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This commit is contained in:
Igor Loskutov
2025-12-10 13:59:46 -05:00
parent b340f3c74e 18a27f7b45
commit 406a7529ee
16 changed files with 698 additions and 195 deletions
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90
.github/workflows/deploy.yml vendored
View File

@@ -1,90 +0,0 @@
name: Build container/push to container registry
on: [workflow_dispatch]
env:
# 950402358378.dkr.ecr.us-east-1.amazonaws.com/reflector
AWS_REGION: us-east-1
ECR_REPOSITORY: reflector
jobs:
build:
strategy:
matrix:
include:
- platform: linux/amd64
runner: linux-amd64
arch: amd64
- platform: linux/arm64
runner: linux-arm64
arch: arm64
runs-on: ${{ matrix.runner }}
permissions:
contents: read
outputs:
registry: ${{ steps.login-ecr.outputs.registry }}
steps:
- uses: actions/checkout@v4
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ env.AWS_REGION }}
- name: Login to Amazon ECR
id: login-ecr
uses: aws-actions/amazon-ecr-login@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Build and push ${{ matrix.arch }}
uses: docker/build-push-action@v5
with:
context: server
platforms: ${{ matrix.platform }}
push: true
tags: ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:latest-${{ matrix.arch }}
cache-from: type=gha,scope=${{ matrix.arch }}
cache-to: type=gha,mode=max,scope=${{ matrix.arch }}
github-token: ${{ secrets.GHA_CACHE_TOKEN }}
provenance: false
create-manifest:
runs-on: ubuntu-latest
needs: [build]
permissions:
deployments: write
contents: read
steps:
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: ${{ env.AWS_REGION }}
- name: Login to Amazon ECR
uses: aws-actions/amazon-ecr-login@v2
- name: Create and push multi-arch manifest
run: |
# Get the registry URL (since we can't easily access job outputs in matrix)
ECR_REGISTRY=$(aws ecr describe-registry --query 'registryId' --output text).dkr.ecr.${{ env.AWS_REGION }}.amazonaws.com
docker manifest create \
$ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest \
$ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest-amd64 \
$ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest-arm64
docker manifest push $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest
echo "✅ Multi-arch manifest pushed: $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest"

17
.github/workflows/dockerhub-backend.yml vendored
View File

@@ -1,13 +1,12 @@
name: Build and Push Backend Docker Image (Docker Hub)
on:
push:
branches:
- main
- dockerhub-2
pull_request:
types:
- closed
paths:
- 'server/**'
- '.github/workflows/dockerhub-backend.yml'
- "server/**"
- ".github/workflows/dockerhub-backend.yml"
workflow_dispatch:
env:
@@ -17,6 +16,10 @@ env:
jobs:
build-and-push:
runs-on: ubuntu-latest
if: |
github.event_name == 'workflow_dispatch' ||
(github.event.pull_request.merged == true &&
startsWith(github.event.pull_request.head.ref, 'release-please--branches--'))
permissions:
contents: read
@@ -39,7 +42,7 @@ jobs:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=branch
type=sha,prefix={{branch}}-
type=ref,event=tag
type=raw,value=latest,enable={{is_default_branch}}
- name: Set up Docker Buildx

36
.github/workflows/dockerhub-frontend.yml vendored
View File

@@ -1,13 +1,12 @@
name: Build and Push Frontend Docker Image
on:
push:
branches:
- main
- dockerhub-2
pull_request:
types:
- closed
paths:
- 'www/**'
- '.github/workflows/dockerhub-frontend.yml'
- "www/**"
- ".github/workflows/dockerhub-frontend.yml"
workflow_dispatch:
env:
@@ -17,6 +16,10 @@ env:
jobs:
build-and-push:
runs-on: ubuntu-latest
if: |
github.event_name == 'workflow_dispatch' ||
(github.event.pull_request.merged == true &&
startsWith(github.event.pull_request.head.ref, 'release-please--branches--'))
permissions:
contents: read
@@ -39,8 +42,9 @@ jobs:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=branch
type=sha,prefix={{branch}}-
type=ref,event=tag
type=raw,value=latest,enable={{is_default_branch}}
github-token: ${{ secrets.GITHUB_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -55,4 +59,20 @@ jobs:
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
platforms: linux/amd64,linux/arm64
platforms: linux/amd64,linux/arm64
deploy:
needs: build-and-push
runs-on: ubuntu-latest
if: success()
strategy:
matrix:
environment: [reflector-monadical, reflector-media]
environment: ${{ matrix.environment }}
steps:
- name: Trigger Coolify deployment
run: |
curl -X POST "${{ secrets.COOLIFY_WEBHOOK_URL }}" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${{ secrets.COOLIFY_WEBHOOK_TOKEN }}" \
-f || (echo "Failed to trigger Coolify deployment for ${{ matrix.environment }}" && exit 1)

1
.gitignore vendored
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@@ -20,3 +20,4 @@ www/.env.development
www/.env.production
.playwright-mcp
docs/pnpm-lock.yaml
.secrets

24
.secrets.example Normal file
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@@ -0,0 +1,24 @@
# Example secrets file for GitHub Actions workflows
# Copy this to .secrets and fill in your values
# These secrets should be configured in GitHub repository settings:
# Settings > Secrets and variables > Actions
# DockerHub Configuration (required for frontend and backend deployment)
# Create a Docker Hub access token at https://hub.docker.com/settings/security
# Username: monadicalsas
DOCKERHUB_TOKEN=your-dockerhub-access-token
# GitHub Token (required for frontend and backend deployment)
# Used by docker/metadata-action for extracting image metadata
# Can use the default GITHUB_TOKEN or create a personal access token
GITHUB_TOKEN=your-github-token-or-use-default-GITHUB_TOKEN
# Coolify Deployment Webhook (required for frontend deployment)
# Used to trigger automatic deployment after image push
# Configure these secrets in GitHub Environments:
# Each environment should have:
# - COOLIFY_WEBHOOK_URL: The webhook URL for that specific deployment
# - COOLIFY_WEBHOOK_TOKEN: The webhook token (can be the same for both if using same token)
# Optional: GitHub Actions Cache Token (for local testing with act)
GHA_CACHE_TOKEN=your-github-token-or-empty

16
CHANGELOG.md
View File

@@ -1,5 +1,21 @@
# Changelog
## [0.23.0](https://github.com/Monadical-SAS/reflector/compare/v0.22.4...v0.23.0) (2025-12-10)
### Features
* dockerhub ci ([#772](https://github.com/Monadical-SAS/reflector/issues/772)) ([00549f1](https://github.com/Monadical-SAS/reflector/commit/00549f153ade922cf4cb6c5358a7d11a39c426d2))
* llm retries ([#739](https://github.com/Monadical-SAS/reflector/issues/739)) ([61f0e29](https://github.com/Monadical-SAS/reflector/commit/61f0e29d4c51eab54ee67af92141fbb171e8ccaa))
### Bug Fixes
* celery inspect bug sidestep in restart script ([#766](https://github.com/Monadical-SAS/reflector/issues/766)) ([ec17ed7](https://github.com/Monadical-SAS/reflector/commit/ec17ed7b587cf6ee143646baaee67a7c017044d4))
* deploy frontend to coolify ([#779](https://github.com/Monadical-SAS/reflector/issues/779)) ([91650ec](https://github.com/Monadical-SAS/reflector/commit/91650ec65f65713faa7ee0dcfb75af427b7c4ba0))
* hide rooms settings instead of disabling ([#763](https://github.com/Monadical-SAS/reflector/issues/763)) ([3ad78be](https://github.com/Monadical-SAS/reflector/commit/3ad78be7628c0d029296b301a0e87236c76b7598))
* return participant emails from transcript endpoint ([#769](https://github.com/Monadical-SAS/reflector/issues/769)) ([d3a5cd1](https://github.com/Monadical-SAS/reflector/commit/d3a5cd12d2d0d9c32af2d5bd9322e030ef69b85d))
## [0.22.4](https://github.com/Monadical-SAS/reflector/compare/v0.22.3...v0.22.4) (2025-12-02)

1
server/pyproject.toml
View File

@@ -126,6 +126,7 @@ markers = [
select = [
"I", # isort - import sorting
"F401", # unused imports
"E402", # module level import not at top of file
"PLC0415", # import-outside-top-level - detect inline imports
]

6
server/reflector/asynctask.py
View File

@@ -1,13 +1,19 @@
import asyncio
import functools
from uuid import uuid4
from celery import current_task
from reflector.db import get_database
from reflector.llm import llm_session_id
def asynctask(f):
@functools.wraps(f)
def wrapper(*args, **kwargs):
async def run_with_db():
task_id = current_task.request.id if current_task else None
llm_session_id.set(task_id or f"random-{uuid4().hex}")
database = get_database()
await database.connect()
try:

225
server/reflector/llm.py
View File

@@ -1,14 +1,29 @@
import logging
from typing import Type, TypeVar
from contextvars import ContextVar
from typing import Generic, Type, TypeVar
from uuid import uuid4
from llama_index.core import Settings
from llama_index.core.output_parsers import PydanticOutputParser
from llama_index.core.program import LLMTextCompletionProgram
from llama_index.core.response_synthesizers import TreeSummarize
from llama_index.core.workflow import (
Context,
Event,
StartEvent,
StopEvent,
Workflow,
step,
)
from llama_index.llms.openai_like import OpenAILike
from pydantic import BaseModel, ValidationError
T = TypeVar("T", bound=BaseModel)
OutputT = TypeVar("OutputT", bound=BaseModel)
# Session ID for LiteLLM request grouping - set per processing run
llm_session_id: ContextVar[str | None] = ContextVar("llm_session_id", default=None)
logger = logging.getLogger(__name__)
STRUCTURED_RESPONSE_PROMPT_TEMPLATE = """
Based on the following analysis, provide the information in the requested JSON format:
@@ -20,6 +35,158 @@ Analysis:
"""
class LLMParseError(Exception):
"""Raised when LLM output cannot be parsed after retries."""
def __init__(self, output_cls: Type[BaseModel], error_msg: str, attempts: int):
self.output_cls = output_cls
self.error_msg = error_msg
self.attempts = attempts
super().__init__(
f"Failed to parse {output_cls.__name__} after {attempts} attempts: {error_msg}"
)
class ExtractionDone(Event):
"""Event emitted when LLM JSON formatting completes."""
output: str
class ValidationErrorEvent(Event):
"""Event emitted when validation fails."""
error: str
wrong_output: str
class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
"""Workflow for structured output extraction with validation retry.
This workflow handles parse/validation retries only. Network error retries
are handled internally by Settings.llm (OpenAILike max_retries=3).
The caller should NOT wrap this workflow in additional retry logic.
"""
def __init__(
self,
output_cls: Type[OutputT],
max_retries: int = 3,
**kwargs,
):
super().__init__(**kwargs)
self.output_cls: Type[OutputT] = output_cls
self.max_retries = max_retries
self.output_parser = PydanticOutputParser(output_cls)
@step
async def extract(
self, ctx: Context, ev: StartEvent | ValidationErrorEvent
) -> StopEvent | ExtractionDone:
"""Extract structured data from text using two-step LLM process.
Step 1 (first call only): TreeSummarize generates text analysis
Step 2 (every call): Settings.llm.acomplete formats analysis as JSON
"""
current_retries = await ctx.store.get("retries", default=0)
await ctx.store.set("retries", current_retries + 1)
if current_retries >= self.max_retries:
last_error = await ctx.store.get("last_error", default=None)
logger.error(
f"Max retries ({self.max_retries}) reached for {self.output_cls.__name__}"
)
return StopEvent(result={"error": last_error, "attempts": current_retries})
if isinstance(ev, StartEvent):
# First call: run TreeSummarize to get analysis, store in context
prompt = ev.get("prompt")
texts = ev.get("texts")
tone_name = ev.get("tone_name")
if not prompt or not isinstance(texts, list):
raise ValueError(
"StartEvent must contain 'prompt' (str) and 'texts' (list)"
)
summarizer = TreeSummarize(verbose=False)
analysis = await summarizer.aget_response(
prompt, texts, tone_name=tone_name
)
await ctx.store.set("analysis", str(analysis))
reflection = ""
else:
# Retry: reuse analysis from context
analysis = await ctx.store.get("analysis")
if not analysis:
raise RuntimeError("Internal error: analysis not found in context")
wrong_output = ev.wrong_output
if len(wrong_output) > 2000:
wrong_output = wrong_output[:2000] + "... [truncated]"
reflection = (
f"\n\nYour previous response could not be parsed:\n{wrong_output}\n\n"
f"Error:\n{ev.error}\n\n"
"Please try again. Return ONLY valid JSON matching the schema above, "
"with no markdown formatting or extra text."
)
# Step 2: Format analysis as JSON using LLM completion
format_instructions = self.output_parser.format(
"Please structure the above information in the following JSON format:"
)
json_prompt = STRUCTURED_RESPONSE_PROMPT_TEMPLATE.format(
analysis=analysis,
format_instructions=format_instructions + reflection,
)
# Network retries handled by OpenAILike (max_retries=3)
response = await Settings.llm.acomplete(json_prompt)
return ExtractionDone(output=response.text)
@step
async def validate(
self, ctx: Context, ev: ExtractionDone
) -> StopEvent | ValidationErrorEvent:
"""Validate extracted output against Pydantic schema."""
raw_output = ev.output
retries = await ctx.store.get("retries", default=0)
try:
parsed = self.output_parser.parse(raw_output)
if retries > 1:
logger.info(
f"LLM parse succeeded on attempt {retries}/{self.max_retries} "
f"for {self.output_cls.__name__}"
)
return StopEvent(result={"success": parsed})
except (ValidationError, ValueError) as e:
error_msg = self._format_error(e, raw_output)
await ctx.store.set("last_error", error_msg)
logger.error(
f"LLM parse error (attempt {retries}/{self.max_retries}): "
f"{type(e).__name__}: {e}\nRaw response: {raw_output[:500]}"
)
return ValidationErrorEvent(
error=error_msg,
wrong_output=raw_output,
)
def _format_error(self, error: Exception, raw_output: str) -> str:
"""Format error for LLM feedback."""
if isinstance(error, ValidationError):
error_messages = []
for err in error.errors():
field = ".".join(str(loc) for loc in err["loc"])
error_messages.append(f"- {err['msg']} in field '{field}'")
return "Schema validation errors:\n" + "\n".join(error_messages)
else:
return f"Parse error: {str(error)}"
class LLM:
def __init__(self, settings, temperature: float = 0.4, max_tokens: int = 2048):
self.settings_obj = settings
@@ -30,11 +197,12 @@ class LLM:
self.temperature = temperature
self.max_tokens = max_tokens
# Configure llamaindex Settings
self._configure_llamaindex()
def _configure_llamaindex(self):
"""Configure llamaindex Settings with OpenAILike LLM"""
session_id = llm_session_id.get() or f"fallback-{uuid4().hex}"
Settings.llm = OpenAILike(
model=self.model_name,
api_base=self.url,
@@ -44,6 +212,7 @@ class LLM:
is_function_calling_model=False,
temperature=self.temperature,
max_tokens=self.max_tokens,
additional_kwargs={"extra_body": {"litellm_session_id": session_id}},
)
async def get_response(
@@ -61,43 +230,25 @@ class LLM:
output_cls: Type[T],
tone_name: str | None = None,
) -> T:
"""Get structured output from LLM for non-function-calling models"""
logger = logging.getLogger(__name__)
summarizer = TreeSummarize(verbose=True)
response = await summarizer.aget_response(prompt, texts, tone_name=tone_name)
output_parser = PydanticOutputParser(output_cls)
program = LLMTextCompletionProgram.from_defaults(
output_parser=output_parser,
prompt_template_str=STRUCTURED_RESPONSE_PROMPT_TEMPLATE,
verbose=False,
"""Get structured output from LLM with validation retry via Workflow."""
workflow = StructuredOutputWorkflow(
output_cls=output_cls,
max_retries=self.settings_obj.LLM_PARSE_MAX_RETRIES + 1,
timeout=120,
)
format_instructions = output_parser.format(
"Please structure the above information in the following JSON format:"
result = await workflow.run(
prompt=prompt,
texts=texts,
tone_name=tone_name,
)
try:
output = await program.acall(
analysis=str(response), format_instructions=format_instructions
if "error" in result:
error_msg = result["error"] or "Max retries exceeded"
raise LLMParseError(
output_cls=output_cls,
error_msg=error_msg,
attempts=result.get("attempts", 0),
)
except ValidationError as e:
# Extract the raw JSON from the error details
errors = e.errors()
if errors and "input" in errors[0]:
raw_json = errors[0]["input"]
logger.error(
f"JSON validation failed for {output_cls.__name__}. "
f"Full raw JSON output:\n{raw_json}\n"
f"Validation errors: {errors}"
)
else:
logger.error(
f"JSON validation failed for {output_cls.__name__}. "
f"Validation errors: {errors}"
)
raise
return output
return result["success"]

1
server/reflector/pipelines/main_file_pipeline.py
View File

@@ -340,7 +340,6 @@ async def task_send_webhook_if_needed(*, transcript_id: str):
@asynctask
async def task_pipeline_file_process(*, transcript_id: str):
"""Celery task for file pipeline processing"""
transcript = await transcripts_controller.get_by_id(transcript_id)
if not transcript:
raise Exception(f"Transcript {transcript_id} not found")

5
server/reflector/services/transcript_process.py
View File

@@ -160,7 +160,10 @@ def dispatch_transcript_processing(config: ProcessingConfig) -> AsyncResult:
def task_is_scheduled_or_active(task_name: str, **kwargs):
inspect = celery.current_app.control.inspect()
for worker, tasks in (inspect.scheduled() | inspect.active()).items():
scheduled = inspect.scheduled() or {}
active = inspect.active() or {}
all = scheduled | active
for worker, tasks in all.items():
for task in tasks:
if task["name"] == task_name and task["kwargs"] == kwargs:
return True

4
server/reflector/settings.py
View File

@@ -76,6 +76,10 @@ class Settings(BaseSettings):
LLM_API_KEY: str | None = None
LLM_CONTEXT_WINDOW: int = 16000
LLM_PARSE_MAX_RETRIES: int = (
3 # Max retries for JSON/validation errors (total attempts = retries + 1)
)
# Diarization
# backends:
# - pyannote: in-process model loading (no HTTP, runs in same process)

8
server/tests/conftest.py
View File

@@ -318,6 +318,14 @@ async def dummy_storage():
yield
@pytest.fixture
def test_settings():
"""Provide isolated settings for tests to avoid modifying global settings"""
from reflector.settings import Settings
return Settings()
@pytest.fixture(scope="session")
def celery_enable_logging():
return True

357
server/tests/test_llm_retry.py Normal file
View File

@@ -0,0 +1,357 @@
"""Tests for LLM parse error recovery using llama-index Workflow"""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from pydantic import BaseModel, Field
from workflows.errors import WorkflowRuntimeError
from reflector.llm import LLM, LLMParseError, StructuredOutputWorkflow
class TestResponse(BaseModel):
"""Test response model for structured output"""
title: str = Field(description="A title")
summary: str = Field(description="A summary")
confidence: float = Field(description="Confidence score", ge=0, le=1)
def make_completion_response(text: str):
"""Create a mock CompletionResponse with .text attribute"""
response = MagicMock()
response.text = text
return response
class TestLLMParseErrorRecovery:
"""Test parse error recovery with Workflow feedback loop"""
@pytest.mark.asyncio
async def test_parse_error_recovery_with_feedback(self, test_settings):
"""Test that parse errors trigger retry with error feedback"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
# TreeSummarize returns plain text analysis (step 1)
mock_summarizer.aget_response = AsyncMock(
return_value="The analysis shows a test with summary and high confidence."
)
call_count = {"count": 0}
async def acomplete_handler(prompt, *args, **kwargs):
call_count["count"] += 1
if call_count["count"] == 1:
# First JSON formatting call returns invalid JSON
return make_completion_response('{"title": "Test"}')
else:
# Second call should have error feedback in prompt
assert "Your previous response could not be parsed:" in prompt
assert '{"title": "Test"}' in prompt
assert "Error:" in prompt
assert "Please try again" in prompt
return make_completion_response(
'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
)
mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
result = await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
assert result.title == "Test"
assert result.summary == "Summary"
assert result.confidence == 0.95
# TreeSummarize called once, Settings.llm.acomplete called twice
assert mock_summarizer.aget_response.call_count == 1
assert call_count["count"] == 2
@pytest.mark.asyncio
async def test_max_parse_retry_attempts(self, test_settings):
"""Test that parse error retry stops after max attempts"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
# Always return invalid JSON from acomplete
mock_settings.llm.acomplete = AsyncMock(
return_value=make_completion_response(
'{"invalid": "missing required fields"}'
)
)
with pytest.raises(LLMParseError, match="Failed to parse"):
await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
expected_attempts = test_settings.LLM_PARSE_MAX_RETRIES + 1
# TreeSummarize called once, acomplete called max_retries times
assert mock_summarizer.aget_response.call_count == 1
assert mock_settings.llm.acomplete.call_count == expected_attempts
@pytest.mark.asyncio
async def test_raw_response_logging_on_parse_error(self, test_settings, caplog):
"""Test that raw response is logged when parse error occurs"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
caplog.at_level("ERROR"),
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
call_count = {"count": 0}
async def acomplete_handler(*args, **kwargs):
call_count["count"] += 1
if call_count["count"] == 1:
return make_completion_response('{"title": "Test"}') # Invalid
return make_completion_response(
'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
)
mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
result = await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
assert result.title == "Test"
error_logs = [r for r in caplog.records if r.levelname == "ERROR"]
raw_response_logged = any("Raw response:" in r.message for r in error_logs)
assert raw_response_logged, "Raw response should be logged on parse error"
@pytest.mark.asyncio
async def test_multiple_validation_errors_in_feedback(self, test_settings):
"""Test that validation errors are included in feedback"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
call_count = {"count": 0}
async def acomplete_handler(prompt, *args, **kwargs):
call_count["count"] += 1
if call_count["count"] == 1:
# Missing title and summary
return make_completion_response('{"confidence": 0.5}')
else:
# Should have schema validation errors in prompt
assert (
"Schema validation errors" in prompt
or "error" in prompt.lower()
)
return make_completion_response(
'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
)
mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
result = await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
assert result.title == "Test"
assert call_count["count"] == 2
@pytest.mark.asyncio
async def test_success_on_first_attempt(self, test_settings):
"""Test that no retry happens when first attempt succeeds"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
mock_settings.llm.acomplete = AsyncMock(
return_value=make_completion_response(
'{"title": "Test", "summary": "Summary", "confidence": 0.95}'
)
)
result = await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
assert result.title == "Test"
assert result.summary == "Summary"
assert result.confidence == 0.95
assert mock_summarizer.aget_response.call_count == 1
assert mock_settings.llm.acomplete.call_count == 1
class TestStructuredOutputWorkflow:
"""Direct tests for the StructuredOutputWorkflow"""
@pytest.mark.asyncio
async def test_workflow_retries_on_validation_error(self):
"""Test workflow retries when validation fails"""
workflow = StructuredOutputWorkflow(
output_cls=TestResponse,
max_retries=3,
timeout=30,
)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
call_count = {"count": 0}
async def acomplete_handler(*args, **kwargs):
call_count["count"] += 1
if call_count["count"] < 2:
return make_completion_response('{"title": "Only title"}')
return make_completion_response(
'{"title": "Test", "summary": "Summary", "confidence": 0.9}'
)
mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
result = await workflow.run(
prompt="Extract data",
texts=["Some text"],
tone_name=None,
)
assert "success" in result
assert result["success"].title == "Test"
assert call_count["count"] == 2
@pytest.mark.asyncio
async def test_workflow_returns_error_after_max_retries(self):
"""Test workflow returns error after exhausting retries"""
workflow = StructuredOutputWorkflow(
output_cls=TestResponse,
max_retries=2,
timeout=30,
)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
# Always return invalid JSON
mock_settings.llm.acomplete = AsyncMock(
return_value=make_completion_response('{"invalid": true}')
)
result = await workflow.run(
prompt="Extract data",
texts=["Some text"],
tone_name=None,
)
assert "error" in result
# TreeSummarize called once, acomplete called max_retries times
assert mock_summarizer.aget_response.call_count == 1
assert mock_settings.llm.acomplete.call_count == 2
class TestNetworkErrorRetries:
"""Test that network error retries are handled by OpenAILike, not Workflow"""
@pytest.mark.asyncio
async def test_network_error_propagates_after_openai_retries(self, test_settings):
"""Test that network errors are retried by OpenAILike and then propagate.
Network retries are handled by OpenAILike (max_retries=3), not by our
StructuredOutputWorkflow. This test verifies that network errors propagate
up after OpenAILike exhausts its retries.
"""
llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
# Simulate network error from acomplete (after OpenAILike retries exhausted)
network_error = ConnectionError("Connection refused")
mock_settings.llm.acomplete = AsyncMock(side_effect=network_error)
# Network error wrapped in WorkflowRuntimeError
with pytest.raises(WorkflowRuntimeError, match="Connection refused"):
await llm.get_structured_response(
prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
)
# acomplete called only once - network error propagates, not retried by Workflow
assert mock_settings.llm.acomplete.call_count == 1
@pytest.mark.asyncio
async def test_network_error_not_retried_by_workflow(self, test_settings):
"""Test that Workflow does NOT retry network errors (OpenAILike handles those).
This verifies the separation of concerns:
- StructuredOutputWorkflow: retries parse/validation errors
- OpenAILike: retries network errors (internally, max_retries=3)
"""
workflow = StructuredOutputWorkflow(
output_cls=TestResponse,
max_retries=3,
timeout=30,
)
with (
patch("reflector.llm.TreeSummarize") as mock_summarize,
patch("reflector.llm.Settings") as mock_settings,
):
mock_summarizer = MagicMock()
mock_summarize.return_value = mock_summarizer
mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
# Network error should propagate immediately, not trigger Workflow retry
mock_settings.llm.acomplete = AsyncMock(
side_effect=TimeoutError("Request timed out")
)
# Network error wrapped in WorkflowRuntimeError
with pytest.raises(WorkflowRuntimeError, match="Request timed out"):
await workflow.run(
prompt="Extract data",
texts=["Some text"],
tone_name=None,
)
# Only called once - Workflow doesn't retry network errors
assert mock_settings.llm.acomplete.call_count == 1

2
www/package.json
View File

@@ -31,7 +31,7 @@
"ioredis": "^5.7.0",
"jest-worker": "^29.6.2",
"lucide-react": "^0.525.0",
"next": "^15.5.3",
"next": "^15.5.7",
"next-auth": "^4.24.7",
"next-themes": "^0.4.6",
"nuqs": "^2.4.3",

100
www/pnpm-lock.yaml generated
View File

@@ -27,7 +27,7 @@ importers:
version: 0.2.3(@fortawesome/fontawesome-svg-core@6.7.2)(react@18.3.1)
"@sentry/nextjs":
specifier: ^10.11.0
version: 10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)
version: 10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)
"@tanstack/react-query":
specifier: ^5.85.9
version: 5.85.9(react@18.3.1)
@@ -62,17 +62,17 @@ importers:
specifier: ^0.525.0
version: 0.525.0(react@18.3.1)
next:
specifier: ^15.5.3
version: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
specifier: ^15.5.7
version: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
next-auth:
specifier: ^4.24.7
version: 4.24.11(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
version: 4.24.11(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
next-themes:
specifier: ^0.4.6
version: 0.4.6(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
nuqs:
specifier: ^2.4.3
version: 2.4.3(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)
version: 2.4.3(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)
openapi-fetch:
specifier: ^0.14.0
version: 0.14.0
@@ -1184,10 +1184,10 @@ packages:
integrity: sha512-ZVWUcfwY4E/yPitQJl481FjFo3K22D6qF0DuFH6Y/nbnE11GY5uguDxZMGXPQ8WQ0128MXQD7TnfHyK4oWoIJQ==,
}
"@next/env@15.5.3":
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resolution:
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integrity: sha512-RSEDTRqyihYXygx/OJXwvVupfr9m04+0vH8vyy0HfZ7keRto6VX9BbEk0J2PUk0VGy6YhklJUSrgForov5F9pw==,
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@@ -1196,73 +1196,73 @@ packages:
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}
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resolution:
{
integrity: sha512-nzbHQo69+au9wJkGKTU9lP7PXv0d1J5ljFpvb+LnEomLtSbJkbZyEs6sbF3plQmiOB2l9OBtN2tNSvCH1nQ9Jg==,
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engines: { node: ">= 10" }
cpu: [arm64]
os: [darwin]
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engines: { node: ">= 10" }
cpu: [x64]
os: [darwin]
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engines: { node: ">= 10" }
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cpu: [arm64]
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engines: { node: ">= 10" }
cpu: [x64]
os: [linux]
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engines: { node: ">= 10" }
cpu: [x64]
os: [linux]
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resolution:
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engines: { node: ">= 10" }
cpu: [arm64]
os: [win32]
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resolution:
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integrity: sha512-JMoLAq3n3y5tKXPQwCK5c+6tmwkuFDa2XAxz8Wm4+IVthdBZdZGh+lmiLUHg9f9IDwIQpUjp+ysd6OkYTyZRZw==,
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}
engines: { node: ">= 10" }
cpu: [x64]
@@ -6863,10 +6863,10 @@ packages:
react: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc
react-dom: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc
next@15.5.3:
next@15.5.7:
resolution:
{
integrity: sha512-r/liNAx16SQj4D+XH/oI1dlpv9tdKJ6cONYPwwcCC46f2NjpaRWY+EKCzULfgQYV6YKXjHBchff2IZBSlZmJNw==,
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}
engines: { node: ^18.18.0 || ^19.8.0 || >= 20.0.0 }
hasBin: true
@@ -9877,34 +9877,34 @@ snapshots:
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optional: true
"@next/env@15.5.3": {}
"@next/env@15.5.7": {}
"@next/eslint-plugin-next@15.5.3":
dependencies:
fast-glob: 3.3.1
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"@next/swc-darwin-arm64@15.5.7":
optional: true
"@next/swc-darwin-x64@15.5.3":
"@next/swc-darwin-x64@15.5.7":
optional: true
"@next/swc-linux-arm64-gnu@15.5.3":
"@next/swc-linux-arm64-gnu@15.5.7":
optional: true
"@next/swc-linux-arm64-musl@15.5.3":
"@next/swc-linux-arm64-musl@15.5.7":
optional: true
"@next/swc-linux-x64-gnu@15.5.3":
"@next/swc-linux-x64-gnu@15.5.7":
optional: true
"@next/swc-linux-x64-musl@15.5.3":
"@next/swc-linux-x64-musl@15.5.7":
optional: true
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"@next/swc-win32-arm64-msvc@15.5.7":
optional: true
"@next/swc-win32-x64-msvc@15.5.3":
"@next/swc-win32-x64-msvc@15.5.7":
optional: true
"@nodelib/fs.scandir@2.1.5":
@@ -10684,7 +10684,7 @@ snapshots:
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"@sentry/nextjs@10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)":
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dependencies:
"@opentelemetry/api": 1.9.0
"@opentelemetry/semantic-conventions": 1.37.0
@@ -10698,7 +10698,7 @@ snapshots:
"@sentry/vercel-edge": 10.11.0
"@sentry/webpack-plugin": 4.3.0(webpack@5.101.3)
chalk: 3.0.0
next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
resolve: 1.22.8
rollup: 4.50.1
stacktrace-parser: 0.1.11
@@ -14093,13 +14093,13 @@ snapshots:
neo-async@2.6.2: {}
next-auth@4.24.11(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
next-auth@4.24.11(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
"@babel/runtime": 7.28.2
"@panva/hkdf": 1.2.1
cookie: 0.7.2
jose: 4.15.9
next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
oauth: 0.9.15
openid-client: 5.7.1
preact: 10.27.0
@@ -14113,9 +14113,9 @@ snapshots:
react: 18.3.1
react-dom: 18.3.1(react@18.3.1)
next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0):
next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0):
dependencies:
"@next/env": 15.5.3
"@next/env": 15.5.7
"@swc/helpers": 0.5.15
caniuse-lite: 1.0.30001734
postcss: 8.4.31
@@ -14123,14 +14123,14 @@ snapshots:
react-dom: 18.3.1(react@18.3.1)
styled-jsx: 5.1.6(@babel/core@7.28.3)(babel-plugin-macros@3.1.0)(react@18.3.1)
optionalDependencies:
"@next/swc-darwin-arm64": 15.5.3
"@next/swc-darwin-x64": 15.5.3
"@next/swc-linux-arm64-gnu": 15.5.3
"@next/swc-linux-arm64-musl": 15.5.3
"@next/swc-linux-x64-gnu": 15.5.3
"@next/swc-linux-x64-musl": 15.5.3
"@next/swc-win32-arm64-msvc": 15.5.3
"@next/swc-win32-x64-msvc": 15.5.3
"@next/swc-darwin-arm64": 15.5.7
"@next/swc-darwin-x64": 15.5.7
"@next/swc-linux-arm64-gnu": 15.5.7
"@next/swc-linux-arm64-musl": 15.5.7
"@next/swc-linux-x64-gnu": 15.5.7
"@next/swc-linux-x64-musl": 15.5.7
"@next/swc-win32-arm64-msvc": 15.5.7
"@next/swc-win32-x64-msvc": 15.5.7
"@opentelemetry/api": 1.9.0
sass: 1.90.0
sharp: 0.34.3
@@ -14159,12 +14159,12 @@ snapshots:
dependencies:
path-key: 3.1.1
nuqs@2.4.3(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1):
nuqs@2.4.3(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1):
dependencies:
mitt: 3.0.1
react: 18.3.1
optionalDependencies:
next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
oauth@0.9.15: {}