Post
333
Hi everyone, I have updated the space from its original version.
mallocode200/Deep_Research_Assistant
The main changes are:
- The possibility for users to insert their own OpenAI API Key
- The possibility for users to select the model they want from OpenAI
- An improved UI to see the process going on when the research is running
- A better Gradio interface for both light and dark themes
Why use only OpenAI models?
For this research assistant, I've chosen to focus exclusively on OpenAI models for several key reasons:
- Reliability & Consistency: OpenAI's models provide consistent, high-quality responses that are crucial for research tasks requiring accuracy and depth.
- Advanced Reasoning: Models like GPT-4o and o1-preview excel at complex analytical thinking, making them ideal for comprehensive research synthesis and evaluation.
- Proven Performance: The research pipeline has been extensively tested and optimised specifically for OpenAI's model behaviours and capabilities.
- API Stability: OpenAI offers robust API infrastructure with reliable uptime and consistent response formats, essential for a production research tool.
- Quality Assurance: The built-in evaluation and optimisation system is fine-tuned to work with OpenAI's specific output patterns and capabilities.
That said, I'm open to expanding model support in the future! The architecture is designed to be flexible, and I'm considering adding support for other leading models, such as Claude and Gemini, as well as open-source alternatives, as the ecosystem evolves. The goal is to provide users with the best possible research experience, regardless of their preferred AI provider.
The main changes are:
- The possibility for users to insert their own OpenAI API Key
- The possibility for users to select the model they want from OpenAI
- An improved UI to see the process going on when the research is running
- A better Gradio interface for both light and dark themes
Why use only OpenAI models?
For this research assistant, I've chosen to focus exclusively on OpenAI models for several key reasons:
- Reliability & Consistency: OpenAI's models provide consistent, high-quality responses that are crucial for research tasks requiring accuracy and depth.
- Advanced Reasoning: Models like GPT-4o and o1-preview excel at complex analytical thinking, making them ideal for comprehensive research synthesis and evaluation.
- Proven Performance: The research pipeline has been extensively tested and optimised specifically for OpenAI's model behaviours and capabilities.
- API Stability: OpenAI offers robust API infrastructure with reliable uptime and consistent response formats, essential for a production research tool.
- Quality Assurance: The built-in evaluation and optimisation system is fine-tuned to work with OpenAI's specific output patterns and capabilities.
That said, I'm open to expanding model support in the future! The architecture is designed to be flexible, and I'm considering adding support for other leading models, such as Claude and Gemini, as well as open-source alternatives, as the ecosystem evolves. The goal is to provide users with the best possible research experience, regardless of their preferred AI provider.