NuclearGeek's AI Playground is an interactive web application utilizing multiple AI models. With a user-friendly Gradio interface, it allows the user to communicate with various OpenAI, Ollama, Google Gemini, and Stability.ai models including tools to analyze images with Vision, create images with Dall-e-3 or stability, search the web and news articles with Bing, search journal articles using Annas or even look for a new job with Indeed. The application supports multiple GPT and diffusion models and is designed with a set of examples to provide a good starting point for various scenarios. Tabs include OpenAI, Ollama, Anthropic, Google Gemini, Stability.ai, Bing Search, and some various image editing tools.
- Clone the repository:
git clone https://github.com/NuclearGeekETH/chatGPT-web-ui.git
- Navigate to the project directory:
cd chatGPT-web-ui
- Set up your OpenAI API and Bing key:
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Rename
.env.exampleto.env:# For macOS and Linux: mv .env.example .env # For Windows: move .env.example .env -
Replace
your_openai_keywith your actual OpenAI, Bing, Google, and Stability.ai API keys.OPENAI_API_KEY=your_openai_key BING_SEARCH_V7_SUBSCRIPTION_KEY=your_bing_key GOOGLE_API_KEY=your_google_key STABILITY_API_KEY=your_stability_key ANTHROPIC_API_KEY=your_anthropic_key
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Set up Ollama according to your operating system and preference: Ollama.
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Ensure Ollama is running, models will download upon request but larger models take longer than gradio will wait before throwing an error.
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Start the chatbot application by double clicking on the
startup_chat.batfile. -
Access the Gradio interface through the URL displayed in the terminal.
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Choose a GPT model, enter a system message or select one from the provided examples, and start chatting with the chatbot.
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Open Terminal in your macOS.
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Navigate to the project directory if you're not already there.
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Before running this script on macOS, ensure you have the necessary permissions to execute it by running the following command in your terminal. This grants execution rights to the script:
chmod +x startup_chat.sh
- Run the following command to start the chatbot application (assumes you have the necessary runtime environment like Python and required libraries installed):
bash startup_chat.sh
if startup_chat.sh does not work then setup environment manually using python3 -m venv venv, then use source venv/bin/activate and pip install -r requirements.txt, and finally python3 chat_interface.py.
- Access the Gradio interface through the URL displayed in the Terminal.
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Choose a GPT model, enter a system message or select one from the provided examples, and start chatting with the chatbot.
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For web and news search using bing, just use simple search terms like you would in a search engine.
Text generation models (often called generative pre-trained transformers or large language models) have been trained to understand natural language, code, and images. The models provide text outputs in response to their inputs. The inputs to these models are also referred to as "prompts". Designing a prompt is essentially how you “program” a large language model model, usually by providing instructions or some examples of how to successfully complete a task.
Using text generation models, you can build applications to:
- Draft documents
- Write computer code
- Answer questions about a knowledge base
- Analyze texts
- Give software a natural language interface
- Tutor in a range of subjects
- Translate languages
- Simulate characters for games
GPT-4 with Vision, sometimes referred to as GPT-4V or gpt-4-vision-preview in the API, allows the model to take in images and answer questions about them. Historically, language model systems have been limited by taking in a single input modality, text. For many use cases, this constrained the areas where models like GPT-4 could be used.
GPT-4 with vision is currently available to all developers who have access to GPT-4 via the gpt-4-vision-preview model and the Chat Completions API which has been updated to support image inputs. Note that the Assistants API does not currently support image inputs.
Along with OpenAI, now Vision is offered in Ollama, Anthropic and Google Gemini tabs.
The image generations endpoint allows you to create an original image given a text prompt. When using DALL·E 3, images can have a size of 1024x1024, 1024x1792 or 1792x1024 pixels.
By default, images are generated at standard quality, but when using DALL·E 3 you can set quality: "hd" for enhanced detail. Square, standard quality images are the fastest to generate.
Image generation is also available in the Stability.ai tab. There is Text-to-Image, Image-to-Image, Image Upscaling, and Image-to-Video tools available.
In the OpenAI tab, the Audio API provides a speech endpoint based on our TTS (text-to-speech) model. It comes with 6 built-in voices and can be used to:
- Narrate a written blog post
- Produce spoken audio in multiple languages
- Give real time audio output using streaming
Gemini is a family of generative AI models that lets developers generate content and solve problems. These models are designed and trained to handle both text and images as input.
Offering Claude 3, the next generation of AI models.
The three state-of-the-art models—Claude 3 Opus, Claude 3 Sonnet, and Claude 3 Haiku—set new industry benchmarks across reasoning, math, coding, multilingual understanding, and vision.
Run Llama 2, Code Llama, and other models. Customize and create your own.
Stability.ai is the company that created Stable Diffusion and SDXL. Tools available through their API are packaged here: Text-to-Image, Image-to-Image and Upscale-Image.
An easy-to-use, ad-free, commercial-grade search tool that lets you deliver the results you want.
Search Anna's Archive. Anna's Archive mirrors Open Library, Library Genesis, Sci-Hub and Z-Library. Anna's Archive says that it does not host copyrighted materials and that it only indexes metadata that is already publicly available. As of February 1, 2024, Anna's Archive includes 25,530,302 books and 99,425,822 papers.
Keyword and Location based job search using the Indeed XML feed.