mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-23 11:02:40 +03:00
Merge pull request #2304 from kqlio67/main
Add new provider, enhance functionality, and update docs
This commit is contained in:
Tekky
GitHub
commit
1c8061af55
70
README.md
70
README.md
@ -1,12 +1,11 @@
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<a href="https://trendshift.io/repositories/1692" target="_blank"><img src="https://trendshift.io/api/badge/repositories/1692" alt="xtekky%2Fgpt4free | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
|
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|
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---
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Written by [@xtekky](https://github.com/xtekky)
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<p align="center"><strong>Written by <a href="https://github.com/xtekky">@xtekky</a></strong></p>
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<div id="top"></div>
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|
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@ -17,7 +16,7 @@ Written by [@xtekky](https://github.com/xtekky)
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> _"gpt4free"_ serves as a **PoC** (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control.
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> [!NOTE]
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> <sup><strong>Lastet version:</strong></sup> [](https://pypi.org/project/g4f) [](https://hub.docker.com/r/hlohaus789/g4f)
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> <sup><strong>Latest version:</strong></sup> [](https://pypi.org/project/g4f) [](https://hub.docker.com/r/hlohaus789/g4f)
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> <sup><strong>Stats:</strong></sup> [](https://pepy.tech/project/g4f) [](https://pepy.tech/project/g4f)
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|
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```sh
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@ -30,10 +29,11 @@ docker pull hlohaus789/g4f
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## 🆕 What's New
|
||||
- **For comprehensive details on new features and updates, please refer to our [Releases](https://github.com/xtekky/gpt4free/releases) page**
|
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- **Installation Guide for Windows (.exe):** 💻 [#installation-guide-for-windows](#installation-guide-for-windows-exe)
|
||||
- **Installation Guide for Windows (.exe):** 💻 [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)
|
||||
- **Join our Telegram Channel:** 📨 [telegram.me/g4f_channel](https://telegram.me/g4f_channel)
|
||||
- **Join our Discord Group:** 💬 [discord.gg/XfybzPXPH5](https://discord.gg/XfybzPXPH5)
|
||||
|
||||
|
||||
## 🔻 Site Takedown
|
||||
|
||||
Is your site on this repository and you want to take it down? Send an email to takedown@g4f.ai with proof it is yours and it will be removed as fast as possible. To prevent reproduction please secure your API. 😉
|
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@ -53,33 +53,32 @@ Is your site on this repository and you want to take it down? Send an email to t
|
||||
- [ ] 🚧 Improve compatibility and error handling
|
||||
|
||||
## 📚 Table of Contents
|
||||
|
||||
- [🆕 What's New](#-whats-new)
|
||||
- [📚 Table of Contents](#-table-of-contents)
|
||||
- [🛠️ Getting Started](#-getting-started)
|
||||
- [Docker Container Guide](#docker-container-guide)
|
||||
- [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)
|
||||
- [Use python](#use-python)
|
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- [Prerequisites](#prerequisites)
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- [Install using PyPI package:](#install-using-pypi-package)
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||||
- [Install from source:](#install-from-source)
|
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- [Install using Docker:](#install-using-docker)
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- [💡 Usage](#-usage)
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- [Text Generation](#text-generation)
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- [Image Generation](#image-generation)
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- [Web UI](#web-ui)
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- [Interference API](docs/interference.md)
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- [Local inference](docs/local.md)
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- [Configuration](#configuration)
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- [🚀 Providers and Models](docs/providers-and-models.md)
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- [🔗 Powered by gpt4free](#-powered-by-gpt4free)
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- [🤝 Contribute](#-contribute)
|
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- [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)
|
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- [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)
|
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- [🙌 Contributors](#-contributors)
|
||||
- [©️ Copyright](#-copyright)
|
||||
- [⭐ Star History](#-star-history)
|
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- [📄 License](#-license)
|
||||
- [🆕 What's New](#-whats-new)
|
||||
- [📚 Table of Contents](#-table-of-contents)
|
||||
- [🛠️ Getting Started](#-getting-started)
|
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- [Docker Container Guide](#docker-container-guide)
|
||||
- [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)
|
||||
- [Use python](#use-python)
|
||||
- [Prerequisites](#prerequisites)
|
||||
- [Install using PyPI package](#install-using-pypi-package)
|
||||
- [Install from source](#install-from-source)
|
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- [Install using Docker](#install-using-docker)
|
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- [💡 Usage](#-usage)
|
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- [Text Generation](#text-generation)
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- [Image Generation](#image-generation)
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- [Web UI](#web-ui)
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- [Interference API](#interference-api)
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- [Local Inference](docs/local.md)
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- [Configuration](#configuration)
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- [🚀 Providers and Models](docs/providers-and-models.md)
|
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- [🔗 Powered by gpt4free](#-powered-by-gpt4free)
|
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- [🤝 Contribute](#-contribute)
|
||||
- [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)
|
||||
- [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)
|
||||
- [🙌 Contributors](#-contributors)
|
||||
- [©️ Copyright](#-copyright)
|
||||
- [⭐ Star History](#-star-history)
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- [📄 License](#-license)
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|
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## 🛠️ Getting Started
|
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|
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@ -123,7 +122,7 @@ To ensure the seamless operation of our application, please follow the instructi
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By following these steps, you should be able to successfully install and run the application on your Windows system. If you encounter any issues during the installation process, please refer to our Issue Tracker or try to get contact over Discord for assistance.
|
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|
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Run the **Webview UI** on other Platfroms:
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Run the **Webview UI** on other Platforms:
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- [/docs/guides/webview](docs/webview.md)
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@ -771,10 +770,10 @@ set G4F_PROXY=http://host:port
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We welcome contributions from the community. Whether you're adding new providers or features, or simply fixing typos and making small improvements, your input is valued. Creating a pull request is all it takes – our co-pilot will handle the code review process. Once all changes have been addressed, we'll merge the pull request into the main branch and release the updates at a later time.
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###### Guide: How do i create a new Provider?
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- Read: [/docs/guides/create_provider](docs/guides/create_provider.md)
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- Read: [Create Provider Guide](docs/guides/create_provider.md)
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###### Guide: How can AI help me with writing code?
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- Read: [/docs/guides/help_me](docs/guides/help_me.md)
|
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- Read: [AI Assistance Guide](docs/guides/help_me.md)
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## 🙌 Contributors
|
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A list of all contributors is available [here](https://github.com/xtekky/gpt4free/graphs/contributors)
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@ -866,4 +865,7 @@ This project is licensed under <a href="https://github.com/xtekky/gpt4free/blob/
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</tr>
|
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</table>
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---
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<p align="right">(<a href="#top">🔼 Back to top</a>)</p>
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@ -10,6 +10,7 @@ The G4F async client API is designed to be compatible with the OpenAI API, makin
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- [Key Features](#key-features)
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- [Getting Started](#getting-started)
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- [Initializing the Client](#initializing-the-client)
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- [Creating Chat Completions](#creating-chat-completions)
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- [Configuration](#configuration)
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- [Usage Examples](#usage-examples)
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- [Text Completions](#text-completions)
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@ -51,6 +52,28 @@ client = Client(
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)
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```
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## Creating Chat Completions
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**Here’s an improved example of creating chat completions:**
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```python
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response = await async_client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{
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"role": "user",
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"content": "Say this is a test"
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}
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]
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# Add other parameters as needed
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)
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```
|
||||
|
||||
**This example:**
|
||||
- Asks a specific question `Say this is a test`
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- Configures various parameters like temperature and max_tokens for more control over the output
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- Disables streaming for a complete response
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|
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You can adjust these parameters based on your specific needs.
|
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|
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### Configuration
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@ -164,7 +187,7 @@ async def main():
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response = await client.images.async_generate(
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prompt="a white siamese cat",
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model="dall-e-3"
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model="flux"
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)
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image_url = response.data[0].url
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@ -185,7 +208,7 @@ async def main():
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response = await client.images.async_generate(
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prompt="a white siamese cat",
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model="dall-e-3",
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model="flux",
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response_format="b64_json"
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)
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@ -217,7 +240,7 @@ async def main():
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)
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task2 = client.images.async_generate(
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model="dall-e-3",
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model="flux",
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prompt="a white siamese cat"
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)
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@ -7,6 +7,7 @@
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- [Getting Started](#getting-started)
|
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- [Switching to G4F Client](#switching-to-g4f-client)
|
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- [Initializing the Client](#initializing-the-client)
|
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- [Creating Chat Completions](#creating-chat-completions)
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- [Configuration](#configuration)
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- [Usage Examples](#usage-examples)
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- [Text Completions](#text-completions)
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@ -56,6 +57,28 @@ client = Client(
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# Add any other necessary parameters
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)
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```
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|
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## Creating Chat Completions
|
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**Here’s an improved example of creating chat completions:**
|
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```python
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response = client.chat.completions.create(
|
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model="gpt-3.5-turbo",
|
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messages=[
|
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{
|
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"role": "user",
|
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"content": "Say this is a test"
|
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}
|
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]
|
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# Add any other necessary parameters
|
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)
|
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```
|
||||
|
||||
**This example:**
|
||||
- Asks a specific question `Say this is a test`
|
||||
- Configures various parameters like temperature and max_tokens for more control over the output
|
||||
- Disables streaming for a complete response
|
||||
|
||||
You can adjust these parameters based on your specific needs.
|
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|
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|
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## Configuration
|
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@ -129,7 +152,7 @@ from g4f.client import Client
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client = Client()
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response = client.images.generate(
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model="dall-e-3",
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model="flux",
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prompt="a white siamese cat"
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# Add any other necessary parameters
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)
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@ -139,6 +162,23 @@ image_url = response.data[0].url
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print(f"Generated image URL: {image_url}")
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```
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|
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#### Base64 Response Format
|
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```python
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from g4f.client import Client
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client = Client()
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|
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response = client.images.generate(
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model="flux",
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prompt="a white siamese cat",
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response_format="b64_json"
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)
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|
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base64_text = response.data[0].b64_json
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print(base64_text)
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```
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|
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### Creating Image Variations
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@ -1,23 +1,30 @@
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# G4F - Interference API Usage Guide
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|
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|
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## Table of Contents
|
||||
- [Introduction](#introduction)
|
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- [Running the Interference API](#running-the-interference-api)
|
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- [From PyPI Package](#from-pypi-package)
|
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- [From Repository](#from-repository)
|
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- [Usage with OpenAI Library](#usage-with-openai-library)
|
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- [Usage with Requests Library](#usage-with-requests-library)
|
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- [Using the Interference API](#using-the-interference-api)
|
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- [Basic Usage](#basic-usage)
|
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- [With OpenAI Library](#with-openai-library)
|
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- [With Requests Library](#with-requests-library)
|
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- [Key Points](#key-points)
|
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- [Conclusion](#conclusion)
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|
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|
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## Introduction
|
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The Interference API allows you to serve other OpenAI integrations with G4F. It acts as a proxy, translating requests to the OpenAI API into requests to the G4F providers.
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The G4F Interference API is a powerful tool that allows you to serve other OpenAI integrations using G4F (Gpt4free). It acts as a proxy, translating requests intended for the OpenAI API into requests compatible with G4F providers. This guide will walk you through the process of setting up, running, and using the Interference API effectively.
|
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|
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|
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## Running the Interference API
|
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**You can run the Interference API in two ways:** using the PyPI package or from the repository.
|
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|
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|
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### From PyPI Package
|
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**You can run the Interference API directly from the G4F PyPI package:**
|
||||
**To run the Interference API directly from the G4F PyPI package, use the following Python code:**
|
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|
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```python
|
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from g4f.api import run_api
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|
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@ -25,37 +32,80 @@ run_api()
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```
|
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|
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|
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|
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### From Repository
|
||||
Alternatively, you can run the Interference API from the cloned repository.
|
||||
**If you prefer to run the Interference API from the cloned repository, you have two options:**
|
||||
|
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**Run the server with:**
|
||||
1. **Using the command line:**
|
||||
```bash
|
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g4f api
|
||||
```
|
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or
|
||||
|
||||
2. **Using Python:**
|
||||
```bash
|
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python -m g4f.api.run
|
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```
|
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|
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**Once running, the API will be accessible at:** `http://localhost:1337/v1`
|
||||
|
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|
||||
## Usage with OpenAI Library
|
||||
## Using the Interference API
|
||||
|
||||
|
||||
### Basic Usage
|
||||
**You can interact with the Interference API using curl commands for both text and image generation:**
|
||||
|
||||
**For text generation:**
|
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```bash
|
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curl -X POST "http://localhost:1337/v1/chat/completions" \
|
||||
-H "Content-Type: application/json" \
|
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-d '{
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Hello"
|
||||
}
|
||||
],
|
||||
"model": "gpt-3.5-turbo"
|
||||
}'
|
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```
|
||||
|
||||
**For image generation:**
|
||||
1. **url:**
|
||||
```bash
|
||||
curl -X POST "http://localhost:1337/v1/images/generate" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "a white siamese cat",
|
||||
"model": "flux",
|
||||
"response_format": "url"
|
||||
}'
|
||||
```
|
||||
|
||||
2. **b64_json**
|
||||
```bash
|
||||
curl -X POST "http://localhost:1337/v1/images/generate" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "a white siamese cat",
|
||||
"model": "flux",
|
||||
"response_format": "b64_json"
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
### With OpenAI Library
|
||||
|
||||
**You can use the Interference API with the OpenAI Python library by changing the `base_url`:**
|
||||
```python
|
||||
from openai import OpenAI
|
||||
|
||||
client = OpenAI(
|
||||
api_key="",
|
||||
# Change the API base URL to the local interference API
|
||||
base_url="http://localhost:1337/v1"
|
||||
base_url="http://localhost:1337/v1"
|
||||
)
|
||||
|
||||
response = client.chat.completions.create(
|
||||
model="gpt-3.5-turbo",
|
||||
messages=[{"role": "user", "content": "write a poem about a tree"}],
|
||||
messages=[{"role": "user", "content": "Write a poem about a tree"}],
|
||||
stream=True,
|
||||
)
|
||||
|
||||
@ -68,20 +118,20 @@ else:
|
||||
content = token.choices[0].delta.content
|
||||
if content is not None:
|
||||
print(content, end="", flush=True)
|
||||
```
|
||||
|
||||
```
|
||||
|
||||
|
||||
## Usage with Requests Library
|
||||
You can also send requests directly to the Interference API using the requests library.
|
||||
### With Requests Library
|
||||
|
||||
**Send a POST request to `/v1/chat/completions` with the request body containing the model and other parameters:**
|
||||
**You can also send requests directly to the Interference API using the `requests` library:**
|
||||
```python
|
||||
import requests
|
||||
|
||||
url = "http://localhost:1337/v1/chat/completions"
|
||||
|
||||
body = {
|
||||
"model": "gpt-3.5-turbo",
|
||||
"model": "gpt-3.5-turbo",
|
||||
"stream": False,
|
||||
"messages": [
|
||||
{"role": "assistant", "content": "What can you do?"}
|
||||
@ -92,18 +142,20 @@ json_response = requests.post(url, json=body).json().get('choices', [])
|
||||
|
||||
for choice in json_response:
|
||||
print(choice.get('message', {}).get('content', ''))
|
||||
|
||||
```
|
||||
|
||||
|
||||
|
||||
## Key Points
|
||||
- The Interference API translates OpenAI API requests into G4F provider requests
|
||||
- You can run it from the PyPI package or the cloned repository
|
||||
- It supports usage with the OpenAI Python library by changing the `base_url`
|
||||
- Direct requests can be sent to the API endpoints using libraries like `requests`
|
||||
- The Interference API translates OpenAI API requests into G4F provider requests.
|
||||
- It can be run from either the PyPI package or the cloned repository.
|
||||
- The API supports usage with the OpenAI Python library by changing the `base_url`.
|
||||
- Direct requests can be sent to the API endpoints using libraries like `requests`.
|
||||
- Both text and image generation are supported.
|
||||
|
||||
|
||||
**_The Interference API allows easy integration of G4F with existing OpenAI-based applications and tools._**
|
||||
## Conclusion
|
||||
The G4F Interference API provides a seamless way to integrate G4F with existing OpenAI-based applications and tools. By following this guide, you should now be able to set up, run, and use the Interference API effectively. Whether you're using it for text generation, image creation, or as a drop-in replacement for OpenAI in your projects, the Interference API offers flexibility and power for your AI-driven applications.
|
||||
|
||||
|
||||
---
|
||||
|
||||
|
||||
@ -51,6 +51,7 @@ This document provides an overview of various AI providers and models, including
|
||||
|[free.netfly.top](https://free.netfly.top)|`g4f.Provider.FreeNetfly`|✔|❌|❌|?||❌|
|
||||
|[gemini.google.com](https://gemini.google.com)|`g4f.Provider.Gemini`|✔|❌|❌|✔||✔|
|
||||
|[ai.google.dev](https://ai.google.dev)|`g4f.Provider.GeminiPro`|✔|❌|✔|?||✔|
|
||||
|[app.giz.ai](https://app.giz.ai/assistant/)|`g4f.Provider.GizAI`|`gemini-flash, gemini-pro, gpt-4o-mini, gpt-4o, claude-3.5-sonnet, claude-3-haiku, llama-3.1-70b, llama-3.1-8b, mistral-large`|`sdxl, sd-1.5, sd-3.5, dalle-3, flux-schnell, flux1-pro`|❌|✔||❌|
|
||||
|[developers.sber.ru](https://developers.sber.ru/gigachat)|`g4f.Provider.GigaChat`|✔|❌|❌|✔||✔|
|
||||
|[gprochat.com](https://gprochat.com)|`g4f.Provider.GPROChat`|`gemini-pro`|❌|❌|✔||❌|
|
||||
|[console.groq.com/playground](https://console.groq.com/playground)|`g4f.Provider.Groq`|✔|❌|❌|?||✔|
|
||||
@ -63,10 +64,7 @@ This document provides an overview of various AI providers and models, including
|
||||
|[app.myshell.ai/chat](https://app.myshell.ai/chat)|`g4f.Provider.MyShell`|✔|❌|?|?||❌|
|
||||
|[nexra.aryahcr.cc/bing](https://nexra.aryahcr.cc/documentation/bing/en)|`g4f.Provider.NexraBing`|✔|❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/blackbox](https://nexra.aryahcr.cc/documentation/blackbox/en)|`g4f.Provider.NexraBlackbox`|`blackboxai` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT4o`|`gpt-4o` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGptV2`|`gpt-4` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGptWeb`|`gpt-4` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3, gpt-4o` |❌|❌|✔||❌|
|
||||
|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE`|❌|`dalle`|❌|❌||❌|
|
||||
|[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE2`|❌|`dalle-2`|❌|❌||❌|
|
||||
|[nexra.aryahcr.cc/emi](https://nexra.aryahcr.cc/documentation/emi/en)|`g4f.Provider.NexraEmi`|❌|`emi`|❌|❌||❌|
|
||||
@ -108,18 +106,18 @@ This document provides an overview of various AI providers and models, including
|
||||
|-------|---------------|-----------|---------|
|
||||
|gpt-3|OpenAI|1+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-base)|
|
||||
|gpt-3.5-turbo|OpenAI|5+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-3-5-turbo)|
|
||||
|gpt-4|OpenAI|33+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
|
||||
|gpt-4-turbo|OpenAI|2+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
|
||||
|gpt-4o|OpenAI|7+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)|
|
||||
|gpt-4|OpenAI|7+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
|
||||
|gpt-4-turbo|OpenAI|3+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|
|
||||
|gpt-4o|OpenAI|10+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)|
|
||||
|gpt-4o-mini|OpenAI|14+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o-mini)|
|
||||
|o1|OpenAI|1+ Providers|[platform.openai.com](https://openai.com/index/introducing-openai-o1-preview/)|
|
||||
|o1-mini|OpenAI|1+ Providers|[platform.openai.com](https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/)|
|
||||
|o1-mini|OpenAI|2+ Providers|[platform.openai.com](https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/)|
|
||||
|llama-2-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-2-7b)|
|
||||
|llama-2-13b|Meta Llama|1+ Providers|[llama.com](https://www.llama.com/llama2/)|
|
||||
|llama-3-8b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)|
|
||||
|llama-3-70b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)|
|
||||
|llama-3.1-8b|Meta Llama|7+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
|
||||
|llama-3.1-70b|Meta Llama|13+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
|
||||
|llama-3.1-70b|Meta Llama|14+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
|
||||
|llama-3.1-405b|Meta Llama|5+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|
|
||||
|llama-3.2-1b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-3.2-1B)|
|
||||
|llama-3.2-3b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/blog/llama32)|
|
||||
@ -127,17 +125,17 @@ This document provides an overview of various AI providers and models, including
|
||||
|llama-3.2-90b|Meta Llama|2+ Providers|[ai.meta.com](https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/)|
|
||||
|llamaguard-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/LlamaGuard-7b)|
|
||||
|llamaguard-2-8b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Meta-Llama-Guard-2-8B)|
|
||||
|mistral-7b|Mistral AI|5+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)|
|
||||
|mistral-7b|Mistral AI|4+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)|
|
||||
|mixtral-8x7b|Mistral AI|6+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-of-experts/)|
|
||||
|mixtral-8x22b|Mistral AI|3+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-8x22b/)|
|
||||
|mistral-nemo|Mistral AI|1+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|
|
||||
|mistral-large|Mistral AI|1+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)|
|
||||
|mistral-nemo|Mistral AI|2+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|
|
||||
|mistral-large|Mistral AI|2+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)|
|
||||
|mixtral-8x7b-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|
|
||||
|yi-34b|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B)|
|
||||
|hermes-3|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|
|
||||
|hermes-3|NousResearch|2+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|
|
||||
|gemini|Google DeepMind|1+ Providers|[deepmind.google](http://deepmind.google/technologies/gemini/)|
|
||||
|gemini-flash|Google DeepMind|3+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)|
|
||||
|gemini-pro|Google DeepMind|9+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)|
|
||||
|gemini-flash|Google DeepMind|4+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)|
|
||||
|gemini-pro|Google DeepMind|10+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)|
|
||||
|gemma-2b|Google|5+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2b)|
|
||||
|gemma-2b-9b|Google|1+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-9b)|
|
||||
|gemma-2b-27b|Google|2+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-27b)|
|
||||
@ -145,10 +143,10 @@ This document provides an overview of various AI providers and models, including
|
||||
|gemma-2|Google|2+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|
|
||||
|gemma_2_27b|Google|1+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|
|
||||
|claude-2.1|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)|
|
||||
|claude-3-haiku|Anthropic|3+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|
|
||||
|claude-3-haiku|Anthropic|4+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|
|
||||
|claude-3-sonnet|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
|
||||
|claude-3-opus|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|
|
||||
|claude-3.5-sonnet|Anthropic|5+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
|
||||
|claude-3.5-sonnet|Anthropic|6+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|
|
||||
|blackboxai|Blackbox AI|2+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)|
|
||||
|blackboxai-pro|Blackbox AI|1+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)|
|
||||
|yi-1.5-9b|01-ai|1+ Providers|[huggingface.co](https://huggingface.co/01-ai/Yi-1.5-9B)|
|
||||
@ -196,11 +194,12 @@ This document provides an overview of various AI providers and models, including
|
||||
### Image Models
|
||||
| Model | Base Provider | Providers | Website |
|
||||
|-------|---------------|-----------|---------|
|
||||
|sdxl|Stability AI|2+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/en/using-diffusers/sdxl)|
|
||||
|sdxl|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/en/using-diffusers/sdxl)|
|
||||
|sdxl-lora|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/blog/lcm_lora)|
|
||||
|sdxl-turbo|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/stabilityai/sdxl-turbo)|
|
||||
|sd-1.5|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/runwayml/stable-diffusion-v1-5)|
|
||||
|sd-3|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/stable_diffusion_3)|
|
||||
|sd-3.5|Stability AI|1+ Providers|[stability.ai](https://stability.ai/news/introducing-stable-diffusion-3-5)|
|
||||
|playground-v2.5|Playground AI|1+ Providers|[huggingface.co](https://huggingface.co/playgroundai/playground-v2.5-1024px-aesthetic)|
|
||||
|flux|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)|
|
||||
|flux-pro|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)|
|
||||
@ -210,10 +209,9 @@ This document provides an overview of various AI providers and models, including
|
||||
|flux-disney|Flux AI|1+ Providers|[]()|
|
||||
|flux-pixel|Flux AI|1+ Providers|[]()|
|
||||
|flux-4o|Flux AI|1+ Providers|[]()|
|
||||
|flux-schnell|Black Forest Labs|1+ Providers|[huggingface.co](https://huggingface.co/black-forest-labs/FLUX.1-schnell)|
|
||||
|flux-schnell|Black Forest Labs|2+ Providers|[huggingface.co](https://huggingface.co/black-forest-labs/FLUX.1-schnell)|
|
||||
|dalle|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e/)|
|
||||
|dalle-2|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e-2/)|
|
||||
|dalle-3|OpenAI|2+ Providers|[openai.com](https://openai.com/index/dall-e-3/)|
|
||||
|emi||1+ Providers|[]()|
|
||||
|any-dark||1+ Providers|[]()|
|
||||
|midjourney|Midjourney|1+ Providers|[docs.midjourney.com](https://docs.midjourney.com/docs/model-versions)|
|
||||
|
||||
@ -10,7 +10,7 @@ from .helper import format_prompt
|
||||
class AI365VIP(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://chat.ai365vip.com"
|
||||
api_endpoint = "/api/chat"
|
||||
working = True
|
||||
working = False
|
||||
default_model = 'gpt-3.5-turbo'
|
||||
models = [
|
||||
'gpt-3.5-turbo',
|
||||
|
||||
@ -59,10 +59,6 @@ class AiMathGPT(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
async with ClientSession(headers=headers) as session:
|
||||
data = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": ""
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": format_prompt(messages)
|
||||
|
||||
@ -51,7 +51,6 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
'ReactAgent',
|
||||
'XcodeAgent',
|
||||
'AngularJSAgent',
|
||||
'RepoMap',
|
||||
]
|
||||
|
||||
agentMode = {
|
||||
@ -78,7 +77,6 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
'ReactAgent': {'mode': True, 'id': "React Agent"},
|
||||
'XcodeAgent': {'mode': True, 'id': "Xcode Agent"},
|
||||
'AngularJSAgent': {'mode': True, 'id': "AngularJS Agent"},
|
||||
'RepoMap': {'mode': True, 'id': "repomap"},
|
||||
}
|
||||
|
||||
userSelectedModel = {
|
||||
@ -174,7 +172,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
proxy: Optional[str] = None,
|
||||
image: ImageType = None,
|
||||
image_name: str = None,
|
||||
websearch: bool = False,
|
||||
web_search: bool = False,
|
||||
**kwargs
|
||||
) -> AsyncGenerator[Union[str, ImageResponse], None]:
|
||||
"""
|
||||
@ -186,7 +184,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
proxy (Optional[str]): Proxy URL, if needed.
|
||||
image (ImageType): Image data to be processed, if any.
|
||||
image_name (str): Name of the image file, if an image is provided.
|
||||
websearch (bool): Enables or disables web search mode.
|
||||
web_search (bool): Enables or disables web search mode.
|
||||
**kwargs: Additional keyword arguments.
|
||||
|
||||
Yields:
|
||||
@ -276,7 +274,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
"clickedForceWebSearch": False,
|
||||
"visitFromDelta": False,
|
||||
"mobileClient": False,
|
||||
"webSearchMode": websearch,
|
||||
"webSearchMode": web_search,
|
||||
"userSelectedModel": cls.userSelectedModel.get(model, model)
|
||||
}
|
||||
|
||||
@ -313,7 +311,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
else:
|
||||
yield cleaned_response
|
||||
else:
|
||||
if websearch:
|
||||
if web_search:
|
||||
match = re.search(r'\$~~~\$(.*?)\$~~~\$', cleaned_response, re.DOTALL)
|
||||
if match:
|
||||
source_part = match.group(1).strip()
|
||||
|
||||
151
g4f/Provider/GizAI.py
Normal file
151
g4f/Provider/GizAI.py
Normal file
@ -0,0 +1,151 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import AsyncResult, Messages
|
||||
from ..image import ImageResponse
|
||||
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from .helper import format_prompt
|
||||
|
||||
class GizAI(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
url = "https://app.giz.ai/assistant/"
|
||||
api_endpoint = "https://app.giz.ai/api/data/users/inferenceServer.infer"
|
||||
working = True
|
||||
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
|
||||
# Chat models
|
||||
default_model = 'chat-gemini-flash'
|
||||
chat_models = [
|
||||
default_model,
|
||||
'chat-gemini-pro',
|
||||
'chat-gpt4m',
|
||||
'chat-gpt4',
|
||||
'claude-sonnet',
|
||||
'claude-haiku',
|
||||
'llama-3-70b',
|
||||
'llama-3-8b',
|
||||
'mistral-large',
|
||||
'chat-o1-mini'
|
||||
]
|
||||
|
||||
# Image models
|
||||
image_models = [
|
||||
'flux1',
|
||||
'sdxl',
|
||||
'sd',
|
||||
'sd35',
|
||||
]
|
||||
|
||||
models = [*chat_models, *image_models]
|
||||
|
||||
model_aliases = {
|
||||
# Chat model aliases
|
||||
"gemini-flash": "chat-gemini-flash",
|
||||
"gemini-pro": "chat-gemini-pro",
|
||||
"gpt-4o-mini": "chat-gpt4m",
|
||||
"gpt-4o": "chat-gpt4",
|
||||
"claude-3.5-sonnet": "claude-sonnet",
|
||||
"claude-3-haiku": "claude-haiku",
|
||||
"llama-3.1-70b": "llama-3-70b",
|
||||
"llama-3.1-8b": "llama-3-8b",
|
||||
"o1-mini": "chat-o1-mini",
|
||||
# Image model aliases
|
||||
"sd-1.5": "sd",
|
||||
"sd-3.5": "sd35",
|
||||
"flux-schnell": "flux1",
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
if model in cls.models:
|
||||
return model
|
||||
elif model in cls.model_aliases:
|
||||
return cls.model_aliases[model]
|
||||
else:
|
||||
return cls.default_model
|
||||
|
||||
@classmethod
|
||||
def is_image_model(cls, model: str) -> bool:
|
||||
return model in cls.image_models
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
'Accept': 'application/json, text/plain, */*',
|
||||
'Accept-Language': 'en-US,en;q=0.9',
|
||||
'Cache-Control': 'no-cache',
|
||||
'Connection': 'keep-alive',
|
||||
'Content-Type': 'application/json',
|
||||
'Origin': 'https://app.giz.ai',
|
||||
'Pragma': 'no-cache',
|
||||
'Sec-Fetch-Dest': 'empty',
|
||||
'Sec-Fetch-Mode': 'cors',
|
||||
'Sec-Fetch-Site': 'same-origin',
|
||||
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36',
|
||||
'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"',
|
||||
'sec-ch-ua-mobile': '?0',
|
||||
'sec-ch-ua-platform': '"Linux"'
|
||||
}
|
||||
|
||||
async with ClientSession() as session:
|
||||
if cls.is_image_model(model):
|
||||
# Image generation
|
||||
prompt = messages[-1]["content"]
|
||||
data = {
|
||||
"model": model,
|
||||
"input": {
|
||||
"width": "1024",
|
||||
"height": "1024",
|
||||
"steps": 4,
|
||||
"output_format": "webp",
|
||||
"batch_size": 1,
|
||||
"mode": "plan",
|
||||
"prompt": prompt
|
||||
}
|
||||
}
|
||||
async with session.post(
|
||||
cls.api_endpoint,
|
||||
headers=headers,
|
||||
data=json.dumps(data),
|
||||
proxy=proxy
|
||||
) as response:
|
||||
response.raise_for_status()
|
||||
response_data = await response.json()
|
||||
if response_data.get('status') == 'completed' and response_data.get('output'):
|
||||
for url in response_data['output']:
|
||||
yield ImageResponse(images=url, alt="Generated Image")
|
||||
else:
|
||||
# Chat completion
|
||||
data = {
|
||||
"model": model,
|
||||
"input": {
|
||||
"messages": [
|
||||
{
|
||||
"type": "human",
|
||||
"content": format_prompt(messages)
|
||||
}
|
||||
],
|
||||
"mode": "plan"
|
||||
},
|
||||
"noStream": True
|
||||
}
|
||||
async with session.post(
|
||||
cls.api_endpoint,
|
||||
headers=headers,
|
||||
data=json.dumps(data),
|
||||
proxy=proxy
|
||||
) as response:
|
||||
response.raise_for_status()
|
||||
result = await response.json()
|
||||
yield result.get('output', '')
|
||||
@ -47,6 +47,7 @@ from .FreeChatgpt import FreeChatgpt
|
||||
from .FreeGpt import FreeGpt
|
||||
from .FreeNetfly import FreeNetfly
|
||||
from .GeminiPro import GeminiPro
|
||||
from .GizAI import GizAI
|
||||
from .GPROChat import GPROChat
|
||||
from .HuggingChat import HuggingChat
|
||||
from .HuggingFace import HuggingFace
|
||||
|
||||
@ -1,45 +1,52 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import requests
|
||||
from typing import Any, Dict
|
||||
|
||||
from ...typing import CreateResult, Messages
|
||||
from ..base_provider import ProviderModelMixin, AbstractProvider
|
||||
from ...typing import AsyncResult, Messages
|
||||
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
|
||||
from ..helper import format_prompt
|
||||
|
||||
class NexraChatGPT(AbstractProvider, ProviderModelMixin):
|
||||
|
||||
class NexraChatGPT(AsyncGeneratorProvider, ProviderModelMixin):
|
||||
label = "Nexra ChatGPT"
|
||||
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
|
||||
api_endpoint = "https://nexra.aryahcr.cc/api/chat/gpt"
|
||||
api_endpoint_nexra_chatgpt = "https://nexra.aryahcr.cc/api/chat/gpt"
|
||||
api_endpoint_nexra_chatgpt4o = "https://nexra.aryahcr.cc/api/chat/complements"
|
||||
api_endpoint_nexra_chatgpt_v2 = "https://nexra.aryahcr.cc/api/chat/complements"
|
||||
api_endpoint_nexra_gptweb = "https://nexra.aryahcr.cc/api/chat/gptweb"
|
||||
working = True
|
||||
supports_system_message = True
|
||||
supports_message_history = True
|
||||
supports_stream = True
|
||||
|
||||
default_model = 'gpt-3.5-turbo'
|
||||
models = ['gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314', default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002']
|
||||
nexra_chatgpt = [
|
||||
'gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314',
|
||||
default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301',
|
||||
'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002'
|
||||
]
|
||||
nexra_chatgpt4o = ['gpt-4o']
|
||||
nexra_chatgptv2 = ['chatgpt']
|
||||
nexra_gptweb = ['gptweb']
|
||||
models = nexra_chatgpt + nexra_chatgpt4o + nexra_chatgptv2 + nexra_gptweb
|
||||
|
||||
model_aliases = {
|
||||
"gpt-4": "gpt-4-0613",
|
||||
"gpt-4": "gpt-4-32k",
|
||||
"gpt-4": "gpt-4-0314",
|
||||
"gpt-4": "gpt-4-32k-0314",
|
||||
|
||||
"gpt-4-32k": "gpt-4-32k-0314",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-16k-0613",
|
||||
"gpt-3.5-turbo": "gpt-3.5-turbo-0301",
|
||||
|
||||
"gpt-3.5-turbo-0613": "gpt-3.5-turbo-16k-0613",
|
||||
"gpt-3": "text-davinci-003",
|
||||
"gpt-3": "text-davinci-002",
|
||||
"gpt-3": "code-davinci-002",
|
||||
"gpt-3": "text-curie-001",
|
||||
"gpt-3": "text-babbage-001",
|
||||
"gpt-3": "text-ada-001",
|
||||
"gpt-3": "text-ada-001",
|
||||
"gpt-3": "davinci",
|
||||
"gpt-3": "curie",
|
||||
"gpt-3": "babbage",
|
||||
"gpt-3": "ada",
|
||||
"gpt-3": "babbage-002",
|
||||
"gpt-3": "davinci-002",
|
||||
"text-davinci-002": "code-davinci-002",
|
||||
"text-curie-001": "text-babbage-001",
|
||||
"text-ada-001": "davinci",
|
||||
"curie": "babbage",
|
||||
"ada": "babbage-002",
|
||||
"davinci-002": "davinci-002",
|
||||
"chatgpt": "chatgpt",
|
||||
"gptweb": "gptweb"
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@ -50,40 +57,229 @@ class NexraChatGPT(AbstractProvider, ProviderModelMixin):
|
||||
return cls.model_aliases[model]
|
||||
else:
|
||||
return cls.default_model
|
||||
|
||||
|
||||
@classmethod
|
||||
def create_completion(
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool = False,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
if model in cls.nexra_chatgpt:
|
||||
async for chunk in cls._create_async_generator_nexra_chatgpt(model, messages, proxy, **kwargs):
|
||||
yield chunk
|
||||
elif model in cls.nexra_chatgpt4o:
|
||||
async for chunk in cls._create_async_generator_nexra_chatgpt4o(model, messages, stream, proxy, markdown, **kwargs):
|
||||
yield chunk
|
||||
elif model in cls.nexra_chatgptv2:
|
||||
async for chunk in cls._create_async_generator_nexra_chatgpt_v2(model, messages, stream, proxy, markdown, **kwargs):
|
||||
yield chunk
|
||||
elif model in cls.nexra_gptweb:
|
||||
async for chunk in cls._create_async_generator_nexra_gptweb(model, messages, proxy, **kwargs):
|
||||
yield chunk
|
||||
|
||||
@classmethod
|
||||
async def _create_async_generator_nexra_chatgpt(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json'
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
prompt = format_prompt(messages)
|
||||
data = {
|
||||
"messages": [],
|
||||
"prompt": format_prompt(messages),
|
||||
"messages": messages,
|
||||
"prompt": prompt,
|
||||
"model": model,
|
||||
"markdown": markdown
|
||||
}
|
||||
|
||||
response = requests.post(cls.api_endpoint, headers=headers, json=data)
|
||||
|
||||
return cls.process_response(response)
|
||||
loop = asyncio.get_event_loop()
|
||||
try:
|
||||
response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt, data, headers, proxy)
|
||||
filtered_response = cls._filter_response(response)
|
||||
|
||||
for chunk in filtered_response:
|
||||
yield chunk
|
||||
except Exception as e:
|
||||
print(f"Error during API request (nexra_chatgpt): {e}")
|
||||
|
||||
@classmethod
|
||||
def process_response(cls, response):
|
||||
async def _create_async_generator_nexra_chatgpt4o(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool = False,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
prompt = format_prompt(messages)
|
||||
data = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
}
|
||||
],
|
||||
"stream": stream,
|
||||
"markdown": markdown,
|
||||
"model": model
|
||||
}
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
try:
|
||||
response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt4o, data, headers, proxy, stream)
|
||||
|
||||
if stream:
|
||||
async for chunk in cls._process_streaming_response(response):
|
||||
yield chunk
|
||||
else:
|
||||
for chunk in cls._process_non_streaming_response(response):
|
||||
yield chunk
|
||||
except Exception as e:
|
||||
print(f"Error during API request (nexra_chatgpt4o): {e}")
|
||||
|
||||
@classmethod
|
||||
async def _create_async_generator_nexra_chatgpt_v2(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool = False,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
prompt = format_prompt(messages)
|
||||
data = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
}
|
||||
],
|
||||
"stream": stream,
|
||||
"markdown": markdown,
|
||||
"model": model
|
||||
}
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
try:
|
||||
response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt_v2, data, headers, proxy, stream)
|
||||
|
||||
if stream:
|
||||
async for chunk in cls._process_streaming_response(response):
|
||||
yield chunk
|
||||
else:
|
||||
for chunk in cls._process_non_streaming_response(response):
|
||||
yield chunk
|
||||
except Exception as e:
|
||||
print(f"Error during API request (nexra_chatgpt_v2): {e}")
|
||||
|
||||
@classmethod
|
||||
async def _create_async_generator_nexra_gptweb(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> AsyncResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
prompt = format_prompt(messages)
|
||||
data = {
|
||||
"prompt": prompt,
|
||||
"markdown": markdown,
|
||||
}
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
try:
|
||||
response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_gptweb, data, headers, proxy)
|
||||
|
||||
for chunk in response.iter_content(1024):
|
||||
if chunk:
|
||||
decoded_chunk = chunk.decode().lstrip('_')
|
||||
try:
|
||||
response_json = json.loads(decoded_chunk)
|
||||
if response_json.get("status"):
|
||||
yield response_json.get("gpt", "")
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
except Exception as e:
|
||||
print(f"Error during API request (nexra_gptweb): {e}")
|
||||
|
||||
@staticmethod
|
||||
def _sync_post_request(url: str, data: Dict[str, Any], headers: Dict[str, str], proxy: str = None, stream: bool = False) -> requests.Response:
|
||||
proxies = {
|
||||
"http": proxy,
|
||||
"https": proxy,
|
||||
} if proxy else None
|
||||
|
||||
try:
|
||||
response = requests.post(url, json=data, headers=headers, proxies=proxies, stream=stream)
|
||||
response.raise_for_status()
|
||||
return response
|
||||
except requests.RequestException as e:
|
||||
print(f"Request failed: {e}")
|
||||
raise
|
||||
|
||||
@staticmethod
|
||||
def _process_non_streaming_response(response: requests.Response) -> str:
|
||||
if response.status_code == 200:
|
||||
try:
|
||||
data = response.json()
|
||||
return data.get('gpt', '')
|
||||
content = response.text.lstrip(' ')
|
||||
data = json.loads(content)
|
||||
return data.get('message', '')
|
||||
except json.JSONDecodeError:
|
||||
return "Error: Unable to decode JSON response"
|
||||
else:
|
||||
return f"Error: {response.status_code}"
|
||||
|
||||
@staticmethod
|
||||
async def _process_streaming_response(response: requests.Response):
|
||||
full_message = ""
|
||||
for line in response.iter_lines(decode_unicode=True):
|
||||
if line:
|
||||
try:
|
||||
line = line.lstrip(' ')
|
||||
data = json.loads(line)
|
||||
if data.get('finish'):
|
||||
break
|
||||
message = data.get('message', '')
|
||||
if message:
|
||||
yield message[len(full_message):]
|
||||
full_message = message
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
@staticmethod
|
||||
def _filter_response(response: requests.Response) -> str:
|
||||
response_json = response.json()
|
||||
return response_json.get("gpt", "")
|
||||
|
||||
@ -1,86 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import requests
|
||||
|
||||
from ...typing import CreateResult, Messages
|
||||
from ..base_provider import ProviderModelMixin, AbstractProvider
|
||||
from ..helper import format_prompt
|
||||
|
||||
class NexraChatGPT4o(AbstractProvider, ProviderModelMixin):
|
||||
label = "Nexra ChatGPT4o"
|
||||
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
|
||||
api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
|
||||
working = True
|
||||
supports_stream = True
|
||||
|
||||
default_model = "gpt-4o"
|
||||
models = [default_model]
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
return cls.default_model
|
||||
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json'
|
||||
}
|
||||
|
||||
data = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": format_prompt(messages)
|
||||
}
|
||||
],
|
||||
"stream": stream,
|
||||
"markdown": markdown,
|
||||
"model": model
|
||||
}
|
||||
|
||||
response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)
|
||||
|
||||
if stream:
|
||||
return cls.process_streaming_response(response)
|
||||
else:
|
||||
return cls.process_non_streaming_response(response)
|
||||
|
||||
@classmethod
|
||||
def process_non_streaming_response(cls, response):
|
||||
if response.status_code == 200:
|
||||
try:
|
||||
content = response.text.lstrip(' ')
|
||||
data = json.loads(content)
|
||||
return data.get('message', '')
|
||||
except json.JSONDecodeError:
|
||||
return "Error: Unable to decode JSON response"
|
||||
else:
|
||||
return f"Error: {response.status_code}"
|
||||
|
||||
@classmethod
|
||||
def process_streaming_response(cls, response):
|
||||
full_message = ""
|
||||
for line in response.iter_lines(decode_unicode=True):
|
||||
if line:
|
||||
try:
|
||||
line = line.lstrip(' ')
|
||||
data = json.loads(line)
|
||||
if data.get('finish'):
|
||||
break
|
||||
message = data.get('message', '')
|
||||
if message and message != full_message:
|
||||
yield message[len(full_message):]
|
||||
full_message = message
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
@ -1,92 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import requests
|
||||
|
||||
from ...typing import CreateResult, Messages
|
||||
from ..base_provider import ProviderModelMixin, AbstractProvider
|
||||
from ..helper import format_prompt
|
||||
|
||||
class NexraChatGptV2(AbstractProvider, ProviderModelMixin):
|
||||
label = "Nexra ChatGPT v2"
|
||||
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
|
||||
api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
|
||||
working = True
|
||||
supports_stream = True
|
||||
|
||||
default_model = 'chatgpt'
|
||||
models = [default_model]
|
||||
model_aliases = {"gpt-4": "chatgpt"}
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
if model in cls.models:
|
||||
return model
|
||||
elif model in cls.model_aliases:
|
||||
return cls.model_aliases[model]
|
||||
else:
|
||||
return cls.default_model
|
||||
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
stream: bool,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
model = cls.get_model(model)
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json'
|
||||
}
|
||||
|
||||
data = {
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": format_prompt(messages)
|
||||
}
|
||||
],
|
||||
"stream": stream,
|
||||
"markdown": markdown,
|
||||
"model": model
|
||||
}
|
||||
|
||||
response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)
|
||||
|
||||
if stream:
|
||||
return cls.process_streaming_response(response)
|
||||
else:
|
||||
return cls.process_non_streaming_response(response)
|
||||
|
||||
@classmethod
|
||||
def process_non_streaming_response(cls, response):
|
||||
if response.status_code == 200:
|
||||
try:
|
||||
content = response.text.lstrip(' ')
|
||||
data = json.loads(content)
|
||||
return data.get('message', '')
|
||||
except json.JSONDecodeError:
|
||||
return "Error: Unable to decode JSON response"
|
||||
else:
|
||||
return f"Error: {response.status_code}"
|
||||
|
||||
@classmethod
|
||||
def process_streaming_response(cls, response):
|
||||
full_message = ""
|
||||
for line in response.iter_lines(decode_unicode=True):
|
||||
if line:
|
||||
try:
|
||||
line = line.lstrip(' ')
|
||||
data = json.loads(line)
|
||||
if data.get('finish'):
|
||||
break
|
||||
message = data.get('message', '')
|
||||
if message:
|
||||
yield message[len(full_message):]
|
||||
full_message = message
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
@ -1,64 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import requests
|
||||
|
||||
from ...typing import CreateResult, Messages
|
||||
from ..base_provider import ProviderModelMixin, AbstractProvider
|
||||
from ..helper import format_prompt
|
||||
|
||||
class NexraChatGptWeb(AbstractProvider, ProviderModelMixin):
|
||||
label = "Nexra ChatGPT Web"
|
||||
url = "https://nexra.aryahcr.cc/documentation/chatgpt/en"
|
||||
working = True
|
||||
|
||||
default_model = "gptweb"
|
||||
models = [default_model]
|
||||
model_aliases = {"gpt-4": "gptweb"}
|
||||
api_endpoints = {"gptweb": "https://nexra.aryahcr.cc/api/chat/gptweb"}
|
||||
|
||||
@classmethod
|
||||
def get_model(cls, model: str) -> str:
|
||||
if model in cls.models:
|
||||
return model
|
||||
elif model in cls.model_aliases:
|
||||
return cls.model_aliases[model]
|
||||
else:
|
||||
return cls.default_model
|
||||
|
||||
@classmethod
|
||||
def create_completion(
|
||||
cls,
|
||||
model: str,
|
||||
messages: Messages,
|
||||
proxy: str = None,
|
||||
markdown: bool = False,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
model = cls.get_model(model)
|
||||
api_endpoint = cls.api_endpoints.get(model, cls.api_endpoints[cls.default_model])
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json'
|
||||
}
|
||||
|
||||
data = {
|
||||
"prompt": format_prompt(messages),
|
||||
"markdown": markdown
|
||||
}
|
||||
|
||||
response = requests.post(api_endpoint, headers=headers, json=data)
|
||||
|
||||
return cls.process_response(response)
|
||||
|
||||
@classmethod
|
||||
def process_response(cls, response):
|
||||
if response.status_code == 200:
|
||||
try:
|
||||
content = response.text.lstrip('_')
|
||||
json_response = json.loads(content)
|
||||
return json_response.get('gpt', '')
|
||||
except json.JSONDecodeError:
|
||||
return "Error: Unable to decode JSON response"
|
||||
else:
|
||||
return f"Error: {response.status_code}"
|
||||
@ -1,9 +1,6 @@
|
||||
from .NexraBing import NexraBing
|
||||
from .NexraBlackbox import NexraBlackbox
|
||||
from .NexraChatGPT import NexraChatGPT
|
||||
from .NexraChatGPT4o import NexraChatGPT4o
|
||||
from .NexraChatGptV2 import NexraChatGptV2
|
||||
from .NexraChatGptWeb import NexraChatGptWeb
|
||||
from .NexraDallE import NexraDallE
|
||||
from .NexraDallE2 import NexraDallE2
|
||||
from .NexraEmi import NexraEmi
|
||||
|
||||
@ -14,17 +14,18 @@ from starlette.status import HTTP_422_UNPROCESSABLE_ENTITY, HTTP_401_UNAUTHORIZE
|
||||
from fastapi.encoders import jsonable_encoder
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel
|
||||
from typing import Union, Optional
|
||||
from typing import Union, Optional, Iterator
|
||||
|
||||
import g4f
|
||||
import g4f.debug
|
||||
from g4f.client import Client
|
||||
from g4f.client import Client, ChatCompletion, ChatCompletionChunk, ImagesResponse
|
||||
from g4f.typing import Messages
|
||||
from g4f.cookies import read_cookie_files
|
||||
|
||||
def create_app():
|
||||
def create_app(g4f_api_key: str = None):
|
||||
app = FastAPI()
|
||||
api = Api(app)
|
||||
|
||||
# Add CORS middleware
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origin_regex=".*",
|
||||
@ -32,18 +33,19 @@ def create_app():
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
api = Api(app, g4f_api_key=g4f_api_key)
|
||||
api.register_routes()
|
||||
api.register_authorization()
|
||||
api.register_validation_exception_handler()
|
||||
|
||||
# Read cookie files if not ignored
|
||||
if not AppConfig.ignore_cookie_files:
|
||||
read_cookie_files()
|
||||
|
||||
return app
|
||||
|
||||
def create_app_debug():
|
||||
g4f.debug.logging = True
|
||||
return create_app()
|
||||
|
||||
class ChatCompletionsForm(BaseModel):
|
||||
class ChatCompletionsConfig(BaseModel):
|
||||
messages: Messages
|
||||
model: str
|
||||
provider: Optional[str] = None
|
||||
@ -55,15 +57,12 @@ class ChatCompletionsForm(BaseModel):
|
||||
web_search: Optional[bool] = None
|
||||
proxy: Optional[str] = None
|
||||
|
||||
class ImagesGenerateForm(BaseModel):
|
||||
model: Optional[str] = None
|
||||
provider: Optional[str] = None
|
||||
class ImageGenerationConfig(BaseModel):
|
||||
prompt: str
|
||||
response_format: Optional[str] = None
|
||||
api_key: Optional[str] = None
|
||||
proxy: Optional[str] = None
|
||||
model: Optional[str] = None
|
||||
response_format: str = "url"
|
||||
|
||||
class AppConfig():
|
||||
class AppConfig:
|
||||
ignored_providers: Optional[list[str]] = None
|
||||
g4f_api_key: Optional[str] = None
|
||||
ignore_cookie_files: bool = False
|
||||
@ -74,16 +73,23 @@ class AppConfig():
|
||||
for key, value in data.items():
|
||||
setattr(cls, key, value)
|
||||
|
||||
list_ignored_providers: list[str] = None
|
||||
|
||||
def set_list_ignored_providers(ignored: list[str]):
|
||||
global list_ignored_providers
|
||||
list_ignored_providers = ignored
|
||||
|
||||
class Api:
|
||||
def __init__(self, app: FastAPI) -> None:
|
||||
def __init__(self, app: FastAPI, g4f_api_key=None) -> None:
|
||||
self.app = app
|
||||
self.client = Client()
|
||||
self.g4f_api_key = g4f_api_key
|
||||
self.get_g4f_api_key = APIKeyHeader(name="g4f-api-key")
|
||||
|
||||
def register_authorization(self):
|
||||
@self.app.middleware("http")
|
||||
async def authorization(request: Request, call_next):
|
||||
if AppConfig.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions"]:
|
||||
if self.g4f_api_key and request.url.path in ["/v1/chat/completions", "/v1/completions", "/v1/images/generate"]:
|
||||
try:
|
||||
user_g4f_api_key = await self.get_g4f_api_key(request)
|
||||
except HTTPException as e:
|
||||
@ -92,22 +98,26 @@ class Api:
|
||||
status_code=HTTP_401_UNAUTHORIZED,
|
||||
content=jsonable_encoder({"detail": "G4F API key required"}),
|
||||
)
|
||||
if not secrets.compare_digest(AppConfig.g4f_api_key, user_g4f_api_key):
|
||||
if not secrets.compare_digest(self.g4f_api_key, user_g4f_api_key):
|
||||
return JSONResponse(
|
||||
status_code=HTTP_403_FORBIDDEN,
|
||||
content=jsonable_encoder({"detail": "Invalid G4F API key"}),
|
||||
)
|
||||
return await call_next(request)
|
||||
|
||||
response = await call_next(request)
|
||||
return response
|
||||
|
||||
def register_validation_exception_handler(self):
|
||||
@self.app.exception_handler(RequestValidationError)
|
||||
async def validation_exception_handler(request: Request, exc: RequestValidationError):
|
||||
details = exc.errors()
|
||||
modified_details = [{
|
||||
"loc": error["loc"],
|
||||
"message": error["msg"],
|
||||
"type": error["type"],
|
||||
} for error in details]
|
||||
modified_details = []
|
||||
for error in details:
|
||||
modified_details.append({
|
||||
"loc": error["loc"],
|
||||
"message": error["msg"],
|
||||
"type": error["type"],
|
||||
})
|
||||
return JSONResponse(
|
||||
status_code=HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
content=jsonable_encoder({"detail": modified_details}),
|
||||
@ -121,25 +131,23 @@ class Api:
|
||||
@self.app.get("/v1")
|
||||
async def read_root_v1():
|
||||
return HTMLResponse('g4f API: Go to '
|
||||
'<a href="/v1/chat/completions">chat/completions</a> '
|
||||
'or <a href="/v1/models">models</a>.')
|
||||
'<a href="/v1/chat/completions">chat/completions</a>, '
|
||||
'<a href="/v1/models">models</a>, or '
|
||||
'<a href="/v1/images/generate">images/generate</a>.')
|
||||
|
||||
@self.app.get("/v1/models")
|
||||
async def models():
|
||||
model_list = {
|
||||
model: g4f.models.ModelUtils.convert[model]
|
||||
model_list = dict(
|
||||
(model, g4f.models.ModelUtils.convert[model])
|
||||
for model in g4f.Model.__all__()
|
||||
}
|
||||
)
|
||||
model_list = [{
|
||||
'id': model_id,
|
||||
'object': 'model',
|
||||
'created': 0,
|
||||
'owned_by': model.base_provider
|
||||
} for model_id, model in model_list.items()]
|
||||
return JSONResponse({
|
||||
"object": "list",
|
||||
"data": model_list,
|
||||
})
|
||||
return JSONResponse(model_list)
|
||||
|
||||
@self.app.get("/v1/models/{model_name}")
|
||||
async def model_info(model_name: str):
|
||||
@ -155,7 +163,7 @@ class Api:
|
||||
return JSONResponse({"error": "The model does not exist."})
|
||||
|
||||
@self.app.post("/v1/chat/completions")
|
||||
async def chat_completions(config: ChatCompletionsForm, request: Request = None, provider: str = None):
|
||||
async def chat_completions(config: ChatCompletionsConfig, request: Request = None, provider: str = None):
|
||||
try:
|
||||
config.provider = provider if config.provider is None else config.provider
|
||||
if config.api_key is None and request is not None:
|
||||
@ -164,17 +172,27 @@ class Api:
|
||||
auth_header = auth_header.split(None, 1)[-1]
|
||||
if auth_header and auth_header != "Bearer":
|
||||
config.api_key = auth_header
|
||||
# Use the asynchronous create method and await it
|
||||
response = await self.client.chat.completions.async_create(
|
||||
|
||||
# Create the completion response
|
||||
response = self.client.chat.completions.create(
|
||||
**{
|
||||
**AppConfig.defaults,
|
||||
**config.dict(exclude_none=True),
|
||||
},
|
||||
ignored=AppConfig.ignored_providers
|
||||
)
|
||||
if not config.stream:
|
||||
|
||||
# Check if the response is synchronous or asynchronous
|
||||
if isinstance(response, ChatCompletion):
|
||||
# Synchronous response
|
||||
return JSONResponse(response.to_json())
|
||||
|
||||
if not config.stream:
|
||||
# If the response is an iterator but not streaming, collect the result
|
||||
response_list = list(response) if isinstance(response, Iterator) else [response]
|
||||
return JSONResponse(response_list[0].to_json())
|
||||
|
||||
# Streaming response
|
||||
async def streaming():
|
||||
try:
|
||||
async for chunk in response:
|
||||
@ -185,41 +203,38 @@ class Api:
|
||||
logging.exception(e)
|
||||
yield f'data: {format_exception(e, config)}\n\n'
|
||||
yield "data: [DONE]\n\n"
|
||||
|
||||
return StreamingResponse(streaming(), media_type="text/event-stream")
|
||||
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
return Response(content=format_exception(e, config), status_code=500, media_type="application/json")
|
||||
|
||||
@self.app.post("/v1/images/generate")
|
||||
async def generate_image(config: ImageGenerationConfig):
|
||||
try:
|
||||
response: ImagesResponse = await self.client.images.async_generate(
|
||||
prompt=config.prompt,
|
||||
model=config.model,
|
||||
response_format=config.response_format
|
||||
)
|
||||
# Convert Image objects to dictionaries
|
||||
response_data = [image.to_dict() for image in response.data]
|
||||
return JSONResponse({"data": response_data})
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
return Response(content=format_exception(e, config), status_code=500, media_type="application/json")
|
||||
|
||||
@self.app.post("/v1/completions")
|
||||
async def completions():
|
||||
return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json")
|
||||
|
||||
@self.app.post("/v1/images/generations")
|
||||
async def images_generate(config: ImagesGenerateForm, request: Request = None, provider: str = None):
|
||||
try:
|
||||
config.provider = provider if config.provider is None else config.provider
|
||||
if config.api_key is None and request is not None:
|
||||
auth_header = request.headers.get("Authorization")
|
||||
if auth_header is not None:
|
||||
auth_header = auth_header.split(None, 1)[-1]
|
||||
if auth_header and auth_header != "Bearer":
|
||||
config.api_key = auth_header
|
||||
# Use the asynchronous generate method and await it
|
||||
response = await self.client.images.async_generate(
|
||||
**config.dict(exclude_none=True),
|
||||
)
|
||||
return JSONResponse(response.to_json())
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
return Response(content=format_exception(e, config), status_code=500, media_type="application/json")
|
||||
|
||||
def format_exception(e: Exception, config: ChatCompletionsForm) -> str:
|
||||
def format_exception(e: Exception, config: Union[ChatCompletionsConfig, ImageGenerationConfig]) -> str:
|
||||
last_provider = g4f.get_last_provider(True)
|
||||
return json.dumps({
|
||||
"error": {"message": f"{e.__class__.__name__}: {e}"},
|
||||
"model": last_provider.get("model") if last_provider else config.model,
|
||||
"provider": last_provider.get("name") if last_provider else config.provider
|
||||
"model": last_provider.get("model") if last_provider else getattr(config, 'model', None),
|
||||
"provider": last_provider.get("name") if last_provider else getattr(config, 'provider', None)
|
||||
})
|
||||
|
||||
def run_api(
|
||||
@ -228,18 +243,22 @@ def run_api(
|
||||
bind: str = None,
|
||||
debug: bool = False,
|
||||
workers: int = None,
|
||||
use_colors: bool = None
|
||||
use_colors: bool = None,
|
||||
g4f_api_key: str = None
|
||||
) -> None:
|
||||
print(f'Starting server... [g4f v-{g4f.version.utils.current_version}]' + (" (debug)" if debug else ""))
|
||||
if use_colors is None:
|
||||
use_colors = debug
|
||||
if bind is not None:
|
||||
host, port = bind.split(":")
|
||||
if debug:
|
||||
g4f.debug.logging = True
|
||||
uvicorn.run(
|
||||
f"g4f.api:create_app{'_debug' if debug else ''}",
|
||||
host=host, port=int(port),
|
||||
workers=workers,
|
||||
use_colors=use_colors,
|
||||
factory=True,
|
||||
"g4f.api:create_app",
|
||||
host=host,
|
||||
port=int(port),
|
||||
workers=workers,
|
||||
use_colors=use_colors,
|
||||
factory=True,
|
||||
reload=debug
|
||||
)
|
||||
|
||||
@ -531,3 +531,4 @@ class Images:
|
||||
async def create_variation(self, image: Union[str, bytes], model: str = None, response_format: str = "url", **kwargs):
|
||||
# Existing implementation, adjust if you want to support b64_json here as well
|
||||
pass
|
||||
|
||||
|
||||
@ -224,28 +224,35 @@
|
||||
</div>
|
||||
</div>
|
||||
<div class="buttons">
|
||||
<div class="field">
|
||||
<select name="model" id="model">
|
||||
<option value="">Model: Default</option>
|
||||
<option value="gpt-4">gpt-4</option>
|
||||
<option value="gpt-3.5-turbo">gpt-3.5-turbo</option>
|
||||
<option value="llama-3-70b-chat">llama-3-70b-chat</option>
|
||||
<option value="llama-3.1-70b">llama-3.1-70b</option>
|
||||
<option value="gemini-pro">gemini-pro</option>
|
||||
<option value="">----</option>
|
||||
</select>
|
||||
<select name="model2" id="model2" class="hidden"></select>
|
||||
</div>
|
||||
<div class="field">
|
||||
<select name="provider" id="provider">
|
||||
<option value="">Provider: Auto</option>
|
||||
<option value="Bing">Bing</option>
|
||||
<option value="OpenaiChat">OpenAI ChatGPT</option>
|
||||
<option value="Gemini">Gemini</option>
|
||||
<option value="Liaobots">Liaobots</option>
|
||||
<option value="MetaAI">Meta AI</option>
|
||||
<option value="You">You</option>
|
||||
<option value="">----</option>
|
||||
<div class="field">
|
||||
<select name="model" id="model">
|
||||
<option value="">Model: Default</option>
|
||||
<option value="gpt-4">gpt-4</option>
|
||||
<option value="gpt-4o">gpt-4o</option>
|
||||
<option value="gpt-4o-mini">gpt-4o-mini</option>
|
||||
<option value="llama-3.1-70b">llama-3.1-70b</option>
|
||||
<option value="llama-3.1-70b">llama-3.1-405b</option>
|
||||
<option value="llama-3.1-70b">mixtral-8x7b</option>
|
||||
<option value="gemini-pro">gemini-pro</option>
|
||||
<option value="gemini-flash">gemini-flash</option>
|
||||
<option value="claude-3-haiku">claude-3-haiku</option>
|
||||
<option value="claude-3.5-sonnet">claude-3.5-sonnet</option>
|
||||
<option value="">----</option>
|
||||
</select>
|
||||
<select name="model2" id="model2" class="hidden"></select>
|
||||
</div>
|
||||
<div class="field">
|
||||
<select name="provider" id="provider">
|
||||
<option value="">Provider: Auto</option>
|
||||
<option value="OpenaiChat">OpenAI ChatGPT</option>
|
||||
<option value="Gemini">Gemini</option>
|
||||
<option value="MetaAI">Meta AI</option>
|
||||
<option value="DeepInfraChat">DeepInfraChat</option>
|
||||
<option value="Blackbox">Blackbox</option>
|
||||
<option value="HuggingChat">HuggingChat</option>
|
||||
<option value="DDG">DDG</option>
|
||||
<option value="Pizzagpt">Pizzagpt</option>
|
||||
<option value="">----</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@ -338,6 +338,14 @@ const prepare_messages = (messages, message_index = -1) => {
|
||||
messages = messages.filter((_, index) => message_index >= index);
|
||||
}
|
||||
|
||||
let new_messages = [];
|
||||
if (systemPrompt?.value) {
|
||||
new_messages.push({
|
||||
"role": "system",
|
||||
"content": systemPrompt.value
|
||||
});
|
||||
}
|
||||
|
||||
// Remove history, if it's selected
|
||||
if (document.getElementById('history')?.checked) {
|
||||
if (message_index == null) {
|
||||
@ -347,13 +355,6 @@ const prepare_messages = (messages, message_index = -1) => {
|
||||
}
|
||||
}
|
||||
|
||||
let new_messages = [];
|
||||
if (systemPrompt?.value) {
|
||||
new_messages.push({
|
||||
"role": "system",
|
||||
"content": systemPrompt.value
|
||||
});
|
||||
}
|
||||
messages.forEach((new_message) => {
|
||||
// Include only not regenerated messages
|
||||
if (new_message && !new_message.regenerate) {
|
||||
@ -366,6 +367,7 @@ const prepare_messages = (messages, message_index = -1) => {
|
||||
return new_messages;
|
||||
}
|
||||
|
||||
|
||||
async function add_message_chunk(message) {
|
||||
if (message.type == "conversation") {
|
||||
console.info("Conversation used:", message.conversation)
|
||||
|
||||
@ -2,12 +2,11 @@ from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
import os.path
|
||||
import uuid
|
||||
import asyncio
|
||||
import time
|
||||
from aiohttp import ClientSession
|
||||
from typing import Iterator, Optional
|
||||
from typing import Iterator, Optional, AsyncIterator, Union
|
||||
from flask import send_from_directory
|
||||
|
||||
from g4f import version, models
|
||||
@ -20,21 +19,20 @@ from g4f.Provider import ProviderType, __providers__, __map__
|
||||
from g4f.providers.base_provider import ProviderModelMixin, FinishReason
|
||||
from g4f.providers.conversation import BaseConversation
|
||||
|
||||
conversations: dict[dict[str, BaseConversation]] = {}
|
||||
# Define the directory for generated images
|
||||
images_dir = "./generated_images"
|
||||
|
||||
# Function to ensure the images directory exists
|
||||
def ensure_images_dir():
|
||||
if not os.path.exists(images_dir):
|
||||
os.makedirs(images_dir)
|
||||
|
||||
conversations: dict[dict[str, BaseConversation]] = {}
|
||||
|
||||
|
||||
class Api:
|
||||
@staticmethod
|
||||
def get_models() -> list[str]:
|
||||
"""
|
||||
Return a list of all models.
|
||||
|
||||
Fetches and returns a list of all available models in the system.
|
||||
|
||||
Returns:
|
||||
List[str]: A list of model names.
|
||||
"""
|
||||
return models._all_models
|
||||
|
||||
@staticmethod
|
||||
@ -82,9 +80,6 @@ class Api:
|
||||
|
||||
@staticmethod
|
||||
def get_providers() -> list[str]:
|
||||
"""
|
||||
Return a list of all working providers.
|
||||
"""
|
||||
return {
|
||||
provider.__name__: (
|
||||
provider.label if hasattr(provider, "label") else provider.__name__
|
||||
@ -99,12 +94,6 @@ class Api:
|
||||
|
||||
@staticmethod
|
||||
def get_version():
|
||||
"""
|
||||
Returns the current and latest version of the application.
|
||||
|
||||
Returns:
|
||||
dict: A dictionary containing the current and latest version.
|
||||
"""
|
||||
try:
|
||||
current_version = version.utils.current_version
|
||||
except VersionNotFoundError:
|
||||
@ -115,18 +104,10 @@ class Api:
|
||||
}
|
||||
|
||||
def serve_images(self, name):
|
||||
ensure_images_dir()
|
||||
return send_from_directory(os.path.abspath(images_dir), name)
|
||||
|
||||
def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict):
|
||||
"""
|
||||
Prepares arguments for chat completion based on the request data.
|
||||
|
||||
Reads the request and prepares the necessary arguments for handling
|
||||
a chat completion request.
|
||||
|
||||
Returns:
|
||||
dict: Arguments prepared for chat completion.
|
||||
"""
|
||||
model = json_data.get('model') or models.default
|
||||
provider = json_data.get('provider')
|
||||
messages = json_data['messages']
|
||||
@ -134,7 +115,7 @@ class Api:
|
||||
if api_key is not None:
|
||||
kwargs["api_key"] = api_key
|
||||
if json_data.get('web_search'):
|
||||
if provider in ("Bing", "HuggingChat"):
|
||||
if provider:
|
||||
kwargs['web_search'] = True
|
||||
else:
|
||||
from .internet import get_search_message
|
||||
@ -159,13 +140,11 @@ class Api:
|
||||
result = ChatCompletion.create(**kwargs)
|
||||
first = True
|
||||
if isinstance(result, ImageResponse):
|
||||
# Якщо результат є ImageResponse, обробляємо його як одиночний елемент
|
||||
if first:
|
||||
first = False
|
||||
yield self._format_json("provider", get_last_provider(True))
|
||||
yield self._format_json("content", str(result))
|
||||
else:
|
||||
# Якщо результат є ітерабельним, обробляємо його як раніше
|
||||
for chunk in result:
|
||||
if first:
|
||||
first = False
|
||||
@ -181,7 +160,6 @@ class Api:
|
||||
elif isinstance(chunk, ImagePreview):
|
||||
yield self._format_json("preview", chunk.to_string())
|
||||
elif isinstance(chunk, ImageResponse):
|
||||
# Обробка ImageResponse
|
||||
images = asyncio.run(self._copy_images(chunk.get_list(), chunk.options.get("cookies")))
|
||||
yield self._format_json("content", str(ImageResponse(images, chunk.alt)))
|
||||
elif not isinstance(chunk, FinishReason):
|
||||
@ -190,8 +168,8 @@ class Api:
|
||||
logging.exception(e)
|
||||
yield self._format_json('error', get_error_message(e))
|
||||
|
||||
# Додайте цей метод до класу Api
|
||||
async def _copy_images(self, images: list[str], cookies: Optional[Cookies] = None):
|
||||
ensure_images_dir()
|
||||
async with ClientSession(
|
||||
connector=get_connector(None, os.environ.get("G4F_PROXY")),
|
||||
cookies=cookies
|
||||
@ -212,16 +190,6 @@ class Api:
|
||||
return await asyncio.gather(*[copy_image(image) for image in images])
|
||||
|
||||
def _format_json(self, response_type: str, content):
|
||||
"""
|
||||
Formats and returns a JSON response.
|
||||
|
||||
Args:
|
||||
response_type (str): The type of the response.
|
||||
content: The content to be included in the response.
|
||||
|
||||
Returns:
|
||||
str: A JSON formatted string.
|
||||
"""
|
||||
return {
|
||||
'type': response_type,
|
||||
response_type: content
|
||||
@ -229,15 +197,6 @@ class Api:
|
||||
|
||||
|
||||
def get_error_message(exception: Exception) -> str:
|
||||
"""
|
||||
Generates a formatted error message from an exception.
|
||||
|
||||
Args:
|
||||
exception (Exception): The exception to format.
|
||||
|
||||
Returns:
|
||||
str: A formatted error message string.
|
||||
"""
|
||||
message = f"{type(exception).__name__}: {exception}"
|
||||
provider = get_last_provider()
|
||||
if provider is None:
|
||||
|
||||
@ -27,6 +27,10 @@ class Website:
|
||||
'function': redirect_home,
|
||||
'methods': ['GET', 'POST']
|
||||
},
|
||||
'/images/': {
|
||||
'function': redirect_home,
|
||||
'methods': ['GET', 'POST']
|
||||
},
|
||||
}
|
||||
|
||||
def _chat(self, conversation_id):
|
||||
@ -35,4 +39,4 @@ class Website:
|
||||
return render_template('index.html', chat_id=conversation_id)
|
||||
|
||||
def _index(self):
|
||||
return render_template('index.html', chat_id=str(uuid.uuid4()))
|
||||
return render_template('index.html', chat_id=str(uuid.uuid4()))
|
||||
|
||||
@ -23,7 +23,6 @@ from .Provider import (
|
||||
DDG,
|
||||
DeepInfra,
|
||||
DeepInfraChat,
|
||||
DeepInfraImage,
|
||||
Editee,
|
||||
Free2GPT,
|
||||
FreeChatgpt,
|
||||
@ -31,6 +30,7 @@ from .Provider import (
|
||||
FreeNetfly,
|
||||
Gemini,
|
||||
GeminiPro,
|
||||
GizAI,
|
||||
GigaChat,
|
||||
GPROChat,
|
||||
HuggingChat,
|
||||
@ -42,9 +42,6 @@ from .Provider import (
|
||||
NexraBing,
|
||||
NexraBlackbox,
|
||||
NexraChatGPT,
|
||||
NexraChatGPT4o,
|
||||
NexraChatGptV2,
|
||||
NexraChatGptWeb,
|
||||
NexraDallE,
|
||||
NexraDallE2,
|
||||
NexraEmi,
|
||||
@ -87,6 +84,8 @@ class Model:
|
||||
"""Returns a list of all model names."""
|
||||
return _all_models
|
||||
|
||||
|
||||
### Default ###
|
||||
default = Model(
|
||||
name = "",
|
||||
base_provider = "",
|
||||
@ -113,6 +112,8 @@ default = Model(
|
||||
])
|
||||
)
|
||||
|
||||
|
||||
|
||||
############
|
||||
### Text ###
|
||||
############
|
||||
@ -136,13 +137,13 @@ gpt_35_turbo = Model(
|
||||
gpt_4o = Model(
|
||||
name = 'gpt-4o',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([NexraChatGPT4o, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, Liaobots, Airforce, OpenaiChat])
|
||||
best_provider = IterListProvider([NexraChatGPT, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, GizAI, Airforce, Liaobots, OpenaiChat])
|
||||
)
|
||||
|
||||
gpt_4o_mini = Model(
|
||||
name = 'gpt-4o-mini',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, ChatgptFree, Koala, OpenaiChat, ChatGpt])
|
||||
best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, GizAI, ChatgptFree, Koala, OpenaiChat, ChatGpt])
|
||||
)
|
||||
|
||||
gpt_4_turbo = Model(
|
||||
@ -154,7 +155,7 @@ gpt_4_turbo = Model(
|
||||
gpt_4 = Model(
|
||||
name = 'gpt-4',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider])
|
||||
best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider])
|
||||
)
|
||||
|
||||
# o1
|
||||
@ -167,7 +168,7 @@ o1 = Model(
|
||||
o1_mini = Model(
|
||||
name = 'o1-mini',
|
||||
base_provider = 'OpenAI',
|
||||
best_provider = AmigoChat
|
||||
best_provider = IterListProvider([AmigoChat, GizAI])
|
||||
)
|
||||
|
||||
|
||||
@ -216,13 +217,13 @@ llama_3_70b = Model(
|
||||
llama_3_1_8b = Model(
|
||||
name = "llama-3.1-8b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, PerplexityLabs])
|
||||
best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, GizAI, PerplexityLabs])
|
||||
)
|
||||
|
||||
llama_3_1_70b = Model(
|
||||
name = "llama-3.1-70b",
|
||||
base_provider = "Meta Llama",
|
||||
best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, HuggingFace, PerplexityLabs])
|
||||
best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, GizAI, HuggingFace, PerplexityLabs])
|
||||
)
|
||||
|
||||
llama_3_1_405b = Model(
|
||||
@ -299,7 +300,7 @@ mistral_nemo = Model(
|
||||
mistral_large = Model(
|
||||
name = "mistral-large",
|
||||
base_provider = "Mistral",
|
||||
best_provider = Editee
|
||||
best_provider = IterListProvider([Editee, GizAI])
|
||||
)
|
||||
|
||||
|
||||
@ -347,13 +348,13 @@ phi_3_5_mini = Model(
|
||||
gemini_pro = Model(
|
||||
name = 'gemini-pro',
|
||||
base_provider = 'Google DeepMind',
|
||||
best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, Liaobots, Airforce])
|
||||
best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, GizAI, Airforce, Liaobots])
|
||||
)
|
||||
|
||||
gemini_flash = Model(
|
||||
name = 'gemini-flash',
|
||||
base_provider = 'Google DeepMind',
|
||||
best_provider = IterListProvider([Blackbox, Liaobots, Airforce])
|
||||
best_provider = IterListProvider([Blackbox, GizAI, Airforce, Liaobots])
|
||||
)
|
||||
|
||||
gemini = Model(
|
||||
@ -424,14 +425,14 @@ claude_3_sonnet = Model(
|
||||
claude_3_haiku = Model(
|
||||
name = 'claude-3-haiku',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([DDG, Airforce, Liaobots])
|
||||
best_provider = IterListProvider([DDG, Airforce, GizAI, Liaobots])
|
||||
)
|
||||
|
||||
# claude 3.5
|
||||
claude_3_5_sonnet = Model(
|
||||
name = 'claude-3.5-sonnet',
|
||||
base_provider = 'Anthropic',
|
||||
best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, Liaobots])
|
||||
best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, GizAI, Liaobots])
|
||||
)
|
||||
|
||||
|
||||
@ -753,14 +754,14 @@ sdxl_lora = Model(
|
||||
sdxl = Model(
|
||||
name = 'sdxl',
|
||||
base_provider = 'Stability AI',
|
||||
best_provider = IterListProvider([ReplicateHome, DeepInfraImage])
|
||||
best_provider = IterListProvider([ReplicateHome])
|
||||
|
||||
)
|
||||
|
||||
sd_1_5 = Model(
|
||||
name = 'sd-1.5',
|
||||
base_provider = 'Stability AI',
|
||||
best_provider = NexraSD15
|
||||
best_provider = IterListProvider([NexraSD15, GizAI])
|
||||
|
||||
)
|
||||
|
||||
@ -771,6 +772,13 @@ sd_3 = Model(
|
||||
|
||||
)
|
||||
|
||||
sd_3_5 = Model(
|
||||
name = 'sd-3.5',
|
||||
base_provider = 'Stability AI',
|
||||
best_provider = GizAI
|
||||
|
||||
)
|
||||
|
||||
### Playground ###
|
||||
playground_v2_5 = Model(
|
||||
name = 'playground-v2.5',
|
||||
@ -791,7 +799,7 @@ flux = Model(
|
||||
flux_pro = Model(
|
||||
name = 'flux-pro',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = IterListProvider([AmigoChat, NexraFluxPro])
|
||||
best_provider = IterListProvider([NexraFluxPro, AmigoChat])
|
||||
|
||||
)
|
||||
|
||||
@ -840,7 +848,7 @@ flux_4o = Model(
|
||||
flux_schnell = Model(
|
||||
name = 'flux-schnell',
|
||||
base_provider = 'Flux AI',
|
||||
best_provider = ReplicateHome
|
||||
best_provider = IterListProvider([ReplicateHome, GizAI])
|
||||
|
||||
)
|
||||
|
||||
@ -1123,6 +1131,7 @@ class ModelUtils:
|
||||
'sdxl-turbo': sdxl_turbo,
|
||||
'sd-1.5': sd_1_5,
|
||||
'sd-3': sd_3,
|
||||
'sd-3.5': sd_3_5,
|
||||
|
||||
|
||||
### Playground ###
|
||||
|
||||
Loading…
Reference in New Issue
Block a user