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app.py
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##################################################
# Brian Lesko
# 2024-12-24
# In this Low code UI, we interact with a large language transformer model (LLM) through an Application Programming Interface (API).
import streamlit as st
from aitools import AIClient
import base64
def write_stream(stream):
text = ""
for chunk in stream:
content = chunk.choices[0].delta.content
if content is not None:
text += content
with Stream:
if do_html is True:
st.html(f'''<p style="padding: 0; margin: 0;"> {text} </p>''')
else:
st.markdown(f"""<div style="height: 80vh; background-color: white;" class="flex flex-col"> <div>{text}</div>""", unsafe_allow_html=True)
return text
# {"Original" if i == len(messages) else "Iteration" + str(len(messages) - i)}
def write_recursive_stream(stream, messages):
tab_name = "Most concise"
past_tabs = " ".join(f'''
<input type="radio" name="my_tabs_2" role="tab" class="tab p-2 m-2" aria-label="tabn" />
<label for="tab_{i}" class="p-2 m-2 tab-label"><!-- This is the visible text -->{ "Original" if i == len(messages) else f"Iteration {len(messages) - i}" }
</label>
<div role="tabpanel" class="tab-content bg-base-100 border-base-300 rounded-box p-6 m-6">
<div style="padding: 10px; margin: 10px;">
{s}
</div>
</div>''' for i, s in enumerate(reversed(messages)))
text = "\n"
for chunk in stream:
chunk_text = chunk.choices[0].delta.content
if chunk_text is not None:
text += chunk_text
# build our HTML
my_html = f"""
<div role="tablist" class="tabs tabs-lifted p-6">
<input type="radio" name="my_tabs_2" role="tab" class="tab" aria-label="{tab_name}" checked="checked" />
<label for="tab" class="p-2 m-2 tab-label">
<!-- This is the visible text -->
Most Concise
</label>
<div role="tabpanel" class="tab-content bg-base-100 border-base-300 rounded-box p-6 m-6">
<div style = "padding: 10px; margin: 10px;">
{text}
</div>
</div>{past_tabs}
</div>
"""
# Display in Streamlit
# (If you only want to show the final result once all chunks have arrived)
with Stream:
if do_html:
st.html(f"""<p>{text}</p>""")
else:
st.markdown(f"""<div style="min-height: 80vh; background-color: white;" class="flex flex-col">{my_html}</div>""",unsafe_allow_html=True)
return text
st.set_page_config(page_title='LLM0',page_icon='')
tailwind_cdn = """
<link href="https://cdn.jsdelivr.net/npm/daisyui@4.12.23/dist/full.min.css" rel="stylesheet" type="text/css" />
<script src="https://cdn.tailwindcss.com"></script>
"""
st.markdown(tailwind_cdn, unsafe_allow_html=True)
hide_streamlit_style = "<style>#MainMenu, footer, header {visibility: hidden;}</style>"
st.markdown(hide_streamlit_style, unsafe_allow_html=True)
ai_choice = st.sidebar.selectbox("Choose an API", ["xai", "openai"])
if "myai" not in st.session_state or st.session_state.myai.company_name != ai_choice:
st.session_state.myai = AIClient(ai_choice)
if st.session_state.myai.api_key is None:
Message = st.empty()
import base64
msg="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"
Message.html(base64.b64decode(msg).decode("utf-8"))
st.stop()
st.session_state.myai.setup()
Title = st.empty()
Title.markdown('<h1 style="text-align: center; padding-top: 60px;">My llm</h1>', unsafe_allow_html=True)
Upload = st.empty()
Chat = st.empty()
file = Upload.file_uploader("", accept_multiple_files=False)
if file: st.session_state.file = st.session_state.myai._reduce_image_size(file)
if "file" in st.session_state:
b64 = st.session_state.file
st.html(f"""
<div style="text-align: center; padding-top: 40px; padding-bottom: 20px;">
<img src="data:image/png;base64,{b64}" alt="Base64 Image" style="max-width: 100%; height: auto; border-radius: 10px;">
</div>
""")
if "messages" not in st.session_state:
st.session_state["messages"] = []
else:
Title.empty()
Upload.empty()
do_html = st.sidebar.checkbox("Use HTML", value=False)
recursion = st.sidebar.checkbox("Recursion", value=True)
recursion_instances = 0
if recursion:
recursion_instances = st.sidebar.number_input("Recursion Instances", value=3)
recursion_prompt = st.sidebar.text_input("Recursion Prompt", value="Be more terse.")
# Display all the historical messages
def write_history(messages):
to_write = [""]
for msg in messages:
if msg["role"] == "system":
continue # Skip system messages
if msg["role"] == "user":
to_write.append("\n ## " + msg["content"])
else:
to_write.append(msg["content"])
History.markdown(f"<div style='padding-top: 40px;'>{"\n".join(to_write)}</div>", unsafe_allow_html=True)
def write_mixed_content_history(messages):
# Similar to the unified approach, but specifically assumes
# each user message has a list with image + text blocks
to_write = [""]
for msg in messages:
if msg["role"] == "system":
continue
content_str = ""
for block in msg["content"]:
if block["type"] == "image_url":
image_url = block["image_url"]["url"]
content_str += f"\n\n"
elif block["type"] == "text":
content_str += block["text"]
if msg["role"] == "user":
to_write.append(f"\n ## {content_str}")
else:
to_write.append(content_str)
History.markdown(
f"<div style='padding-top: 40px;'>{'\n'.join(to_write)}</div>",
unsafe_allow_html=True
)
def write_msg(msg):
if isinstance(msg["content"], str): # This is a text message
if msg["role"] == "user":
st.markdown(f"<h2 style='padding-top: 40px;'>{msg['content']}</h2>", unsafe_allow_html=True)
else:
st.markdown(f'''<p style="padding: 0; margin: 0;"> {msg["content"]} </p>''', unsafe_allow_html=True)
else: # This is an image message
url = next(item["image_url"]["url"] for item in msg["content"] if item["type"] == "image_url")
st.markdown(f"<h2 style='padding-top: 40px;'>{msg['content'][1]['text']}</h2>", unsafe_allow_html=True)
History = st.empty()
if recursion: write_history(st.session_state.messages)
else: write_mixed_content_history(st.session_state.messages)
User = st.empty()
Stream = st.empty()
prompt = st.chat_input("Write a message")
count = 0
messages = []
while prompt:
# If there is a prompt and an image
if "file" in st.session_state:
b64 = st.session_state.file
st.session_state.messages.append({
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}", "detail": "high"}}, # add the upload every time we send a new query
{"type": "text", "text": prompt}
]
})
User.markdown(f""" ## {prompt} """, unsafe_allow_html=True)
completion = st.session_state.myai.client.chat.completions.create(
model="grok-2-vision-1212",
messages=st.session_state.messages,
temperature=0.01,
)
text = completion.choices[0].message.content
st.markdown(text)
st.session_state.messages.append({"role": "assistant", "content": [{"type": "text", "text": text}]})
st.session_state.pop("file", None)
break
# If there is only a prompt
else:
if count == 0: st.session_state.messages.append({"role": "user", "content": prompt})
Stream.html("""<div style="height: 80vh; background-color: white;"></div>""")
User.markdown(f""" ## {prompt} """, unsafe_allow_html=True)
stream = st.session_state.myai.get_stream(st.session_state.messages+messages+ ([{"role": "system", "content": recursion_prompt}] if recursion and count>0 else []))
if not recursion:
text = write_stream(stream)
else:
strings = [message["content"] for message in messages if "content" in message]
text = write_recursive_stream(stream, strings)
messages.append({"role": "assistant", "content": text})
#st.session_state.messages.append({"role": "assistant", "content": text})
if count >= recursion_instances or not recursion:
# add the last message to the history
if recursion:
st.session_state.messages.append(messages[-1])
else:
st.session_state.messages.append({"role": "assistant", "content": text})
break
else:
count = count + 1
messages = []