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add scrape graph script
Browse files- app.py +35 -0
- requirements.txt +3 -0
app.py
CHANGED
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import streamlit as st
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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import streamlit as st
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from transformers import AutoTokenizer, AutoModel, AutoModelForCausalLM
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from scrapegraphai.graphs import SmartScraperGraph
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from scrapegraphai.utils import prettify_exec_info
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tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
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model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1")
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modelNomic = AutoModel.from_pretrained("nomic-ai/nomic-embed-text-v1.5", trust_remote_code=True)
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graph_config = {
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"llm": {
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"model-instance": model,
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"temperature": 1,
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"format": "json", # Ollama needs the format to be specified explicitly
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"model_tokens": 4096, # depending on the model set context length
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},
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"embeddings": {
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"model-instance": modelNomic,
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"temperature": 0,
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}
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}
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# ************************************************
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# Create the SmartScraperGraph instance and run it
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# ************************************************
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smart_scraper_graph = SmartScraperGraph(
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prompt="List me shoes in first page with names, prices and image urls",
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# also accepts a string with the already downloaded HTML code
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source="https://www.footlocker.co.uk/en/category/sale/men.html",
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config=graph_config
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)
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result = smart_scraper_graph.run()
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print(result)
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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requirements.txt
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streamlit
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transformers
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scrapegraphai
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