deployment = "gpt4"
model = "gpt-4"

import openai
def convert(input):
    prompt = """
    按以下规则将0-100的数值，转化为A,B,C,D,E 5个等级:
    [80,100]之间 为 A
    [60,79]之间 为 B
    [40,59]之间 为 C
    [20,39]之间 为 D
    [0,19]之间 为 E
    仅输出数值对应的等级
    """
    response = openai.ChatCompletion.create(
        engine=deployment, # engine = "deployment_name".
        temperature = 0,
        messages=[
            {"role":"system","content":prompt},
            {"role": "user", "content": input}
        ]
      )
    return (response.choices[0].message.content)

print(convert("100"))

print(convert("15,70,50,23"))

import openai
response = openai.ChatCompletion.create(
    engine=deployment, # engine = "deployment_name".
    temperature = 0,
    messages=[
        {"role": "user", "content": "如果11 + 11 = 4， 12 + 12 = 6， 那么13 + 13是多少？",
        }
    ]
  )
print(response.choices[0].message.content)

import openai
response = openai.ChatCompletion.create(
    engine=deployment, # engine = "deployment_name".
    temperature = 0,
    messages=[
        {"role": "user", "content": "如果11 + 11 = 4， 12 + 12 = 6， 那么13 + 13是多少？一步步的思考",
        }
    ]
  )
print(response.choices[0].message.content)

import openai
response = openai.ChatCompletion.create(
    engine=deployment, # engine = "deployment_name".
    temperature = 0,
    messages=[
        {"role": "user", "content": "The cafeteria 23 apples. if they used 20 to make lunch and bought 6 more, how many apples do they have?",
        }
    ]
  )
print(response.choices[0].message.content)

import openai
response = openai.ChatCompletion.create(
    engine=deployment, # engine = "deployment_name".
    temperature = 0,
    messages=[
        {"role": "user", "content": "今天北京适合穿什么？一步步的思考",
        }
    ]
  )
print(response.choices[0].message.content)

import openai
tool = """
1 tool: python_interpreter, description: use it to execute python code
2 tool: web_access, description: use it to get realtime info, input is the question or query 
"""

react_prompt = f"""
Try your best to anwser user's question, and 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 use one of tools in the given tool list:

[{tool}]

Action Input: the input to the action

Here, you should pause the process and return to wait the outside observation. 

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 question
"""

def react_demo(request):
    response = openai.ChatCompletion.create(
        engine=deployment, # engine = "deployment_name".
        temperature = 0,
        messages=[
            {"role": "system", "content": react_prompt,
            },
            {"role": "user", "content": request}
        ]
      )
    print(response.choices[0].message.content)

print(react_demo("今天北京适合穿什么？"))

# run the web_access tool to get the Beijing's weather today. For example, 
weather = "The weather today in Beijing is 33°C, with 0% precipitation, 31% humidity, and a wind speed of 4 mph."

next_prompt = """
Question: 今天北京适合穿什么？

Thought: I need to check the current weather in Beijing to give a proper clothing suggestion.

Action: web_access

Action Input: 今天北京天气如何？

Observation: """ + weather

print(react_demo(next_prompt))