refactor(commands): remove pre-1.6 embedding shims and dead tool config

The embed_single_item, embed_chunk and vectorize_source command handlers
existed only so jobs queued by a pre-1.6 version could drain after an
upgrade; any worker restarted on 1.6+ has no such jobs. Remove them, their
input/output models and their tests.

Also drop dead tooling config from pyproject.toml: the [tool.mypy] block
(mypy.ini takes precedence and is the real config) and the Streamlit-era
ruff per-file-ignores for app_home.py and pages/**, which no longer exist.

Author: lfnovo

CHANGELOG.md

@@ -12,6 +12,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Removed
 - Dead Streamlit-era service layer (~2,000 lines): `api/client.py` (a synchronous HTTP client that called the app's own API) and 13 `api/*_service.py` wrappers that consumed the app's own HTTP API — none were imported by any router, command or test. Also removed the toy `process_text`/`analyze_data` demo commands (`commands/example_commands.py`) from the background worker
+- Pre-1.6 embedding job compatibility shims (the `embed_single_item`, `embed_chunk` and `vectorize_source` command handlers) — they existed only so jobs queued by a pre-1.6 version could drain after an upgrade, and any worker restarted on 1.6+ has no such jobs. **Upgrade note:** if you are upgrading from a version older than 1.6 with embedding jobs still queued, drain the queue on a 1.x release before upgrading past this change. Also removed dead tooling config from `pyproject.toml`: the `[tool.mypy]` block (the real config is `mypy.ini`) and Streamlit-era ruff per-file-ignores for files that no longer exist
 
 ## [1.11.0] - 2026-07-11
 

commands/embedding_commands.py

@@ -118,58 +118,6 @@ class EmbedSourceOutput(CommandOutput):
     error_message: Optional[str] = None
 
 
-class LegacyEmbedSingleItemInput(CommandInput):
-    """Input for the pre-1.6 embed_single_item command kept for queued jobs."""
-
-    item_id: str
-    item_type: Literal["source", "note", "insight"]
-
-
-class LegacyEmbedSingleItemOutput(CommandOutput):
-    """Output matching the pre-1.6 embed_single_item command shape."""
-
-    success: bool
-    item_id: str
-    item_type: str
-    chunks_created: int = 0
-    processing_time: float
-    error_message: Optional[str] = None
-
-
-class LegacyEmbedChunkInput(CommandInput):
-    """Input for the pre-1.6 per-chunk embedding command kept for queued jobs."""
-
-    source_id: str
-    chunk_index: int
-    chunk_text: str
-
-
-class LegacyEmbedChunkOutput(CommandOutput):
-    """Output matching the pre-1.6 embed_chunk command shape."""
-
-    success: bool
-    source_id: str
-    chunk_index: int
-    error_message: Optional[str] = None
-
-
-class LegacyVectorizeSourceInput(CommandInput):
-    """Input for the pre-1.6 vectorize_source command kept for queued jobs."""
-
-    source_id: str
-
-
-class LegacyVectorizeSourceOutput(CommandOutput):
-    """Output matching the pre-1.6 vectorize_source command shape."""
-
-    success: bool
-    source_id: str
-    total_chunks: int
-    jobs_submitted: int
-    processing_time: float
-    error_message: Optional[str] = None
-
-
 @command(
     "embed_note",
     app="open_notebook",
@@ -501,218 +449,6 @@ async def embed_source_command(input_data: EmbedSourceInput) -> EmbedSourceOutpu
         raise
 
 
-@command(
-    "embed_single_item",
-    app="open_notebook",
-    retry={
-        "max_attempts": 5,
-        "wait_strategy": "exponential_jitter",
-        "wait_min": 1,
-        "wait_max": 60,
-        "stop_on": [ValueError, ConfigurationError],
-        "retry_log_level": "debug",
-    },
-)
-async def legacy_embed_single_item_command(
-    input_data: LegacyEmbedSingleItemInput,
-) -> LegacyEmbedSingleItemOutput:
-    """
-    Compatibility handler for pre-1.6 queued embed_single_item jobs.
-
-    New code submits embed_source, embed_note, or embed_insight directly. This
-    alias lets workers drain older queues after an upgrade.
-    """
-    start_time = time.time()
-
-    try:
-        logger.info(
-            f"Processing legacy embed_single_item for "
-            f"{input_data.item_type}: {input_data.item_id}"
-        )
-
-        if input_data.item_type == "source":
-            result = await embed_source_command(
-                EmbedSourceInput(
-                    source_id=input_data.item_id,
-                    execution_context=input_data.execution_context,
-                )
-            )
-            chunks_created = result.chunks_created
-        elif input_data.item_type == "note":
-            result = await embed_note_command(
-                EmbedNoteInput(
-                    note_id=input_data.item_id,
-                    execution_context=input_data.execution_context,
-                )
-            )
-            chunks_created = 0
-        elif input_data.item_type == "insight":
-            result = await embed_insight_command(
-                EmbedInsightInput(
-                    insight_id=input_data.item_id,
-                    execution_context=input_data.execution_context,
-                )
-            )
-            chunks_created = 0
-        else:
-            raise ValueError(f"Invalid item_type: {input_data.item_type}")
-
-        return LegacyEmbedSingleItemOutput(
-            success=result.success,
-            item_id=input_data.item_id,
-            item_type=input_data.item_type,
-            chunks_created=chunks_created,
-            processing_time=time.time() - start_time,
-            error_message=result.error_message,
-        )
-
-    except ValueError as e:
-        processing_time = time.time() - start_time
-        logger.error(
-            f"Failed legacy embed_single_item for "
-            f"{input_data.item_type} {input_data.item_id}: {e}"
-        )
-        return LegacyEmbedSingleItemOutput(
-            success=False,
-            item_id=input_data.item_id,
-            item_type=input_data.item_type,
-            processing_time=processing_time,
-            error_message=str(e),
-        )
-    except Exception as e:
-        logger.debug(
-            f"Transient error in legacy embed_single_item for "
-            f"{input_data.item_type} {input_data.item_id}: {e}"
-        )
-        raise
-
-
-@command(
-    "embed_chunk",
-    app="open_notebook",
-    retry={
-        "max_attempts": 5,
-        "wait_strategy": "exponential_jitter",
-        "wait_min": 1,
-        "wait_max": 60,
-        "stop_on": [ValueError, ConfigurationError],
-        "retry_log_level": "debug",
-    },
-)
-async def legacy_embed_chunk_command(
-    input_data: LegacyEmbedChunkInput,
-) -> LegacyEmbedChunkOutput:
-    """
-    Compatibility handler for pre-1.6 queued embed_chunk jobs.
-
-    The legacy vectorizer stored the full chunk payload in each job. Keeping this
-    command registered prevents upgraded workers from crashing on stale queues.
-    """
-    try:
-        logger.debug(
-            f"Processing legacy chunk {input_data.chunk_index} "
-            f"for source {input_data.source_id}"
-        )
-
-        cmd_id = get_command_id(input_data)
-        embedding = await generate_embedding(
-            input_data.chunk_text,
-            content_type=ContentType.PLAIN,
-            command_id=cmd_id,
-        )
-
-        await repo_query(
-            """
-            CREATE source_embedding CONTENT {
-                "source": $source_id,
-                "order": $order,
-                "content": $content,
-                "embedding": $embedding,
-            };
-            """,
-            {
-                "source_id": ensure_record_id(input_data.source_id),
-                "order": input_data.chunk_index,
-                "content": input_data.chunk_text,
-                "embedding": embedding,
-            },
-        )
-
-        return LegacyEmbedChunkOutput(
-            success=True,
-            source_id=input_data.source_id,
-            chunk_index=input_data.chunk_index,
-        )
-
-    except ValueError as e:
-        logger.error(
-            f"Failed legacy embed_chunk for source {input_data.source_id} "
-            f"chunk {input_data.chunk_index}: {e}"
-        )
-        return LegacyEmbedChunkOutput(
-            success=False,
-            source_id=input_data.source_id,
-            chunk_index=input_data.chunk_index,
-            error_message=str(e),
-        )
-    except Exception as e:
-        logger.debug(
-            f"Transient error in legacy embed_chunk for source "
-            f"{input_data.source_id} chunk {input_data.chunk_index}: {e}"
-        )
-        raise
-
-
-@command("vectorize_source", app="open_notebook", retry=None)
-async def legacy_vectorize_source_command(
-    input_data: LegacyVectorizeSourceInput,
-) -> LegacyVectorizeSourceOutput:
-    """
-    Compatibility handler for pre-1.6 queued vectorize_source jobs.
-
-    The old command submitted one job per chunk. Current embed_source does the
-    same source embedding work in one batch-aware command.
-    """
-    start_time = time.time()
-
-    try:
-        logger.info(f"Processing legacy vectorize_source for {input_data.source_id}")
-        result = await embed_source_command(
-            EmbedSourceInput(
-                source_id=input_data.source_id,
-                execution_context=input_data.execution_context,
-            )
-        )
-        jobs_submitted = 1 if result.success else 0
-
-        return LegacyVectorizeSourceOutput(
-            success=result.success,
-            source_id=input_data.source_id,
-            total_chunks=result.chunks_created,
-            jobs_submitted=jobs_submitted,
-            processing_time=time.time() - start_time,
-            error_message=result.error_message,
-        )
-
-    except ValueError as e:
-        processing_time = time.time() - start_time
-        logger.error(f"Failed legacy vectorize_source for {input_data.source_id}: {e}")
-        return LegacyVectorizeSourceOutput(
-            success=False,
-            source_id=input_data.source_id,
-            total_chunks=0,
-            jobs_submitted=0,
-            processing_time=processing_time,
-            error_message=str(e),
-        )
-    except Exception as e:
-        logger.debug(
-            f"Transient error in legacy vectorize_source for "
-            f"{input_data.source_id}: {e}"
-        )
-        raise
-
-
 @command(
     "create_insight",
     app="open_notebook",

pyproject.toml

@@ -92,17 +92,6 @@ ignore = [
     "F841",  # local variable assigned but never used
 ]
 
-[tool.ruff.lint.per-file-ignores]
-# Streamlit files need nest_asyncio.apply() before imports
-"app_home.py" = ["E402"]
-"pages/**/*.py" = ["E402"]
-
-[tool.mypy]
-# Exclude Streamlit UI pages from type checking
-[[tool.mypy.overrides]]
-module = "pages.*"
-ignore_errors = true
-
 [tool.uv]
 # Pillow < 12.2.0 has open security advisories (PSD OOB write, FITS
 # decompression bomb, PDF trailer DoS). The only thing holding it back is