update

app.py

@@ -6,7 +6,10 @@
 Demo script to launch Language chat model 
 """
 
-import spaces
+try:
+    import spaces
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
 import os
 from gradio.themes import ThemeClass as Theme
 import numpy as np
@@ -102,12 +105,15 @@ def launch_demo():
             MODEL_INFO.format(model_path=model_path)
         )
 
-    demo = CustomTabbedInterface(
-        interface_list=list(demos.values()),
-        tab_names=demos_names,
-        title=f"{MODEL_TITLE}",
-        description=descriptions,
-    )
+    if len(demos) == 1:
+        demo = demos[DEMOS[0]]
+    else:
+        demo = CustomTabbedInterface(
+            interface_list=list(demos.values()),
+            tab_names=demos_names,
+            title=f"{MODEL_TITLE}",
+            description=descriptions,
+        )
 
     demo.title = MODEL_NAME
     

multipurpose_chatbot/configs.py

@@ -1,4 +1,3 @@
-
 import os
 
 # ! UI Markdown information
@@ -35,19 +34,19 @@ MODEL_DESC = f"""
 <span style="color: red">The chatbot may produce false and harmful content!</span>
 By using our service, you are required to agree to our <a href="https://huggingface.co/SeaLLMs/SeaLLM-Chat-13b/blob/main/LICENSE" target="_blank" style="color: red">Terms Of Use</a>
 </span>
-
 """.strip()
 
+# Explore <a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B" target="_blank">SeaLMMM-7B</a> - our multi-modal version of SeaLLMs.
 MODEL_DESC = f"""
 <div style='display:flex; gap: 0.25rem; '>
+<a href='https://damo-nlp-sg.github.io/SeaLLMs/'><img src='https://img.shields.io/badge/Blog-red'></a>
 <a href='https://github.com/damo-nlp-sg/seallms'><img src='https://img.shields.io/badge/Github-Code-success'></a>
 <a href='https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B-v2.5'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> 
 <a href='https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> 
-<a href='https://arxiv.org/pdf/2312.00738.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a>
+<a href='https://arxiv.org/pdf/2312.00738.pdf'><img src='https://img.shields.io/badge/Paper-red'></a>
 </div>
 <span style="font-size: larger">
-<a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5" target="_blank">SeaLLM-7B-v2.5</a> - a helpful assistant for Southeast Asian Languages 🇬🇧 🇻🇳 🇮🇩 🇹🇭 🇲🇾 🇰🇭 🇱🇦 🇵🇭 🇲🇲.
-Explore <a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B" target="_blank">SeaLMMM-7B</a> - our multi-modal version of SeaLLMs.
+<a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5" target="_blank">SeaLLM-7B-v2.5</a> - a assistant for Southeast Asian Languages 🇬🇧 🇻🇳 🇮🇩 🇹🇭 🇲🇾 🇰🇭 🇱🇦 🇵🇭 🇲🇲.
 </span>
 <br>
 <span>
@@ -68,10 +67,8 @@ By using our service, you are required to agree to our <a href="https://huggingf
 not to use our service to generate any harmful, inappropriate or illegal content. 
 The service collects user dialogue data for testing and improvement under 
 <a href="https://creativecommons.org/licenses/by/4.0/">(CC-BY)</a> or similar license. So do not enter any personal information!
-
 """
 
-
 # MODEL_INFO = """
 # <h4 style="display: hidden;">Model Name: {model_path}</h4>
 # """
@@ -82,7 +79,9 @@ CITE_MARKDOWN = """
 If you find our project useful, hope you can star our repo and cite our paper as follows:
 ```
 @article{damonlpsg2023seallm,
-  author = {Xuan-Phi Nguyen*, Wenxuan Zhang*, Xin Li*, Mahani Aljunied*, Zhiqiang Hu, Chenhui Shen^, Yew Ken Chia^, Xingxuan Li, Jianyu Wang, Qingyu Tan, Liying Cheng, Guanzheng Chen, Yue Deng, Sen Yang, Chaoqun Liu, Hang Zhang, Lidong Bing},
+  author = {Xuan-Phi Nguyen*, Wenxuan Zhang*, Xin Li*, Mahani Aljunied*, Weiwen Xu, Hou Pong Chan, 
+            Zhiqiang Hu, Chenhui Shen^, Yew Ken Chia^, Xingxuan Li, Jianyu Wang, Qingyu Tan, Liying Cheng, 
+            Guanzheng Chen, Yue Deng, Sen Yang, Chaoqun Liu, Hang Zhang, Lidong Bing},
   title = {SeaLLMs - Large Language Models for Southeast Asia},
   year = 2023,
 }
@@ -137,7 +136,7 @@ PRESENCE_PENALTY = float(os.environ.get("PRESENCE_PENALTY", "0.0"))
 
 
 # Transformers or vllm
-MODEL_PATH = os.environ.get("MODEL_PATH", "mistralai/Mistral-7B-Instruct-v0.2")
+MODEL_PATH = os.environ.get("MODEL_PATH", "SeaLLMs/SeaLLM-7B-v2")
 MODEL_NAME = os.environ.get("MODEL_NAME", "Cool-Chatbot")
 DTYPE = os.environ.get("DTYPE", "bfloat16")
 DEVICE = os.environ.get("DEVICE", "cuda")

multipurpose_chatbot/demos/__init__.py

@@ -6,4 +6,5 @@ from .rag_chat_interface import RagChatInterfaceDemo
 from .multimodal_chat_interface import *
 from .text_completion import *
 from .batch_inference import *
-from .multimodal_preference_interface import *
+from .multimodal_preference_interface import *
+from .mm_chat_interface import *

multipurpose_chatbot/demos/chat_interface.py

@@ -1,5 +1,12 @@
-import os
-import spaces
+try:
+    import spaces
+    def maybe_spaces_gpu(fn):
+        fn = spaces.GPU(fn)
+        return fn
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
+    def maybe_spaces_gpu(fn):
+        return fn
 from gradio.themes import ThemeClass as Theme
 import numpy as np
 import argparse
@@ -122,7 +129,7 @@ def format_conversation(history, system_prompt=None):
     return _str
 
 
-@spaces.GPU
+@maybe_spaces_gpu
 def chat_response_stream_multiturn_engine(
     message: str, 
     history: List[Tuple[str, str]], 

multipurpose_chatbot/demos/mm_chat_interface.py

@@ -0,0 +1,965 @@
+import os
+from gradio.themes import ThemeClass as Theme
+import numpy as np
+import argparse
+import gradio as gr
+from typing import Any, Iterator
+from typing import Iterator, List, Optional, Tuple
+import filelock
+import glob
+import json
+import time
+from gradio.routes import Request
+from gradio.utils import SyncToAsyncIterator, async_iteration
+from gradio.helpers import special_args
+import anyio
+from typing import AsyncGenerator, Callable, Literal, Union, cast, Generator
+
+from gradio_client.documentation import document, set_documentation_group
+from gradio.components import Button, Component
+from gradio.events import Dependency, EventListenerMethod
+from typing import List, Optional, Union, Dict, Tuple
+from tqdm.auto import tqdm
+from huggingface_hub import snapshot_download
+from gradio.components.base import Component
+
+from .base_demo import register_demo, get_demo_class, BaseDemo
+
+
+from .chat_interface import (
+    SYSTEM_PROMPT,
+    MODEL_NAME,
+    MAX_TOKENS,
+    TEMPERATURE,
+    CHAT_EXAMPLES,
+    format_conversation,
+    gradio_history_to_openai_conversations,
+    gradio_history_to_conversation_prompt,
+    DATETIME_FORMAT,
+    get_datetime_string,
+    chat_response_stream_multiturn_engine,
+    ChatInterfaceDemo,
+    CustomizedChatInterface,
+)
+
+from gradio.events import Events
+
+import inspect
+from typing import AsyncGenerator, Callable, Literal, Union, cast
+
+import anyio
+from gradio_client import utils as client_utils
+from gradio_client.documentation import document
+
+from gradio.blocks import Blocks
+from gradio.components import (
+    Button,
+    Chatbot,
+    Component,
+    Markdown,
+    State,
+    Textbox,
+    get_component_instance,
+)
+from gradio.events import Dependency, on
+from gradio.helpers import create_examples as Examples  # noqa: N812
+from gradio.helpers import special_args
+from gradio.layouts import Accordion, Group, Row
+from gradio.routes import Request
+from gradio.themes import ThemeClass as Theme
+from gradio.utils import SyncToAsyncIterator, async_iteration
+
+from ..globals import MODEL_ENGINE
+
+from ..configs import (
+    USE_PANEL,
+    IMAGE_TOKEN,
+    IMAGE_TOKEN_INTERACTIVE,
+    CHATBOT_HEIGHT,
+)
+
+from .multimodal_chat_interface import (
+    undo_history,
+    undo_history_until_last_assistant_turn,
+    vision_chat_response_stream_multiturn_engine,
+    doc_chat_response_stream_multiturn_engine,
+    vision_doc_chat_response_stream_multiturn_engine,
+    gradio_history_to_conversation_prompt,
+    gradio_history_to_openai_conversations,
+    gradio_history_to_doc_conversation_prompt,
+    gradio_history_to_vision_conversation_prompt_paths,
+    gradio_history_to_vision_doc_conversation_prompt_paths,
+)
+
+# .message-fit {
+#     min-width: 20em; 
+#     width: fit-content !important;
+# }
+
+EXAMPLES_PER_PAGE = int(os.environ.get("EXAMPLES_PER_PAGE", 10))
+
+CSS = """
+.message.svelte-1lcyrx4.svelte-1lcyrx4.svelte-1lcyrx4 {
+    padding-top: 1em;
+}
+"""
+
+CSS = """
+.panel-full-width.svelte-1lcyrx4.svelte-1lcyrx4.svelte-1lcyrx4 {
+    padding: calc(var(--spacing-xxl) * 1);
+    width: 100%
+}
+"""
+
+DOC_TEMPLATE = """###
+{content}
+###
+
+"""
+
+DOC_INSTRUCTION = """Answer the following query exclusively based on the information provided in the document above. \
+If the information is not found, please say so instead of making up facts! Remember to answer the question in the same language as the user query!
+"""
+
+
+MultimodalTextbox = None
+
+try:
+    from gradio import MultimodalTextbox
+except ImportError as e:
+    print(f'Cannot import MultiModalTextbox: {MultimodalTextbox}')
+
+
+class MultiModalTextChatInterface(CustomizedChatInterface):
+    def __init__(
+        self,
+        fn: Callable,
+        *,
+        chatbot: Chatbot | None = None,
+        textbox: Textbox | None = None,
+        additional_inputs: str | Component | list[str | Component] | None = None,
+        additional_inputs_accordion_name: str | None = None,
+        additional_inputs_accordion: str | Accordion | None = None,
+        examples: list[str] | None = None,
+        cache_examples: bool | None = None,
+        title: str | None = None,
+        description: str | None = None,
+        theme: Theme | str | None = None,
+        css: str | None = None,
+        js: str | None = None,
+        head: str | None = None,
+        analytics_enabled: bool | None = None,
+        submit_btn: str | None | Button = "Submit",
+        stop_btn: str | None | Button = "Stop",
+        retry_btn: str | None | Button = "🔄  Retry",
+        undo_btn: str | None | Button = "↩️ Undo",
+        clear_btn: str | None | Button = "🗑️  Clear",
+        autofocus: bool = True,
+        concurrency_limit: int | None | Literal["default"] = "default",
+        fill_height: bool = True,
+    ):
+        """
+        Parameters:
+            fn: The function to wrap the chat interface around. Should accept two parameters: a string input message and list of two-element lists of the form [[user_message, bot_message], ...] representing the chat history, and return a string response. See the Chatbot documentation for more information on the chat history format.
+            chatbot: An instance of the gr.Chatbot component to use for the chat interface, if you would like to customize the chatbot properties. If not provided, a default gr.Chatbot component will be created.
+            textbox: An instance of the gr.Textbox component to use for the chat interface, if you would like to customize the textbox properties. If not provided, a default gr.Textbox component will be created.
+            additional_inputs: An instance or list of instances of gradio components (or their string shortcuts) to use as additional inputs to the chatbot. If components are not already rendered in a surrounding Blocks, then the components will be displayed under the chatbot, in an accordion.
+            additional_inputs_accordion_name: Deprecated. Will be removed in a future version of Gradio. Use the `additional_inputs_accordion` parameter instead.
+            additional_inputs_accordion: If a string is provided, this is the label of the `gr.Accordion` to use to contain additional inputs. A `gr.Accordion` object can be provided as well to configure other properties of the container holding the additional inputs. Defaults to a `gr.Accordion(label="Additional Inputs", open=False)`. This parameter is only used if `additional_inputs` is provided.
+            examples: Sample inputs for the function; if provided, appear below the chatbot and can be clicked to populate the chatbot input.
+            cache_examples: If True, caches examples in the server for fast runtime in examples. The default option in HuggingFace Spaces is True. The default option elsewhere is False.
+            title: a title for the interface; if provided, appears above chatbot in large font. Also used as the tab title when opened in a browser window.
+            description: a description for the interface; if provided, appears above the chatbot and beneath the title in regular font. Accepts Markdown and HTML content.
+            theme: Theme to use, loaded from gradio.themes.
+            css: Custom css as a string or path to a css file. This css will be included in the demo webpage.
+            js: Custom js or path to js file to run when demo is first loaded. This javascript will be included in the demo webpage.
+            head: Custom html to insert into the head of the demo webpage. This can be used to add custom meta tags, scripts, stylesheets, etc. to the page.
+            analytics_enabled: Whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED environment variable if defined, or default to True.
+            submit_btn: Text to display on the submit button. If None, no button will be displayed. If a Button object, that button will be used.
+            stop_btn: Text to display on the stop button, which replaces the submit_btn when the submit_btn or retry_btn is clicked and response is streaming. Clicking on the stop_btn will halt the chatbot response. If set to None, stop button functionality does not appear in the chatbot. If a Button object, that button will be used as the stop button.
+            retry_btn: Text to display on the retry button. If None, no button will be displayed. If a Button object, that button will be used.
+            undo_btn: Text to display on the delete last button. If None, no button will be displayed. If a Button object, that button will be used.
+            clear_btn: Text to display on the clear button. If None, no button will be displayed. If a Button object, that button will be used.
+            autofocus: If True, autofocuses to the textbox when the page loads.
+            concurrency_limit: If set, this is the maximum number of chatbot submissions that can be running simultaneously. Can be set to None to mean no limit (any number of chatbot submissions can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `.queue()`, which is 1 by default).
+            fill_height: If True, the chat interface will expand to the height of window.
+        """
+        try:
+            super(gr.ChatInterface, self).__init__(
+                analytics_enabled=analytics_enabled,
+                mode="chat_interface",
+                css=css,
+                title=title or "Gradio",
+                theme=theme,
+                js=js,
+                head=head,
+                fill_height=fill_height,
+            )
+        except Exception as e:
+            # Handling some old gradio version with out fill_height
+            super(gr.ChatInterface, self).__init__(
+                analytics_enabled=analytics_enabled,
+                mode="chat_interface",
+                css=css,
+                title=title or "Gradio",
+                theme=theme,
+                js=js,
+                head=head,
+                # fill_height=fill_height,
+            )
+        self.concurrency_limit = concurrency_limit
+        self.fn = fn
+        self.is_async = inspect.iscoroutinefunction(
+            self.fn
+        ) or inspect.isasyncgenfunction(self.fn)
+        self.is_generator = inspect.isgeneratorfunction(
+            self.fn
+        ) or inspect.isasyncgenfunction(self.fn)
+        self.examples = examples
+        if self.space_id and cache_examples is None:
+            self.cache_examples = True
+        else:
+            self.cache_examples = cache_examples or False
+        self.buttons: list[Button | None] = []
+
+        if additional_inputs:
+            if not isinstance(additional_inputs, list):
+                additional_inputs = [additional_inputs]
+            self.additional_inputs = [
+                get_component_instance(i)
+                for i in additional_inputs  # type: ignore
+            ]
+        else:
+            self.additional_inputs = []
+        if additional_inputs_accordion_name is not None:
+            print(
+                "The `additional_inputs_accordion_name` parameter is deprecated and will be removed in a future version of Gradio. Use the `additional_inputs_accordion` parameter instead."
+            )
+            self.additional_inputs_accordion_params = {
+                "label": additional_inputs_accordion_name
+            }
+        if additional_inputs_accordion is None:
+            self.additional_inputs_accordion_params = {
+                "label": "Additional Inputs",
+                "open": False,
+            }
+        elif isinstance(additional_inputs_accordion, str):
+            self.additional_inputs_accordion_params = {
+                "label": additional_inputs_accordion
+            }
+        elif isinstance(additional_inputs_accordion, Accordion):
+            self.additional_inputs_accordion_params = (
+                additional_inputs_accordion.recover_kwargs(
+                    additional_inputs_accordion.get_config()
+                )
+            )
+        else:
+            raise ValueError(
+                f"The `additional_inputs_accordion` parameter must be a string or gr.Accordion, not {type(additional_inputs_accordion)}"
+            )
+
+        with self:
+            if title:
+                Markdown(
+                    f"<h1 style='text-align: center; margin-bottom: 1rem'>{self.title}</h1>"
+                )
+            if description:
+                Markdown(description)
+
+            if chatbot:
+                self.chatbot = chatbot.render()
+            else:
+                self.chatbot = Chatbot(
+                    label="Chatbot", scale=1, height=200 if fill_height else None
+                )
+
+            with Row():
+                for btn in [retry_btn, undo_btn, clear_btn]:
+                    if btn is not None:
+                        if isinstance(btn, Button):
+                            btn.render()
+                        elif isinstance(btn, str):
+                            btn = Button(btn, variant="secondary", size="sm")
+                        else:
+                            raise ValueError(
+                                f"All the _btn parameters must be a gr.Button, string, or None, not {type(btn)}"
+                            )
+                    self.buttons.append(btn)  # type: ignore
+            
+            # =------
+            with Row():
+                if textbox:
+                    # textbox.container = False
+                    # textbox.show_label = False
+                    textbox_ = textbox.render()
+                    # assert isinstance(textbox_, Textbox)
+                    self.textbox = textbox_
+                else:
+                    self.textbox = Textbox(
+                        container=False,
+                        show_label=False,
+                        label="Message",
+                        placeholder="Type a message...",
+                        scale=7,
+                        autofocus=autofocus,
+                    )
+                if stop_btn is not None:
+                    if isinstance(stop_btn, Button):
+                        stop_btn.visible = False
+                        stop_btn.render()
+                    elif isinstance(stop_btn, str):
+                        stop_btn = Button(
+                            stop_btn,
+                            variant="stop",
+                            visible=False,
+                            scale=2,
+                            min_width=150,
+                        )
+                    else:
+                        raise ValueError(
+                            f"The stop_btn parameter must be a gr.Button, string, or None, not {type(stop_btn)}"
+                        )
+                self.buttons.extend([stop_btn])  # type: ignore
+
+                self.num_tokens = Textbox(
+                        # container=False,
+                        show_label=False,
+                        label="# Tokens",
+                        placeholder="0 tokens",
+                        scale=1,
+                        interactive=False,
+                        # autofocus=autofocus,
+                        min_width=10
+                    )
+            
+            self.fake_api_btn = Button("Fake API", visible=False)
+            self.fake_response_textbox = Textbox(label="Response", visible=False)
+            (
+                self.retry_btn,
+                self.undo_btn,
+                self.clear_btn,
+                # self.submit_btn,
+                self.stop_btn,
+            ) = self.buttons
+            self.submit_btn = None
+
+            if examples:
+                if self.is_generator:
+                    examples_fn = self._examples_stream_fn
+                else:
+                    # examples_fn = self._examples_fn
+                    raise NotImplementedError()
+                
+                def copy_to_mm_textbox(message, image, filename):
+                    save_input = {"text": message, "files": []}
+                    if filename is not None and os.path.exists(filename):
+                        # save_input['files'].append({"path": file})
+                        save_input['files'].append(filename)
+                    if image is not None and os.path.exists(image):
+                        # save_input['files'].append({"path": file})
+                        save_input['files'].append(image)
+                    print(save_input)
+                    return save_input
+                
+                # self.example_textbox = gr.Textbox(visible=False)
+                # self.example_file = gr.File(file_count='single', type='filepath', visible=False)
+                # self.example_image = gr.Image(type='filepath', visible=False)
+
+                # self.examples_handler = Examples(
+                #     examples=examples,
+                #     inputs=[self.example_textbox, self.example_image, self.example_file],
+                #     outputs=self.textbox,
+                #     # fn=examples_fn,
+                #     fn=copy_to_mm_textbox,
+                #     run_on_click=True
+                # )
+                self.examples_handler = Examples(
+                    examples=examples,
+                    # inputs=[self.textbox] + self.additional_inputs,
+                    inputs=[self.textbox],
+                    # outputs=self.chatbot,
+                    # fn=examples_fn,
+                    examples_per_page=EXAMPLES_PER_PAGE,
+                )
+
+            any_unrendered_inputs = any(
+                not inp.is_rendered for inp in self.additional_inputs
+            )
+            if self.additional_inputs and any_unrendered_inputs:
+                with Accordion(**self.additional_inputs_accordion_params):  # type: ignore
+                    for input_component in self.additional_inputs:
+                        if not input_component.is_rendered:
+                            input_component.render()
+
+            # The example caching must happen after the input components have rendered
+            if cache_examples:
+                client_utils.synchronize_async(self.examples_handler.cache)
+
+            self.saved_input = State()
+            self.chatbot_state = (
+                State(self.chatbot.value) if self.chatbot.value else State([])
+            )
+
+            self._setup_events()
+            self._setup_api()
+
+    def _clear_and_save_textbox(self, saved_input: Dict[str, Union[str, list]]) -> Tuple[Dict[str, Union[str, list]], Dict[str, Union[str, list]]]:
+        return {"text": "", "files": []}, saved_input
+
+    def _add_inputs_to_history(self, history: List[List[Union[str, None]]], save_input: Dict[str, Union[str, list]]):
+        message = save_input['text']
+        files = save_input['files']
+        if files is not None and len(files) > 0:
+            for f in files:
+                fpath = f['path'] if isinstance(f, dict) else f
+                history.append([(fpath, ), None])
+        if message is not None and message.strip() != "":
+            history.append([message, None])
+        return history
+    
+    def _display_input(
+        self, saved_input: Dict[str, Union[str, list]], history: List[List[Union[str, None]]]
+    ) -> Tuple[List[List[Union[str, None]]], List[List[list[Union[str, None]]]]]:
+        message = saved_input["text"]
+        files = saved_input['files']
+        if files is not None and len(files) > 0:
+            print(files)
+            for f in files:
+                fpath = f['path'] if isinstance(f, dict) else f
+                history.append([(fpath, ), None])
+        if message is not None and message.strip() != "":
+            history.append([message, None])
+        return history, history
+
+    def _delete_prev_fn(
+        self, history: list[list[str | None]]
+    ) -> tuple[list[list[str | None]], str, list[list[str | None]]]:
+        try:
+            message, _ = history.pop()
+        except IndexError:
+            message = ""
+        # saved_input = [message or ""] + [None] * len(self.multimodal_inputs)
+        saved_input = {"text": message, "files": []}
+        return history, saved_input, history
+    
+    def _setup_events(self) -> None:
+        from gradio.components import State
+        has_on = False
+        try:
+            from gradio.events import Dependency, EventListenerMethod, on
+            has_on = True
+        except ImportError as ie:
+            has_on = False
+        submit_fn = self._stream_fn if self.is_generator else self._submit_fn
+        if not self.is_generator:
+            raise NotImplementedError(f'should use generator')
+
+        if has_on:
+            # new version
+            submit_triggers = (
+                # [self.textbox.submit, self.submit_btn.click]
+                [self.textbox.submit]
+                if self.submit_btn
+                else [self.textbox.submit]
+            )
+            submit_event = (
+                on(
+                    submit_triggers,
+                    self._clear_and_save_textbox,
+                    [self.textbox],
+                    [self.textbox] + [self.saved_input],
+                    api_name=False,
+                    queue=False,
+                )
+                .then(
+                    self._display_input,
+                    [self.saved_input, self.chatbot_state],
+                    [self.chatbot, self.chatbot_state],
+                    api_name=False,
+                    queue=False,
+                )
+                .success(
+                    submit_fn,
+                    [self.chatbot_state] + self.additional_inputs,
+                    [self.chatbot, self.chatbot_state, self.num_tokens],
+                    api_name=False,
+                )
+            )
+            self._setup_stop_events(submit_triggers, submit_event)
+        else:
+            raise ValueError(f'Better install new gradio version than 3.44.0')
+
+        if self.retry_btn:
+            retry_event = (
+                self.retry_btn.click(
+                    self._delete_prev_fn,
+                    [self.chatbot_state],
+                    [self.chatbot, self.saved_input, self.chatbot_state],
+                    api_name=False,
+                    queue=False,
+                )
+                .then(
+                    self._display_input,
+                    [self.saved_input, self.chatbot_state],
+                    [self.chatbot, self.chatbot_state],
+                    api_name=False,
+                    queue=False,
+                )
+                .success(
+                    submit_fn,
+                    [self.chatbot_state] + self.additional_inputs,
+                    [self.chatbot, self.chatbot_state, self.num_tokens],
+                    api_name=False,
+                )
+            )
+            self._setup_stop_events([self.retry_btn.click], retry_event)
+
+        if self.undo_btn:
+            self.undo_btn.click(
+                # self._delete_prev_fn,
+                # [self.chatbot_state],
+                # [self.chatbot, self.saved_input, self.chatbot_state],
+                undo_history_until_last_assistant_turn,
+                [self.chatbot_state],
+                [self.chatbot, self.chatbot_state],
+                api_name=False,
+                queue=False,
+            )
+            # .then(
+            #     lambda x: x,
+            #     [self.saved_input],
+            #     [self.textbox],
+            #     api_name=False,
+            #     queue=False,
+            # )
+    
+    def _setup_stop_events(
+        self, event_triggers: list[EventListenerMethod], event_to_cancel: Dependency
+    ) -> None:
+        from gradio.components import State
+        event_triggers = event_triggers if isinstance(event_triggers, (list, tuple)) else [event_triggers]
+        if self.stop_btn and self.is_generator:
+            if self.submit_btn:
+                for event_trigger in event_triggers:
+                    event_trigger(
+                        lambda: (
+                            Button(visible=False),
+                            Button(visible=True),
+                        ),
+                        None,
+                        [self.submit_btn, self.stop_btn],
+                        api_name=False,
+                        queue=False,
+                    )
+                event_to_cancel.then(
+                    lambda: (Button(visible=True), Button(visible=False)),
+                    None,
+                    [self.submit_btn, self.stop_btn],
+                    api_name=False,
+                    queue=False,
+                )
+            else:
+                for event_trigger in event_triggers:
+                    event_trigger(
+                        lambda: Button(visible=True),
+                        None,
+                        [self.stop_btn],
+                        api_name=False,
+                        queue=False,
+                    )
+                event_to_cancel.then(
+                    lambda: Button(visible=False),
+                    None,
+                    [self.stop_btn],
+                    api_name=False,
+                    queue=False,
+                )
+            self.stop_btn.click(
+                None,
+                None,
+                None,
+                cancels=event_to_cancel,
+                api_name=False,
+            )
+        else:
+            if self.submit_btn:
+                for event_trigger in event_triggers:
+                    event_trigger(
+                        lambda: Button(interactive=False),
+                        None,
+                        [self.submit_btn],
+                        api_name=False,
+                        queue=False,
+                    )
+                event_to_cancel.then(
+                    lambda: Button(interactive=True),
+                    None,
+                    [self.submit_btn],
+                    api_name=False,
+                    queue=False,
+                )
+        # upon clear, cancel the submit event as well
+        if self.clear_btn:
+            if self.submit_btn:
+                self.clear_btn.click(
+                    lambda: ([], [], None, Button(interactive=True)),
+                    None,
+                    [self.chatbot, self.chatbot_state, self.saved_input, self.submit_btn],
+                    queue=False,
+                    api_name=False,
+                    cancels=event_to_cancel,
+                )
+            else:
+                self.clear_btn.click(
+                    lambda: ([], [], None),
+                    None,
+                    [self.chatbot, self.chatbot_state, self.saved_input],
+                    queue=False,
+                    api_name=False,
+                    cancels=event_to_cancel,
+                )
+    
+    async def _stream_fn(
+        self,
+        # message: str,
+        history_with_input,
+        request: Request,
+        *args,
+    ) -> AsyncGenerator:
+        history = history_with_input[:-1]
+        message = history_with_input[-1][0]
+        inputs, _, _ = special_args(
+            self.fn, inputs=[history_with_input, *args], request=request
+        )
+
+        if self.is_async:
+            generator = self.fn(*inputs)
+        else:
+            generator = await anyio.to_thread.run_sync(
+                self.fn, *inputs, limiter=self.limiter
+            )
+            generator = SyncToAsyncIterator(generator, self.limiter)
+
+        # ! In case of error, yield the previous history & undo any generation before raising error
+        try:
+            first_response_pack = await async_iteration(generator)
+            if isinstance(first_response_pack, (tuple, list)):
+                first_response, num_tokens = first_response_pack
+            else:
+                first_response, num_tokens = first_response_pack, -1
+            update = history + [[message, first_response]]
+            # print(f"===\n{update}")
+            yield update, update, f"{num_tokens} toks"
+        except StopIteration:
+            update = history + [[message, None]]
+            yield update, update, "NaN toks"
+        except Exception as e:
+            yield history, history, "NaN toks"
+            raise e
+
+        try:
+            async for response_pack in generator:
+                if isinstance(response_pack, (tuple, list)):
+                    response, num_tokens = response_pack
+                else:
+                    response, num_tokens = response_pack, "NaN toks"
+                update = history + [[message, response]]
+                # print(f"------\n{update}")
+                yield update, update, f"{num_tokens} toks"
+        except Exception as e:
+            yield history, history, "NaN toks"
+            raise e
+    
+    async def _examples_stream_fn(
+        self,
+        # message: str,
+        *args,
+    ) -> AsyncGenerator:
+        raise ValueError(f'invalid')
+        history = []
+        # input_len = 1 + len(self.multimodal_inputs)
+        # input_len = 2
+        # saved_input = args[:input_len]
+        # saved_input = args[0]
+        # message = saved_input['text']
+        # files = saved_input['files']
+        message = args[0]
+        fname = args[1]
+        saved_input = {
+            "text": message,
+            "files": []
+        }
+        if fname is not None and os.path.exists(fname):
+            # saved_input['files'].append({"path": fname})
+            saved_input['files'].append(fname)
+
+        additional_inputs = args[2:]
+        history = self._add_inputs_to_history(history, saved_input)
+        inputs, _, _ = special_args(self.fn, inputs=[history, *additional_inputs], request=None)
+
+        if self.is_async:
+            generator = self.fn(*inputs)
+        else:
+            generator = await anyio.to_thread.run_sync(
+                self.fn, *inputs, limiter=self.limiter
+            )
+            generator = SyncToAsyncIterator(generator, self.limiter)
+        # async for response in generator:
+        #     yield [[message, response]]
+        
+        try:
+            async for response_pack in generator:
+                if isinstance(response_pack, (tuple, list)):
+                    response, num_tokens = response_pack
+                else:
+                    response, num_tokens = response_pack, "NaN toks"
+                update = history + [[message, response]]
+                yield update, update, f"{num_tokens} toks"
+        except Exception as e:
+            yield history, history, "NaN toks"
+            raise e
+
+
+
+@register_demo
+class VisionMMChatInterfaceDemo(ChatInterfaceDemo):
+    """
+    Accept vision image
+    """
+
+    @property
+    def tab_name(self):
+        return "Vision Chat"
+    
+    @property
+    def examples(self):
+        from pathlib import Path
+        from gradio.data_classes import FileData, GradioModel
+        # return [
+        #     ["What's strange about this image?", "assets/dog_monalisa.jpeg", None],
+        #     ["Explain why the sky is blue.", None,],
+        # ]
+        return [
+            # [{"text": "Summarize the document", "files": [{
+            #     "path": "assets/attention_short.pdf", "orig_name": "attention_short", "mime_type": "application/pdf",
+            #     "size": Path("assets/attention_short.pdf").stat().st_size
+            #     }
+            # ]}],
+            # [{"text": "Summarize the document", "files": ["assets/attention_short.pdf"]}],
+            # [{"text": "Summarize the document", "files": [
+            #     FileData(
+            #         path="assets/attention_short.pdf",
+            #         mime_type="application/pdf",
+            #         orig_name="attention_short",
+            #         size=Path("assets/attention_short.pdf").stat().st_size,
+            #         url="attention_short.pdf",
+            #     )    
+            # ]}],
+            # [{"text": "What's strange about this image?", "files": ["assets/dog_monalisa.jpeg"]},],
+            # [{"text": "Explain why the sky is blue.", "files": []},],
+            [{"text": "Mô tả chi tiết bức ảnh.", "files": ["assets/imgs/athlete.jpeg", ]} ],
+            [{"text": "Mô tả chi tiết bức ảnh.", "files": ["assets/imgs/chart_algo.png", ]} ],
+            [{"text": "Explain the image.", "files": ["assets/imgs/chart_soap_sense_cycle.png", ]} ],
+            [{"text": "Provide a detailed description of the poster.", "files": ["assets/imgs/covid.jpeg", ]} ],
+            [{"text": "Where is this place exactly?", "files": ["assets/imgs/danang.jpeg", ]} ],
+            [{"text": "What's strange about this image?", "files": ["assets/dog_monalisa.jpeg",]} ],
+            [{"text": "Đây là ở đâu?", "files": ["assets/imgs/great_wall.png", ]} ],
+            [{"text": "Giới thiệu về nơi này.", "files": ["assets/imgs/hochiminh_city.jpeg", ]} ],
+            [{"text": "Đây là ở đâu?", "files": ["assets/imgs/hochiminh_mausoleum.jpeg", ]} ],
+            [{"text": "Suy nghĩ từng bước một để tìm x.", "files": ["assets/imgs/find_x_triangle.jpeg", ]} ],
+            [{"text": "Provide a detailed description of the poster.", "files": ["assets/imgs/home_injury.jpeg", ]} ],
+            [{"text": "Đây là hành tinh gì?", "files": ["assets/imgs/jupyter.jpeg", ]} ],
+            [{"text": "Miêu tả bức ảnh trên.", "files": ["assets/imgs/leaf.png", ]} ],
+            [{"text": "Đây là đâu?", "files": ["assets/imgs/mbs.png", ]} ],
+            [{"text": "Introduce this figure.", "files": ["assets/imgs/merlion_2.jpeg", ]} ],
+            [{"text": "Explain the figure.", "files": ["assets/imgs/photosynthesis.png", ]} ],
+            [{"text": "List out all the details of the image.", "files": ["assets/imgs/sewing_tools.png", ]} ],
+            [{"text": "What happened in this photo.", "files": ["assets/imgs/tiananmen_tankman.jpeg", ]} ],
+            [{"text": "Có gì ngoài 2 con mèo?", "files": ["assets/imgs/two_cats.jpeg", ]} ],
+            [{"text": "Biển báo nói gì?", "files": ["assets/imgs/cau_oo.jpeg", ]} ],
+            [{"text": "Đây là món gì và hướng dẫn cách làm.", "files": ["assets/imgs/banhmy.jpeg", ]} ],
+            [{"text": "Hãy hướng dẫn nấu món này.", "files": ["assets/imgs/cach-nau-pho-bo-nam-dinh.jpeg", ]} ],
+            [{"text": "Bức tường nói gì?", "files": ["assets/imgs/camdaibay.jpeg", ]} ],
+            [{"text": "Công thức này là gì", "files": ["assets/imgs/eistein_field_equation.png", ]} ],
+            [{"text": "What is this formula about?", "files": ["assets/imgs/eistein_field_equation.png", ]} ],
+            [{"text": "Hãy tìm góc còn lại.", "files": ["assets/imgs/triangle_find_angle.png", ]} ],
+            [{"text": "Đây là đâu?", "files": ["assets/imgs/seattle_space_needle.jpeg", ]} ],
+            [{"text": "Describe the image", "files": ["assets/imgs/seal_logo.png", ]} ],
+            # [{"text": "Explain why the sky is blue.", None,} ],
+            [{"text": "Hãy giải thích thuyết tương đối rộng.", "files": []},],
+            [{"text": "Hãy giải thích vấn đề P vs NP.", "files": []},],
+            [{"text": "Explain general relativity.", "files": []},],
+            [{"text": 'Vừa gà vừa chó, bó lại cho tròn, 36 con và 100 chân chẵn. Hỏi có bao nhiêu gà và chó?', "files": []},],
+            [{"text": 'Hôm nay tôi có 5 quả cam. Hôm qua tôi ăn 2 quả. Vậy hôm nay tôi có mấy quả cam?', "files": []},],
+            [{"text": '5 điều bác Hồ dạy là gì?', "files": []},],
+            [{"text": "Tolong bantu saya menulis email ke lembaga pemerintah untuk mencari dukungan finansial untuk penelitian AI.", "files": []},],
+            [{"text": "ຂໍແຈ້ງ 5 ສະຖານທີ່ທ່ອງທ່ຽວໃນນະຄອນຫຼວງວຽງຈັນ", "files": []},],
+            [{"text": 'ငွေကြေးအခက်အခဲကြောင့် ပညာသင်ဆုတောင်းဖို့ တက္ကသိုလ်ကို စာတစ်စောင်ရေးပြီး ကူညီပေးပါ။', "files": []},],
+            [{"text": "Sally has 3 brothers, each brother has 2 sisters. How many sister sally has?", "files": []},],
+            [{"text": "There are 3 killers in a room. Someone enters the room and kills 1 of them. Assuming no one leaves the room. How many killers are left in the room?", "files": []},],
+            [{"text": "Assume the laws of physics on Earth. A small marble is put into a normal cup and the cup is placed upside down on a table. Someone then takes the cup and puts it inside the microwave. Where is the ball now? Explain your reasoning step by step.", "files": []},],
+            [{"text": "Why my parents did not invited me to their weddings?", "files": []},],
+        ]
+    
+    @property
+    def mm_textbox_placeholder(self):
+        return "Type message or upload an image"
+    
+    @property
+    def mm_accept_file_types(self):
+        return ["image"]
+    
+    @property
+    def gradio_fn(self):
+        return vision_chat_response_stream_multiturn_engine
+
+    def create_demo(
+            self, 
+            title: str | None = None, 
+            description: str | None = None, 
+            additional_inputs: List[Any] | None = None,
+            **kwargs
+        ) -> gr.Blocks:
+        system_prompt = kwargs.get("system_prompt", SYSTEM_PROMPT)
+        max_tokens = kwargs.get("max_tokens", MAX_TOKENS)
+        temperature = kwargs.get("temperature", TEMPERATURE)
+        model_name = kwargs.get("model_name", MODEL_NAME)
+        description = description or """Upload an image to ask question about it."""
+
+        assert MultimodalTextbox is not None
+
+        additional_inputs = additional_inputs or [
+            gr.Number(value=temperature, label='Temperature', min_width=20), 
+            gr.Number(value=max_tokens, label='Max-tokens', min_width=20), 
+            gr.Textbox(value=system_prompt, label='System prompt', lines=1),
+            gr.Textbox(value=IMAGE_TOKEN, label='Visual token', lines=1, interactive=IMAGE_TOKEN_INTERACTIVE, min_width=20),
+        ]
+
+
+        demo_chat = MultiModalTextChatInterface(
+            self.gradio_fn,
+            chatbot=gr.Chatbot(
+                label=model_name,
+                bubble_full_width=False,
+                latex_delimiters=[
+                    { "left": "$", "right": "$", "display": False},
+                    { "left": "$$", "right": "$$", "display": True},
+                ],
+                show_copy_button=True,
+                layout="panel" if USE_PANEL else "bubble",
+                height=CHATBOT_HEIGHT,
+            ),
+            # textbox=gr.Textbox(placeholder='Type message', lines=4, max_lines=128, min_width=200),
+            textbox=MultimodalTextbox(
+                placeholder=self.mm_textbox_placeholder, 
+                interactive=True,
+                scale=9,
+                show_label=False,
+                # file_types=["image", '.pdf', '.docx', '.txt'],
+                file_types=self.mm_accept_file_types,
+            ),
+            title=title,
+            description=description,
+            additional_inputs=additional_inputs, 
+            additional_inputs_accordion=gr.Accordion("Additional Inputs", open=False),
+            examples=self.examples,
+            cache_examples=False,
+            css=CSS,
+            fill_height=True,
+        )
+
+        return demo_chat
+
+
+
+@register_demo
+class DocMMChatInterfaceDemo(VisionMMChatInterfaceDemo):
+    """
+    Accept vision image
+    """
+
+    @property
+    def tab_name(self):
+        return "Doc Chat"
+    
+    @property
+    def mm_textbox_placeholder(self):
+        return "Type message or upload a doc file (pdf, docx, txt)"
+    
+    @property
+    def mm_accept_file_types(self):
+        return ['.pdf', '.docx', '.txt']
+
+    @property
+    def examples(self):
+        from pathlib import Path
+        from gradio.data_classes import FileData, GradioModel
+        return [
+            [{"text": "Hãy giải thích thuyết tương đối rộng.", "files": []},],
+            [{"text": "Hãy giải thích vấn đề P vs NP.", "files": []},],
+            [{"text": "Explain general relativity in details.", "files": []},],
+            # [{"text": 'Vừa gà v���a chó, bó lại cho tròn, 36 con và 100 chân chẵn. Hỏi có bao nhiêu gà và chó?', "files": []},],
+            # [{"text": 'Hôm nay tôi có 5 quả cam. Hôm qua tôi ăn 2 quả. Vậy hôm nay tôi có mấy quả cam?', "files": []},],
+            # [{"text": '5 điều bác Hồ dạy là gì?', "files": []},],
+            [{"text": "Tolong bantu saya menulis email ke lembaga pemerintah untuk mencari dukungan finansial untuk penelitian AI.", "files": []},],
+            [{"text": "ຂໍແຈ້ງ 5 ສະຖານທີ່ທ່ອງທ່ຽວໃນນະຄອນຫຼວງວຽງຈັນ", "files": []},],
+            # [{"text": 'ငွေကြေးအခက်အခဲကြောင့် ပညာသင်ဆုတောင်းဖို့ တက္ကသိုလ်ကို စာတစ်စောင်ရေးပြီး ကူညီပေးပါ။', "files": []},],
+            # [{"text": "Sally has 3 brothers, each brother has 2 sisters. How many sister sally has?", "files": []},],
+            # [{"text": "There are 3 killers in a room. Someone enters the room and kills 1 of them. Assuming no one leaves the room. How many killers are left in the room?", "files": []},],
+            # [{"text": "Assume the laws of physics on Earth. A small marble is put into a normal cup and the cup is placed upside down on a table. Someone then takes the cup and puts it inside the microwave. Where is the ball now? Explain your reasoning step by step.", "files": []},],
+            # [{"text": "Why my parents did not invited me to their weddings?", "files": []},],
+        ]
+
+    def create_demo(
+            self, 
+            title: str | None = None, 
+            description: str | None = None, 
+            additional_inputs: List[Any] | None = None,
+            **kwargs
+    ) -> gr.Blocks:
+        system_prompt = kwargs.get("system_prompt", SYSTEM_PROMPT)
+        max_tokens = kwargs.get("max_tokens", MAX_TOKENS)
+        temperature = kwargs.get("temperature", TEMPERATURE)
+        additional_inputs = additional_inputs or [
+            gr.Number(value=temperature, label='Temperature', min_width=20), 
+            gr.Number(value=max_tokens, label='Max-tokens', min_width=20), 
+            gr.Textbox(value=system_prompt, label='System prompt', lines=1),
+        ]
+        return super().create_demo(title, description, additional_inputs, **kwargs)
+    
+    @property
+    def gradio_fn(self):
+        # return vision_chat_response_stream_multiturn_engine
+        return doc_chat_response_stream_multiturn_engine
+    
+
+
+
+
+@register_demo
+class VisionDocMMChatInterfaceDemo(VisionMMChatInterfaceDemo):
+    """
+    Accept vision image
+    """
+
+    @property
+    def tab_name(self):
+        return "Vision Doc Chat"
+    
+    @property
+    def mm_textbox_placeholder(self):
+        return "Type message or upload an image or doc file (pdf, docx, txt)"
+    
+    @property
+    def mm_accept_file_types(self):
+        return ['image', '.pdf', '.docx', '.txt']
+    
+    @property
+    def gradio_fn(self):
+        # return vision_chat_response_stream_multiturn_engine
+        return vision_doc_chat_response_stream_multiturn_engine
+    
+
+
+
+

multipurpose_chatbot/demos/multimodal_chat_interface.py

@@ -1,4 +1,14 @@
-import spaces
+try:
+    import spaces
+    def maybe_spaces_gpu(fn):
+        fn = spaces.GPU(fn)
+        return fn
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
+    def maybe_spaces_gpu(fn):
+        return fn
+    
+
 import os
 from gradio.themes import ThemeClass as Theme
 import numpy as np
@@ -904,7 +914,7 @@ def gradio_history_to_vision_doc_conversation_prompt_paths(
     return full_prompt, image_paths, conversations
 
 
-@spaces.GPU
+@maybe_spaces_gpu
 def vision_chat_response_stream_multiturn_engine(
     history: List[Tuple[str, str]], 
     temperature: float, 
@@ -957,7 +967,7 @@ def vision_chat_response_stream_multiturn_engine(
         yield response, num_tokens
 
 
-@spaces.GPU
+@maybe_spaces_gpu
 def doc_chat_response_stream_multiturn_engine(
     history: List[Tuple[str, str]], 
     temperature: float, 
@@ -1008,7 +1018,7 @@ def doc_chat_response_stream_multiturn_engine(
 
 
 
-@spaces.GPU
+@maybe_spaces_gpu
 def vision_doc_chat_response_stream_multiturn_engine(
     history: List[Tuple[str, str]], 
     temperature: float, 

multipurpose_chatbot/demos/text_completion.py

@@ -1,4 +1,13 @@
-import spaces
+try:
+    import spaces
+    def maybe_spaces_gpu(fn):
+        fn = spaces.GPU(fn)
+        return fn
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
+    def maybe_spaces_gpu(fn):
+        return fn
+
 import os
 from gradio.themes import ThemeClass as Theme
 import numpy as np
@@ -62,7 +71,7 @@ from ..configs import (
 
 from ..globals import MODEL_ENGINE
 
-@spaces.GPU
+@maybe_spaces_gpu
 def generate_text_completion_stream_engine(
     message: str, 
     temperature: float, 

multipurpose_chatbot/engines/sealmmm_engine.py

@@ -1,7 +1,10 @@
 # from transformers_stream_generator import init_stream_support
 # init_stream_support()
 
-import spaces
+try:
+    import spaces
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
 import os
 import numpy as np
 import argparse

multipurpose_chatbot/engines/transformers_engine.py

@@ -1,5 +1,8 @@
 
-import spaces
+try:
+    import spaces
+except ModuleNotFoundError:
+    print(f'Cannot import hf `spaces` with `import spaces`.')
 import os
 import numpy as np
 import argparse