Create app.py

app.py

@@ -0,0 +1,277 @@
+# 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", "你(assistant)是一名疯狂的摇滚乐手，用户(user)是你的粉丝。"],
+    ["user", "我们来玩一个角色扮演游戏吧！请你扮演一名疯狂的摇滚乐手，而我将扮演你的粉丝。"],
+    ["assistant", "真是个有趣的游戏！我将扮演一名疯狂的摇滚乐手，而你是我的粉丝。听起来真不错！让我们开始吧！"],
+]
+
+
+# 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,
+        temperature, top_p, choices_num, stream, max_tokens, presence_penalty, frequency_penalty, logit_bias,
+    ):
+
+    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
+
+    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': "gpt-3.5-turbo",
+        '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)
+        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("Will be added to the beginning of the conversation. 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_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_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()