Create app.py

app.py

@@ -0,0 +1,418 @@
+import os
+import argparse
+from typing import Iterator
+
+import gradio as gr
+from dotenv import load_dotenv
+from distutils.util import strtobool
+
+from llama2_wrapper import LLAMA2_WRAPPER
+
+import logging
+
+from prompts.utils import PromtsContainer
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model_path", type=str, default="", help="model path")
+    parser.add_argument(
+        "--backend_type",
+        type=str,
+        default="",
+        help="Backend options: llama.cpp, gptq, transformers",
+    )
+    parser.add_argument(
+        "--load_in_8bit",
+        type=bool,
+        default=False,
+        help="Whether to use bitsandbytes 8 bit.",
+    )
+    parser.add_argument(
+        "--share",
+        type=bool,
+        default=False,
+        help="Whether to share public for gradio.",
+    )
+    args = parser.parse_args()
+
+    load_dotenv()
+
+    DEFAULT_SYSTEM_PROMPT = os.getenv("DEFAULT_SYSTEM_PROMPT", "")
+    MAX_MAX_NEW_TOKENS = int(os.getenv("MAX_MAX_NEW_TOKENS", 2048))
+    DEFAULT_MAX_NEW_TOKENS = int(os.getenv("DEFAULT_MAX_NEW_TOKENS", 1024))
+    MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", 4000))
+
+    MODEL_PATH = os.getenv("MODEL_PATH")
+    assert MODEL_PATH is not None, f"MODEL_PATH is required, got: {MODEL_PATH}"
+    BACKEND_TYPE = os.getenv("BACKEND_TYPE")
+    assert BACKEND_TYPE is not None, f"BACKEND_TYPE is required, got: {BACKEND_TYPE}"
+
+    LOAD_IN_8BIT = bool(strtobool(os.getenv("LOAD_IN_8BIT", "True")))
+
+    if args.model_path != "":
+        MODEL_PATH = args.model_path
+    if args.backend_type != "":
+        BACKEND_TYPE = args.backend_type
+    if args.load_in_8bit:
+        LOAD_IN_8BIT = True
+
+    llama2_wrapper = LLAMA2_WRAPPER(
+        model_path=MODEL_PATH,
+        backend_type=BACKEND_TYPE,
+        max_tokens=MAX_INPUT_TOKEN_LENGTH,
+        load_in_8bit=LOAD_IN_8BIT,
+        # verbose=True,
+    )
+
+    DESCRIPTION = """
+    # llama2-webui
+    """
+    DESCRIPTION2 = """
+    - Supporting models: [Llama-2-7b](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML)/[13b](https://huggingface.co/llamaste/Llama-2-13b-chat-hf)/[70b](https://huggingface.co/llamaste/Llama-2-70b-chat-hf), [Llama-2-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ), [Llama-2-GGML](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML), [CodeLlama](https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GPTQ) ...
+    - Supporting model backends: [tranformers](https://github.com/huggingface/transformers), [bitsandbytes(8-bit inference)](https://github.com/TimDettmers/bitsandbytes), [AutoGPTQ(4-bit inference)](https://github.com/PanQiWei/AutoGPTQ), [llama.cpp](https://github.com/ggerganov/llama.cpp)
+    """
+
+    def clear_and_save_textbox(message: str) -> tuple[str, str]:
+        return "", message
+
+    def save_textbox_for_prompt(message: str) -> str:
+        logging.info("start save_textbox_from_prompt")
+        message = convert_summary_to_prompt(message)
+        return message
+
+    def display_input(
+        message: str, history: list[tuple[str, str]]
+    ) -> list[tuple[str, str]]:
+        history.append((message, ""))
+        return history
+
+    def delete_prev_fn(
+        history: list[tuple[str, str]]
+    ) -> tuple[list[tuple[str, str]], str]:
+        try:
+            message, _ = history.pop()
+        except IndexError:
+            message = ""
+        return history, message or ""
+
+    def generate(
+        message: str,
+        history_with_input: list[tuple[str, str]],
+        system_prompt: str,
+        max_new_tokens: int,
+        temperature: float,
+        top_p: float,
+        top_k: int,
+    ) -> Iterator[list[tuple[str, str]]]:
+        if max_new_tokens > MAX_MAX_NEW_TOKENS:
+            raise ValueError
+        try:
+            history = history_with_input[:-1]
+            generator = llama2_wrapper.run(
+                message,
+                history,
+                system_prompt,
+                max_new_tokens,
+                temperature,
+                top_p,
+                top_k,
+            )
+            try:
+                first_response = next(generator)
+                yield history + [(message, first_response)]
+            except StopIteration:
+                yield history + [(message, "")]
+            for response in generator:
+                yield history + [(message, response)]
+        except Exception as e:
+            logging.exception(e)
+
+    def check_input_token_length(
+        message: str, chat_history: list[tuple[str, str]], system_prompt: str
+    ) -> None:
+        input_token_length = llama2_wrapper.get_input_token_length(
+            message, chat_history, system_prompt
+        )
+        if input_token_length > MAX_INPUT_TOKEN_LENGTH:
+            raise gr.Error(
+                f"The accumulated input is too long ({input_token_length} > {MAX_INPUT_TOKEN_LENGTH}). Clear your chat history and try again."
+            )
+
+    prompts_container = PromtsContainer()
+    prompts = prompts_container.get_prompts_tab_dict()
+    default_prompts_checkbox = False
+    default_advanced_checkbox = False
+
+    def convert_summary_to_prompt(summary):
+        return prompts_container.get_prompt_by_summary(summary)
+
+    def two_columns_list(tab_data, chatbot):
+        result = []
+        for i in range(int(len(tab_data) / 2) + 1):
+            row = gr.Row()
+            with row:
+                for j in range(2):
+                    index = 2 * i + j
+                    if index >= len(tab_data):
+                        break
+                    item = tab_data[index]
+                    with gr.Group():
+                        gr.HTML(
+                            f'<p style="color: black; font-weight: bold;">{item["act"]}</p>'
+                        )
+                        prompt_text = gr.Button(
+                            label="",
+                            value=f"{item['summary']}",
+                            size="sm",
+                            elem_classes="text-left-aligned",
+                        )
+                        prompt_text.click(
+                            fn=save_textbox_for_prompt,
+                            inputs=prompt_text,
+                            outputs=saved_input,
+                            api_name=False,
+                            queue=True,
+                        ).then(
+                            fn=display_input,
+                            inputs=[saved_input, chatbot],
+                            outputs=chatbot,
+                            api_name=False,
+                            queue=True,
+                        ).then(
+                            fn=check_input_token_length,
+                            inputs=[saved_input, chatbot, system_prompt],
+                            api_name=False,
+                            queue=False,
+                        ).success(
+                            fn=generate,
+                            inputs=[
+                                saved_input,
+                                chatbot,
+                                system_prompt,
+                                max_new_tokens,
+                                temperature,
+                                top_p,
+                                top_k,
+                            ],
+                            outputs=chatbot,
+                            api_name=False,
+                        )
+                result.append(row)
+        return result
+
+    CSS = """
+        .contain { display: flex; flex-direction: column;}
+        #component-0 #component-1 #component-2 #component-4 #component-5 { height:71vh !important; }
+        #component-0 #component-1 #component-24 > div:nth-child(2) { height:80vh !important; overflow-y:auto }
+        .text-left-aligned {text-align: left !important; font-size: 16px;}
+    """
+    with gr.Blocks(css=CSS) as demo:
+        with gr.Row(equal_height=True):
+            with gr.Column(scale=2):
+                gr.Markdown(DESCRIPTION)
+                with gr.Group():
+                    chatbot = gr.Chatbot(label="Chatbot")
+                    with gr.Row():
+                        textbox = gr.Textbox(
+                            container=False,
+                            show_label=False,
+                            placeholder="Type a message...",
+                            scale=10,
+                        )
+                        submit_button = gr.Button(
+                            "Submit", variant="primary", scale=1, min_width=0
+                        )
+                with gr.Row():
+                    retry_button = gr.Button("🔄  Retry", variant="secondary")
+                    undo_button = gr.Button("↩️ Undo", variant="secondary")
+                    clear_button = gr.Button("🗑️  Clear", variant="secondary")
+
+                saved_input = gr.State()
+                with gr.Row():
+                    advanced_checkbox = gr.Checkbox(
+                        label="Advanced",
+                        value=default_prompts_checkbox,
+                        container=False,
+                        elem_classes="min_check",
+                    )
+                    prompts_checkbox = gr.Checkbox(
+                        label="Prompts",
+                        value=default_prompts_checkbox,
+                        container=False,
+                        elem_classes="min_check",
+                    )
+                with gr.Column(visible=default_advanced_checkbox) as advanced_column:
+                    system_prompt = gr.Textbox(
+                        label="System prompt", value=DEFAULT_SYSTEM_PROMPT, lines=6
+                    )
+                    max_new_tokens = gr.Slider(
+                        label="Max new tokens",
+                        minimum=1,
+                        maximum=MAX_MAX_NEW_TOKENS,
+                        step=1,
+                        value=DEFAULT_MAX_NEW_TOKENS,
+                    )
+                    temperature = gr.Slider(
+                        label="Temperature",
+                        minimum=0.1,
+                        maximum=4.0,
+                        step=0.1,
+                        value=1.0,
+                    )
+                    top_p = gr.Slider(
+                        label="Top-p (nucleus sampling)",
+                        minimum=0.05,
+                        maximum=1.0,
+                        step=0.05,
+                        value=0.95,
+                    )
+                    top_k = gr.Slider(
+                        label="Top-k",
+                        minimum=1,
+                        maximum=1000,
+                        step=1,
+                        value=50,
+                    )
+            with gr.Column(scale=1, visible=default_prompts_checkbox) as prompt_column:
+                gr.HTML(
+                    '<p style="color: green; font-weight: bold;font-size: 16px;">\N{four leaf clover} prompts</p>'
+                )
+                for k, v in prompts.items():
+                    with gr.Tab(k, scroll_to_output=True):
+                        lst = two_columns_list(v, chatbot)
+            prompts_checkbox.change(
+                lambda x: gr.update(visible=x),
+                prompts_checkbox,
+                prompt_column,
+                queue=False,
+            )
+            advanced_checkbox.change(
+                lambda x: gr.update(visible=x),
+                advanced_checkbox,
+                advanced_column,
+                queue=False,
+            )
+
+        textbox.submit(
+            fn=clear_and_save_textbox,
+            inputs=textbox,
+            outputs=[textbox, saved_input],
+            api_name=False,
+            queue=False,
+        ).then(
+            fn=display_input,
+            inputs=[saved_input, chatbot],
+            outputs=chatbot,
+            api_name=False,
+            queue=False,
+        ).then(
+            fn=check_input_token_length,
+            inputs=[saved_input, chatbot, system_prompt],
+            api_name=False,
+            queue=False,
+        ).success(
+            fn=generate,
+            inputs=[
+                saved_input,
+                chatbot,
+                system_prompt,
+                max_new_tokens,
+                temperature,
+                top_p,
+                top_k,
+            ],
+            outputs=chatbot,
+            api_name=False,
+        )
+
+        button_event_preprocess = (
+            submit_button.click(
+                fn=clear_and_save_textbox,
+                inputs=textbox,
+                outputs=[textbox, saved_input],
+                api_name=False,
+                queue=False,
+            )
+            .then(
+                fn=display_input,
+                inputs=[saved_input, chatbot],
+                outputs=chatbot,
+                api_name=False,
+                queue=False,
+            )
+            .then(
+                fn=check_input_token_length,
+                inputs=[saved_input, chatbot, system_prompt],
+                api_name=False,
+                queue=False,
+            )
+            .success(
+                fn=generate,
+                inputs=[
+                    saved_input,
+                    chatbot,
+                    system_prompt,
+                    max_new_tokens,
+                    temperature,
+                    top_p,
+                    top_k,
+                ],
+                outputs=chatbot,
+                api_name=False,
+            )
+        )
+
+        retry_button.click(
+            fn=delete_prev_fn,
+            inputs=chatbot,
+            outputs=[chatbot, saved_input],
+            api_name=False,
+            queue=False,
+        ).then(
+            fn=display_input,
+            inputs=[saved_input, chatbot],
+            outputs=chatbot,
+            api_name=False,
+            queue=False,
+        ).then(
+            fn=generate,
+            inputs=[
+                saved_input,
+                chatbot,
+                system_prompt,
+                max_new_tokens,
+                temperature,
+                top_p,
+                top_k,
+            ],
+            outputs=chatbot,
+            api_name=False,
+        )
+
+        undo_button.click(
+            fn=delete_prev_fn,
+            inputs=chatbot,
+            outputs=[chatbot, saved_input],
+            api_name=False,
+            queue=False,
+        ).then(
+            fn=lambda x: x,
+            inputs=[saved_input],
+            outputs=textbox,
+            api_name=False,
+            queue=False,
+        )
+
+        clear_button.click(
+            fn=lambda: ([], ""),
+            outputs=[chatbot, saved_input],
+            queue=False,
+            api_name=False,
+        )
+
+    demo.queue(max_size=20).launch(share=args.share)
+
+
+if __name__ == "__main__":
+    main()