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import streamlit as st
from streamlit.components.v1 import html
from streamlit_extras.stylable_container import stylable_container
import re
import urllib.parse
import traceback
import os
st.title("Claude Chat UI")
if "api_key" not in st.session_state and os.path.exists("api_key.dat"):
with open("api_key.dat", "r", encoding="utf-8") as f:
st.session_state.api_key = f.readline().strip()
if "api_key" not in st.session_state:
api_key = st.text_input("Enter your API Key", type="password")
if not api_key:
st.warning("Please enter your API key to use the app.")
st.stop()
if not api_key.isascii():
st.warning("Please enter your API key correctly.")
st.stop()
st.session_state.api_key = api_key
client = anthropic.Anthropic(api_key=api_key)
st.rerun()
else:
client = anthropic.Anthropic(api_key=st.session_state.api_key)
if "messages" not in st.session_state:
st.session_state.messages = []
if "prefill" not in st.session_state:
st.session_state.prefill = ""
if "use_continue" not in st.session_state:
st.session_state.use_continue = False
if "message_continue" not in st.session_state:
st.session_state.message_continue = ""
if "exception" not in st.session_state:
st.session_state.exception = None
if "use_thinking" not in st.session_state:
st.session_state.use_thinking = False
if "thinking_budget_tokens" not in st.session_state:
st.session_state.thinking_budget_tokens = 1024
if "last_thinking" not in st.session_state:
st.session_state.last_thinking = ""
def count_tokens(text):
if len(text) > 0:
response = client.messages.count_tokens(
model=model,
messages = [{
"role": "user",
"content": text
}]
)
tokens = response.input_tokens
return tokens
else:
return 0
def get_truncated_index(messages, limit_val, limit_unit, additional_tokens):
""" Find index of first message within truncated context
Args:
messages (list): Input messages for anthropic API
limit_val (int): Context length limitation
limit_unit (str): "Turns" or "Tokens"
additional_tokens (int): Token count of system prompt
Returns:
int: index of first message within truncated context
"""
if limit_val == 0:
return 0
if limit_unit == "Turns":
# Unit: Turns
count_turn = 0
for i in reversed(range(len(messages))):
if messages[i]["role"] == "user":
count_turn += 1
if count_turn == limit_val:
return i
return 0
else:
# Unit: Tokens
last_user_index = len(messages)
total_tokens = additional_tokens
for i in reversed(range(len(messages))):
total_tokens += count_tokens(messages[i]["content"])
if total_tokens > limit_val:
return last_user_index
if messages[i]["role"] == "user":
last_user_index = i
return last_user_index
def get_truncated_context(messages, limit_val, limit_unit, additional_tokens):
""" Return truncated context
Args:
messages (list): Input messages for anthropic API
limit_val (int): Context length limitation
limit_unit (str): "Turns" or "Tokens"
additional_tokens (int): Token count of system prompt
Returns:
list: Truncated input messages for anthropic API
"""
first_message_index = get_truncated_index(messages, limit_val, limit_unit, additional_tokens)
if first_message_index >= len(messages):
return []
return messages[first_message_index:]
def get_ai_response(messages):
st.session_state.is_streaming = True
st.session_state.response = ""
shown_message = ""
st.session_state.last_thinking = ""
st.session_state.message_continue = st.session_state.message_continue.strip()
st.session_state.prefill = st.session_state.prefill.strip()
if st.session_state.message_continue != "":
messages.append({"role": "assistant", "content": st.session_state.message_continue})
st.session_state.response += st.session_state.message_continue
shown_message = st.session_state.message_continue.replace("\n", " \n")
elif st.session_state.prefill:
messages.append({"role": "assistant", "content": st.session_state.prefill})
st.session_state.response += st.session_state.prefill
shown_message = st.session_state.prefill.replace("\n", " \n")
api_messages = []
for msg in messages:
api_msg = {"role": msg["role"], "content": msg["content"]}
api_messages.append(api_msg)
api_messages = get_truncated_context(api_messages, limit_val, limit_unit, count_tokens(system_prompt))
st.session_state.exception = None
try:
with st.chat_message("assistant", avatar=st.session_state.assistant_avatar):
placeholder = st.empty()
with stylable_container(
key="stop_generating",
css_styles="""
button {
position: fixed;
bottom: 100px;
left: 50%;
transform: translateX(-50%);
z-index: 1;
}
""",
):
st.button("Stop generating")
# Configure thinking parameter
thinking_param = None
if st.session_state.use_thinking:
thinking_param = {
"type": "enabled",
"budget_tokens": st.session_state.thinking_budget_tokens
}
# Prepare kwargs for the API call
stream_kwargs = {
"messages": api_messages,
"model": model,
"max_tokens": max_tokens,
"system": system_prompt,
"temperature": temperature,
}
# Add thinking parameter if enabled
if thinking_param:
stream_kwargs["thinking"] = thinking_param
elif "-4-5-" not in model:
# Only add top_p and top_k when thinking is disabled and not a 4-5 model
# Claude 4-5 models don't support temperature + top_p/top_k simultaneously
stream_kwargs["top_p"] = top_p
stream_kwargs["top_k"] = top_k
with client.messages.stream(**stream_kwargs) as stream:
# Stream event handling
current_block_type = None
for event in stream:
if event.type == "content_block_start":
current_block_type = event.content_block.type
elif event.type == "content_block_delta":
if event.delta.type == "thinking_delta" and current_block_type == "thinking":
content = str(event.delta.thinking) if event.delta.thinking is not None else ""
st.session_state.last_thinking += content
shown_message += content.replace("\n", " \n")\
.replace("<", "\\<")\
.replace(">", "\\>")
placeholder.markdown(shown_message)
elif event.delta.type == "text_delta" and current_block_type == "text":
content = str(event.delta.text) if event.delta.text is not None else ""
st.session_state.response += content
shown_message += content.replace("\n", " \n")\
.replace("<", "\\<")\
.replace(">", "\\>")
placeholder.markdown(shown_message)
except Exception as e:
st.session_state.exception = e
st.session_state.is_streaming = False
return st.session_state.response
def normalize_code_block(match):
return match.group(0).replace(" \n", "\n")\
.replace("\\<", "<")\
.replace("\\>", ">")
def normalize_inline(match):
return match.group(0).replace("\\<", "<")\
.replace("\\>", ">")
code_block_pattern = r"(```.*?```)"
inline_pattern = r"`([^`\n]+?)`"
def display_messages():
for i, message in enumerate(st.session_state.messages):
if message["role"] == "user":
avatar = st.session_state.user_avatar
else:
avatar = st.session_state.assistant_avatar
with st.chat_message(message["role"], avatar=avatar):
# Add expander for thinking if it exists
if message["role"] == "assistant" and "thinking" in message and message["thinking"]:
with st.expander("Show Claude's thinking process"):
thinking_text = message["thinking"].replace("\n", " \n")\
.replace("<", "\\<")\
.replace(">", "\\>")
if "```" in thinking_text:
thinking_text = re.sub(code_block_pattern, normalize_code_block, thinking_text, flags=re.DOTALL)
if "`" in thinking_text:
thinking_text = re.sub(inline_pattern, normalize_inline, thinking_text)
st.markdown(thinking_text)
shown_message = message["content"].replace("\n", " \n")\
.replace("<", "\\<")\
.replace(">", "\\>")
if "```" in shown_message:
# Replace " \n" with "\n" within code blocks
shown_message = re.sub(code_block_pattern, normalize_code_block, shown_message, flags=re.DOTALL)
if "`" in shown_message:
shown_message = re.sub(inline_pattern, normalize_inline, shown_message)
st.markdown(shown_message)
if st.session_state.get("show_message_tokens"):
message_tokens = count_tokens(message["content"])
st.info(f'Tokens: {message_tokens}')
col1, col2, col3, col4 = st.columns([1, 1, 1, 1])
with col1:
if st.button("Edit", key=f"edit_{i}_{len(st.session_state.messages)}"):
st.session_state.edit_index = i
st.rerun()
with col2:
if st.session_state.is_delete_mode and st.button("Delete", key=f"delete_{i}_{len(st.session_state.messages)}"):
del st.session_state.messages[i]
st.rerun()
with col3:
text_to_copy = message["content"]
# Encode the string to escape
text_to_copy_escaped = urllib.parse.quote(text_to_copy)
copy_button_html = f"""
<button id="copy-msg-btn-{i}" style='font-size: 1em; padding: 0.5em;' onclick='copyMessage("{i}")'>Copy</button>
<script>
function copyMessage(index) {{
navigator.clipboard.writeText(decodeURIComponent("{text_to_copy_escaped}"));
let copyBtn = document.getElementById("copy-msg-btn-" + index);
copyBtn.innerHTML = "Copied!";
setTimeout(function(){{ copyBtn.innerHTML = "Copy"; }}, 2000);
}}
</script>
"""
html(copy_button_html, height=50)
if i == len(st.session_state.messages) - 1 and message["role"] == "assistant":
with col4:
if st.button("Retry", key=f"retry_{i}_{len(st.session_state.messages)}"):
if len(st.session_state.messages) >= 2:
if st.session_state.get("use_continue"):
st.session_state.message_continue = st.session_state.messages[-1]["content"]
del st.session_state.messages[-1]
st.session_state.retry_flag = True
st.rerun()
if "edit_index" in st.session_state and st.session_state.edit_index == i:
with st.form(key=f"edit_form_{i}_{len(st.session_state.messages)}"):
new_content = st.text_area("Edit message", height=200, value=st.session_state.messages[i]["content"])
col1, col2 = st.columns([1, 1])
with col1:
if st.form_submit_button("Save"):
st.session_state.messages[i]["content"] = new_content
del st.session_state.edit_index
st.rerun()
with col2:
if st.form_submit_button("Cancel"):
del st.session_state.edit_index
st.rerun()
if st.session_state.exception:
st.exception(st.session_state.exception)
# Add sidebar for advanced settings
with st.sidebar:
settings_tab, appearance_tab = st.tabs(["Settings", "Appearance"])
with settings_tab:
st.markdown("Help (Japanese): https://rentry.org/9hgneofz")
# Copy Conversation History button
log_text = ""
for message in st.session_state.messages:
if message["role"] == "user":
log_text += "<USER>\n"
log_text += message["content"] + "\n\n"
else:
log_text += "<ASSISTANT>\n"
if "thinking" in message and message["thinking"]:
log_text += "<THINKING>\n"
log_text += message["thinking"] + "\n</THINKING>\n"
log_text += message["content"] + "\n\n"
log_text = log_text.rstrip("\n")
# Encode the string to escape
log_text_escaped = urllib.parse.quote(log_text)
copy_log_button_html = f"""
<button id="copy-log-btn" style='font-size: 1em; padding: 0.5em;' onclick='copyLog()'>Copy Conversation History</button>
<script>
const log_text_escaped = "{log_text_escaped}";
function copyLog() {{
navigator.clipboard.writeText(decodeURIComponent(log_text_escaped));
const copyBtn = document.getElementById("copy-log-btn");
copyBtn.innerHTML = "Copied!";
setTimeout(function(){{ copyBtn.innerHTML = "Copy Conversation History"; }}, 2000);
}}
window.parent.document.addEventListener('keydown', (e) => {{
if ( e.code == "Pause" ){{
window.parent.navigator.clipboard.writeText(decodeURIComponent(log_text_escaped));
const copyBtn = document.getElementById("copy-log-btn");
copyBtn.innerHTML = "Copied!";
setTimeout(function(){{ copyBtn.innerHTML = "Copy Conversation History"; }}, 2000);
}}
}} , false);
</script>
"""
html(copy_log_button_html, height=50)
if st.session_state.get("is_history_shown") != True:
if st.button("Display History as Code Block"):
st.session_state.is_history_shown = True
st.rerun()
else:
if st.button("Hide History"):
st.session_state.is_history_shown = False
st.rerun()
st.code(log_text)
st.session_state.is_delete_mode = st.toggle("Enable Delete button")
st.session_state.use_continue = st.toggle("Use Continue instead of Retry", value=st.session_state.use_continue)
st.header("Advanced Settings")
model_list = ["claude-sonnet-4-5-20250929",
"claude-opus-4-5-20251101",
"claude-haiku-4-5-20251001",
"claude-opus-4-1-20250805",
"claude-opus-4-20250514",
"claude-sonnet-4-20250514",
"claude-3-7-sonnet-20250219",
"claude-3-5-haiku-20241022",
"claude-3-haiku-20240307",
"claude-3-opus-20240229",
]
model = st.selectbox("Model", options=model_list, index=0)
system_prompt = st.text_area("System prompt", height=200)
st.session_state.prefill = st.text_area("Prefill", height=68, value=st.session_state.prefill,
help="You can prefill the assistant's responses. You can also directly type the @prefill command into the chat field (e.g., \"Write a novel. @prefill Sure! I'd be happy to write a novel for you.\")")
save_prefill = st.toggle("Save the @prefill command input in the sidebar", value=True)
temperature = st.slider("Temperature", min_value=0.0, max_value=1.0, value=1.0, step=0.1)
top_k = st.slider("Top-K", min_value=0, max_value=500, value=0, step=1)
top_p = st.slider("Top-P", min_value=0.01, max_value=1.00, value=1.00, step=0.01)
max_tokens = st.slider("Max Output Tokens", min_value=1, max_value=4096, value=4096, step=1)
st.header("Extended Thinking")
st.session_state.use_thinking = st.toggle(
"Enable extended thinking",
value=st.session_state.use_thinking,
help="Enable Claude's enhanced reasoning capabilities"
)
if st.session_state.use_thinking:
st.session_state.thinking_budget_tokens = st.slider(
"Thinking budget tokens",
min_value=1024,
max_value=4000,
value=st.session_state.thinking_budget_tokens,
step=100,
help="Maximum tokens Claude can use for internal reasoning"
)
# Check relationship between max_tokens and budget_tokens
if st.session_state.thinking_budget_tokens >= max_tokens:
st.warning("Thinking budget tokens must be less than Max Output Tokens")
st.header("Context limitation")
col_limit_val, col_limit_unit = st.columns([1, 1])
with col_limit_val:
limit_val = st.number_input("Limit", min_value=0, max_value=200000, value="min", help="0 means no limit")
with col_limit_unit:
limit_unit = st.selectbox("Unit", options=["Turns","Tokens"], index=0, help="Tokens Unit is a rough estimate")
st.header("Tokens")
st.session_state.show_message_tokens = st.toggle("Show message tokens")
system_prompt_tokens = count_tokens(system_prompt)
prefill_tokens = count_tokens(st.session_state.prefill)
messages_tokens = 0
for message in st.session_state.messages:
messages_tokens += count_tokens(message["content"])
total_tokens = system_prompt_tokens + prefill_tokens + messages_tokens
tokens_table_md = f"| Part | Tokens |\n"
tokens_table_md += f"| ---- | ---- |\n"
tokens_table_md += f"| System | {system_prompt_tokens} |\n"
tokens_table_md += f"| Prefill | {prefill_tokens} |\n"
tokens_table_md += f"| Message | {messages_tokens}({len(st.session_state.messages)}) |\n"
tokens_table_md += f"| Total | {total_tokens} |\n\n"
tokens_table_md += f"These token counts are very rough estimates.\n"
st.markdown(tokens_table_md)
st.header("Restore History")
history_input = st.text_area("Paste conversation history:", height=200)
if st.button("Restore History"):
st.session_state.messages = []
st.session_state.exception = None
messages = re.split(r"^(<USER>|<ASSISTANT>)\n", history_input, flags=re.MULTILINE)
role = None
text = ""
for message in messages:
if message.strip() in ["<USER>", "<ASSISTANT>"]:
if role and text:
if role == "assistant":
thinking_match = re.search(r"<THINKING>\n(.*?)</THINKING>\n", text, re.DOTALL)
if thinking_match:
thinking_content = thinking_match.group(1).strip()
content = re.sub(r"<THINKING>\n.*?</THINKING>\n", "", text, flags=re.DOTALL).strip()
st.session_state.messages.append({
"role": role,
"content": content,
"thinking": thinking_content
})
else:
st.session_state.messages.append({"role": role, "content": text.strip()})
else:
st.session_state.messages.append({"role": role, "content": text.strip()})
text = ""
role = "user" if message.strip() == "<USER>" else "assistant"
else:
text += message
if role and text:
if role == "assistant":
thinking_match = re.search(r"<THINKING>\n(.*?)</THINKING>\n", text, re.DOTALL)
if thinking_match:
thinking_content = thinking_match.group(1).strip()
content = re.sub(r"<THINKING>\n.*?</THINKING>\n", "", text, flags=re.DOTALL).strip()
st.session_state.messages.append({
"role": role,
"content": content,
"thinking": thinking_content
})
else:
st.session_state.messages.append({"role": role, "content": text.strip()})
else:
st.session_state.messages.append({"role": role, "content": text.strip()})
st.rerun()
st.header("Clear History")
if st.button("Clear Chat History"):
st.session_state.messages = []
st.session_state.exception = None
st.rerun()
st.header("Change API Key")
new_api_key = st.text_input("Enter new API Key", type="password")
if st.button("Update API Key"):
if new_api_key:
st.session_state.api_key = new_api_key
client = anthropic.Anthropic(api_key=new_api_key)
st.success("API Key updated successfully!")
else:
st.warning("Please enter a valid API Key.")
with appearance_tab:
st.header("Font Selection")
font_options = {
"Zen Maru Gothic": "Zen Maru Gothic",
"Noto Sans JP": "Noto Sans JP",
"Sawarabi Mincho": "Sawarabi Mincho"
}
selected_font = st.selectbox("Choose a font", ["Default"] + list(font_options.keys()))
st.header("Change the font size")
st.session_state.font_size = st.slider("Font size", min_value=16.0, max_value=50.0, value=16.0, step=1.0)
st.header("Change the user's icon")
st.session_state.user_avatar = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg", "webp", "gif", "bmp", "svg",], key="user_avatar_uploader")
st.header("Change the assistant's icon")
st.session_state.assistant_avatar = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg", "webp", "gif", "bmp", "svg",], key="assistant_avatar_uploader")
st.header("Change the icon size")
st.session_state.avatar_size = st.slider("Icon size", min_value=2.0, max_value=20.0, value=2.0, step=0.2)
# After Stop generating
if st.session_state.get("is_streaming"):
message_content = {"role": "assistant", "content": st.session_state.response}
if st.session_state.last_thinking:
message_content["thinking"] = st.session_state.last_thinking
st.session_state.messages.append(message_content)
st.session_state.is_streaming = False
if "retry_flag" in st.session_state and st.session_state.retry_flag:
st.session_state.retry_flag = False
st.session_state.message_continue = ""
st.rerun()
# Change the font
if selected_font != "Default":
with open("style.css") as css:
st.markdown(f'<style>{css.read()}</style>', unsafe_allow_html=True)
st.markdown(f'<style>body * {{ font-family: "{font_options[selected_font]}", serif !important; }}</style>', unsafe_allow_html=True)
# Change font size
st.markdown(f'<style>[data-testid="stChatMessageContent"] .st-emotion-cache-kj6hex p{{font-size: {st.session_state.font_size}px;}}</style>', unsafe_allow_html=True)
# Change icon size
# (CSS element names may be subject to change.)
# (Contributor: ā
31 >>538)
AVATAR_SIZE_STYLE = f"""
<style>
[data-testid="stChatMessageAvatarUser"] {{
width: {st.session_state.avatar_size}rem;
height: {st.session_state.avatar_size}rem;
}}
[data-testid="stChatMessageAvatarAssistant"] {{
width: {st.session_state.avatar_size}rem;
height: {st.session_state.avatar_size}rem;
}}
[data-testid="stChatMessage"] .st-emotion-cache-1pbsqtx {{
width: {st.session_state.avatar_size / 1.6}rem;
height: {st.session_state.avatar_size / 1.6}rem;
}}
[data-testid="stChatMessage"] .st-emotion-cache-p4micv {{
width: {st.session_state.avatar_size}rem;
height: {st.session_state.avatar_size}rem;
}}
</style>
"""
st.markdown(AVATAR_SIZE_STYLE, unsafe_allow_html=True)
display_messages()
# After Retry
if st.session_state.get("retry_flag"):
if len(st.session_state.messages) > 0:
messages = st.session_state.messages.copy()
response = get_ai_response(messages)
message_content = {"role": "assistant", "content": response}
if st.session_state.last_thinking:
message_content["thinking"] = st.session_state.last_thinking
st.session_state.messages.append(message_content)
st.session_state.retry_flag = False
st.session_state.message_continue = ""
st.rerun()
else:
st.session_state.retry_flag = False
st.session_state.message_continue = ""
if prompt := st.chat_input("Enter your message here..."):
used_prefill = False
prefill_pattern = r"([@ļ¼ ](prefill|ć·ććµćć|ćć¬ćć£ć«)\s?(.*))"
prefill_match = re.search(prefill_pattern, prompt)
if prefill_match:
used_prefill = True
if not save_prefill:
original_prefill = st.session_state.prefill
st.session_state.prefill = prefill_match.group(3)
prompt = prompt.replace(prefill_match.group(1), '')
st.session_state.messages.append({"role": "user", "content": prompt})
messages = st.session_state.messages.copy()
shown_message = prompt.replace("\n", " \n")\
.replace("<", "\\<")\
.replace(">", "\\>")
with st.chat_message("user", avatar=st.session_state.user_avatar):
st.write(shown_message)
response = get_ai_response(messages)
message_content = {"role": "assistant", "content": response}
if st.session_state.last_thinking:
message_content["thinking"] = st.session_state.last_thinking
st.session_state.messages.append(message_content)
if used_prefill and not save_prefill:
st.session_state.prefill = original_prefill
st.rerun() |