Question Answering

POST

api

collection

generative-qa

curl --request POST \
  --url https://app.twilix.io/api/v1/collection/generative-qa \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
  "collection": "<string>",
  "prompt": "<string>",
  "promptFields": [
    {}
  ],
  "fields": [
    {}
  ],
  "conversationID": "<string>",
  "minimumScore": 123,
  "includeModeration": true,
  "limit": 123,
  "stream": true
}'

Generative QA returns relevant answers to the user input question.

Under the hood, we perform vector search and reranking on the input collection to retrieve the most relevant results, then use the results to generate an answer.

collection

string

required

The collection to query.

prompt

string

required

The question from the user

promptFields

array

The fields that you want the generation to be based on.

fields

array

The fields that you want to be returned as reference. If not specified, it returns all fields as reference.

conversationID

string

The conversation ID. This is returned in the response so you can use the one that has been automatically generated for you or you can also supply your own to keep track of the conversation on your side.

minimumScore

float

The minimum score.

includeModeration

boolean

If true then there will be a moderation layer applied after the user inputs a query and when the AI outputs to ensure that the generated content is not harmful or violent.

limit

integer

The max number of documents to returned

stream

boolean

Whether or not a stream response should be returned. See examples below for details.

Content-Type

default: "application/json"required

Requires JSON Content Type

Since it could take up to a few seconds for the answer to complete. Streaming is encouraged for the best user experience.

You can pass in stream=true in the request to enable streaming response, and easily setup stream handling with Microsoft’s fetch-event-source package.

Example.ts

const requestBody = {
  collection: "insurancePdfs",
  prompt: "Can I claim wear and tear?",
  promptFields: ["content", "url", "pageNumber"],
  stream: true, // <------- IMPORTANT
}; // Define your request body

const options = {
  method: "POST",
  headers: {
    Authorization: `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify(requestBody),
  signal: abortSignal, // This is optional
};

await fetchEventSource(
  `https://app.twilix.io/api/v1/collection/generative-qa`,
  {
    ...options,
    onopen(response) {
      // ...
    },
    onmessage: (event) => {
      const decodedJson = JSON.parse(event.data);
      const decodedMessage: GenerativeQnAResponse = {
        message: decodedJson.message,
        conversationID: decodedJson.conversationID,
        references: decodedJson.references ?? [],
        confidenceScore: decodedJson.confidenceScore,
      };
      onNewData(decodedMessage);
    },
    openWhenHidden: true,
    onerror: (error) => {
      // ...
    },
  }
);

The event stream looks like this:

data: {"message": ""}
data: {"message": "Hello"}
data: {"message": "!"}
data: {"message": " How"}
data: {"message": " can"}
data: {"message": " I"}
data: {"message": " assist"}
data: {"message": " you"}
data: {"message": " today"}
data: {"message": "?"}
data: {"message": "", "conversationID": "f4eb4cdf-bf94-438f-9143-8d96d6d4d0d8", "references": [{"reference": "Dummy PDF file\n", "content": "Dummy PDF file\n", "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "pageNumber": 1}], "confidenceScore": null}

If latency is not a concern, you can alternatively use the normal calling method and wait for the entire response.

Note it could take up to a few seconds for the answer to complete.

Example.ts

const requestBody = {
  collection: "insurancePdfs",
  prompt: "hi",
  stream: true, // <------- IMPORTANT
}; // Define your request body

return axios
    .post(`https://app.twilix.io/api/v1/collection/generative-qa`, requestBody, {
        headers: {
            Authorization: `Bearer ${apiKey}`,
            "Content-Type": "application/json",
        },
    })
    .then((res) => {
        // Handle Response here
        return res.data;
    })
    .catch((err) => {
        // Handle Error
    });

The response looks like this:

{
  "message": "Hello! How can I assist you today?",
  "conversationID": "01f02c68-584a-42d0-bc1c-71016b127f93",
  "references": [],
  "confidenceScore": 1
}

Inserting a CSV CoPilot

curl --request POST \
  --url https://app.twilix.io/api/v1/collection/generative-qa \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
  "collection": "<string>",
  "prompt": "<string>",
  "promptFields": [
    {}
  ],
  "fields": [
    {}
  ],
  "conversationID": "<string>",
  "minimumScore": 123,
  "includeModeration": true,
  "limit": 123,
  "stream": true
}'

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