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Running on Zero
Running on Zero
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917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 | import os
import re
from collections.abc import Iterator
from pathlib import Path
from threading import Thread
PREVIEW = os.getenv("TWIL_UI_PREVIEW") == "1"
if not PREVIEW:
import spaces
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
else:
class spaces: # type: ignore[no-redef]
@staticmethod
def GPU(duration=None, **kwargs):
def decorator(fn):
return fn
return decorator
import gradio as gr
MODEL_ID = "webAI-Official/TwIL-LM3"
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "8192"))
ASSETS = Path(__file__).resolve().parent / "brand"
AVATAR = ASSETS / "avatar.svg"
THINK_OPEN = chr(60) + "think" + chr(62)
THINK_CLOSE = chr(60) + chr(47) + "think" + chr(62)
_THINK_RE = re.compile(
re.escape(THINK_OPEN) + r".*?(" + re.escape(THINK_CLOSE) + r"|$)",
re.DOTALL,
)
SYSTEM_PROMPT = (
"You are TwIL, a formal-logic reasoning model created by webAI Intelligence Lab. "
"You specialise in entailment, first-order logic, semantic parsing, Lean, and proof critique. "
f"Work through the problem in a {THINK_OPEN} block, then give a concise, precise answer."
)
CHIPS = [
(
"Analyze an argument",
"Analyze this argument: identify the premises and the conclusion, say whether it is valid, and name any fallacy.\n\n",
),
(
"Check an entailment",
"Do these premises entail the conclusion? Give a formal proof or a counterexample.\n\nPremise 1: \nPremise 2: \nConclusion: ",
),
(
"Translate to FOL",
"Translate into first-order logic: Every student who studies hard passes at least one exam.",
),
]
SHOWCASE_TEMPLATE = (
"Analyze this argument: extract the premises and the conclusion, translate them "
"into first-order logic, state whether the argument is valid, and name any fallacy.\n\n"
'Argument: "{argument}"'
)
SHOWCASE = [
{
"kicker": "Viral tweet",
"quote": "The streets are wet this morning, and rain always makes the streets wet. So it obviously rained last night.",
"hint": "Can wet streets prove rain?",
},
{
"kicker": "School board speech",
"quote": "If we let students retake this one exam, soon they will demand to retake every exam, and before long no grade at this school will mean anything.",
"hint": "Does one retake doom every grade?",
},
{
"kicker": "Supplement ad",
"quote": "Our formula is 100% natural, and nature knows best. That means it is completely safe for your body.",
"hint": "Does natural imply safe?",
},
{
"kicker": "Campaign rally",
"quote": "Either you support this bill or you don't care about public safety. You oppose the bill, so you don't care about public safety.",
"hint": "Are those really the only options?",
},
{
"kicker": "Toothpaste commercial",
"quote": "4 out of 5 dentists we surveyed recommend SparkleDent, and experts know best. You should switch to SparkleDent today.",
"hint": "What is the survey hiding?",
},
{
"kicker": "HR policy memo",
"quote": "Every employee who completes the security training receives a certificate. Sam completed the security training. Therefore Sam receives a certificate.",
"hint": "One of these six actually holds up.",
},
]
SHOWCASE_INTRO = """
<div class="twil-showcase-intro">
<h2>Can TwIL spot the flaw?</h2>
<p>Six arguments from the wild. One click and TwIL extracts the premises, translates
them to first-order logic, and rules on validity. Five are broken — one holds up.</p>
</div>
"""
def _card_html(case: dict) -> str:
return (
'<div class="twil-card-body">'
f'<div class="twil-card-kicker">{case["kicker"]}</div>'
f'<div class="twil-card-quote">“{case["quote"]}”</div>'
f'<div class="twil-card-hint">{case["hint"]}</div>'
"</div>"
)
WAITLIST_URL = "https://www.webai.com/waitlist"
HEADER = f"""
<div class="twil-header">
<img class="twil-mark" src="/gradio_api/file=brand/AppiCon.svg" alt="webAI" />
<div class="twil-header-copy">
<div class="twil-wordmark">webAI</div>
<div class="twil-product">TwIL-LM3 · Intelligence Lab</div>
</div>
<a class="twil-cta twil-cta-header" href="{WAITLIST_URL}" target="_blank" rel="noopener">Get early access</a>
</div>
"""
HEAD = """
<script>
document.addEventListener("keydown", (e) => {
if (e.key !== "Enter" || e.shiftKey || e.isComposing) return;
const ta = document.querySelector("#twil-input textarea");
if (!ta || e.target !== ta) return;
e.preventDefault();
e.stopPropagation();
document.querySelector("#send-btn")?.click();
}, true);
</script>
"""
PLACEHOLDER = f"""
<div class="twil-empty">
<img class="twil-cube" src="/gradio_api/file=brand/webai-cube-256.webp" alt="" />
<h1>What should we work on?</h1>
<p>TwIL-LM3 is webAI's formal-logic model — entailment, FOL, Lean, rule induction.</p>
<div class="twil-waitlist">
<p>TwIL and the full family of webAI models are coming to the webAI app.
Be the first to try expert intelligence on everyday devices.</p>
<a class="twil-cta" href="{WAITLIST_URL}" target="_blank" rel="noopener">Join the waitlist</a>
</div>
</div>
"""
CSS = """
:root {
--weba-canvas: #f4f4f4;
--weba-fg: #161616;
--weba-muted: #737373;
--weba-secondary: #e8e8e8;
--weba-border: rgba(22, 22, 22, 0.1);
--weba-composer: #ffffff;
--weba-primary: #232323;
--weba-primary-fg: #fafafa;
}
.dark {
--weba-canvas: #232323;
--weba-fg: #fafafa;
--weba-muted: #a8a8a8;
--weba-secondary: #323232;
--weba-border: rgba(255, 255, 255, 0.1);
--weba-composer: #161616;
--weba-primary: #e8e8e8;
--weba-primary-fg: #232323;
}
* { box-shadow: none !important; text-shadow: none !important; }
html, body, #root, .gradio-container, .gradio-container > .main,
.gradio-container .contain, .fillable,
.gradio-container .column, .gradio-container .row, .contain, .wrapper {
background: var(--weba-canvas) !important;
box-shadow: none !important;
filter: none !important;
}
/* Never paint over content while a job is running: the status tracker
overlay must stay transparent or the chat looks blank mid-generation. */
.gradio-container [data-testid="status-tracker"],
.gradio-container .wrap.default {
background: transparent !important;
}
html, body, .gradio-container, .gradio-container > .main, .fillable,
.contain, .app {
height: 100% !important;
min-height: 100vh !important;
max-height: 100vh !important;
max-width: none !important;
margin: 0 !important;
overflow: hidden !important;
}
.gradio-container, .main.fillable, .contain {
display: flex !important;
flex-direction: column !important;
padding: 0 !important;
}
.gradio-container {
font-family: ui-sans-serif, system-ui, -apple-system, "Segoe UI", sans-serif !important;
color: var(--weba-fg) !important;
}
footer, .footer, .built-with, .settings, .settings-bar, .show-api,
.show-api-divider, .divider {
display: none !important;
}
#app-shell {
flex: 1 1 auto !important;
height: 100% !important;
max-height: 100% !important;
min-height: 0 !important;
display: flex !important;
flex-direction: column !important;
padding: 16px 24px 12px !important;
box-sizing: border-box !important;
overflow: hidden !important;
background: var(--weba-canvas) !important;
}
#app-shell > .gap, #app-shell > div {
background: transparent !important;
flex-grow: 0 !important;
height: auto !important;
min-height: 0 !important;
}
#app-shell > #twil-chat,
#app-shell > .block:has(#twil-chat),
#app-shell > div:has(#twil-chat) {
flex: 1 1 auto !important;
min-height: 0 !important;
height: auto !important;
}
.twil-header {
display: flex;
align-items: center;
gap: 12px;
padding: 4px 0 8px;
flex-shrink: 0;
}
.twil-mark { width: 28px; height: 28px; border-radius: 6px; }
.twil-wordmark { font-weight: 600; font-size: 15px; letter-spacing: -0.02em; line-height: 1.2; color: var(--weba-fg); }
.twil-product { font-size: 12px; color: var(--weba-muted); line-height: 1.3; }
.twil-cta {
display: inline-flex;
align-items: center;
height: 34px;
padding: 0 18px;
border-radius: 999px;
background: var(--weba-primary);
color: var(--weba-primary-fg) !important;
font-size: 13px;
font-weight: 500;
text-decoration: none !important;
border: none;
white-space: nowrap;
transition: opacity 0.15s ease;
}
.twil-cta:hover { opacity: 0.85; }
.twil-cta-header {
/* Keep clear of the floating HF Space pill in the top-right corner */
margin-left: 20px;
height: 30px;
padding: 0 14px;
font-size: 12px;
}
.twil-waitlist {
margin-top: 28px;
display: flex;
flex-direction: column;
align-items: center;
gap: 12px;
}
.twil-waitlist p {
margin: 0;
max-width: 30rem;
font-size: 13px;
line-height: 1.5;
color: var(--weba-muted);
}
.twil-empty {
height: 100%;
min-height: 280px;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
text-align: center;
padding: 12px;
}
.twil-cube { width: 96px; height: 96px; margin-bottom: 24px; }
.twil-empty h1 {
font-size: 28px;
font-weight: 500;
letter-spacing: -0.03em;
margin: 0 0 8px;
color: var(--weba-fg);
}
.twil-empty p {
margin: 0;
max-width: 28rem;
font-size: 15px;
line-height: 1.5;
color: var(--weba-muted);
}
#twil-chat, #twil-chat > .wrapper, #twil-chat .bubble-wrap,
#twil-chat .message-wrap, #twil-chat .placeholder-content {
background: transparent !important;
border: none !important;
box-shadow: none !important;
flex: 1 1 auto !important;
min-height: 0 !important;
}
#twil-chat {
max-width: 768px !important;
width: 100% !important;
margin: 0 auto !important;
flex: 1 1 auto !important;
}
#twil-chat .message.user, #twil-chat .user, #twil-chat .bubble.user {
background: var(--weba-secondary) !important;
color: var(--weba-fg) !important;
border: none !important;
box-shadow: none !important;
border-radius: 12px !important;
}
#twil-chat .message.bot, #twil-chat .bot, #twil-chat .bubble.bot {
background: transparent !important;
border: none !important;
box-shadow: none !important;
}
#twil-chat [aria-label="Delete"], #twil-chat [aria-label="Copy"],
#twil-chat [aria-label="Share"], #twil-chat .message-buttons {
display: none !important;
}
#twil-chat details, #twil-chat .thought, #twil-chat .md.thought {
background: transparent !important;
border: none !important;
box-shadow: none !important;
color: var(--weba-muted) !important;
}
#composer-row {
max-width: 768px !important;
width: 100% !important;
margin: 8px auto 0 !important;
display: flex !important;
flex-direction: row !important;
flex-wrap: nowrap !important;
align-items: center !important;
gap: 10px !important;
flex: 0 0 auto !important;
min-height: 56px !important;
background: transparent !important;
}
#composer-row > .block:has(#twil-input),
#twil-input {
flex: 1 1 0% !important;
min-width: 0 !important;
width: auto !important;
height: 52px !important;
min-height: 52px !important;
max-height: 52px !important;
background: var(--weba-composer) !important;
border: 1px solid var(--weba-border) !important;
border-radius: 999px !important;
box-shadow: none !important;
overflow: hidden !important;
}
#twil-input label,
#twil-input .input-container {
display: flex !important;
align-items: stretch !important;
width: 100% !important;
height: 100% !important;
min-height: 52px !important;
margin: 0 !important;
padding: 0 !important;
border: none !important;
background: transparent !important;
box-sizing: border-box !important;
}
#twil-input textarea,
#twil-input input,
#twil-input .scroll-hide,
#twil-input [data-testid="textbox"] {
display: block !important;
background: transparent !important;
color: var(--weba-fg) !important;
border: none !important;
box-shadow: none !important;
width: 100% !important;
height: 52px !important;
min-height: 52px !important;
max-height: 52px !important;
padding: 16px 18px !important;
font-size: 16px !important;
line-height: 20px !important;
overflow-y: auto !important;
overflow-x: hidden !important;
resize: none !important;
white-space: pre-wrap !important;
field-sizing: fixed !important;
pointer-events: auto !important;
}
#twil-input button, #twil-input .show-count, #twil-input .icon-button,
#twil-input .sr-only, #twil-input span[data-testid="block-info"] {
display: none !important;
}
#composer-row > .form,
#composer-row > .block:has(#send-btn) {
flex: 0 0 40px !important;
width: 40px !important;
min-width: 40px !important;
max-width: 40px !important;
background: transparent !important;
border: none !important;
padding: 0 !important;
box-shadow: none !important;
}
#send-btn {
flex: 0 0 40px !important;
width: 40px !important;
min-width: 40px !important;
max-width: 40px !important;
height: 40px !important;
border-radius: 999px !important;
background: var(--weba-secondary) !important;
color: var(--weba-fg) !important;
border: none !important;
box-shadow: none !important;
align-self: center !important;
padding: 0 !important;
}
#chips-row {
max-width: 768px !important;
width: 100% !important;
margin: 0 auto !important;
display: flex !important;
flex-wrap: wrap !important;
justify-content: center !important;
gap: 8px !important;
flex-shrink: 0 !important;
background: transparent !important;
padding: 4px 0 8px !important;
}
#chips-row button {
height: 32px !important;
padding: 0 14px !important;
border-radius: 999px !important;
border: 1px solid var(--weba-border) !important;
background: transparent !important;
color: var(--weba-muted) !important;
box-shadow: none !important;
font-size: 13px !important;
font-weight: 400 !important;
}
#chips-row button:hover {
background: var(--weba-secondary) !important;
color: var(--weba-fg) !important;
}
@keyframes twil-pulse {
0%, 100% { opacity: 0.4; }
50% { opacity: 1; }
}
#twil-chat .pending, #twil-chat [data-status="pending"] {
animation: twil-pulse 1.1s ease-in-out infinite;
}
#params-box,
#params-box.block,
#params-box .wrap,
#params-box .styler,
#params-box .gap,
#accordion-content {
max-width: 768px !important;
margin: 4px auto 0 !important;
background: transparent !important;
border: none !important;
box-shadow: none !important;
flex: 0 0 auto !important;
flex-grow: 0 !important;
height: auto !important;
min-height: 0 !important;
max-height: none !important;
overflow: visible !important;
}
#params-box .label-wrap, #params-box .icon {
color: var(--weba-muted) !important;
font-size: 12px !important;
box-shadow: none !important;
background: transparent !important;
border: none !important;
}
.twil-disclaimer {
margin: 8px 0 0;
text-align: center;
font-size: 11px;
color: var(--weba-muted);
flex-shrink: 0;
}
/* Tabs shell: keep the chat layout filling the viewport */
#twil-tabs {
flex: 1 1 auto !important;
min-height: 0 !important;
display: flex !important;
flex-direction: column !important;
background: transparent !important;
border: none !important;
box-shadow: none !important;
}
#twil-tabs > .tab-wrapper,
#twil-tabs .tab-container,
#twil-tabs .tab-nav {
flex: 0 0 auto !important;
background: transparent !important;
border: none !important;
box-shadow: none !important;
justify-content: center !important;
}
#twil-tabs .tab-container button,
#twil-tabs .tab-nav button {
background: transparent !important;
border: none !important;
border-bottom: 2px solid transparent !important;
border-radius: 0 !important;
box-shadow: none !important;
color: var(--weba-muted) !important;
font-size: 13px !important;
padding: 6px 14px !important;
}
#twil-tabs .tab-container button.selected,
#twil-tabs .tab-nav button.selected {
color: var(--weba-fg) !important;
border-bottom-color: var(--weba-fg) !important;
}
#twil-tabs .tabitem {
flex: 1 1 auto !important;
min-height: 0 !important;
background: transparent !important;
border: none !important;
box-shadow: none !important;
padding: 0 !important;
}
#tab-chat > .gap, #tab-chat > .column,
#tab-chat, #tab-chat .column:has(> div > #twil-chat) {
height: 100% !important;
min-height: 0 !important;
}
#tab-chat > .gap, #tab-chat > .column {
display: flex !important;
flex-direction: column !important;
}
#tab-chat .block:has(#twil-chat),
#tab-chat div:has(> #twil-chat) {
flex: 1 1 auto !important;
min-height: 0 !important;
height: auto !important;
}
#tab-showcase {
overflow-y: auto !important;
}
/* Showcase cards */
.twil-showcase-intro {
max-width: 768px;
margin: 8px auto 4px;
text-align: center;
}
.twil-showcase-intro h2 {
font-size: 22px;
font-weight: 500;
letter-spacing: -0.02em;
margin: 0 0 6px;
color: var(--weba-fg);
}
.twil-showcase-intro p {
margin: 0 0 8px;
font-size: 14px;
line-height: 1.5;
color: var(--weba-muted);
}
.twil-card-row {
max-width: 900px !important;
width: 100% !important;
margin: 6px auto !important;
display: flex !important;
gap: 12px !important;
align-items: stretch !important;
background: transparent !important;
}
.twil-card {
background: var(--weba-composer) !important;
border: 1px solid var(--weba-border) !important;
border-radius: 16px !important;
box-shadow: none !important;
padding: 16px !important;
gap: 10px !important;
display: flex !important;
flex-direction: column !important;
justify-content: space-between !important;
min-height: 170px !important;
}
.twil-card > * { background: transparent !important; }
.twil-card-kicker {
font-size: 11px;
font-weight: 600;
letter-spacing: 0.06em;
text-transform: uppercase;
color: var(--weba-muted);
margin-bottom: 8px;
}
.twil-card-quote {
font-size: 14px;
line-height: 1.45;
color: var(--weba-fg);
margin-bottom: 8px;
}
.twil-card-hint {
font-size: 12px;
color: var(--weba-muted);
font-style: italic;
}
.twil-card-btn {
height: 32px !important;
border-radius: 999px !important;
border: 1px solid var(--weba-border) !important;
background: var(--weba-secondary) !important;
color: var(--weba-fg) !important;
box-shadow: none !important;
font-size: 13px !important;
font-weight: 500 !important;
align-self: flex-start !important;
padding: 0 16px !important;
width: auto !important;
min-width: 0 !important;
flex: 0 0 auto !important;
}
.twil-card-btn:hover {
background: var(--weba-fg) !important;
color: var(--weba-canvas) !important;
}
"""
THEME = gr.themes.Base(
primary_hue="zinc",
secondary_hue="zinc",
neutral_hue="zinc",
font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"],
radius_size=gr.themes.sizes.radius_lg,
).set(
body_background_fill="#f4f4f4",
body_background_fill_dark="#232323",
body_text_color="#161616",
body_text_color_dark="#fafafa",
background_fill_primary="transparent",
background_fill_primary_dark="transparent",
background_fill_secondary="#e8e8e8",
background_fill_secondary_dark="#323232",
border_color_primary="rgba(22,22,22,0.1)",
border_color_primary_dark="rgba(255,255,255,0.1)",
block_background_fill="transparent",
block_background_fill_dark="transparent",
block_border_width="0px",
block_shadow="none",
block_shadow_dark="none",
shadow_drop="none",
shadow_drop_lg="none",
input_background_fill="#ffffff",
input_background_fill_dark="#161616",
input_border_color="rgba(22,22,22,0.1)",
input_border_color_dark="rgba(255,255,255,0.1)",
input_shadow="none",
button_secondary_background_fill="#e8e8e8",
button_secondary_background_fill_dark="#323232",
button_secondary_text_color="#161616",
button_secondary_text_color_dark="#fafafa",
button_secondary_shadow="none",
)
tokenizer = None
model = None
EOS_TOKEN_ID = None
if not PREVIEW:
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
dtype=torch.bfloat16,
attn_implementation="sdpa",
).to("cuda")
model.eval()
model.generation_config.use_cache = True
EOS_TOKEN_ID = tokenizer.eos_token_id
def _strip_thinking(text: str) -> str:
if not isinstance(text, str):
return ""
return _THINK_RE.sub("", text).strip()
def _parse_think(raw: str) -> tuple[str, str, bool]:
"""Return (think, answer, think_open) from a possibly streaming reply."""
open_idx = raw.find(THINK_OPEN)
if open_idx == -1:
# A partially streamed opening tag is not an answer yet.
if raw.strip() and THINK_OPEN.startswith(raw.strip()):
return "", "", False
return "", raw, False
rest = raw[open_idx + len(THINK_OPEN) :]
close_idx = rest.find(THINK_CLOSE)
before = raw[:open_idx]
if close_idx == -1:
# Hide a partially streamed closing tag at the end of the think block.
for i in range(len(THINK_CLOSE) - 1, 0, -1):
if rest.endswith(THINK_CLOSE[:i]):
rest = rest[:-i]
break
return rest.strip(), before.strip(), True
think = rest[:close_idx].strip()
answer = (before + rest[close_idx + len(THINK_CLOSE) :]).strip()
return think, answer, False
def _gpu_seconds(history, max_new_tokens=1024, *args, **kwargs):
# ZeroGPU adds its own startup overhead on top of this request, and
# anonymous visitors have a small quota — keep the ask modest.
tokens = int(max_new_tokens or 1024)
return min(90, max(25, 10 + tokens // 30))
def _history_for_model(history: list) -> list[dict]:
conversation = [{"role": "system", "content": SYSTEM_PROMPT}]
for msg in history or []:
role = msg.get("role", "user")
meta = msg.get("metadata") or {}
# Only skip thought/tool bubbles; Gradio attaches an empty metadata
# dict to ordinary messages, so a bare truthiness check drops them all.
is_thought = isinstance(meta, dict) and bool(meta.get("title"))
if role == "system" or is_thought:
continue
content = msg.get("content", "")
if isinstance(content, list):
# Gradio 6 sends message content as a list of blocks.
parts = []
for block in content:
if isinstance(block, str):
parts.append(block)
elif isinstance(block, dict):
text = block.get("text") or block.get("content") or ""
if isinstance(text, str) and text:
parts.append(text)
content = "\n".join(parts)
if role == "assistant":
content = _strip_thinking(content)
if content:
conversation.append({"role": role, "content": content})
return conversation
def _stream_tokens(conversation: list[dict], max_new_tokens: int, temperature: float, top_p: float, enable_thinking: bool) -> Iterator[str]:
if PREVIEW:
import time
demo = (
f"{THINK_OPEN}\n"
"Check the premises, then the conclusion. Premise 1 gives Rain -> Wet. "
"Premise 2 observes Wet. Inferring Rain from Wet affirms the consequent, "
"which is invalid. The argument is a classic Barbara syllogism otherwise.\n"
f"{THINK_CLOSE}\n\n"
"Answer: entailment."
)
acc = ""
for ch in demo:
acc += ch
time.sleep(0.02)
yield acc
return
encoded = tokenizer.apply_chat_template(
conversation,
add_generation_prompt=True,
return_tensors="pt",
return_dict=True,
enable_thinking=enable_thinking,
)
input_ids = encoded["input_ids"]
attention_mask = encoded["attention_mask"]
if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
attention_mask = attention_mask[:, -MAX_INPUT_TOKEN_LENGTH:]
gr.Warning(f"Trimmed the conversation to the last {MAX_INPUT_TOKEN_LENGTH} tokens.")
input_ids = input_ids.to(model.device)
attention_mask = attention_mask.to(model.device)
streamer = TextIteratorStreamer(
tokenizer, timeout=30.0, skip_prompt=True, skip_special_tokens=True
)
generate_kwargs = dict(
input_ids=input_ids,
attention_mask=attention_mask,
streamer=streamer,
max_new_tokens=int(max_new_tokens),
num_beams=1,
use_cache=True,
eos_token_id=EOS_TOKEN_ID,
pad_token_id=tokenizer.pad_token_id or EOS_TOKEN_ID,
)
if temperature == 0:
generate_kwargs["do_sample"] = False
else:
generate_kwargs["do_sample"] = True
generate_kwargs["temperature"] = float(temperature)
generate_kwargs["top_p"] = float(top_p)
Thread(target=model.generate, kwargs=generate_kwargs, daemon=True).start()
acc = ""
for text in streamer:
acc += text
yield acc
def queue_message(message, history):
"""Paint the user turn immediately so the GPU wait is not a blank screen."""
message = (message or "").strip()
if not message:
return "", history, gr.skip()
history = [dict(m) if isinstance(m, dict) else m for m in (history or [])]
history.append({"role": "user", "content": message})
history.append(
{
"role": "assistant",
"content": "",
"metadata": {"title": "Logicizing…", "status": "pending"},
}
)
return "", history, gr.update(visible=False)
@spaces.GPU(duration=_gpu_seconds)
def generate_reply(history, max_new_tokens, temperature, top_p, enable_thinking):
history = [dict(m) if isinstance(m, dict) else m for m in (history or [])]
if not any(m.get("role") == "user" for m in history):
yield history
return
conversation = _history_for_model(history)
# Stream only into a bubble at the END of the history. Reaching for any
# older assistant message would overwrite a previous turn in place.
think_msg = None
last = history[-1] if history else None
if (
last is not None
and last.get("role") == "assistant"
and isinstance(last.get("metadata"), dict)
and last["metadata"].get("status") == "pending"
):
think_msg = last
think_msg["content"] = ""
elif last is not None and last.get("role") == "user":
# Gradio strips the empty pending bubble in preprocessing; recreate it.
think_msg = {"role": "assistant", "content": ""}
history.append(think_msg)
else:
# No new user turn (e.g. an empty submit); don't regenerate old answers.
yield history
return
think_msg["metadata"] = {"title": "Logicizing…", "status": "pending"}
yield history
answer_msg = {"role": "assistant", "content": ""}
for raw in _stream_tokens(
conversation, max_new_tokens, temperature, top_p, enable_thinking
):
think, answer, think_open = _parse_think(raw)
if think or think_open:
think_msg["content"] = think
think_msg["metadata"] = {
"title": "Logicizing…" if think_open else "Logic",
"status": "pending" if think_open else "done",
}
if answer:
answer_msg["content"] = answer
if not any(m is answer_msg for m in history):
history.append(answer_msg)
elif not think_open and not think and raw.strip():
answer_msg["content"] = raw.strip()
if not any(m is answer_msg for m in history):
history.append(answer_msg)
elif any(m is answer_msg for m in history):
# A partial tag was mistaken for an answer earlier; retract it.
history.remove(answer_msg)
answer_msg["content"] = ""
yield history
if think_msg["content"]:
think_msg["metadata"] = {"title": "Logic", "status": "done"}
yield history
elif think_msg in history and not think_msg["content"]:
history.remove(think_msg)
yield history
with gr.Blocks(fill_height=True, fill_width=True, elem_id="app-root") as demo:
with gr.Column(elem_id="app-shell"):
gr.HTML(HEADER)
with gr.Tabs(elem_id="twil-tabs") as tabs:
with gr.Tab("Chat", id="chat", elem_id="tab-chat"):
chatbot = gr.Chatbot(
value=[],
placeholder=PLACEHOLDER,
label="",
show_label=False,
layout="bubble",
avatar_images=(None, str(AVATAR) if AVATAR.exists() else None),
allow_tags=["think"],
reasoning_tags=[(THINK_OPEN, THINK_CLOSE)],
buttons=None,
editable=False,
line_breaks=False,
elem_id="twil-chat",
scale=1,
height="100%",
)
with gr.Row(elem_id="chips-row") as chips_row:
chip_btns = [
gr.Button(label, variant="secondary", size="sm", elem_classes=["twil-chip"])
for label, _ in CHIPS
]
with gr.Row(elem_id="composer-row"):
prompt = gr.Textbox(
placeholder="Ask webAI anything…",
show_label=False,
container=False,
lines=2,
max_lines=2,
elem_id="twil-input",
scale=8,
)
send = gr.Button("↑", elem_id="send-btn", scale=0)
with gr.Accordion("Parameters", open=False, elem_id="params-box"):
max_new_tokens = gr.Slider(256, 4096, value=1024, step=256, label="Max new tokens")
temperature = gr.Slider(0, 1.5, value=0, step=0.05, label="Temperature (0 = greedy)")
top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
enable_thinking = gr.Checkbox(value=True, label="Enable thinking")
gr.HTML('<p class="twil-disclaimer">This is AI and it can make mistakes</p>')
with gr.Tab("Showcase", id="showcase", elem_id="tab-showcase"):
gr.HTML(SHOWCASE_INTRO)
card_btns = []
for start in range(0, len(SHOWCASE), 3):
with gr.Row(elem_classes=["twil-card-row"]):
for case in SHOWCASE[start : start + 3]:
with gr.Column(elem_classes=["twil-card"], scale=1, min_width=220):
gr.HTML(_card_html(case))
card_btns.append(
gr.Button("Analyze it", size="sm", elem_classes=["twil-card-btn"])
)
# Lock the composer while a turn is running: overlapping events make the
# finishing stream overwrite the chat with its own stale history.
lockable = [prompt, send, *card_btns]
def _lock():
return [gr.update(interactive=False)] * len(lockable)
def _unlock():
return [gr.update(interactive=True)] * len(lockable)
def _wire(event, prep_fn=None, prep_outputs=None):
chain = event(_lock, None, lockable, show_progress="hidden")
if prep_fn is not None:
chain = chain.then(prep_fn, outputs=prep_outputs, show_progress="hidden")
chain = chain.then(
queue_message,
[prompt, chatbot],
[prompt, chatbot, chips_row],
show_progress="hidden",
).then(
generate_reply,
[chatbot, max_new_tokens, temperature, top_p, enable_thinking],
chatbot,
concurrency_limit=1,
show_progress="hidden",
)
chain.then(_unlock, None, lockable, show_progress="hidden")
_wire(send.click)
_wire(prompt.submit)
for btn, (_, template) in zip(chip_btns, CHIPS):
btn.click(lambda t=template: t, outputs=prompt)
for btn, case in zip(card_btns, SHOWCASE):
case_prompt = SHOWCASE_TEMPLATE.format(argument=case["quote"])
_wire(
btn.click,
prep_fn=lambda p=case_prompt: (p, gr.Tabs(selected="chat")),
prep_outputs=[prompt, tabs],
)
if __name__ == "__main__":
demo.launch(
theme=THEME,
css=CSS,
head=HEAD,
allowed_paths=[str(ASSETS), str(ASSETS.parent)],
ssr_mode=False,
show_error=True,
)
|