Quick Start - Retrieval
Updated as of 2023-Jun-24
In this example, we will upload documents to a vector database so our AI chatbot can use the information. We will be uploading information from the NCBI StatPearls article on Acute Bronchitis.
1. Add your OpenAI API key
Go to the Dashboard and submit your OpenAI API Key.
2. Get an API Key
Go to the Dashboard and create an API Key.
3. Create a chat
If you have already created a chat in Quick Start - Memory, skip this step.
Chats are used to organize conversational memory.
4. Create a collection
Information uploaded to the vector database are organized into collections.
5. Upload an article by URL
DopplerAI provides 2 API endpoints for uploading information to the vector database.
/uploads/textlets you upload a string./uploads/urllets you upload the contents from an URL.DopplerAI will automatically detect whether the URL is an image, PDF or a regular webpage.
If it's an image, the text from the image will be extracted and uploaded to the vector database. Max file size is 1MB.
If it's a PDF, the text from the PDF will be extracted. Max file size is 1MB.
If it's a webpage, the webpage's HTML will be extracted.
This endpoint uses
text-embedding-ada-002for embeddings. If you want to a different model, or your own fine-tuned model, please just let us know on Discord or via an email to [email protected].
6. Upload an article by text
Upload a string to the vector database.
7. Send a message with retrieval enabled
Send a message, allowing the LLM to access information from the uploaded articles.
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