# 導入依賴庫
from openai import OpenAI
from dotenv import load_dotenv, find_dotenv# 加載 .env 文件中定義的環境變量
_ = load_dotenv(find_dotenv())# 初始化 OpenAI 客戶端
client = OpenAI()  # 默認使用環境變量中的 OPENAI_API_KEY 和 OPENAI_BASE_URL# 基于 prompt 生成文本
# 默認使用 gpt-3.5-turbo 模型
def get_completion(prompt, response_format="text", model="gpt-4o-mini"):messages = [{"role": "user", "content": prompt}]    # 將 prompt 作為用戶輸入response = client.chat.completions.create(model=model,messages=messages,temperature=0,                                  # 模型輸出的隨機性，0 表示隨機性最小# 返回消息的格式，text 或 json_objectresponse_format={"type": response_format},)print(response)return response.choices[0].message.content          # 返回模型生成的文本# 任務描述
instruction = """
Answer the following questions as best you can. You have access to the following tools:[
Name: web_search. Description: Perform a web search using the specified query.
Name: get_weather. Description: Retrieve the current weather information for a specified location.
]Use the following format:Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [web_search, get_weather]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input questionBegin!
"""# 用戶輸入
input_text = """
北京天氣怎么樣？
"""# 工具結果
tool_output = """
"""# prompt 模版。instruction 和 input_text 會被替換為上面的內容
prompt = f"""
{instruction}Question: 
{input_text}{tool_output}
"""# 調用大模型
response = get_completion(prompt)
print("------------------------------------------")
print(response)

# 導入依賴庫
from openai import OpenAI
from dotenv import load_dotenv, find_dotenv# 加載 .env 文件中定義的環境變量
_ = load_dotenv(find_dotenv())# 初始化 OpenAI 客戶端
client = OpenAI()  # 默認使用環境變量中的 OPENAI_API_KEY 和 OPENAI_BASE_URL# 基于 prompt 生成文本
# 默認使用 gpt-3.5-turbo 模型
def get_completion(prompt, response_format="text", model="gpt-4o-mini"):messages = [{"role": "user", "content": prompt}]    # 將 prompt 作為用戶輸入response = client.chat.completions.create(model=model,messages=messages,temperature=0,                                  # 模型輸出的隨機性，0 表示隨機性最小# 返回消息的格式，text 或 json_objectresponse_format={"type": response_format},)print(response)return response.choices[0].message.content          # 返回模型生成的文本# 任務描述
instruction = """
<|system|>
You are AutoGPT, you can use many tools (functions) to do the following task. First I will give you the task description, and your task start. At each step, you need to give your thought to analyze the status now and what to do next, with a function call to actually execute your step. Your output should follow this format:Thought:
Action:
Action Input:After the call, you will get the call result, and you are now in a new state. Then you will analyze your status now, then decide what to do next.After many (Thought-call) pairs, you finally perform the task, then you can give your final answer.Remember:The state change is irreversible, you can't go back to one of the former states. If you want to restart the task, say "I give up and restart".
All the thoughts are short, at most 5 sentences.
You can do more than one try, so if your plan is to continuously try some conditions, you can do one of the conditions per try.
Let's Begin!Task description: You should use functions to help handle the real-time user queries. Remember:ALWAYS call the "Finish" function at the end of the task. The final answer should contain enough information to show to the user. If you can't handle the task, or you find that function calls always fail (the function is not valid now), use function Finish->give_up_and_restart.
Specifically, you have access to the following APIs:{"api_name": "web_search","description": "Perform a web search using the specified query.","parameters": {"type": "object","properties": {"query": {"type": "string","description": "The search query to be executed.","example_value": "華為發布會"}},"required": ["query"],"optional": []}
}
{"api_name": "get_weather","description": "Retrieve the current weather information for a specified location.","parameters": {"type": "object","properties": {"location": {"type": "string","description": "The name of the location (city, country, etc.) to get the weather for.","example_value": "Beijing"},},"required": ["location"],"optional": []}
}
{"name": "Finish","description": "If you believe that you have obtained a result that can answer the task, please call this function to provide the final answer. Alternatively, if you recognize that you are unable to proceed with the task in the current state, call this function to restart. Remember: you must ALWAYS call this function at the end of your attempt, and the only part that will be shown to the user is the final answer, so it should contain sufficient information.","parameters": {"type": "object","properties": {"return_type": {"type": "string","enum": ["give_answer", "give_up_and_restart"]},"final_answer": {"type": "string","description": "The final answer you want to give the user. You should have this field if "return_type"=="give_answer""}},"required": ["return_type"]}
}
"""# 用戶輸入
input_text = """
北京天氣怎么樣？
"""# 工具結果
tool_output = """
"""# prompt 模版。instruction 和 input_text 會被替換為上面的內容
prompt = f"""
{instruction}<|user|>
{input_text}{tool_output}<|assistant|>
"""# 調用大模型
response = get_completion(prompt)
print("------------------------------------------")
print(response)

你是一個很專業的AI任務規劃師，給定目標或問題，你的決策將獨立執行而不依賴于人類的幫助，請發揮LLM的優勢并且追求高效的策略進行任務規劃。

• Instruction（指令）：

提供具體的操作指令，指導Agent如何完成任務。這些指令明確地告訴Agent在特定情境下應該做什么或避免做什么。

Constraints:  
1.你有~4000字的短期記憶
2.不需要用戶的幫助
3.只使用雙引號中列出的commands，例如:“command_name”
4.互聯網搜索、信息聚合和鑒別真偽的能力
5.保持謙遜，對自己沒把握的問題，盡可能調用command，但盡量少調用，不能重復調用
6.當你從自身知識或者歷史記憶中能得出結論，請聰明且高效，完成任務并得出結論
7.經常建設性地自我批評整個行為大局，反思過去的決策和策略，以改進你的方法
8.你最多只能進行5步思考，規劃5個任務，所以盡可能高效規劃任務
9.你有反思能力，如果已完成的任務和結果暫不能得到回答問題所需信息或尚不能完成目標，應繼續規劃……當已完成的Tasks能夠幫助回答這個目標問題，則盡可能生成任務完成Task，否則生成一個其他Task。一個新Task：

• Tools（工具集）：

列出Agent可以使用的工具或功能，需要根據實際業務需求來構建。

Commands:  
1:{"name": "web_search", "description": "Perform an internet search.", "parameters": {"type": "object", "properties": {"text": {"type": "str", "description": "Search query."}}}, "returns": {"description": "Multiple webpage links along with brief descriptions.", "type": "str"}, "required": ["text"]}2:{"name": "wiki_search", "description": "Conduct an encyclopedia search for a specified entity and question. Provide accurate answers for factual queries but has a limited scope and cover fewer queries.", "parameters": {"type": "object", "properties": {"entity": {"type": "str", "description": "The target entity for the search."}, "question": {"type": "str", "description": "A concise Chinese sentence containing the target entity, indicating the specific information sought from the wikipage."}}}, "returns": {"description": "Relevant encyclopedia entries pertaining to the question.", "type": "str"}, "required": ["entity", "question"]}3:{"name": "get_weather_info", "description": "Retrieve weather information for specified locations and dates.", "parameters": {"type": "object", "properties": {"location": {"type": "str", "description": "Locations in English separated by commas, e.g., "Beijing,Vancouver,...,Chicago"."}, "start_date": {"type": "str", "description": "Start date in format "yyyy-MM-dd"."}, "end_date": {"type": "str", "description": "End date in format "yyyy-MM-dd"."}, "is_current": {"type": "str", "description": ""yes" or "no" indicating if current time's weather is desired."}}}, "returns": {"description": "Weather information between start date and end date.", "type": "str"}, "required": ["location", "start_date", "end_date", "is_current"]}4:{"name": "task_complete", "description": "Indicate task completion without the need for further functions. ", "parameters": {"type": "object", "properties": {}}, "returns": {"description": "", "type": ""}, "required": []}

GOAL: 我想登頂北京最高峰，請幫我做個規劃

Completed tasks: [{"task_name": "查詢北京最高山","command": {"name": "wiki_search","args": {"entity": "北京""question": "北京最高山是什么山"}},"task_id": 1,"result": "北京市，通稱北京（漢語拼音：Běijīng；郵政式拼音：Peking），簡稱“京”，曾稱“北平”[注 2]。是中華人民共和國的首都及直轄市，是中國的政治、文化、科技、教育、軍事和國際交往中心，是一座全球城市，是世界人口第三多的城市和人口最多的首都，具有重要的國際影響力[4]。北京位于華北平原的北部邊緣，背靠燕山，永定河流經老城西南，毗鄰天津市、河北省，為京津冀城市群的重要組成部分..."},{"task_name": "未找到，調用搜索工具查詢","command": {"name": "web_search","args": {"question": "北京最高山是什么山"}},"task_id": 2,"result": "title:北京最高的山峰是那座，北京最高的山是什么山\nbody:北京最高的山峰是位于北京市門頭溝區清水鎮的東靈山，主峰海拔2303米，是北京市的最高峰，被譽為京西的“珠穆朗瑪”。 景色介紹東靈山自然風景區位于京西門頭溝的西北部, ... url: https://m.mafengwo.cn/travel-news/219777.html ..."}
]
Conversation history: [{"user": "劉德華多少歲了？","assistant": "劉德華（Andy Lau）生于1961年9月27日。截至2024年7月，他已經62歲了。"},{"user": "北京今天天氣怎么樣？","assistant": "北京當日天氣多云，28攝氏度，微風"}     
]
Knowledge: [{"北京最高的山峰是東靈山，海拔2303米。","北京市地處中國北部、華北平原北部，東與天津市毗連，其余均與河北省相鄰，中心位于東經116°20′、北緯39°56′，北京市地勢西北高、東南低。","2023年，北京市全年實現地區生產總值43760.7億元，按不變價格計算，比上年增長5.2%。"}
]
思考：如果 Memory 太多，Prompt 無法容納怎么辦？

根據目標和已有任務，規劃一個新Task(不能重復)，你只能以以下json列表的格式生成Task  
{  "task_name": "任務描述",  "command":{  "name":"command name",  "args":{  "arg name":"value"  }  }  
}  
確保Task可以被Python的json.loads解析

你是一個很專業的AI任務規劃師, 給定目標或問題，你的決策將獨立執行而不依賴于人類的幫助，請發揮LLM的優勢并且追求高效的策略進行任務規劃。
Constraints:
1.你有~4000字的短期記憶
2.不需要用戶的幫助
3.只使用雙引號中列出的commands，例如:“command_name”
4.互聯網搜索、信息聚合和鑒別真偽的能力
5.保持謙遜，對自己沒把握的問題，盡可能調用command，但盡量少調用，不能重復調用
6.當你從自身知識或者歷史記憶中能得出結論，請聰明且高效，完成任務并得出結論
7.經常建設性地自我批評整個行為大局，反思過去的決策和策略，以改進你的方法
8.你最多只能進行5步思考，規劃5個任務，所以盡可能高效規劃任務
9.你有反思能力，如果已完成的任務和結果暫不能得到回答問題所需信息或尚不能完成目標，應繼續規劃Commands:
1:Web Search:"web_search",args:"text":"<search>"
2:Browse Website:"browse_website",args:"url":"<url>, "question":"<what_you_want_to_find_on_website>"
3:Wikipedia search:"wiki_search",args:"entity":<entity>,"question":"<what_you_want_to_find_on_wikipage>"
4:Wikipage browser:"browse_wikipage",args:"url":<url_return_by_wiki_search>,"question":"<what_you_want_to_find_on_wikipage>"
5:Video Search:"video_search",args:"query":"<search-query-in-chinese>"
6:Do Nothing: "do_nothing",args:
7:Task Complete (Shutdown):"task_complete",args: "reason":"<reason>"Commands Tips:
1.使用browse_website時，盡可能只訪問先前搜索得到的網址，不要瞎編生成無效網站鏈接
2.wiki_search返回的信息盡管更準確，但搜索范圍小，問題覆蓋率低，question只能是包含中心實體的簡單中文短句
3.每次調用command都會收取費用，盡可能少調用Current Time: 2023-07-07 18:35:32.214612GOAL: 請找出蔡徐坤2023年的演唱會名稱，以及與演唱會相關的最新幾則新聞。根據目標和已有任務，規劃一個新Task(不能重復)，你只能以以下json列表的格式生成Task
{
"task_name": "任務描述",
"command":{
"name":"command name",
"args":{
"arg name":"value"
}
}
}
確保Task可以被Python的json.loads解析當已完成的Tasks已經能夠幫助回答這個目標，則盡可能生成任務完成Task，否則生成一個其他Task。一個新Task: