Metadata-Version: 2.1
Name: openai-api-call
Version: 1.1.1
Summary: A short wrapper of the OpenAI api call.
Home-page: https://github.com/cubenlp/openai_api_call
Author: Rex Wang
Author-email: 1073853456@qq.com
License: MIT license
Keywords: openai_api_call
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: Click >=7.0
Requires-Dist: requests >=2.20
Requires-Dist: tqdm >=4.60
Requires-Dist: aiohttp >=3.8
Requires-Dist: tiktoken >=0.4.0

> **中文文档移步[这里](README_zh_CN.md)。**

# Openai API call
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A Python wrapper for OpenAI API, supporting multi-turn dialogue, proxy, and asynchronous data processing.

## Installation

```bash
pip install openai-api-call --upgrade
```

## Usage

### Set API Key and Base URL

Method 1, write in Python code:

```python
import openai_api_call
openai_api_call.api_key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
openai_api_call.base_url = "https://api.example.com"
```

Method 2, set environment variables in `~/.bashrc` or `~/.zshrc`:

```bash
export OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
export OPENAI_BASE_URL="https://api.example.com"
```

## Examples

Example 1, simulate multi-turn dialogue:

```python
# first chat
chat = Chat("Hello, GPT-3.5!")
resp = chat.getresponse()

# continue the chat
chat.user("How are you?")
next_resp = chat.getresponse()

# add response manually
chat.user("What's your name?")
chat.assistant("My name is GPT-3.5.")

# save the chat history
chat.save("chat.json", mode="w") # default to "a"

# print the chat history
chat.print_log()
```

Example 2, process data in batch, and use a checkpoint file `checkpoint`:

```python
# write a function to process the data
def msg2chat(msg):
    chat = Chat(api_key=api_key)
    chat.system("You are a helpful translator for numbers.")
    chat.user(f"Please translate the digit to Roman numerals: {msg}")
    chat.getresponse()

checkpoint = "chat.jsonl"
msgs = ["%d" % i for i in range(1, 10)]
# process the data
chats = process_chats(msgs[:5], msg2chat, checkpoint, clearfile=True)
# process the rest data, and read the cache from the last time
continue_chats = process_chats(msgs, msg2chat, checkpoint)
```

Example 3, process data in batch (asynchronous), print hello using different languages, and use two coroutines:

```python
from openai_api_call import async_chat_completion

chatlogs = [
    {"role":"user", "content":"print hello using %s" % lang} 
    for lang in ["python", "java", "Julia", "C++"]]
async_chat_completion(chatlogs, chkpoint="async_chat.jsonl", ncoroutines=2)
```

## License

This package is licensed under the MIT license. See the LICENSE file for more details.

## update log

Current version `1.0.0` is a stable version, with the redundant feature `function call` removed, and the asynchronous data processing tool added.

### Beta version
- Since version `0.2.0`, `Chat` type is used to handle data
- Since version `0.3.0`, you can use different API Key to send requests.
- Since version `0.4.0`, this package is mantained by [cubenlp](https://github.com/cubenlp).
- Since version `0.5.0`, one can use `process_chats` to process the data, with a customized `msg2chat` function and a checkpoint file.
- Since version `0.6.0`, the feature [function call](https://platform.openai.com/docs/guides/gpt/function-calling) is added.

