file-store

name	file-store
description	Using FileStore to wrap files (images, PDFs, data) for use in EDSL survey scenarios.

FileStore: Working with Files in EDSL

Creating a FileStore

Use FileStore(path=...) to wrap any file for use in surveys:

from edsl import FileStore

fs = FileStore(path="photo.png")

This works with many file types: images (png, jpeg, svg), documents (pdf, docx, pptx), data (csv, xlsx, json), text (txt, md, html), code (py, sql), databases (db/sqlite), video (mp4, webm), and LaTeX.

Using FileStore in Scenarios

Pass a FileStore as a scenario value, then reference it in question text with Jinja2 templating:

from edsl import FileStore, Scenario, QuestionFreeText, Survey

fs = FileStore(path="chart.png")
scenario = Scenario({"file_path": fs})

q = QuestionFreeText(
    question_name="describe",
    question_text="What is in this image: {{ scenario.file_path }}?"
)

survey = Survey([q])
results = survey.by(scenario).run()

The {{ scenario.file_path }} placeholder is replaced with the file content at runtime, so the model sees the actual image/document.

Multiple Files with ScenarioList

Process many files by creating a scenario for each:

from edsl import FileStore, Scenario, ScenarioList

filenames = ["doc1.pdf", "doc2.pdf", "doc3.pdf"]

scenarios = ScenarioList([
    Scenario({"file_path": FileStore(path=f)}) for f in filenames
])

results = survey.by(scenarios).run()

Combining Files with Other Scenario Data

Scenarios can contain both files and regular data:

scenario = Scenario({
    "file_path": FileStore(path="resume.pdf"),
    "job_title": "Software Engineer"
})

q = QuestionFreeText(
    question_name="evaluate",
    question_text="Review this resume: {{ scenario.file_path }}. How well does the candidate fit the role of {{ job_title }}?"
)

Quick Reference

Task	Code
Create from file	FileStore(path="file.png")
Wrap in scenario	Scenario({"file_path": fs})
Reference in question	{{ scenario.file_path }}
Multiple files	ScenarioList([Scenario({"file_path": FileStore(path=f)}) for f in files])
Extract text	fs.extract_text()
CSV to scenarios	FileStore(path="data.csv").to_scenario_list()
Get MIME type	fs.mime_type
Check if image	fs.is_image()