Revert "try forking"

This reverts commit ea050d25027e369a21bcacab2841d061659086d8.

app.py

@@ -1,367 +1,11 @@
-# pylint: disable=broad-exception-caught, redefined-outer-name, missing-function-docstring, missing-module-docstring, too-many-arguments, line-too-long, invalid-name, redefined-builtin, redefined-argument-from-local
-# import gradio as gr
+import streamlit as st
 
-# model_name = "models/THUDM/chatglm2-6b-int4"
-# gr.load(model_name).lauch()
+# Title and input
+st.title("Reverse Text")
+input_text = st.text_input("Enter some text")
 
-# %%writefile demo-4bit.py
+# Reverse the input text
+reversed_text = input_text[::-1]
 
-from textwrap import dedent
-
-import gradio as gr
-import mdtex2html
-import torch
-from loguru import logger
-
-# credit to https://github.com/THUDM/ChatGLM2-6B/blob/main/web_demo.py
-# while mistakes are mine
-from transformers import AutoModel, AutoTokenizer
-
-# model_name = "THUDM/chatglm2-6b"
-# model_name = "THUDM/chatglm2-6b-int4"
-model_name = "gorkemgoknar/gpt2chatbotenglish"
-
-RETRY_FLAG = False
-
-tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
-
-# model = AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda()
-
-# 4/8 bit
-# model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).quantize(4).cuda()
-
-has_cuda = torch.cuda.is_available()
-# has_cuda = False  # force cpu
-
-if has_cuda:
-    model = AutoModel.from_pretrained(
-        model_name, trust_remote_code=True
-    ).cuda()  # 3.92G
-else:
-    model = AutoModel.from_pretrained(
-        model_name, trust_remote_code=True
-    ).half()  # .float() .half().float()
-
-model = model.eval()
-
-_ = """Override Chatbot.postprocess"""
-
-
-def postprocess(self, y):
-    if y is None:
-        return []
-    for i, (message, response) in enumerate(y):
-        y[i] = (
-            None if message is None else mdtex2html.convert((message)),
-            None if response is None else mdtex2html.convert(response),
-        )
-    return y
-
-
-gr.Chatbot.postprocess = postprocess
-
-
-def parse_text(text):
-    """copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
-    lines = text.split("\n")
-    lines = [line for line in lines if line != ""]
-    count = 0
-    for i, line in enumerate(lines):
-        if "```" in line:
-            count += 1
-            items = line.split("`")
-            if count % 2 == 1:
-                lines[i] = f'<pre><code class="language-{items[-1]}">'
-            else:
-                lines[i] = "<br></code></pre>"
-        else:
-            if i > 0:
-                if count % 2 == 1:
-                    line = line.replace("`", r"\`")
-                    line = line.replace("<", "&lt;")
-                    line = line.replace(">", "&gt;")
-                    line = line.replace(" ", "&nbsp;")
-                    line = line.replace("*", "&ast;")
-                    line = line.replace("_", "&lowbar;")
-                    line = line.replace("-", "&#45;")
-                    line = line.replace(".", "&#46;")
-                    line = line.replace("!", "&#33;")
-                    line = line.replace("(", "&#40;")
-                    line = line.replace(")", "&#41;")
-                    line = line.replace("$", "&#36;")
-                lines[i] = "<br>" + line
-    text = "".join(lines)
-    return text
-
-
-def predict(
-    RETRY_FLAG, input, chatbot, max_length, top_p, temperature, history, past_key_values
-):
-    try:
-        chatbot.append((parse_text(input), ""))
-    except Exception as exc:
-        logger.error(exc)
-        logger.debug(f"{chatbot=}")
-        _ = """
-        if chatbot:
-            chatbot[-1] = (parse_text(input), str(exc))
-            yield chatbot, history, past_key_values
-        # """
-        yield chatbot, history, past_key_values
-
-    for response, history, past_key_values in model.stream_chat(
-        tokenizer,
-        input,
-        history,
-        past_key_values=past_key_values,
-        return_past_key_values=True,
-        max_length=max_length,
-        top_p=top_p,
-        temperature=temperature,
-    ):
-        chatbot[-1] = (parse_text(input), parse_text(response))
-
-        yield chatbot, history, past_key_values
-
-
-def trans_api(input, max_length=4096, top_p=0.8, temperature=0.2):
-    if max_length < 10:
-        max_length = 4096
-    if top_p < 0.1 or top_p > 1:
-        top_p = 0.85
-    if temperature <= 0 or temperature > 1:
-        temperature = 0.01
-    try:
-        res, _ = model.chat(
-            tokenizer,
-            input,
-            history=[],
-            past_key_values=None,
-            max_length=max_length,
-            top_p=top_p,
-            temperature=temperature,
-        )
-        # logger.debug(f"{res=} \n{_=}")
-    except Exception as exc:
-        logger.error(f"{exc=}")
-        res = str(exc)
-
-    return res
-
-
-def reset_user_input():
-    return gr.update(value="")
-
-
-def reset_state():
-    return [], [], None
-
-
-# Delete last turn
-def delete_last_turn(chat, history):
-    if chat and history:
-        chat.pop(-1)
-        history.pop(-1)
-    return chat, history
-
-
-# Regenerate response
-def retry_last_answer(
-    user_input, chatbot, max_length, top_p, temperature, history, past_key_values
-):
-    if chatbot and history:
-        # Removing the previous conversation from chat
-        chatbot.pop(-1)
-        # Setting up a flag to capture a retry
-        RETRY_FLAG = True
-        # Getting last message from user
-        user_input = history[-1][0]
-        # Removing bot response from the history
-        history.pop(-1)
-
-    yield from predict(
-        RETRY_FLAG,
-        user_input,
-        chatbot,
-        max_length,
-        top_p,
-        temperature,
-        history,
-        past_key_values,
-    )
-
-
-with gr.Blocks(title="ChatGLM2-6B-int4", theme=gr.themes.Soft(text_size="sm")) as demo:
-    # gr.HTML("""<h1 align="center">ChatGLM2-6B-int4</h1>""")
-    gr.HTML(
-        """<center><a href="https://huggingface.co/spaces/mikeee/chatglm2-6b-4bit?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>To avoid the queue and for faster inference Duplicate this Space and upgrade to GPU</center>"""
-    )
-
-    with gr.Accordion("Info", open=False):
-        _ = """
-            ## ChatGLM2-6B-int4
-
-            With a GPU, a query takes from a few seconds to a few tens of seconds, dependent on the number of words/characters
-            the question and responses contain. The quality of the responses varies quite a bit it seems. Even the same
-            question with the same parameters, asked at different times, can result in quite different responses.
-
-            * Low temperature: responses will be more deterministic and focused; High temperature: responses more creative.
-
-            * Suggested temperatures -- translation: up to 0.3; chatting: > 0.4
-
-            * Top P controls dynamic vocabulary selection based on context.
-
-            For a table of example values for different scenarios, refer to [this](https://community.openai.com/t/cheat-sheet-mastering-temperature-and-top-p-in-chatgpt-api-a-few-tips-and-tricks-on-controlling-the-creativity-deterministic-output-of-prompt-responses/172683)
-
-            If the instance is not on a GPU (T4), it will be very slow. You can try to run the colab notebook [chatglm2-6b-4bit colab notebook](https://colab.research.google.com/drive/1WkF7kOjVCcBBatDHjaGkuJHnPdMWNtbW?usp=sharing) for a spin.
-
-            The T4 GPU is sponsored by a community GPU grant from Huggingface. Thanks a lot!
-            """
-        gr.Markdown(dedent(_))
-    chatbot = gr.Chatbot()
-    with gr.Row():
-        with gr.Column(scale=4):
-            with gr.Column(scale=12):
-                user_input = gr.Textbox(
-                    show_label=False,
-                    placeholder="Input...",
-                ).style(container=False)
-                RETRY_FLAG = gr.Checkbox(value=False, visible=False)
-            with gr.Column(min_width=32, scale=1):
-                with gr.Row():
-                    submitBtn = gr.Button("Submit", variant="primary")
-                    deleteBtn = gr.Button("Delete last turn", variant="secondary")
-                    retryBtn = gr.Button("Regenerate", variant="secondary")
-        with gr.Column(scale=1):
-            emptyBtn = gr.Button("Clear History")
-            max_length = gr.Slider(
-                0,
-                32768,
-                value=8192,
-                step=1.0,
-                label="Maximum length",
-                interactive=True,
-            )
-            top_p = gr.Slider(
-                0, 1, value=0.85, step=0.01, label="Top P", interactive=True
-            )
-            temperature = gr.Slider(
-                0.01, 1, value=0.95, step=0.01, label="Temperature", interactive=True
-            )
-
-    history = gr.State([])
-    past_key_values = gr.State(None)
-
-    user_input.submit(
-        predict,
-        [
-            RETRY_FLAG,
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        [chatbot, history, past_key_values],
-        show_progress="full",
-    )
-    submitBtn.click(
-        predict,
-        [
-            RETRY_FLAG,
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        [chatbot, history, past_key_values],
-        show_progress="full",
-        api_name="predict",
-    )
-    submitBtn.click(reset_user_input, [], [user_input])
-
-    emptyBtn.click(
-        reset_state, outputs=[chatbot, history, past_key_values], show_progress="full"
-    )
-
-    retryBtn.click(
-        retry_last_answer,
-        inputs=[
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        # outputs = [chatbot, history, last_user_message, user_message]
-        outputs=[chatbot, history, past_key_values],
-    )
-    deleteBtn.click(delete_last_turn, [chatbot, history], [chatbot, history])
-
-    with gr.Accordion("Example inputs", open=True):
-        etext = """In America, where cars are an important part of the national psyche, a decade ago people had suddenly started to drive less, which had not happened since the oil shocks of the 1970s. """
-        examples = gr.Examples(
-            examples=[
-                ["Explain the plot of Cinderella in a sentence."],
-                [
-                    "How long does it take to become proficient in French, and what are the best methods for retaining information?"
-                ],
-                ["What are some common mistakes to avoid when writing code?"],
-                ["Build a prompt to generate a beautiful portrait of a horse"],
-                ["Suggest four metaphors to describe the benefits of AI"],
-                ["Write a pop song about leaving home for the sandy beaches."],
-                ["Write a summary demonstrating my ability to tame lions"],
-                ["鲁迅和周树人什么关系"],
-                ["从前有一头牛，这头牛后面有什么？"],
-                ["正无穷大加一大于正无穷大吗？"],
-                ["正无穷大加正无穷大大于正无穷大吗？"],
-                ["-2的平方根等于什么"],
-                ["树上有5只鸟，猎人开枪打死了一只。树上还有几只鸟？"],
-                ["树上有11只鸟，猎人开枪打死了一只。树上还有几只鸟？提示：需考虑鸟可能受惊吓飞走。"],
-                ["鲁迅和周树人什么关系 用英文回答"],
-                ["以红楼梦的行文风格写一张委婉的请假条。不少于320字。"],
-                [f"{etext} 翻成中文，列出3个版本"],
-                [f"{etext} \n 翻成中文，保留原意，但使用文学性的语言。不要写解释。列出3个版本"],
-                ["js 判断一个数是不是质数"],
-                ["js 实现python 的 range(10)"],
-                ["js 实现python 的 [*(range(10)]"],
-                ["假定 1 + 2 = 4, 试求 7 + 8"],
-                ["Erkläre die Handlung von Cinderella in einem Satz."],
-                ["Erkläre die Handlung von Cinderella in einem Satz. Auf Deutsch"],
-            ],
-            inputs=[user_input],
-            examples_per_page=30,
-        )
-
-    with gr.Accordion("For Chat/Translation API", open=False, visible=False):
-        input_text = gr.Text()
-        tr_btn = gr.Button("Go", variant="primary")
-        out_text = gr.Text()
-    tr_btn.click(
-        trans_api,
-        [input_text, max_length, top_p, temperature],
-        out_text,
-        # show_progress="full",
-        api_name="tr",
-    )
-    _ = """
-    input_text.submit(
-        trans_api,
-        [input_text, max_length, top_p, temperature],
-        out_text,
-        show_progress="full",
-        api_name="tr1",
-    )
-    # """
-
-# demo.queue().launch(share=False, inbrowser=True)
-# demo.queue().launch(share=True, inbrowser=True, debug=True)
-
-demo.queue().launch(debug=True)
+# Display the reversed text
+st.write("Reversed text:", reversed_text)

app1.py

@@ -1,11 +0,0 @@
-import streamlit as st
-
-# Title and input
-st.title("Reverse Text")
-input_text = st.text_input("Enter some text")
-
-# Reverse the input text
-reversed_text = input_text[::-1]
-
-# Display the reversed text
-st.write("Reversed text:", reversed_text)

app22.py

@@ -4,8 +4,6 @@ import streamlit as st
 
 model = st.text_input("model name: ")
 
-model = "gorkemgoknar/gpt2chatbotenglish"
-
 while model == "":
     time.sleep(0.1)