RAG on Specified Chunks

curl --request POST \
  --url https://api.trieve.ai/api/chunk/generate \
  --header 'Authorization: <api-key>' \
  --header 'Content-Type: application/json' \
  --header 'TR-Dataset: <tr-dataset>' \
  --data '
{
  "chunk_ids": [
    "d290f1ee-6c54-4b01-90e6-d701748f0851"
  ],
  "prev_messages": [
    {
      "content": "How do I setup RAG with Trieve?",
      "role": "user"
    }
  ],
  "prompt": "Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:",
  "stream_response": true
}
'

import requests

url = "https://api.trieve.ai/api/chunk/generate"

payload = {
    "chunk_ids": ["d290f1ee-6c54-4b01-90e6-d701748f0851"],
    "prev_messages": [
        {
            "content": "How do I setup RAG with Trieve?",
            "role": "user"
        }
    ],
    "prompt": "Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:",
    "stream_response": True
}
headers = {
    "TR-Dataset": "<tr-dataset>",
    "Authorization": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {
    'TR-Dataset': '<tr-dataset>',
    Authorization: '<api-key>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    chunk_ids: ['d290f1ee-6c54-4b01-90e6-d701748f0851'],
    prev_messages: [{content: 'How do I setup RAG with Trieve?', role: 'user'}],
    prompt: 'Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:',
    stream_response: true
  })
};

fetch('https://api.trieve.ai/api/chunk/generate', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.trieve.ai/api/chunk/generate",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'chunk_ids' => [
        'd290f1ee-6c54-4b01-90e6-d701748f0851'
    ],
    'prev_messages' => [
        [
                'content' => 'How do I setup RAG with Trieve?',
                'role' => 'user'
        ]
    ],
    'prompt' => 'Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:',
    'stream_response' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <api-key>",
    "Content-Type: application/json",
    "TR-Dataset: <tr-dataset>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.trieve.ai/api/chunk/generate"

	payload := strings.NewReader("{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("TR-Dataset", "<tr-dataset>")
	req.Header.Add("Authorization", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.trieve.ai/api/chunk/generate")
  .header("TR-Dataset", "<tr-dataset>")
  .header("Authorization", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.trieve.ai/api/chunk/generate")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["TR-Dataset"] = '<tr-dataset>'
request["Authorization"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}"

response = http.request(request)
puts response.read_body

<string>

{
  "message": "Bad Request"
}

POST

api

chunk

generate

RAG on Specified Chunks

curl --request POST \
  --url https://api.trieve.ai/api/chunk/generate \
  --header 'Authorization: <api-key>' \
  --header 'Content-Type: application/json' \
  --header 'TR-Dataset: <tr-dataset>' \
  --data '
{
  "chunk_ids": [
    "d290f1ee-6c54-4b01-90e6-d701748f0851"
  ],
  "prev_messages": [
    {
      "content": "How do I setup RAG with Trieve?",
      "role": "user"
    }
  ],
  "prompt": "Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:",
  "stream_response": true
}
'

import requests

url = "https://api.trieve.ai/api/chunk/generate"

payload = {
    "chunk_ids": ["d290f1ee-6c54-4b01-90e6-d701748f0851"],
    "prev_messages": [
        {
            "content": "How do I setup RAG with Trieve?",
            "role": "user"
        }
    ],
    "prompt": "Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:",
    "stream_response": True
}
headers = {
    "TR-Dataset": "<tr-dataset>",
    "Authorization": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {
    'TR-Dataset': '<tr-dataset>',
    Authorization: '<api-key>',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    chunk_ids: ['d290f1ee-6c54-4b01-90e6-d701748f0851'],
    prev_messages: [{content: 'How do I setup RAG with Trieve?', role: 'user'}],
    prompt: 'Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:',
    stream_response: true
  })
};

fetch('https://api.trieve.ai/api/chunk/generate', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.trieve.ai/api/chunk/generate",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'chunk_ids' => [
        'd290f1ee-6c54-4b01-90e6-d701748f0851'
    ],
    'prev_messages' => [
        [
                'content' => 'How do I setup RAG with Trieve?',
                'role' => 'user'
        ]
    ],
    'prompt' => 'Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:',
    'stream_response' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <api-key>",
    "Content-Type: application/json",
    "TR-Dataset: <tr-dataset>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.trieve.ai/api/chunk/generate"

	payload := strings.NewReader("{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("TR-Dataset", "<tr-dataset>")
	req.Header.Add("Authorization", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.trieve.ai/api/chunk/generate")
  .header("TR-Dataset", "<tr-dataset>")
  .header("Authorization", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.trieve.ai/api/chunk/generate")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["TR-Dataset"] = '<tr-dataset>'
request["Authorization"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"chunk_ids\": [\n    \"d290f1ee-6c54-4b01-90e6-d701748f0851\"\n  ],\n  \"prev_messages\": [\n    {\n      \"content\": \"How do I setup RAG with Trieve?\",\n      \"role\": \"user\"\n    }\n  ],\n  \"prompt\": \"Respond to the instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:\",\n  \"stream_response\": true\n}"

response = http.request(request)
puts response.read_body

<string>

{
  "message": "Bad Request"
}

Authorizations

Authorization

string

header

required

Headers

TR-Dataset

string<uuid>

required

The dataset id or tracking_id to use for the request. We assume you intend to use an id if the value is a valid uuid.

Body

application/json

JSON request payload to perform RAG on some chunks (chunks)

chunk_ids

string<uuid>[]

required

The ids of the chunks to be retrieved and injected into the context window for RAG.

prev_messages

object[]

required

The previous messages to be placed into the chat history. There must be at least one previous message.

Show child attributes

audio_input

string | null

Audio input to be used in the chat. This will be used to generate the audio tokens for the model. The default is None.

context_options

object | null

Context options to use for the completion. If not specified, all options will default to false.

Show child attributes

frequency_penalty

number<float> | null

Frequency penalty is a number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. Default is 0.7.

highlight_results

boolean | null

Set highlight_results to false for a slight latency improvement (1-10ms). If not specified, this defaults to true. This will add <mark><b> tags to the chunk_html of the chunks to highlight matching splits.

image_config

object | null

Configuration for sending images to the llm

Show child attributes

Example:

{ "images_per_chunk": 1, "use_images": true }

image_urls

string[] | null

Image URLs to be used in the chat. These will be used to generate the image tokens for the model. The default is None.

max_tokens

integer<int32> | null

The maximum number of tokens to generate in the chat completion. Default is None.

Required range: x >= 0

metadata

any | null

Metadata is any metadata you want to associate w/ the event that is created from this request

model

string | null

Model to use for the completion. If not specified, the default model configured for the dataset will be used.

presence_penalty

number<float> | null

Presence penalty is a number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. Default is 0.7.

prompt

string | null

Prompt will be used to tell the model what to generate in the next message in the chat. The default is 'Respond to the previous instruction and include the doc numbers that you used in square brackets at the end of the sentences that you used the docs for:'. You can also specify an empty string to leave the final message alone such that your user's final message can be used as the prompt. See docs.trieve.ai or contact us for more information.

stop_tokens

string[] | null

Stop tokens are up to 4 sequences where the API will stop generating further tokens. Default is None.

stream_response

boolean | null

Whether or not to stream the response. If this is set to true or not included, the response will be a stream. If this is set to false, the response will be a normal JSON response. Default is true.

temperature

number<float> | null

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Default is 0.5.

user_id

string | null

User ID is the id of the user who is making the request. This is used to track user interactions with the RAG results.

Response

This will be a JSON response of a string containing the LLM's generated inference. Response if not streaming.

The response is of type string.

Chunk

Chunk Group

Topic

Message

Crawl

File

Analytics

Experiments

Dataset

Organization

User

Auth

Health

Invitation

Stripe

Metrics

Public

RAG on Specified Chunks

Authorizations

Headers

Body

Response