AI Feedback (oridecon-ai-feedback)

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

---

Overview

AI feedback collection and continuous-learning loop for the Oridecon 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.

Full documentation: oridecon.dev

Install

uv add oridecon-ai-feedback

Quick Start

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

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


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


async with Application.boot(modules=[AppModule]) as app:
    # use app.container to resolve services
    ...

Configuration

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

Option 1 — YAML file

application.yaml

ai_feedback:
  enabled: true
  async_processing: true
  store_raw_payloads: false

Option 2 — Profiles + Environment Variables (recommended)

export ORI_AI_FEEDBACK__ENABLED=true
# Environment variables for each field

Option 3 — Python

from oridecon.ai.feedback.config import FeedbackConfig
from oridecon.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	ORI_AI_FEEDBACK__ENABLED	Master on/off switch for all feedback collection
async_processing	True	ORI_AI_FEEDBACK__ASYNC_PROCESSING	Process feedback handlers asynchronously in the background
store_raw_payloads	False	ORI_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

Security

Enforced payload size limits

Submitted feedback is validated at the submission chokepoints (FeedbackCollector._store() for the middleware/processor pipeline and the collect_* API; FeedbackService.submit_feedback() for the programmatic service). Oversized payloads are rejected with FeedbackTooLargeError (never silently truncated); boundary values (exactly at the limit) pass.

Limit	Constant	Applied to
10,000 characters	MAX_FEEDBACK_TEXT_LENGTH	TEXT feedback values and submit_feedback(comment=...)
50,000 characters (serialized JSON)	MAX_CONTEXT_SIZE	context and metadata dicts

Optional endpoint authorization

create_feedback_endpoint() performs no identity check by default — an endpoint mounted without an authorize callback accepts feedback from anyone who can reach it; that is an explicit, informed choice, not an enforced control. Pass an authorization callback to gate submissions:

from oridecon.ai.feedback import FeedbackCollector, FeedbackMiddleware


def authorize(ctx) -> bool:
    # ctx.context_id is the context being submitted against;
    # ctx.metadata carries what the host framework supplied (e.g. user)
    return ctx.metadata.get("user_id") is not None


middleware = FeedbackMiddleware(
    collector=FeedbackCollector(),
    authorize=authorize,
)
app.post("/feedback", middleware.create_feedback_endpoint())

Sync and async (bool | Awaitable[bool]) callables are supported. A denied submission raises FeedbackAuthorizationError before any processing.

Testing

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

Key Source Files

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