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| # import gradio as gr | |
| import gradio | |
| # import lmdb | |
| # import base64 | |
| # import io | |
| # import random | |
| # import time | |
| import json | |
| import copy | |
| # import sqlite3 | |
| from urllib.parse import urljoin | |
| import openai | |
| DEFAULT_PROMPT = [ | |
| ["system", "You(assistant) are a helpful AI assistant."], | |
| ] | |
| # def get_settings(old_state): | |
| # db_path = './my_app_state' | |
| # env = lmdb.open(db_path, max_dbs=2*1024*1024) | |
| # # print(env.stat()) | |
| # txn = env.begin() | |
| # saved_api_key = txn.get(key=b'api_key').decode('utf-8') or '' | |
| # txn.commit() | |
| # env.close() | |
| # new_state = copy.deepcopy(old_state) or {} | |
| # new_state['api_key'] = saved_api_key | |
| # return new_state, saved_api_key | |
| # def save_settings(old_state, api_key_text): | |
| # db_path = './my_app_state' | |
| # env = lmdb.open(db_path, max_dbs=2*1024*1024) | |
| # # print(env.stat()) | |
| # txn = env.begin(write=True) | |
| # txn.put(key=b'api_key', value=api_key_text.encode('utf-8')) | |
| # # 提交事务 | |
| # txn.commit() | |
| # return get_settings(old_state) | |
| def on_click_send_btn( | |
| old_state, api_key_text, chat_input_role, chat_input, prompt_table, chat_use_prompt, chat_use_history, chat_log, | |
| chat_model, temperature, top_p, choices_num, stream, max_tokens, presence_penalty, frequency_penalty, logit_bias, | |
| ): | |
| print('\n\n\n\n\n') | |
| print(prompt_table) | |
| prompt_table = prompt_table or [] | |
| chat_log = chat_log or [] | |
| chat_log_md = '' | |
| if chat_use_prompt: | |
| chat_log_md += '<center>(prompt)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)]) | |
| chat_log_md += '\n---\n' | |
| if True: | |
| chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)]) | |
| chat_log_md += '\n---\n' | |
| # if chat_input=='': | |
| # return old_state, chat_log, chat_log_md, None, None, chat_input | |
| print('\n') | |
| print(chat_input) | |
| print('') | |
| try: | |
| logit_bias_json = json.dumps(logit_bias) if logit_bias else None | |
| except: | |
| return old_state, chat_log, chat_log_md, None, None, chat_input | |
| new_state = copy.deepcopy(old_state) or {} | |
| req_hist = copy.deepcopy(prompt_table) if chat_use_prompt else [] | |
| if chat_use_history: | |
| for hh in (chat_log or []): | |
| req_hist.append(hh) | |
| if chat_input and chat_input!="": | |
| req_hist.append([(chat_input_role or 'user'), chat_input]) | |
| openai.api_key = api_key_text | |
| props = { | |
| 'model': chat_model, | |
| 'messages': [xx for xx in map(lambda it: {'role':it[0], 'content':it[1]}, req_hist)], | |
| 'temperature': temperature, | |
| 'top_p': top_p, | |
| 'n': choices_num, | |
| 'stream': stream, | |
| 'presence_penalty': presence_penalty, | |
| 'frequency_penalty': frequency_penalty, | |
| } | |
| if max_tokens>0: | |
| props['max_tokens'] = max_tokens | |
| if logit_bias_json is not None: | |
| props['logit_bias'] = logit_bias_json | |
| props_json = json.dumps(props) | |
| try: | |
| completion = openai.ChatCompletion.create(**props) | |
| print('') | |
| print(completion.choices) | |
| the_response_role = completion.choices[0].message.role | |
| the_response = completion.choices[0].message.content | |
| print(the_response) | |
| print('') | |
| chat_last_resp = json.dumps(completion.__dict__) | |
| chat_last_resp_dict = json.loads(chat_last_resp) | |
| chat_last_resp_dict['api_key'] = "hidden by UI" | |
| chat_last_resp_dict['organization'] = "hidden by UI" | |
| chat_last_resp = json.dumps(chat_last_resp_dict) | |
| chat_log_md = '' | |
| if chat_use_prompt: | |
| chat_log_md += '<center>(prompt)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)]) | |
| chat_log_md += '\n---\n' | |
| if True: | |
| chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)]) | |
| chat_log_md += '\n---\n' | |
| if chat_input and chat_input!="": | |
| chat_log.append([(chat_input_role or 'user'), chat_input]) | |
| chat_log_md += f"##### `{(chat_input_role or 'user')}`\n\n{chat_input}\n\n" | |
| chat_log.append([the_response_role, the_response]) | |
| chat_log_md += f"##### `{the_response_role}`\n\n{the_response}\n\n" | |
| return new_state, chat_log, chat_log_md, chat_last_resp, props_json, '' | |
| except Exception as error: | |
| print(error) | |
| chat_log_md = '' | |
| if chat_use_prompt: | |
| chat_log_md += '<center>(prompt)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)]) | |
| chat_log_md += '\n---\n' | |
| if True: | |
| chat_log_md += '<center>(history)</center>\n\n' if chat_use_history else '<center>(not used history)</center>\n\n' | |
| chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", chat_log)]) | |
| chat_log_md += '\n---\n' | |
| # chat_log_md = '' | |
| # chat_log_md = "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", prompt_table)]) if chat_use_prompt else '' | |
| # chat_log_md += "\n".join([xx for xx in map(lambda it: f"##### `{it[0]}`\n\n{it[1]}\n\n", hist)]) | |
| chat_log_md += "\n" | |
| chat_log_md += str(error) | |
| return new_state, chat_log, chat_log_md, None, props_json, chat_input | |
| def clear_history(): | |
| return [], "" | |
| css = """ | |
| .table-wrap .cell-wrap input {min-width:80%} | |
| #api-key-textbox textarea {filter:blur(8px); transition: filter 0.25s} | |
| #api-key-textbox textarea:focus {filter:none} | |
| """ | |
| with gradio.Blocks(title="ChatGPT", css=css) as demo: | |
| global_state = gradio.State(value={}) | |
| # https://gradio.app/docs | |
| # https://platform.openai.com/docs/api-reference/chat/create | |
| with gradio.Tab("ChatGPT"): | |
| with gradio.Row(): | |
| with gradio.Column(scale=10): | |
| gradio.Markdown("Go to https://platform.openai.com/account/api-keys to get your API key.") | |
| api_key_text = gradio.Textbox(label="Your API key", elem_id="api-key-textbox") | |
| with gradio.Row(): | |
| with gradio.Column(scale=2): | |
| api_key_refresh_btn = gradio.Button("🔄 Load from browser storage") | |
| api_key_refresh_btn.click( | |
| # get_settings, | |
| None, | |
| inputs=[global_state], | |
| outputs=[global_state, api_key_text], | |
| api_name="load-settings", | |
| _js="""(global_state, api_key_text)=>{ | |
| global_state=(global_state??{}); | |
| global_state['api_key_text']=localStorage?.getItem?.('[gradio][chat-gpt-ui][api_key_text]'); | |
| return [global_state, global_state['api_key_text']]; | |
| }""", | |
| ) | |
| with gradio.Column(scale=2): | |
| api_key_save_btn = gradio.Button("💾 Save to browser storage") | |
| api_key_save_btn.click( | |
| # save_settings, | |
| None, | |
| inputs=[global_state, api_key_text], | |
| outputs=[global_state, api_key_text], | |
| api_name="save-settings", | |
| _js="""(global_state, api_key_text)=>{ | |
| localStorage.setItem('[gradio][chat-gpt-ui][api_key_text]', api_key_text); | |
| global_state=(global_state??{}); | |
| global_state['api_key_text']=localStorage?.getItem?.('[gradio][chat-gpt-ui][api_key_text]'); | |
| return [global_state, global_state['api_key_text']]; | |
| }""", | |
| ) | |
| with gradio.Row(): | |
| with gradio.Column(scale=10): | |
| with gradio.Box(): | |
| prompt_table = gradio.Dataframe( | |
| type='array', | |
| label='Prompt', col_count=(2, 'fixed'), max_cols=2, | |
| value=DEFAULT_PROMPT, headers=['role', 'content'], interactive=True, | |
| ) | |
| gradio.Markdown("The Table above is editable. The content will be added to the beginning of the conversation (if you check 'send with prompt' as `√`). See https://platform.openai.com/docs/guides/chat/introduction .") | |
| with gradio.Row(): | |
| with gradio.Column(scale=4): | |
| with gradio.Box(): | |
| gradio.Markdown("See https://platform.openai.com/docs/api-reference/chat/create .") | |
| chat_model = gradio.Dropdown(label="model", choices=[ | |
| "gpt-3.5-turbo", "gpt-3.5-turbo-0301", | |
| "gpt-4", "gpt-4-0314", "gpt-4-32k", "gpt-4-32k-0314", | |
| ], value="gpt-3.5-turbo") | |
| chat_temperature = gradio.Slider(label="temperature", value=1, minimum=0, maximum=2) | |
| chat_top_p = gradio.Slider(label="top_p", value=1, minimum=0, maximum=1) | |
| chat_choices_num = gradio.Slider(label="choices num(n)", value=1, minimum=1, maximum=20) | |
| chat_stream = gradio.Checkbox(label="stream", value=False, visible=False) | |
| chat_max_tokens = gradio.Slider(label="max_tokens", value=-1, minimum=-1, maximum=4096) | |
| chat_presence_penalty = gradio.Slider(label="presence_penalty", value=0, minimum=-2, maximum=2) | |
| chat_frequency_penalty = gradio.Slider(label="frequency_penalty", value=0, minimum=-2, maximum=2) | |
| chat_logit_bias = gradio.Textbox(label="logit_bias", visible=False) | |
| pass | |
| with gradio.Column(scale=8): | |
| with gradio.Row(): | |
| with gradio.Column(scale=10): | |
| chat_log = gradio.State() | |
| with gradio.Box(): | |
| chat_log_box = gradio.Markdown(label='chat history') | |
| chat_input_role = gradio.Textbox(lines=1, label='role', value='user') | |
| chat_input = gradio.Textbox(lines=4, label='input') | |
| with gradio.Row(): | |
| chat_clear_history_btn = gradio.Button("clear history") | |
| chat_clear_history_btn.click(clear_history, inputs=[], outputs=[chat_log, chat_log_box]) | |
| chat_use_prompt = gradio.Checkbox(label='send with prompt', value=True) | |
| chat_use_history = gradio.Checkbox(label='send with history', value=True) | |
| chat_send_btn = gradio.Button("send") | |
| pass | |
| with gradio.Row(): | |
| chat_last_req = gradio.JSON(label='last request') | |
| chat_last_resp = gradio.JSON(label='last response') | |
| chat_send_btn.click( | |
| on_click_send_btn, | |
| inputs=[ | |
| global_state, api_key_text, chat_input_role, chat_input, prompt_table, chat_use_prompt, chat_use_history, chat_log, | |
| chat_model, chat_temperature, chat_top_p, chat_choices_num, chat_stream, chat_max_tokens, chat_presence_penalty, chat_frequency_penalty, chat_logit_bias, | |
| ], | |
| outputs=[global_state, chat_log, chat_log_box, chat_last_resp, chat_last_req, chat_input], | |
| api_name="click-send-btn", | |
| ) | |
| pass | |
| with gradio.Tab("Settings"): | |
| gradio.Markdown('Currently nothing.') | |
| pass | |
| if __name__ == "__main__": | |
| demo.queue(concurrency_count=20).launch() | |