what are some prompt ways to extract data from url and ...

aandysingal

@kapa.ai what are some prompt ways to extract data from url and query it?

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kkapa.ai

Please stand by @andysingal as I search the knowledge base. I normally take about 20 seconds or so. :wave:

kkapa.ai

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To extract data from a URL and query it using LlamaIndex, you can follow these steps:

Load documents from a URL: You can use a data connector like firecrawl_reader to load data from a URL. Here's an example of how to do this:

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documents = firecrawl_reader.load_data(url="<http://paulgraham.com/">)

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Create an index from the documents: Once you have the documents, you can create an index from them. Here's how you can do it:

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index = SummaryIndex.from_documents(documents)

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Query the index: After creating the index, you can query it. Here's an example:

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query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")

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Remember to replace "<http://paulgraham.com/"> and "What did the author do growing up?" with your own URL and query.

For more complex queries, you can use prompts. For example, you can use a text_qa_template and a refine_template to customize how the AI handles the query. Here's an example:

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print(
    index.as_query_engine(
        text_qa_template=text_qa_template,
        refine_template=refine_template,
        llm=llm,
    ).query("Who is Joe Biden?")
)

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kkapa.ai

In this example, replace "Who is Joe Biden?" with your own query, and text_qa_template and refine_template with your own templates.
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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aandysingal

@kapa.ai how to add url and query in a prompt string?

kkapa.ai

Let me check the knowledge base for you. One moment! :books:

kkapa.ai

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To add a URL and a query in a prompt string, you can use Python's string formatting. Here's an example:

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from llama_index.core import PromptTemplate

# Define your prompt template string
prompt_tmpl_str = """\
We are extracting data from the following URL: {url}
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Given the URL, please answer the query: {query_str}
"""

# Create a PromptTemplate
prompt_tmpl = PromptTemplate(prompt_tmpl_str)

# Format the prompt with your URL and query
formatted_prompt = prompt_tmpl.format(url="<http://example.com",> query_str="What is the title of the homepage?")

In this example, replace "<http://example.com"> with your own URL and "What is the title of the homepage?" with your own query.

Please note that this is just a way to format a string with a URL and a query. It doesn't actually extract data from the URL or perform a query. To do that, you would need to use other parts of the LlamaIndex library or other libraries.

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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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aandysingal

@kapa.ai show the example with firecrawl

kkapa.ai

Let me check the knowledge base for you. One moment! :books:

kkapa.ai

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Sure, here's an example of how you can use FireCrawl to load data from a URL and then query it:

First, you need to initialize the FireCrawlWebReader with your API key and desired mode:

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from llama_index.readers.web import FireCrawlWebReader

firecrawl_reader = FireCrawlWebReader(
    api_key="<your_api_key>",  # Replace with your actual API key from <https://www.firecrawl.dev/>
    mode="scrape",  # Choose between "crawl" and "scrape" for single page scraping
    params={"additional": "parameters"},  # Optional additional parameters
)

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Then, you can load documents from a single page URL:

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documents = firecrawl_reader.load_data(url="<http://paulgraham.com/">)

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Next, you can create an index from the documents:

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index = SummaryIndex.from_documents(documents)

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Finally, you can query the index:

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query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")

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Remember to replace <your_api_key> with your actual API key from FireCrawl, "<http://paulgraham.com/"> with your own URL, and "What did the author do growing up?" with your own query.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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