Chat Completions

Our Agent (chat completions) endpoint is fully compatible with the OpenAI chat completions API specification. This means that our API is a like-for-like swap for any application currently using the popular LLM chat completions API signature, and should be plug and play with any of the many OpenAI SDKs in the language of your choice.

Demo Chatbot App

Minimal Request Example #

Since your Agent is configured on the platform, API calls to get completions can be extremely minimal. All that’s required is the prompt for which you want a response:

curl \
--header 'x-api-key: apg_xxxxxxxxxxxxxxxxxxxxxxxxxxxx' \
--header 'Content-Type: text/plain' \
--data '{
    "prompt": "How can a good God allow so much evil in the world?"
}' \
--url https://my.gospel.bot/api/v1/chat/completions

Please note: you must replace the x-api-key value with your API key and my.gospel.bot with your Agent’s domain.

Full Request Example #

However, the API supports overriding the default Agent configuration options, as well as several other runtime options. Here’s an example of all supported parameters that have an effect on the output:

curl \
--header 'Authorization: Bearer apg_xxxxxxxxxxxxxxxxxxxxxxxxxxxx' \
--header 'Content-Type: application/json' \
--data '{
    "model": "openai/gpt/4o",
    "stream": false,
    "messages": [
        {
            "role": "system",
            "content": "This a system prompt override."
        },
        {
            "role": "user",
            "content": "This is a previous prompt."
        },
        {
            "role": "assistant",
            "content": "This is a previous completion."
        },
        {
            "role": "user",
            "content": "This is the current prompt."
        }
    ],
    "response_format": { 
        "type": "json" 
    },
    "metadata": {
        "anonymous": true,
        "conversation": null,
        "language": "en",
        "session": null,
        "device": null,
        "bible": "esv"
    },
    "frequency_penalty": 0.25,
    "presence_penalty": -0.25,
    "max_completion_tokens": 1024,
    "reasoning_effort": "high",
    "temperature": 0.5,
    "top_p": 0.9,
    "user": null
}' \
--url https://my.gospel.bot/api/v1/chat/completions

Please note: you must replace the Authorization bearer token value with your API key and my.gospel.bot with your Agent’s domain.

API Keys #

API keys are provisioned against a given Agent and cannot be used for another Agent.

Prompt and Messages #

You must either supply the prompt string or a messages array.

The messages parameter is an array of message objects, each with a role and a content property. By default, an Agent will have a system prompt that is automatically applied. Also by default, previous exchanges between an Agent and user as defined by the metadata.device, metadata.session, metadata.conversation, and user parameters are prepended to the array of messages which are eventually sent to the LLM. You may control how many past exchanges you wish Agent to use by passing an integer for the metadata.max_memories parameter. You only need supply a messages array if you wish to override this default behavior.

If you want to use the aforementioned defaults, or the response doesn’t require context from previous exchanges with Agent, you may simply provide a prompt string.

If you wish to prevent any context of previous exchanges altogether, regardless of the value of metadata.device, metadata.session, metadata.conversation, and user — you may pass metadata.anonymous as true.

• user: any string identifier for the user (100 characters max)
• metadata.conversation: any string identifier for the conversation within a single session (100 characters max)
• metadata.session: any string identifier for the user’s session (100 characters max)
• metadata.device: any string identifier for the user’s device (100 characters max)
• metadata.anonymous: if set to true, no past exchange context is provided to the Agent (one-shot); equivalent to setting metadata.max_memories: 0
• metadata.max_memories: the number of previous exchanges to provide to Agent

Streaming vs Non-Streaming #

The stream parameter controls whether the response should be streamed or delivered all at once. Typically, chat interfaces benefit from streaming output as the user gets more instantaneous feedback. However, there are use cases that lend themselves to non-streaming output as well.

Response Format #

The response format may be specified using the response_format.type parameter. Valid values are as follows:

• raw: raw OpenAI compatible chunked chat completion JSON. Only available if the stream option is true. Setting this format will allow any OpenAI compatible library / SDK to be used against this endpoint, as long as it has a way to set the response_format parameter. [default when streaming]
  
• text: plain text output; may include markdown
  
• html: HTML formatted, converted from markdown where applicable
  
• json: structured JSON response; includes completion as well as token usage and timing stats. Only available if the stream option is false. [default when not streaming]

Your Agent can be configured via Apologist Ignite to use any of the above response formats above by default for the chat completions endpoint. This is especially useful in situations where a 3rd party integration doesn’t allow sending custom parameters. Note that if text is specified, you may also toggle an option in your Agent configuration in Apologist Ignite to automatically strip all markdown to ensure only plain text is returned.

Bible Translation #

The metadata.bible parameter indicates to the Agent which Bible translation is preferred to use. The following is the list of supported Bible translations at this time:

Language #

Use the metadata.language parameter to control the output language. Language support varies by model and is specific to a given Agent. However, any Agent can be upgraded to utilize real-time translation, expanding its language support to 192 languages. Here is the full list of supported languages:

Model #

Agent supports dozens of models across many providers using a standardized naming scheme: creator/family/variant. Pass the model name via the model parameter.

Limited Models #

Low-latency, inexpensive models with very limited reasoning abilities.

Model	Model ID	Supported Languages	Credits
OpenAI GPT-5.4 nano	openai/gpt/5.4-nano	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	1
OpenAI GPT-5 mini	openai/gpt/5-mini	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	1
Anthropic Claude Haiku 3.5	anthropic/claude/haiku-3.5	ar, de, en, es, fr, hi, it, ja, ko, pt, ru, zh	2
Google Gemini 3 Flash	google/gemini/3-flash	ar, bg, bn, cs, da, de, el, en, es, et, fi, fr, he, hi, hr, hu, id, it, ja, ko, lt, lv, nl, no, pl, pt, ro, ru, sk, sl, sr, sv, sw, th, tr, uk, vi, zh, zh-TW	2
Meta Llama 4 Scout	meta/llama4/scout	ar, de, en, es, fr, hi, id, it, ja, nl, pt, ru, th, tr, zh	1
Mistral Medium 3	mistral/medium/3	de, en, es, fr, it, ja, ko, nl, po, pt, zh	1
OpenAI GPT-4o mini	openai/gpt/4o-mini	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	1
Alibaba Qwen 3 Next 80B Instruct	alibaba/qwen3/next-80b-instruct	af, ar, as, awa, az, ba, ban, be, bg, bho, bn, bs, ca, ceb, cs, cy, da, de, el, en, es, et, eu, fa, fi, fr, fr-CA, ga, gl, gu, he, hi, hr, ht, hu, hy, id, ilo, is, it, ja, jw, ka, kk, km, kn, ko, lb, li, lij, lmo, lo, lt, lv, mai, min, mk, ml, mr, ms, mt, my, ne, nl, no, oc, or, pa, pag, pap, pl, pt, pt-BR, ro, ru, scn, sd, si, sk, sl, sq, sr, su, sv, sw, szl, ta, te, tg, th, tl, tr, tt, uk, ur, uz, vi, yi, yue, zh, zh-TW	1
Google Gemma 4 31B	google/gemma/gemma-4-31b	ar, bg, bn, cs, da, de, el, en, es, et, fi, fr, he, hi, hr, hu, id, it, ja, ko, lt, lv, nl, no, pl, pt, ro, ru, sk, sl, sr, sv, sw, th, tr, uk, vi, zh, zh-TW	1
MiniMax M2.7 FP4	minimaxai/m/2.7	af, ar, bg, ca, cs, da, de, el, en, es, fa, fi, fr, fr-CA, he, hi, hr, hu, id, it, ja, ko, ms, nl, nno, no, pl, pt, pt-BR, ro, ru, sk, sl, sv, ta, th, tl, tr, uk, vi, yue, zh, zh-TW	1
Sarvam 30B	sarvam/sarvam/30b	as, bn, brx, doi, en, gu, hi, kn, kok, ks, mai, ml, mni, mr, ne, or, pa, sa, sat, sd, ta, te, ur	1

Standard Models #

Economic models that balance lower cost with better responses.

Model	Model ID	Supported Languages	Credits
xAI Grok 4 Fast	xai/grok/4-fast	ar, bn, cs, de, en, es, fa, fr, he, hi, id, it, ja, km, ko, lo, ms, my, nl, pl, pt, ru, th, tl, tr, ur, vi, zh	1
DeepSeek v3.1 Terminus	deepseek/deepseek/v3.1	af, am, ar, az, bg, bn, ca, cs, cy, da, de, el, en, eo, es, eu, fi, fr, fr-CA, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, ig, is, it, ja, ka, kk, km, kn, ko, lo, ml, mn, mr, ms, mt, my, ne, nl, no, pa, pl, ps, pt, pt-BR, ro, ru, si, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, uz, vi, yo, zh, zh-TW, zu	1
OpenAI GPT-5.4 mini	openai/gpt/5.4-mini	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	2
Anthropic Claude Haiku 4.5	anthropic/claude/haiku-4.5	ar, de, en, es, fr, hi, it, ja, ko, pt, ru, zh	3
OpenAI GPT OSS 120b	openai/gpt/oss-120b	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	1
Alibaba Qwen 3 235B	alibaba/qwen3/235b	af, ar, as, awa, az, ba, ban, be, bg, bho, bn, bs, ca, ceb, cs, cy, da, de, el, en, es, et, eu, fa, fi, fr, fr-CA, ga, gl, gu, he, hi, hr, ht, hu, hy, id, ilo, is, it, ja, jw, ka, kk, km, kn, ko, lb, li, lij, lmo, lo, lt, lv, mai, min, mk, ml, mr, ms, mt, my, ne, nl, no, oc, or, pa, pag, pap, pl, pt, pt-BR, ro, ru, scn, sd, si, sk, sl, sq, sr, su, sv, sw, szl, ta, te, tg, th, tl, tr, tt, uk, ur, uz, vi, yi, yue, zh, zh-TW	1
Alibaba Qwen3.5 397B A17b	alibaba/qwen3.5/397b-a17b	af, ar, as, awa, az, ba, ban, be, bg, bho, bn, bs, ca, ceb, cs, cy, da, de, el, en, es, et, eu, fa, fi, fr, fr-CA, ga, gl, gu, he, hi, hr, ht, hu, hy, id, ilo, is, it, ja, jw, ka, kk, km, kn, ko, lb, li, lij, lmo, lo, lt, lv, mai, min, mk, ml, mr, ms, mt, my, ne, nl, no, oc, or, pa, pag, pap, pl, pt, pt-BR, ro, ru, scn, sd, si, sk, sl, sq, sr, su, sv, sw, szl, ta, te, tg, th, tl, tr, tt, uk, ur, uz, vi, yi, yue, zh, zh-TW	2
Meta Llama 4 Maverick	meta/llama4/maverick	ar, de, en, es, fr, hi, id, it, ja, nl, pt, ru, th, tr, zh	2
Kimi K2.6 FP4	moonshotai/kimi/k2.6	af, am, ar, bg, bn, ceb, cs, da, de, el, en, es, et, fa, fi, fr, ga, gu, ha, he, hi, hr, hu, id, ig, is, it, ja, kk, km, kn, ko, lo, lt, lv, ml, mr, ms, mt, my, nb, ne, nl, pa, pa-Arab, pl, ps, pt, ro, ru, si, sk, so, sr, sv, sw, ta, te, th, tl, tr, uk, ur, uz, vi, xh, yo, zh, zh-TW, zu	3
GLM 5.1 FP4	zai/glm/5.1	en, es, fr, ja, ko, ru, zh	3
DeepSeek v3	deepseek/deepseek/v3	af, am, ar, az, bg, bn, ca, cs, cy, da, de, el, en, eo, es, eu, fi, fr, fr-CA, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, ig, is, it, ja, ka, kk, km, kn, ko, lo, ml, mn, mr, ms, mt, my, ne, nl, no, pa, pl, ps, pt, pt-BR, ro, ru, si, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, uz, vi, yo, zh, zh-TW, zu	2
DeepSeek V4 Pro	deepseek/deepseek/v4-pro	af, am, ar, az, bg, bn, ca, cs, cy, da, de, el, en, eo, es, eu, fi, fr, fr-CA, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, ig, is, it, ja, ka, kk, km, kn, ko, lo, ml, mn, mr, ms, mt, my, ne, nl, no, pa, pl, ps, pt, pt-BR, ro, ru, si, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, uz, vi, yo, zh, zh-TW, zu	3
Sarvam 105B	sarvam/sarvam/105b	as, bn, brx, doi, en, gu, hi, kn, kok, ks, mai, ml, mni, mr, ne, or, pa, sa, sat, sd, ta, te, ur	3

Premium Models #

Higher quality output at a premium price point.

Model	Model ID	Supported Languages	Credits
OpenAI GPT-5.1 Chat	openai/gpt/5.1	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	4
OpenAI GPT-5.4	openai/gpt/5.4	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	7
Anthropic Claude 4.6 Sonnet	anthropic/claude/sonnet-4.6	ar, bn, de, en, es, fr, hi, id, it, ja, ko, pt, ru, sw, yo, zh	7
xAI Grok 4	xai/grok/4	ar, bn, cs, de, en, es, fa, fr, he, hi, id, it, ja, km, ko, lo, ms, my, nl, pl, pt, ru, th, tl, tr, ur, vi, zh	7
Google Gemini 3 Pro	google/gemini/3-pro	ar, bg, bn, cs, da, de, el, en, es, et, fi, fr, he, hi, hr, hu, id, it, ja, ko, lt, lv, nl, no, pl, pt, ro, ru, sk, sl, sr, sv, sw, th, tr, uk, vi, zh, zh-TW	5
OpenAI GPT-5.2 Chat	openai/gpt/5.2	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	6
OpenAI GPT-5.3 Chat	openai/gpt/5.3	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	6
OpenAI GPT-5 Chat	openai/gpt/5-chat	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	4
OpenAI GPT-4.1	openai/gpt/4.1	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	4

Reasoning Models #

High-latency but extremely high quality output.

Model	Model ID	Supported Languages	Credits
DeepSeek R1	deepseek/deepseek/r1	af, am, ar, az, bg, bn, ca, cs, cy, da, de, el, en, eo, es, eu, fi, fr, fr-CA, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, ig, is, it, ja, ka, kk, km, kn, ko, lo, ml, mn, mr, ms, mt, my, ne, nl, no, pa, pl, ps, pt, pt-BR, ro, ru, si, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, uz, vi, yo, zh, zh-TW, zu	4
Anthropic Claude Opus 4.7	anthropic/claude/opus-4.7	ar, bn, de, en, es, fr, hi, id, it, ja, ko, pt, ru, sw, yo, zh	11
OpenAI GPT-5.5	openai/gpt/5.5	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, he, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	13
Anthropic Claude Opus 4.6	anthropic/claude/opus-4.6	ar, bn, de, en, es, fr, hi, id, it, ja, ko, pt, ru, sw, yo, zh	11
OpenAI o4 mini	openai/gpt/o4-mini	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	3
OpenAI o3	openai/gpt/o3	am, ar, bg, bn, bs, ca, cs, da, de, el, en, es, et, fa, fi, fr, fr-CA, gu, hi, hr, hu, hy, id, is, it, ja, ka, kk, kn, ko, lt, lv, mk, ml, mn, mr, ms, my, nl, no, pa, pl, pt, pt-BR, ro, ru, sk, sl, so, sq, sr, sv, sw, ta, te, tg, th, tl, tr, uk, ur, vi, zh, zh-TW	4

Standard LLM Parameters #

The chat completion endpoint supports standard LLM parameters that modify the behavior of the model:

• frequency_penalty
• presence_penalty
• max_completion_tokens
• reasoning_effort (for reasoning models only)
• temperature
• top_p

See OpenAI’s docs for more information about these parameters.

Ineffectual Passthrough Parameters #

There are some parameters that do not directly affect Agent’s response, but we pass them along to the target LLM for your convenience in order to be fully compatible with OpenAI’s chat completions endpoint:

• audio
• logit_bias
• logprobs
• modalities
• n
• parallel_tool_calls
• prediction
• seed
• service_tier
• stop
• store
• stream_options
• tools
• tool_choice

Agent does not currently support multi-modal input or output. Agent supports returning only a single response at a time. Agent does not currently support the use of external tools.

Starter Chatbot App in NextJS #

Check out our bare bones chatbot starter kit which demonstrates how to quickly get up and running with this endpoint using Vercel’s AI SDK. Here is where the magic happens in the endpoint that streams responses from our Agent (chat completions) API:

import { createOpenAICompatible } from "@ai-sdk/openai-compatible";
import { streamText } from "ai";

export async function POST(req: Request) {

  const { messages } = await req.json();

  const apologist = createOpenAICompatible({
    name: 'apologist',
    apiKey: process.env.APOLOGIST_API_KEY,
    baseURL: `${process.env.APOLOGIST_API_URL}`,
  });

  const result = streamText({
    model: apologist('openai/gpt/4o'),
    messages: messages,
  });

  return result.toDataStreamResponse();

}

Yes, it’s really that simple.

Caching #

The completion endpoint supports caching. Under the hood, each version of an Agent’s configuration is stored. In order to have a cached value match, the Agent configuration version, messages (including the current prompt), language, and Bible translation must all match. The cache is very unlikely to be utilized in a chat context, except for pre-defined preliminary prompts. A more common use case would be caching responses for pre-defined text (e.g., a Bible verse).

Learn more about how caching works in our system.

Feedback #

There are 3 additional feedback fields that can set on a given chat completion once it’s been created. These can be used to identify positive, negative, and qualitative feedback on the prompt itself for later viewing / retrieval.

Likes #

Use the POST /api/v1/chat/completions/[prompt_id]/like with a payload as follows to set the liked field:

{
    "liked": [true|false]
}

Flags #

Use the POST /api/v1/chat/completions/[prompt_id]/flag with a payload as follows to set the flagged field:

{
    "flagged": [true|false]
}

Feedback #

Use the POST /api/v1/chat/completions/[prompt_id]/feedback with a payload as follows to set the feedback field:

{
    "feedback": [string|null]
}

List Chat Completions #

Use the GET /api/v1/chat/completions endpoint to get a paginated list of chat completion records belonging to the authenticated team, ordered by prompted_at descending.

Pagination #

Parameter	Type	Default	Max	Description
page	integer	1	—	Page number
per_page	integer	50	100	Records per page

Filter Parameters #

All filters are optional and combinable. Omitting a filter returns all records.

Parameter	Type	Description
language	string	Language code (e.g. en)
min_timestamp	string	Minimum prompted_at (ISO 8601 timestamp)
max_timestamp	string	Maximum prompted_at (ISO 8601 timestamp)
config_id	integer	Agent configuration ID
flagged	boolean	true or false
liked	boolean	true or false
favorited	boolean	true or false
cached	boolean	true or false
conversation_id	string	Conversation identifier
session_id	string	Session identifier
device_id	string	Device identifier
user_id	string	User identifier
bible_id	integer	Bible ID
client	string	Client type (e.g. standalone, embedded, api, integration)
agent_id	integer	Specific agent within the team
agent_integration_id	integer	Agent integration ID

Boolean filter parameters accept true/false as strings or native booleans.

Response #

{
    "data": [ /* array of prompt objects */ ],
    "total": 142,
    "page": 1,
    "per_page": 50
}

total reflects the full count matching the applied filters (not just the current page), and can be used to calculate page counts.

---

Get Chat Completion #

Use the GET /api/v1/chat/completions/{prompt_id} endpoint to get a single chat completion record by ID. The endpoint accepts both UUID and legacy numeric integer IDs:

• UUID (current format)
• Numeric integer (legacy)

If the record does not exist or does not belong to the authenticated Agent, a 404 is returned.

Response #

{
    "data": { /* prompt object */ }
}

Prompt Object #

All fields from the prompts table are returned. The id field contains the record’s UUID — the raw uuid column is not included separately.

Field	Type	Description
id	string (UUID)	Unique identifier
language	string	Language code
prompt	string	The user’s prompt text
response	string | null	The generated response text
prompted_at	string	UTC timestamp when the prompt was submitted
response_started_at	string | null	UTC timestamp when streaming began
response_completed_at	string | null	UTC timestamp when the response finished
flagged	boolean	Whether the completion has been flagged
liked	boolean	Whether the completion has been liked
favorited	boolean	Whether the completion has been favorited
cached	boolean	Whether the response was served from cache
feedback	string | null	Free-text feedback submitted by the user
score	integer | null	Numeric score
config_id	integer | null	Agent configuration used
agent_id	integer | null	Agent that handled the completion
agent_token_id	integer | null	API token used to submit the request
agent_integration_id	integer | null	Integration that submitted the request
bible_id	integer | null	Bible context used
client	string | null	Client type (standalone, embedded, api, integration)
conversation_id	string | null	Conversation grouping identifier
session_id	string | null	Session identifier
device_id	string | null	Device identifier
user_id	string | null	User identifier
prompt_tokens	integer | null	Token count for the prompt
response_tokens	integer | null	Token count for the response
chat_tokens	integer | null	Token count for the conversation history
reasoning_tokens	integer | null	Token count for reasoning (where applicable)
translated_prompt	string | null	Real-time translated prompt text
translated_response	string | null	Real-time translated response text
reasoning	string | null	Model reasoning output
has_persisted_sources	boolean	Whether source documents were stored
response_metadata	object | null	Additional metadata from the model response
notes	string | null	Internal notes
archived_at	string | null	UTC timestamp when the record was archived

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Error Responses #

Status	Meaning
403	Missing or invalid API key
404	Record not found or not accessible by this team
500	Internal server error
503	Agent not found or inactive for the request’s host