https://github.com/gbaeke/openai_responses
https://github.com/gbaeke/openai_responses
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/gbaeke/openai_responses
- Owner: gbaeke
- Created: 2025-03-14T17:45:12.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-03-14T17:46:14.000Z (about 2 months ago)
- Last Synced: 2025-03-14T18:42:48.830Z (about 2 months ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# OpenAI API Responses Examples
This repository contains examples of using the OpenAI API's new Responses feature, which provides a more streamlined way to interact with OpenAI's models.
## Setup
1. Make sure you have Python installed
2. Install the required packages:
```
pip install openai rich pydantic requests
```
3. Create a `.env` file with your OpenAI API key:
```
OPENAI_API_KEY=your_api_key_here
```
## Examples
### 1. Basics (`1_basics.py`)
This script demonstrates the basic usage of the OpenAI Responses API:
- Creating simple responses with instructions
- Using the traditional messages array format
- Maintaining conversation context with `previous_response_id`
- Converting responses to dictionaries for inspection
### 2. Interactive Chat (`2_chat.py`)
A command-line chat interface built with the Rich library:
- Maintains conversation context across multiple exchanges
- Streams responses for a more interactive experience
- Displays token usage statistics
- Supports exiting the chat with the 'exit' command
### 3. Image Analysis (`3_images.py`)
Shows how to use the API to analyze images:
- Sends an image URL to the model
- Requests a description of the image content
- Uses the gpt-4o-mini model for efficient image analysis
### 4. Structured Outputs (`4_structured_outputs.py`)
Demonstrates how to get structured data from the API:
- Uses JSON Schema to define the expected output format
- Extracts structured information from natural language
- Shows integration with Pydantic for type validation
- Compares different methods for structured output
### 5. Web Search Integration (`5_built_in_web_search.py`)
Showcases the built-in web search capability:
- Configures the web search tool with user location
- Extracts and displays search results with annotations
- Uses Rich library to format and display the results in a visually appealing way
- Demonstrates how to parse the complex response structure
## Usage
Run any example with Python:
```
python 1_basics.py
```
For the interactive chat example:
```
python 2_chat.py
```
## Notes
- These examples use the latest OpenAI API features as of February 2025
- The Responses API provides a more streamlined interface compared to the older Chat Completions API
- The older Chat Completions API is still available and is still supported