54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
import json
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import os
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import logging
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from langchain_community.document_loaders import WebBaseLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from rag_system.loaders.firecrawl import FireCrawlLoader
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from dotenv import load_dotenv
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load_dotenv() # take environment variables]
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# Configure the logging
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logging.basicConfig(level=logging.INFO)
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firecrawl_api_key = os.getenv("FIRECRAWL_API_KEY")
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firecrawl_api_url = os.getenv("FIRECRAWL_API_URL")
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firecrawl_mode = os.getenv("FIRECRAWL_MODE")
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firecrawl_params = os.getenv("FIRECRAWL_PARAMS")
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if firecrawl_params:
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firecrawl_params = json.loads(firecrawl_params)
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logging.info(f"web_loader firecrawl_api_url: {firecrawl_api_url}")
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logging.info(f"web_loader firecrawl_mode: {firecrawl_mode}")
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logging.info(f"web_loader firecrawl_params: {firecrawl_params}")
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def load_web_crawl(url):
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logging.info(f"load_web_crawl url: {url}")
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loader = FireCrawlLoader(
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url=url,
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api_key=firecrawl_api_key,
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api_url=firecrawl_api_url,
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mode=firecrawl_mode,
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params=firecrawl_params,
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)
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docs = []
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docs_lazy = loader.load()
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for doc in docs_lazy:
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print(".", end="")
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docs.append(doc)
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print()
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# Load documents from the URLs
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# docs = [WebBaseLoader(url).load() for url in urls]
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# docs_list = [item for sublist in docs for item in sublist]
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# Initialize a text splitter with specified chunk size and overlap
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text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
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chunk_size=250, chunk_overlap=0
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)
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# Split the documents into chunks
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return text_splitter.split_documents(docs)
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