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BoldStudio commited on Apr 16, 2023

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Duplicate from BoldStudio/wab

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Co-authored-by: Kadir <BoldStudio@users.noreply.huggingface.co>

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.gitattributes +36 -0
README.md +13 -0
app.py +313 -0
requirements.txt +3 -0

.gitattributes ADDED Viewed

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+# GIT
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
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+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
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+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md ADDED Viewed

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+---
+title: wab assist
+emoji: 📊
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+sdk_version: 3.20.1
+app_file: app.py
+pinned: false
+duplicated_from: BoldStudio/wab
+---
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py ADDED Viewed

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+import os
+import gradio as gr
+from gradio import interface, blocks
+import requests
+from text_generation import Client, InferenceAPIClient
+openchat_preprompt = (
+    "\n<prompter>: Generate a button that says hello\n<assistant>:<button>hello</button>\n"
+)
+preprompt = "[REQUIRMENTS]:\n Only output in html syntax.\n Do not output a html file! \n Do not use the <html> tag! \n DO NOT USE <br/> tag, DO not output explanation. Do not use Natural Language, Only answer in html syntax, \n only output the html for the elements in my question, DO NOT USE HELLO WORLD!!!,"
+prepromptTags = [
+    '<div>',
+    '<p>',
+    '<h1>',
+    '<h2>',
+    '<h3>',
+    '<h4>',
+    '<h5>',
+    '<h6>',
+    '<table>',
+    '<form>',
+    '<a>',
+]
+def get_client(model: str):
+    if model == "togethercomputer/GPT-NeoXT-Chat-Base-20B":
+        return Client(os.getenv("OPENCHAT_API_URL"))
+    return InferenceAPIClient(model, token=os.getenv("HF_TOKEN", None))
+def get_usernames(model: str):
+    """
+    Returns:
+        (str, str, str, str): pre-prompt, username, bot name, separator
+    """
+    if model == "OpenAssistant/oasst-sft-1-pythia-12b":
+        return "", "<|prompter|>", "<|assistant|>", "<|endoftext|>"
+    if model == "togethercomputer/GPT-NeoXT-Chat-Base-20B":
+        return openchat_preprompt, "<human>: ", "<bot>: ", "\n"
+    return "", "User: ", "Assistant: ", "\n"
+def predict(
+    model: str,
+    inputs: str,
+    typical_p: float,
+    top_p: float,
+    temperature: float,
+    top_k: int,
+    repetition_penalty: float,
+    watermark: bool,
+    chatbot,
+    history,
+):
+    client = get_client(model)
+    preprompt, user_name, assistant_name, sep = get_usernames(model)
+    history.append(inputs)
+    past = []
+    for data in chatbot:
+        user_data, model_data = data
+        if not user_data.startswith(user_name):
+            user_data = user_name + user_data
+        if not model_data.startswith(sep + assistant_name):
+            model_data = sep + assistant_name + model_data
+        past.append(user_data + model_data.rstrip() + sep)
+    if not inputs.startswith(user_name):
+        inputs = user_name + inputs
+    total_inputs = preprompt + \
+        "".join(prepromptTags) + "".join(past) + \
+        inputs + sep + assistant_name.rstrip()
+    partial_words = ""
+    if model == "OpenAssistant/oasst-sft-1-pythia-12b":
+        iterator = client.generate_stream(
+            total_inputs,
+            typical_p=typical_p,
+            truncate=1000,
+            watermark=watermark,
+            max_new_tokens=500,
+        )
+    else:
+        iterator = client.generate_stream(
+            total_inputs,
+            top_p=top_p if top_p < 1.0 else None,
+            top_k=top_k,
+            truncate=1000,
+            repetition_penalty=repetition_penalty,
+            watermark=watermark,
+            temperature=temperature,
+            max_new_tokens=500,
+            stop_sequences=[user_name.rstrip(), assistant_name.rstrip()],
+        )
+    for i, response in enumerate(iterator):
+        if response.token.special:
+            continue
+        partial_words = partial_words + response.token.text
+        if partial_words.endswith(user_name.rstrip()):
+            partial_words = partial_words.rstrip(user_name.rstrip())
+        if partial_words.endswith(assistant_name.rstrip()):
+            partial_words = partial_words.rstrip(assistant_name.rstrip())
+        if i == 0:
+            history.append(" " + partial_words)
+        elif response.token.text not in user_name:
+            history[-1] = partial_words
+        chat = [
+            (history[i].strip(), history[i + 1].strip())
+            for i in range(0, len(history) - 1, 2)
+        ]
+        yield chat, history
+def reset_textbox():
+    return gr.update(value="")
+def radio_on_change(
+    value: str,
+    typical_p,
+    top_p,
+    top_k,
+    temperature,
+    repetition_penalty,
+    watermark,
+):
+    if value == "OpenAssistant/oasst-sft-1-pythia-12b":
+        typical_p = typical_p.update(value=0.2, visible=True)
+        top_p = top_p.update(visible=False)
+        top_k = top_k.update(visible=False)
+        temperature = temperature.update(visible=False)
+        repetition_penalty = repetition_penalty.update(visible=False)
+        watermark = watermark.update(False)
+    elif value == "togethercomputer/GPT-NeoXT-Chat-Base-20B":
+        typical_p = typical_p.update(visible=False)
+        top_p = top_p.update(value=0.25, visible=True)
+        top_k = top_k.update(value=50, visible=True)
+        temperature = temperature.update(value=0.6, visible=True)
+        repetition_penalty = repetition_penalty.update(
+            value=1.01, visible=True)
+        watermark = watermark.update(False)
+    else:
+        typical_p = typical_p.update(visible=False)
+        top_p = top_p.update(value=0.95, visible=True)
+        top_k = top_k.update(value=4, visible=True)
+        temperature = temperature.update(value=0.5, visible=True)
+        repetition_penalty = repetition_penalty.update(
+            value=1.03, visible=True)
+        watermark = watermark.update(True)
+    return (
+        typical_p,
+        top_p,
+        top_k,
+        temperature,
+        repetition_penalty,
+        watermark,
+    )
+title = """<h3 align="left">WAB-Assist</h3>"""
+with gr.Blocks(
+    css="""
+        #col_container {margin-left: auto; margin-right: auto;}
+        #chatbot {height: 420px; overflow: auto; box-shadow: 0 0 10px rgba(0,0,0,0.2)}
+        #userInput { box-shadow: 0 0 10px rgba(0,0,0,0.2);padding:0px;}
+        #userInput span{display:none}
+        #submit, #api {max-width: max-content;background: #313170;color: white;}
+        """
+) as view:
+    gr.HTML(title)
+    gr.Markdown(visible=True)
+    with gr.Column(elem_id="col_container"):
+        model = gr.Radio(
+            value="OpenAssistant/oasst-sft-1-pythia-12b",
+            choices=[
+                "OpenAssistant/oasst-sft-1-pythia-12b",
+                # "togethercomputer/GPT-NeoXT-Chat-Base-20B",
+                # "google/flan-t5-xxl",
+                # "google/flan-ul2",
+                # "bigscience/bloom",
+                # "bigscience/bloomz",
+                # "EleutherAI/gpt-neox-20b",
+            ],
+            label="Model",
+            interactive=False,
+            visible=False
+        )
+        chatbot = gr.Chatbot(elem_id="chatbot")
+        with gr.Row(elem_id="row"):
+            inputs = gr.Textbox(
+                placeholder="hey!",
+                label="",
+                elem_id="userInput"
+            )
+            buttonSend = gr.Button(value="send", elem_id="submit")
+            buttonAPI = gr.Button(value="api", elem_id="api")
+        state = gr.State([])
+        with gr.Accordion("Parameters", open=False, visible=False):
+            typical_p = gr.Slider(
+                minimum=-0,
+                maximum=1.0,
+                value=0.55,
+                step=0.05,
+                interactive=True,
+                label="Typical P mass",
+            )
+            top_p = gr.Slider(
+                minimum=-0,
+                maximum=1.0,
+                value=0.55,
+                step=0.05,
+                interactive=True,
+                label="Top-p (nucleus sampling)",
+                visible=True,
+            )
+            temperature = gr.Slider(
+                minimum=-0,
+                maximum=5.0,
+                value=3,
+                step=0.1,
+                interactive=True,
+                label="Temperature",
+                visible=True,
+            )
+            top_k = gr.Slider(
+                minimum=1,
+                maximum=50,
+                value=50,
+                step=1,
+                interactive=True,
+                label="Top-k",
+                visible=True,
+            )
+            repetition_penalty = gr.Slider(
+                minimum=0.1,
+                maximum=3.0,
+                value=2,
+                step=0.01,
+                interactive=True,
+                label="Repetition Penalty",
+                visible=True,
+            )
+            watermark = gr.Checkbox(value=False, label="Text watermarking")
+    model.change(
+        lambda value: radio_on_change(
+            value,
+            typical_p,
+            top_p,
+            top_k,
+            temperature,
+            repetition_penalty,
+            watermark,
+        ),
+        inputs=model,
+        outputs=[
+            typical_p,
+            top_p,
+            top_k,
+            temperature,
+            repetition_penalty,
+            watermark,
+        ],
+    )
+    inputs.submit(
+        predict,
+        [
+            model,
+            inputs,
+            typical_p,
+            top_p,
+            temperature,
+            top_k,
+            repetition_penalty,
+            watermark,
+            chatbot,
+            state,
+        ],
+        [chatbot, state],
+    )
+    buttonSend.click(
+        predict,
+        [
+            model,
+            inputs,
+            typical_p,
+            top_p,
+            temperature,
+            top_k,
+            repetition_penalty,
+            watermark,
+            chatbot,
+            state,
+        ],
+        [chatbot, state],
+    )
+    buttonSend.click(reset_textbox, [], [inputs])
+    inputs.submit(reset_textbox, [], [inputs])
+    view.launch()

requirements.txt ADDED Viewed

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+# REQUIRMENTS
+text-generation==0.3.0
+gradio==3.20.1