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import json |
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import os |
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import sys |
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import time |
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import re |
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from pathlib import Path |
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from typing import List, Literal, Optional, Tuple, TypedDict, Dict |
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prj_root_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) |
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sys.path.append(prj_root_path) |
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from code_interpreter.JuypyterClient import JupyterNotebook |
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from code_interpreter.BaseCodeInterpreter import BaseCodeInterpreter |
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from utils.const import * |
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from prompt.gpt4_prompt import CODE_INTERPRETER_SYSTEM_PROMPT |
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from colorama import init, Fore, Style |
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from rich.markdown import Markdown |
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import base64 |
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import openai |
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from retrying import retry |
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import logging |
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from termcolor import colored |
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with open("./openai_api_key.txt") as f: |
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OPENAI_API_KEY = key = f.read() |
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openai.api_key = OPENAI_API_KEY |
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from utils.cleaner import clean_error_msg |
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def remove_string(s): |
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pattern = r"\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d{6}:.*LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64\n" |
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return re.sub(pattern, "", s) |
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def clean_the_dialog(dialog, question): |
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question_idx = 0 |
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for idx, item in enumerate(dialog): |
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if item["content"] == question: |
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question_idx = idx |
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filtered_dialog = dialog[question_idx:] |
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user_qinit_dict = filtered_dialog[0] |
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answer_fuse_str = "\n".join([i["content"].strip() for i in filtered_dialog[1::2]]) |
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final_dialog_dict = [ |
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{"role": "user", "content": user_qinit_dict["content"]}, |
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{"role": "assistant", "content": answer_fuse_str}, |
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] |
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return final_dialog_dict |
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class GPTCodeInterpreter(BaseCodeInterpreter): |
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def __init__(self, model="gpt-4"): |
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self.model = model |
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self.dialog = [ |
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{ |
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"role": "system", |
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"content": CODE_INTERPRETER_SYSTEM_PROMPT, |
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}, |
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] |
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self.response = None |
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assert os.path.isfile( |
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"./openai_api_key.txt" |
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), "The openai_api_key.txt file could not be found. Please make sure it is in the same directory as this script, and that it contains your OpenAI API key." |
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with open("./openai_api_key.txt") as f: |
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OPENAI_API_KEY = f.read() |
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openai.api_key = OPENAI_API_KEY |
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self.nb = JupyterNotebook() |
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out = self.nb.add_and_run(TOOLS_CODE) |
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def get_response_content(self): |
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if self.response: |
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return self.response["choices"][0]["message"]["content"] |
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else: |
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return None |
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@retry( |
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stop_max_attempt_number=7, |
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wait_exponential_multiplier=1000, |
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wait_exponential_max=10000, |
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) |
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def ChatCompletion(self): |
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try: |
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self.response = openai.ChatCompletion.create( |
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model=self.model, messages=self.dialog, temperature=0.2, top_p=0.9 |
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) |
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except Exception as e: |
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print(f"error while OPENAI api call {e}") |
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def close(self): |
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""" |
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close jupyter notebook, and this class instance |
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""" |
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self.nb.close() |
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def save_dialog(self, path: str = "./output/dialog.json"): |
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with open(path, "w") as f: |
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json.dump(self.dialog, f) |
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print(f" ++Dialog saved to [{path}]") |
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def chat( |
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self, |
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user_message: str, |
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VERBOSE: bool = False, |
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MAX_TRY: int = 6, |
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code_exec_prefix: str = "", |
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feedback_prompt: str = "", |
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append_result: bool = True, |
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): |
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self.dialog.append({"role": "user", "content": user_message}) |
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code_block_output = "" |
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attempt = 0 |
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img_data = None |
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if VERBOSE: |
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print( |
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"###User : " + Fore.BLUE + Style.BRIGHT + user_message + Style.RESET_ALL |
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) |
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print("\n###Assistant : ") |
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for i in range(MAX_TRY): |
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self.ChatCompletion() |
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generated_text = self.get_response_content() |
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generated_code_blocks = self.extract_code_blocks(generated_text) |
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if len(generated_code_blocks) > 0: |
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first_code_block_pos = ( |
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generated_text.find(generated_code_blocks[0]) |
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if generated_code_blocks |
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else -1 |
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) |
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text_before_first_code_block = ( |
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generated_text |
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if first_code_block_pos == -1 |
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else generated_text[:first_code_block_pos] |
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) |
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if VERBOSE: |
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print(Fore.GREEN + text_before_first_code_block + Style.RESET_ALL) |
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if VERBOSE: |
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print( |
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Fore.YELLOW |
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+ generated_code_blocks[0] |
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+ "\n```\n" |
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+ Style.RESET_ALL |
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) |
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code_block_output, error_flag = self.execute_code_and_return_output( |
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generated_code_blocks[0] |
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) |
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code_block_output = f"{code_block_output}" |
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if code_block_output is not None: |
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code_block_output = code_block_output.strip() |
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code_block_output = remove_string(code_block_output) |
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if len(code_block_output) > 500: |
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code_block_output = ( |
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code_block_output[:200] + "⋯(skip)⋯" + code_block_output[-200:] |
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) |
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code_block_output_str = f"\n```RESULT\n{code_block_output}\n```\n" |
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if append_result: |
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gen_final = f"{text_before_first_code_block}{generated_code_blocks[0]}\n```{code_block_output_str}" |
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if VERBOSE: |
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print( |
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Fore.LIGHTBLACK_EX + code_block_output_str + Style.RESET_ALL |
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) |
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else: |
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gen_final = ( |
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f"{text_before_first_code_block}{generated_code_blocks[0]}\n```" |
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) |
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self.dialog.append( |
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{ |
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"role": "assistant", |
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"content": gen_final, |
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} |
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) |
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if len(feedback_prompt) < 5: |
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feedback_dict = { |
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"role": "user", |
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"content": "Keep going. if you think debugging tell me where you got wrong and better code.\nNeed conclusion to question only text (Do not leave result part alone).\nif doesn't need to generated anything then just say <done>", |
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} |
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else: |
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feedback_dict = { |
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"role": "user", |
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"content": f"{feedback_prompt}", |
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} |
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self.dialog.append(feedback_dict) |
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else: |
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if "<done>" in generated_text: |
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generated_text = generated_text.split("<done>")[0].strip() |
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if len(generated_text) <= 0: |
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break |
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if VERBOSE: |
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print(Fore.GREEN + generated_text + Style.RESET_ALL) |
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self.dialog.append( |
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{ |
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"role": "assistant", |
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"content": f"{generated_text}", |
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} |
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) |
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break |
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self.dialog = [self.dialog[0]] + clean_the_dialog( |
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self.dialog, question=user_message |
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) |
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return self.dialog[-1] |
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