├── src ├── main.jsx ├── FullPageLoader.jsx ├── App.css ├── index.css ├── assets │ └── react.svg ├── columns.jsx ├── App.jsx └── mysvg.jsx ├── index.html ├── .gitignore ├── vite.config.js ├── package.json ├── templates └── latex_template.tex ├── README.md ├── requirements.txt ├── public └── vite.svg ├── agents2.py ├── agents4.py ├── agents3.py ├── agents.py ├── server.py └── LICENSE /src/main.jsx: -------------------------------------------------------------------------------- 1 | import React from 'react' 2 | import ReactDOM from 'react-dom/client' 3 | import App from './App.jsx' 4 | import './index.css' 5 | 6 | ReactDOM.createRoot(document.getElementById('root')).render( 7 | 8 | 9 | , 10 | ) 11 | -------------------------------------------------------------------------------- /src/FullPageLoader.jsx: -------------------------------------------------------------------------------- 1 | // src/components/FullPageLoader.js 2 | 3 | import React from 'react'; 4 | import { Spin } from 'antd'; 5 | 6 | const FullPageLoader = () => { 7 | return ( 8 |
9 | 10 |
11 | ); 12 | }; 13 | 14 | export default FullPageLoader; 15 | -------------------------------------------------------------------------------- /index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | Vite + React 8 | 9 | 10 |
11 | 12 | 13 | 14 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # See https://help.github.com/articles/ignoring-files/ for more about ignoring files. 2 | 3 | # dependencies 4 | /node_modules 5 | /.pnp 6 | .pnp.js 7 | 8 | # testing 9 | /coverage 10 | 11 | # production 12 | /build 13 | /dist 14 | # misc 15 | .DS_Store 16 | .env.local 17 | .env.development.local 18 | .env.test.local 19 | .env.production.local 20 | 21 | npm-debug.log* 22 | yarn-debug.log* 23 | yarn-error.log* 24 | package-lock.json 25 | *.pyc 26 | *.env 27 | *summary.tex 28 | finish-sami_key.pem 29 | 30 | -------------------------------------------------------------------------------- /vite.config.js: -------------------------------------------------------------------------------- 1 | import { defineConfig } from 'vite' 2 | import react from '@vitejs/plugin-react' 3 | 4 | // https://vitejs.dev/config/ 5 | export default defineConfig({ 6 | plugins: [react()], 7 | server:{ 8 | proxy: { 9 | '/api': { 10 | target: 'http://127.0.0.1:5000', 11 | changeOrigin: true, 12 | secure: false, 13 | // rewrite: (path) => {console.log("path:", path) 14 | // return path.replace(/^\/api/, "")} 15 | } 16 | } 17 | } 18 | }) 19 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "init", 3 | "private": true, 4 | "version": "0.0.0", 5 | "type": "module", 6 | "scripts": { 7 | "dev": "vite", 8 | "build": "vite build", 9 | "lint": "eslint . --ext js,jsx --report-unused-disable-directives --max-warnings 0", 10 | "preview": "vite preview" 11 | }, 12 | "dependencies": { 13 | "@ant-design/icons": "^5.3.1", 14 | "antd": "^5.15.0", 15 | "react": "^18.2.0", 16 | "react-dom": "^18.2.0" 17 | }, 18 | "devDependencies": { 19 | "@types/react": "^18.2.56", 20 | "@types/react-dom": "^18.2.19", 21 | "@vitejs/plugin-react": "^4.2.1", 22 | "eslint": "^8.56.0", 23 | "eslint-plugin-react": "^7.33.2", 24 | "eslint-plugin-react-hooks": "^4.6.0", 25 | "eslint-plugin-react-refresh": "^0.4.5", 26 | "vite": "^5.1.4" 27 | } 28 | } 29 | -------------------------------------------------------------------------------- /src/App.css: -------------------------------------------------------------------------------- 1 | /* #root { 2 | max-width: 1280px; 3 | margin: 0 auto; 4 | padding: 2rem; 5 | text-align: center; 6 | } 7 | 8 | .logo { 9 | height: 6em; 10 | padding: 1.5em; 11 | will-change: filter; 12 | transition: filter 300ms; 13 | } 14 | .logo:hover { 15 | filter: drop-shadow(0 0 2em #646cffaa); 16 | } 17 | .logo.react:hover { 18 | filter: drop-shadow(0 0 2em #61dafbaa); 19 | } 20 | 21 | @keyframes logo-spin { 22 | from { 23 | transform: rotate(0deg); 24 | } 25 | to { 26 | transform: rotate(360deg); 27 | } 28 | } 29 | 30 | @media (prefers-reduced-motion: no-preference) { 31 | a:nth-of-type(2) .logo { 32 | animation: logo-spin infinite 20s linear; 33 | } 34 | } 35 | 36 | .card { 37 | padding: 2em; 38 | } 39 | 40 | .read-the-docs { 41 | color: #888; 42 | } */ 43 | 44 | #root { 45 | margin: 0 ; 46 | } 47 | 48 | body { 49 | margin: 0 !important 50 | } 51 | html, body { 52 | scroll-behavior: smooth; 53 | } -------------------------------------------------------------------------------- /templates/latex_template.tex: -------------------------------------------------------------------------------- 1 | \documentclass[11pt]{article} 2 | % Packages 3 | \usepackage[utf8]{inputenc} % Allow UTF-8 input 4 | \usepackage[T1]{fontenc} % Use 8-bit T1 fonts 5 | \usepackage{geometry} % Set page size and margins 6 | \usepackage{graphicx} % Enhanced support for graphics 7 | \usepackage{hyperref} % For hyperlinks in the document 8 | \usepackage{amsmath} % For mathematical formulas 9 | \usepackage{amsfonts} % For mathematical fonts 10 | \usepackage{amssymb} % For mathematical symbols 11 | % Document geometry (page size, margins) 12 | \geometry{a4paper, total={170mm,257mm}, left=20mm, top=20mm} 13 | % Document starts here 14 | \begin{document} 15 | \title{Title of the Document} 16 | \author{Author Name} 17 | \date{\today} 18 | \maketitle 19 | \begin{abstract} 20 | {{ abstract }} 21 | \end{abstract} 22 | \section{Introduction} 23 | {{ introduction }} 24 | \section{Main Content} 25 | % Add your main content here 26 | \section{Conclusion} 27 | {{ conclusion }} 28 | % References 29 | \begin{thebibliography}{9} 30 | % Add your references here 31 | \end{thebibliography} 32 | \end{document} 33 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Flask and React Project 2 | 3 | This project combines a Flask backend with a React frontend to create a web application for generating and summarizing research-related content. 4 | 5 | ## Getting Started 6 | 7 | ### Prerequisites 8 | 9 | - Python (>=3.6) 10 | - Node.js (18.18.2) and npm (9.8.1) 11 | - Git (optional, but recommended) 12 | 13 | ### Installation 14 | 15 | 1. Clone the repository: 16 | 17 | ```bash 18 | git clone 19 | 20 | 1. Install Python dependencies for the Flask backend: 21 | cd slr_automation 22 | pip install -r requirements.txt 23 | 2. Install Node.js dependencies for the React frontend: 24 | cd slr_automation 25 | npm install 26 | 27 | # Running the Application 28 | 29 | 1. Start the Flask backend: 30 | run command python server.py 31 | server will be listening on localhost:5000 32 | 2. Production mode of react app, 33 | run "npm run build" 34 | access localhost:5000 in browser to access react build 35 | 3. for Development mode: 36 | run "npm run dev" 37 | access localhost:5173 in browser 38 | 39 | # Additional Information 40 | Make sure to set up any necessary environment variables in a .env file (not included in the repository for security reasons). Refer to the Flask app code for specific environment variables. 41 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | alabaster==0.7.16 2 | anyio==4.3.0 3 | arrow==1.3.0 4 | attrs==23.2.0 5 | Babel==2.14.0 6 | beautifulsoup4==4.12.3 7 | bibtexparser==1.4.1 8 | blinker==1.7.0 9 | certifi==2024.2.2 10 | charset-normalizer==3.3.2 11 | click==8.1.7 12 | Deprecated==1.2.14 13 | docutils==0.20.1 14 | fake-useragent==1.5.0 15 | Flask==3.0.2 16 | Flask-Cors==4.0.0 17 | free-proxy==1.1.1 18 | h11==0.14.0 19 | httpcore==1.0.4 20 | httpx==0.27.0 21 | idna==3.6 22 | imagesize==1.4.1 23 | itsdangerous==2.1.2 24 | Jinja2==3.1.3 25 | lxml==5.1.0 26 | MarkupSafe==2.1.5 27 | outcome==1.3.0.post0 28 | packaging==24.0 29 | Pygments==2.17.2 30 | pyparsing==3.1.2 31 | PySocks==1.7.1 32 | python-dateutil==2.9.0.post0 33 | python-dotenv==1.0.1 34 | requests==2.31.0 35 | scholarly==1.7.11 36 | selenium==4.18.1 37 | six==1.16.0 38 | sniffio==1.3.1 39 | snowballstemmer==2.2.0 40 | sortedcontainers==2.4.0 41 | soupsieve==2.5 42 | Sphinx==7.2.6 43 | sphinx-rtd-theme==2.0.0 44 | sphinxcontrib-applehelp==1.0.8 45 | sphinxcontrib-devhelp==1.0.6 46 | sphinxcontrib-htmlhelp==2.0.5 47 | sphinxcontrib-jquery==4.1 48 | sphinxcontrib-jsmath==1.0.1 49 | sphinxcontrib-qthelp==1.0.7 50 | sphinxcontrib-serializinghtml==1.1.10 51 | trio==0.24.0 52 | trio-websocket==0.11.1 53 | types-python-dateutil==2.8.19.20240106 54 | typing_extensions==4.10.0 55 | urllib3==2.2.1 56 | Werkzeug==3.0.1 57 | wrapt==1.16.0 58 | wsproto==1.2.0 59 | -------------------------------------------------------------------------------- /public/vite.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /agents2.py: -------------------------------------------------------------------------------- 1 | # agents2.py 2 | import requests 3 | import json 4 | import os 5 | key = os.getenv("API-KEY") 6 | api_key = key 7 | def extract_search_string(content): 8 | possible_operators = ['AND', 'OR', 'NOT', '"'] 9 | for line in content.split('\n'): 10 | if any(op in line for op in possible_operators): 11 | return line 12 | return content 13 | def generate_search_string_with_gpt(objective, research_questions): 14 | 15 | headers = { 16 | "Authorization": f"Bearer {api_key}", 17 | "Content-Type": "application/json" 18 | } 19 | # Removed the explicit instruction for logical operators 20 | combined_prompt = f"Given the research objective: '{objective}', and the following research questions: {', '.join(research_questions)}, generate two concise search string for identifying relevant literature for literature review.Do not include OR. Use AND if needed." 21 | data = { 22 | "model": "gpt-3.5-turbo", 23 | "messages": [ 24 | {"role": "system", "content": "You are a helpful assistant."}, 25 | {"role": "user", "content": combined_prompt} 26 | ], 27 | "temperature": 0.7 28 | } 29 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, data=json.dumps(data)) 30 | if response.status_code == 200: 31 | result = response.json() 32 | content = result['choices'][0]['message']['content'] 33 | search_string = extract_search_string(content) 34 | return search_string.strip() 35 | else: 36 | print(f"Error: {response.status_code}") 37 | print(response.text) 38 | return "An error occurred while generating the search string." -------------------------------------------------------------------------------- /src/index.css: -------------------------------------------------------------------------------- 1 | /* :root { 2 | font-family: Inter, system-ui, Avenir, Helvetica, Arial, sans-serif; 3 | line-height: 1.5; 4 | font-weight: 400; 5 | 6 | color-scheme: light dark; 7 | color: rgba(255, 255, 255, 0.87); 8 | background-color: #242424; 9 | 10 | font-synthesis: none; 11 | text-rendering: optimizeLegibility; 12 | -webkit-font-smoothing: antialiased; 13 | -moz-osx-font-smoothing: grayscale; 14 | } 15 | 16 | a { 17 | font-weight: 500; 18 | color: #646cff; 19 | text-decoration: inherit; 20 | } 21 | a:hover { 22 | color: #535bf2; 23 | } 24 | 25 | body { 26 | margin: 0; 27 | display: flex; 28 | place-items: center; 29 | min-width: 60vw; 30 | min-height: 100vh; 31 | } 32 | 33 | h1 { 34 | font-size: 3.2em; 35 | line-height: 1.1; 36 | } 37 | 38 | button { 39 | border-radius: 8px; 40 | border: 1px solid transparent; 41 | padding: 0.6em 1.2em; 42 | font-size: 1em; 43 | font-weight: 500; 44 | font-family: inherit; 45 | background-color: #1a1a1a; 46 | cursor: pointer; 47 | transition: border-color 0.25s; 48 | } 49 | button:hover { 50 | border-color: #646cff; 51 | } 52 | button:focus, 53 | button:focus-visible { 54 | outline: 4px auto -webkit-focus-ring-color; 55 | } 56 | 57 | @media (prefers-color-scheme: light) { 58 | :root { 59 | color: #213547; 60 | background-color: #ffffff; 61 | } 62 | a:hover { 63 | color: #747bff; 64 | } 65 | button { 66 | background-color: #f9f9f9; 67 | } 68 | } 69 | .tableContainer { 70 | overflow-x: scroll; 71 | } */ 72 | 73 | .footerFixed{ 74 | position: fixed; 75 | width: 100%; 76 | bottom: 0; 77 | } 78 | 79 | .full-page-loader { 80 | position: fixed; 81 | top: 0; 82 | left: 0; 83 | width: 100%; 84 | height: 100%; 85 | display: flex; 86 | justify-content: center; 87 | align-items: center; 88 | background-color: rgba(0, 0, 0, 0.5); /* Add a semi-transparent overlay */ 89 | z-index: 9999; /* Ensure it's on top of other content */ 90 | } 91 | -------------------------------------------------------------------------------- /src/assets/react.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /agents4.py: -------------------------------------------------------------------------------- 1 | # agent4.py 2 | import requests 3 | import os 4 | api_key = os.getenv("API-KEY") 5 | import re 6 | 7 | def check_paper_relevance_and_keywords(title, search_string): 8 | headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"} 9 | # Adjust the prompt to ask for relevance and keywords 10 | prompt = (f"Determine if the paper titled '{title}' is relevant to the topic '{search_string}'. " 11 | "and in return just informed paper is relevant or paper is not relevant, to the point.") 12 | 13 | data = { 14 | "model": "gpt-3.5-turbo", 15 | "messages": [ 16 | {"role": "system", "content": "You are a knowledgeable assistant."}, 17 | {"role": "user", "content": prompt} 18 | ] 19 | } 20 | 21 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=data) 22 | if response.status_code == 200: 23 | result = response.json() 24 | response_text = result['choices'][0]['message']['content'].strip().lower() 25 | print(response_text) 26 | # Check for explicit confirmation of relevance 27 | if "not relevant" in response_text: 28 | return False 29 | else: 30 | # Assuming the model lists keywords after confirming relevance 31 | # Extracting keywords from the response assuming they are listed after "key words:" phrase 32 | return True 33 | else: 34 | print(f"Error: {response.status_code}, Detail: {response.text}") 35 | 36 | return (False, []) 37 | 38 | def filter_papers_with_gpt_turbo(search_string, papers): 39 | 40 | filtered_papers = [] 41 | 42 | for paper in papers: 43 | title = paper['title'] 44 | if check_paper_relevance_and_keywords(title, search_string): 45 | filtered_papers.append(paper) 46 | 47 | return filtered_papers 48 | 49 | 50 | def is_response_relevant(response): 51 | # Define a pattern that matches sentences indicating irrelevance 52 | irrelevance_pattern = re.compile(r"does not appear to be directly relevant", re.IGNORECASE) 53 | 54 | # Define a pattern that matches sentences indicating relevance 55 | relevance_pattern = re.compile(r"topics related", re.IGNORECASE) 56 | 57 | # Check for irrelevance 58 | if irrelevance_pattern.search(response): 59 | return False # Irrelevant based on the matched pattern 60 | 61 | # Check for relevance 62 | if relevance_pattern.search(response): 63 | return True # Relevant based on the matched pattern 64 | 65 | # If neither pattern is matched, you might decide based on other criteria or default assumption 66 | return None # Or False/True based on your default assumption 67 | 68 | 69 | def generate_response_gpt4_turbo(question, papers_info): 70 | messages = [{ 71 | "role": "system", 72 | "content": "You are a knowledgeable assistant who can answer research questions based on provided papers information." 73 | }] 74 | 75 | papers_context = "\n".join([f"- Title: '{paper['title']}', Author: {paper['creator']}, Year: {paper['year']}'." for paper in papers_info]) 76 | messages.append({ 77 | "role": "system", 78 | "content": f"Research Question: {question}\n\nPapers Information:\n{papers_context}" 79 | }) 80 | 81 | messages.append({ 82 | "role": "user", 83 | "content": "Based on the provided papers information, please answer the research question and cite relevant references for cross-verification." 84 | }) 85 | 86 | headers = { 87 | "Authorization": f"Bearer {api_key}", 88 | "Content-Type": "application/json", 89 | } 90 | 91 | data = { 92 | "model": "gpt-4-turbo-preview", 93 | "messages": messages, 94 | "temperature": 0.7, 95 | "max_tokens": 256 96 | } 97 | 98 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=data, timeout=800) 99 | 100 | if response.status_code == 200: 101 | result = response.json() 102 | latest_response = result['choices'][0]['message']['content'] 103 | return latest_response 104 | else: 105 | print(f"Error: {response.status_code}") 106 | print(response.text) 107 | return "An error occurred while generating the response." -------------------------------------------------------------------------------- /agents3.py: -------------------------------------------------------------------------------- 1 | from scholarly import scholarly 2 | import csv 3 | from scholarly import ProxyGenerator, scholarly 4 | import os 5 | import requests 6 | 7 | api_key = os.getenv('ELSEVIER_API_KEY') 8 | # Initialize a global variable to track if the proxy setup has been done 9 | proxy_setup_done = False 10 | 11 | def setup_proxy(): 12 | global proxy_setup_done 13 | # Check if the proxy setup has already been done 14 | if not proxy_setup_done: 15 | # Set up a ProxyGenerator object to use free proxies 16 | pg = ProxyGenerator() 17 | pg.FreeProxies() 18 | scholarly.use_proxy(pg) 19 | 20 | # Mark the setup as done 21 | proxy_setup_done = True 22 | print("Proxy setup completed.") 23 | else: 24 | print("Proxy setup was already completed earlier in this session.") 25 | 26 | # Example usage 27 | setup_proxy() 28 | 29 | 30 | 31 | 32 | def fetch_papers(search_string, min_results=8): 33 | search_query = scholarly.search_pubs(search_string) 34 | papers_details = [] 35 | for _ in range(min_results): 36 | try: 37 | paper = next(search_query) 38 | paper_details = { 39 | 'title': paper['bib']['title'], 40 | 'author': paper['bib'].get('author'), 41 | 'pub_year': paper['bib'].get('pub_year'), 42 | 'publication_url': paper.get('pub_url', 'Not Available'), 43 | 'journal_name': paper['bib'].get('journal', 'Not Available'), 44 | # Attempting to extract DOI, publication date, and making an educated guess on paper type 45 | 'doi': paper.get('doi', 'Not Available'), 46 | 'publication_date': paper['bib'].get('pub_year', 'Not Available'), # Simplified to publication year 47 | 'paper_type': 'Journal' if 'journal' in paper['bib'] else 'Conference' if 'conference' in paper['bib'] else 'Primary Study' # Simplistic categorization 48 | } 49 | papers_details.append(paper_details) 50 | except StopIteration: 51 | break # Exit if there are no more results 52 | return papers_details 53 | 54 | 55 | def save_papers_to_csv(papers_details, filename='papers.csv'): 56 | fieldnames = ['title', 'author', 'pub_year', 'publication_url', 'journal_name', 'doi', 'publication_date', 'paper_type'] 57 | with open(filename, mode='w', newline='', encoding='utf-8') as file: 58 | writer = csv.DictWriter(file, fieldnames=fieldnames) 59 | writer.writeheader() 60 | for paper in papers_details: 61 | writer.writerow(paper) 62 | 63 | 64 | 65 | 66 | def search_elsevier(search_string, start_year, end_year, limit): 67 | 68 | url = "https://api.elsevier.com/content/search/scopus" 69 | headers = { 70 | "X-ELS-APIKey": api_key, 71 | "Accept": "application/json" 72 | } 73 | 74 | query = f"TITLE-ABS-KEY({search_string}) AND PUBYEAR = {start_year}" 75 | params = { 76 | "query": query, 77 | "count": limit, 78 | } 79 | 80 | 81 | response = requests.get(url, headers=headers, params=params) 82 | if response.status_code == 200: 83 | response_data = response.json() 84 | papers = response_data.get('search-results', {}).get('entry', []) 85 | parsed_papers = [] 86 | for paper in papers: 87 | parsed_paper = { 88 | "affiliation-country": next((affil.get("affiliation-country", "Not Available") for affil in paper.get("affiliation", [])), "Not Available"), 89 | "affilname": next((affil.get("affilname", "Not Available") for affil in paper.get("affiliation", [])), "Not Available"), 90 | "creator": paper.get("dc:creator", "Not Available"), 91 | "identifier": paper.get("dc:identifier", "Not Available"), 92 | "title": paper.get("dc:title", "Not Available"), 93 | "link": next((link["@href"] for link in paper.get("link", []) if link["@ref"] == "scopus"), "Not Available"), 94 | "year": paper.get("prism:coverDate", "Not Available").split("-")[0], 95 | "openaccess": paper.get("openaccess", "0") == "1", 96 | "publicationName": paper.get("prism:publicationName", "Not Available"), 97 | "aggregationType": paper.get("prism:aggregationType", "Not Available"), 98 | "volume": paper.get("prism:volume", "Not Available"), 99 | "doi": paper.get("prism:doi", "Not Available") 100 | } 101 | parsed_papers.append(parsed_paper) 102 | return parsed_papers 103 | else: 104 | print(f"Failed to fetch papers: {response.status_code} {response.text}") 105 | return {"error": "Failed to fetch papers from Elsevier", "status_code": response.status_code, "message": response.text} -------------------------------------------------------------------------------- /agents.py: -------------------------------------------------------------------------------- 1 | # agents.py 2 | import requests 3 | import json 4 | from flask import jsonify 5 | import os 6 | key = os.getenv("API-KEY") 7 | api_key = key 8 | import re # Import the regular expressions library 9 | 10 | def generate_research_questions_and_purpose_with_gpt(objective, num_questions): 11 | 12 | headers = { 13 | "Authorization": f"Bearer {api_key}", 14 | "Content-Type": "application/json" 15 | } 16 | # Construct the prompt dynamically 17 | prompt_content = f"You are a helpful assistant capable of generating research questions along with their purposes for a systematic literature review.\n" 18 | prompt_content = f"Given the research objective: '{objective}', generate {num_questions} distinct research questions, each followed by its specific purpose. 'To examine', or 'To investigate'." 19 | data = { 20 | "model": "gpt-3.5-turbo", 21 | "messages": [ 22 | {"role": "system", "content": "You are a helpful assistant capable of generating research questions along with their purposes for a systematic literature review."}, 23 | {"role": "user", "content": prompt_content} 24 | ], 25 | "temperature": 0.7 26 | } 27 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, data=json.dumps(data)) 28 | if response.status_code == 200: 29 | result = response.json() 30 | messages = result['choices'][0]['message']['content'] 31 | lines = [line for line in messages.strip().split('\n') if line] 32 | 33 | question_purpose_objects = [] 34 | for i in range(0, len(lines), 2): 35 | # Using regex to dynamically remove "Research question X:" where X is any number 36 | question = re.sub(r"^Research question( \d+)?: ", "", lines[i], flags=re.IGNORECASE) 37 | purpose = lines[i+1] if i+1 < len(lines) else "Purpose not provided" 38 | # Optionally, remove the prefix from purpose if needed 39 | # purpose = purpose.replace("Purpose: ", "") 40 | question_purpose_objects.append({"question": question, "purpose": purpose}) 41 | 42 | if num_questions == 1 and question_purpose_objects: 43 | 44 | return {"research_questions": question_purpose_objects} 45 | else: 46 | return {"research_questions": question_purpose_objects} 47 | else: 48 | print(f"Error: {response.status_code}") 49 | print(response.text) 50 | return [] 51 | 52 | 53 | 54 | def generate_summary_conclusion(papers_info): 55 | headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"} 56 | 57 | prompt_parts = ["Summarize the conclusions of the following papers:"] 58 | for paper in papers_info: 59 | title = paper.get("title") 60 | author = paper.get("creator", "An author") 61 | year = paper.get("year", "A year") 62 | prompt_parts.append(f"- '{title}' by {author} ({year})") 63 | prompt = " ".join(prompt_parts) 64 | 65 | data = { 66 | "model": "gpt-3.5-turbo", 67 | "messages": [ 68 | {"role": "system", "content": "You are a helpful assistant."}, 69 | {"role": "user", "content": prompt}, 70 | ], 71 | } 72 | 73 | response = requests.post( 74 | "https://api.openai.com/v1/chat/completions", 75 | headers=headers, 76 | data=json.dumps(data), 77 | ) 78 | 79 | if response.status_code == 200: 80 | result = response.json() 81 | content = result["choices"][0]["message"]["content"] 82 | summary_conclusion = content.strip() 83 | else: 84 | return jsonify({"error": "Failed to generate a summary conclusion."}), 500 85 | 86 | return summary_conclusion 87 | 88 | 89 | def generate_abstract_with_openai(prompt): 90 | """Generates a summary abstract using OpenAI's GPT model based on the provided prompt.""" 91 | # Fetching the API key from environment variables for better security practice 92 | 93 | headers = { 94 | "Authorization": f"Bearer {api_key}", # Using the API key from environment variables 95 | "Content-Type": "application/json" 96 | } 97 | data = { 98 | "model": "gpt-3.5-turbo", 99 | "messages": [ 100 | {"role": "system", "content": "You are a helpful assistant."}, 101 | {"role": "user", "content": prompt} 102 | ] 103 | } 104 | 105 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, data=json.dumps(data)) 106 | if response.status_code == 200: 107 | result = response.json() 108 | content = result['choices'][0]['message']['content'] 109 | return content.strip() 110 | else: 111 | raise Exception("Failed to generate a summary abstract from OpenAI.") 112 | 113 | 114 | def generate_introduction_summary_with_openai(prompt): 115 | headers = { 116 | "Authorization": f"Bearer {api_key}", 117 | "Content-Type": "application/json" 118 | } 119 | data = { 120 | "model": "gpt-3.5-turbo", 121 | "messages": [ 122 | {"role": "system", "content": "You are a helpful assistant."}, 123 | {"role": "user", "content": prompt} 124 | ] 125 | } 126 | response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, data=json.dumps(data)) 127 | if response.status_code == 200: 128 | result = response.json() 129 | content = result['choices'][0]['message']['content'] 130 | return content.strip() 131 | else: 132 | raise Exception("Failed to generate the introduction summary from OpenAI.") 133 | -------------------------------------------------------------------------------- /src/columns.jsx: -------------------------------------------------------------------------------- 1 | import React from 'react'; 2 | 3 | 4 | export const columns = [ 5 | { 6 | title: 'No', 7 | dataIndex: 'index', 8 | key: 'index', 9 | width: 80, 10 | render: (text, record, index) => index + 1, // Renders the row number 11 | }, 12 | { 13 | title: 'Purpose', 14 | dataIndex: 'purpose', 15 | key: 'purpose', 16 | width: 500 17 | }, 18 | { 19 | title: 'Question', 20 | dataIndex: 'question', 21 | key: 'question', 22 | width: 500 23 | }, 24 | ]; 25 | 26 | 27 | export const paperColumns = (papersFilterData, handleCheckboxChange) => [ 28 | { 29 | width: 65, 30 | title: 'Filter', 31 | dataIndex: 'checkbox', 32 | render: (_, record) => ( 33 | handleCheckboxChange(record)} 37 | /> 38 | ), 39 | }, 40 | { 41 | title: 'No', 42 | dataIndex: 'index', 43 | key: 'index', 44 | width: 80, 45 | render: (text, record, index) => index + 1, // Renders the row number 46 | }, 47 | { title: 'Title', dataIndex: 'title', key: 'title', width: 200 }, 48 | { title: 'Author', dataIndex: 'creator', key: 'creator', width: 100 }, 49 | 50 | { title: 'Publication URL', dataIndex: 'link', key: 'link', width: 400 }, 51 | { title: 'Journal Name', dataIndex: 'publicationName', key: 'publicationName', width: 200 }, 52 | { title: 'DOI', dataIndex: 'doi', key: 'doi', width: 200 }, 53 | { title: 'Paper Type', dataIndex: 'aggregationType', key: 'aggregationType', width: 150 }, 54 | { title: 'Affiliation Country', dataIndex: 'affiliation-country', key: 'affiliation-country', width: 100 }, 55 | { title: 'Affiliation Name', dataIndex: 'affilname', key: 'affilname', width: 200 }, 56 | { title: 'Volume', dataIndex: 'volume', key: 'volume', width: 90 }, 57 | { title: 'Publication Year', dataIndex: 'year', key: 'year', width: 90 }, 58 | { title: 'Open Access', dataIndex: 'openaccess', key: 'openaccess', render: text => text ? 'Yes' : 'No', width: 150 }, // Assuming openaccess is a boolean 59 | ]; 60 | 61 | 62 | // export const paperColumns= (papersFilterData, handleCheckboxChange) => [ 63 | // { 64 | // width:65, 65 | // title: 'Filter', 66 | // dataIndex: 'checkbox', 67 | // render: (_, record) => ( 68 | // handleCheckboxChange(record)} 72 | // /> 73 | // ), 74 | // }, 75 | // { 76 | // title: 'No', 77 | // dataIndex: 'index', 78 | // key: 'index', 79 | // width: 80, 80 | // render: (text, record, index) => index + 1, // Renders the row number 81 | // }, 82 | // { title: 'Title', dataIndex: 'title', key: 'title', width: 200 }, 83 | // { title: 'Author', dataIndex: 'creator', key: 'creator', width: 100 }, 84 | 85 | // { title: 'Publication URL', dataIndex: 'link', key: 'link', width: 400 }, 86 | // { title: 'Journal Name', dataIndex: 'publicationName', key: 'publicationName', width: 200 }, 87 | // { title: 'DOI', dataIndex: 'doi', key: 'doi', width: 200 }, 88 | // { title: 'Paper Type', dataIndex: 'aggregationType', key: 'aggregationType', width: 150 }, 89 | // { title: 'Affiliation Country', dataIndex: 'affiliation-country', key: 'affiliation-country', width: 100 }, 90 | // { title: 'Affiliation Name', dataIndex: 'affilname', key: 'affilname', width: 200 }, 91 | // { title: 'Volume', dataIndex: 'volume', key: 'volume', width: 90 }, 92 | // { title: 'Publication Year', dataIndex: 'year', key: 'year', width: 90 }, 93 | // { title: 'Open Access', dataIndex: 'openaccess', key: 'openaccess', render: text => text ? 'Yes' : 'No', width: 150 }, // Assuming openaccess is a boolean 94 | // ]; 95 | 96 | export const filterColumns = [ 97 | { 98 | title: 'No', 99 | dataIndex: 'index', 100 | key: 'index', 101 | width: 80, 102 | render: (text, record, index) => index + 1, // Renders the row number 103 | }, 104 | { title: 'Title', dataIndex: 'title', key: 'title', width: 200 }, 105 | { title: 'Author', dataIndex: 'creator', key: 'creator', width: 100 }, 106 | 107 | { title: 'Publication URL', dataIndex: 'link', key: 'link', width: 400 }, 108 | { title: 'Journal Name', dataIndex: 'publicationName', key: 'publicationName', width: 200 }, 109 | { title: 'DOI', dataIndex: 'doi', key: 'doi', width: 200 }, 110 | { title: 'Paper Type', dataIndex: 'aggregationType', key: 'aggregationType', width: 150 }, 111 | { title: 'Affiliation Country', dataIndex: 'affiliation-country', key: 'affiliation-country', width: 100 }, 112 | { title: 'Affiliation Name', dataIndex: 'affilname', key: 'affilname', width: 200 }, 113 | { title: 'Volume', dataIndex: 'volume', key: 'volume', width: 90 }, 114 | { title: 'Publication Year', dataIndex: 'year', key: 'year', width: 90 }, 115 | { title: 'Open Access', dataIndex: 'openaccess', key: 'openaccess', render: text => text ? 'Yes' : 'No', width: 150 }, // Assuming openaccess is a boolean 116 | ]; 117 | 118 | export const answers = [ 119 | { 120 | title: 'No', 121 | dataIndex: 'index', 122 | key: 'index', 123 | width: 80, 124 | render: (text, record, index) => index + 1, // Renders the row number 125 | }, 126 | { 127 | title: 'Question', 128 | dataIndex: 'question', 129 | key: 'question', 130 | width: 280 131 | }, 132 | { 133 | title: 'Answer', 134 | dataIndex: 'answer', 135 | key: 'answer', 136 | }, 137 | ]; -------------------------------------------------------------------------------- /server.py: -------------------------------------------------------------------------------- 1 | from dotenv import load_dotenv 2 | import os 3 | import tempfile 4 | from flask import Flask, render_template,send_file, send_from_directory, request, jsonify 5 | import datetime 6 | from agents import generate_research_questions_and_purpose_with_gpt, generate_abstract_with_openai, generate_summary_conclusion, generate_introduction_summary_with_openai 7 | import json 8 | from agents2 import generate_search_string_with_gpt 9 | from agents3 import fetch_papers, save_papers_to_csv, search_elsevier 10 | from agents4 import filter_papers_with_gpt_turbo, generate_response_gpt4_turbo 11 | from flask_cors import CORS 12 | import requests 13 | from datetime import datetime 14 | 15 | load_dotenv() 16 | # x = datetime.datetime.now() 17 | 18 | key = os.getenv("ELSEVIER_API_KEY") 19 | 20 | app = Flask(__name__, static_folder='dist') 21 | CORS(app) 22 | @app.route('/api/generate_search_string', methods=['POST']) 23 | def generate_search_string_route(): 24 | data = request.json 25 | objective = data.get('objective') 26 | research_questions = data.get('research_questions', []) # Default to an empty list if not provided 27 | 28 | if not objective or not research_questions: 29 | return jsonify({"error": "Objective and research questions are required."}), 400 30 | 31 | search_string = generate_search_string_with_gpt(objective, research_questions) 32 | return jsonify({"search_string": search_string}) 33 | @app.route('/api/generate_research_questions_and_purpose', methods=['POST']) 34 | 35 | def generate_research_questions_and_purpose(): 36 | print("request:", request.method) 37 | data = request.json 38 | objective = data.get('objective') 39 | num_questions = int(data.get('num_questions', 1)) # Ensure num_questions is treated as an integer 40 | 41 | # Validate input 42 | if not objective: 43 | return jsonify({"error": "Objective is required"}), 400 44 | if num_questions < 1: 45 | return jsonify({"error": "Number of questions must be at least 1"}), 400 46 | 47 | questions_and_purposes = generate_research_questions_and_purpose_with_gpt(objective, num_questions) 48 | print(questions_and_purposes) 49 | return jsonify({"research_questions": questions_and_purposes}) 50 | 51 | 52 | # Agent 4 53 | 54 | @app.route('/api/filter_papers', methods=['POST']) 55 | def filter_papers_route(): 56 | data = request.json 57 | search_string = data.get('search_string', '') 58 | papers = data.get('papers', []) # Expecting only titles in papers 59 | 60 | filtered_papers = filter_papers_with_gpt_turbo(search_string, papers) 61 | return jsonify({"filtered_papers": filtered_papers}) 62 | 63 | 64 | @app.route('/api/answer_question', methods=['POST']) 65 | def answer_question(): 66 | data = request.json 67 | questions = data.get('questions') # This should now be a list of questions 68 | papers_info = data.get('papers_info', []) 69 | 70 | if not questions or not papers_info: 71 | return jsonify({"error": "Both questions and papers information are required."}), 400 72 | 73 | answers = [] 74 | for question in questions: 75 | answer = generate_response_gpt4_turbo(question, papers_info) 76 | answers.append({"question": question, "answer": answer}) 77 | 78 | return jsonify({"answers": answers}) 79 | 80 | 81 | @app.route('/api/generate-summary-abstract', methods=['POST']) 82 | def generate_summary_abstract(): 83 | try: 84 | data = request.json 85 | 86 | research_questions = data.get('research_questions', 'No research questions provided.') 87 | objective = data.get('objective', 'No objective provided.') 88 | search_string = data.get('search_string', 'No search string provided.') 89 | 90 | # Constructing the prompt for AI abstract generation 91 | prompt = f"Based on the research questions '{research_questions}', the objective '{objective}', and the search string '{search_string}', generate a comprehensive abstract." 92 | 93 | # Generate the abstract using OpenAI's GPT model 94 | summary_abstract = generate_abstract_with_openai(prompt) 95 | 96 | return jsonify({"summary_abstract": summary_abstract}) 97 | except Exception as e: 98 | return jsonify({"error": str(e)}), 500 99 | 100 | 101 | @app.route("/api/generate-summary-conclusion", methods=["POST"]) 102 | def generate_summary_conclusion_route(): 103 | data = request.json 104 | papers_info = data.get("papers_info", []) 105 | try: 106 | summary_conclusion = generate_summary_conclusion(papers_info) 107 | return jsonify({"summary_conclusion": summary_conclusion}) 108 | except Exception as e: 109 | return jsonify({"error": str(e)}), 500 110 | 111 | @app.route('/api/generate-introduction-summary', methods=['POST']) 112 | def generate_introduction_summary(): 113 | try: 114 | data = request.json 115 | total_papers = len(data.get("all_papers", [])) 116 | filtered_papers_count = len(data.get("filtered_papers", [])) 117 | research_questions = data.get("research_questions", []) 118 | objective = data.get("objective", "") 119 | search_string = data.get("search_string", "") 120 | answers = data.get("answers", []) 121 | 122 | # Constructing the introduction based on the provided data 123 | prompt_intro = f"This document synthesizes findings from {total_papers} papers related to \"{search_string}\". Specifically, {filtered_papers_count} papers were thoroughly examined. The primary objective is {objective}." 124 | 125 | prompt_questions = "\n\nResearch Questions:\n" + "\n".join([f"- {q}" for q in research_questions]) 126 | 127 | prompt_answers = "\n\nSummary of Findings:\n" + "\n".join([f"- {ans['question']}: {ans['answer'][:250]}..." for ans in answers]) # Brief summary of answers 128 | 129 | prompt = prompt_intro + prompt_questions + prompt_answers + "\n\nGenerate a coherent introduction and summary based on this compilation." 130 | 131 | # Generating the introduction summary using OpenAI's GPT model 132 | introduction_summary = generate_introduction_summary_with_openai(prompt) 133 | 134 | return jsonify({"introduction_summary": introduction_summary}) 135 | except Exception as e: 136 | return jsonify({"error": str(e)}), 500 137 | 138 | 139 | @app.route("/api/generate-summary-all", methods=["POST"]) 140 | def generate_summary_all_route(): 141 | data = request.json 142 | abstract_summary = data.get("abstract_summary", "") 143 | intro_summary = data.get("intro_summary", "") # Corrected key to "intro_summary" 144 | conclusion_summary = data.get("conclusion_summary", "") # Corrected key to "conclusion_summary" 145 | 146 | try: 147 | # Assuming you have a LaTeX template named 'latex_template.tex' in the 'templates' folder 148 | print("inside") 149 | latex_content = render_template( 150 | "latex_template.tex", 151 | abstract=abstract_summary, 152 | introduction=intro_summary, 153 | conclusion=conclusion_summary, 154 | ) 155 | 156 | # Save the LaTeX content to a file in the same directory as this script 157 | current_time = datetime.now().strftime('%Y%m%d%H%M%S') 158 | milliseconds = datetime.now().microsecond // 1000 159 | file_path = os.path.join(os.path.dirname(__file__), f"{current_time}_{milliseconds}summary.tex") 160 | print(file_path) 161 | with open(file_path, "w", encoding="utf-8") as file: 162 | file.write(latex_content) 163 | with tempfile.NamedTemporaryFile(mode='w+', suffix='.tex', delete=False, encoding='utf-8') as temp_file: 164 | temp_file.write(latex_content) 165 | temp_file_path = temp_file.name 166 | return send_file(temp_file_path, as_attachment=True, download_name='paper_summary.tex') 167 | # return jsonify({"latex_file_path": file_path}) 168 | except Exception as e: 169 | return jsonify({"error": str(e)}), 500 170 | 171 | # # Route for serving static files (like manifest.json) 172 | @app.route('/') 173 | def index(): 174 | return send_from_directory(app.static_folder, 'index.html') 175 | @app.route('/') 176 | def serve(path): 177 | print("filename:", app.static_folder+ "/" + path) 178 | if path != "" and os.path.exists(app.static_folder+ "/" + path): 179 | return send_from_directory(app.static_folder, path) 180 | else: 181 | return send_from_directory(app.static_folder, 'index.html') 182 | # return send_from_directory('templates/static/', filename) 183 | # # Route for rendering the React app 184 | # @app.route('/') 185 | # def index(): 186 | # print("calling") 187 | # return render_template('index.html') 188 | 189 | 190 | 191 | 192 | 193 | @app.route('/api/search_papers', methods=['POST']) 194 | def search_papers(): 195 | data = request.json 196 | search_string = data.get('search_string', '') 197 | start_year = data.get('start_year', '') 198 | end_year = data.get('end_year', '') 199 | limit = data.get('limit', 4) # Default limit to 10 papers if not specified 200 | 201 | if not search_string or not start_year: 202 | return jsonify({'error': 'Search string and start year are required.'}), 400 203 | 204 | results = search_elsevier(search_string, start_year, end_year, limit) 205 | return jsonify(results) 206 | 207 | # Running app 208 | if __name__ == '__main__': 209 | app.run(debug=True) 210 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. Definitions. 8 | 9 | "License" shall mean the terms and conditions for use, reproduction, 10 | and distribution as defined by Sections 1 through 9 of this document. 11 | 12 | "Licensor" shall mean the copyright owner or entity authorized by 13 | the copyright owner that is granting the License. 14 | 15 | "Legal Entity" shall mean the union of the acting entity and all 16 | other entities that control, are controlled by, or are under common 17 | control with that entity. For the purposes of this definition, 18 | "control" means (i) the power, direct or indirect, to cause the 19 | direction or management of such entity, whether by contract or 20 | otherwise, or (ii) ownership of fifty percent (50%) or more of the 21 | outstanding shares, or (iii) beneficial ownership of such entity. 22 | 23 | "You" (or "Your") shall mean an individual or Legal Entity 24 | exercising permissions granted by this License. 25 | 26 | "Source" form shall mean the preferred form for making modifications, 27 | including but not limited to software source code, documentation 28 | source, and configuration files. 29 | 30 | "Object" form shall mean any form resulting from mechanical 31 | transformation or translation of a Source form, including but 32 | not limited to compiled object code, generated documentation, 33 | and conversions to other media types. 34 | 35 | "Work" shall mean the work of authorship, whether in Source or 36 | Object form, made available under the License, as indicated by a 37 | copyright notice that is included in or attached to the work 38 | (an example is provided in the Appendix below). 39 | 40 | "Derivative Works" shall mean any work, whether in Source or Object 41 | form, that is based on (or derived from) the Work and for which the 42 | editorial revisions, annotations, elaborations, or other modifications 43 | represent, as a whole, an original work of authorship. For the purposes 44 | of this License, Derivative Works shall not include works that remain 45 | separable from, or merely link (or bind by name) to the interfaces of, 46 | the Work and Derivative Works thereof. 47 | 48 | "Contribution" shall mean any work of authorship, including 49 | the original version of the Work and any modifications or additions 50 | to that Work or Derivative Works thereof, that is intentionally 51 | submitted to Licensor for inclusion in the Work by the copyright owner 52 | or by an individual or Legal Entity authorized to submit on behalf of 53 | the copyright owner. For the purposes of this definition, "submitted" 54 | means any form of electronic, verbal, or written communication sent 55 | to the Licensor or its representatives, including but not limited to 56 | communication on electronic mailing lists, source code control systems, 57 | and issue tracking systems that are managed by, or on behalf of, the 58 | Licensor for the purpose of discussing and improving the Work, but 59 | excluding communication that is conspicuously marked or otherwise 60 | designated in writing by the copyright owner as "Not a Contribution." 61 | 62 | "Contributor" shall mean Licensor and any individual or Legal Entity 63 | on behalf of whom a Contribution has been received by Licensor and 64 | subsequently incorporated within the Work. 65 | 66 | 2. Grant of Copyright License. Subject to the terms and conditions of 67 | this License, each Contributor hereby grants to You a perpetual, 68 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 69 | copyright license to reproduce, prepare Derivative Works of, 70 | publicly display, publicly perform, sublicense, and distribute the 71 | Work and such Derivative Works in Source or Object form. 72 | 73 | 3. Grant of Patent License. Subject to the terms and conditions of 74 | this License, each Contributor hereby grants to You a perpetual, 75 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 76 | (except as stated in this section) patent license to make, have made, 77 | use, offer to sell, sell, import, and otherwise transfer the Work, 78 | where such license applies only to those patent claims licensable 79 | by such Contributor that are necessarily infringed by their 80 | Contribution(s) alone or by combination of their Contribution(s) 81 | with the Work to which such Contribution(s) was submitted. If You 82 | institute patent litigation against any entity (including a 83 | cross-claim or counterclaim in a lawsuit) alleging that the Work 84 | or a Contribution incorporated within the Work constitutes direct 85 | or contributory patent infringement, then any patent licenses 86 | granted to You under this License for that Work shall terminate 87 | as of the date such litigation is filed. 88 | 89 | 4. Redistribution. You may reproduce and distribute copies of the 90 | Work or Derivative Works thereof in any medium, with or without 91 | modifications, and in Source or Object form, provided that You 92 | meet the following conditions: 93 | 94 | (a) You must give any other recipients of the Work or 95 | Derivative Works a copy of this License; and 96 | 97 | (b) You must cause any modified files to carry prominent notices 98 | stating that You changed the files; and 99 | 100 | (c) You must retain, in the Source form of any Derivative Works 101 | that You distribute, all copyright, patent, trademark, and 102 | attribution notices from the Source form of the Work, 103 | excluding those notices that do not pertain to any part of 104 | the Derivative Works; and 105 | 106 | (d) If the Work includes a "NOTICE" text file as part of its 107 | distribution, then any Derivative Works that You distribute must 108 | include a readable copy of the attribution notices contained 109 | within such NOTICE file, excluding those notices that do not 110 | pertain to any part of the Derivative Works, in at least one 111 | of the following places: within a NOTICE text file distributed 112 | as part of the Derivative Works; within the Source form or 113 | documentation, if provided along with the Derivative Works; or, 114 | within a display generated by the Derivative Works, if and 115 | wherever such third-party notices normally appear. The contents 116 | of the NOTICE file are for informational purposes only and 117 | do not modify the License. You may add Your own attribution 118 | notices within Derivative Works that You distribute, alongside 119 | or as an addendum to the NOTICE text from the Work, provided 120 | that such additional attribution notices cannot be construed 121 | as modifying the License. 122 | 123 | You may add Your own copyright statement to Your modifications and 124 | may provide additional or different license terms and conditions 125 | for use, reproduction, or distribution of Your modifications, or 126 | for any such Derivative Works as a whole, provided Your use, 127 | reproduction, and distribution of the Work otherwise complies with 128 | the conditions stated in this License. 129 | 130 | 5. Submission of Contributions. Unless You explicitly state otherwise, 131 | any Contribution intentionally submitted for inclusion in the Work 132 | by You to the Licensor shall be under the terms and conditions of 133 | this License, without any additional terms or conditions. 134 | Notwithstanding the above, nothing herein shall supersede or modify 135 | the terms of any separate license agreement you may have executed 136 | with Licensor regarding such Contributions. 137 | 138 | 6. Trademarks. This License does not grant permission to use the trade 139 | names, trademarks, service marks, or product names of the Licensor, 140 | except as required for reasonable and customary use in describing the 141 | origin of the Work and reproducing the content of the NOTICE file. 142 | 143 | 7. Disclaimer of Warranty. Unless required by applicable law or 144 | agreed to in writing, Licensor provides the Work (and each 145 | Contributor provides its Contributions) on an "AS IS" BASIS, 146 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or 147 | implied, including, without limitation, any warranties or conditions 148 | of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A 149 | PARTICULAR PURPOSE. You are solely responsible for determining the 150 | appropriateness of using or redistributing the Work and assume any 151 | risks associated with Your exercise of permissions under this License. 152 | 153 | 8. Limitation of Liability. In no event and under no legal theory, 154 | whether in tort (including negligence), contract, or otherwise, 155 | unless required by applicable law (such as deliberate and grossly 156 | negligent acts) or agreed to in writing, shall any Contributor be 157 | liable to You for damages, including any direct, indirect, special, 158 | incidental, or consequential damages of any character arising as a 159 | result of this License or out of the use or inability to use the 160 | Work (including but not limited to damages for loss of goodwill, 161 | work stoppage, computer failure or malfunction, or any and all 162 | other commercial damages or losses), even if such Contributor 163 | has been advised of the possibility of such damages. 164 | 165 | 9. Accepting Warranty or Additional Liability. While redistributing 166 | the Work or Derivative Works thereof, You may choose to offer, 167 | and charge a fee for, acceptance of support, warranty, indemnity, 168 | or other liability obligations and/or rights consistent with this 169 | License. However, in accepting such obligations, You may act only 170 | on Your own behalf and on Your sole responsibility, not on behalf 171 | of any other Contributor, and only if You agree to indemnify, 172 | defend, and hold each Contributor harmless for any liability 173 | incurred by, or claims asserted against, such Contributor by reason 174 | of your accepting any such warranty or additional liability. 175 | 176 | END OF TERMS AND CONDITIONS 177 | 178 | APPENDIX: How to apply the Apache License to your work. 179 | 180 | To apply the Apache License to your work, attach the following 181 | boilerplate notice, with the fields enclosed by brackets "[]" 182 | replaced with your own identifying information. (Don't include 183 | the brackets!) The text should be enclosed in the appropriate 184 | comment syntax for the file format. We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [yyyy] [name of copyright owner] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /src/App.jsx: -------------------------------------------------------------------------------- 1 | import React, { useState, useRef } from "react"; 2 | import "./App.css"; 3 | import { RQicon } from './mysvg' 4 | import { Button, Divider, Form, Input, Layout, Space, Table, notification } from "antd"; 5 | import { Content, Footer, Header } from "antd/es/layout/layout"; 6 | import { SearchOutlined } from '@ant-design/icons'; 7 | import TextArea from "antd/es/input/TextArea"; 8 | import FullPageLoader from "./FullPageLoader"; 9 | import { answers, columns, filterColumns, paperColumns } from "./columns"; 10 | 11 | function App() { 12 | const [loading, setLoading] = useState(false) 13 | const contentRef = useRef(); 14 | const scrollToBottom = () => { 15 | let elem = document.getElementById("mainContainer") 16 | setTimeout(()=>{ 17 | elem.scroll(0,elem.scrollHeight) 18 | }, 300) 19 | }; 20 | 21 | const [name, setName] = useState("'My work aims to systematically identify and analyze, the literature on Large language models in software development'"); 22 | const [noOfQuestion, setNoOfQuestions] = useState(2) 23 | const [researchQuestions, setResearchQuestions] = useState([]) 24 | const [researchQuestionApiResponse, setResearchQuestionApiResponse] = useState() 25 | const [searchString, setSearchString] = useState('') 26 | const [start_year, setstartYear] = useState(2023) 27 | const [end_year, setEndYear] = useState(2020) 28 | 29 | const generateSearchString = async (e) => { 30 | e.preventDefault(); 31 | try { 32 | setLoading(true) 33 | const response = await fetch("/api/generate_search_string", { 34 | method: "post", 35 | headers: { 36 | "Content-Type": "application/json", 37 | }, 38 | body: JSON.stringify({ 39 | objective: name, 40 | research_questions: researchQuestions 41 | }) 42 | }); 43 | const message = await response.json(); 44 | setSearchString( 45 | message.search_string 46 | .replace(/^\d+\.\s*/, '') // Remove any leading digits and dots 47 | .replace(/\bAND\b/g, 'OR') // Replace "AND" with "OR" 48 | .replace(/[()]/g, '') // Remove parentheses 49 | ); 50 | setLoading(false) 51 | scrollToBottom() 52 | notification.success({ 53 | message:"Search String Generated" 54 | }) 55 | } catch (e) { 56 | notification.error({ 57 | message: `internal Server Error` 58 | }) 59 | setLoading(false) 60 | } 61 | } 62 | const [papersData, setPapersData] = useState() 63 | const [limitPaper, setLimitPaper] = useState(10) 64 | const fetchAndSavePapers = async (e) => { 65 | e.preventDefault(); 66 | try { 67 | setLoading(true) 68 | const response = await fetch("/api/search_papers", { 69 | method: "post", 70 | headers: { 71 | "Content-Type": "application/json", 72 | }, 73 | body: JSON.stringify({ 74 | search_string: searchString, 75 | start_year: start_year, 76 | limit: limitPaper 77 | }) 78 | }); 79 | const message = await response.json(); 80 | if (message) { 81 | setPapersData(message) 82 | } 83 | scrollToBottom() 84 | setLoading(false) 85 | notification.success({ 86 | message:"Papers Found" 87 | }) 88 | } catch (e) { 89 | console.log("error:", e) 90 | setLoading(false) 91 | notification.error({ 92 | message:"Internal Server Error" 93 | }) 94 | } 95 | } 96 | const handleSubmit = async (e) => { 97 | e.preventDefault(); 98 | 99 | try { 100 | setLoading(true) 101 | const response = await fetch("/api/generate_research_questions_and_purpose", { 102 | method: "post", 103 | headers: { 104 | "Content-Type": "application/json", 105 | }, 106 | body: JSON.stringify({ 107 | objective: name, 108 | num_questions: noOfQuestion 109 | }), 110 | }); 111 | const message = await response.json(); 112 | let dataResponse = message.research_questions.research_questions.map((i, index) => ({ ...i, key: index })) 113 | console.log("response:", dataResponse); 114 | setResearchQuestionApiResponse(dataResponse) 115 | let questions = message.research_questions.research_questions.map(i => i.question) 116 | setResearchQuestions(questions) 117 | setLoading(false) 118 | scrollToBottom() 119 | notification.success({ 120 | message:"Research Questions Generated" 121 | }) 122 | } catch (error) { 123 | console.error("Error submitting data:", error); 124 | setLoading(false) 125 | notification.error({ 126 | message:"Internal Server Error" 127 | }) 128 | } 129 | }; 130 | 131 | const [papersFilterData, setPapersFilterData] = useState([]) 132 | const handleCheckboxChange = (key) => { 133 | const newpapersFilterData = [...papersFilterData]; 134 | if (newpapersFilterData.includes(key)) { 135 | newpapersFilterData.splice(newpapersFilterData.indexOf(key), 1); 136 | } else { 137 | newpapersFilterData.push(key); 138 | } 139 | setPapersFilterData(newpapersFilterData); 140 | }; 141 | 142 | const fetchAndFilterPapers = async (e) => { 143 | e.preventDefault(); 144 | try { 145 | setLoading(true) 146 | const response = await fetch("/api/filter_papers", { 147 | method: "post", 148 | headers: { 149 | "Content-Type": "application/json", 150 | }, 151 | body: JSON.stringify({ 152 | search_string: searchString, 153 | papers: papersData 154 | }) 155 | }); 156 | const message = await response.json(); 157 | if (message) { 158 | const newFilteredPapers = message.filtered_papers; 159 | const combinedArray = [...new Set([...papersFilterData, ...newFilteredPapers])]; 160 | setPapersFilterData(combinedArray); 161 | } 162 | scrollToBottom() 163 | setLoading(false) 164 | notification.success({ 165 | message:"Papers Filtered" 166 | }) 167 | } catch (e) { 168 | console.log("error:", e) 169 | setLoading(false) 170 | notification.error({ 171 | message:"internal server error" 172 | }) 173 | } 174 | } 175 | 176 | const [ansWithQuestions, setAnsWithQuestionsData] = useState() 177 | const ansWithQuestionsData = async (e) => { 178 | e.preventDefault(); 179 | try { 180 | setLoading(true) 181 | const response = await fetch("/api/answer_question", { 182 | method: "post", 183 | headers: { 184 | "Content-Type": "application/json", 185 | }, 186 | body: JSON.stringify({ 187 | questions: researchQuestions, 188 | papers_info: [...new Set([...papersFilterData, ...papersFilterData])] 189 | }) 190 | }); 191 | const message = await response.json(); 192 | console.log("message:", message) 193 | if (message) { 194 | setAnsWithQuestionsData(message.answers) 195 | } 196 | setLoading(false) 197 | notification.success({ 198 | message:"Answers Generated" 199 | }) 200 | scrollToBottom() 201 | } catch (e) { 202 | console.log("error:", e) 203 | setLoading(false) 204 | notification.error({ 205 | message:"Internal Server Error" 206 | }) 207 | } 208 | } 209 | const [summary, setSummary] = useState() 210 | const [introSummary, setIntroSummary] = useState() 211 | const generateSummaryAbstract = async (e) =>{ 212 | e.preventDefault() 213 | setLoading(true) 214 | try{ 215 | let response = await fetch ("api/generate-summary-abstract", { 216 | method: "post", 217 | headers: { 218 | "Content-Type": "application/json", 219 | }, 220 | body: JSON.stringify({ 221 | questions: researchQuestions, 222 | objective: name, 223 | search_string: searchString 224 | }) 225 | }); 226 | let message = await response.json() 227 | setSummary(message.summary_abstract) 228 | setLoading(false) 229 | notification.success({ 230 | message:"Summary Abstract Generated" 231 | }) 232 | scrollToBottom() 233 | }catch(error) { 234 | setLoading(false) 235 | console.log("error:", error) 236 | } 237 | } 238 | const introductionSummary = async (e) =>{ 239 | e.preventDefault() 240 | setLoading(true) 241 | try{ 242 | let response = await fetch ("api/generate-introduction-summary", { 243 | method: "post", 244 | headers: { 245 | "Content-Type": "application/json", 246 | }, 247 | body: JSON.stringify({ 248 | questions: researchQuestions, 249 | objective: name, 250 | search_string: searchString, 251 | total_papers: papersData, 252 | filtered_papers: papersFilterData, 253 | answers: ansWithQuestions 254 | }) 255 | }); 256 | let message = await response.json() 257 | setIntroSummary(message.introduction_summary) 258 | setLoading(false) 259 | notification.success({ 260 | message:"Introduction Summary Generated" 261 | }) 262 | scrollToBottom() 263 | }catch(error) { 264 | setLoading(false) 265 | console.log("error:", error) 266 | } 267 | } 268 | const [downloadlink, setDownloadLink] = useState() 269 | const generateAllSummary = async (e) =>{ 270 | e.preventDefault() 271 | setLoading(true) 272 | try{ 273 | let response = await fetch ("api/generate-summary-all", { 274 | method: "post", 275 | headers: { 276 | "Content-Type": "application/json", 277 | }, 278 | body: JSON.stringify({ 279 | abstract_summary: summary, 280 | intro_summary: introSummary, 281 | conclusion_summary: summary 282 | }) 283 | });if (!response.ok) { 284 | throw new Error(`Error: ${response.status} - ${response.statusText}`); 285 | } 286 | const blob = await response.blob(); 287 | const contentDisposition = response.headers.get('Content-Disposition'); 288 | const filename = contentDisposition ? contentDisposition.split('filename=')[1] : 'paper_summary.tex'; 289 | const url = window.URL.createObjectURL(new Blob([blob])); 290 | const link = document.createElement('a'); 291 | link.href = url; 292 | link.setAttribute('download', filename); 293 | document.body.appendChild(link); 294 | link.click(); 295 | window.URL.revokeObjectURL(url); 296 | document.body.removeChild(link); 297 | setLoading(false) 298 | }catch(error) { 299 | setLoading(false) 300 | console.log("error:", error) 301 | } 302 | } 303 | const handleTextareaChange = (event) => { 304 | const newText = event.target.value; 305 | const modifiedString = newText.replace(/^Question \d+: /gm, ''); 306 | console.log("modified value",modifiedString.trim()); 307 | // console.log("question value:", event.target.value) 308 | const newQuestions = modifiedString.split('\n').map((question) => question); 309 | 310 | setResearchQuestions(newQuestions); 311 | }; 312 | const handleSearchStringChange = (event) => { 313 | if(event.target.value == ""){ 314 | setSearchString(" ") 315 | }else{ 316 | setSearchString(event.target.value); 317 | } 318 | }; 319 | return ( 320 | 321 |
322 |
323 |
324 | 325 |
326 |
327 | SLR Automation Tool 328 |
329 |
330 | 331 |
332 |
333 |
334 | 335 | 336 | {loading && } 337 |
353 |
354 |
355 | {/*
*/} 356 |
Hello, I am your Agent, Enter Your Research Objective.
357 |
358 |
359 |
360 | 361 | 362 | setName(e.target.value)} 366 | /> 367 | 368 | 369 | 370 | setNoOfQuestions(e.target.value)} 376 | type="number" 377 | /> 378 | 379 | 380 | 381 | 388 | 389 | 390 |
391 | 392 |
393 |
394 | {researchQuestionApiResponse && 395 |
396 | 397 | 401 | 402 | 403 | } 404 | 405 | {researchQuestions && researchQuestions.length > 0 && 406 |
407 |
408 | 409 |
410 | 411 |