wehub-resource-sync
55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
## Copyright 2025 Google LLC
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## Licensed under the Apache License, Version 2.0 (the "License");
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## you may not use this file except in compliance with the License.
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## You may obtain a copy of the License at
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## https://www.apache.org/licenses/LICENSE-2.0
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## Unless required by applicable law or agreed to in writing, software
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## distributed under the License is distributed on an "AS IS" BASIS,
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## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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## See the License for the specific language
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"""The main landing page for the LLM EvalKit Streamlit application."""
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import streamlit as st
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from dotenv import load_dotenv
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load_dotenv("src/.env")
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def main() -> None:
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"""Renders the main landing page of the application."""
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st.set_page_config(
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page_title="LLM EvalKit",
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layout="wide",
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initial_sidebar_state="expanded",
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page_icon="assets/favicon.ico",
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)
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st.title("Welcome to the LLM EvalKit")
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st.markdown(
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"A suite of tools for managing, evaluating, and optimizing LLM prompts and datasets."
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)
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st.subheader("Getting Started")
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st.markdown(
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"""
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This application helps you streamline your prompt engineering workflow.
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Select a tool from the sidebar on the left to begin.
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**Available Tools:**
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* **Prompt Management:** Create, test, and manage your prompts.
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* **Dataset Creation:** Create evaluation datasets from CSV files.
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* **Simple Evaluation:** Run simple evaluations on your prompts.
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* **Evaluation Human Judge:** Manually rate model responses for evaluation.
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* **Prompt Optimization:** Optimize your prompts for better performance.
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* **Prompt Optimization Results:** View the results of prompt optimization runs.
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* **Prompt Records:** View and manage your prompt records.
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"""
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)
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st.caption("LLM EvalKit | Home")
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if __name__ == "__main__":
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main()
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