Defined in: src/lib/models/cache.ts:12 Type alias representing an entry stored in the Maxim cache. Currently aliases PromptVersionsAndRules, which contains prompt configurations, deployment rules, and version information. This type may be extended in the future to support additional cache entry types.

See

PromptVersionsAndRules For the full structure of cached prompt data

Choice

Choice = object

Defined in: src/lib/models/prompt.ts:163 Represents a single choice/response option from an AI model completion. Contains the generated message, its position in the response array, and the reason why generation finished (e.g., natural stop, length limit).

Example

const choice: Choice = {
  index: 0,
  message: {
    role: "assistant",
    content: "The weather in San Francisco is sunny and 72°F."
  },
  finishReason: "stop"
};

Properties

finishReason

finishReason: string

Defined in: src/lib/models/prompt.ts:166 Reason generation stopped (“stop”, “length”, “function_call”, “tool_calls”, etc.)

index

index: number

Defined in: src/lib/models/prompt.ts:164 Zero-based index of this choice in the response array

message

message: ChatCompletionMessage

Defined in: src/lib/models/prompt.ts:165 The generated assistant message

ColumnStructure

ColumnStructure = Record<string, number>

Defined in: src/lib/utils/csvParser.ts:64 Type representing the structure of columns in a CSV file. Maps column names to their zero-based index positions.

Example

const structure: ColumnStructure = {
  "firstName": 0,
  "lastName": 1,
  "email": 2,
  "age": 3
};

CombinedLocalEvaluatorType<T, U>

CombinedLocalEvaluatorType<T, U> = object

Defined in: src/lib/models/evaluator.ts:31

Type Parameters

T

T extends DataStructure | undefined

U

U extends Record<string, PassFailCriteriaType>

Properties

evaluationFunction()

evaluationFunction: (result, data) => Promise<Record<keyof U, LocalEvaluatorReturnType>> | Record<keyof U, LocalEvaluatorReturnType>

Defined in: src/lib/models/evaluator.ts:33

Parameters

result

contextToEvaluate?

string | string[]

output

string

data

Data<T>

Returns

Promise<Record<keyof U, LocalEvaluatorReturnType>> | Record<keyof U, LocalEvaluatorReturnType>

names

names: keyof U[]

Defined in: src/lib/models/evaluator.ts:32

passFailCriteria

passFailCriteria: U

Defined in: src/lib/models/evaluator.ts:37

CompletionRequestContent

CompletionRequestContent = CompletionRequestTextContent | CompletionRequestImageUrlContent

Defined in: src/lib/models/prompt.ts:80

CompletionRequestImageUrlContent

CompletionRequestImageUrlContent = object

Defined in: src/lib/models/prompt.ts:72 Represents an image URL with optional detail level for vision-enabled models.

Properties

image_url

image_url: object

Defined in: src/lib/models/prompt.ts:74 Image URL configuration

detail?

optional detail: string

url

url: string

type

type: "image_url"

Defined in: src/lib/models/prompt.ts:73 Content type identifier

CompletionRequestTextContent

CompletionRequestTextContent = object

Defined in: src/lib/models/prompt.ts:59

Properties

text

text: string

Defined in: src/lib/models/prompt.ts:61

type

type: "text"

Defined in: src/lib/models/prompt.ts:60

Config

Config = object

Defined in: src/lib/maxim.ts:26 Configuration object for initializing the Maxim SDK.

Properties

apiKey

apiKey: string

Defined in: src/lib/maxim.ts:38 API key for authenticating requests to the Maxim API. Required for all API calls.

See

https://app.getmaxim.ai/workspace?redirect=/settings/api-keys to generate your API key

baseUrl?

optional baseUrl: string

Defined in: src/lib/maxim.ts:31 Base URL for the Maxim API.

Default

"https://app.getmaxim.ai"

cache?

optional cache: MaximCache

Defined in: src/lib/maxim.ts:51 Custom cache implementation for storing and retrieving data.

Default

InMemoryCache - Uses a simple in-memory caching mechanism

debug?

optional debug: boolean

Defined in: src/lib/maxim.ts:58 Enable debug mode for additional logging and troubleshooting information. Useful during development and integration.

Default

false

promptManagement?

optional promptManagement: boolean

Defined in: src/lib/maxim.ts:45 Enable prompt management features. When enabled, allows synchronization of prompts, prompt chains, and folders from Maxim.

Default

false

raiseExceptions?

optional raiseExceptions: boolean

Defined in: src/lib/maxim.ts:64 Raise exceptions instead of logging them.

Default

false

ContextToEvaluateColumn

ContextToEvaluateColumn = "CONTEXT_TO_EVALUATE"

Defined in: src/lib/models/dataset.ts:82

CSVParseOptions

CSVParseOptions = object

Defined in: src/lib/utils/csvParser.ts:30 Configuration options for parsing CSV files.

Examples

// Default CSV parsing
const options: CSVParseOptions = {
  delimiter: ",",
  hasHeader: true,
  quoteChar: '"',
  escapeChar: '"'
};

// Tab-separated values without headers
const tsvOptions: CSVParseOptions = {
  delimiter: "\t",
  hasHeader: false,
  quoteChar: "'",
  escapeChar: "\\"
};

Properties

delimiter?

optional delimiter: string

Defined in: src/lib/utils/csvParser.ts:31 Character used to separate fields in the CSV

escapeChar?

optional escapeChar: string

Defined in: src/lib/utils/csvParser.ts:34 Character used to escape quote characters within quoted fields

hasHeader?

optional hasHeader: boolean

Defined in: src/lib/utils/csvParser.ts:32 Whether the first row contains column headers

quoteChar?

optional quoteChar: string

Defined in: src/lib/utils/csvParser.ts:33 Character used to quote fields containing special characters

CSVWriteOptions

CSVWriteOptions = object

Defined in: src/lib/utils/csvParser.ts:45 Configuration options for writing CSV files.

Properties

delimiter?

optional delimiter: string

Defined in: src/lib/utils/csvParser.ts:46 Character used to separate fields

escapeChar?

optional escapeChar: string

Defined in: src/lib/utils/csvParser.ts:49 Character used to escape quote characters within quoted fields

includeHeader?

optional includeHeader: boolean

Defined in: src/lib/utils/csvParser.ts:47 Whether to include column headers in the output

quoteChar?

optional quoteChar: string

Defined in: src/lib/utils/csvParser.ts:48 Character used to quote fields containing special characters

Data<T>

Data<T> = T extends DataStructure ? { [K in keyof T as (undefined | null) extends MapDataStructureToValue<T[K]> ? never : K]: MapDataStructureToValue<T[K]> } & { [K in keyof T as (undefined | null) extends MapDataStructureToValue<T[K]> ? K : never]?: MapDataStructureToValue<T[K]> } : Record<string, MapDataStructureToValue<DataStructure[string]> | undefined>

Defined in: src/lib/models/dataset.ts:131 Type representing a data entry that conforms to a specific data structure. Provides type-safe access to dataset columns based on the defined data structure. The type automatically handles required vs optional fields based on column types, with nullable variable columns being optional and others being required.

Type Parameters

T

T extends DataStructure | undefined The data structure type defining column names and types

Example

import { Data, createDataStructure } from '@maximai/maxim-js';

// Define a data structure
const structure = createDataStructure({
  userInput: "INPUT",
  expectedResponse: "EXPECTED_OUTPUT",
  context: "CONTEXT_TO_EVALUATE",
  metadata: "NULLABLE_VARIABLE"
});

// Data type is automatically inferred
const dataEntry: Data<typeof structure> = {
  userInput: "What is the weather?",         // Required
  expectedResponse: "Sunny, 72°F",           // Required
  context: ["weather data", "location"],     // Required
  metadata: undefined                        // Optional (nullable)
};

DatasetEntry

DatasetEntry = object

Defined in: src/lib/models/dataset.ts:42

Properties

context?

optional context: Variable

Defined in: src/lib/models/dataset.ts:44

expectedOutput?

optional expectedOutput: Variable

Defined in: src/lib/models/dataset.ts:45

input

input: Variable

Defined in: src/lib/models/dataset.ts:43

DataStructure

DataStructure = Record<string, InputColumn | ExpectedOutputColumn | ContextToEvaluateColumn | VariableColumn | NullableVariableColumn>

Defined in: src/lib/models/dataset.ts:87

DataValue<T>

DataValue<T> = T extends DataStructure ? Data<T>[] | string | CSVFile<Record<keyof T, number>> | (page) => Promise<Data<T>[] | null | undefined> | Data<T>[] | null | undefined : string

Defined in: src/lib/models/dataset.ts:137

Type Parameters

T

T extends DataStructure | undefined

DeploymentVersionDeploymentConfig

DeploymentVersionDeploymentConfig = object

Defined in: src/lib/models/deployment.ts:27

Index Signature

[key: string]: VersionSpecificDeploymentConfig[]

ErrorConfig

ErrorConfig = object

Defined in: src/lib/logger/components/error.ts:8 Configuration object for error.

Properties

code?

optional code: string

Defined in: src/lib/logger/components/error.ts:11

id

id: string

Defined in: src/lib/logger/components/error.ts:9

message

message: string

Defined in: src/lib/logger/components/error.ts:10

metadata?

optional metadata: Record<string, any>

Defined in: src/lib/logger/components/error.ts:15

name?

optional name: string

Defined in: src/lib/logger/components/error.ts:12

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/error.ts:14

type?

optional type: string

Defined in: src/lib/logger/components/error.ts:13

ExpectedOutputColumn

ExpectedOutputColumn = "EXPECTED_OUTPUT"

Defined in: src/lib/models/dataset.ts:81

FileAttachment

FileAttachment = BaseAttachmentProps & object

Defined in: src/lib/logger/components/attachment.ts:21 File attachment type for referencing files on the local filesystem.

Type declaration

path

path: string

type

type: "file"

FileDataAttachment

FileDataAttachment = BaseAttachmentProps & object

Defined in: src/lib/logger/components/attachment.ts:34 File data attachment type for directly embedding binary data.

Type declaration

data

data: Buffer

type

type: "fileData"

Folder

Folder = object

Defined in: src/lib/models/folder.ts:3

Properties

id

id: string

Defined in: src/lib/models/folder.ts:4

name

name: string

Defined in: src/lib/models/folder.ts:5

parentFolderId

parentFolderId: string

Defined in: src/lib/models/folder.ts:6

GenerationConfig

GenerationConfig = object

Defined in: src/lib/logger/components/generation.ts:76 Configuration object for generation.

Properties

id

id: string

Defined in: src/lib/logger/components/generation.ts:77

maximPromptId?

optional maximPromptId: string

Defined in: src/lib/logger/components/generation.ts:81

messages

messages: (CompletionRequest | ChatCompletionMessage)[]

Defined in: src/lib/logger/components/generation.ts:82

model

model: string

Defined in: src/lib/logger/components/generation.ts:80

modelParameters

modelParameters: Record<string, any>

Defined in: src/lib/logger/components/generation.ts:83

name?

optional name: string

Defined in: src/lib/logger/components/generation.ts:78

provider

provider: "openai" | "bedrock" | "anthropic" | "huggingface" | "azure" | "together" | "groq" | "google"

Defined in: src/lib/logger/components/generation.ts:79

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/generation.ts:84

HumanEvaluationConfig

HumanEvaluationConfig = object

Defined in: src/lib/models/evaluator.ts:98

Properties

emails

emails: string[]

Defined in: src/lib/models/evaluator.ts:99

instructions?

optional instructions: string

Defined in: src/lib/models/evaluator.ts:100

ImageUrl

ImageUrl = CompletionRequestImageUrlContent["image_url"]

Defined in: src/lib/models/prompt.ts:142 Type alias for image URL configuration used in vision requests.

See

CompletionRequestImageUrlContent For the full image content structure

InputColumn

InputColumn = "INPUT"

Defined in: src/lib/models/dataset.ts:80

LocalEvaluationResult

LocalEvaluationResult = object

Defined in: src/lib/models/evaluator.ts:92 Result object containing the outcome of a local evaluator execution. Represents the complete evaluation result from running a local evaluator on a single test run entry, including the score, reasoning, evaluator name, and the pass/fail criteria used for assessment.

Examples

// Example result from a custom evaluator
const evaluationResult: LocalEvaluationResult = {
  result: {
    score: 0.85,
    reasoning: "Response demonstrates good accuracy with minor factual errors"
  },
  name: "accuracy-checker",
  passFailCriteria: {
    onEachEntry: {
      scoreShouldBe: ">=",
      value: 0.7
    },
    forTestrunOverall: {
      overallShouldBe: ">=",
      value: 80,
      for: "percentageOfPassedResults"
    }
  }
};

// Boolean evaluation result
const booleanResult: LocalEvaluationResult = {
  result: {
    score: true,
    reasoning: "Output contains required keywords"
  },
  name: "keyword-validator",
  passFailCriteria: {
    onEachEntry: {
      scoreShouldBe: "=",
      value: true
    },
    forTestrunOverall: {
      overallShouldBe: ">=",
      value: 90,
      for: "percentageOfPassedResults"
    }
  }
};

Properties

name

name: string

Defined in: src/lib/models/evaluator.ts:94 The name of the evaluator that produced this result

passFailCriteria

passFailCriteria: PassFailCriteriaType

Defined in: src/lib/models/evaluator.ts:95 The criteria used to determine pass/fail status

result

result: LocalEvaluatorReturnType

Defined in: src/lib/models/evaluator.ts:93 The evaluation result containing score and optional reasoning

LocalEvaluatorType<T>

LocalEvaluatorType<T> = object

Defined in: src/lib/models/evaluator.ts:22

Type Parameters

T

T extends DataStructure | undefined = undefined

Properties

evaluationFunction()

evaluationFunction: (result, data) => Promise<LocalEvaluatorReturnType> | LocalEvaluatorReturnType

Defined in: src/lib/models/evaluator.ts:24

Parameters

result

contextToEvaluate?

string | string[]

output

string

data

Data<T>

Returns

Promise<LocalEvaluatorReturnType> | LocalEvaluatorReturnType

name

name: string

Defined in: src/lib/models/evaluator.ts:23

passFailCriteria

passFailCriteria: PassFailCriteriaType

Defined in: src/lib/models/evaluator.ts:28

LoggerConfig

LoggerConfig = object

Defined in: src/lib/logger/logger.ts:17 Configuration object for initializing a MaximLogger instance.

Properties

autoFlush?

optional autoFlush: boolean

Defined in: src/lib/logger/logger.ts:19

flushIntervalSeconds?

optional flushIntervalSeconds: number

Defined in: src/lib/logger/logger.ts:20

id

id: string

Defined in: src/lib/logger/logger.ts:18

LogWriterConfig

LogWriterConfig = object

Defined in: src/lib/logger/writer.ts:19

Properties

apiKey

apiKey: string

Defined in: src/lib/logger/writer.ts:21

autoFlush?

optional autoFlush: boolean

Defined in: src/lib/logger/writer.ts:23

baseUrl

baseUrl: string

Defined in: src/lib/logger/writer.ts:20

flushInterval?

optional flushInterval: number

Defined in: src/lib/logger/writer.ts:24

isDebug?

optional isDebug: boolean

Defined in: src/lib/logger/writer.ts:25

maxInMemoryLogs?

optional maxInMemoryLogs: number

Defined in: src/lib/logger/writer.ts:26

repositoryId

repositoryId: string

Defined in: src/lib/logger/writer.ts:22

MapDataStructureToValue<T>

MapDataStructureToValue<T> = T extends InputColumn ? string : T extends ExpectedOutputColumn ? string : T extends ContextToEvaluateColumn ? string | string[] : T extends VariableColumn ? string | string[] : T extends NullableVariableColumn ? string | string[] | undefined | null : never

Defined in: src/lib/models/dataset.ts:92

Type Parameters

T

T

NullableVariableColumn

NullableVariableColumn = "NULLABLE_VARIABLE"

Defined in: src/lib/models/dataset.ts:84

OperatorType

OperatorType = ">=" | "<" | "<=" | ">" | "=" | "!="

Defined in: src/lib/models/evaluator.ts:8

PassFailCriteriaType

PassFailCriteriaType = object

Defined in: src/lib/models/evaluator.ts:9

Properties

forTestrunOverall

forTestrunOverall: object

Defined in: src/lib/models/evaluator.ts:19

for

for: "average" | "percentageOfPassedResults"

overallShouldBe

overallShouldBe: OperatorType

value

value: number

onEachEntry

onEachEntry: { scoreShouldBe: "=" | "!="; value: boolean; } | { scoreShouldBe: OperatorType; value: number; }

Defined in: src/lib/models/evaluator.ts:10

Prompt

Prompt = object

Defined in: src/lib/models/prompt.ts:230

Properties

messages

messages: (CompletionRequest | ChatCompletionMessage)[]

Defined in: src/lib/models/prompt.ts:234

model

model: string

Defined in: src/lib/models/prompt.ts:236

modelParameters

modelParameters: object

Defined in: src/lib/models/prompt.ts:235

Index Signature

[key: string]: any

promptId

promptId: string

Defined in: src/lib/models/prompt.ts:231

provider

provider: string

Defined in: src/lib/models/prompt.ts:237

run()

run: (input, options?) => Promise<PromptResponse>

Defined in: src/lib/models/prompt.ts:239

Parameters

input

string

options?

imageUrls?

ImageUrl[]

variables?

{[key: string]: string; }

Returns

Promise<PromptResponse>

version

version: number

Defined in: src/lib/models/prompt.ts:232

versionId

versionId: string

Defined in: src/lib/models/prompt.ts:233

PromptChain

PromptChain = object

Defined in: src/lib/models/promptChain.ts:28

Properties

nodes

nodes: object & PromptNode[]

Defined in: src/lib/models/promptChain.ts:32

promptChainId

promptChainId: string

Defined in: src/lib/models/promptChain.ts:29

run()

run: (input, options?) => Promise<AgentResponse>

Defined in: src/lib/models/promptChain.ts:33

Parameters

input

string

options?

variables?

{[key: string]: string; }

Returns

Promise<AgentResponse>

version

version: number

Defined in: src/lib/models/promptChain.ts:30

versionId

versionId: string

Defined in: src/lib/models/promptChain.ts:31

PromptNode

PromptNode = object

Defined in: src/lib/models/promptChain.ts:36

Properties

prompt

prompt: Prompt

Defined in: src/lib/models/promptChain.ts:37

PromptResponse

PromptResponse = object

Defined in: src/lib/models/prompt.ts:221 Complete response object from a prompt execution. Contains the full response from an AI model including all generated choices, usage statistics, model information, and configuration parameters used. This is the primary response format returned by prompt execution methods.

Examples

// Typical prompt response
const response: PromptResponse = {
  id: "chatcmpl-123",
  provider: "openai",
  model: "gpt-4",
  choices: [{
    index: 0,
    message: {
      role: "assistant",
      content: "Hello! How can I help you today?"
    },
    finishReason: "stop"
  }],
  usage: {
    promptTokens: 12,
    completionTokens: 9,
    totalTokens: 21,
    latency: 1200
  },
  modelParams: {
    temperature: 0.7,
    max_tokens: 1000
  }
};

// Using the response
const content = response.choices[0].message.content;
console.log(`Generated: ${content}`);
console.log(`Used ${response.usage.totalTokens} tokens`);

Properties

choices

choices: Choice[]

Defined in: src/lib/models/prompt.ts:225 Array of generated response choices

id

id: string

Defined in: src/lib/models/prompt.ts:222 Unique identifier for this response

model

model: string

Defined in: src/lib/models/prompt.ts:224 Specific model used (e.g., “gpt-4”, “claude-3-sonnet”)

modelParams

modelParams: object

Defined in: src/lib/models/prompt.ts:227 Model parameters used for generation

Index Signature

[key: string]: any

provider

provider: string

Defined in: src/lib/models/prompt.ts:223 AI provider name (e.g., “openai”, “anthropic”, “azure”)

usage

usage: PromptUsage

Defined in: src/lib/models/prompt.ts:226 Token usage and latency information

PromptTags

PromptTags = object

Defined in: src/lib/models/prompt.ts:3

Index Signature

[key: string]: undefined | string | number | boolean

PromptTagValues

PromptTagValues = object

Defined in: src/lib/models/prompt.ts:242

Index Signature

[key: string]: undefined | string | number | boolean

PromptUsage

PromptUsage = object

Defined in: src/lib/models/prompt.ts:169

Properties

completionTokens

completionTokens: number

Defined in: src/lib/models/prompt.ts:171

latency

latency: number

Defined in: src/lib/models/prompt.ts:173

promptTokens

promptTokens: number

Defined in: src/lib/models/prompt.ts:170

totalTokens

totalTokens: number

Defined in: src/lib/models/prompt.ts:172

PromptVersion

PromptVersion = object

Defined in: src/lib/models/prompt.ts:255

Properties

config?

optional config: PromptVersionConfig

Defined in: src/lib/models/prompt.ts:260

createdAt

createdAt: string

Defined in: src/lib/models/prompt.ts:261

description?

optional description: string

Defined in: src/lib/models/prompt.ts:259

id

id: string

Defined in: src/lib/models/prompt.ts:256

promptId

promptId: string

Defined in: src/lib/models/prompt.ts:258

updatedAt

updatedAt: string

Defined in: src/lib/models/prompt.ts:262

version

version: number

Defined in: src/lib/models/prompt.ts:257

PromptVersionConfig

PromptVersionConfig = object

Defined in: src/lib/models/prompt.ts:246

Properties

id

id: string

Defined in: src/lib/models/prompt.ts:247

messages

messages: object[]

Defined in: src/lib/models/prompt.ts:248

content

content: string

role

role: string

model

model: string

Defined in: src/lib/models/prompt.ts:250

modelParameters

modelParameters: object

Defined in: src/lib/models/prompt.ts:249

Index Signature

[key: string]: any

provider

provider: string

Defined in: src/lib/models/prompt.ts:251

tags?

optional tags: PromptTagValues

Defined in: src/lib/models/prompt.ts:252

PromptVersionsAndRules

PromptVersionsAndRules = object

Defined in: src/lib/models/prompt.ts:265

Properties

fallbackVersion

fallbackVersion: PromptVersion | undefined

Defined in: src/lib/models/prompt.ts:269

folderId

folderId: string

Defined in: src/lib/models/prompt.ts:266

rules

rules: DeploymentVersionDeploymentConfig

Defined in: src/lib/models/prompt.ts:267

versions

versions: PromptVersion[]

Defined in: src/lib/models/prompt.ts:268

QueryRule

QueryRule = object

Defined in: src/lib/models/queryBuilder.ts:27 Configuration object for prompt and prompt chain queries. Defines the parameters used to filter and select specific versions of prompts or prompt chains based on deployment variables, tags, and matching criteria. Used internally by the QueryBuilder to construct queries for the Maxim API.

See

QueryBuilder For constructing QueryRule objects

Example

// Example QueryRule structure
const rule: QueryRule = {
  query: "environment=production,version=v2.0",
  operator: "AND",
  exactMatch: true,
  scopes: { folder: "folder-123" }
};

Properties

exactMatch

exactMatch: boolean

Defined in: src/lib/models/queryBuilder.ts:30 Whether to require exact matching of all criteria

operator

operator: "AND" | "OR"

Defined in: src/lib/models/queryBuilder.ts:29 Logical operator for combining multiple criteria

query

query: string

Defined in: src/lib/models/queryBuilder.ts:28 The query string containing comma-separated key=value pairs

scopes

scopes: Scopes

Defined in: src/lib/models/queryBuilder.ts:31 Additional scope filters like folder restrictions

RetrievalConfig

RetrievalConfig = object

Defined in: src/lib/logger/components/retrieval.ts:9 Configuration object for retrieval.

Properties

id

id: string

Defined in: src/lib/logger/components/retrieval.ts:10

name?

optional name: string

Defined in: src/lib/logger/components/retrieval.ts:11

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/retrieval.ts:12

Scopes

Scopes = object

Defined in: src/lib/models/queryBuilder.ts:34

Index Signature

[key: string]: string

SessionConfig

SessionConfig = object

Defined in: src/lib/logger/components/session.ts:9 Configuration object for session.

Properties

id

id: string

Defined in: src/lib/logger/components/session.ts:10

name?

optional name: string

Defined in: src/lib/logger/components/session.ts:11

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/session.ts:12

SpanConfig

SpanConfig = object

Defined in: src/lib/logger/components/span.ts:13 Configuration object for span.

Properties

id

id: string

Defined in: src/lib/logger/components/span.ts:14

name?

optional name: string

Defined in: src/lib/logger/components/span.ts:15

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/span.ts:16

TestRunBuilder<T>

TestRunBuilder<T> = object

Defined in: src/lib/models/testRun.ts:293

Type Parameters

T

T extends DataStructure | undefined = undefined

Properties

getConfig()

getConfig: () => TestRunConfig<T>

Defined in: src/lib/models/testRun.ts:555 Gets the current TestRunConfig.

Returns

TestRunConfig<T> The current TestRunConfig.

run()

run: (timeoutInMinutes?) => Promise<{ failedEntryIndices: number[]; testRunResult: TestRunResult; }>

Defined in: src/lib/models/testRun.ts:598 Runs the test run with the configured configuration.

Parameters

timeoutInMinutes?

number The timeout in minutes for the test run. Will be rounded to the nearest whole number if given a floating value (optional, defaults to 15 minutes)

Returns

Promise<{ failedEntryIndices: number[]; testRunResult: TestRunResult; }> The test run result.

Async

Throws

for any of the following reasons:

If the test run is not configured properly (sanitization error)
If the test run is taking too long to complete, i.e., passed the timeout limit (you can still view the report on our web portal though)
If the test run itself fails due to any reason.

Example

const testRunResult = await maxim.createTestRun("testRunName", "workspaceId")
    .withDataStructure({
        myInputCol: "INPUT",
        myExp: "EXPECTED_OUTPUT",
        context: "CONTEXT_TO_EVALUATE",
        additionalData: "NULLABLE_VARIABLE",
    })
    .withData(
        "datasetId"
    )
    .withEvaluators(
        "Faithfulness",
        "HumanValidation",
    )
    .withHumanEvaluationConfig({
        emails: ["user@example.com"],
        instructions: "Please provide a brief reasoning behind the scoring.",
    })
    .yieldsOutput(async (data) => {
        const output = await runModel(data.myInputCol, data.context);
        return {
            data: output.text,
            retrievedContext: output.retrievedContext,
            meta: output.meta,
        };
    })
    .run(60 * 2); // while waiting for the test run to finish
    // once all entries are pushed; wait for 2 hours before
    // timing out and throwing an error (test run can still
    // be viewed on our web portal)

withConcurrency()

withConcurrency: (concurrency) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:549 Sets the concurrency for the test run. (optional, defaults to 10).

Parameters

concurrency

TestRunConfig<T>["concurrency"] The concurrency to set.

Returns

TestRunBuilder<T> The TestRunBuilder with the concurrency set.

Example

maxim
    .createTestRun("name", "workspaceId")
    .withConcurrency(10); // defaults to 10

withData()

withData: (data) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:358 Sets the data for the test run.

Parameters

data

TestRunConfig<T>["data"] The data to set. Can be a datasetId(string), a CSV file, an array of column to value mappings, or a function that returns the data in the format of the data structure. (if the data structure is not provided, only datasetId would be a valid type) Note: If the data is a function, you will need to return null or undefined to indicate the end of the data.

Returns

TestRunBuilder<T> The TestRunBuilder with the data set.

See

withDataStructure

Throws

for any of the following reasons:

if the data argument is not a datasetId (when the data structure is not provided)
if the data does not match the data structure. (The data structure can differ from the remote data structure but the keys/column names shouldn’t)
if the data is a CSVFile and it does not exist.

Example

maxim
    .createTestRun("name", "workspaceId")
    .withDataStructure({
        myInputCol: "INPUT",
        myExp: "EXPECTED_OUTPUT",
        context: "CONTEXT_TO_EVALUATE",
        additionalData: "NULLABLE_VARIABLE",
    })
    .withData(
        new maxim.CSVFile("path/to/file.csv")
        // OR
        "datasetId"
        // OR
        [
            {
                myInputCol: "input",
                myExp: "",
                context: "",
            },
            {
                myInputCol: "hello",
                myExp: "hi!",
                context: ["chunk1"],
            },
        ]
        // OR
        async (page) => {
            // Get the data from the page
            const data = await getDataFromPage(page);
            return data; // returning null or undefined will be treated as the end of the data
        }
    );

withDataStructure()

withDataStructure: <U>(dataStructure) => TestRunBuilder<U>

Defined in: src/lib/models/testRun.ts:312 Sets the data structure for the data being used in the test run. Note: Data structure is necessary for manual / CSV data as column types cannot be inferred without it.

Type Parameters

U

U extends DataStructure

Parameters

dataStructure

U The data structure to set.

Returns

TestRunBuilder<U> The TestRunBuilder with the data structure set.

See

withData

Throws

if the data structure contains more than one input, expectedOutput or contextToEvaluate column. (there can be multiple variable columns)

Example

maxim
	.createTestRun("name", "workspaceId")
	.withDataStructure({
		myInputCol: "INPUT",
		myExp: "EXPECTED_OUTPUT",
		context: "CONTEXT_TO_EVALUATE",
		additionalData: "VARIABLE", // or "NULLABLE_VARIABLE"
	});

withEvaluators()

withEvaluators: (…evaluators) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:420 Sets the evaluators from the platform to be used in the test run. Note:

You may create an evaluator locally through code or use an evaluator that is installed in your workspace through the name directly.
If the evaluators contain a human evaluator, you will need to set the human evaluation config or the test run will fail.

Parameters

evaluators

…TestRunConfig<T>["evaluators"] The evaluators to execute.

Returns

TestRunBuilder<T> The TestRunBuilder with the evaluators set.

See

Throws

for any of the following reasons:

if multiple evaluators have the same name

Example

import {
createCustomEvaluator,
createCustomCombinedEvaluatorsFor,
} from "@maximai/maxim-js";

const dataStructure = createDataStructure({
   *  Input: 'INPUT',
   *  'Expected Output': 'EXPECTED_OUTPUT',
   *  Context: 'VARIABLE',
   * });
   *
   * const customApostropheChecker = createCustomEvaluator<typeof dataStructure>(
   *  'apostrophe-checker',
   *  (result, data) => { // data contains the current data entry on which the output was obtained
   *      if (result.output.includes("'")) {
   *          return {
   *              score: true,
   *              reasoning: 'The output contains an apostrophe',
   *          };
   *      } else {
   *          return {
   *              score: false,
   *              reasoning: 'The output does not contain an apostrophe',
   *          };
   *      }
   *  },
   *  {
   *      onEachEntry: {
   *          scoreShouldBe: '=',
   *          value: true,
   *      },
   *      forTestrunOverall: {
   *          overallShouldBe: '>=',
   *          value: 80,
   *          for: 'percentageOfPassedResults',
   *      },
   *  },
   * );
   *
maxim
    .createTestRun("name", "workspaceId")
    .withEvaluators(
        "Faithfulness",
        customApostropheChecker,
    );

withHumanEvaluationConfig()

withHumanEvaluationConfig: (humanEvaluationConfig) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:436 Sets the human evaluation config for the test run.

Parameters

humanEvaluationConfig

HumanEvaluationConfig The human evaluation config.

Returns

TestRunBuilder<T> The ComparisonTestRunBuilder with the human evaluation config set.

Throws

if the emails passed are not valid

Example

maxim
    .createTestRun("name", "workspaceId")
    .withEvaluators("HumanEvaluator")
    .withHumanEvaluationConfig({
        emails: ["user@example.com"],
        instructions: "Please provide a brief reasoning behind the scoring.",
    });

withLogger()

withLogger: (logger) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:538 Sets the logger for the test run. (optional, we have a default logger implemented already).

Parameters

logger

TestRunConfig<T>["logger"] The logger satisfying TestRunLogger interface.

Returns

TestRunBuilder<T> The TestRunBuilder with the logger set.

See

TestRunLogger

Example

maxim
    .createTestRun("name", "workspaceId")
    .withLogger({
         info(message) {
            console.info(message);
        },
        error(message) {
            console.error(message);
        },
        processed(message, data) {
            console.info(message);
            // OR
            // console.log("ran entry =>", data.datasetEntry, data.output, data.evaluationResults);
        },
    })

withPromptChainVersionId()

withPromptChainVersionId: (id, contextToEvaluate?) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:501 Sets the prompt chain version ID for the test run. Optionally, you can also set the context to evaluate for the prompt chain. (Note: setting the context to evaluate will end up overriding the CONTEXT_TO_EVALUATE dataset column value)

Parameters

id

string The prompt chain version ID to set.

contextToEvaluate?

string The context to evaluate for the prompt chain (variable name essentially).

Returns

TestRunBuilder<T> The TestRunBuilder with the prompt chain version set.

Example

maxim
    .createTestRun("name", "workspaceId")
    .withPromptChainVersionId("promptChainVersionId", "contextVariableName");

withPromptVersionId()

withPromptVersionId: (id, contextToEvaluate?) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:489 Sets the prompt version ID for the test run. Optionally, you can also set the context to evaluate for the prompt. (Note: setting the context to evaluate will end up overriding the CONTEXT_TO_EVALUATE dataset column value)

Parameters

id

string The prompt version ID to set.

contextToEvaluate?

string The context to evaluate for the prompt (variable name essentially).

Returns

TestRunBuilder<T> The TestRunBuilder with the prompt version set.

Example

maxim
    .createTestRun("name", "workspaceId")
    .withPromptVersionId("promptVersionId", "contextVariableName");

withWorkflowId()

withWorkflowId: (id, contextToEvaluate?) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:513 Sets the workflow ID for the test run. Optionally, you can also set the context to evaluate for the workflow. (Note: setting the context to evaluate will end up overriding the CONTEXT_TO_EVALUATE dataset column value)

Parameters

id

string The workflow ID to set.

contextToEvaluate?

string The context to evaluate for the workflow (variable name essentially).

Returns

TestRunBuilder<T> The TestRunBuilder with the workflow set.

Example

maxim
    .createTestRun("name", "workspaceId")
    .withWorkflowId("workflowId", "contextVariableName");

yieldsOutput()

yieldsOutput: (outputFunction) => TestRunBuilder<T>

Defined in: src/lib/models/testRun.ts:477 Sets the output retrieval function for the test run. Note: Throwing from this function will cause the test run entry being executed to fail and not added to the test run on the server. You will still get back the indices of all the failed entries once the run is finished.

Parameters

outputFunction

TestRunConfig<T>["outputFunction"] The output retrieval function.

Returns

TestRunBuilder<T> The TestRunBuilder with the output retrieval function set.

Example

maxim
    .createTestRun("name", "workspaceId")
    .yieldsOutput((data) => {
        // This is just an example, you can use
        // the columns from the dataset to
        // retrieve the output anyway you want
        const output = await modelCall(
            data.myInputCol,
            data.context,
        );
        return {
            // The actual output
            data: output.text,
            // Retrieved context (if any)
            retrievedContext: output.retrievedContext,
            // Additional metadata (if any)
            meta: {
                usage: {
                    promptTokens: output.usage.promptTokens,
                    completionTokens: output.usage.completionTokens,
                    totalTokens: output.usage.totalTokens,
                    latency: output.usage.latency,
                },
                cost: {
                    input: output.cost.input,
                    output: output.cost.output,
                    total: output.cost.input + output.cost.output,
                },
            },
        };
    });

TestRunConfig<T>

TestRunConfig<T> = object

Defined in: src/lib/models/testRun.ts:266 Configuration for a test run.

Type Parameters

T

T extends DataStructure | undefined = undefined

Properties

apiKey

apiKey: string

Defined in: src/lib/models/testRun.ts:268

baseUrl

baseUrl: string

Defined in: src/lib/models/testRun.ts:267

concurrency?

optional concurrency: number

Defined in: src/lib/models/testRun.ts:290

data?

optional data: DataValue<T>

Defined in: src/lib/models/testRun.ts:273

dataStructure?

optional dataStructure: T

Defined in: src/lib/models/testRun.ts:272

evaluators

evaluators: (LocalEvaluatorType<T> | CombinedLocalEvaluatorType<T, Record<string, PassFailCriteriaType>> | string)[]

Defined in: src/lib/models/testRun.ts:274

humanEvaluationConfig?

optional humanEvaluationConfig: HumanEvaluationConfig

Defined in: src/lib/models/testRun.ts:275

logger?

optional logger: TestRunLogger<T>

Defined in: src/lib/models/testRun.ts:289

name

name: string

Defined in: src/lib/models/testRun.ts:270

outputFunction()?

optional outputFunction: (data) => YieldedOutput | Promise<YieldedOutput>

Defined in: src/lib/models/testRun.ts:276

Parameters

data

Data<T>

Returns

YieldedOutput | Promise<YieldedOutput>

promptChainVersion?

optional promptChainVersion: object

Defined in: src/lib/models/testRun.ts:281

contextToEvaluate?

optional contextToEvaluate: string

id

id: string

promptVersion?

optional promptVersion: object

Defined in: src/lib/models/testRun.ts:277

contextToEvaluate?

optional contextToEvaluate: string

id

id: string

testConfigId?

optional testConfigId: string

Defined in: src/lib/models/testRun.ts:271

workflow?

optional workflow: object

Defined in: src/lib/models/testRun.ts:285

contextToEvaluate?

optional contextToEvaluate: string

id

id: string

workspaceId

workspaceId: string

Defined in: src/lib/models/testRun.ts:269

TestRunResult

TestRunResult = object

Defined in: src/lib/models/testRun.ts:226 Complete results and metrics from a test run execution. Contains comprehensive information about test run performance including individual evaluator scores, aggregated metrics, token usage, costs, and latency statistics. Provides both detailed results and a link to view the full report in the Maxim web interface.

Examples

// Example test run result
const testResult: TestRunResult = {
  link: "https://app.getmaxim.ai/workspace/123/test-runs/456",
  result: [{
    name: "Accuracy Test Run",
    individualEvaluatorMeanScore: {
      "bias": { score: 0.87, pass: true, outOf: 1.0 },
      "toxicity": { score: 0.92, pass: true, outOf: 1.0 },
      "custom-programmatic-evaluator": { score: 1.0, pass: true }
    },
    usage: {
      total: 15420,
      input: 12300,
      completion: 3120
    },
    cost: {
      total: 0.0234,
      input: 0.0123,
      completion: 0.0111
    },
    latency: {
      min: 890,
      max: 2340,
      p50: 1200,
      p90: 1800,
      p95: 2100,
      p99: 2300,
      mean: 1350,
      standardDeviation: 320,
      total: 135000
    }
  }]
};

// Using test run results
const { testRunResult } = await maxim.createTestRun("my-test", "workspace")
  .withData(dataset)
  .withEvaluators("accuracy", "relevance")
  .yieldsOutput(generateOutput)
  .run();

console.log(`View report: ${testRunResult.link}`);

const scores = testRunResult.result[0].individualEvaluatorMeanScore;
for (const [evaluator, result] of Object.entries(scores)) {
  console.log(`${evaluator}: ${result.score} (${result.pass ? 'PASS' : 'FAIL'})`);
}

Properties

link

link: string

Defined in: src/lib/models/testRun.ts:227 URL to view the detailed test run report in Maxim

result

result: object[]

Defined in: src/lib/models/testRun.ts:228 Array of test run result objects (typically one)

cost?

optional cost: object

cost.completion

completion: number

cost.input

input: number

cost.total

total: number

individualEvaluatorMeanScore

individualEvaluatorMeanScore: object

Index Signature

[key: string]: object & { outOf?: number; score: number; } | { score: boolean | string; }

latency?

optional latency: object

latency.max

max: number

latency.mean

mean: number

latency.min

min: number

latency.p50

p50: number

latency.p90

p90: number

latency.p95

p95: number

latency.p99

p99: number

latency.standardDeviation

standardDeviation: number

latency.total

total: number

name

name: string

usage?

optional usage: object

usage.completion

completion: number

usage.input

input: number

usage.total

total: number

TraceConfig

TraceConfig = object

Defined in: src/lib/logger/components/trace.ts:14 Configuration object for trace.

Properties

id

id: string

Defined in: src/lib/logger/components/trace.ts:15

name?

optional name: string

Defined in: src/lib/logger/components/trace.ts:16

sessionId?

optional sessionId: string

Defined in: src/lib/logger/components/trace.ts:17

tags?

optional tags: Record<string, string>

Defined in: src/lib/logger/components/trace.ts:18

UrlAttachment

UrlAttachment = BaseAttachmentProps & object

Defined in: src/lib/logger/components/attachment.ts:47 URL attachment type for referencing external resources.

Type declaration

type

type: "url"

url

url: string

Variable

Variable = object

Defined in: src/lib/models/dataset.ts:37

Properties

payload

payload: string

Defined in: src/lib/models/dataset.ts:39

type

type: VariableType

Defined in: src/lib/models/dataset.ts:38

VariableColumn

VariableColumn = "VARIABLE"

Defined in: src/lib/models/dataset.ts:83

VersionSpecificDeploymentConfig

VersionSpecificDeploymentConfig = object

Defined in: src/lib/models/deployment.ts:20

Properties

id

id: string

Defined in: src/lib/models/deployment.ts:21

isFallback

isFallback: boolean

Defined in: src/lib/models/deployment.ts:24

rules

rules: DeploymentRules

Defined in: src/lib/models/deployment.ts:23

timestamp

timestamp: Date

Defined in: src/lib/models/deployment.ts:22

YieldedOutput

YieldedOutput = object

Defined in: src/lib/models/testRun.ts:144 Output data structure returned by test run output functions. Contains the generated output data along with optional metadata about the generation process including token usage, costs, and retrieved context. This is the expected return type for functions passed to yieldsOutput().

Examples

// Simple output
const output: YieldedOutput = {
  data: "The weather in San Francisco is sunny and 72°F"
};

// Output with full metadata
const output: YieldedOutput = {
  data: "Based on the provided documents, the answer is...",
  retrievedContextToEvaluate: [
    "Document 1: Weather data shows...",
    "Document 2: Historical trends indicate..."
  ],
  meta: {
    usage: {
      promptTokens: 150,
      completionTokens: 45,
      totalTokens: 195,
      latency: 1200
    },
    cost: {
      input: 0.0015,
      output: 0.0045,
      total: 0.006
    }
  }
};

// Using in yieldsOutput function
maxim.createTestRun("accuracy-test", "workspace-id")
  .yieldsOutput(async (data) => {
    const response = await callLLM(data.input);
    return {
      data: response.text,
      meta: {
        usage: response.usage,
        cost: response.cost
      }
    };
  });

Properties

data

data: string

Defined in: src/lib/models/testRun.ts:145 The main generated output text

meta?

optional meta: object

Defined in: src/lib/models/testRun.ts:147 Optional metadata about the generation process

cost?

optional cost: object

cost.input

input: number

cost.output

output: number

cost.total

total: number

usage?

optional usage: { completionTokens: number; latency?: number; promptTokens: number; totalTokens: number; } | { latency: number; }

retrievedContextToEvaluate?

optional retrievedContextToEvaluate: string | string[]

Defined in: src/lib/models/testRun.ts:146 Context retrieved during generation for evaluation

Functions

createCustomCombinedEvaluatorsFor()

createCustomCombinedEvaluatorsFor<U>(…names): object

Defined in: src/lib/evaluators/evaluators.ts:134 Creates a builder for combined evaluators that can output multiple evaluator scores under the same evaluation function. Combined evaluators allow a single evaluation function to return multiple named scores, useful when one analysis can produce several metrics. Each named score must have corresponding pass/fail criteria.

Type Parameters

U

U extends string[] String literal array type containing evaluator names

Parameters

names

…U Array of evaluator names that will be returned by the evaluation function

Returns

Builder object with a build method to create the combined evaluator

build()

build: <T>(evaluationFunction, passFailCriteria) => CombinedLocalEvaluatorType<T, Record<U[number], PassFailCriteriaType>>

Builds the combined evaluator with evaluation function and pass/fail criteria.

Type Parameters

T

T extends undefined | DataStructure = undefined The data structure type for the evaluator

Parameters

evaluationFunction

(result, data) => Record<U[number], LocalEvaluatorReturnType> | Promise<Record<U[number], LocalEvaluatorReturnType>> Function returning multiple named scores

passFailCriteria

Record<U[number], PassFailCriteriaType> Criteria for each named evaluator

Returns

CombinedLocalEvaluatorType<T, Record<U[number], PassFailCriteriaType>> The configured combined evaluator

Throws

When passFailCriteria is missing or contains invalid criteria

Throws

When passFailCriteria contains evaluator names not in the names array

Example

import { createCustomCombinedEvaluatorsFor, createDataStructure } from '@maximai/maxim-js';

const dataStructure = createDataStructure({
  input: "INPUT",
  expectedOutput: "EXPECTED_OUTPUT"
});

const qualityEvaluator = createCustomCombinedEvaluatorsFor("accuracy", "relevance", "fluency")
  .build<typeof dataStructure>(
    (result, data) => {
      // Single function returns multiple scores
      const analysis = analyzeText(result.output);
      return {
        accuracy: { score: analysis.factualScore, reasoning: "Fact-checked against sources" },
        relevance: { score: analysis.topicScore, reasoning: "Relevance to user query" },
        fluency: { score: analysis.grammarScore, reasoning: "Grammar and readability" }
      };
    },
    {
      accuracy: {
        onEachEntry: { scoreShouldBe: ">=", value: 0.8 },
        forTestrunOverall: { overallShouldBe: ">=", value: 85, for: "average" }
      },
      relevance: {
        onEachEntry: { scoreShouldBe: ">=", value: 0.7 },
        forTestrunOverall: { overallShouldBe: ">=", value: 80, for: "average" }
      },
      fluency: {
        onEachEntry: { scoreShouldBe: ">=", value: 0.9 },
        forTestrunOverall: { overallShouldBe: ">=", value: 90, for: "percentageOfPassedResults" }
      }
    }
  );

// Usage in a test run
maxim.createTestRun("quality-test", "workspace-id")
  .withEvaluators(qualityEvaluator)
  .run();

createCustomEvaluator()

createCustomEvaluator<T>(name, evaluationFunction, passFailCriteria): LocalEvaluatorType<T>

Defined in: src/lib/evaluators/evaluators.ts:67 Creates a custom evaluator for local evaluation of test run outputs. Local evaluators run client-side during test runs to score each executed row (with output and retrieved context). They must define both an evaluation function and pass/fail criteria to determine success.

Type Parameters

T

T extends undefined | DataStructure = undefined The data structure type for the evaluator, extending DataStructure or undefined

Parameters

name

string Unique name for the evaluator. Must be unique within a test run.

evaluationFunction

(result, data) => LocalEvaluatorReturnType | Promise<LocalEvaluatorReturnType> Function that scores outputs

passFailCriteria

PassFailCriteriaType Criteria defining pass/fail thresholds

Returns

LocalEvaluatorType<T> A configured local evaluator ready for use in test runs

Throws

When passFailCriteria is null, undefined, or invalid

Examples

import { createCustomEvaluator, createDataStructure } from '@maximai/maxim-js';

const dataStructure = createDataStructure({
  input: "INPUT",
  expectedOutput: "EXPECTED_OUTPUT"
});

const lengthEvaluator = createCustomEvaluator<typeof dataStructure>(
  "response-length",
  (result, data) => {
    const wordCount = result.output.split(' ').length;
    return {
      score: wordCount,
      reasoning: `Response contains ${wordCount} words`
    };
  },
  {
    onEachEntry: {
      scoreShouldBe: ">=",
      value: 10
    },
    forTestrunOverall: {
      overallShouldBe: ">=",
      value: 80,
      for: "percentageOfPassedResults"
    }
  }
);

// Boolean evaluator example
const containsKeywordEvaluator = createCustomEvaluator<typeof dataStructure>(
  "keyword-checker",
  (result, data) => ({
    score: result.output.toLowerCase().includes("important"),
    reasoning: result.output.includes("important") ? "Contains keyword" : "Missing keyword"
  }),
  {
    onEachEntry: {
      scoreShouldBe: "=",
      value: true
    },
    forTestrunOverall: {
      overallShouldBe: ">=",
      value: 75,
      for: "percentageOfPassedResults"
    }
  }
);

createDataStructure()

createDataStructure<T>(dataStructure): T

Defined in: src/lib/dataset/dataset.ts:24 Creates and validates a data structure definition for test run. Data structures define the schema and column types for datasets used in test runs and evaluations within. This function ensures the structure is valid and returns it for use within test runs.

Type Parameters

T

T extends undefined | DataStructure = undefined The data structure type, extending the type DataStructure or undefined

Parameters

dataStructure

T The data structure definition to create and validate

Returns

T The validated data structure, unchanged if valid

Throws

When the data structure contains multiple INPUT, EXPECTED_OUTPUT, or CONTEXT_TO_EVALUATE columns

Example

import { createDataStructure } from '@maximai/maxim-js';

const dataStructure = createDataStructure({
  userInput: "INPUT",
  expectedResponse: "EXPECTED_OUTPUT",
  context: "CONTEXT_TO_EVALUATE",
  metadata: "VARIABLE"
});

sanitizeDataStructure()

sanitizeDataStructure(dataStructure): void

Defined in: src/lib/dataset/dataset.ts:29

Parameters

dataStructure

undefined | DataStructure

Returns

void

validateDataStructure()

validateDataStructure(dataStructure, againstDataStructure): void

Defined in: src/lib/dataset/dataset.ts:52

Parameters

dataStructure

DataStructure

againstDataStructure

DataStructure

Returns

void

Overview

Python

Typescript

​index

​Enumerations

​Classes

​Interfaces

​Type Aliases

​AgentResponse

​Properties

meta

response

​AgentResponseMeta

​Properties

boundVariableResponses?

Index Signature

cost

retrievedContext?

usage

​Attachment

​BaseAttachmentProps

​Properties

id

metadata?

mimeType?

name?

size?

tags?

​BaseConfig

​Properties

id

name?

spanId?

tags?

​CacheEntry

​See

​Choice

​Example

​Properties

finishReason

index

message

​ColumnStructure

​Example

​CombinedLocalEvaluatorType<T, U>

​Type Parameters

T

U

​Properties

evaluationFunction()

Parameters

result

contextToEvaluate?

output

data

Returns

names

passFailCriteria

​CompletionRequestContent

​CompletionRequestImageUrlContent

​Properties

image_url

detail?

url

type

​CompletionRequestTextContent

​Properties

text

type

​Config

​Properties

apiKey

See

baseUrl?

Default

cache?

Default

debug?

Default

promptManagement?

index

Enumerations

Classes

Interfaces

Type Aliases

AgentResponse

Properties

AgentResponseMeta

Properties

Attachment

BaseAttachmentProps

Properties

BaseConfig

Properties

CacheEntry

See

Choice

Example

Properties

ColumnStructure

Example

CombinedLocalEvaluatorType<T, U>

Type Parameters

Properties

CompletionRequestContent

CompletionRequestImageUrlContent

Properties

CompletionRequestTextContent

Properties

Config

Properties

ContextToEvaluateColumn

CSVParseOptions

Examples

Properties

CSVWriteOptions

Properties

Data<T>

Type Parameters

Example

DatasetEntry

Properties

DataStructure

DataValue<T>

Type Parameters

DeploymentVersionDeploymentConfig

Index Signature

ErrorConfig

Properties

ExpectedOutputColumn

FileAttachment

Type declaration

FileDataAttachment

Type declaration

Folder

Properties

GenerationConfig

Properties

HumanEvaluationConfig

Properties