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In June, OpenAI announced that third-party applications’ APIs can be passed into the GPT model, opening up a wide range of possibilities for creating specialized agents. Our team decided to write our own chat for working with GPT4 from OpenAI and other ML/LLM models with the ability to customize for the company’s internal needs. The project is open source, and can be downloaded via the link. It is currently in active development, so we would be glad to see your comments / wishes in the comments. Also, send us your pull requests with corrections.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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The OpenAI API returns responses in Markdown format. To display responses from the chat, which contain formatting, I used the ReactMarkdown component. For code inserts, I used React Syntax Highlighter.
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react-syntax-highlighter
syntax highlighting component for react with prismjs or highlightjs ast using inline styles
The OpenAI API returns responses in Markdown format. To display responses from the chat, which contain formatting, I used the ReactMarkdown component. For code inserts, I used React Syntax Highlighter.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.
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For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.