AI Feedback (lexigram-ai-feedback)

AI feedback collection for the Lexigram Framework — collection, processing, and storage

Overview

AI feedback collection and continuous-learning loop for the Lexigram Framework. Captures user ratings, corrections, text feedback, and ground-truth labels from LLM interactions and routes them through an extensible processor pipeline to configurable storage backends. Zero-config usage starts with sensible defaults.

Install

uv add lexigram-ai-feedback

Quick Start

from lexigram import Application
from lexigram.di.module import Module, module

from lexigram.ai.feedback import FeedbackModule
from lexigram.ai.feedback.config import FeedbackConfig

@module(imports=[
    FeedbackModule.configure(
        FeedbackConfig(
            enabled=True,
            async_processing=True,
            store_raw_payloads=False,
        )
    )
])
class AppModule(Module):
    pass

app = Application(modules=[AppModule])
if __name__ == "__main__":
    app.run()

Configuration

Zero-config usage: Call FeedbackModule.configure() with no arguments to use defaults.

Option 1 — YAML file

ai_feedback:
  enabled: true
  async_processing: true
  store_raw_payloads: false

Option 2 — Profiles + Environment Variables (recommended)

export LEX_AI_FEEDBACK__ENABLED=true
# Environment variables for each field

Option 3 — Python

from lexigram.ai.feedback.config import FeedbackConfig
from lexigram.ai.feedback import FeedbackModule

config = FeedbackConfig(
    enabled=True,
    async_processing=True,
    store_raw_payloads=False,
)
FeedbackModule.configure(config)

Config reference

Field	Default	Env var	Description
`enabled`	`True`	`LEX_AI_FEEDBACK__ENABLED`	Master on/off switch for all feedback collection
`async_processing`	`True`	`LEX_AI_FEEDBACK__ASYNC_PROCESSING`	Process feedback handlers asynchronously in the background
`store_raw_payloads`	`False`	`LEX_AI_FEEDBACK__STORE_RAW_PAYLOADS`	Persist raw incoming feedback payloads for auditing

Module Factory Methods

Method	Description
`FeedbackModule.configure(config)`	Configure with explicit config
`FeedbackModule.stub()`	Minimal config for testing

Key Features

Four feedback types: Rating, free-text, correction (original → corrected), and ground-truth labels
Extensible processor pipeline: Custom processors via FeedbackProcessorRegistry
Storage backends: In-memory, database (DatabaseFeedbackStore), and cache (CachedFeedbackStore)
Middleware integration: FeedbackMiddleware and FeedbackContext for request/response capture
Lifecycle hooks: FeedbackSubmittedHook, FeedbackProcessedHook, FeedbackStoredHook

Testing

async with Application.boot(modules=[FeedbackModule.stub()]) as app:
    # your test code
    ...

Key Source Files

File	What it contains
`src/lexigram/ai/feedback/module.py`	`FeedbackModule.configure()`, `.stub()`
`src/lexigram/ai/feedback/config.py`	`FeedbackConfig`
`src/lexigram/ai/feedback/services/collector.py`	`FeedbackCollector` core service
`src/lexigram/ai/feedback/storage/database.py`	`DatabaseFeedbackStore`
`src/lexigram/ai/feedback/storage/cache.py`	`CachedFeedbackStore`
`src/lexigram/ai/feedback/processors/processor_registry.py`	`FeedbackProcessorRegistry`
`src/lexigram/ai/feedback/di/provider.py`	`FeedbackProvider` boot and registration