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Jon Saad-FalconandClaude Opus 4.6
d73014d6bb
Full morning digest system: - MorningDigestAgent, DigestStore, digest_collect tool, TTS backends - Connectors: Oura, Strava, Spotify, Google Tasks, Apple Health, Apple Music - CLI `jarvis digest` command + FastAPI /api/digest endpoints - Cartesia, Kokoro, OpenAI TTS backends with persona prompts Unified OAuth setup across all surfaces: - Generic OAuthProvider registry for Google, Strava, Spotify - CLI auto-opens browser + catches callback (no more paste-code) - Server /oauth/start + /oauth/callback endpoints for desktop/browser - Frontend OAuthPanel with popup + polling Apple connectors: - Apple Health reads from HealthKit DB or iPhone export XML - Apple Music queries Music.app via AppleScript Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
80 lines
2.3 KiB
Python
80 lines
2.3 KiB
Python
"""End-to-end integration test for the morning digest pipeline.
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Uses mocked connectors and engine to verify the full flow:
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digest_collect -> LLM synthesis -> TTS -> DigestStore -> CLI delivery.
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"""
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from __future__ import annotations
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from datetime import datetime
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from pathlib import Path
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from unittest.mock import MagicMock, patch
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import pytest
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from openjarvis.agents.digest_store import DigestStore
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from openjarvis.core.types import ToolResult
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def test_full_digest_pipeline(tmp_path):
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"""Verify collect -> synthesize -> TTS -> store -> retrieve."""
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from openjarvis.agents.morning_digest import MorningDigestAgent
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# Mock engine returns a narrative
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mock_engine = MagicMock()
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mock_engine.generate.return_value = {
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"content": (
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"Good morning, sir. You slept 7.5 hours with a readiness score of 78. "
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"You have 2 meetings today and 5 unread emails. "
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"In the news, a new GPT-5 paper dropped on Arxiv."
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),
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"finish_reason": "stop",
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"usage": {},
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}
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# Mock tool results
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collect_result = ToolResult(
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tool_name="digest_collect",
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content="## gmail (3 items)\n## oura (1 items)\n## gcalendar (2 items)",
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success=True,
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metadata={"total_items": 6},
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)
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tts_result = ToolResult(
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tool_name="text_to_speech",
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content=str(tmp_path / "digest.mp3"),
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success=True,
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metadata={"audio_path": str(tmp_path / "digest.mp3")},
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)
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# Write fake audio
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(tmp_path / "digest.mp3").write_bytes(b"fake-mp3-audio")
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db_path = str(tmp_path / "digest.db")
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agent = MorningDigestAgent(
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mock_engine,
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"claude-sonnet-4-6",
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tools=[],
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persona="neutral",
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digest_store_path=db_path,
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)
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with patch.object(
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agent._executor,
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"execute",
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side_effect=[collect_result, tts_result],
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):
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result = agent.run("Generate morning digest")
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# Verify agent result
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assert "Good morning" in result.content
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assert result.metadata["audio_path"] == str(tmp_path / "digest.mp3")
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# Verify stored in DigestStore
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store = DigestStore(db_path=db_path)
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artifact = store.get_latest()
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assert artifact is not None
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assert "Good morning" in artifact.text
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assert artifact.model_used == "claude-sonnet-4-6"
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store.close()
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