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| import streamlit as st | |
| from utils import get_api_key, get_response | |
| def main(): | |
| st.header('Welcome to SciDocuParse! 🧑🔬📚') | |
| st.write('A scientific document parser, particularly specializing in graph analysis 📊 and data interpretation 🔍.') | |
| st.session_state["thought_process"] = "" | |
| st.session_state["response"] = "" | |
| with st.sidebar: | |
| st.header('SciDocuParse Sidebar 🔧') | |
| st.caption('A tool to help you analyze scientific papers and documents efficiently! 📝') | |
| paper = st.text_area('Paste scientific document citation here 🧑🏫', | |
| """@article{wang2020automated, | |
| title={Automated diabetic retinopathy grading and lesion detection based on the modified R-FCN object-detection algorithm}, | |
| author={Wang, Jialiang and Luo, Jianxu and Liu, Bin and Feng, Rui and Lu, Lina and Zou, Haidong}, | |
| journal={IET Computer Vision}, | |
| volume={14}, | |
| number={1}, | |
| pages={1--8}, | |
| year={2020}, | |
| publisher={Wiley Online Library} | |
| }""", height=350, help='Paste your document citation in BiBtex format.') | |
| if not paper: | |
| st.error('Provide a citation first! ⚠️') | |
| user_prompt = st.text_area("Enter your query for analysis 🔍:", | |
| "Summarize this document and highlight key findings in graphs 📈") | |
| persona = "You are a master Scientific Graph Analyzer skilled in interpreting graphs across all fields. Analyze trends (linear/exponential growth, correlations, outliers) and statistical patterns (mean, variance). Summarize key findings in plain language, Expalin data about causality, anomalies, or data limitations. Prioritize clarity: ensure outputs are accessible to technical and non-technical audiences. Combine technical precision with intuitive communication to deliver accurate, user-friendly interpretations." | |
| user_prompt = persona + paper + user_prompt | |
| # api_key = get_api_key() | |
| if st.button('Analyze with LLM 🚀'): | |
| with st.spinner('Processing your document...'): | |
| api_key = get_api_key() | |
| thought_process, response = get_response(user_prompt, api_key) # uncommenting it to save tokens | |
| st.session_state["thought_process"] = thought_process | |
| st.session_state["response"] = response | |
| if "thought_process" in st.session_state and "response" in st.session_state: | |
| if len(st.session_state["thought_process"]) >= 1 and len(st.session_state["response"]) >= 1: | |
| with st.expander('Show thought process 💭'): | |
| st.caption(thought_process) | |
| st.subheader('RESPONSE 📝') | |
| st.write(response) | |
| st.caption('SciDocuParse is made by John Manuel Carado') | |
| st.caption('Intelligent Systems course in WVSU - CICT, Midterm Requirement') | |
| if __name__ == '__main__': | |
| main() |