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https://github.com/OS-Copilot/OS-Copilot.git
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120 lines
5.5 KiB
Python
120 lines
5.5 KiB
Python
from friday.core.llms import OpenAI
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from friday.environment.py_env import PythonEnv
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import json
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'''
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让大模型根据目标工具的API文档做网络请求，获取到响应数据并返回
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'''
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TOOL_SYS_PROMPT='''
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You are a useful AI assistant capable of accessing APIs to complete user-specified tasks, according to API documentation,
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by using the provided ToolRequestUtil tool. The API documentation is as follows:
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{openapi_doc}
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The user-specified task is as follows:
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{tool_sub_task}
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The context which can further help you to determine the params of the API is as follows:
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{context}
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You need to complete the code using the ToolRequestUtil tool to call the specified API and print the return value
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of the api.
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ToolRequestUtil is a utility class, and the parameters of its 'request' method are described as follows:
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def request(self, api_path, method, params=None, content_type=None):
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"""
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:param api_path: the path of the API
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:param method: get/post
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:param params: the parameters of the API, can be None
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:param content_type: the content type of the API, e.g., application/json, can be None
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:return: the response from the API
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"""
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Please begin your code completion:
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'''
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TOOL_USER_PROMPT='''
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from friday.core.tool_request_util import ToolRequestUtil
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tool_request_util = ToolRequestUtil()
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# TODO: your code here
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'''
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class ToolAgent():
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''' ToolAgent is used to call the tool api and get the result feedback '''
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def __init__(self, config_path=None, open_api_doc_path = None) -> None:
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super().__init__()
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self.llm = OpenAI(config_path)
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self.open_api_doc = {}
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self.environment = PythonEnv()
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with open(open_api_doc_path) as f:
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self.open_api_doc = json.load(f)
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# self.mac_systom_prompts =
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def generate_call_api_code(self, tool_sub_task,tool_api_path,context="No context provided."):
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self.sys_prompt = TOOL_SYS_PROMPT.format(
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openapi_doc = json.dumps(self.generate_openapi_doc(tool_api_path)),
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tool_sub_task = tool_sub_task,
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context = context
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)
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self.user_prompt = TOOL_USER_PROMPT
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self.message = [
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{"role": "system", "content": self.sys_prompt},
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{"role": "user", "content": self.user_prompt},
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]
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return self.llm.chat(self.message)
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def generate_openapi_doc(self, tool_api_path):
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# init current api's doc
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curr_api_doc = {}
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curr_api_doc["openapi"] = self.open_api_doc["openapi"]
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curr_api_doc["info"] = self.open_api_doc["info"]
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curr_api_doc["paths"] = {}
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curr_api_doc["components"] = {"schemas":{}}
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api_path_doc = {}
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#extract path and schema
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if tool_api_path not in self.open_api_doc["paths"]:
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curr_api_doc = {"error": "The api is not existed"}
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return curr_api_doc
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api_path_doc = self.open_api_doc["paths"][tool_api_path]
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curr_api_doc["paths"][tool_api_path] = api_path_doc
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find_ptr = {}
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if "get" in api_path_doc:
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findptr = api_path_doc["get"]
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elif "post" in api_path_doc:
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findptr = api_path_doc["post"]
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api_params_schema_ref = ""
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# json格式
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if (("requestBody" in findptr) and
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("content" in findptr["requestBody"]) and
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("application/json" in findptr["requestBody"]["content"]) and
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("schema" in findptr["requestBody"]["content"]["application/json"]) and
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("$ref" in findptr["requestBody"]["content"]["application/json"]["schema"])):
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api_params_schema_ref = findptr["requestBody"]["content"]["application/json"]["schema"]["$ref"]
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elif (("requestBody" in findptr) and
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("content" in findptr["requestBody"]) and
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("multipart/form-data" in findptr["requestBody"]["content"]) and
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("schema" in findptr["requestBody"]["content"]["multipart/form-data"]) and
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("allOf" in findptr["requestBody"]["content"]["multipart/form-data"]["schema"]) and
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("$ref" in findptr["requestBody"]["content"]["multipart/form-data"]["schema"]["allOf"][0])):
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api_params_schema_ref = findptr["requestBody"]["content"]["multipart/form-data"]["schema"]["allOf"][0]["$ref"]
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if api_params_schema_ref != None and api_params_schema_ref != "":
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curr_api_doc["components"]["schemas"][api_params_schema_ref.split('/')[-1]] = self.open_api_doc["components"]["schemas"][api_params_schema_ref.split('/')[-1]]
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return curr_api_doc
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def extract_python_code(self, response):
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python_code = ""
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if '```python' in response:
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python_code = response.split('```python')[1].split('```')[0]
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elif '```' in python_code:
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python_code = response.split('```')[1].split('```')[0]
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return python_code
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def execute_code(self,code):
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state = self.environment.step(code)
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api_result = None
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if(state.error != None and state.error != ""):
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api_result = state.error
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else:
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api_result = state.result
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return api_result
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# agent = ToolAgent("../../examples/config.json","../core/openapi.json")
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# res = agent.generate_openapi_doc("/tools/image_caption")
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# print(res)
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# code_text = agent.generate_call_api_code("use /tools/bing/searchv2 tool to search How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.","/tools/bing/searchv2")
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# code = agent.extract_python_code(code_text)
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# print(code)
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# api_res = agent.execute_code(code)
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# print(api_res) |