├── .flake8 ├── .gitignore ├── .python-version ├── README.md ├── app.py ├── oai.py ├── poetry.lock ├── pyproject.toml └── scrape.py /.flake8: -------------------------------------------------------------------------------- 1 | [flake8] 2 | max-line-length = 88 3 | extend-ignore = E203 4 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .venv 2 | .env 3 | __pycache__ 4 | .DS_Store 5 | .vscode 6 | -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.10.9 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Text Summarization with OpenAI GPT-3 2 | 3 | Live version of this app at [web-summarizer.streamlit.app](https://web-summarizer.streamlit.app) 4 | 5 | ## Description 6 | 7 | This [Streamlit](https://streamlit.io) mini-app scrapes the paragraphs from a web page, e.g. a blog post, and summarizes them into a Tweet-sized statement using [OpenAI's GPTs](https://beta.openai.com/docs/models/overview). 8 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | """Streamlit app to summarize text, e.g. blog articles""" 2 | 3 | # Import from standard library 4 | import logging 5 | 6 | # Import from 3rd party libraries 7 | import streamlit as st 8 | import streamlit.components.v1 as components 9 | 10 | # Import modules 11 | import scrape as scr 12 | import oai 13 | 14 | # Configure logger 15 | logging.basicConfig(format="\n%(asctime)s\n%(message)s", level=logging.INFO, force=True) 16 | 17 | 18 | # Define functions 19 | def summarize(text: str): 20 | """Summarize text.""" 21 | summary_prompt = "\n\Write an engaging summary for the above article in less than 120 characters:\n\n" 22 | openai = oai.Openai() 23 | flagged = openai.moderate(text) 24 | if flagged: 25 | st.session_state.error = "Input flagged as inappropriate." 26 | return 27 | st.session_state.error = "" 28 | st.session_state.summary = ( 29 | openai.complete(prompt=text + summary_prompt) 30 | .strip() 31 | .replace("\n", " ") 32 | .replace('"', "") 33 | ) 34 | 35 | 36 | # Render streamlit page 37 | st.set_page_config(page_title="Summarizer", page_icon="🤖") 38 | if "summary" not in st.session_state: 39 | st.session_state.summary = "" 40 | if "error" not in st.session_state: 41 | st.session_state.error = "" 42 | 43 | st.title("Summarize web content") 44 | st.markdown( 45 | """This mini-app scrapes the paragraphs from a web page, 46 | e.g. a blog post, and summarizes them into a Tweet-sized 47 | statement using OpenAI's [GPTs](https://beta.openai.com/docs/models/overview). You can find the code on [GitHub](https://github.com/kinosal/summarizer) and the author on [Twitter](https://twitter.com/kinosal).""" 48 | ) 49 | 50 | selectbox = st.selectbox("Raw text or URL source", ("URL", "Raw text")) 51 | 52 | if selectbox == "Raw text": 53 | raw_text = st.text_area(label="Text", height=300, max_chars=6000) 54 | if raw_text: 55 | summarize(raw_text) 56 | if st.session_state.summary: 57 | st.text_area( 58 | label="Raw text summary", 59 | value=st.session_state.summary, 60 | height=100, 61 | ) 62 | logging.info(f"Text: {raw_text}\nSummary: {st.session_state.summary}") 63 | st.button( 64 | label="Regenerate summary", 65 | type="secondary", 66 | on_click=summarize, 67 | args=[raw_text], 68 | ) 69 | 70 | elif selectbox == "URL": 71 | url = st.text_input(label="URL") 72 | if url: 73 | scraper = scr.Scraper() 74 | response = scraper.request_url(url) 75 | if "invalid" in str(response).lower(): 76 | st.error(str(response)) 77 | elif response.status_code != 200: 78 | st.error(f"Response status {response.status_code}") 79 | else: 80 | url_text = ( 81 | scraper.extract_content(response)[:6000].strip().replace("\n", " ") 82 | ) 83 | summarize(url_text) 84 | if st.session_state.summary: 85 | st.text_area( 86 | label="URL summary", value=st.session_state.summary, height=100 87 | ) 88 | logging.info(f"URL: {url}\nSummary: {st.session_state.summary}") 89 | # Force responsive layout for columns also on mobile 90 | st.write( 91 | """""", 98 | unsafe_allow_html=True, 99 | ) 100 | col1, col2 = st.columns(2) 101 | with col1: 102 | components.html( 103 | f""" 104 | Tweet 105 | """, 106 | height=45, 107 | ) 108 | with col2: 109 | st.button( 110 | label="Regenerate summary", 111 | type="secondary", 112 | on_click=summarize, 113 | args=[url_text], 114 | ) 115 | 116 | if st.session_state.error: 117 | st.error(st.session_state.error) 118 | 119 | if st.session_state.summary: 120 | st.markdown("""---""") 121 | col1, col2 = st.columns(2) 122 | with col1: 123 | st.markdown( 124 | "**Other Streamlit apps by [@kinosal](https://twitter.com/kinosal)**" 125 | ) 126 | st.markdown("[Tweet Generator](https://tweets.streamlit.app)") 127 | st.markdown("[Twitter Wrapped](https://twitter-likes.streamlit.app)") 128 | st.markdown("[Code Translator](https://english-to-code.streamlit.app)") 129 | st.markdown("[PDF Analyzer](https://pdf-keywords.streamlit.app)") 130 | with col2: 131 | st.write("If you like this app, please consider to") 132 | components.html( 133 | """ 134 |
135 | 136 | 137 | 138 |
139 | """, 140 | height=45, 141 | ) 142 | st.write("so I can keep it alive. Thank you!") 143 | -------------------------------------------------------------------------------- /oai.py: -------------------------------------------------------------------------------- 1 | """OpenAI API connector.""" 2 | 3 | # Import from standard library 4 | import os 5 | import logging 6 | 7 | # Import from 3rd party libraries 8 | from openai import OpenAI 9 | import streamlit as st 10 | 11 | # Instantiate OpenAI with credentials from environment or streamlit secrets 12 | openai_key = os.getenv("OPENAI_API_KEY") or st.secrets["OPENAI_API_KEY"] 13 | client = OpenAI(api_key=openai_key) 14 | 15 | # Suppress openai request/response logging 16 | # Handle by manually changing the respective APIRequestor methods in the openai package 17 | # Does not work hosted on Streamlit since all packages are re-installed by Poetry 18 | # Alternatively (affects all messages from this logger): 19 | logging.getLogger("openai").setLevel(logging.WARNING) 20 | 21 | 22 | class Openai: 23 | """OpenAI Connector.""" 24 | 25 | @staticmethod 26 | def moderate(prompt: str) -> bool: 27 | """Call OpenAI GPT Moderation with text prompt. 28 | Args: 29 | prompt: text prompt 30 | Return: boolean if flagged 31 | """ 32 | try: 33 | response = client.moderations.create(input=prompt) 34 | return response.results[0].flagged 35 | 36 | except Exception as e: 37 | logging.error(f"OpenAI API error: {e}") 38 | st.session_state.text_error = f"OpenAI API error: {e}" 39 | 40 | @staticmethod 41 | def complete( 42 | prompt: str, 43 | model: str = "gpt-3.5-turbo", 44 | temperature: float = 0.9, 45 | max_tokens: int = 50, 46 | ) -> str: 47 | """Call OpenAI GPT Completion with text prompt. 48 | Args: 49 | prompt: text prompt 50 | model: OpenAI model name, e.g. "gpt-3.5-turbo" 51 | temperature: float between 0 and 1 52 | max_tokens: int between 1 and 2048 53 | Return: predicted response text 54 | """ 55 | try: 56 | response = client.chat.completions.create( 57 | model=model, 58 | messages=[{"role": "user", "content": prompt}], 59 | temperature=temperature, 60 | max_tokens=max_tokens, 61 | ) 62 | return response.choices[0].message.content 63 | 64 | except Exception as e: 65 | logging.error(f"OpenAI API error: {e}") 66 | st.error(f"OpenAI API error: {e}") 67 | -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "altair" 5 | version = "5.2.0" 6 | description = "Vega-Altair: A declarative statistical visualization library for Python." 7 | optional = false 8 | python-versions = ">=3.8" 9 | files = [ 10 | {file = "altair-5.2.0-py3-none-any.whl", hash = "sha256:8c4888ad11db7c39f3f17aa7f4ea985775da389d79ac30a6c22856ab238df399"}, 11 | {file = "altair-5.2.0.tar.gz", hash = "sha256:2ad7f0c8010ebbc46319cc30febfb8e59ccf84969a201541c207bc3a4fa6cf81"}, 12 | 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Schriefer "] 6 | 7 | [tool.poetry.dependencies] 8 | python = "^3.10" 9 | streamlit = "^1.15" 10 | openai = "^1.6" 11 | bs4 = "^0.0" 12 | 13 | [tool.poetry.dev-dependencies] 14 | black = "^23.3" 15 | pycodestyle = "^2.9" 16 | 17 | [build-system] 18 | requires = ["poetry-core>=1.0.0"] 19 | build-backend = "poetry.core.masonry.api" 20 | -------------------------------------------------------------------------------- /scrape.py: -------------------------------------------------------------------------------- 1 | """Web content scraper.""" 2 | 3 | # Import from standard library 4 | import requests 5 | import random 6 | 7 | # Import from 3rd party libraries 8 | from bs4 import BeautifulSoup 9 | 10 | 11 | class Scraper: 12 | """Simple web scraper.""" 13 | 14 | AGENTS = [ 15 | "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36", 16 | "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/106.0.0.0 Safari/537.36", 17 | "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:106.0) Gecko/20100101 Firefox/106.0", 18 | ] 19 | agent = AGENTS[random.randint(0, len(AGENTS) - 1)] 20 | 21 | @staticmethod 22 | def set_option(options, current): 23 | """Select next option list element.""" 24 | i = options.index(current) 25 | return options[0] if i + 1 == len(options) else options[i + 1] 26 | 27 | def switch_agent(self) -> None: 28 | """Switch to next agent to avoid blocking.""" 29 | self.agent = self.set_option(self.AGENTS, self.agent) 30 | 31 | def request_url(self, url) -> requests.Response: 32 | """Request URL with agent.""" 33 | try: 34 | response = requests.get( 35 | url, headers={"User-Agent": self.agent, "Connection": "close"} 36 | ) 37 | self.switch_agent() 38 | return response 39 | except Exception as exception: 40 | return exception 41 | 42 | def extract_content(self, html: requests.Response) -> str: 43 | """Extract plain text from html.""" 44 | soup = BeautifulSoup(html.text, "html.parser") 45 | elements = [ 46 | element.text for element in soup.find_all(["h1", "h2", "h3", "p"]) 47 | if len(element.text) > 5 48 | ] 49 | return "\n\n".join(elements) 50 | --------------------------------------------------------------------------------