Metadata-Version: 1.0
Name: robotgpt
Version: 0.0.6
Summary: RobotGPT LLM 支持Langchain
Home-page: https://src.cloudminds.com/ai-api/robotgptllm
Author: blaze.zhang
Author-email: blaze.zhang@cloudminds.com
License: UNKNOWN
Description: * RobotGPT LLM
        
            RobotGPT 支持langchain
        
        * Quick Install
        
            `pip install robotgpt`
        
        * 使用样例
        
        agent块式输出::
        
            from robotgpt.robotgpt import RobotGPTLLM
            from langchain.agents import AgentType, initialize_agent
            from langchain.tools import BaseTool, StructuredTool, Tool, tool
            class CoffeeMaking:
                def inference(self):
                    return "Making coffee requires a coffee machine, coffee beans, sugar packets, and paper cups."
            
            class ImageObjectDetect:
                def inference(self, obj):
                    if obj == "sugar packets":
                        return "No "+obj
                    return "There is a "+obj
            
            class AskCustomer:
                def inference(self,):
                    return "Hello! We don’t have any sugar packets at the moment. Do you need to add milk?"
            
            robotgpt_api_url = "https://dataai.harix.iamidata.com/llm/api/ask"  #流式智能问答统一适配服务，从用户控制台购买https://console.openai.iamidata.com/api/apiList
            model_name = "openai/gpt-3.5-turbo-0613"
            robotgpt_api_token = "Your token" #https://dataai-doc.dataarobotics.com/docs/getting-started/authentication
            llm = RobotGPTLLM(temperature=0, model_name=model_name,robotgpt_api_token=robotgpt_api_token,robotgpt_api_url=robotgpt_api_url)
            
            imgObjDetect = ImageObjectDetect()
            tools = [
                Tool.from_function(
                    func=CoffeeMaking.inference,
                    name="Coffee making",
                    description="useful for when the user needs to make coffee."
                    # coroutine= ... <- you can specify an async method if desired as well
                ),
                Tool.from_function(
                    func=imgObjDetect.inference,
                    name="Determine whether the object exists in the picture",
                    description="useful for when you want to know what is inside the photo. receives object as input. The input to this tool should be a string, representing the object. "
                    # coroutine= ... <- you can specify an async method if desired as well
                ),
                Tool.from_function(
                    func=AskCustomer.inference,
                    name="Ask the customer whether to add milk",
                    description="useful for when making coffee without sugar packets, you can ask the customer whether you need to add milk. The input to this tool should be a bool, represents whether there is a sugar packet."
                    # coroutine= ... <- you can specify an async method if desired as well
                ),
            ]
            agent = initialize_agent(
                tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
            )
            agent.run(
                "给我做杯咖啡"
            )      
            
        块式输出::
        
            from robotgpt.robotgpt import RobotGPTLLM
            from langchain.schema import HumanMessage
            
            robotgpt_api_url = "https://dataai.harix.iamidata.com/llm/api/ask"  #流式智能问答统一适配服务
            model_name = "openai/gpt-3.5-turbo-0613"
            robotgpt_api_token = "Your token" #https://dataai-doc.dataarobotics.com/docs/getting-started/authentication
            
            llm = RobotGPTLLM(temperature=0, model_name=model_name,robotgpt_api_token=robotgpt_api_token,robotgpt_api_url=robotgpt_api_url)
            resp = llm([HumanMessage(content="Write me a song about sparkling water.")])
            print(resp)
        
        流式输出::
            
            from langchain.callbacks import StreamingStdOutCallbackHandler
            from langchain.schema import HumanMessage
            from robotgpt.robotgpt import RobotGPTLLM
            robotgpt_api_url = "https://dataai.harix.iamidata.com/llm/api/ask"  #流式智能问答统一适配服务
            model_name = "openai/gpt-3.5-turbo-0613"
            robotgpt_api_token = "Your token" #https://dataai-doc.dataarobotics.com/docs/getting-started/authentication
            chat = RobotGPTLLM(streaming=True, callbacks=[StreamingStdOutCallbackHandler()], temperature=0,model_name=model_name,robotgpt_api_token=robotgpt_api_token,robotgpt_api_url=robotgpt_api_url)
            resp = chat([HumanMessage(content="Write me a song about sparkling water.")])
            print(resp)
Platform: UNKNOWN
