🧮 refactor: Bulk Transactions & Balance Updates for Token Spending (#11996)
* refactor: transaction handling by integrating pricing and bulk write operations
- Updated `recordCollectedUsage` to accept pricing functions and bulk write operations, improving transaction management.
- Refactored `AgentClient` and related controllers to utilize the new transaction handling capabilities, ensuring better performance and accuracy in token spending.
- Added tests to validate the new functionality, ensuring correct behavior for both standard and bulk transaction paths.
- Introduced a new `transactions.ts` file to encapsulate transaction-related logic and types, enhancing code organization and maintainability.
* chore: reorganize imports in agents client controller
- Moved `getMultiplier` and `getCacheMultiplier` imports to maintain consistency and clarity in the import structure.
- Removed duplicate import of `updateBalance` and `bulkInsertTransactions`, streamlining the code for better readability.
* refactor: add TransactionData type and CANCEL_RATE constant to data-schemas
Establishes a single source of truth for the transaction document shape
and the incomplete-context billing rate constant, both consumed by
packages/api and api/.
* refactor: use proper types in data-schemas transaction methods
- Replace `as unknown as { tokenCredits }` with `lean<IBalance>()`
- Use `TransactionData[]` instead of `Record<string, unknown>[]`
for bulkInsertTransactions parameter
- Add JSDoc noting insertMany bypasses document middleware
- Remove orphan section comment in methods/index.ts
* refactor: use shared types in transactions.ts, fix bulk write logic
- Import CANCEL_RATE from data-schemas instead of local duplicate
- Import TransactionData from data-schemas for PreparedEntry/BulkWriteDeps
- Use tilde alias for EndpointTokenConfig import
- Pass valueKey through to getMultiplier
- Only sum tokenValue for balance-enabled docs in bulkWriteTransactions
- Consolidate two loops into single-pass map
* refactor: remove duplicate updateBalance from Transaction.js
Import updateBalance from ~/models (sourced from data-schemas) instead
of maintaining a second copy. Also import CANCEL_RATE from data-schemas
and remove the Balance model import (no longer needed directly).
* fix: test real spendCollectedUsage instead of IIFE replica
Export spendCollectedUsage from abortMiddleware.js and rewrite the test
file to import and test the actual function. Previously the tests ran
against a hand-written replica that could silently diverge from the real
implementation.
* test: add transactions.spec.ts and restore regression comments
Add 22 direct unit tests for transactions.ts financial logic covering
prepareTokenSpend, prepareStructuredTokenSpend, bulkWriteTransactions,
CANCEL_RATE paths, NaN guards, disabled transactions, zero tokens,
cache multipliers, and balance-enabled filtering.
Restore critical regression documentation comments in
recordCollectedUsage.spec.js explaining which production bugs the
tests guard against.
* fix: widen setValues type to include lastRefill
The UpdateBalanceParams.setValues type was Partial<Pick<IBalance,
'tokenCredits'>> which excluded lastRefill — used by
createAutoRefillTransaction. Widen to also pick 'lastRefill'.
* test: use real MongoDB for bulkWriteTransactions tests
Replace mock-based bulkWriteTransactions tests with real DB tests using
MongoMemoryServer. Pure function tests (prepareTokenSpend,
prepareStructuredTokenSpend) remain mock-based since they don't touch
DB. Add end-to-end integration tests that verify the full prepare →
bulk write → DB state pipeline with real Transaction and Balance models.
* chore: update @librechat/agents dependency to version 3.1.54 in package-lock.json and related package.json files
* test: add bulk path parity tests proving identical DB outcomes
Three test suites proving the bulk path (prepareTokenSpend/
prepareStructuredTokenSpend + bulkWriteTransactions) produces
numerically identical results to the legacy path for all scenarios:
- usage.bulk-parity.spec.ts: mirrors all legacy recordCollectedUsage
tests; asserts same return values and verifies metadata fields on
the insertMany docs match what spendTokens args would carry
- transactions.bulk-parity.spec.ts: real-DB tests using actual
getMultiplier/getCacheMultiplier pricing functions; asserts exact
tokenValue, rate, rawAmount and balance deductions for standard
tokens, structured/cache tokens, CANCEL_RATE, premium pricing,
multi-entry batches, and edge cases (NaN, zero, disabled)
- Transaction.spec.js: adds describe('Bulk path parity') that mirrors
7 key legacy tests via recordCollectedUsage + bulk deps against
real MongoDB, asserting same balance deductions and doc counts
* refactor: update llmConfig structure to use modelKwargs for reasoning effort
Refactor the llmConfig in getOpenAILLMConfig to store reasoning effort within modelKwargs instead of directly on llmConfig. This change ensures consistency in the configuration structure and improves clarity in the handling of reasoning properties in the tests.
* test: update performance checks in processAssistantMessage tests
Revise the performance assertions in the processAssistantMessage tests to ensure that each message processing time remains under 100ms, addressing potential ReDoS vulnerabilities. This change enhances the reliability of the tests by focusing on maximum processing time rather than relative ratios.
* test: fill parity test gaps — model fallback, abort context, structured edge cases
- usage.bulk-parity: add undefined model fallback test
- transactions.bulk-parity: add abort context test (txns inserted,
balance unchanged when balance not passed), fix readTokens type cast
- Transaction.spec: add 3 missing mirrors — balance disabled with
transactions enabled, structured transactions disabled, structured
balance disabled
* fix: deduct balance before inserting transactions to prevent orphaned docs
Swap the order in bulkWriteTransactions: updateBalance runs before
insertMany. If updateBalance fails (after exhausting retries), no
transaction documents are written — avoiding the inconsistent state
where transactions exist in MongoDB with no corresponding balance
deduction.
* chore: import order
* test: update config.spec.ts for OpenRouter reasoning in modelKwargs
Same fix as llm.spec.ts — OpenRouter reasoning is now passed via
modelKwargs instead of llmConfig.reasoning directly.
2026-03-01 12:26:36 -05:00
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const { logger, CANCEL_RATE } = require('@librechat/data-schemas');
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2024-08-17 03:24:09 -04:00
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const { getMultiplier, getCacheMultiplier } = require('./tx');
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🧮 refactor: Bulk Transactions & Balance Updates for Token Spending (#11996)
* refactor: transaction handling by integrating pricing and bulk write operations
- Updated `recordCollectedUsage` to accept pricing functions and bulk write operations, improving transaction management.
- Refactored `AgentClient` and related controllers to utilize the new transaction handling capabilities, ensuring better performance and accuracy in token spending.
- Added tests to validate the new functionality, ensuring correct behavior for both standard and bulk transaction paths.
- Introduced a new `transactions.ts` file to encapsulate transaction-related logic and types, enhancing code organization and maintainability.
* chore: reorganize imports in agents client controller
- Moved `getMultiplier` and `getCacheMultiplier` imports to maintain consistency and clarity in the import structure.
- Removed duplicate import of `updateBalance` and `bulkInsertTransactions`, streamlining the code for better readability.
* refactor: add TransactionData type and CANCEL_RATE constant to data-schemas
Establishes a single source of truth for the transaction document shape
and the incomplete-context billing rate constant, both consumed by
packages/api and api/.
* refactor: use proper types in data-schemas transaction methods
- Replace `as unknown as { tokenCredits }` with `lean<IBalance>()`
- Use `TransactionData[]` instead of `Record<string, unknown>[]`
for bulkInsertTransactions parameter
- Add JSDoc noting insertMany bypasses document middleware
- Remove orphan section comment in methods/index.ts
* refactor: use shared types in transactions.ts, fix bulk write logic
- Import CANCEL_RATE from data-schemas instead of local duplicate
- Import TransactionData from data-schemas for PreparedEntry/BulkWriteDeps
- Use tilde alias for EndpointTokenConfig import
- Pass valueKey through to getMultiplier
- Only sum tokenValue for balance-enabled docs in bulkWriteTransactions
- Consolidate two loops into single-pass map
* refactor: remove duplicate updateBalance from Transaction.js
Import updateBalance from ~/models (sourced from data-schemas) instead
of maintaining a second copy. Also import CANCEL_RATE from data-schemas
and remove the Balance model import (no longer needed directly).
* fix: test real spendCollectedUsage instead of IIFE replica
Export spendCollectedUsage from abortMiddleware.js and rewrite the test
file to import and test the actual function. Previously the tests ran
against a hand-written replica that could silently diverge from the real
implementation.
* test: add transactions.spec.ts and restore regression comments
Add 22 direct unit tests for transactions.ts financial logic covering
prepareTokenSpend, prepareStructuredTokenSpend, bulkWriteTransactions,
CANCEL_RATE paths, NaN guards, disabled transactions, zero tokens,
cache multipliers, and balance-enabled filtering.
Restore critical regression documentation comments in
recordCollectedUsage.spec.js explaining which production bugs the
tests guard against.
* fix: widen setValues type to include lastRefill
The UpdateBalanceParams.setValues type was Partial<Pick<IBalance,
'tokenCredits'>> which excluded lastRefill — used by
createAutoRefillTransaction. Widen to also pick 'lastRefill'.
* test: use real MongoDB for bulkWriteTransactions tests
Replace mock-based bulkWriteTransactions tests with real DB tests using
MongoMemoryServer. Pure function tests (prepareTokenSpend,
prepareStructuredTokenSpend) remain mock-based since they don't touch
DB. Add end-to-end integration tests that verify the full prepare →
bulk write → DB state pipeline with real Transaction and Balance models.
* chore: update @librechat/agents dependency to version 3.1.54 in package-lock.json and related package.json files
* test: add bulk path parity tests proving identical DB outcomes
Three test suites proving the bulk path (prepareTokenSpend/
prepareStructuredTokenSpend + bulkWriteTransactions) produces
numerically identical results to the legacy path for all scenarios:
- usage.bulk-parity.spec.ts: mirrors all legacy recordCollectedUsage
tests; asserts same return values and verifies metadata fields on
the insertMany docs match what spendTokens args would carry
- transactions.bulk-parity.spec.ts: real-DB tests using actual
getMultiplier/getCacheMultiplier pricing functions; asserts exact
tokenValue, rate, rawAmount and balance deductions for standard
tokens, structured/cache tokens, CANCEL_RATE, premium pricing,
multi-entry batches, and edge cases (NaN, zero, disabled)
- Transaction.spec.js: adds describe('Bulk path parity') that mirrors
7 key legacy tests via recordCollectedUsage + bulk deps against
real MongoDB, asserting same balance deductions and doc counts
* refactor: update llmConfig structure to use modelKwargs for reasoning effort
Refactor the llmConfig in getOpenAILLMConfig to store reasoning effort within modelKwargs instead of directly on llmConfig. This change ensures consistency in the configuration structure and improves clarity in the handling of reasoning properties in the tests.
* test: update performance checks in processAssistantMessage tests
Revise the performance assertions in the processAssistantMessage tests to ensure that each message processing time remains under 100ms, addressing potential ReDoS vulnerabilities. This change enhances the reliability of the tests by focusing on maximum processing time rather than relative ratios.
* test: fill parity test gaps — model fallback, abort context, structured edge cases
- usage.bulk-parity: add undefined model fallback test
- transactions.bulk-parity: add abort context test (txns inserted,
balance unchanged when balance not passed), fix readTokens type cast
- Transaction.spec: add 3 missing mirrors — balance disabled with
transactions enabled, structured transactions disabled, structured
balance disabled
* fix: deduct balance before inserting transactions to prevent orphaned docs
Swap the order in bulkWriteTransactions: updateBalance runs before
insertMany. If updateBalance fails (after exhausting retries), no
transaction documents are written — avoiding the inconsistent state
where transactions exist in MongoDB with no corresponding balance
deduction.
* chore: import order
* test: update config.spec.ts for OpenRouter reasoning in modelKwargs
Same fix as llm.spec.ts — OpenRouter reasoning is now passed via
modelKwargs instead of llmConfig.reasoning directly.
2026-03-01 12:26:36 -05:00
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const { Transaction } = require('~/db/models');
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const { updateBalance } = require('~/models');
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2025-03-22 17:54:25 -04:00
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2024-08-17 03:24:09 -04:00
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/** Method to calculate and set the tokenValue for a transaction */
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2025-05-30 22:18:13 -04:00
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function calculateTokenValue(txn) {
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2026-02-06 18:35:36 -05:00
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const { valueKey, tokenType, model, endpointTokenConfig, inputTokenCount } = txn;
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const multiplier = Math.abs(
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getMultiplier({ valueKey, tokenType, model, endpointTokenConfig, inputTokenCount }),
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);
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2025-05-30 22:18:13 -04:00
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txn.rate = multiplier;
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txn.tokenValue = txn.rawAmount * multiplier;
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if (txn.context && txn.tokenType === 'completion' && txn.context === 'incomplete') {
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🧮 refactor: Bulk Transactions & Balance Updates for Token Spending (#11996)
* refactor: transaction handling by integrating pricing and bulk write operations
- Updated `recordCollectedUsage` to accept pricing functions and bulk write operations, improving transaction management.
- Refactored `AgentClient` and related controllers to utilize the new transaction handling capabilities, ensuring better performance and accuracy in token spending.
- Added tests to validate the new functionality, ensuring correct behavior for both standard and bulk transaction paths.
- Introduced a new `transactions.ts` file to encapsulate transaction-related logic and types, enhancing code organization and maintainability.
* chore: reorganize imports in agents client controller
- Moved `getMultiplier` and `getCacheMultiplier` imports to maintain consistency and clarity in the import structure.
- Removed duplicate import of `updateBalance` and `bulkInsertTransactions`, streamlining the code for better readability.
* refactor: add TransactionData type and CANCEL_RATE constant to data-schemas
Establishes a single source of truth for the transaction document shape
and the incomplete-context billing rate constant, both consumed by
packages/api and api/.
* refactor: use proper types in data-schemas transaction methods
- Replace `as unknown as { tokenCredits }` with `lean<IBalance>()`
- Use `TransactionData[]` instead of `Record<string, unknown>[]`
for bulkInsertTransactions parameter
- Add JSDoc noting insertMany bypasses document middleware
- Remove orphan section comment in methods/index.ts
* refactor: use shared types in transactions.ts, fix bulk write logic
- Import CANCEL_RATE from data-schemas instead of local duplicate
- Import TransactionData from data-schemas for PreparedEntry/BulkWriteDeps
- Use tilde alias for EndpointTokenConfig import
- Pass valueKey through to getMultiplier
- Only sum tokenValue for balance-enabled docs in bulkWriteTransactions
- Consolidate two loops into single-pass map
* refactor: remove duplicate updateBalance from Transaction.js
Import updateBalance from ~/models (sourced from data-schemas) instead
of maintaining a second copy. Also import CANCEL_RATE from data-schemas
and remove the Balance model import (no longer needed directly).
* fix: test real spendCollectedUsage instead of IIFE replica
Export spendCollectedUsage from abortMiddleware.js and rewrite the test
file to import and test the actual function. Previously the tests ran
against a hand-written replica that could silently diverge from the real
implementation.
* test: add transactions.spec.ts and restore regression comments
Add 22 direct unit tests for transactions.ts financial logic covering
prepareTokenSpend, prepareStructuredTokenSpend, bulkWriteTransactions,
CANCEL_RATE paths, NaN guards, disabled transactions, zero tokens,
cache multipliers, and balance-enabled filtering.
Restore critical regression documentation comments in
recordCollectedUsage.spec.js explaining which production bugs the
tests guard against.
* fix: widen setValues type to include lastRefill
The UpdateBalanceParams.setValues type was Partial<Pick<IBalance,
'tokenCredits'>> which excluded lastRefill — used by
createAutoRefillTransaction. Widen to also pick 'lastRefill'.
* test: use real MongoDB for bulkWriteTransactions tests
Replace mock-based bulkWriteTransactions tests with real DB tests using
MongoMemoryServer. Pure function tests (prepareTokenSpend,
prepareStructuredTokenSpend) remain mock-based since they don't touch
DB. Add end-to-end integration tests that verify the full prepare →
bulk write → DB state pipeline with real Transaction and Balance models.
* chore: update @librechat/agents dependency to version 3.1.54 in package-lock.json and related package.json files
* test: add bulk path parity tests proving identical DB outcomes
Three test suites proving the bulk path (prepareTokenSpend/
prepareStructuredTokenSpend + bulkWriteTransactions) produces
numerically identical results to the legacy path for all scenarios:
- usage.bulk-parity.spec.ts: mirrors all legacy recordCollectedUsage
tests; asserts same return values and verifies metadata fields on
the insertMany docs match what spendTokens args would carry
- transactions.bulk-parity.spec.ts: real-DB tests using actual
getMultiplier/getCacheMultiplier pricing functions; asserts exact
tokenValue, rate, rawAmount and balance deductions for standard
tokens, structured/cache tokens, CANCEL_RATE, premium pricing,
multi-entry batches, and edge cases (NaN, zero, disabled)
- Transaction.spec.js: adds describe('Bulk path parity') that mirrors
7 key legacy tests via recordCollectedUsage + bulk deps against
real MongoDB, asserting same balance deductions and doc counts
* refactor: update llmConfig structure to use modelKwargs for reasoning effort
Refactor the llmConfig in getOpenAILLMConfig to store reasoning effort within modelKwargs instead of directly on llmConfig. This change ensures consistency in the configuration structure and improves clarity in the handling of reasoning properties in the tests.
* test: update performance checks in processAssistantMessage tests
Revise the performance assertions in the processAssistantMessage tests to ensure that each message processing time remains under 100ms, addressing potential ReDoS vulnerabilities. This change enhances the reliability of the tests by focusing on maximum processing time rather than relative ratios.
* test: fill parity test gaps — model fallback, abort context, structured edge cases
- usage.bulk-parity: add undefined model fallback test
- transactions.bulk-parity: add abort context test (txns inserted,
balance unchanged when balance not passed), fix readTokens type cast
- Transaction.spec: add 3 missing mirrors — balance disabled with
transactions enabled, structured transactions disabled, structured
balance disabled
* fix: deduct balance before inserting transactions to prevent orphaned docs
Swap the order in bulkWriteTransactions: updateBalance runs before
insertMany. If updateBalance fails (after exhausting retries), no
transaction documents are written — avoiding the inconsistent state
where transactions exist in MongoDB with no corresponding balance
deduction.
* chore: import order
* test: update config.spec.ts for OpenRouter reasoning in modelKwargs
Same fix as llm.spec.ts — OpenRouter reasoning is now passed via
modelKwargs instead of llmConfig.reasoning directly.
2026-03-01 12:26:36 -05:00
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txn.tokenValue = Math.ceil(txn.tokenValue * CANCEL_RATE);
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txn.rate *= CANCEL_RATE;
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feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
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}
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2025-05-30 22:18:13 -04:00
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}
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feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
|
|
|
|
2025-03-22 17:54:25 -04:00
|
|
|
/**
|
|
|
|
|
* New static method to create an auto-refill transaction that does NOT trigger a balance update.
|
|
|
|
|
* @param {object} txData - Transaction data.
|
|
|
|
|
* @param {string} txData.user - The user ID.
|
|
|
|
|
* @param {string} txData.tokenType - The type of token.
|
|
|
|
|
* @param {string} txData.context - The context of the transaction.
|
|
|
|
|
* @param {number} txData.rawAmount - The raw amount of tokens.
|
|
|
|
|
* @returns {Promise<object>} - The created transaction.
|
|
|
|
|
*/
|
2025-05-30 22:18:13 -04:00
|
|
|
async function createAutoRefillTransaction(txData) {
|
2025-03-22 17:54:25 -04:00
|
|
|
if (txData.rawAmount != null && isNaN(txData.rawAmount)) {
|
|
|
|
|
return;
|
|
|
|
|
}
|
2025-05-30 22:18:13 -04:00
|
|
|
const transaction = new Transaction(txData);
|
2025-03-22 17:54:25 -04:00
|
|
|
transaction.endpointTokenConfig = txData.endpointTokenConfig;
|
2026-02-06 18:35:36 -05:00
|
|
|
transaction.inputTokenCount = txData.inputTokenCount;
|
2025-05-30 22:18:13 -04:00
|
|
|
calculateTokenValue(transaction);
|
2025-03-22 17:54:25 -04:00
|
|
|
await transaction.save();
|
|
|
|
|
|
|
|
|
|
const balanceResponse = await updateBalance({
|
|
|
|
|
user: transaction.user,
|
|
|
|
|
incrementValue: txData.rawAmount,
|
|
|
|
|
setValues: { lastRefill: new Date() },
|
|
|
|
|
});
|
|
|
|
|
const result = {
|
|
|
|
|
rate: transaction.rate,
|
|
|
|
|
user: transaction.user.toString(),
|
|
|
|
|
balance: balanceResponse.tokenCredits,
|
|
|
|
|
};
|
|
|
|
|
logger.debug('[Balance.check] Auto-refill performed', result);
|
|
|
|
|
result.transaction = transaction;
|
|
|
|
|
return result;
|
2025-05-30 22:18:13 -04:00
|
|
|
}
|
2025-03-22 17:54:25 -04:00
|
|
|
|
2024-08-17 03:24:09 -04:00
|
|
|
/**
|
|
|
|
|
* Static method to create a transaction and update the balance
|
2025-08-26 12:10:18 -04:00
|
|
|
* @param {txData} _txData - Transaction data.
|
2024-08-17 03:24:09 -04:00
|
|
|
*/
|
2025-08-26 12:10:18 -04:00
|
|
|
async function createTransaction(_txData) {
|
2025-09-06 00:21:02 +09:00
|
|
|
const { balance, transactions, ...txData } = _txData;
|
2024-12-28 17:15:03 -05:00
|
|
|
if (txData.rawAmount != null && isNaN(txData.rawAmount)) {
|
|
|
|
|
return;
|
|
|
|
|
}
|
feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
|
|
|
|
2025-09-06 00:21:02 +09:00
|
|
|
if (transactions?.enabled === false) {
|
|
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
|
2024-08-17 03:24:09 -04:00
|
|
|
const transaction = new Transaction(txData);
|
|
|
|
|
transaction.endpointTokenConfig = txData.endpointTokenConfig;
|
2026-02-06 18:35:36 -05:00
|
|
|
transaction.inputTokenCount = txData.inputTokenCount;
|
2025-05-30 22:18:13 -04:00
|
|
|
calculateTokenValue(transaction);
|
feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
|
|
|
|
|
|
|
|
await transaction.save();
|
2025-03-21 22:48:11 +01:00
|
|
|
if (!balance?.enabled) {
|
feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
|
2024-04-07 23:28:40 -04:00
|
|
|
let incrementValue = transaction.tokenValue;
|
2025-03-22 17:54:25 -04:00
|
|
|
const balanceResponse = await updateBalance({
|
|
|
|
|
user: transaction.user,
|
|
|
|
|
incrementValue,
|
|
|
|
|
});
|
2024-03-01 13:42:04 -05:00
|
|
|
|
|
|
|
|
return {
|
2024-03-06 00:04:52 -05:00
|
|
|
rate: transaction.rate,
|
2024-03-01 13:42:04 -05:00
|
|
|
user: transaction.user.toString(),
|
2025-03-21 22:48:11 +01:00
|
|
|
balance: balanceResponse.tokenCredits,
|
2024-04-07 23:28:40 -04:00
|
|
|
[transaction.tokenType]: incrementValue,
|
2024-03-01 13:42:04 -05:00
|
|
|
};
|
2025-05-30 22:18:13 -04:00
|
|
|
}
|
feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* refactor(Chains/llms): allow passing callbacks
* refactor(BaseClient): accurately count completion tokens as generation only
* refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM
* wip: summary prompt tokens
* refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end
wip: draft out relevant providers and variables for token tracing
* refactor(createLLM): make streaming prop false by default
* chore: remove use of getTokenCountForResponse
* refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace
* chore: remove passing of streaming prop, also console log useful vars for tracing
* feat: formatFromLangChain helper function to count tokens for ChatModelStart
* refactor(initializeLLM): add role for LLM tracing
* chore(formatFromLangChain): update JSDoc
* feat(formatMessages): formats langChain messages into OpenAI payload format
* chore: install openai-chat-tokens
* refactor(formatMessage): optimize conditional langChain logic
fix(formatFromLangChain): fix destructuring
* feat: accurate prompt tokens for ChatModelStart before generation
* refactor(handleChatModelStart): move to callbacks dir, use factory function
* refactor(initializeLLM): rename 'role' to 'context'
* feat(Balance/Transaction): new schema/models for tracking token spend
refactor(Key): factor out model export to separate file
* refactor(initializeClient): add req,res objects to client options
* feat: add-balance script to add to an existing users' token balance
refactor(Transaction): use multiplier map/function, return balance update
* refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match
* refactor(Tx): add fair fallback value multiplier incase the config result is undefined
* refactor(Balance): rename 'tokens' to 'tokenCredits'
* feat: balance check, add tx.js for new tx-related methods and tests
* chore(summaryPrompts): update prompt token count
* refactor(callbacks): pass req, res
wip: check balance
* refactor(Tx): make convoId a String type, fix(calculateTokenValue)
* refactor(BaseClient): add conversationId as client prop when assigned
* feat(RunManager): track LLM runs with manager, track token spend from LLM,
refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls
* feat(spendTokens): helper to spend prompt/completion tokens
* feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds
refactor(Balance): static check method to return object instead of boolean now
wip(OpenAIClient): implement use of checkBalance
* refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large
refactor(OpenAIClient): add checkBalance
refactor(createStartHandler): add checkBalance
* chore: remove prompt and completion token logging from route handler
* chore(spendTokens): add JSDoc
* feat(logTokenCost): record transactions for basic api calls
* chore(ask/edit): invoke getResponseSender only once per API call
* refactor(ask/edit): pass promptTokens to getIds and include in abort data
* refactor(getIds -> getReqData): rename function
* refactor(Tx): increase value if incomplete message
* feat: record tokenUsage when message is aborted
* refactor: subtract tokens when payload includes function_call
* refactor: add namespace for token_balance
* fix(spendTokens): only execute if corresponding token type amounts are defined
* refactor(checkBalance): throws Error if not enough token credits
* refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run'
* fix(abortMiddleware): circular dependency, and default to empty string for completionTokens
* fix: properly cancel title requests when there isn't enough tokens to generate
* feat(predictNewSummary): custom chain for summaries to allow signal passing
refactor(summaryBuffer): use new custom chain
* feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError
* refactor(createStartHandler): if summary, add error details to runs
* fix(OpenAIClient): support aborting from summarization & showing error to user
refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer
* refactor(logTokenCost -> recordTokenUsage): rename
* refactor(checkBalance): include promptTokens in errorMessage
* refactor(checkBalance/spendTokens): move to models dir
* fix(createLanguageChain): correctly pass config
* refactor(initializeLLM/title): add tokenBuffer of 150 for balance check
* refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called
* refactor(createStartHandler): add error to run if context is plugins as well
* refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run
* refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic
* chore: use absolute equality for addTitle condition
* refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional
* style: icon changes to match official
* fix(BaseClient): getTokenCountForResponse -> getTokenCount
* fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc
* refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled
* fix(e2e/cleanUp): cleanup new collections, import all model methods from index
* fix(config/add-balance): add uncaughtException listener
* fix: circular dependency
* refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance
* fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped
* fix(createStartHandler): correct condition for generations
* chore: bump postcss due to moderate severity vulnerability
* chore: bump zod due to low severity vulnerability
* chore: bump openai & data-provider version
* feat(types): OpenAI Message types
* chore: update bun lockfile
* refactor(CodeBlock): add error block formatting
* refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON
* chore(logViolation): delete user_id after error is logged
* refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex
* fix(DALL-E): use latest openai SDK
* chore: reorganize imports, fix type issue
* feat(server): add balance route
* fix(api/models): add auth
* feat(data-provider): /api/balance query
* feat: show balance if checking is enabled, refetch on final message or error
* chore: update docs, .env.example with token_usage info, add balance script command
* fix(Balance): fallback to empty obj for balance query
* style: slight adjustment of balance element
* docs(token_usage): add PR notes
2023-10-05 18:34:10 -04:00
|
|
|
|
2024-08-17 03:24:09 -04:00
|
|
|
/**
|
|
|
|
|
* Static method to create a structured transaction and update the balance
|
2025-08-26 12:10:18 -04:00
|
|
|
* @param {txData} _txData - Transaction data.
|
2024-08-17 03:24:09 -04:00
|
|
|
*/
|
2025-08-26 12:10:18 -04:00
|
|
|
async function createStructuredTransaction(_txData) {
|
2025-09-06 00:21:02 +09:00
|
|
|
const { balance, transactions, ...txData } = _txData;
|
|
|
|
|
if (transactions?.enabled === false) {
|
|
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
|
2026-02-06 18:35:36 -05:00
|
|
|
const transaction = new Transaction(txData);
|
|
|
|
|
transaction.endpointTokenConfig = txData.endpointTokenConfig;
|
|
|
|
|
transaction.inputTokenCount = txData.inputTokenCount;
|
2024-08-17 03:24:09 -04:00
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
calculateStructuredTokenValue(transaction);
|
2024-08-17 03:24:09 -04:00
|
|
|
|
|
|
|
|
await transaction.save();
|
|
|
|
|
|
2025-03-21 22:48:11 +01:00
|
|
|
if (!balance?.enabled) {
|
2024-08-24 04:36:08 -04:00
|
|
|
return;
|
2024-08-17 03:24:09 -04:00
|
|
|
}
|
|
|
|
|
|
|
|
|
|
let incrementValue = transaction.tokenValue;
|
|
|
|
|
|
2025-03-22 17:54:25 -04:00
|
|
|
const balanceResponse = await updateBalance({
|
|
|
|
|
user: transaction.user,
|
|
|
|
|
incrementValue,
|
|
|
|
|
});
|
2024-08-17 03:24:09 -04:00
|
|
|
|
|
|
|
|
return {
|
|
|
|
|
rate: transaction.rate,
|
|
|
|
|
user: transaction.user.toString(),
|
2025-03-21 22:48:11 +01:00
|
|
|
balance: balanceResponse.tokenCredits,
|
2024-08-17 03:24:09 -04:00
|
|
|
[transaction.tokenType]: incrementValue,
|
|
|
|
|
};
|
2025-05-30 22:18:13 -04:00
|
|
|
}
|
2024-08-17 03:24:09 -04:00
|
|
|
|
|
|
|
|
/** Method to calculate token value for structured tokens */
|
2025-05-30 22:18:13 -04:00
|
|
|
function calculateStructuredTokenValue(txn) {
|
|
|
|
|
if (!txn.tokenType) {
|
|
|
|
|
txn.tokenValue = txn.rawAmount;
|
2024-08-17 03:24:09 -04:00
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
|
2026-02-06 18:35:36 -05:00
|
|
|
const { model, endpointTokenConfig, inputTokenCount } = txn;
|
2024-08-17 03:24:09 -04:00
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
if (txn.tokenType === 'prompt') {
|
2026-02-06 18:35:36 -05:00
|
|
|
const inputMultiplier = getMultiplier({
|
|
|
|
|
tokenType: 'prompt',
|
|
|
|
|
model,
|
|
|
|
|
endpointTokenConfig,
|
|
|
|
|
inputTokenCount,
|
|
|
|
|
});
|
2024-08-17 03:24:09 -04:00
|
|
|
const writeMultiplier =
|
|
|
|
|
getCacheMultiplier({ cacheType: 'write', model, endpointTokenConfig }) ?? inputMultiplier;
|
|
|
|
|
const readMultiplier =
|
|
|
|
|
getCacheMultiplier({ cacheType: 'read', model, endpointTokenConfig }) ?? inputMultiplier;
|
|
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.rateDetail = {
|
2024-08-17 03:24:09 -04:00
|
|
|
input: inputMultiplier,
|
|
|
|
|
write: writeMultiplier,
|
|
|
|
|
read: readMultiplier,
|
|
|
|
|
};
|
|
|
|
|
|
2024-08-24 04:36:08 -04:00
|
|
|
const totalPromptTokens =
|
2025-05-30 22:18:13 -04:00
|
|
|
Math.abs(txn.inputTokens || 0) +
|
|
|
|
|
Math.abs(txn.writeTokens || 0) +
|
|
|
|
|
Math.abs(txn.readTokens || 0);
|
2024-08-17 03:24:09 -04:00
|
|
|
|
2024-08-24 04:36:08 -04:00
|
|
|
if (totalPromptTokens > 0) {
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.rate =
|
|
|
|
|
(Math.abs(inputMultiplier * (txn.inputTokens || 0)) +
|
|
|
|
|
Math.abs(writeMultiplier * (txn.writeTokens || 0)) +
|
|
|
|
|
Math.abs(readMultiplier * (txn.readTokens || 0))) /
|
2024-08-24 04:36:08 -04:00
|
|
|
totalPromptTokens;
|
2024-08-17 03:24:09 -04:00
|
|
|
} else {
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.rate = Math.abs(inputMultiplier); // Default to input rate if no tokens
|
2024-08-17 03:24:09 -04:00
|
|
|
}
|
|
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.tokenValue = -(
|
|
|
|
|
Math.abs(txn.inputTokens || 0) * inputMultiplier +
|
|
|
|
|
Math.abs(txn.writeTokens || 0) * writeMultiplier +
|
|
|
|
|
Math.abs(txn.readTokens || 0) * readMultiplier
|
2024-08-17 03:24:09 -04:00
|
|
|
);
|
2024-08-24 04:36:08 -04:00
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.rawAmount = -totalPromptTokens;
|
|
|
|
|
} else if (txn.tokenType === 'completion') {
|
2026-02-06 18:35:36 -05:00
|
|
|
const multiplier = getMultiplier({
|
|
|
|
|
tokenType: txn.tokenType,
|
|
|
|
|
model,
|
|
|
|
|
endpointTokenConfig,
|
|
|
|
|
inputTokenCount,
|
|
|
|
|
});
|
2025-05-30 22:18:13 -04:00
|
|
|
txn.rate = Math.abs(multiplier);
|
|
|
|
|
txn.tokenValue = -Math.abs(txn.rawAmount) * multiplier;
|
|
|
|
|
txn.rawAmount = -Math.abs(txn.rawAmount);
|
2024-08-17 03:24:09 -04:00
|
|
|
}
|
|
|
|
|
|
2025-05-30 22:18:13 -04:00
|
|
|
if (txn.context && txn.tokenType === 'completion' && txn.context === 'incomplete') {
|
🧮 refactor: Bulk Transactions & Balance Updates for Token Spending (#11996)
* refactor: transaction handling by integrating pricing and bulk write operations
- Updated `recordCollectedUsage` to accept pricing functions and bulk write operations, improving transaction management.
- Refactored `AgentClient` and related controllers to utilize the new transaction handling capabilities, ensuring better performance and accuracy in token spending.
- Added tests to validate the new functionality, ensuring correct behavior for both standard and bulk transaction paths.
- Introduced a new `transactions.ts` file to encapsulate transaction-related logic and types, enhancing code organization and maintainability.
* chore: reorganize imports in agents client controller
- Moved `getMultiplier` and `getCacheMultiplier` imports to maintain consistency and clarity in the import structure.
- Removed duplicate import of `updateBalance` and `bulkInsertTransactions`, streamlining the code for better readability.
* refactor: add TransactionData type and CANCEL_RATE constant to data-schemas
Establishes a single source of truth for the transaction document shape
and the incomplete-context billing rate constant, both consumed by
packages/api and api/.
* refactor: use proper types in data-schemas transaction methods
- Replace `as unknown as { tokenCredits }` with `lean<IBalance>()`
- Use `TransactionData[]` instead of `Record<string, unknown>[]`
for bulkInsertTransactions parameter
- Add JSDoc noting insertMany bypasses document middleware
- Remove orphan section comment in methods/index.ts
* refactor: use shared types in transactions.ts, fix bulk write logic
- Import CANCEL_RATE from data-schemas instead of local duplicate
- Import TransactionData from data-schemas for PreparedEntry/BulkWriteDeps
- Use tilde alias for EndpointTokenConfig import
- Pass valueKey through to getMultiplier
- Only sum tokenValue for balance-enabled docs in bulkWriteTransactions
- Consolidate two loops into single-pass map
* refactor: remove duplicate updateBalance from Transaction.js
Import updateBalance from ~/models (sourced from data-schemas) instead
of maintaining a second copy. Also import CANCEL_RATE from data-schemas
and remove the Balance model import (no longer needed directly).
* fix: test real spendCollectedUsage instead of IIFE replica
Export spendCollectedUsage from abortMiddleware.js and rewrite the test
file to import and test the actual function. Previously the tests ran
against a hand-written replica that could silently diverge from the real
implementation.
* test: add transactions.spec.ts and restore regression comments
Add 22 direct unit tests for transactions.ts financial logic covering
prepareTokenSpend, prepareStructuredTokenSpend, bulkWriteTransactions,
CANCEL_RATE paths, NaN guards, disabled transactions, zero tokens,
cache multipliers, and balance-enabled filtering.
Restore critical regression documentation comments in
recordCollectedUsage.spec.js explaining which production bugs the
tests guard against.
* fix: widen setValues type to include lastRefill
The UpdateBalanceParams.setValues type was Partial<Pick<IBalance,
'tokenCredits'>> which excluded lastRefill — used by
createAutoRefillTransaction. Widen to also pick 'lastRefill'.
* test: use real MongoDB for bulkWriteTransactions tests
Replace mock-based bulkWriteTransactions tests with real DB tests using
MongoMemoryServer. Pure function tests (prepareTokenSpend,
prepareStructuredTokenSpend) remain mock-based since they don't touch
DB. Add end-to-end integration tests that verify the full prepare →
bulk write → DB state pipeline with real Transaction and Balance models.
* chore: update @librechat/agents dependency to version 3.1.54 in package-lock.json and related package.json files
* test: add bulk path parity tests proving identical DB outcomes
Three test suites proving the bulk path (prepareTokenSpend/
prepareStructuredTokenSpend + bulkWriteTransactions) produces
numerically identical results to the legacy path for all scenarios:
- usage.bulk-parity.spec.ts: mirrors all legacy recordCollectedUsage
tests; asserts same return values and verifies metadata fields on
the insertMany docs match what spendTokens args would carry
- transactions.bulk-parity.spec.ts: real-DB tests using actual
getMultiplier/getCacheMultiplier pricing functions; asserts exact
tokenValue, rate, rawAmount and balance deductions for standard
tokens, structured/cache tokens, CANCEL_RATE, premium pricing,
multi-entry batches, and edge cases (NaN, zero, disabled)
- Transaction.spec.js: adds describe('Bulk path parity') that mirrors
7 key legacy tests via recordCollectedUsage + bulk deps against
real MongoDB, asserting same balance deductions and doc counts
* refactor: update llmConfig structure to use modelKwargs for reasoning effort
Refactor the llmConfig in getOpenAILLMConfig to store reasoning effort within modelKwargs instead of directly on llmConfig. This change ensures consistency in the configuration structure and improves clarity in the handling of reasoning properties in the tests.
* test: update performance checks in processAssistantMessage tests
Revise the performance assertions in the processAssistantMessage tests to ensure that each message processing time remains under 100ms, addressing potential ReDoS vulnerabilities. This change enhances the reliability of the tests by focusing on maximum processing time rather than relative ratios.
* test: fill parity test gaps — model fallback, abort context, structured edge cases
- usage.bulk-parity: add undefined model fallback test
- transactions.bulk-parity: add abort context test (txns inserted,
balance unchanged when balance not passed), fix readTokens type cast
- Transaction.spec: add 3 missing mirrors — balance disabled with
transactions enabled, structured transactions disabled, structured
balance disabled
* fix: deduct balance before inserting transactions to prevent orphaned docs
Swap the order in bulkWriteTransactions: updateBalance runs before
insertMany. If updateBalance fails (after exhausting retries), no
transaction documents are written — avoiding the inconsistent state
where transactions exist in MongoDB with no corresponding balance
deduction.
* chore: import order
* test: update config.spec.ts for OpenRouter reasoning in modelKwargs
Same fix as llm.spec.ts — OpenRouter reasoning is now passed via
modelKwargs instead of llmConfig.reasoning directly.
2026-03-01 12:26:36 -05:00
|
|
|
txn.tokenValue = Math.ceil(txn.tokenValue * CANCEL_RATE);
|
|
|
|
|
txn.rate *= CANCEL_RATE;
|
2025-05-30 22:18:13 -04:00
|
|
|
if (txn.rateDetail) {
|
|
|
|
|
txn.rateDetail = Object.fromEntries(
|
🧮 refactor: Bulk Transactions & Balance Updates for Token Spending (#11996)
* refactor: transaction handling by integrating pricing and bulk write operations
- Updated `recordCollectedUsage` to accept pricing functions and bulk write operations, improving transaction management.
- Refactored `AgentClient` and related controllers to utilize the new transaction handling capabilities, ensuring better performance and accuracy in token spending.
- Added tests to validate the new functionality, ensuring correct behavior for both standard and bulk transaction paths.
- Introduced a new `transactions.ts` file to encapsulate transaction-related logic and types, enhancing code organization and maintainability.
* chore: reorganize imports in agents client controller
- Moved `getMultiplier` and `getCacheMultiplier` imports to maintain consistency and clarity in the import structure.
- Removed duplicate import of `updateBalance` and `bulkInsertTransactions`, streamlining the code for better readability.
* refactor: add TransactionData type and CANCEL_RATE constant to data-schemas
Establishes a single source of truth for the transaction document shape
and the incomplete-context billing rate constant, both consumed by
packages/api and api/.
* refactor: use proper types in data-schemas transaction methods
- Replace `as unknown as { tokenCredits }` with `lean<IBalance>()`
- Use `TransactionData[]` instead of `Record<string, unknown>[]`
for bulkInsertTransactions parameter
- Add JSDoc noting insertMany bypasses document middleware
- Remove orphan section comment in methods/index.ts
* refactor: use shared types in transactions.ts, fix bulk write logic
- Import CANCEL_RATE from data-schemas instead of local duplicate
- Import TransactionData from data-schemas for PreparedEntry/BulkWriteDeps
- Use tilde alias for EndpointTokenConfig import
- Pass valueKey through to getMultiplier
- Only sum tokenValue for balance-enabled docs in bulkWriteTransactions
- Consolidate two loops into single-pass map
* refactor: remove duplicate updateBalance from Transaction.js
Import updateBalance from ~/models (sourced from data-schemas) instead
of maintaining a second copy. Also import CANCEL_RATE from data-schemas
and remove the Balance model import (no longer needed directly).
* fix: test real spendCollectedUsage instead of IIFE replica
Export spendCollectedUsage from abortMiddleware.js and rewrite the test
file to import and test the actual function. Previously the tests ran
against a hand-written replica that could silently diverge from the real
implementation.
* test: add transactions.spec.ts and restore regression comments
Add 22 direct unit tests for transactions.ts financial logic covering
prepareTokenSpend, prepareStructuredTokenSpend, bulkWriteTransactions,
CANCEL_RATE paths, NaN guards, disabled transactions, zero tokens,
cache multipliers, and balance-enabled filtering.
Restore critical regression documentation comments in
recordCollectedUsage.spec.js explaining which production bugs the
tests guard against.
* fix: widen setValues type to include lastRefill
The UpdateBalanceParams.setValues type was Partial<Pick<IBalance,
'tokenCredits'>> which excluded lastRefill — used by
createAutoRefillTransaction. Widen to also pick 'lastRefill'.
* test: use real MongoDB for bulkWriteTransactions tests
Replace mock-based bulkWriteTransactions tests with real DB tests using
MongoMemoryServer. Pure function tests (prepareTokenSpend,
prepareStructuredTokenSpend) remain mock-based since they don't touch
DB. Add end-to-end integration tests that verify the full prepare →
bulk write → DB state pipeline with real Transaction and Balance models.
* chore: update @librechat/agents dependency to version 3.1.54 in package-lock.json and related package.json files
* test: add bulk path parity tests proving identical DB outcomes
Three test suites proving the bulk path (prepareTokenSpend/
prepareStructuredTokenSpend + bulkWriteTransactions) produces
numerically identical results to the legacy path for all scenarios:
- usage.bulk-parity.spec.ts: mirrors all legacy recordCollectedUsage
tests; asserts same return values and verifies metadata fields on
the insertMany docs match what spendTokens args would carry
- transactions.bulk-parity.spec.ts: real-DB tests using actual
getMultiplier/getCacheMultiplier pricing functions; asserts exact
tokenValue, rate, rawAmount and balance deductions for standard
tokens, structured/cache tokens, CANCEL_RATE, premium pricing,
multi-entry batches, and edge cases (NaN, zero, disabled)
- Transaction.spec.js: adds describe('Bulk path parity') that mirrors
7 key legacy tests via recordCollectedUsage + bulk deps against
real MongoDB, asserting same balance deductions and doc counts
* refactor: update llmConfig structure to use modelKwargs for reasoning effort
Refactor the llmConfig in getOpenAILLMConfig to store reasoning effort within modelKwargs instead of directly on llmConfig. This change ensures consistency in the configuration structure and improves clarity in the handling of reasoning properties in the tests.
* test: update performance checks in processAssistantMessage tests
Revise the performance assertions in the processAssistantMessage tests to ensure that each message processing time remains under 100ms, addressing potential ReDoS vulnerabilities. This change enhances the reliability of the tests by focusing on maximum processing time rather than relative ratios.
* test: fill parity test gaps — model fallback, abort context, structured edge cases
- usage.bulk-parity: add undefined model fallback test
- transactions.bulk-parity: add abort context test (txns inserted,
balance unchanged when balance not passed), fix readTokens type cast
- Transaction.spec: add 3 missing mirrors — balance disabled with
transactions enabled, structured transactions disabled, structured
balance disabled
* fix: deduct balance before inserting transactions to prevent orphaned docs
Swap the order in bulkWriteTransactions: updateBalance runs before
insertMany. If updateBalance fails (after exhausting retries), no
transaction documents are written — avoiding the inconsistent state
where transactions exist in MongoDB with no corresponding balance
deduction.
* chore: import order
* test: update config.spec.ts for OpenRouter reasoning in modelKwargs
Same fix as llm.spec.ts — OpenRouter reasoning is now passed via
modelKwargs instead of llmConfig.reasoning directly.
2026-03-01 12:26:36 -05:00
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Object.entries(txn.rateDetail).map(([k, v]) => [k, v * CANCEL_RATE]),
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2024-08-17 03:24:09 -04:00
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);
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}
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}
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2025-05-30 22:18:13 -04:00
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}
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2024-03-15 19:48:42 -04:00
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/**
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* Queries and retrieves transactions based on a given filter.
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* @async
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* @function getTransactions
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* @param {Object} filter - MongoDB filter object to apply when querying transactions.
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* @returns {Promise<Array>} A promise that resolves to an array of matched transactions.
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* @throws {Error} Throws an error if querying the database fails.
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*/
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async function getTransactions(filter) {
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try {
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return await Transaction.find(filter).lean();
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} catch (error) {
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2024-03-29 08:23:38 -04:00
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logger.error('Error querying transactions:', error);
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2024-03-15 19:48:42 -04:00
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throw error;
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}
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}
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2025-05-30 22:18:13 -04:00
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module.exports = {
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getTransactions,
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createTransaction,
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createAutoRefillTransaction,
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createStructuredTransaction,
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};
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