chat-gpt-ui / app.py
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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.Dropdown(lines=1, label='role', choices=['user', 'system', 'assistant'], 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()