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@markprompt/core
Advanced tools
`@markprompt/core` is the core library for Markprompt, a conversational AI component for your website, trained on your data.
@markprompt/core
@markprompt/core
is the core library for Markprompt, a conversational AI
component for your website, trained on your data.
It contains core functionality for Markprompt and allows you to build abstractions on top of it.
npm install @markprompt/core
In browsers with esm.sh:
<script type="module">
import {
submitChat,
submitSearchQuery,
submitFeedback,
} from 'https://esm.sh/@markprompt/core';
</script>
import { submitChat } from '@markprompt/core';
for await (const chunk of submitChat(
[{ content: 'What is Markprompt?', role: 'user' }],
'YOUR-PROJECT-KEY',
{
model: 'gpt-4-turbo-preview',
systemPrompt: 'You are a helpful AI assistant'
}
)) {
console.debug(chunk);
}
submitChat(messages: ChatMessage[], projectKey: string, options?)
Submit a prompt to the Markprompt Completions API.
messages
(ChatMessage[]
): Chat messages to submit to the modelprojectKey
(string
): Project key for the projectoptions
(SubmitChatOptions
): Optional parametersAll options are optional.
apiUrl
(string
): URL at which to fetch completionsconversationId
(string
): Conversation IDiDontKnowMessage
(string
): Message returned when the model does not have
an answermodel
(OpenAIModelId
): The OpenAI model to usesystemPrompt
(string
): The prompt templatetemperature
(number
): The model temperaturetopP
(number
): The model top PfrequencyPenalty
(number
): The model frequency penaltypresencePenalty
(number
): The model present penaltymaxTokens
(number
): The max number of tokens to include in the responsesectionsMatchCount
(number
): The number of sections to include in the
prompt contextsectionsMatchThreshold
(number
): The similarity threshold between thesignal
(AbortSignal
): AbortController signaltools
: (OpenAI.ChatCompletionTool[]
): A list of tools the model may calltool_choice
: (OpenAI.ChatCompletionToolChoiceOption
): Controls which (if
any) function is called by the modelA promise that resolves when the response is fully handled.
submitSearchQuery(query, projectKey, options?)
Submit a search query to the Markprompt Search API.
query
(string
): Search queryprojectKey
(string
): Project key for the projectoptions
(object
): Optional parametersapiUrl
(string
): URL at which to fetch search resultslimit
(number
): Maximum amount of results to returnsignal
(AbortSignal
): AbortController signalA list of search results.
submitFeedback(feedback, projectKey, options?)
Submit feedback to the Markprompt Feedback API about a specific prompt.
feedback
(object
): Feedback to submitfeedback.feedback
(object
): Feedback datafeedback.feedback.vote
("1" | "-1" | "escalated"
): Votefeedback.promptId
(string
): Prompt IDprojectKey
(string
): Project key for the projectoptions
(object
): Optional parametersoptions.apiUrl
(string
): URL at which to post feedbackoptions.onFeedbackSubmitted
(function
): Callback function when feedback is
submittedoptions.signal
(AbortSignal
): AbortController signalA promise that resolves when the feedback is submitted. Has no return value.
This library is created by the team behind Markprompt (@markprompt).
FAQs
`@markprompt/core` is the core library for Markprompt, a conversational AI component for your website, trained on your data.
We found that @markprompt/core demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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