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a138eb5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | import streamlit as st
from src.api.model_integration import stream_response
from src.utils.prompt_templates import (
get_translation_prompt,
get_sentiment_analysis_prompt,
get_cultural_reference_explanation_prompt,
get_interactive_translation_prompt,
)
from config.config import Config
def setup_page():
"""
Sets up the page with custom styles and page configuration.
"""
st.set_page_config(
page_title="Translator-AI (Llama3.1)",
layout="wide",
initial_sidebar_state="expanded",
)
st.markdown(
"""
<style>
:root {
--llama-color: #4e8cff;
--llama-color-light: #e6f0ff;
--llama-color-dark: #1a3a6c;
--llama-gradient-start: #4e54c8;
--llama-gradient-end: #8f94fb;
}
.stApp {
margin: auto;
background-color: var(--background-color);
color: var(--text-color);
}
.logo-container {
display: flex;
justify-content: center;
margin-bottom: 1rem;
}
.logo-container img {
width: 150px;
}
</style>
""",
unsafe_allow_html=True,
)
def main():
setup_page()
# Header section with title and subtitle
st.markdown(
"""
<div style="text-align: center;">
<h1 class="header-title">🦙 Meta-Llama 3.1 Translator-AI</h1>
<p class="header-subtitle">Powered by Meta's advanced language models</p>
</div>
""",
unsafe_allow_html=True,
)
# Meta logo
st.markdown(
"""
<div class="logo-container">
<img src="https://upload.wikimedia.org/wikipedia/commons/7/7b/Meta_Platforms_Inc._logo.svg" alt="Meta Logo">
</div>
""",
unsafe_allow_html=True,
)
# Remove the Llama image display
# Sidebar for settings
with st.sidebar:
st.title("🦙 Llama Translator Settings")
model_name = st.selectbox("Choose a model", Config.AVAILABLE_MODELS)
source_lang = st.selectbox(
"From", ["English", "Spanish", "French", "German", "Japanese"]
)
target_lang = st.selectbox(
"To", ["Spanish", "English", "French", "German", "Japanese"]
)
cultural_context = st.selectbox(
"Context", ["Formal", "Casual", "Business", "Youth Slang", "Poetic"]
)
# Main container with border
main_container = st.container(border=True)
with main_container:
st.header("Enter Text for Translation and Analysis")
text = st.text_area(
"Text to translate",
"It was the best of times, it was the worst of times...",
height=200,
)
st.caption(f"Character count: {len(text)}")
if st.button("Translate and Analyze", type="primary"):
if text:
# Tabs for different analysis types
tab1, tab2, tab3, tab4 = st.tabs(
[
"Translation",
"Sentiment Analysis",
"Cultural References",
"Interactive Translation",
]
)
# Tab 1: Translation
with tab1:
st.subheader("Translation Result")
translation_container = st.empty()
translation_prompt = get_translation_prompt(
text, source_lang, target_lang, cultural_context
)
translation = stream_response(
[{"role": "user", "content": translation_prompt}],
translation_container,
model_name,
)
# Tab 2: Sentiment Analysis
with tab2:
st.subheader("Sentiment Analysis")
sentiment_container = st.empty()
sentiment_prompt = get_sentiment_analysis_prompt(text, source_lang)
sentiment_analysis = stream_response(
[{"role": "user", "content": sentiment_prompt}],
sentiment_container,
model_name,
)
# Tab 3: Cultural References
with tab3:
st.subheader("Cultural References")
cultural_container = st.empty()
cultural_prompt = get_cultural_reference_explanation_prompt(
text, source_lang, target_lang
)
cultural_references = stream_response(
[{"role": "user", "content": cultural_prompt}],
cultural_container,
model_name,
)
# Tab 4: Interactive Translation
with tab4:
st.subheader("Interactive Translation")
interactive_container = st.empty()
interactive_prompt = get_interactive_translation_prompt(
text, source_lang, target_lang
)
interactive_translation = stream_response(
[{"role": "user", "content": interactive_prompt}],
interactive_container,
model_name,
)
# Sidebar for additional information and feedback
with st.sidebar:
st.subheader("About")
st.info("This app demonstrates Meta's Llama 3.1 capabilities.")
st.subheader("Feedback")
feedback = st.text_area("Leave your feedback here", height=100)
if st.button("Submit Feedback"):
st.success("Thank you for your feedback!")
if __name__ == "__main__":
main()
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