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# References for vLLM:
# https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/openai/completion/protocol.py
import streamlit as st
import requests
import json
placeholders_to_try = '#.?!@$%^&*()_+-=~`|;:"<>,./\\'
def show_token(token: str, escape_markdown=True) -> str:
token_display = token.replace('\n', '↵').replace('\t', '⇥')
if escape_markdown:
for c in "\\`*_{}[]()#+-.!":
token_display = token_display.replace(c, "\\" + c)
return token_display
def show_internals():
if 'messages' not in st.session_state or st.button("Start a new conversation"):
st.session_state['messages'] = [{"role": "user", "content": ""}]
st.session_state['msg_in_progress'] = ""
st.session_state['placeholder_token'] = placeholders_to_try[0]
messages = st.session_state.messages
def rewind_to(i):
st.session_state.messages = st.session_state.messages[:i+1]
st.session_state['msg_in_progress'] = st.session_state.messages[-1]['content']
for i, message in enumerate(st.session_state.messages[:-1]):
with st.chat_message(message["role"]):
st.markdown(message["content"])
st.button("Edit", on_click=rewind_to, args=(i,), key=f"rewind_to_{i}")
# Display message-in-progress in chat message container
last_role = messages[-1]["role"]
with st.chat_message(last_role):
label = "Your message" if last_role == "user" else "Assistant response"
msg_in_progress = st.text_area(label, placeholder="Clicking the buttons below will update this field. You can also edit it directly; press Ctrl+Enter to apply changes.", height=300, key="msg_in_progress")
if msg_in_progress is None:
msg_in_progress = ""
# Unfortunately chat templates include things like this:
# {%- set content = render_content(message.content, true)|trim %}
# so we can't include leading or trailing whitespace.
# Can't do much about leading whitespace, but we can at least allow trailing whitespace by including a special token for it.
# Unfortunately there's no single token that never gets joined with any other one, so we have to try a few different ones and see which one actually gets separated out by the tokenizer.
messages[-1]['content'] = msg_in_progress + st.session_state.placeholder_token
st.write(messages)
def send_message():
other_role = "assistant" if last_role == "user" else "user"
st.session_state['messages'].append({"role": other_role, "content": ""})
st.session_state['msg_in_progress'] = ""
st.button("Send", on_click=send_message)
token_ids_req = requests.post(
"https://vllm.thoughtful-ai.com/tokenize",
headers={"Content-Type": "application/json"},
json={
"model": "Qwen/Qwen3.5-9B",
"messages": messages,
"continue_final_message": True,
"add_generation_prompt": False,
"return_token_strs": True,
}
)
token_ids_req = token_ids_req.json()
token_ids = token_ids_req['tokens']
token_strs = token_ids_req['token_strs']
# completion given prompt token ids
logprobs_request = requests.post(
"https://vllm.thoughtful-ai.com/v1/completions",
headers={"Content-Type": "application/json"},
json={
"model": "Qwen/Qwen3.5-9B",
"prompt": token_ids,
"max_tokens": 2,
"logprobs": 5,
"echo": True,
}
)
logprobs_request = logprobs_request.json()
complete_text = logprobs_request['choices'][0]['text']
logprobs_part = logprobs_request['choices'][0]['logprobs']
logprobs = []
for i in range(len(token_ids)):
if i == 0:
# first token has no logprobs, but show the token string.
logprobs.append({
"token": logprobs_part['tokens'][0],
"logprobs": None
})
continue
top_logprobs = logprobs_part['top_logprobs'][i]
logprobs.append({
"token": logprobs_part['tokens'][i],
"logprobs": {tok: logprob for tok, logprob in top_logprobs.items()}
})
#st.write(logprobs_part)
if logprobs and logprobs[-1]['token'] == st.session_state.placeholder_token:
logprobs[-1]['token'] = None
# remove the placeholder token logprobs, since they aren't meaningful
logprobs[-1]['logprobs'] = {tok: logprob for tok, logprob in logprobs[-1]['logprobs'].items() if tok != st.session_state.placeholder_token}
else:
st.warning("Expected the last token to be the placeholder token, but it wasn't. Logprobs may not display correctly.")
if st.button("Try a different placeholder token"):
current_index = placeholders_to_try.index(st.session_state.placeholder_token)
next_index = (current_index + 1) % len(placeholders_to_try)
st.session_state.placeholder_token = placeholders_to_try[next_index]
st.rerun()
#st.write(last_token_logprobs)
st.write("Conversation so far as tokens (click to show logprobs):")
logprobs_component(logprobs)
def logprobs_component(logprobs):
# logprobs is a list of tokens:
# {
# "token": "the",
# "logprobs": [{"the": -0.1, "a": -0.2, ...}]
# }
import html, json
html_out = ''
for i, entry in enumerate(logprobs):
token = entry['token']
if token is not None:
token_to_show = html.escape(show_token(token, escape_markdown=False))
else:
token_to_show = html.escape("[____]")
html_out += f'<span style="border: 1px solid black; display: inline-block;" onclick="showLogprobs({i})" title="Click to show logprobs for this token">{token_to_show}</span>'
show_logprob_js = '''
const makeElt = (tag, attrs, children) => {
const elt = document.createElement(tag);
for (const [attr, val] of Object.entries(attrs)) {
elt.setAttribute(attr, val);
}
for (const child of children) {
if(typeof child === 'string') {
elt.appendChild(document.createTextNode(child));
} else {
elt.appendChild(child);
}
}
return elt;
}
function escapeToken(token) {
return token.replace(/\\n/g, '↵').replace(/\\t/g, '⇥');
}
function showLogprobs(i) {
const logprobs = allLogprobs[i].logprobs;
const container = document.getElementById('logprobs-display');
container.innerHTML = '';
container.appendChild(makeElt('ul', {}, Object.entries(logprobs).map(([token, logprob]) => makeElt('li', {}, `${escapeToken(token)}: ${Math.exp(logprob)}`))));
}
'''
html_out = f"""
<style>
p.logprobs-container {{
background: white;
line-height: 1.5;
}}
p.logprobs-container > span {{
position: relative;
padding: 2px 1px;
border-radius: 3px;
}}
</style>
<p class="logprobs-container">{html_out}</p>
<div id="logprobs-display"></div>
<script>allLogprobs = {json.dumps(logprobs)};
{show_logprob_js}
showLogprobs(allLogprobs.length - 1);
</script>
"""
import streamlit.components.v1 as components
return components.html(html_out, height=300, scrolling=True)
show_internals()