Add tutorial code

Author: lsjsj92

env_ex.txt

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+OPENAI_API_KEY=YOUR_KEY
+api_host=0.0.0.0
+api_port=8088

example/openai/.env

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+OPENAI_API_KEY=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
+api_host=0.0.0.0
+api_port=8088
+slack_bot=xoxb-3046854232455-3063781203860-VlGZPUoHPz87Z98qsvLqoK3E
+slack_ch=C04MQPVJGQK

example/openai/example.jsonl

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+{"prompt": "Feel: Smile \nMsg: 내 이름은 이수진이라고 해. \n ->", "completion": ":) ㅎㅎ 이수진!"}
+{"prompt": "Feel: Smile \nMsg: 내 이름은 홍길동이라고 해. \n ->", "completion": ":) ㅎㅎ 홍길동!"}
+{"prompt": "Feel: Smile \nMsg: 내 이름은 철수라고 해. \n ->", "completion": ":) ㅎㅎ 철수!"}
+{"prompt": "Feel: Smile \nMsg: 내 이름은 오옹이라고 해. \n ->", "completion": ":) ㅎㅎ 오옹!"}
+{"prompt": "Feel: Sad \nMsg: 내 이름은 이수진이라고 해. \n ->", "completion": ":( ㅠ_ㅜ 이수진"}
+{"prompt": "Feel: Sad \nMsg: 내 이름은 홍길동이라고 해. \n ->", "completion": ":( ㅠ_ㅜ 홍길동"}
+{"prompt": "Feel: Sad \nMsg: 내 이름은 철수라고 해. \n ->", "completion": ":( ㅠ_ㅜ 철수"}
+{"prompt": "Feel: Sad \nMsg: 내 이름은 오옹이라고 해. \n ->", "completion": ":( ㅠ_ㅜ 오옹"}

example/openai/example_prepared.jsonl

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+{"prompt":"Feel: Smile \nMsg: 내 이름은 이수진이라고 해. \n ->","completion":" :) ㅎㅎ 이수진!\n"}
+{"prompt":"Feel: Smile \nMsg: 내 이름은 홍길동이라고 해. \n ->","completion":" :) ㅎㅎ 홍길동!\n"}
+{"prompt":"Feel: Smile \nMsg: 내 이름은 철수라고 해. \n ->","completion":" :) ㅎㅎ 철수!\n"}
+{"prompt":"Feel: Smile \nMsg: 내 이름은 오옹이라고 해. \n ->","completion":" :) ㅎㅎ 오옹!\n"}
+{"prompt":"Feel: Sad \nMsg: 내 이름은 이수진이라고 해. \n ->","completion":" :( ㅠ_ㅜ 이수진\n"}
+{"prompt":"Feel: Sad \nMsg: 내 이름은 홍길동이라고 해. \n ->","completion":" :( ㅠ_ㅜ 홍길동\n"}
+{"prompt":"Feel: Sad \nMsg: 내 이름은 철수라고 해. \n ->","completion":" :( ㅠ_ㅜ 철수\n"}
+{"prompt":"Feel: Sad \nMsg: 내 이름은 오옹이라고 해. \n ->","completion":" :( ㅠ_ㅜ 오옹\n"}

example/openai/gpt3.py

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+import os
+import openai
+import argparse
+from dotenv import load_dotenv
+
+
+class OpenAIGpt:
+  def __init__(self):
+    load_dotenv()    
+
+  def run(self, args):
+    body = input("body : ")
+    question = input("Question : ")
+    text = f"{body} \n\nQ: {question}\nA:"
+    openai.api_key = os.getenv("OPENAI_API_KEY")
+    response = openai.Completion.create(
+      model="text-davinci-003",
+      prompt=f"{text}",
+      temperature=args.temperature,
+      max_tokens=100,
+      top_p=1,
+      frequency_penalty=0.0,
+      presence_penalty=0.0,
+      stop=["\n"]
+    )
+    print(response)
+    print(response.choices[0].text.strip())
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  # python gpt3.py --temperature 0.3
+  parser.add_argument('--temperature', default=0.3)
+
+  args = parser.parse_args()
+  openai_gpt = OpenAIGpt()
+  openai_gpt.run(args)
+

example/openai/gpt3_finetuning.py

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+import os
+import openai
+import argparse
+from dotenv import load_dotenv
+
+
+class OpenAIGpt:
+  def __init__(self):
+    load_dotenv()    
+
+  def run(self, args):
+    question = input("Question : ")
+    openai.api_key = os.getenv("OPENAI_API_KEY")
+    response = openai.Completion.create(
+      #model="text-davinci-003",
+      model="davinci:ft-wjtb-2023-01-29-10-42-22",
+      prompt=f"{question}",
+      temperature=args.temperature,
+      max_tokens=100,
+      top_p=1,
+      frequency_penalty=0.0,
+      presence_penalty=0.0,
+      stop=["\n"]
+      #stop=None
+    )
+    #print(response)
+    print(response.choices[0].text.strip())
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  # python gpt3.py --temperature 0.3
+  parser.add_argument('--temperature', default=0.3)
+
+  args = parser.parse_args()
+  openai_gpt = OpenAIGpt()
+  openai_gpt.run(args)
+

example/openai/gpt3_slack.py

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+
+import os
+import openai
+import argparse
+from dotenv import load_dotenv
+from slack_sdk import WebClient
+from slack_sdk.errors import SlackApiError
+
+
+class OpenAIGpt:
+  def run(self, msg):
+    openai.api_key = os.getenv("OPENAI_API_KEY")
+    response = openai.Completion.create(
+      model="text-davinci-003",
+      prompt=f"{msg}.",
+      temperature=0.3,
+      max_tokens=512,
+      top_p=1,
+      frequency_penalty=0.0,
+      presence_penalty=0.0,
+      stop=None
+    )
+    
+    return response.choices[0].text.strip()
+
+
+load_dotenv()
+
+client = WebClient(token=f"{os.getenv('slack_bot')}")
+channel_id = os.getenv('slack_ch')
+
+try:
+    result = client.conversations_history(channel=channel_id)
+
+    conversation_history = result["messages"]
+    openai_gpt = OpenAIGpt()
+    ans = openai_gpt.run(conversation_history[0]['text'])
+    print("conversation_history[0]['text'] : ", conversation_history[0]['text'])
+    print(ans)
+    client.chat_postMessage(channel='#alert_msg', text=f"{ans}")
+except SlackApiError as e:
+    print("Error creating conversation: {}".format(e))
+

example/openai/web.py

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+import streamlit as st
+import requests
+headers = {
+    "Content-type": "application/json",
+    "accept": "application/json"
+}
+model_url = "http://localhost:8088/gpt3/predict"
+save_url = "http://localhost:8088/save_qa"
+
+
+body = st.text_area('본문을 입력해주세요')
+
+Q = st.text_input("질문을 입력해주세요")
+
+btn_clicked = st.button("전송", key='confirm_btn')
+
+if btn_clicked:
+    
+    params = {
+        "model": "gpt3",
+        "temperature": 0,
+        "max_tokens": 512,
+        "top_p": 1,
+        "frequency_penalty": 0,
+        "presence_penalty": 0,
+        "body_text": f"{body}",
+        "q_text": f"{Q}"
+    }
+    
+    res = requests.post(model_url, json=params, headers=headers)
+    st.title("정답은 아래와 같습니다.")
+    st.text_input("", f"{res.json()['response']['choices'][0]['text']}", disabled=True, key="answer")
+    
+save_btn = st.button("저장")
+
+if (save_btn) and ('answer' in st.session_state):
+    params = {
+        "body_text": body,
+        "q_text": Q,
+        "a_text": st.session_state.answer
+    }
+    res = requests.post(save_url, json=params, headers=headers)
+    st.text_input("", f"{res.json()['response']}", disabled=True, key="final")
+    

example/openai/web_chat.py

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+import os
+
+import openai 
+import streamlit as st
+
+from streamlit_chat import message
+from dotenv import load_dotenv
+
+load_dotenv()    
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+def generate_response(prompt1, prompt2, p_type):
+    completions = openai.Completion.create(
+        engine = "text-davinci-003",
+        prompt = prompt2,
+        max_tokens = 1024,
+        n = 1,
+        stop = None,
+        temperature=0.5,
+    )
+    message = completions.choices[0].text
+    return message
+
+def get_text():
+    input_text1 = st.text_input("Write message : ", key='input_text1')
+    input_text2 = st.text_input("Write message222 : ", key='input_text2')
+    return input_text1, input_text2
+
+st.title("chatBot : Streamlit + openAI")
+
+# Storing the chat
+if 'generated' not in st.session_state:
+    st.session_state['generated'] = []
+
+if 'past' not in st.session_state:
+    st.session_state['past'] = []
+
+user_input1, user_input2 = get_text()
+p_type = st.radio(label = 'type_btn', options = ['단답형', 'O/X'], horizontal=True)
+
+if (user_input1) and (user_input2):
+    output = generate_response(user_input1, user_input2, p_type)
+    # store the output 
+    st.session_state.past.append(user_input2)
+    st.session_state.generated.append(output)
+
+if st.session_state['generated']:
+    for i in range(len(st.session_state['generated'])-1, -1, -1):
+        message(st.session_state["generated"][i], key=str(i))
+        message(st.session_state['past'][i], is_user=True, key=str(i) + '_user')

main.py

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+import uvicorn
+from fastapi import FastAPI
+
+from utils import gpt3, save_qa
+from utils import APIConfig
+
+
+class FastAPIRunner:
+    def __init__(self):        
+        pass
+
+    def run(self):
+        # API config data type 체크 
+        api_info_data = APIConfig().dict()
+        uvicorn.run(f"{api_info_data['api_name']}", 
+                    host=api_info_data['api_info']['host']
+                    ,port=api_info_data['api_info']['port']
+                    ,reload=True
+                    )
+
+app = FastAPI()
+app.include_router(gpt3)
+app.include_router(save_qa)
+
+@app.get('/')
+def read_results():
+    return {'msg' : 'Main'}
+    
+if __name__ == "__main__":
+    # python main.py
+    api = FastAPIRunner()
+    api.run()
+