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voice-to-notes/python/voice_to_notes/ipc/protocol.py

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"""JSON-line protocol reader/writer over stdin/stdout.
IMPORTANT: stdout is reserved exclusively for IPC messages.
At init time we save the real stdout, then redirect sys.stdout stderr
so that any rogue print() calls from libraries don't corrupt the IPC stream.
"""
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
from __future__ import annotations
import io
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
import json
import os
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
import sys
from typing import Any
from voice_to_notes.ipc.messages import IPCMessage
# Save the real stdout fd for IPC before any library can pollute it.
# Then redirect sys.stdout to stderr so library prints go to stderr.
_ipc_out: io.TextIOWrapper | None = None
def init_ipc() -> None:
"""Capture real stdout for IPC and redirect sys.stdout to stderr.
Must be called once at sidecar startup, before importing any ML libraries.
"""
global _ipc_out
if _ipc_out is not None:
return # already initialised
# Duplicate the real stdout fd so we keep it even after redirect
real_stdout_fd = os.dup(sys.stdout.fileno())
_ipc_out = io.TextIOWrapper(
io.BufferedWriter(io.FileIO(real_stdout_fd, "w")),
encoding="utf-8",
line_buffering=True,
)
# Redirect sys.stdout → stderr so print() from libraries goes to stderr
sys.stdout = sys.stderr
def _get_ipc_out() -> io.TextIOWrapper:
"""Return the IPC output stream, falling back to sys.__stdout__."""
if _ipc_out is not None:
return _ipc_out
# Fallback if init_ipc() was never called (e.g. in tests)
return sys.__stdout__
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
def read_message() -> IPCMessage | None:
"""Read a single JSON-line message from stdin. Returns None on EOF."""
try:
line = sys.stdin.readline()
if not line:
return None # EOF
line = line.strip()
if not line:
return None
data = json.loads(line)
return IPCMessage.from_dict(data)
except json.JSONDecodeError as e:
_log(f"Invalid JSON: {e}")
return None
except Exception as e:
_log(f"Read error: {e}")
return None
def write_message(msg: IPCMessage) -> None:
"""Write a JSON-line message to the IPC channel (real stdout)."""
out = _get_ipc_out()
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
line = json.dumps(msg.to_dict(), separators=(",", ":"))
out.write(line + "\n")
out.flush()
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
def write_dict(data: dict[str, Any]) -> None:
"""Write a raw dict as a JSON-line message to the IPC channel."""
out = _get_ipc_out()
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
line = json.dumps(data, separators=(",", ":"))
out.write(line + "\n")
out.flush()
Phase 1 foundation: Tauri shell, Python sidecar, SQLite database Tauri v2 + Svelte + TypeScript frontend: - App shell with workspace layout (waveform, transcript, speakers, AI chat) - Placeholder components for all major UI areas - Typed stores (project, transcript, playback, AI) - TypeScript interfaces matching the database schema - Tauri bridge service with typed invoke wrappers - svelte-check passes with 0 errors Rust backend: - Tauri v2 app entry point with command registration - SQLite database layer (rusqlite with bundled SQLite) - Full schema: projects, media_files, speakers, segments, words, ai_outputs, annotations (with indexes) - Model structs with serde serialization - CRUD queries for projects, speakers, segments, words - Segment text editing preserves original text - Schema versioning for future migrations - 6 tests passing - Command stubs for project, transcribe, export, AI, settings, system - App state management Python sidecar: - JSON-line IPC protocol (stdin/stdout) - Message types: IPCMessage, progress, error, ready - Handler registry with routing and error handling - Ping/pong handler for connectivity testing - Service stubs: transcribe, diarize, pipeline, AI, export - Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM - Hardware detection stubs - 14 tests passing, ruff clean Also adds: - Testing strategy document (docs/TESTING.md) - Validation script (scripts/validate.sh) - Updated .gitignore for Svelte, Rust, Python artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 15:16:06 -08:00
def _log(message: str) -> None:
"""Log to stderr (stdout is reserved for IPC)."""
print(f"[sidecar] {message}", file=sys.stderr, flush=True)