LLM4SciLit / src /llm4scilit_gradio_interface.py
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"""
This file defines a useful high-level abstraction to build Gradio chatbots: ChatInterface.
"""
from __future__ import annotations
import inspect
from typing import AsyncGenerator, Callable
import anyio
from gradio_client import utils as client_utils
from gradio_client.documentation import document, set_documentation_group
from gradio.blocks import Blocks
from gradio.components import (
Button,
Chatbot,
IOComponent,
Markdown,
State,
Textbox,
get_component_instance,
)
from gradio.events import Dependency, EventListenerMethod, on
from gradio.helpers import create_examples as Examples # noqa: N812
from gradio.layouts import Accordion, Column, Group, Row
from gradio.themes import ThemeClass as Theme
from gradio.utils import SyncToAsyncIterator, async_iteration
set_documentation_group("chatinterface")
@document()
class LLM4SciLitChatInterface(Blocks):
"""
ChatInterface is Gradio's high-level abstraction for creating chatbot UIs, and allows you to create
a web-based demo around a chatbot model in a few lines of code. Only one parameter is required: fn, which
takes a function that governs the response of the chatbot based on the user input and chat history. Additional
parameters can be used to control the appearance and behavior of the demo.
Example:
import gradio as gr
def echo(message, history):
return message
demo = gr.ChatInterface(fn=echo, examples=["hello", "hola", "merhaba"], title="Echo Bot")
demo.launch()
Demos: chatinterface_random_response, chatinterface_streaming_echo
Guides: creating-a-chatbot-fast, sharing-your-app
"""
def __init__(
self,
fn: Callable,
*,
chatbot: Chatbot | None = None,
textbox: Textbox | None = None,
additional_inputs: str | IOComponent | list[str | IOComponent] | None = None,
additional_inputs_accordion_name: str = "Additional Inputs",
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,
analytics_enabled: bool | None = None,
submit_btn: str | None | Button = "Submit",
stop_btn: str | None | Button = "Stop",
retry_btn: str | None | Button = "πŸ”„ Retry",
undo_btn: str | None | Button = "↩️ Undo",
clear_btn: str | None | Button = "πŸ—‘οΈ Clear",
autofocus: 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: the label of the accordion to use for additional inputs, 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 or path to custom css file to use with interface.
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.
"""
super().__init__(
analytics_enabled=analytics_enabled,
mode="chat_interface",
css=css,
title=title or "Gradio",
theme=theme,
)
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] = []
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 = []
self.additional_inputs_accordion_name = additional_inputs_accordion_name
self.additional_outputs = []
with self:
if title:
Markdown(
f"<h1 style='text-align: center; margin-bottom: 1rem'>{self.title}</h1>"
)
if description:
Markdown(description)
with Row():
with Column(variant="panel", scale=1):
if chatbot:
self.chatbot = chatbot.render()
else:
self.chatbot = Chatbot(label="Chatbot")
with Group():
with Row():
if textbox:
textbox.container = False
textbox.show_label = False
self.textbox = textbox.render()
else:
self.textbox = Textbox(
container=False,
show_label=False,
label="Message",
placeholder="Type a message...",
scale=7,
autofocus=autofocus,
)
if submit_btn:
if isinstance(submit_btn, Button):
submit_btn.render()
elif isinstance(submit_btn, str):
submit_btn = Button(
submit_btn,
variant="primary",
scale=1,
min_width=150,
)
else:
raise ValueError(
f"The submit_btn parameter must be a gr.Button, string, or None, not {type(submit_btn)}"
)
if stop_btn:
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=1,
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([submit_btn, stop_btn])
with Row():
for btn in [retry_btn, undo_btn, clear_btn]:
if btn:
if isinstance(btn, Button):
btn.render()
elif isinstance(btn, str):
btn = Button(btn, variant="secondary")
else:
raise ValueError(
f"All the _btn parameters must be a gr.Button, string, or None, not {type(btn)}"
)
self.buttons.append(btn)
self.fake_api_btn = Button("Fake API", visible=False)
self.fake_response_textbox = Textbox(
label="Response", visible=False
)
(
self.submit_btn,
self.stop_btn,
self.retry_btn,
self.undo_btn,
self.clear_btn,
) = self.buttons
with Column(variant="panel", scale=2):
for i in range(4):
self.additional_outputs.append(
Textbox(
interactive=False,
label=f"Document {i+1}"
)
)
if examples:
if self.is_generator:
examples_fn = self._examples_stream_fn
else:
examples_fn = self._examples_fn
self.examples_handler = Examples(
examples=examples,
inputs=[self.textbox] + self.additional_inputs,
outputs=self.chatbot,
fn=examples_fn,
)
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_name, open=False):
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._setup_events()
self._setup_api()
def _setup_events(self) -> None:
submit_fn = self._stream_fn if self.is_generator else self._submit_fn
submit_triggers = (
[self.textbox.submit, self.submit_btn.click]
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,
)
.then(
submit_fn,
[self.saved_input, self.chatbot_state] + self.additional_inputs,
[self.chatbot, self.chatbot_state] + self.additional_outputs,
api_name=False,
)
)
self._setup_stop_events(submit_triggers, submit_event)
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,
)
.then(
submit_fn,
[self.saved_input, self.chatbot_state] + self.additional_inputs,
[self.chatbot, self.chatbot_state],
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],
api_name=False,
queue=False,
).then(
lambda x: x,
[self.saved_input],
[self.textbox],
api_name=False,
queue=False,
)
if self.clear_btn:
self.clear_btn.click(
lambda: ([], [], None),
None,
[self.chatbot, self.chatbot_state, self.saved_input],
queue=False,
api_name=False,
)
def _setup_stop_events(
self, event_triggers: list[EventListenerMethod], event_to_cancel: Dependency
) -> None:
if self.stop_btn and self.is_generator:
if self.submit_btn:
for event_trigger in event_triggers:
event_trigger(
lambda: (
Button.update(visible=False),
Button.update(visible=True),
),
None,
[self.submit_btn, self.stop_btn],
api_name=False,
queue=False,
)
event_to_cancel.then(
lambda: (Button.update(visible=True), Button.update(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.update(visible=True),
None,
[self.stop_btn],
api_name=False,
queue=False,
)
event_to_cancel.then(
lambda: Button.update(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,
)
def _setup_api(self) -> None:
api_fn = self._api_stream_fn if self.is_generator else self._api_submit_fn
self.fake_api_btn.click(
api_fn,
[self.textbox, self.chatbot_state] + self.additional_inputs,
[self.textbox, self.chatbot_state],
api_name="chat",
)
def _clear_and_save_textbox(self, message: str) -> tuple[str, str]:
return "", message
def _display_input(
self, message: str, history: list[list[str | None]]
) -> tuple[list[list[str | None]], list[list[str | None]]]:
history.append([message, None])
return history, history
async def _submit_fn(
self,
message: str,
history_with_input: list[list[str | None]],
*args,
) -> tuple[list[list[str | None]], list[list[str | None]]]:
history = history_with_input[:-1]
if self.is_async:
[response, *other_outputs] = await self.fn(message, history, *args)
else:
[response, *other_outputs] = await anyio.to_thread.run_sync(
self.fn, message, history, *args, limiter=self.limiter
)
history.append([message, response])
return history, history, *other_outputs
async def _stream_fn(
self,
message: str,
history_with_input: list[list[str | None]],
*args,
) -> AsyncGenerator:
history = history_with_input[:-1]
if self.is_async:
generator = self.fn(message, history, *args)
else:
generator = await anyio.to_thread.run_sync(
self.fn, message, history, *args, limiter=self.limiter
)
generator = SyncToAsyncIterator(generator, self.limiter)
try:
first_response = await async_iteration(generator)
update = history + [[message, first_response]]
yield update, update
except StopIteration:
update = history + [[message, None]]
yield update, update
async for response in generator:
update = history + [[message, response]]
yield update, update
async def _api_submit_fn(
self, message: str, history: list[list[str | None]], *args
) -> tuple[str, list[list[str | None]]]:
if self.is_async:
response = await self.fn(message, history, *args)
else:
response = await anyio.to_thread.run_sync(
self.fn, message, history, *args, limiter=self.limiter
)
history.append([message, response])
return response, history
async def _api_stream_fn(
self, message: str, history: list[list[str | None]], *args
) -> AsyncGenerator:
if self.is_async:
generator = self.fn(message, history, *args)
else:
generator = await anyio.to_thread.run_sync(
self.fn, message, history, *args, limiter=self.limiter
)
generator = SyncToAsyncIterator(generator, self.limiter)
try:
first_response = await async_iteration(generator)
yield first_response, history + [[message, first_response]]
except StopIteration:
yield None, history + [[message, None]]
async for response in generator:
yield response, history + [[message, response]]
async def _examples_fn(self, message: str, *args) -> list[list[str | None]]:
if self.is_async:
response = await self.fn(message, [], *args)
else:
response = await anyio.to_thread.run_sync(
self.fn, message, [], *args, limiter=self.limiter
)
return [[message, response]]
async def _examples_stream_fn(
self,
message: str,
*args,
) -> AsyncGenerator:
if self.is_async:
generator = self.fn(message, [], *args)
else:
generator = await anyio.to_thread.run_sync(
self.fn, message, [], *args, limiter=self.limiter
)
generator = SyncToAsyncIterator(generator, self.limiter)
async for response in generator:
yield [[message, response]]
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 = ""
return history, message or "", history