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To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" @@ -186,16 +186,16 @@ same "printed page" as the copyright notice for easier identification within third-party archives. - Copyright [yyyy] [name of copyright owner] +Copyright 2024 Marco Vinciguerra - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. diff --git a/README.md b/README.md index 3f359169..39746b01 100644 --- a/README.md +++ b/README.md @@ -2,14 +2,20 @@ This repo is a Python open source library for making a faster scraping using AI and without any knowledge about the HTML code. -The tech stack is fully in Python and the main libraries used are pydantic, langchain and requests. +The tech stack is fully in Python and the main libraries used are pydantic, langchain and requests. All the required libraries are in the requirements.txt file. The use of this library allows to scrape and extract informations from websites in just few seconds instead of write ad-hoc code for each website. This library can work passing as a parameter from the code the HTML to scrape or it can work passing the link of the website that you want to extract informations. -# Setup +# 🔍 Demo + +Try out AmazScraper in your browser: + +[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/VinciGit00/AmazScraper) + +# 🔧 Quick Setup Follow the following steps: @@ -18,8 +24,8 @@ Follow the following steps: ``` 2. (Optional) ```bash - python -m venv venv - source ./venv/bin/activate + python -m venv venv + source ./venv/bin/activate ``` 3. ```bash pip install -r requirements.txt @@ -44,34 +50,40 @@ API_KEY="your openai.com api key" 8. You are ready to go! 🚀 9. Try running the examples using: - ```bash - python -m examples.html_scraping - ``` - or - ```bash - python -m AmazScraper.examples.html_scraping - ``` -# Practical use +```bash +python -m examples.html_scraping +``` -## Using AmazScraper as a library +or + +```bash +python -m AmazScraper.examples.html_scraping +``` + +# 📖 Examples ```python -from classes.class_generator import Generator +import os +from dotenv import load_dotenv +from utils.getter import scraper +from utils.class_generator import Generator -from utils.getter import get_function, scraper +load_dotenv() + +MY_ENV_VAR = os.getenv('API_KEY') values = [ { - "title": "title", + "title": "title_website", "type": "str", - "description": "Title of the items" + "description": "Give me the website name" } ] if __name__ == "__main__": - generator_instance = Generator(values, 0, "gpt-3.5-turbo") + generator_instance = Generator(values, MY_ENV_VAR, 0, "gpt-3.5-turbo") res = generator_instance.invocation(scraper("https://www.mockupworld.co", 4197)) @@ -81,8 +93,13 @@ if __name__ == "__main__": ### Case 2: Passing your own HTML code ```python -import sys -from classes.class_generator import Generator +import os +from dotenv import load_dotenv +from utils.class_generator import Generator + +load_dotenv() + +MY_ENV_VAR = os.getenv('API_KEY') values = [ { @@ -132,7 +149,7 @@ query_info = ''' if __name__ == "__main__": - generator_instance = Generator(values, 0, "gpt-3.5-turbo") + generator_instance = Generator(values, MY_ENV_VAR, 0, "gpt-3.5-turbo") res = generator_instance.invocation(query_info) print(res) @@ -145,13 +162,13 @@ Is it possible to run the examples through the command line inside the principal For the first example: ```bash - python -m examples.value_scraping +python -m examples.value_scraping ``` For the second example: ```bash - python -m examples.html_scraping +python -m examples.html_scraping ``` # Example of output diff --git a/amazscraper/class_creator.py b/amazscraper/class_creator.py index d1b1dd3f..312512a0 100644 --- a/amazscraper/class_creator.py +++ b/amazscraper/class_creator.py @@ -1,14 +1,17 @@ +import time + base_script = ''' from langchain_core.pydantic_v1 import BaseModel, Field class _Response(BaseModel): ''' - -# This function creates a class at runtime using the values from the list. def create_class(data_dict: dict): + ''' + This function creates a class at runtime using the values from the list. + ''' for elem in data_dict: global base_script base_script = base_script + f" {elem['title']}: {elem['type']} = Field(description='{elem['description']}')\n" - with open("./pydantic_class.py", "w") as f: - f.write(base_script) + with open("./utils/pydantic_class.py", "w") as f: + f.write(base_script) \ No newline at end of file diff --git a/amazscraper/class_generator.py b/amazscraper/class_generator.py index 92363e3a..22f54e4e 100644 --- a/amazscraper/class_generator.py +++ b/amazscraper/class_generator.py @@ -1,4 +1,3 @@ -import os from dotenv import load_dotenv from .pydantic_class import _Response from .class_creator import create_class @@ -7,12 +6,8 @@ from langchain.prompts import PromptTemplate from langchain_core.pydantic_v1 import Field from langchain.output_parsers import PydanticOutputParser -load_dotenv() - -MY_ENV_VAR = os.getenv('API_KEY') - class Generator: - def __init__(self, values:list, temperature_param:float = 0, model_name:str = "gpt-3.5-turbo"): + def __init__(self, values:list, api_key:str, temperature_param:float = 0, model_name:str = "gpt-3.5-turbo"): """ Initializes the Generator object. @@ -35,7 +30,7 @@ class Generator: partial_variables={"format_instructions": self.parser.get_format_instructions()}, ) - self.model = ChatOpenAI(openai_api_key=MY_ENV_VAR, temperature=temperature_param, model=model_name) + self.model = ChatOpenAI(openai_api_key=api_key, temperature=temperature_param, model=model_name) self.chain = self.prompt | self.model | self.parser diff --git a/amazscraper/getter.py b/amazscraper/getter.py index e499621f..1c1b509d 100644 --- a/amazscraper/getter.py +++ b/amazscraper/getter.py @@ -15,7 +15,7 @@ def get_function(link:str, param = HEADERS) -> str: Returns: str: The content of the response as a string. """ - response = requests.get(url=link, headers=HEADERS) + response = requests.get(url=link, headers=param) return str(response.content) def scraper(link: str, max_char: int) -> str: diff --git a/amazscraper/pydantic_class.py b/amazscraper/pydantic_class.py index e9b554d1..8566aa09 100644 --- a/amazscraper/pydantic_class.py +++ b/amazscraper/pydantic_class.py @@ -2,4 +2,4 @@ from langchain_core.pydantic_v1 import BaseModel, Field class _Response(BaseModel): - title: str = Field(description='Title of the news') + title_website: str = Field(description='Give me the website name') diff --git a/.env.example b/examples/.env.example similarity index 100% rename from .env.example rename to examples/.env.example diff --git a/examples/html_scraping.py b/examples/html_scraping.py index 61eb99e4..a360813e 100644 --- a/examples/html_scraping.py +++ b/examples/html_scraping.py @@ -1,6 +1,11 @@ -import sys +import os +from dotenv import load_dotenv from amazscraper.class_generator import Generator +load_dotenv() + +MY_ENV_VAR = os.getenv('API_KEY') + values = [ { "title": "title", @@ -49,7 +54,7 @@ query_info = ''' if __name__ == "__main__": - generator_instance = Generator(values, 0, "gpt-3.5-turbo") + generator_instance = Generator(values, MY_ENV_VAR, 0, "gpt-3.5-turbo") res = generator_instance.invocation(query_info) print(res) \ No newline at end of file diff --git a/examples/value_scraping.py b/examples/value_scraping.py new file mode 100644 index 00000000..7c338f5c --- /dev/null +++ b/examples/value_scraping.py @@ -0,0 +1,24 @@ +import os +from dotenv import load_dotenv +from utils.getter import scraper +from utils.class_generator import Generator + +load_dotenv() + +MY_ENV_VAR = os.getenv('API_KEY') + +values = [ + { + "title": "title_website", + "type": "str", + "description": "Give me the website name" + } +] + +if __name__ == "__main__": + + generator_instance = Generator(values, MY_ENV_VAR, 0, "gpt-3.5-turbo") + + res = generator_instance.invocation(scraper("https://www.mockupworld.co", 4197)) + + print(res) \ No newline at end of file