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import gradio as gr |
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import time |
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import os |
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import datetime |
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from openai import OpenAI |
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from openai.types.beta.threads.runs import ( |
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ToolCallsStepDetails, |
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) |
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SYS_PROMPT_DEFAULT = "あなたは優秀なアシスタントです。質問をされた場合は、質問に答えるコードを作成して実行します。回答は日本語でお願いします。" |
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DUMMY = "********************" |
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file_format = {".txt", ".csv", ".pdf"} |
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IMG_FOLDER = "sample_data" |
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ANT_FOLDER = "sample_data" |
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IMG_MSG = "(画像ファイルを追加しました。送信ボタンの下に表示されています。)" |
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ANT_MSG = "(下部の[出力ファイル]にファイルを追加しました。)" |
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MAX_TRIAL = 30 |
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INTER_SEC = 3 |
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examples = ["sample_data/東京都年別人口.csv", "sample_data/練馬区年齢別人口.csv"] |
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example_toid = {"東京都年別人口.csv" : "file-GOEk4X4WpU5gBJAuHCMtiJrn" |
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, "練馬区年齢別人口.csv" : "file-YAFPMMqG3Zl5DRx5hTLjCfFa"} |
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code_mode = {'ON': True, 'OFF': False} |
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def set_state(openai_key, sys_prompt, code_output, state): |
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""" 設定タブの情報をセッションに保存する関数 """ |
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state["openai_key"] = openai_key |
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state["system_prompt"] = sys_prompt |
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state["code_mode"] = code_mode[code_output] |
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return state |
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def init(state, text, file): |
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""" 入力チェックを行う関数 |
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※ここで例外を起こすと入力できなくなるので次の関数でエラーにする """ |
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err_msg = "" |
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file_id = None |
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if not text: |
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err_msg = "テキストを入力して下さい。" |
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return state, text, file, file_id, err_msg |
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elif file: |
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root, ext = os.path.splitext(file) |
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if ext not in file_format: |
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err_msg = "指定した形式のファイルをアップしてください。(注意事項タブに記載)" |
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return state, text, gr.Image(value=None,type="filepath", interactive=False), file_id, err_msg |
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if state["client"] is None: |
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os.environ["OPENAI_API_KEY"] = os.environ["TEST_OPENAI_KEY"] |
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client = OpenAI() |
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os.environ["OPENAI_API_KEY"] = "" |
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thread = client.beta.threads.create() |
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state["client"] = client |
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state["assistant_id"] = os.environ["ASSIST_ID"] |
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state["thread_id"] = thread.id |
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if file: |
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basename = os.path.basename(file) |
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if example_toid.get(basename): |
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file_id = example_toid.get(basename) |
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else: |
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file_id = "" |
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return state, text, file, file_id, err_msg |
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def raise_exception(err_msg): |
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""" エラーの場合例外を起こす関数 """ |
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if err_msg != "": |
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raise Exception("これは入力チェックでの例外です。") |
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return |
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def add_history(history, text, file_id): |
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""" Chat履歴"history"に追加を行う関数 """ |
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err_msg = "" |
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new_row_flg = False |
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new_row_flg = True |
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if file_id is None or file_id == "": |
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if new_row_flg: |
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history = history + [(text, None)] |
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else: |
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history[-1][0] = text |
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elif file_id is not None: |
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if new_row_flg: |
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history = history + [("file:" + file_id, DUMMY)] |
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history = history + [(text, None)] |
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else: |
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history[-1][0] = "file:" + file_id |
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history = history + [(text, None)] |
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print(history) |
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new_text = gr.Textbox(value="", interactive=True) |
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return history, new_text, err_msg |
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def bot(state, history, file_id): |
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err_msg = "" |
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image_file = None |
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ant_file = None |
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system_prompt = state["system_prompt"] |
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client = state["client"] |
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assistant_id = state["assistant_id"] |
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thread_id = state["thread_id"] |
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msg_id = state["last_msg_id"] |
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code_mode = state["code_mode"] |
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print("system_prompt") |
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if file_id is None or file_id == "": |
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message = client.beta.threads.messages.create( |
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thread_id=thread_id, |
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role="user", |
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content=history[-1][0], |
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) |
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else: |
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message = client.beta.threads.messages.create( |
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thread_id=thread_id, |
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role="user", |
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content=history[-1][0], |
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file_ids=[file_id] |
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) |
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print(message) |
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run = client.beta.threads.runs.create( |
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thread_id=thread_id, |
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assistant_id=assistant_id, |
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instructions=system_prompt |
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) |
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for i in range(0, MAX_TRIAL, 1): |
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if i > 0: |
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time.sleep(INTER_SEC) |
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run = client.beta.threads.runs.retrieve( |
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thread_id=thread_id, |
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run_id=run.id |
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) |
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messages = client.beta.threads.messages.list( |
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thread_id=thread_id, |
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after=msg_id, |
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order="asc" |
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) |
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msg_log = client.beta.threads.messages.list( |
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thread_id=thread_id, |
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order="asc" |
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) |
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print(msg_log) |
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for msg in messages: |
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msg_id = msg.id |
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if msg.role == "assistant": |
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for content in msg.content: |
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res_text = "" |
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file_id = "" |
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ant_file = None |
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cont_dict = content.model_dump() |
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ct_image_file = cont_dict.get("image_file") |
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if ct_image_file: |
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res_file_id = ct_image_file.get("file_id") |
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image_file = file_download(client, res_file_id, IMG_FOLDER , ".png") |
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if image_file is None: |
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err_msg = "ファイルのダウンロードに失敗しました。" |
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else: |
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print("画像ファイル追加") |
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res_text = IMG_MSG |
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history = history + [[None, res_text]] |
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else: |
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res_text = cont_dict["text"].get("value") |
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if len(cont_dict.get("text").get("annotations")) > 0: |
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ct_ant = cont_dict.get("text").get("annotations") |
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if ct_ant[0].get("file_path") is not None: |
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ant_file_id = ct_ant[0].get("file_path").get("file_id") |
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if ct_ant[0].get("text") is not None: |
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ext = "." + ct_ant[0].get("text")[ct_ant[0].get("text").rfind('.') + 1:] |
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ant_file = file_download(client, ant_file_id, ANT_FOLDER, ext) |
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if ant_file is None: |
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err_msg = "参照ファイルのダウンロードに失敗しました。" |
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else: |
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res_text = res_text + "\n\n" + ANT_MSG |
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print(res_text) |
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if res_text != "": |
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if history[-1][1] is not None: |
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history = history + [[None, res_text]] |
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else: |
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history[-1][1] = res_text |
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yield gr.Chatbot(label=run.status ,value=history), image_file, ant_file, err_msg |
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print(run.status) |
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state["last_msg_id"] = msg_id |
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if run.status == "completed": |
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if not code_mode: |
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break |
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else: |
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run_steps = client.beta.threads.runs.steps.list( |
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thread_id=thread_id, run_id=run.id |
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) |
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input_code = get_code(run_steps) |
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if len(input_code) > 0: |
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for code in input_code: |
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code = "[input_code]\n\n" + code |
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history = history + [[None, code]] |
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yield gr.Chatbot(label=run.status ,value=history), image_file, ant_file, err_msg |
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break |
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if run.status == "failed": |
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err_msg = "※メッセージ取得に失敗しました。" |
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return history, image_file, ant_file, err_msg |
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if i == MAX_TRIAL: |
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err_msg = "※メッセージ取得の際にタイムアウトしました。" |
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return history, image_file, ant_file, err_msg |
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def get_code(run_steps): |
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input_code = [] |
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for data in run_steps.data: |
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if isinstance(data.step_details, ToolCallsStepDetails): |
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for tool_call in data.step_details.tool_calls: |
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input_code.append(tool_call.code_interpreter.input) |
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return input_code |
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def file_download(client, file_id, folder, ext): |
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""" OpenAIからファイルをダウンロードしてパスを返す """ |
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api_response = client.files.with_raw_response.retrieve_content(file_id) |
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if api_response.status_code == 200: |
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content = api_response.content |
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file_path = folder + "/" + file_id + ext |
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with open(file_path, 'wb') as f: |
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f.write(content) |
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return file_path |
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else: |
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return None |
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def finally_proc(): |
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""" 最終処理用関数 """ |
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new_up_file = gr.File(value=None, interactive = True) |
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new_file_id = gr.Textbox(value="") |
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return new_up_file, new_file_id |
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with gr.Blocks() as demo: |
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gr.Markdown("<h2>GPT Code Interpreter対応チャット</h2>") |
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state = gr.State({ |
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"system_prompt": SYS_PROMPT_DEFAULT, |
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"openai_key" : None, |
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"code_mode" : True, |
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"client" : None, |
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"assistant_id" : None, |
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"thread_id" : None, |
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"last_msg_id" : "" |
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}) |
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with gr.Tab("Chat画面") as chat: |
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chatbot = gr.Chatbot(label="チャット画面") |
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text_msg = gr.Textbox(label="テキスト") |
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with gr.Row(): |
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up_file = gr.File(label="ファイルアップロード", type="filepath",interactive = True) |
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result_image = gr.Image(label="出力画像", type="filepath", interactive = False) |
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gr.Examples(label="サンプルデータ", examples=examples, inputs=[up_file]) |
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with gr.Row(): |
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btn = gr.Button(value="送信") |
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btn_clear = gr.ClearButton(value="リセット", components=[chatbot, text_msg, up_file, state]) |
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sys_msg = gr.Textbox(label="システムメッセージ", interactive = False) |
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result_file = gr.File(label="出力ファイル", type="filepath",interactive = False) |
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file_id = gr.Textbox(visible=False) |
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bc = btn.click(init, [state, text_msg, up_file], [state, text_msg, up_file, file_id, sys_msg], queue=False).success( |
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raise_exception, sys_msg, None).success( |
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add_history, [chatbot, text_msg, file_id], [chatbot, text_msg, sys_msg], queue=False).success( |
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bot, [state, chatbot, file_id],[chatbot, result_image, result_file, sys_msg]).then( |
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finally_proc, None, [up_file, file_id], queue=False |
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) |
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with gr.Tab("設定") as set: |
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openai_key = gr.Textbox(label="OpenAI API Key") |
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system_prompt = gr.Textbox(value = SYS_PROMPT_DEFAULT,lines = 5, label="Custom instructions", interactive = True) |
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code_output = gr.Dropdown(label="コード出力", choices=["OFF", "ON"], value = "OFF", interactive = True) |
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chat.select(set_state, [openai_key, system_prompt, code_output, state], state) |
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demo.queue() |
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demo.launch(debug=True) |