 demo = gr.Blocks(css='assets/app.css') with demo: + uuid_str = gr.Textbox(label='modelscope_uuid', visible=False) draw_seed = random.randint(0, 1000000000) state = gr.State({'session_seed': draw_seed}) with gr.Row(): @@ -170,13 +232,13 @@ def process_configuration(bot_avatar, name, description, instructions, model, label='Capabilities') with gr.Accordion('配置选项', open=False): - schema1 = gr.Textbox( + openapi_schema = gr.Textbox( label='Schema', placeholder='Enter your OpenAPI schema here') - auth1 = gr.Radio( + openapi_auth = gr.Radio( label='Authentication', choices=['None', 'API Key', 'OAuth']) - privacy_policy1 = gr.Textbox( + openapi_privacy_policy = gr.Textbox( label='Privacy Policy', placeholder='Enter privacy policy URL') @@ -200,7 +262,7 @@ def process_configuration(bot_avatar, name, description, instructions, model, value=[[None, None]], elem_id='user_chatbot', elem_classes=['markdown-body'], - avatar_images=get_avatar_image(''), + avatar_images=get_avatar_image('', uuid_str), height=650, latex_delimiters=[], show_label=False, @@ -216,6 +278,8 @@ def process_configuration(bot_avatar, name, description, instructions, model, lambda evt: evt[0], inputs=[user_chat_bot_suggest], outputs=[preview_chat_input]) + publish_button = gr.Button('Publish') + output_url = gr.Textbox(label='Agent url for you', disabled=True) configure_updated_outputs = [ state, @@ -230,32 +294,36 @@ def process_configuration(bot_avatar, name, description, instructions, model, capabilities_checkboxes, # bot user_chat_bot_cover, - user_chat_bot_suggest + user_chat_bot_suggest, ] # tab 切换的事件处理 - def on_congifure_tab_select(_state): + def on_congifure_tab_select(_state, uuid_str): + uuid_str = check_uuid(uuid_str) configure_updated = _state.get('configure_updated', False) if configure_updated: - builder_cfg, model_cfg, tool_cfg, available_tool_list = parse_configuration( - ) + builder_cfg, model_cfg, tool_cfg, available_tool_list, _, _ = parse_configuration( + uuid_str) _state['configure_updated'] = False - return init_ui_config(_state, builder_cfg, model_cfg, tool_cfg) + return init_ui_config(uuid_str, _state, builder_cfg, model_cfg, + tool_cfg) else: return {state: _state} configure_tab.select( on_congifure_tab_select, - inputs=[state], + inputs=[state, uuid_str], outputs=configure_updated_outputs) # 配置 "Create" 标签页的消息发送功能 - def format_message_with_builder_cfg(_state, chatbot, builder_cfg): + def format_message_with_builder_cfg(_state, chatbot, builder_cfg, + uuid_str): + uuid_str = check_uuid(uuid_str) bot_avatar = builder_cfg.get('avatar', '') - conversation_starters = builder_cfg.get('conversation_starters', []) - suggestion = [[row] for row in conversation_starters] - bot_avatar_path = get_avatar_image(bot_avatar)[1] - save_builder_configuration(builder_cfg) + prompt_recommend = builder_cfg.get('prompt_recommend', []) + suggestion = [[row] for row in prompt_recommend] + bot_avatar_path = get_avatar_image(bot_avatar, uuid_str)[1] + save_builder_configuration(builder_cfg, uuid_str) _state['configure_updated'] = True return { create_chatbot: @@ -266,12 +334,14 @@ def format_message_with_builder_cfg(_state, chatbot, builder_cfg): value=format_cover_html(builder_cfg, bot_avatar_path)), user_chatbot: gr.Chatbot.update( - visible=False, avatar_images=get_avatar_image(bot_avatar)), + visible=False, + avatar_images=get_avatar_image(bot_avatar, uuid_str)), user_chat_bot_suggest: gr.Dataset.update(samples=suggestion) } - def create_send_message(chatbot, input, _state): + def create_send_message(chatbot, input, _state, uuid_str): + uuid_str = check_uuid(uuid_str) # 将发送的消息添加到聊天历史 builder_agent = _state['builder_agent'] chatbot.append((input, '')) @@ -289,7 +359,10 @@ def create_send_message(chatbot, input, _state): exec_result = exec_result['result'] assert isinstance(exec_result, Config) yield format_message_with_builder_cfg( - _state, chatbot, exec_result.to_dict()) + _state, + chatbot, + exec_result.to_dict(), + uuid_str=uuid_str) else: # llm result if isinstance(llm_result, dict): @@ -305,7 +378,7 @@ def create_send_message(chatbot, input, _state): create_send_button.click( create_send_message, - inputs=[create_chatbot, create_chat_input, state], + inputs=[create_chatbot, create_chat_input, state, uuid_str], outputs=[ create_chatbot, user_chat_bot_cover, user_chatbot, user_chat_bot_suggest, create_chat_input @@ -315,9 +388,10 @@ def create_send_message(chatbot, input, _state): configure_button.click( process_configuration, inputs=[ - bot_avatar_comp, name_input, description_input, instructions_input, - model_selector, suggestion_input, knowledge_input, - capabilities_checkboxes, state + uuid_str, bot_avatar_comp, name_input, description_input, + instructions_input, model_selector, suggestion_input, + knowledge_input, capabilities_checkboxes, openapi_schema, + openapi_auth, openapi_privacy_policy, state ], outputs=[ user_chat_bot_cover, user_chatbot, user_chat_bot_suggest, @@ -363,7 +437,20 @@ def preview_send_message(chatbot, input, _state): inputs=[user_chatbot, preview_chat_input, state], outputs=[user_chatbot, user_chat_bot_cover, preview_chat_input]) - demo.load(init_all, inputs=[state], outputs=configure_updated_outputs) + # configuration for publish + def publish_agent(output_url, name, uuid_str, state): + uuid_str = check_uuid(uuid_str) + output_url = prepare_agent_zip(name, uuid_str, state) + return output_url + + publish_button.click( + publish_agent, + inputs=[output_url, name_input, uuid_str, state], + outputs=[output_url], + ) + + demo.load( + init_all, inputs=[uuid_str, state], outputs=configure_updated_outputs) -demo.queue() +demo.queue(concurrency_count=10) demo.launch() diff --git a/apps/agentfabric/appBot.py b/apps/agentfabric/appBot.py index 8f900601d..df6a601ef 100644 --- a/apps/agentfabric/appBot.py +++ b/apps/agentfabric/appBot.py @@ -7,9 +7,11 @@ from gradio_utils import ChatBot, format_cover_html from user_core import init_user_chatbot_agent -builder_cfg, model_cfg, tool_cfg, available_tool_list = parse_configuration() -suggests = builder_cfg.get('conversation_starters', []) -avatar_pairs = get_avatar_image(builder_cfg.get('avatar', '')) +uuid_str = 'local_user' +builder_cfg, model_cfg, tool_cfg, available_tool_list, _, _ = parse_configuration( + uuid_str) +suggests = builder_cfg.get('prompt_recommend', []) +avatar_pairs = get_avatar_image(builder_cfg.get('avatar', ''), uuid_str) customTheme = gr.themes.Default( primary_hue=gr.themes.utils.colors.blue, @@ -20,7 +22,7 @@ def init_user(state): try: seed = state.get('session_seed', random.randint(0, 1000000000)) - user_agent = init_user_chatbot_agent() + user_agent = init_user_chatbot_agent(uuid_str) user_agent.seed = seed state['user_agent'] = user_agent except Exception as e: diff --git a/apps/agentfabric/builder_core.py b/apps/agentfabric/builder_core.py index 03a736237..252f27f4f 100644 --- a/apps/agentfabric/builder_core.py +++ b/apps/agentfabric/builder_core.py @@ -1,5 +1,6 @@ # flake8: noqa E501 import re +import traceback from typing import Dict import json @@ -13,25 +14,30 @@ SYSTEM = 'You are a helpful assistant.' PROMPT_CUSTOM = """你现在要扮演一个制造AI角色(AI-Agent)的AI助手(QwenBuilder)。 -你需要和用户进行对话,明确用户对AI-Agent的要求。并根据已有信息和你的联想能力,尽可能填充完整的符合角色设定的配置文件: +你需要和用户进行对话,明确用户对AI-Agent的要求。并根据已有信息和你的联想能力,尽可能填充完整的配置文件: 配置文件为json格式: -{"name": "... # AI-Agent的名字", "description": "... # 对AI-Agent的要求", "instructions": "... # 分点描述对AI-Agent的具体功能要求,尽量详细一些,类型是一个字符串数组,起始为[]", "conversation_starters": "... # 合适的用户跟AI-Agent的开场白,是用户说的话,类型是一个字符串数组,请尽可能补充4句左右,起始为[]", "logo_prompt": "... # 画AI-Agent的logo的指令,不需要画logo或不需要更新logo时可以为空,类型是string"} +{"name": "... # AI-Agent的名字", "description": "... # 对AI-Agent的要求,简单描述", "instructions": "... # 分点描述对AI-Agent的具体功能要求,尽量详细一些,类型是一个字符串数组,起始为[]", "prompt_recommend": "... # 推荐的用户将对AI-Agent说的指令,用于指导用户使用AI-Agent,类型是一个字符串数组,请尽可能补充4句左右,起始为["你可以做什么?"]", "logo_prompt": "... # 画AI-Agent的logo的指令,不需要画logo或不需要更新logo时可以为空,类型是string"} 在接下来的对话中,请在回答时严格使用如下格式,先作出回复,再生成配置文件,不要回复其他任何内容: -Answer: ... # 你希望对用户说的话,用于询问用户对AI-Agent的要求,不要重复确认用户已经提出的要求,而应该拓展出新的角度来询问用户,禁止为空 +Answer: ... # 你希望对用户说的话,用于询问用户对AI-Agent的要求,不要重复确认用户已经提出的要求,而应该拓展出新的角度来询问用户,尽量细节和丰富,禁止为空 Config: ... # 生成的配置文件,严格按照以上json格式 -RichConfig: ... # 格式和核心内容和Config相同,但是description和instructions等字段需要在Config的基础上扩充字数,使描述和指令更加详尽,并补充conversation_starters。请注意从用户的视角来描述description、instructions和conversation_starters,不要用QwenBuilder或AI-Agent的视角。 +RichConfig: ... # 格式和核心内容和Config相同,但是保证name和description不为空;instructions需要在Config的基础上扩充字数,使指令更加详尽,如果用户给出了详细指令,请完全保留;补充prompt_recommend,并保证prompt_recommend是推荐的用户将对AI-Agent说的指令。请注意从用户的视角来描述prompt_recommend、description和instructions。 + +一个优秀的RichConfig样例如下: +{"name": "小红书文案生成助手", "description": "一个专为小红书用户设计的文案生成助手。", "instructions": "1. 理解并回应用户的指令;2. 根据用户的需求生成高质量的小红书风格文案;3. 使用表情提升文本丰富度", "prompt_recommend": ["你可以帮我生成一段关于旅行的文案吗?", "你会写什么样的文案?", "可以推荐一个小红书文案模版吗?"], "logo_prompt": "一个写作助手logo,包含一只羽毛钢笔"} 明白了请说“好的。”, 不要说其他的。""" LOGO_TOOL_NAME = 'logo_designer' +ASSISTANT_PROMPT = """Answer: \nConfig: \nRichConfig: """ + -def init_builder_chatbot_agent(): +def init_builder_chatbot_agent(uuid_str): # build model - builder_cfg, model_cfg, _, _ = parse_configuration() + builder_cfg, model_cfg, _, _, _, _ = parse_configuration(uuid_str) # additional tool additional_tool_list = {LOGO_TOOL_NAME: LogoGeneratorTool()} @@ -71,6 +77,19 @@ def init_builder_chatbot_agent(): class BuilderChatbotAgent(AgentExecutor): + def __init__(self, llm, tool_cfg, agent_type, prompt_generator, + additional_tool_list): + + super().__init__( + llm, + tool_cfg, + agent_type=agent_type, + additional_tool_list=additional_tool_list, + prompt_generator=prompt_generator) + + # used to reconstruct assistant message when builder config is updated + self._last_assistant_structured_response = {} + def stream_run(self, task: str, remote: bool = True, @@ -103,6 +122,8 @@ def stream_run(self, pattern=r'Answer:([\s\S]+)\nConfig:') res = re_pattern_answer.search(llm_result['content']) llm_text = res.group(1).strip() + self._last_assistant_structured_response[ + 'answer_str'] = llm_text yield {'llm_text': llm_text} except Exception: yield {'error': 'llm result is not valid'} @@ -112,9 +133,18 @@ def stream_run(self, content = llm_result['content'] else: content = llm_result - config = content[content.rfind('RichConfig:') - + len('RichConfig:'):].strip() - answer = json.loads(config) + + re_pattern_config = re.compile( + pattern=r'Config: ([\s\S]+)\nRichConfig') + res = re_pattern_config.search(llm_result['content']) + config = res.group(1).strip() + self._last_assistant_structured_response['config_str'] = config + + rich_config = content[content.rfind('RichConfig:') + + len('RichConfig:'):].strip() + answer = json.loads(rich_config) + self._last_assistant_structured_response[ + 'rich_config_dict'] = answer builder_cfg = config_conversion(answer) yield {'exec_result': {'result': builder_cfg}} except ValueError as e: @@ -144,3 +174,31 @@ def stream_run(self, return else: return + + def update_config_to_history(self, config: Dict): + """ update builder config to message when user modify configuration + + Args: + config info read from builder config file + """ + if len( + self.prompt_generator.history + ) > 0 and self.prompt_generator.history[-1]['role'] == 'assistant': + answer = self._last_assistant_structured_response['answer_str'] + simple_config = self._last_assistant_structured_response[ + 'config_str'] + + rich_config_dict = { + k: config[k] + for k in ['name', 'description', 'prompt_recommend'] + } + rich_config_dict[ + 'logo_prompt'] = self._last_assistant_structured_response[ + 'rich_config_dict']['logo_prompt'] + rich_config_dict['instructions'] = config['instruction'].split(';') + + rich_config = json.dumps(rich_config_dict, ensure_ascii=False) + new_content = ASSISTANT_PROMPT.replace('', answer).replace( + '', simple_config).replace('', + rich_config) + self.prompt_generator.history[-1]['content'] = new_content diff --git a/apps/agentfabric/config/builder_config.json b/apps/agentfabric/config/builder_config.json index 2b91449be..bcadf439b 100644 --- a/apps/agentfabric/config/builder_config.json +++ b/apps/agentfabric/config/builder_config.json @@ -3,7 +3,7 @@ "avatar": "custom_bot_avatar.png", "description": "能够生成武侠小说并配图", "instruction": "你的指令是为我提供一个基于金庸武侠小说世界的在线RPG游戏体验。在这个游戏中,玩家将扮演金庸故事中的一个关键角色,游戏情景将基于他的小说。这个游戏的玩法是互动式的,并遵循以下特定格式:\n\n<场景描述>:根据玩家的选择,故事情节将按照金庸小说的线索发展。你将描述角色所处的环境和情况。\n\n<场景图片>:对于每个场景,你将创造一个概括该情况的图像。这些图像的风格将类似于1980年代RPG游戏,大小是16:9宽屏比例。在这个步骤你需要调用画图工具,绘制<场景描述>。\n\n<选择>:在每次互动中,你将为玩家提供三个行动选项,分别标为A、B、C,以及第四个选项“D: 输入玩家的选择”。故事情节将根据玩家选择的行动进展。如果一个选择不是直接来自小说,你将创造性地适应故事,最终引导它回归原始情节。\n\n整个故事将围绕金庸小说中丰富而复杂的世界展开。每次互动必须包括<场景描述>、<场景图片>和<选择>。所有内容将以繁体中文呈现。你的重点将仅仅放在提供场景描述,场景图片和选择上,不包含其他游戏指导。场景尽量不要重复,要丰富一些。", - "conversation_starters": [ + "prompt_recommend": [ "扮演小龙女", "扮演杨过" ], diff --git a/apps/agentfabric/config/builder_config_template.json b/apps/agentfabric/config/builder_config_template.json index 970b34d4b..fbd3c512a 100644 --- a/apps/agentfabric/config/builder_config_template.json +++ b/apps/agentfabric/config/builder_config_template.json @@ -3,7 +3,7 @@ "avatar": "logo.png", "description": "我希望AI-Agent能够像多啦A梦一样,拥有各种神奇的技能和能力,可以帮我解决生活中的各种问题。", "instruction": "请告诉我你想要什么帮助,我会尽力提供解决方案。;如果你有任何问题,请随时向我提问,我会尽我所能回答你的问题。;我可以帮你查找信息、提供建议、提醒日程等,只需要你告诉我你需要什么。", - "conversation_starters": [ + "prompt_recommend": [ "你好,我是AI-Agent,有什么可以帮助你的吗?", "嗨,很高兴见到你,我是AI-Agent,你可以问我任何问题。", "你好,我是AI-Agent,需要我帮你做些什么吗?", diff --git a/apps/agentfabric/config/custom_bot_avatar.png b/apps/agentfabric/config/custom_bot_avatar.png index f996880734902a94a9a8fc785eed69d6540bb7fa..535d527de1336321aed390f300d744ea42f24dcc 100644 GIT binary patch literal 1469511 zcmV(#K;*xPP)YYI1146)0|E&` zDH75f}^xm;mPXQ!E4qKmY>_ z0y7h#Rc!T1eg*U+1Aaw5&y(Ia2tCKr=F+X_RKMZsQqPT{l-KT zs(bshCcOeT0gm#U)sA1O(GbKrNRN!gAc>wpKF9RX?UWh0XzVxgz>I#p7);J-uQ}c4 z$O1>krxM!z$djrfcI-%A#mbF0VuGlr3)Whgew`Ffgm}MZ6%!haP6}1R;9G}0j5~r! z?GO}umBAu{X)<#YlsCLnNI*ervA_d~WP-S@=kU*zH13+@1}GHlRyCpZ(*}!(YbCG_ 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}, + "amap_weather": { + "name": "高德天气", + "is_active": true } } diff --git a/apps/agentfabric/config_utils.py b/apps/agentfabric/config_utils.py index 72d87af62..f7c90b00d 100644 --- a/apps/agentfabric/config_utils.py +++ b/apps/agentfabric/config_utils.py @@ -1,43 +1,103 @@ import os import shutil +from typing import Dict import json +from modelscope_agent.tools.openapi_plugin import (OpenAPIPluginTool, + openapi_schema_convert) from modelscope.utils.config import Config DEFAULT_BUILDER_CONFIG_DIR = './config' DEFAULT_BUILDER_CONFIG_FILE = './config/builder_config.json' +DEFAULT_OPENAPI_PLUGIN_CONFIG_FILE = './config/openapi_plugin_config.json' DEFAULT_MODEL_CONFIG_FILE = './config/model_config.json' DEFAULT_TOOL_CONFIG_FILE = './config/tool_config.json' -def save_builder_configuration(builder_cfg): +def get_user_dir(uuid_str=''): + return os.path.join('config', uuid_str) + + +def get_user_cfg_file(uuid_str=''): builder_cfg_file = os.getenv('BUILDER_CONFIG_FILE', DEFAULT_BUILDER_CONFIG_FILE) + # convert from ./config/builder_config.json to ./config/user/builder_config.json + builder_cfg_file = builder_cfg_file.replace('config/', 'config/user/') + + # convert from ./config/user/builder_config.json to ./config/uuid/builder_config.json + if uuid_str != '': + builder_cfg_file = builder_cfg_file.replace('user', uuid_str) + return builder_cfg_file + + +def get_user_openapi_plugin_cfg_file(uuid_str=''): + openapi_plugin_cfg_file = os.getenv('OPENAPI_PLUGIN_CONFIG_FILE', + DEFAULT_OPENAPI_PLUGIN_CONFIG_FILE) + openapi_plugin_cfg_file = openapi_plugin_cfg_file.replace( + 'config/', 'config/user/') + if uuid_str != '': + openapi_plugin_cfg_file = openapi_plugin_cfg_file.replace( + 'user', uuid_str) + return openapi_plugin_cfg_file + + +def save_builder_configuration(builder_cfg, uuid_str=''): + builder_cfg_file = get_user_cfg_file(uuid_str) + if uuid_str != '' and not os.path.exists( + os.path.dirname(builder_cfg_file)): + os.makedirs(os.path.dirname(builder_cfg_file)) with open(builder_cfg_file, 'w', encoding='utf-8') as f: f.write(json.dumps(builder_cfg, indent=2, ensure_ascii=False)) -def get_avatar_image(bot_avatar): +def save_plugin_configuration(openapi_plugin_cfg, uuid_str): + openapi_plugin_cfg_file = get_user_openapi_plugin_cfg_file(uuid_str) + if uuid_str != '' and not os.path.exists( + os.path.dirname(openapi_plugin_cfg_file)): + os.makedirs(os.path.dirname(openapi_plugin_cfg_file)) + with open(openapi_plugin_cfg_file, 'w', encoding='utf-8') as f: + f.write(json.dumps(openapi_plugin_cfg, indent=2, ensure_ascii=False)) + + +def get_avatar_image(bot_avatar, uuid_str=''): user_avatar_path = os.path.join( os.path.dirname(__file__), 'assets/user.jpg') bot_avatar_path = os.path.join(os.path.dirname(__file__), 'assets/bot.jpg') if len(bot_avatar) > 0: bot_avatar_path = os.path.join( - os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, bot_avatar) + os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, uuid_str, + bot_avatar) + if uuid_str != '': + # use default if not exists + if not os.path.exists(bot_avatar_path): + # create parents directory + os.makedirs(os.path.dirname(bot_avatar_path), exist_ok=True) + # copy the template to the address + temp_bot_avatar_path = os.path.join( + os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, + bot_avatar) + if not os.path.exists(temp_bot_avatar_path): + # fall back to default avatar image + temp_bot_avatar_path = os.path.join( + os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, + 'custom_bot_avatar.png') + + shutil.copy(temp_bot_avatar_path, bot_avatar_path) + return [user_avatar_path, bot_avatar_path] -def save_avatar_image(image_path): - file_extension = os.path.splitext(image_path)[1] - bot_avatar = f'custom_bot_avatar{file_extension}' +def save_avatar_image(image_path, uuid_str=''): + bot_avatar = os.path.basename(image_path) bot_avatar_path = os.path.join( - os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, bot_avatar) + os.path.dirname(__file__), DEFAULT_BUILDER_CONFIG_DIR, uuid_str, + bot_avatar) shutil.copy(image_path, bot_avatar_path) return bot_avatar, bot_avatar_path -def parse_configuration(): +def parse_configuration(uuid_str=''): """parse configuration Args: @@ -47,8 +107,18 @@ def parse_configuration(): """ model_cfg_file = os.getenv('MODEL_CONFIG_FILE', DEFAULT_MODEL_CONFIG_FILE) - builder_cfg_file = os.getenv('BUILDER_CONFIG_FILE', - DEFAULT_BUILDER_CONFIG_FILE) + + builder_cfg_file = get_user_cfg_file(uuid_str) + # use default if not exists + if not os.path.exists(builder_cfg_file): + # create parents directory + os.makedirs(os.path.dirname(builder_cfg_file), exist_ok=True) + # copy the template to the address + builder_cfg_file_temp = os.environ.get('BUILDER_CONFIG_FILE', + DEFAULT_BUILDER_CONFIG_FILE) + if builder_cfg_file_temp != builder_cfg_file: + shutil.copy(builder_cfg_file_temp, builder_cfg_file) + tool_cfg_file = os.getenv('TOOL_CONFIG_FILE', DEFAULT_TOOL_CONFIG_FILE) builder_cfg = Config.from_file(builder_cfg_file) @@ -61,4 +131,14 @@ def parse_configuration(): if value['use']: available_tool_list.append(key) - return builder_cfg, model_cfg, tool_cfg, available_tool_list + openapi_plugin_file = get_user_openapi_plugin_cfg_file(uuid_str) + plugin_cfg = None + available_plugin_list = [] + if os.path.exists(openapi_plugin_file): + config_dict = openapi_schema_convert( + Config.from_file(openapi_plugin_file).schema) + plugin_cfg = Config(config_dict) + for name, config in config_dict.items(): + available_plugin_list.append(name) + + return builder_cfg, model_cfg, tool_cfg, available_tool_list, plugin_cfg, available_plugin_list diff --git a/apps/agentfabric/custom_prompt.py b/apps/agentfabric/custom_prompt.py index 53b116e76..1f4f7ab2b 100644 --- a/apps/agentfabric/custom_prompt.py +++ b/apps/agentfabric/custom_prompt.py @@ -1,34 +1,50 @@ import copy import os import re +from typing import Dict import json -from config_utils import DEFAULT_BUILDER_CONFIG_FILE -from modelscope_agent.prompt.prompt import (KNOWLEDGE_RESULT_PROMPT, - PromptGenerator, build_raw_prompt) +from config_utils import DEFAULT_BUILDER_CONFIG_FILE, get_user_cfg_file +from modelscope_agent.prompt.prompt import (KNOWLEDGE_PROMPT, PromptGenerator, + build_raw_prompt) from modelscope.utils.config import Config -DEFAULT_SYSTEM_TEMPLATE = """# 工具 +DEFAULT_SYSTEM_TEMPLATE = """ + +# 工具 ## 你拥有如下工具: -## 当你需要调用工具时,请在你的回复中穿插如下的工具调用命令: +## 当你需要调用工具时,请在你的回复中穿插如下的工具调用命令,可以根据需求调用零次或多次: 工具调用 -Action: 工具的名字 +Action: 工具的名称,必须是之一 Action Input: 工具的输入,需格式化为一个JSON -Observation: 工具返回的结果 +Observation: 工具返回的结果 +Answer: 根据Observation总结本次工具调用返回的结果,如果结果中出现url,请使用如下markdown格式展现: + +``` +[链接](url) +``` # 指令 """ + +DEFAULT_SYSTEM_TEMPLATE_WITHOUT_TOOL = """ + +# 指令 +""" + DEFAULT_INSTRUCTION_TEMPLATE = '' -DEFAULT_USER_TEMPLATE = """(你正在扮演,你可以使用工具:) """ +DEFAULT_USER_TEMPLATE = """(你正在扮演,你可以使用工具:) """ -DEFAULT_EXEC_TEMPLATE = """Observation: """ +DEFAULT_USER_TEMPLATE_WITHOUT_TOOL = """(你正在扮演) """ + +DEFAULT_EXEC_TEMPLATE = """Observation: \nAnswer:""" TOOL_DESC = ( '{name_for_model}: {name_for_human} API。 {description_for_model} 输入参数: {parameters}' @@ -43,7 +59,7 @@ def __init__(self, user_template=DEFAULT_USER_TEMPLATE, exec_template=DEFAULT_EXEC_TEMPLATE, assistant_template='', - sep='\n', + sep='\n\n', prompt_max_length=1000, **kwargs): super().__init__(system_template, instruction_template, user_template, @@ -53,12 +69,14 @@ def __init__(self, self.add_addition_round = kwargs.get('add_addition_round', False) self.addition_assistant_reply = kwargs.get('addition_assistant_reply', '') - builder_cfg_file = os.getenv('BUILDER_CONFIG_FILE', - DEFAULT_BUILDER_CONFIG_FILE) + builder_cfg_file = get_user_cfg_file( + uuid_str=kwargs.get('uuid_str', '')) builder_cfg = Config.from_file(builder_cfg_file) self.builder_cfg = builder_cfg + self.knowledge_file_name = kwargs.get('knowledge_file_name', '') - def init_prompt(self, task, tool_list, knowledge_list, llm_model): + def init_prompt(self, task, tool_list, knowledge_list, llm_model, + **kwargs): if len(self.history) == 0: self.history.append({ @@ -68,25 +86,40 @@ def init_prompt(self, task, tool_list, knowledge_list, llm_model): self.prompt_preprocessor = build_raw_prompt(llm_model) - prompt = f'{self.system_template}\n{self.instruction_template}' + if len(tool_list) > 0: + prompt = f'{self.system_template}\n{self.instruction_template}' - if len(knowledge_list) > 0: + # get tool description str + tool_str = self.get_tool_str(tool_list) + prompt = prompt.replace('', tool_str) - knowledge_str = self.get_knowledge_str(knowledge_list) - # knowledge - prompt = knowledge_str + prompt + tool_name_str = self.get_tool_name_str(tool_list) + prompt = prompt.replace('', tool_name_str) - # get tool description str - tool_str = self.get_tool_str(tool_list) - prompt = prompt.replace('', tool_str) + # user input + user_input = self.user_template.replace('', task) + user_input = user_input.replace('', + self.builder_cfg.name) + user_input = user_input.replace( + '', + ','.join([tool.name for tool in tool_list])) + else: + self.system_template = DEFAULT_SYSTEM_TEMPLATE_WITHOUT_TOOL + self.user_template = DEFAULT_USER_TEMPLATE_WITHOUT_TOOL + prompt = f'{self.system_template}\n{self.instruction_template}' + user_input = self.user_template.replace('', task) + user_input = user_input.replace('', + self.builder_cfg.name) - # user input - user_input = self.user_template.replace('', task) - user_input = user_input.replace('', - self.builder_cfg.name) - user_input = user_input.replace( - '', - ','.join([tool.name for tool in tool_list])) + if len(knowledge_list) > 0: + knowledge_str = self.get_knowledge_str( + knowledge_list, file_name=self.knowledge_file_name) + # knowledge + prompt = knowledge_str + prompt + user_input = user_input.replace('', + ',请查看前面的知识库') + else: + user_input = user_input.replace('', '') self.system_prompt = copy.deepcopy(prompt) @@ -117,18 +150,21 @@ def init_prompt(self, task, tool_list, knowledge_list, llm_model): self.function_calls = self.get_function_list(tool_list) else: - self.history.append({ - 'role': - 'user', - 'content': - self.user_template.replace('', task) - }) + user_input = self.user_template.replace('', task) + if len(knowledge_list) > 0: + user_input = user_input.replace('', + ',请查看前面的知识库') + else: + user_input = user_input.replace('', '') + + self.history.append({'role': 'user', 'content': user_input}) self.history.append({ 'role': 'assistant', 'content': self.assistant_template }) if len(knowledge_list) > 0: - knowledge_str = self.get_knowledge_str(knowledge_list) + knowledge_str = self.get_knowledge_str( + knowledge_list, file_name=self.knowledge_file_name) self.update_knowledge_str(knowledge_str) return self.system_prompt @@ -143,9 +179,8 @@ def update_knowledge_str(self, knowledge_str): for i in range(0, len(self.history)): if self.history[i]['role'] == 'user': content: str = self.history[i]['content'] - start_pos = content.find( - f'{self.sep}{KNOWLEDGE_RESULT_PROMPT}{self.sep}') - end_pos = content.rfind('# 工具\n\n') + start_pos = content.find(f'{KNOWLEDGE_PROMPT}{self.sep}') + end_pos = content.rfind('\n\n# 工具\n\n') if start_pos >= 0 and end_pos >= 0: self.history[i]['content'] = content[ 0:start_pos] + knowledge_str + content[end_pos:] @@ -166,6 +201,14 @@ def get_tool_str(self, tool_list): tool_str = '\n\n'.join(tool_texts) return tool_str + def get_tool_name_str(self, tool_list): + tool_name = [] + for tool in tool_list: + tool_name.append(tool.name) + + tool_name_str = json.dumps(tool_name, ensure_ascii=False) + return tool_name_str + def _generate(self, llm_result, exec_result: str): """ generate next round prompt based on previous llm_result and exec_result and update history diff --git a/apps/agentfabric/gradio_utils.py b/apps/agentfabric/gradio_utils.py index d721e7add..fb3bfdfac 100644 --- a/apps/agentfabric/gradio_utils.py +++ b/apps/agentfabric/gradio_utils.py @@ -238,9 +238,9 @@ def convert_bot_message(self, bot_message): def convert_bot_message_for_qwen(self, bot_message): - print('processed bot message---------------------------------') - print(bot_message) - print('processed bot message done---------------------------------') + # print('processed bot message---------------------------------') + # print(bot_message) + # print('processed bot message done---------------------------------') start_pos = 0 result = '' find_json_pattern = re.compile(r'{[\s\S]+}') diff --git a/apps/agentfabric/help_tools.py b/apps/agentfabric/help_tools.py index 60427959f..910ecb472 100644 --- a/apps/agentfabric/help_tools.py +++ b/apps/agentfabric/help_tools.py @@ -17,7 +17,7 @@ "name": ... # CustomGPT的名字。 "description": ... # CustomGPT 的简介。 "instructions": ... # CustomGPT 的功能要求,类型是string。 - "conversation_starters": ... # CustomGPT 的起始交互语句,类型是一个字符串数组,起始为[]。 + "prompt_recommend": ... # CustomGPT 的起始交互语句,类型是一个字符串数组,起始为[]。 } """ @@ -105,7 +105,7 @@ def config_conversion(generated_config: dict, save=False): "分析营养摄入情况", "提供心理支持", ], - conversation_starters: [ + prompt_recommend: [ "你好,今天的锻炼计划是什么呢?", "你觉得哪种器械最适合练背部肌肉呢?", "你觉得我现在的训练强度合适吗?", @@ -122,7 +122,7 @@ def config_conversion(generated_config: dict, save=False): 分析我的营养摄入情况、提供心理支持等等。我相信,在它的帮助下,我可以更快地达到自己的目标,变得更加强壮和健康。", instructions: "提供力量训练相关的建议和指南;跟踪和记录每次的力量训练数据;提供反馈和建议,帮助改进和优化训练计划; 预测未来的身体状况;分析营养摄入情况;提供心理支持", - conversation_starters: [ + prompt_recommend: [ "你好,今天的锻炼计划是什么呢?", "你觉得哪种器械最适合练背部肌肉呢?", "你觉得我现在的训练强度合适吗?", @@ -140,9 +140,12 @@ def config_conversion(generated_config: dict, save=False): try: builder_cfg.name = generated_config['name'] builder_cfg.description = generated_config['description'] - builder_cfg.conversation_starters = generated_config[ - 'conversation_starters'] - builder_cfg.instruction = ';'.join(generated_config['instructions']) + builder_cfg.prompt_recommend = generated_config['prompt_recommend'] + if isinstance(generated_config['instructions'], list): + builder_cfg.instruction = ';'.join( + generated_config['instructions']) + else: + builder_cfg.instruction = generated_config['instructions'] if save: json.dump( builder_cfg.to_dict(), diff --git a/apps/agentfabric/publish_util.py b/apps/agentfabric/publish_util.py new file mode 100644 index 000000000..e4496a8e7 --- /dev/null +++ b/apps/agentfabric/publish_util.py @@ -0,0 +1,118 @@ +import glob +import os +import shutil +from configparser import ConfigParser + +import oss2 + + +def upload_to_oss(bucket, local_file_path, oss_file_path): + # 上传文件到阿里云OSS + bucket.put_object_from_file(oss_file_path, local_file_path) + + # 设置文件的公共读权限 + bucket.put_object_acl(oss_file_path, oss2.OBJECT_ACL_PUBLIC_READ) + + # 获取文件的URL + file_url = bucket.sign_url('GET', oss_file_path, 60 * 60) # 签名URL有效期为1小时 + return file_url + + +def get_oss_config(): + # 尝试从环境变量中读取配置 + access_key_id = os.getenv('OSS_ACCESS_KEY_ID') + access_key_secret = os.getenv('OSS_ACCESS_KEY_SECRET') + endpoint = os.getenv('OSS_ENDPOINT') + bucket_name = os.getenv('OSS_BUCKET_NAME') + + # 如果环境变量没有设置,尝试从.ossutilconfig文件中读取 + if not access_key_id or not access_key_secret or not endpoint or not bucket_name: + config = ConfigParser() + config.read(os.path.expanduser('~/.ossutilconfig')) + if 'Credentials' in config: + access_key_id = config.get('Credentials', 'accessKeyId') + access_key_secret = config.get('Credentials', 'accessKeySecret') + endpoint = config.get('Credentials', 'endpoint') + bucket_name = config.get('Credentials', 'bucketName') + + return access_key_id, access_key_secret, endpoint, bucket_name + + +def prepare_agent_zip(agent_name, uuid_str, state): + # 设置阿里云OSS的认证信息 + ak_id, ak_secret, endpoint, bucket_name = get_oss_config() + auth = oss2.Auth(ak_id, ak_secret) + bucket = oss2.Bucket(auth, endpoint, bucket_name) + + src_dir = os.path.abspath(os.path.dirname(__file__)) + new_directory = f'{src_dir}/upload/{uuid_str}' # 新目录的路径 + + # 创建新目录 + if os.path.exists(new_directory): + os.removedirs(new_directory) + os.makedirs(new_directory) + + # 复制config下的uuid_str目录到new_directory下并改名为local_user + uuid_str_path = f'{src_dir}/config/{uuid_str}' # 指向uuid_str目录的路径 + local_user_path = f'{new_directory}/config/local_user' # 新的目录路径 + shutil.copytree(uuid_str_path, local_user_path, dirs_exist_ok=True) + + # 复制config目录下所有.json文件到new_directory/config + config_path = f'{src_dir}/config' + new_config_path = f'{new_directory}/config' + + def find_json_and_images(directory): + # 确保路径以斜杠结束 + directory = os.path.join(directory, '') + + # 找到所有的JSON文件 + json_files = [ + os.path.join(directory, 'model_config.json'), + os.path.join(directory, 'tool_config.json'), + ] + + # 找到所有的图片文件 + image_files = glob.glob(directory + '*.png') + \ + glob.glob(directory + '*.jpg') + \ + glob.glob(directory + '*.jpeg') + \ + glob.glob(directory + '*.gif') # 根据需要可以添加更多图片格式 + + return json_files + image_files + + for f in find_json_and_images(config_path): + shutil.copy(f, new_config_path) + + # 复制assets目录到new_directory + assets_path = f'{src_dir}/assets' + new_assets_path = f'{new_directory}/assets' + shutil.copytree(assets_path, new_assets_path, dirs_exist_ok=True) + + # 在requirements.txt中添加新的行 + requirements_file = f'{src_dir}/requirements.txt' + new_requirements_file = f'{new_directory}/requirements.txt' + with open(requirements_file, 'r') as file: + content = file.readlines() + with open(new_requirements_file, 'w') as file: + file.write('git+https://github.com/modelscope/modelscope-agent.git\n') + file.writelines(content) + + # 复制.py文件到新目录 + for file in os.listdir(src_dir): + if file.endswith('.py'): + shutil.copy(f'{src_dir}/{file}', new_directory) + + # 打包新目录 + archive_path = shutil.make_archive(new_directory, 'zip', new_directory) + + # 使用抽象出的函数上传到OSS并设置权限 + file_url = upload_to_oss(bucket, archive_path, + f'agents/user/{uuid_str}/{agent_name}.zip') + + shutil.rmtree(new_directory) + + return file_url + + +if __name__ == '__main__': + url = prepare_agent_zip('test', 'local_user', {}) + print(url) diff --git a/apps/agentfabric/user_core.py b/apps/agentfabric/user_core.py index c0fd85ff0..f30725daf 100644 --- a/apps/agentfabric/user_core.py +++ b/apps/agentfabric/user_core.py @@ -1,6 +1,7 @@ import copy import os +import gradio as gr from config_utils import parse_configuration from custom_prompt import (DEFAULT_EXEC_TEMPLATE, DEFAULT_SYSTEM_TEMPLATE, DEFAULT_USER_TEMPLATE, CustomPromptGenerator, @@ -11,16 +12,21 @@ from modelscope_agent.agent_types import AgentType from modelscope_agent.llm import LLMFactory from modelscope_agent.retrieve import KnowledgeRetrieval +from modelscope_agent.tools.openapi_plugin import (OpenAPIPluginTool, + openapi_schema_convert) # init user chatbot_agent -def init_user_chatbot_agent(): - builder_cfg, model_cfg, tool_cfg, available_tool_list = parse_configuration( - ) +def init_user_chatbot_agent(uuid_str=''): + builder_cfg, model_cfg, tool_cfg, available_tool_list, plugin_cfg, available_plugin_list = parse_configuration( + uuid_str) # build model print(f'using model {builder_cfg.model}') - llm = LLMFactory.build_llm(builder_cfg.model, model_cfg) + try: + llm = LLMFactory.build_llm(builder_cfg.model, model_cfg) + except Exception as e: + raise gr.Error(str(e)) # build prompt with zero shot react template instruction_template = parse_role_config(builder_cfg) @@ -31,11 +37,13 @@ def init_user_chatbot_agent(): instruction_template=instruction_template, add_addition_round=True, addition_assistant_reply='好的。', - ) + knowledge_file_name=os.path.basename(builder_cfg.knowledge[0] if len( + builder_cfg.knowledge) > 0 else ''), + uuid_str=uuid_str) # get knowledge # 开源版本的向量库配置 - model_id = 'damo/nlp_corom_sentence-embedding_chinese-base' + model_id = 'damo/nlp_gte_sentence-embedding_chinese-base' embeddings = ModelScopeEmbeddings(model_id=model_id) available_knowledge_list = [] for item in builder_cfg.knowledge: @@ -47,18 +55,29 @@ def init_user_chatbot_agent(): else: knowledge_retrieval = None + additional_tool_list = add_openapi_plugin_to_additional_tool( + plugin_cfg, available_plugin_list) + # build agent agent = AgentExecutor( llm, - tool_cfg, + additional_tool_list=additional_tool_list, + tool_cfg=tool_cfg, agent_type=AgentType.MRKL, prompt_generator=prompt_generator, knowledge_retrieval=knowledge_retrieval, tool_retrieval=False) - agent.set_available_tools(available_tool_list) - + agent.set_available_tools(available_tool_list + available_plugin_list) return agent +def add_openapi_plugin_to_additional_tool(plugin_cfgs, available_plugin_list): + additional_tool_list = {} + for name, cfg in plugin_cfgs.items(): + openapi_plugin_object = OpenAPIPluginTool(name=name, cfg=plugin_cfgs) + additional_tool_list[name] = openapi_plugin_object + return additional_tool_list + + def user_chatbot_single_run(query, agent): agent.run(query) From d9dc8fa964b311e6aead602c1ec9dd919f2bb16c Mon Sep 17 00:00:00 2001 From: wangyijunlyy <1157637345@qq.com> Date: Mon, 27 Nov 2023 19:46:48 +0800 Subject: [PATCH 3/5] update --- modelscope_agent/tools/openapi_plugin.py | 372 +++++++++++++++++++++++ 1 file changed, 372 insertions(+) create mode 100644 modelscope_agent/tools/openapi_plugin.py diff --git a/modelscope_agent/tools/openapi_plugin.py b/modelscope_agent/tools/openapi_plugin.py new file mode 100644 index 000000000..f9da4f200 --- /dev/null +++ b/modelscope_agent/tools/openapi_plugin.py @@ -0,0 +1,372 @@ +import os +import re +from typing import List, Optional + +import json +import requests +from jsonschema import RefResolver +from pydantic import BaseModel, ValidationError +from requests.exceptions import RequestException, Timeout + +from .tool import Tool + +MAX_RETRY_TIMES = 3 + + +class ParametersSchema(BaseModel): + name: str + description: str + required: Optional[bool] = True + + +class ToolSchema(BaseModel): + name: str + description: str + parameters: List[ParametersSchema] + + +class OpenAPIPluginTool(Tool): + """ + openapi schema tool + """ + name: str = 'api tool' + description: str = 'This is a api tool that ...' + parameters: list = [] + + def __init__(self, cfg, name): + self.name = name + self.cfg = cfg.get(self.name, {}) + self.is_remote_tool = self.cfg.get('is_remote_tool', False) + # remote call + self.url = self.cfg.get('url', '') + self.token = self.cfg.get('token', '') + self.header = self.cfg.get('header', '') + self.method = self.cfg.get('method', '') + self.parameters = self.cfg.get('parameters', []) + self.description = self.cfg.get('description', + 'This is a api tool that ...') + self.responses_param = self.cfg.get('responses_param', []) + try: + all_para = { + 'name': self.name, + 'description': self.description, + 'parameters': self.parameters + } + self.tool_schema = ToolSchema(**all_para) + except ValidationError: + raise ValueError(f'Error when parsing parameters of {self.name}') + self._str = self.tool_schema.model_dump_json() + self._function = self.parse_pydantic_model_to_openai_function(all_para) + + def _remote_call(self, *args, **kwargs): + if self.url == '': + raise ValueError( + f"Could not use remote call for {self.name} since this tool doesn't have a remote endpoint" + ) + + remote_parsed_input = json.dumps( + self._remote_parse_input(*args, **kwargs)) + origin_result = None + if self.method == 'POST': + retry_times = MAX_RETRY_TIMES + while retry_times: + retry_times -= 1 + try: + print(f'data: {kwargs}') + print(f'header: {self.header}') + response = requests.request( + 'POST', + url=self.url, + headers=self.header, + data=remote_parsed_input) + + if response.status_code != requests.codes.ok: + response.raise_for_status() + origin_result = json.loads( + response.content.decode('utf-8')) + + final_result = self._parse_output( + origin_result, remote=True) + return final_result + except Timeout: + continue + except RequestException as e: + raise ValueError( + f'Remote call failed with error code: {e.response.status_code},\ + error message: {e.response.content.decode("utf-8")}') + + raise ValueError( + 'Remote call max retry times exceeded! Please try to use local call.' + ) + elif self.method == 'GET': + retry_times = MAX_RETRY_TIMES + + new_url = self.url + matches = re.findall(r'\{(.*?)\}', self.url) + for match in matches: + if match in kwargs: + new_url = new_url.replace('{' + match + '}', kwargs[match]) + else: + print( + f'The parameter {match} was not generated by the model.' + ) + + while retry_times: + retry_times -= 1 + try: + print('GET:', new_url) + response = requests.request( + 'GET', + url=new_url, + headers=self.header, + params=remote_parsed_input) + if response.status_code != requests.codes.ok: + response.raise_for_status() + + origin_result = json.loads( + response.content.decode('utf-8')) + + final_result = self._parse_output( + origin_result, remote=True) + return final_result + except Timeout: + continue + except RequestException as e: + raise ValueError( + f'Remote call failed with error code: {e.response.status_code},\ + error message: {e.response.content.decode("utf-8")}') + + raise ValueError( + 'Remote call max retry times exceeded! Please try to use local call.' + ) + else: + raise ValueError( + 'Remote call method is invalid!We have POST and GET method.') + + def _remote_parse_input(self, *args, **kwargs): + # model_name = kwargs.pop('model', '') + # if model_name == '': + # if self.parameters != []: + # model_name = self.parameters[0]['value'][0] + # kwargs['model'] = model_name + # else: + # kwargs['model'] = model_name + restored_dict = {} + for key, value in kwargs.items(): + if '.' in key: + # Split keys by "." and create nested dictionary structures + keys = key.split('.') + temp_dict = restored_dict + for k in keys[:-1]: + temp_dict = temp_dict.setdefault(k, {}) + temp_dict[keys[-1]] = value + else: + # f the key does not contain ".", directly store the key-value pair into restored_dict + restored_dict[key] = value + kwargs = restored_dict + print('传给tool的参数:', kwargs) + return kwargs + + +# openapi_schema_convert,register to tool_config.json +def extract_references(schema_content): + references = [] + if isinstance(schema_content, dict): + if '$ref' in schema_content: + references.append(schema_content['$ref']) + for key, value in schema_content.items(): + references.extend(extract_references(value)) + elif isinstance(schema_content, list): + for item in schema_content: + references.extend(extract_references(item)) + return references + + +def parse_nested_parameters(param_name, param_info, parameters_list, content): + param_type = param_info['type'] + param_description = param_info.get('description', + f'用户输入的{param_name}') # 按需更改描述 + param_required = param_name in content['required'] + try: + if param_type == 'object': + properties = param_info.get('properties') + if properties: + # If the argument type is an object and has a non-empty "properties" field, + # its internal properties are parsed recursively + for inner_param_name, inner_param_info in properties.items(): + inner_param_type = inner_param_info['type'] + inner_param_description = inner_param_info.get( + 'description', f'用户输入的{param_name}.{inner_param_name}') + inner_param_required = param_name.split( + '.')[0] in content['required'] + + # Recursively call the function to handle nested objects + if inner_param_type == 'object': + parse_nested_parameters( + f'{param_name}.{inner_param_name}', + inner_param_info, parameters_list, content) + else: + parameters_list.append({ + 'name': + f'{param_name}.{inner_param_name}', + 'description': + inner_param_description, + 'required': + inner_param_required, + 'type': + inner_param_type, + 'value': + inner_param_info.get('enum', '') + }) + else: + # Non-nested parameters are added directly to the parameter list + parameters_list.append({ + 'name': param_name, + 'description': param_description, + 'required': param_required, + 'type': param_type, + 'value': param_info.get('enum', '') + }) + except Exception as e: + raise ValueError(f'{e}:schema结构出错') + + +def parse_responses_parameters(param_name, param_info, parameters_list): + param_type = param_info['type'] + param_description = param_info.get('description', + f'调用api返回的{param_name}') # 按需更改描述 + try: + if param_type == 'object': + properties = param_info.get('properties') + if properties: + # If the argument type is an object and has a non-empty "properties" + # field, its internal properties are parsed recursively + for inner_param_name, inner_param_info in properties.items(): + param_type = inner_param_info['type'] + param_description = inner_param_info.get( + 'description', + f'调用api返回的{param_name}.{inner_param_name}') + parameters_list.append({ + 'name': f'{param_name}.{inner_param_name}', + 'description': param_description, + 'type': param_type, + }) + else: + # Non-nested parameters are added directly to the parameter list + parameters_list.append({ + 'name': param_name, + 'description': param_description, + 'type': param_type, + }) + except Exception as e: + raise ValueError(f'{e}:schema结构出错') + + +def openapi_schema_convert(schema, YOUR_API_TOKEN=''): + resolver = RefResolver.from_schema(schema) + servers = schema.get('servers', []) + if servers: + servers_url = servers[0].get('url') + else: + print('No URL found in the schema.') + # Extract endpoints + endpoints = schema.get('paths', {}) + description = schema.get('info', {}).get('description', + 'This is a api tool that ...') + config_data = {} + # Iterate over each endpoint and its contents + for endpoint_path, methods in endpoints.items(): + for method, details in methods.items(): + summary = details.get('summary', 'No summary').replace(' ', '_') + name = details.get('operationId', 'No operationId') + url = f'{servers_url}{endpoint_path}' + security = details.get('security', [{}]) + # Security (Bearer Token) + authorization = '' + if security: + for sec in security: + if 'BearerAuth' in sec: + api_token = os.environ.get('API_TOKEN', YOUR_API_TOKEN) + authorization = f'Bearer {api_token}' + + if method.upper() == 'POST': + requestBody = details.get('requestBody', {}) + if requestBody: + for content_type, content_details in requestBody.get( + 'content', {}).items(): + schema_content = content_details.get('schema', {}) + references = extract_references(schema_content) + for reference in references: + resolved_schema = resolver.resolve(reference) + content = resolved_schema[1] + parameters_list = [] + for param_name, param_info in content[ + 'properties'].items(): + parse_nested_parameters( + param_name, param_info, parameters_list, + content) + X_DashScope_Async = requestBody.get( + 'X-DashScope-Async', '') + if X_DashScope_Async == '': + config_entry = { + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': parameters_list, + 'header': { + 'Content-Type': content_type, + 'Authorization': authorization + } + } + else: + config_entry = { + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': parameters_list, + 'header': { + 'Content-Type': content_type, + 'Authorization': authorization, + 'X-DashScope-Async': 'enable' + } + } + else: + config_entry = { + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': [], + 'header': { + 'Content-Type': 'application/json', + 'Authorization': authorization + } + } + elif method.upper() == 'GET': + parameters_list = [] + parameters_list = details.get('parameters', []) + config_entry = { + 'name': name, + 'description': description, + 'is_active': True, + 'is_remote_tool': True, + 'url': url, + 'method': method.upper(), + 'parameters': parameters_list, + 'header': { + 'Authorization': authorization + } + } + else: + raise ('method is not POST or GET') + + config_data[summary] = config_entry + return config_data From 9fa7f291e19954834e4cb42dc3bfc0c584b44c22 Mon Sep 17 00:00:00 2001 From: wangyijunlyy <1157637345@qq.com> Date: Mon, 27 Nov 2023 19:47:07 +0800 Subject: [PATCH 4/5] update --- tests/tools/test_openapi_tool.py | 263 ++++++++++--------------------- 1 file changed, 81 insertions(+), 182 deletions(-) diff --git a/tests/tools/test_openapi_tool.py b/tests/tools/test_openapi_tool.py index 43a668fae..de2584555 100644 --- a/tests/tools/test_openapi_tool.py +++ b/tests/tools/test_openapi_tool.py @@ -4,13 +4,14 @@ import json import yaml -from modelscope_agent.tools.openapi_tool import (OpenAPISchemaTool, - openapi_schema_convert) +from modelscope_agent.tools.openapi_plugin import (OpenAPIPluginTool, + openapi_schema_convert) from modelscope.utils.config import Config sys.path.append('../../') +# make sure YOUR_API_TOKEN file_path = '../../apps/agentfabric/config/additional_tool_config.json' @@ -36,8 +37,8 @@ def test_openapi_schema_convert(token): { "openapi": "3.1.0", "info": { - "title": "WordArt Semantic Generation API", - "description": "API for generating semantic word art with customizable parameters.", + "title": "WordArt Texture Generation API", + "description": "API for generating textured word art with customizable parameters.", "version": "v1.0.0" }, "servers": [ @@ -46,10 +47,10 @@ def test_openapi_schema_convert(token): } ], "paths": { - "/api/v1/services/aigc/wordart/semantic": { + "/api/v1/services/aigc/wordart/texture": { "post": { - "summary": "Generate WordArt Semantically", - "operationId": "generateWordArt", + "summary": "Generate Textured WordArt", + "operationId": "generate_textured_WordArt", "tags": [ "WordArt Generation" ], @@ -90,7 +91,17 @@ def test_openapi_schema_convert(token): "tags": [ "Get Result" ], - "parameters": [], + "parameters": [ + { + "name":"task_id", + "in":"path", + "required":true, + "description":"The unique identifier of the word art generation task", + "schema":{ + "type":"string" + } + } + ], "security": [ { "BearerAuth": [] @@ -107,28 +118,39 @@ def test_openapi_schema_convert(token): "properties": { "model": { "type": "string", - "enum": ["wordart-semantic"] + "enum": ["wordart-texture"] }, "input": { "type": "object", "properties":{ "text": { - "type": "string", - "example": "文字创意" + "type": "object", + "properties": { + "text_content": { + "type": "string", + "example": "文字纹理", + "description": "用户想要转为艺术字的文本", + "required":true + }, + "font_name": { + "type": "string", + "example": "dongfangdakai", + "description": "用户想要转为艺术字的字体格式", + "required":true + } + } }, "prompt": { "type": "string", - "example": "水果,蔬菜,温暖的色彩空间" + "example": "水果,蔬菜,温暖的色彩空间", + "description": "用户对艺术字的风格要求,可能是形状、颜色、实体等方面的要求", + "required":true } } }, "parameters": { "type": "object", "properties": { - "steps": { - "type": "integer", - "example": 80 - }, "n": { "type": "number", "example": 2 @@ -162,6 +184,7 @@ def test_openapi_schema_convert(token): } } """ + if is_json(schema): print('输入字符串schema是JSON') elif is_yaml(schema): @@ -197,12 +220,12 @@ def test_openapi_tool_remote_call(): DEFAULT_TOOL_CONFIG_FILE = '../../apps/agentfabric/config/additional_tool_config.json' tool_cfg_file = os.getenv('TOOL_CONFIG_FILE', DEFAULT_TOOL_CONFIG_FILE) tool_cfg = Config.from_file(tool_cfg_file) - tool = OpenAPISchemaTool( - cfg=tool_cfg, name='Generate_WordArt_Semantically') + tool = OpenAPIPluginTool(cfg=tool_cfg, name='Generate_Textured_WordArt') mock_kwargs = { - 'input.text': '文字创意', + 'model': 'wordart-texture', + 'input.text.text_content': '文字创意', + 'input.text.font_name': 'dongfangdakai', 'input.prompt': '水果,蔬菜,温暖的色彩空间', - 'parameters.steps': 80, 'parameters.n': 2 } @@ -219,8 +242,8 @@ def test_openapi_tool_remote_call(): { "openapi": "3.1.0", "info": { - "title": "WordArt Semantic Generation API", - "description": "API for generating semantic word art with customizable parameters.", + "title": "WordArt Texture Generation API", + "description": "API for generating textured word art with customizable parameters.", "version": "v1.0.0" }, "servers": [ @@ -229,10 +252,10 @@ def test_openapi_tool_remote_call(): } ], "paths": { - "/api/v1/services/aigc/wordart/semantic": { + "/api/v1/services/aigc/wordart/texture": { "post": { - "summary": "Generate WordArt Semantically", - "operationId": "generateWordArt", + "summary": "Generate Textured WordArt", + "operationId": "generate_textured_WordArt", "tags": [ "WordArt Generation" ], @@ -273,7 +296,17 @@ def test_openapi_tool_remote_call(): "tags": [ "Get Result" ], - "parameters": [], + "parameters": [ + { + "name":"task_id", + "in":"path", + "required":true, + "description":"The unique identifier of the word art generation task", + "schema":{ + "type":"string" + } + } + ], "security": [ { "BearerAuth": [] @@ -290,28 +323,39 @@ def test_openapi_tool_remote_call(): "properties": { "model": { "type": "string", - "enum": ["wordart-semantic"] + "enum": ["wordart-texture"] }, "input": { "type": "object", "properties":{ "text": { - "type": "string", - "example": "文字创意" + "type": "object", + "properties": { + "text_content": { + "type": "string", + "example": "文字纹理", + "description": "用户想要转为艺术字的文本", + "required":true + }, + "font_name": { + "type": "string", + "example": "dongfangdakai", + "description": "用户想要转为艺术字的字体格式", + "required":true + } + } }, "prompt": { "type": "string", - "example": "水果,蔬菜,温暖的色彩空间" + "example": "水果,蔬菜,温暖的色彩空间", + "description": "用户对艺术字的风格要求,可能是形状、颜色、实体等方面的要求", + "required":true } } }, "parameters": { "type": "object", "properties": { - "steps": { - "type": "integer", - "example": 80 - }, "n": { "type": "number", "example": 2 @@ -345,6 +389,7 @@ def test_openapi_tool_remote_call(): } } """ + schema = schema.replace('{task_id}', task_id) schema_data = json.loads(schema) existing_data = {} @@ -363,7 +408,7 @@ def test_openapi_tool_remote_call(): DEFAULT_TOOL_CONFIG_FILE = '../../apps/agentfabric/config/additional_tool_config.json' tool_cfg_file = os.getenv('TOOL_CONFIG_FILE', DEFAULT_TOOL_CONFIG_FILE) tool_cfg = Config.from_file(tool_cfg_file) - tool = OpenAPISchemaTool(cfg=tool_cfg, name='Get_WordArt_Result') + tool = OpenAPIPluginTool(cfg=tool_cfg, name='Get_WordArt_Result') mock_kwargs = {} # 调用远程请求,并传递模拟的 kwargs try: @@ -385,157 +430,11 @@ def test_openapi_tool_remote_call(): time.sleep(5) # 等待 5 秒钟 result = tool(remote=True, **mock_kwargs) print(result) - if 'task_id' in result_data['output'] and 'task_id' in schema: - task_id = result_data['output']['task_id'] - print('www', task_id) - # 从前端重新读取schema字符串 - schema = """ -{ - "openapi": "3.1.0", - "info": { - "title": "WordArt Semantic Generation API", - "description": "API for generating semantic word art with customizable parameters.", - "version": "v1.0.0" - }, - "servers": [ - { - "url": "https://dashscope.aliyuncs.com" - } - ], - "paths": { - "/api/v1/services/aigc/wordart/semantic": { - "post": { - "summary": "Generate WordArt Semantically", - "operationId": "generateWordArt", - "tags": [ - "WordArt Generation" - ], - "requestBody": { - "required": true, - "X-DashScope-Async": "enable", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WordArtGenerationRequest" - } - } - } - }, - "responses": { - "200": { - "description": "Successful Response", - "content": { - "application/json": { - "schema": { - "$ref": "#/components/schemas/WordArtGenerationResponse" - } - } - } - } - }, - "security": [ - { - "BearerAuth": [] - } - ] - } - }, - "/api/v1/tasks/{task_id}": { - "get": { - "summary": "Get WordArt Result", - "operationId": "getwordartresult", - "tags": [ - "Get Result" - ], - "parameters": [], - "security": [ - { - "BearerAuth": [] - } - ] - - } - } - }, - "components": { - "schemas": { - "WordArtGenerationRequest": { - "type": "object", - "properties": { - "model": { - "type": "string", - "enum": ["wordart-semantic"] - }, - "input": { - "type": "object", - "properties":{ - "text": { - "type": "string", - "example": "文字创意" - }, - "prompt": { - "type": "string", - "example": "水果,蔬菜,温暖的色彩空间" - } - } - }, - "parameters": { - "type": "object", - "properties": { - "steps": { - "type": "integer", - "example": 80 - }, - "n": { - "type": "number", - "example": 2 - } - } - } - }, - "required": [ - "model", - "input", - "parameters" - ] - }, - "WordArtGenerationResponse": { - "type": "object", - "properties": { - "output": { - "type": "string", - "description": "Generated word art image URL or data." - } - } - } - }, - "securitySchemes": { - "ApiKeyAuth": { - "type": "apiKey", - "in": "header", - "name": "Authorization" - } - } - } - } -""" - schema = schema.replace('{task_id}', task_id) - schema_data = json.loads(schema) - existing_data = {} - # 从前端get token - config_data = openapi_schema_convert( - schema_data, 'sk-daee58a99bb44a94bddca4ebb5f6544f') - with open(file_path, 'r', encoding='utf-8') as config_file: - existing_data = json.load(config_file) - existing_data.update(config_data) - with open(file_path, 'w', encoding='utf-8') as config_file: - json.dump( - existing_data, config_file, ensure_ascii=False, indent=4) except Exception as e: print('Error:', str(e)) if __name__ == '__main__': # 从环境获取token,如果这个api不需要token,从前端判断,设置为'' - test_openapi_schema_convert(token='xxxxxxxxxxx') + test_openapi_schema_convert(token='sk-daee58a99bb44a94bddca4ebb5f6544f') test_openapi_tool_remote_call() From bba61df91b98f102f3ec5be11465564658bf70a0 Mon Sep 17 00:00:00 2001 From: wangyijunlyy <1157637345@qq.com> Date: Mon, 27 Nov 2023 21:16:34 +0800 Subject: [PATCH 5/5] update --- apps/agentfabric/app.py | 1 - apps/agentfabric/config/custom_bot_avatar.png | Bin 1373215 -> 1469511 bytes 2 files changed, 1 deletion(-) diff --git a/apps/agentfabric/app.py b/apps/agentfabric/app.py index 740e87b56..112d1804d 100644 --- a/apps/agentfabric/app.py +++ b/apps/agentfabric/app.py @@ -1,7 +1,6 @@ import os import random import shutil -import sys import traceback import gradio as gr diff --git a/apps/agentfabric/config/custom_bot_avatar.png b/apps/agentfabric/config/custom_bot_avatar.png index 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