* ♻️ refactor: Compute Context Gauge Client-Side, Drop Projection Endpoint The /api/endpoints/context-projection endpoint re-fetched a conversation's messages from Mongo and re-tokenized them to project the context gauge for snapshot-less branches. The browser already holds those messages and their per-message tokenCounts, so this duplicated work on the request path (an unbounded read + server-side BPE tokenization until it was later capped). Move the snapshot-less estimate fully client-side, from the in-memory index: - sumBranch accumulates an uncalibrated char/4 estimate (estTokens) for count-less messages (imports / pre-feature) under the same summary cutoff - useTokenUsage folds estTokens (calibrated via the existing calibrationFamily ratio) into the existing fallback; known per-message counts render unchanged - delete the endpoint, controller, rate limiter, route, the getMessageTextStats data-schemas method, and the data-provider surface (endpoint/key/type/service/query) No DB read, no server tokenization, no rate-limit knobs; the gauge recomputes reactively from the index. Net -793 lines. * 🩹 fix: Count quotes and object-form content in client context estimate Address Codex review on the client-side context estimate: - messageChars now reads object-form content text (part.text.value), not only string text/think, so imported / pre-feature messages whose body lives in content parts are no longer estimated as zero. - Count-less user messages include their merged quote excerpts in the estimate, mirroring what the send path prepends into the prompt. * 🩹 fix: Cap over-window estimate and surface estimated tokens in breakdown Address remaining Codex review on the client-side context estimate: - Clamp the snapshot-less estimate's displayed usedTokens to maxTokens. The send path prunes an over-window branch before calling the model, so the gauge never actually exceeds the window; this avoids impossible values (e.g. 50k / 8k) without re-introducing client-side pruning. - Surface the calibrated count-less estimate as its own "Estimated" row in the breakdown popover, so a branch of only count-less imported / pre-feature messages is no longer shown as Input 0 / Output 0 under a non-zero header. * 🩹 fix: Refine client context estimate per Codex re-review - Drop calibration from the snapshot-less estimate. The removed projection never actually calibrated (the client never sent a ratio), and a ratio inflated by provider-injected context over-estimates visible imported text. - Exclude reasoning (think) / error parts from the estimate; the send path strips them, so they are not part of the next call's context. - Fold quote text into the estimate even when a tokenCount is present, since the edit route recounts tokenCount from text only and drops the merged quote. * 🩹 fix: Recount quoted user turns instead of topping up the stored count The previous round added quote chars on top of a quoted message's stored tokenCount, which double-counts the common (unedited) case where the count already includes the merged quote prompt. Match the removed projection instead: for quoted user turns, ignore the stored count and estimate the full merged text. This both avoids the double-count and still corrects the stale text-only count an edit leaves behind. * 🩹 fix: Trust stored counts for quoted turns; count tool-call parts - Quoted user turns: revert to trusting a present tokenCount. The send path's stored count already includes the merged quote (and any calibration), and the client's char/4 path is coarser, so recounting regressed normal turns. Only count-less messages estimate quotes from text. - Count tool-call name/args/output for count-less assistant messages; the formatter sends them back as context, so omitting them under-reported imported branches with tool history. * 🩹 fix: Exclude in-flight tail from estimate to avoid resume double-count On resume the live path seeds liveTokens from the partial response and also writes that content into the messages cache, where the count-less response is estimated into estTokens too — double-counting the in-flight output on the snapshot-less estimate path. sumBranch now exposes the tail message's own estimate (tailEstTokens); the estimate path drops it while a stream is live, so the in-flight response is counted once (via liveTokens). The breakdown's Estimated row uses the same in-flight-adjusted value. * 🩹 fix: Recount quoted user turns in context estimate (match send path) A quoted user turn's stored tokenCount is unreliable for the gauge: a text-only Save edit recomputes it from text alone, and the send path (needsCanonicalTokenCount in agents/client.js) recounts the quote-merged prompt every turn regardless of the stored value. Mirror that on the client — estimate quoted turns from the merged text+quotes and ignore the stored count — so snapshot-less branches don't under-report by the quote block. Reverts the earlier "trust the count" assumption, which the server disproves. * 🧹 chore: Route useResumableSSE diagnostics through the frontend logger Convert the [ResumableSSE]/[Debug] console.log and console.error diagnostics to the gated frontend `logger` (client/src/utils/logger), splitting the tag from the message so object arguments are passed through as real args (logged expandably, not stringified) and the logs stay tag-filterable and off the production console unless explicitly enabled. All log statements preserved; nothing removed. * 🩹 fix: Prefer content over text when estimating count-less messages A stopped agent response is saved with both a `text` field and a structured `content` array, and the send path formats from content. messageChars early-returned on `text`, dropping the content array (and the tool-call tokens it carries) from the snapshot-less estimate — also making the tool_call handling dead for such messages. Prefer content when present, fall back to text. |
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| src | ||
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| jest.config.mjs | ||
| LICENSE | ||
| package.json | ||
| README.md | ||
| tsconfig.build.json | ||
| tsconfig.json | ||
| tsconfig.spec.json | ||
| tsdown.config.mjs | ||
LibreChat Data Schemas Package
This package provides the database schemas, models, types, and methods for LibreChat using Mongoose ODM.
📁 Package Structure
packages/data-schemas/
├── src/
│ ├── schema/ # Mongoose schema definitions
│ ├── models/ # Model factory functions
│ ├── types/ # TypeScript type definitions
│ ├── methods/ # Database operation methods
│ ├── common/ # Shared constants and enums
│ ├── config/ # Configuration files (winston, etc.)
│ └── index.ts # Main package exports
🏗️ Architecture Patterns
1. Schema Files (src/schema/)
Schema files define the Mongoose schema structure. They follow these conventions:
- Naming: Use lowercase filenames (e.g.,
user.ts,accessRole.ts) - Imports: Import types from
~/typesfor TypeScript support - Exports: Export only the schema as default
Example:
import { Schema } from 'mongoose';
import type { IUser } from '~/types';
const userSchema = new Schema<IUser>(
{
name: { type: String },
email: { type: String, required: true },
// ... other fields
},
{ timestamps: true }
);
export default userSchema;
2. Type Definitions (src/types/)
Type files define TypeScript interfaces and types. They follow these conventions:
- Base Type: Define a plain type without Mongoose Document properties
- Document Interface: Extend the base type with Document and
_id - Enums/Constants: Place related enums in the type file or
common/if shared
Example:
import type { Document, Types } from 'mongoose';
export type User = {
name?: string;
email: string;
// ... other fields
};
export type IUser = User &
Document & {
_id: Types.ObjectId;
};
3. Model Factory Functions (src/models/)
Model files create Mongoose models using factory functions. They follow these conventions:
- Function Name:
create[EntityName]Model - Singleton Pattern: Check if model exists before creating
- Type Safety: Use the corresponding interface from types
Example:
import userSchema from '~/schema/user';
import type * as t from '~/types';
export function createUserModel(mongoose: typeof import('mongoose')) {
return mongoose.models.User || mongoose.model<t.IUser>('User', userSchema);
}
4. Database Methods (src/methods/)
Method files contain database operations for each entity. They follow these conventions:
- Function Name:
create[EntityName]Methods - Return Type: Export a type for the methods object
- Operations: Include CRUD operations and entity-specific queries
Example:
import type { Model } from 'mongoose';
import type { IUser } from '~/types';
export function createUserMethods(mongoose: typeof import('mongoose')) {
async function findUserById(userId: string): Promise<IUser | null> {
const User = mongoose.models.User as Model<IUser>;
return await User.findById(userId).lean();
}
async function createUser(userData: Partial<IUser>): Promise<IUser> {
const User = mongoose.models.User as Model<IUser>;
return await User.create(userData);
}
return {
findUserById,
createUser,
// ... other methods
};
}
export type UserMethods = ReturnType<typeof createUserMethods>;
5. Main Exports (src/index.ts)
The main index file exports:
createModels()- Factory function for all modelscreateMethods()- Factory function for all methods- Type exports from
~/types - Shared utilities and constants
🚀 Adding a New Entity
To add a new entity to the data-schemas package, follow these steps:
Step 1: Create the Type Definition
Create src/types/[entityName].ts:
import type { Document, Types } from 'mongoose';
export type EntityName = {
/** Field description */
fieldName: string;
// ... other fields
};
export type IEntityName = EntityName &
Document & {
_id: Types.ObjectId;
};
Step 2: Update Types Index
Add to src/types/index.ts:
export * from './entityName';
Step 3: Create the Schema
Create src/schema/[entityName].ts:
import { Schema } from 'mongoose';
import type { IEntityName } from '~/types';
const entityNameSchema = new Schema<IEntityName>(
{
fieldName: { type: String, required: true },
// ... other fields
},
{ timestamps: true }
);
export default entityNameSchema;
Step 4: Create the Model Factory
Create src/models/[entityName].ts:
import entityNameSchema from '~/schema/entityName';
import type * as t from '~/types';
export function createEntityNameModel(mongoose: typeof import('mongoose')) {
return (
mongoose.models.EntityName ||
mongoose.model<t.IEntityName>('EntityName', entityNameSchema)
);
}
Step 5: Update Models Index
Add to src/models/index.ts:
- Import the factory function:
import { createEntityNameModel } from './entityName';
- Add to the return object in
createModels():
EntityName: createEntityNameModel(mongoose),
Step 6: Create Database Methods
Create src/methods/[entityName].ts:
import type { Model, Types } from 'mongoose';
import type { IEntityName } from '~/types';
export function createEntityNameMethods(mongoose: typeof import('mongoose')) {
async function findEntityById(id: string | Types.ObjectId): Promise<IEntityName | null> {
const EntityName = mongoose.models.EntityName as Model<IEntityName>;
return await EntityName.findById(id).lean();
}
// ... other methods
return {
findEntityById,
// ... other methods
};
}
export type EntityNameMethods = ReturnType<typeof createEntityNameMethods>;
Step 7: Update Methods Index
Add to src/methods/index.ts:
- Import the methods:
import { createEntityNameMethods, type EntityNameMethods } from './entityName';
- Add to the return object in
createMethods():
...createEntityNameMethods(mongoose),
- Add to the
AllMethodstype:
export type AllMethods = UserMethods &
// ... other methods
EntityNameMethods;
📝 Best Practices
- Consistent Naming: Use lowercase for filenames, PascalCase for types/interfaces
- Type Safety: Always use TypeScript types, avoid
any - JSDoc Comments: Document complex fields and methods
- Indexes: Define database indexes in schema files for query performance
- Validation: Use Mongoose schema validation for data integrity
- Lean Queries: Use
.lean()for read operations when you don't need Mongoose document methods
🔧 Common Patterns
Enums and Constants
Place shared enums in src/common/:
// src/common/permissions.ts
export enum PermissionBits {
VIEW = 1,
EDIT = 2,
DELETE = 4,
SHARE = 8,
}
Compound Indexes
For complex queries, add compound indexes:
schema.index({ field1: 1, field2: 1 });
schema.index(
{ uniqueField: 1 },
{
unique: true,
partialFilterExpression: { uniqueField: { $exists: true } }
}
);
Virtual Properties
Add computed properties using virtuals:
schema.virtual('fullName').get(function() {
return `${this.firstName} ${this.lastName}`;
});
🧪 Testing
When adding new entities, ensure:
- Types compile without errors
- Models can be created successfully
- Methods handle edge cases (null checks, validation)
- Indexes are properly defined for query patterns