π PDFScraperGraph Module
The PDFScraperGraph
module defines a class for creating and executing a graph that extracts information from PDF files using a natural language model to interpret and answer prompts.
Classesβ
PDFScraperGraph
β
PDFScraperGraph
is a scraping pipeline that extracts information from PDF files using a natural language model to interpret and answer prompts.
Attributesβ
- prompt (str): The prompt for the graph.
- source (str): The source of the graph.
- config (dict): Configuration parameters for the graph.
- schema (str): The schema for the graph output.
- llm_model: An instance of a language model client, configured for generating answers.
- embedder_model: An instance of an embedding model client, configured for generating embeddings.
- verbose (bool): A flag indicating whether to show print statements during execution.
- headless (bool): A flag indicating whether to run the graph in headless mode.
- model_token (int): The token limit for the language model.
Methodsβ
-
__init__(self, prompt: str, source: str, config: dict, schema: Optional[str] = None)
- Initializes the
PDFScraperGraph
with a prompt, source, configuration, and schema. - Args:
prompt (str)
: The prompt for the graph.source (str)
: The source of the graph.config (dict)
: Configuration parameters for the graph.schema (str)
: The schema for the graph output.
- Initializes the
-
_create_graph(self) -> BaseGraph
- Creates the graph of nodes representing the workflow for PDF scraping.
- Returns: An instance of
BaseGraph
.
-
run(self) -> str
- Executes the PDF scraping process and returns the answer to the prompt.
- Returns: The answer to the prompt.
Example Usageβ
Here is an example of how to use the PDFScraperGraph
class:
from pdf_scraper_graph import PDFScraperGraph
# Define the prompt, source, and configuration
prompt = "List me all the attractions in Chioggia."
source = "data/chioggia.pdf"
config = {
"llm": {"model": "gpt-3.5-turbo"},
"verbose": True,
"headless": False
}
# Create the PDF scraper graph
pdf_scraper = PDFScraperGraph(prompt, source, config)
# Run the PDF scraper graph
result = pdf_scraper.run()
print(result)