How to Beginner to Intermediate · 4 min read

How to build a file reading agent with OpenAI

Q: How to build a file reading agent with OpenAI

Use the OpenAI Python SDK to build a file reading agent by loading file content, sending it as a prompt to a model like gpt-4o, and processing the response. This approach enables you to query or summarize file contents dynamically with client.chat.completions.create.

Quick answer

Use the OpenAI Python SDK to build a file reading agent by loading file content, sending it as a prompt to a model like gpt-4o, and processing the response. This approach enables you to query or summarize file contents dynamically with client.chat.completions.create.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install openai>=1.0

Setup

Install the OpenAI Python SDK and set your API key as an environment variable for secure access.

bash

pip install openai>=1.0

Step by step

This example reads a text file, sends its content to the gpt-4o model, and prints a summary generated by the agent.

python

import os
from openai import OpenAI

# Initialize OpenAI client
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

# Read file content
file_path = "example.txt"
with open(file_path, "r", encoding="utf-8") as f:
    file_content = f.read()

# Prepare prompt to summarize file content
prompt = f"Summarize the following text:\n\n{file_content}"

# Call OpenAI chat completion
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": prompt}]
)

# Output the summary
print("Summary of file content:")
print(response.choices[0].message.content)

output

Summary of file content:
[Model-generated summary of the file's text]

Common variations

Use async calls with asyncio for non-blocking file reading and API requests.
Switch models to gpt-4o-mini for faster, cheaper responses.
Implement streaming responses to process large file summaries incrementally.

python

import os
import asyncio
import aiofiles
from openai import OpenAI

async def async_file_reading_agent():
    client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
    file_path = "example.txt"
    async with aiofiles.open(file_path, mode='r', encoding='utf-8') as f:
        file_content = await f.read()
    prompt = f"Summarize the following text:\n\n{file_content}"
    response = await client.chat.completions.acreate(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}]
    )
    print("Async summary:")
    print(response.choices[0].message.content)

# asyncio.run(async_file_reading_agent())

output

Async summary:
[Model-generated summary]

Troubleshooting

If you get a FileNotFoundError, verify the file path is correct and accessible.
If the API returns an error, check your OPENAI_API_KEY environment variable and model name.
For large files, consider chunking the content before sending to avoid token limits.

✅

Key Takeaways

Use the OpenAI Python SDK with environment variables for secure API access.
Read file content and send it as a prompt to gpt-4o for summarization or querying.
Adapt the agent with async calls or smaller models for efficiency and cost control.

Verified 2026-04 · gpt-4o, gpt-4o-mini

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