From d5091a321e3df33257fa3834f21782c7f3625a5b Mon Sep 17 00:00:00 2001
From: Pierre Brunelle <pbrunelle@pixeltable.com>
Date: Wed, 9 Sep 2026 21:23:14 -0700
Subject: [PATCH 1/3] fix: run on Pixeltable 0.7.6, and add the CI that would
 have caught this

Document, audio and video memories raised on construction against any
Pixeltable >= 0.5.6. config.py carried the 0.4.2 iterator parameter names,
and those names are not cosmetic: they go through dataclasses.asdict()
straight into the iterator call, so each one is an API contract.
chunk_duration_sec/overlap_sec/min_chunk_duration_sec are now
duration/overlap/min_segment_duration, and html_skip_tags is skip_tags.
The pixeltable.iterators shims forward **kwargs verbatim with no name
mapping, which is why these were hard errors rather than warnings; they are
replaced by document_splitter / audio_splitter / string_splitter /
frame_iterator.

Also fixed:
- the audio view output column is `audio_segment`, not `audio_chunk`
- transcriptions() kwargs were splatted top-level; the signature is
  (audio, model, model_kwargs), so WhisperParams(language='en') raised
- if_exists="replace_force" on five paths dropped and rebuilt every view and
  index on every construction, re-running Whisper and re-embedding
  everything; now "ignore", which the existing get_table fallbacks expect
- non-nullable-by-default (0.7.3) made every field mandatory; Context gains
  `required` so a field can be optional
- pxt.list_dirs() returns slash paths, so the dotted-namespace check never
  matched and nested namespaces failed on second construction; replaced by
  create_dir(parents=True, if_exists="ignore")
- __getattr__ dereferenced self.resources from inside itself, so any __init__
  failure turned the next attribute access into RecursionError
- vision.py moves off the deprecated openai.vision to chat_completions, and
  the anthropic path gains its required max_tokens, base64-encodes the image
  instead of passing a raw column reference as the data value, and routes
  llm_kwargs through model_kwargs

None of this was caught because there was no CI on any branch and uv.lock
pinned pixeltable 0.4.2, so local installs resolved to a version where the
code worked while `pip install pixelmemory` got a package that could not run
its own README. The most recent commit on main was "Removed test".

The new suite is construction-only, so it needs no API key, no model weights,
no spaCy and no media fixtures; conftest.py pops the provider keys from the
environment so the tests prove it. It asserts on get_metadata()['iterator_call']
(which catches the kwarg-rename class of bug precisely) and on view ids being
stable across reconstruction (which catches replace_force). CI installs
pixeltable unpinned with a weekly cron, so the next breaking release turns
this build red instead of a user's install.

Against the pre-fix source the suite reports 14 failures; against this commit,
19 pass.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
---
 .github/workflows/test.yml         |   52 +
 .gitignore                         |   11 +-
 examples/fastapi/memory_service.py |    2 +-
 examples/mcp/memory.py             |    1 -
 pixelmemory/config.py              |    8 +-
 pixelmemory/context.py             |    6 +-
 pixelmemory/indexing.py            |   60 +-
 pixelmemory/memory.py              |   11 +-
 pixelmemory/vision.py              |   74 +-
 pyproject.toml                     |   57 +-
 tests/conftest.py                  |   42 +
 tests/test_construction.py         |  233 ++
 uv.lock                            | 4652 ++++++++++++++++++----------
 13 files changed, 3556 insertions(+), 1653 deletions(-)
 create mode 100644 .github/workflows/test.yml
 create mode 100644 tests/conftest.py
 create mode 100644 tests/test_construction.py

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
new file mode 100644
index 0000000..4ef4f6f
--- /dev/null
+++ b/.github/workflows/test.yml
@@ -0,0 +1,52 @@
+name: test
+
+# No `secrets:` block appears anywhere in this file, and that absence is the
+# assertion: the suite must pass with no provider credentials at all. A test that
+# needs a key fails here.
+
+on:
+  push:
+    branches: ["**"]
+  pull_request:
+  workflow_dispatch:
+  schedule:
+    # Weekly canary. The install step below takes Pixeltable unpinned, so the
+    # release that breaks pixelmemory turns this build red before a user finds it.
+    - cron: "0 6 * * 1"
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11", "3.12"]
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+
+      - name: Install
+        run: uv sync --python ${{ matrix.python-version }}
+
+      - name: Take Pixeltable unpinned
+        # Deliberately ignores the `<0.8` pin in pyproject.toml. This is the canary.
+        # Every step after this uses --no-sync, or uv would restore the pinned version.
+        run: uv pip install --upgrade pixeltable
+
+      - name: Record the Pixeltable version under test
+        run: uv run --no-sync python -c "import pixeltable; print(pixeltable.__version__)"
+
+      - name: Lint
+        run: uv run --no-sync ruff check .
+
+      - name: Test
+        env:
+          HF_HUB_DISABLE_PROGRESS_BARS: "1"
+        run: uv run --no-sync python -m pytest tests/ -v
diff --git a/.gitignore b/.gitignore
index 525213e..f41f6f1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,12 @@
+**/__pycache__
+*.egg-info
+*.py[cod]
+.pytest_cache/
+.ruff_cache
+.ruff_cache/
 .venv
+.venv/
 .vscode
+__pycache__/
 dist
-**/__pycache__
-*.egg-info
 resources/
-.ruff_cache
\ No newline at end of file
diff --git a/examples/fastapi/memory_service.py b/examples/fastapi/memory_service.py
index 3f9e5c6..3e52727 100644
--- a/examples/fastapi/memory_service.py
+++ b/examples/fastapi/memory_service.py
@@ -1,5 +1,5 @@
 from fastapi import FastAPI, HTTPException, Query
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
 from typing import List, Dict, Any, Optional
 from pixelmemory import Memory
 from pixelmemory.context import Text, Image, Video, Audio, Document
diff --git a/examples/mcp/memory.py b/examples/mcp/memory.py
index f8f8890..a06b30b 100644
--- a/examples/mcp/memory.py
+++ b/examples/mcp/memory.py
@@ -1,4 +1,3 @@
-import asyncio
 import contextlib
 import logging
 from collections.abc import AsyncIterator
diff --git a/pixelmemory/config.py b/pixelmemory/config.py
index c64b83f..a0b45cd 100644
--- a/pixelmemory/config.py
+++ b/pixelmemory/config.py
@@ -20,9 +20,9 @@
 
 @dataclass
 class AudioSplitterParams:
-    chunk_duration_sec: float = 30.0
-    overlap_sec: float = 0.0
-    min_chunk_duration_sec: float = 0.0
+    duration: float = 30.0
+    overlap: float = 0.0
+    min_segment_duration: float = 0.0
 
 
 @dataclass
@@ -31,7 +31,7 @@ class DocumentSplitterParams:
     limit: Optional[int] = 300
     overlap: Optional[int] = None
     metadata: str = ""
-    html_skip_tags: list[str] = field(default_factory=lambda: ["nav"])
+    skip_tags: list[str] = field(default_factory=lambda: ["nav"])
     tiktoken_encoding: str = "cl100k_base"
     tiktoken_target_model: Optional[str] = None
 
diff --git a/pixelmemory/context.py b/pixelmemory/context.py
index 5734c5f..98116aa 100644
--- a/pixelmemory/context.py
+++ b/pixelmemory/context.py
@@ -16,6 +16,8 @@ class Context:
     embed: bool = True
     embed_model: Optional[Union[str, pxt.Function]] = "all-mpnet-base-v2"
     index_name: Optional[str] = None
+    required: bool = True
+    """When False, the column accepts nulls. Pixeltable columns are non-nullable by default."""
 
 
 @dataclass
@@ -23,7 +25,7 @@ class Audio(Context):
     transcription_model: str = "whisper-1"
     transcription_kwargs: WhisperParams = field(default_factory=WhisperParams)
     chunk_params: AudioSplitterParams = field(
-        default_factory=lambda: AudioSplitterParams(chunk_duration_sec=30.0)
+        default_factory=lambda: AudioSplitterParams(duration=30.0)
     )
     _pxt_type: pxt.Audio = pxt.Audio
 
@@ -60,7 +62,7 @@ class Video(Context):
     transcription_model: str = "whisper-1"
     transcription_kwargs: WhisperParams = field(default_factory=WhisperParams)
     audio_chunk_params: AudioSplitterParams = field(
-        default_factory=lambda: AudioSplitterParams(chunk_duration_sec=30.0)
+        default_factory=lambda: AudioSplitterParams(duration=30.0)
     )
     provider: Literal["openai", "anthropic"] = "openai"
     model: str = "gpt-4o-mini"
diff --git a/pixelmemory/indexing.py b/pixelmemory/indexing.py
index f4a1ba5..dfb6f8b 100644
--- a/pixelmemory/indexing.py
+++ b/pixelmemory/indexing.py
@@ -1,4 +1,3 @@
-import pixeltable as pxt
 from typing import Any, Optional
 import pixeltable as pxt
 import dataclasses
@@ -103,7 +102,7 @@ def setup_document_indexing(
     index_name: str,
     col_settings: Document,
 ) -> None:
-    from pixeltable.iterators import DocumentSplitter
+    from pixeltable.functions.document import document_splitter
 
     chunk_view_name = f"{memory_instance.table_name}_{col_name}_chunks"
     chunk_view_path = f"{memory_instance.namespace}.{chunk_view_name}"
@@ -113,12 +112,12 @@ def setup_document_indexing(
     chunk_view = pxt.create_view(
         chunk_view_path,
         memory_instance.table,
-        iterator=DocumentSplitter.create(
+        iterator=document_splitter(
             document=document_source, **dataclasses.asdict(col_settings.chunk_params)
         ),
-        if_exists="replace_force",
+        if_exists="ignore",
     )
-    if not chunk_view:
+    if chunk_view is None:
         chunk_view = pxt.get_table(chunk_view_path)
 
     memory_instance.resources.chunk_views.append(
@@ -152,9 +151,10 @@ def setup_audio_indexing(
     embed_model: pxt.Function,
     index_name: str,
     col_settings: Audio,
-    audio_col: Optional[pxt.Column] = None,
+    audio_col: Optional[pxt.exprs.ColumnRef] = None,
 ) -> None:
-    from pixeltable.iterators import AudioSplitter, StringSplitter
+    from pixeltable.functions.audio import audio_splitter
+    from pixeltable.functions.string import string_splitter
     from pixeltable.functions.openai import transcriptions
 
     transcription_kwargs = {
@@ -173,23 +173,24 @@ def setup_audio_indexing(
     audio_chunk_view = pxt.create_view(
         audio_chunk_view_path,
         memory_instance.table,
-        iterator=AudioSplitter.create(
+        iterator=audio_splitter(
             audio=audio_source, **dataclasses.asdict(col_settings.chunk_params)
         ),
-        if_exists="replace_force",
+        if_exists="ignore",
     )
-    if not audio_chunk_view:
+    if audio_chunk_view is None:
         audio_chunk_view = pxt.get_table(audio_chunk_view_path)
 
     transcription_col_name = f"{col_name}_transcription"
-    whisper_args = {
-        "audio": audio_chunk_view.audio_chunk,
-        "model": col_settings.transcription_model,
-        **transcription_kwargs,
-    }
-
     audio_chunk_view.add_computed_column(
-        **{transcription_col_name: transcriptions(**whisper_args)}, if_exists="ignore"
+        **{
+            transcription_col_name: transcriptions(
+                audio=audio_chunk_view.audio_segment,
+                model=col_settings.transcription_model,
+                model_kwargs=transcription_kwargs or None,
+            )
+        },
+        if_exists="ignore",
     )
 
     sentence_view_name = f"{memory_instance.table_name}_{col_name}_sentence_chunks"
@@ -200,12 +201,10 @@ def setup_audio_indexing(
     sentence_chunk_view = pxt.create_view(
         sentence_view_path,
         audio_chunk_view,
-        iterator=StringSplitter.create(
-            text=transcription_text_col, separators="sentence"
-        ),
-        if_exists="replace_force",
+        iterator=string_splitter(text=transcription_text_col, separators="sentence"),
+        if_exists="ignore",
     )
-    if not sentence_chunk_view:
+    if sentence_chunk_view is None:
         sentence_chunk_view = pxt.get_table(sentence_view_path)
 
     memory_instance.resources.chunk_views.append(
@@ -224,8 +223,7 @@ def setup_video_indexing(
     index_name: str,
     col_settings: Video,
 ) -> None:
-    from pixeltable.functions.video import extract_audio
-    from pixeltable.iterators import FrameIterator
+    from pixeltable.functions.video import extract_audio, frame_iterator
 
     audio_col_name = f"{col_name}_audio"
     memory_instance.table.add_computed_column(
@@ -254,13 +252,13 @@ def setup_video_indexing(
     frame_view = pxt.create_view(
         frame_view_path,
         memory_instance.table,
-        iterator=FrameIterator.create(
+        iterator=frame_iterator(
             video=getattr(memory_instance.table, col_name),
             **dataclasses.asdict(col_settings.frame_params),
         ),
         if_exists="ignore",
     )
-    if not frame_view:
+    if frame_view is None:
         frame_view = pxt.get_table(frame_view_path)
     memory_instance.resources.frame_views.append(
         FrameView(name=col_name, table=frame_view)
@@ -293,7 +291,7 @@ def setup_string_indexing(
     col_settings: Text,
 ) -> None:
     if col_settings.use_chunking:
-        from pixeltable.iterators import StringSplitter
+        from pixeltable.functions.string import string_splitter
 
         chunk_view_name = f"{memory_instance.table_name}_{col_name}_chunks"
         chunk_view_path = f"{memory_instance.namespace}.{chunk_view_name}"
@@ -303,12 +301,12 @@ def setup_string_indexing(
         chunk_view = pxt.create_view(
             chunk_view_path,
             memory_instance.table,
-            iterator=StringSplitter.create(
+            iterator=string_splitter(
                 text=text_source, **dataclasses.asdict(col_settings.chunk_params)
             ),
-            if_exists="replace_force",
+            if_exists="ignore",
         )
-        if not chunk_view:
+        if chunk_view is None:
             chunk_view = pxt.get_table(chunk_view_path)
 
         memory_instance.resources.chunk_views.append(
@@ -333,5 +331,5 @@ def setup_string_indexing(
             column=col_name,
             idx_name=index_name,
             embedding=embed_model,
-            if_exists="replace_force",
+            if_exists="ignore",
         )
diff --git a/pixelmemory/memory.py b/pixelmemory/memory.py
index 9ca9901..fb8f7dd 100644
--- a/pixelmemory/memory.py
+++ b/pixelmemory/memory.py
@@ -37,15 +37,15 @@ def __init__(
         self.if_exists = if_exists
 
         self.schema: Dict[str, pxt.ColumnType] = {
-            col.id: col._pxt_type for col in self.context
+            col.id: (col._pxt_type if col.required else col._pxt_type | None)
+            for col in self.context
         }
         self.columns_to_embed: Dict[str, Context] = {
             col.id: col for col in self.context if col.embed
         }
 
         table_path = f"{self.namespace}.{self.table_name}"
-        if self.namespace not in pxt.list_dirs():
-            pxt.create_dir(self.namespace)
+        pxt.create_dir(self.namespace, if_exists="ignore", parents=True)
 
         self.table: pxt.Table = pxt.create_table(
             table_path, schema=self.schema, if_exists=self.if_exists, **kwargs
@@ -116,6 +116,11 @@ def add(self, *rows: "Memory.Entry") -> None:
         self.table.insert(row_dicts)
 
     def __getattr__(self, name: str) -> Any:
+        # __getattr__ runs whenever normal lookup fails, including while __init__ is
+        # still running or after it raised. Reading self.resources through it would
+        # recurse; bail out to a plain AttributeError instead.
+        if name.startswith("_") or "resources" not in self.__dict__:
+            raise AttributeError(name)
         if hasattr(self.resources.main_table, name):
             return getattr(self.resources.main_table, name)
         raise AttributeError(
diff --git a/pixelmemory/vision.py b/pixelmemory/vision.py
index 0527e84..afead60 100644
--- a/pixelmemory/vision.py
+++ b/pixelmemory/vision.py
@@ -1,18 +1,21 @@
 import pixeltable as pxt
+import pixeltable.functions as pxtf
 from typing import Dict, Any
 
+DEFAULT_MAX_TOKENS = 1024
+
 
 def get_vision_function(provider: str):
     if provider == "openai":
         try:
-            import openai
-            from pixeltable.functions.openai import vision
+            import openai  # noqa: F401
+            from pixeltable.functions.openai import chat_completions
         except ImportError:
             raise ImportError("Please install the openai package. pip install openai.")
-        return vision
+        return chat_completions
     elif provider == "anthropic":
         try:
-            import anthropic
+            import anthropic  # noqa: F401
             from pixeltable.functions.anthropic import messages
         except ImportError:
             raise ImportError(
@@ -32,15 +35,32 @@ def prepare_vision_args(
     target_obj: pxt.Table,
 ) -> dict:
     image_col = getattr(target_obj, col_name)
+    # Both providers take the image inline as base64; b64_encode makes that explicit
+    # rather than relying on how a raw ColumnRef happens to serialize.
+    encoded = pxtf.image.b64_encode(image_col, "png")
+    model_kwargs = dict(llm_kwargs or {})
 
     if provider == "openai":
-        args = {"prompt": prompt, "image": image_col, "model": model}
-        if llm_kwargs:
-            args["model_kwargs"] = llm_kwargs
-        return args
+        return {
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": prompt},
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": "data:image/png;base64," + encoded},
+                        },
+                    ],
+                }
+            ],
+            "model": model,
+            "model_kwargs": model_kwargs or None,
+        }
 
     elif provider == "anthropic":
-        args = {
+        max_tokens = model_kwargs.pop("max_tokens", DEFAULT_MAX_TOKENS)
+        return {
             "messages": [
                 {
                     "role": "user",
@@ -50,18 +70,17 @@ def prepare_vision_args(
                             "type": "image",
                             "source": {
                                 "type": "base64",
-                                "media_type": "image/jpeg",
-                                "data": image_col,
+                                "media_type": "image/png",
+                                "data": encoded,
                             },
                         },
                     ],
                 }
             ],
             "model": model,
+            "max_tokens": max_tokens,
+            "model_kwargs": model_kwargs or None,
         }
-        if llm_kwargs:
-            args.update(llm_kwargs)
-        return args
 
     else:
         raise ValueError(f"Unsupported vision provider: {provider}")
@@ -71,19 +90,24 @@ def create_vision_computed_column(
     provider: str, col_name: str, vision_func, vision_args: dict, target_obj: pxt.Table
 ) -> str:
     description_col_name = f"{col_name}_description"
+    response_col = f"{col_name}_response"
+
+    target_obj.add_computed_column(
+        **{response_col: vision_func(**vision_args)}, if_exists="ignore"
+    )
+    response = getattr(target_obj, response_col)
 
     if provider == "openai":
-        target_obj.add_computed_column(
-            **{description_col_name: vision_func(**vision_args)}, if_exists="ignore"
-        )
+        description = response.choices[0].message.content
     elif provider == "anthropic":
-        response_col = f"{col_name}_response"
-        target_obj.add_computed_column(
-            **{response_col: vision_func(**vision_args)}, if_exists="ignore"
-        )
-        target_obj.add_computed_column(
-            **{description_col_name: getattr(target_obj, response_col).content[0].text},
-            if_exists="ignore",
-        )
+        description = response.content[0].text
+    else:
+        raise ValueError(f"Unsupported vision provider: {provider}")
+
+    # Both providers return Json, so the extracted field is Json too. An embedding
+    # index needs a String column, hence the cast.
+    target_obj.add_computed_column(
+        **{description_col_name: description.astype(pxt.String)}, if_exists="ignore"
+    )
 
     return description_col_name
diff --git a/pyproject.toml b/pyproject.toml
index 74ecc1b..4db785c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,5 +1,5 @@
 [build-system]
-requires = ["poetry-core>=1.0.0"]
+requires = ["poetry-core>=2.0.0"]
 build-backend = "poetry.core.masonry.api"
 
 [project]
@@ -8,8 +8,8 @@ version = "0.1.0"
 description = "Multimodal Memory for AI Agents and MCP."
 license = "Apache-2.0"
 readme = "README.md"
-requires-python = ">=3.10,<4.0"
-authors = [{ name = "Pixeltable, Inc.", email = "contact@pixeltable.com>" }]
+requires-python = ">=3.11"
+authors = [{ name = "Pixeltable, Inc.", email = "contact@pixeltable.com" }]
 keywords = [
     "data-science", "machine-learning", "database", "ai", "computer-vision",
     "chatbot", "ml", "artificial-intelligence", "feature-engineering", "multimodal",
@@ -22,7 +22,6 @@ classifiers = [
     "Operating System :: MacOS",
     "Operating System :: Microsoft :: Windows",
     "Operating System :: POSIX :: Linux",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
@@ -31,8 +30,10 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 dependencies = [
-    "pixeltable>=0.4.0",
-    "sentence-transformers (>=4.1.0)",
+    "pixeltable>=0.7.6,<0.8",
+    "sentence-transformers>=4.1.0",
+    # DocumentSplitterParams defaults to separators="token_limit", which needs tiktoken.
+    "tiktoken>=0.7",
 ]
 
 [project.urls]
@@ -40,30 +41,28 @@ homepage = "https://pixeltable.com/"
 repository = "https://github.com/pixeltable/pixelmemory"
 documentation = "https://docs.pixeltable.com/docs/libraries/pixelmemory"
 
+[dependency-groups]
+dev = [
+    "pytest>=8.0",
+    "ruff>=0.12.2,<0.15",
+    # Provider SDKs are optional at runtime (pixelmemory raises a clear ImportError
+    # if you use an Image context without them), but CI must cover the vision paths.
+    "openai>=1.0",
+    "anthropic>=0.40",
+]
 
-[tool.poetry]
-requires-poetry = ">=2.0"
-
-[tool.poetry.group.dev]
-optional = true
-
-[tool.poetry.group.dev.dependencies]
-coverage = "^7.4"
-# type checking
-mypy = "^1.13.0"
-# linting
-ruff = "^0.9.7"
-# mkdocs-related
-mkdocs = "^1.6.0"
-mkdocs-material = "^9.5.23"
-mkdocstrings-python = "^1.10.2"
-black = ">=24.4"  # Needed for mkdocs
+[tool.ruff]
+line-length = 88
 
-[tool.uv.sources]
-pixelmemory = { workspace = true }
+[tool.ruff.lint]
+# Pinned explicitly so CI does not change meaning when ruff changes its defaults.
+select = ["E4", "E7", "E9", "F"]
 
-[dependency-groups]
-dev = [
-    "pixelmemory",
-    "ruff>=0.12.2",
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+log_cli = false
+# The iterator and vision migrations are verified, not asserted: any surviving
+# deprecated Pixeltable call fails the suite.
+filterwarnings = [
+    "error::pixeltable.exceptions.PixeltableDeprecationWarning",
 ]
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..3520dfe
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,42 @@
+"""Keyless, offline test environment.
+
+Two things this file guarantees, and the whole suite depends on both:
+
+1. Every run gets its own throwaway Pixeltable catalog, so tests never see or
+   corrupt a developer's `~/.pixeltable`.
+2. `OPENAI_API_KEY` and `ANTHROPIC_API_KEY` are removed from the environment
+   before Pixeltable is imported. A test that needs a key fails here rather
+   than passing on the machine that happens to have one.
+
+Both must happen before `import pixeltable`, which is why they run at module
+import time and why no test module imports pixelmemory at the top level.
+"""
+
+import os
+import tempfile
+
+_CATALOG = tempfile.mkdtemp(prefix="pixelmemory-tests-")
+os.environ["PIXELTABLE_HOME"] = _CATALOG
+os.environ.pop("OPENAI_API_KEY", None)
+os.environ.pop("ANTHROPIC_API_KEY", None)
+
+import pytest  # noqa: E402
+
+# A small model, and one that is never actually loaded: the tests construct
+# schemas and never insert, so no weights are downloaded.
+EMBED_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
+
+
+@pytest.fixture(scope="session")
+def embed_model() -> str:
+    return EMBED_MODEL
+
+
+@pytest.fixture
+def namespace(request: pytest.FixtureRequest) -> str:
+    """A namespace unique to the test, so tests cannot collide in the catalog.
+
+    Lowercased because Pixeltable normalizes catalog paths to lower case.
+    """
+    name = request.node.name.replace("[", "_").replace("]", "").replace("-", "_")
+    return ("t_" + name).lower()
diff --git a/tests/test_construction.py b/tests/test_construction.py
new file mode 100644
index 0000000..bb21067
--- /dev/null
+++ b/tests/test_construction.py
@@ -0,0 +1,233 @@
+"""Construction smoke tests: no API key, no insert, no network call to a provider.
+
+Every test here builds a Memory and inspects the catalog metadata Pixeltable
+recorded. That is enough to catch the whole class of breakage this suite exists
+for: a renamed iterator kwarg, a view rebuilt on every construction, a column
+that should accept nulls and does not.
+"""
+
+import os
+
+import pytest
+
+import pixeltable as pxt
+
+from pixelmemory import Memory
+from pixelmemory.config import WhisperParams
+from pixelmemory.context import Audio, Document, Image, Text, Video
+
+
+def _make(kind, embed_model, **kw):
+    return kind(id=kind.__name__.lower(), embed_model=embed_model, **kw)
+
+
+def test_no_api_keys_in_env() -> None:
+    """The suite's own precondition, asserted rather than assumed."""
+    assert "OPENAI_API_KEY" not in os.environ
+    assert "ANTHROPIC_API_KEY" not in os.environ
+
+
+@pytest.mark.parametrize("kind", [Text, Document, Audio, Video, Image])
+def test_every_context_type_constructs(kind, embed_model, namespace) -> None:
+    """Document, Audio and Video all raised on Pixeltable 0.7.6 before this commit."""
+    memory = Memory(context=[_make(kind, embed_model)], namespace=namespace)
+    assert memory.table.get_metadata()["path"] == f"{namespace}/memory"
+
+
+def test_audio_iterator_uses_current_kwarg_names(embed_model, namespace) -> None:
+    """`iterator_call` is the printed form of what the catalog stored.
+
+    It names the kwargs verbatim, so it is the most precise available check that
+    `chunk_duration_sec`/`overlap_sec`/`min_chunk_duration_sec` really became
+    `duration`/`overlap`/`min_segment_duration`.
+    """
+    Memory(context=[Audio(id="aud", embed_model=embed_model)], namespace=namespace)
+    call = pxt.get_table(f"{namespace}.memory_aud_audio_chunks").get_metadata()[
+        "iterator_call"
+    ]
+    assert call.startswith("audio_splitter(")
+    assert "duration=30.0" in call
+    assert "min_segment_duration=" in call
+    assert "overlap=" in call
+    for gone in ("chunk_duration_sec", "overlap_sec", "min_chunk_duration_sec"):
+        assert gone not in call
+
+
+def test_document_iterator_uses_current_kwarg_names(embed_model, namespace) -> None:
+    Memory(context=[Document(id="doc", embed_model=embed_model)], namespace=namespace)
+    call = pxt.get_table(f"{namespace}.memory_doc_chunks").get_metadata()[
+        "iterator_call"
+    ]
+    assert call.startswith("document_splitter(")
+    assert "skip_tags=['nav']" in call
+    assert "html_skip_tags" not in call
+
+
+def test_audio_view_exposes_audio_segment(embed_model, namespace) -> None:
+    """The AudioSplitter output column was `audio_chunk`; it is now `audio_segment`."""
+    Memory(context=[Audio(id="aud", embed_model=embed_model)], namespace=namespace)
+    columns = pxt.get_table(f"{namespace}.memory_aud_audio_chunks").get_metadata()[
+        "columns"
+    ]
+    assert "audio_segment" in columns
+    assert "audio_chunk" not in columns
+
+
+def test_reconstruction_does_not_rebuild_views(embed_model, namespace) -> None:
+    """`if_exists='replace_force'` gave every view a new id on every construction,
+    which meant re-chunking and re-embedding everything. Ids must be stable."""
+    context = [
+        Text(id="txt", embed_model=embed_model, use_chunking=True),
+        Audio(id="aud", embed_model=embed_model),
+    ]
+    Memory(context=context, namespace=namespace)
+    paths = [
+        f"{namespace}.memory",
+        f"{namespace}.memory_txt_chunks",
+        f"{namespace}.memory_aud_audio_chunks",
+        f"{namespace}.memory_aud_sentence_chunks",
+    ]
+    before = {p: pxt.get_table(p).get_metadata()["id"] for p in paths}
+
+    Memory(context=context, namespace=namespace)
+    after = {p: pxt.get_table(p).get_metadata()["id"] for p in paths}
+
+    assert before == after
+
+
+def test_reconstruction_does_not_rebuild_embedding_index(
+    embed_model, namespace
+) -> None:
+    """The unchunked-text path used `replace_force` on `add_embedding_index`, so a
+    second construction re-embedded the whole table."""
+    context = [Text(id="txt", embed_model=embed_model)]
+    Memory(context=context, namespace=namespace)
+    table = pxt.get_table(f"{namespace}.memory")
+    version_before = table.get_metadata()["version"]
+
+    Memory(context=context, namespace=namespace)
+    assert pxt.get_table(f"{namespace}.memory").get_metadata()["version"] == (
+        version_before
+    )
+
+
+def test_openai_vision_uses_chat_completions(embed_model, namespace) -> None:
+    """`pixeltable.functions.openai.vision` is deprecated. The replacement takes a
+    messages list with an image_url block, and `llm_kwargs` go to `model_kwargs`."""
+    memory = Memory(
+        context=[
+            Image(id="img", embed_model=embed_model, llm_kwargs={"temperature": 0.2})
+        ],
+        namespace=namespace,
+    )
+    columns = memory.table.get_metadata()["columns"]
+    call = columns["img_response"]["computed_with"]
+    assert call.startswith("chat_completions(")
+    assert "'type': 'image_url'" in call
+    assert "b64_encode(img, 'png')" in call
+    assert "model_kwargs={'temperature': 0.2}" in call
+    assert (
+        columns["img_description"]["computed_with"]
+        == "img_response.choices[0].message.content.astype(String)"
+    )
+
+
+def test_anthropic_vision_passes_max_tokens(embed_model, namespace) -> None:
+    """`anthropic.messages` requires `max_tokens`, and the image must be base64
+    text rather than a raw Image ColumnRef."""
+    memory = Memory(
+        context=[
+            Image(
+                id="img",
+                provider="anthropic",
+                model="claude-sonnet-4-5",
+                embed_model=embed_model,
+                llm_kwargs={"temperature": 0.2},
+            )
+        ],
+        namespace=namespace,
+    )
+    call = memory.table.get_metadata()["columns"]["img_response"]["computed_with"]
+    assert call.startswith("messages(")
+    assert "max_tokens=1024" in call
+    assert "'data': b64_encode(img, 'png')" in call
+    assert "model_kwargs={'temperature': 0.2}" in call
+
+
+def test_whisper_kwargs_go_to_model_kwargs(embed_model, namespace) -> None:
+    """`transcriptions` is `(audio, model, model_kwargs)`. Splatting WhisperParams
+    at the top level raised."""
+    Memory(
+        context=[
+            Audio(
+                id="aud",
+                embed_model=embed_model,
+                transcription_kwargs=WhisperParams(language="en"),
+            )
+        ],
+        namespace=namespace,
+    )
+    columns = pxt.get_table(f"{namespace}.memory_aud_audio_chunks").get_metadata()[
+        "columns"
+    ]
+    assert columns["aud_transcription"]["computed_with"] == (
+        "transcriptions(audio=audio_segment, model='whisper-1', "
+        "model_kwargs={'language': 'en'})"
+    )
+
+
+def test_nested_namespace(embed_model) -> None:
+    """`pxt.list_dirs()` returns slash-separated paths, so the old
+    `namespace not in pxt.list_dirs()` check never matched a dotted namespace and
+    the second construction failed."""
+    ns = "org.team.project"
+    Memory(context=[Text(id="txt", embed_model=embed_model)], namespace=ns)
+    Memory(context=[Text(id="txt", embed_model=embed_model)], namespace=ns)
+    assert pxt.get_table(f"{ns}.memory").get_metadata()["path"] == (
+        "org/team/project/memory"
+    )
+
+
+def test_optional_column_accepts_null(namespace) -> None:
+    """Pixeltable columns are non-nullable by default since 0.7.3."""
+    memory = Memory(
+        context=[
+            Text(id="body", embed=False),
+            Text(id="note", embed=False, required=False),
+        ],
+        namespace=namespace,
+    )
+    columns = memory.table.get_metadata()["columns"]
+    assert columns["body"]["type_"] == "String"
+    assert columns["note"]["type_"] == "String | None"
+
+    memory.table.insert([{"body": "hello", "note": None}])
+    assert memory.table.count() == 1
+
+
+def test_required_column_rejects_null(namespace) -> None:
+    memory = Memory(
+        context=[Text(id="body", embed=False)],
+        namespace=namespace,
+    )
+    with pytest.raises(pxt.Error):
+        memory.table.insert([{"body": None}])
+
+
+def test_getattr_passthrough_still_works(embed_model, namespace) -> None:
+    """`memory.where(...)` / `memory.collect()` are used throughout the README."""
+    memory = Memory(context=[Text(id="txt", embed=False)], namespace=namespace)
+    assert memory.collect() is not None
+    with pytest.raises(AttributeError):
+        getattr(memory, "definitely_not_a_table_method")
+
+
+def test_failed_init_gives_attribute_error_not_recursion_error() -> None:
+    """A Memory whose __init__ never set `resources` used to turn any attribute
+    access into infinite recursion, hiding the real construction failure."""
+    broken = Memory.__new__(Memory)
+    with pytest.raises(AttributeError):
+        getattr(broken, "collect")
+    # Dunder lookups (copy, pickle, repr helpers) took the same recursive path.
+    # hasattr only swallows AttributeError, so a RecursionError still fails here.
+    assert not hasattr(broken, "__deepcopy__")
diff --git a/uv.lock b/uv.lock
index 64bbf5c..56f7156 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,226 +1,666 @@
 version = 1
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 resolution-markers = [
-    "python_full_version >= '3.12'",
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-    "python_full_version < '3.11'",
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+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'emscripten'",
+    "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
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 [[package]]
@@ -1096,71 +2028,82 @@ source = { editable = "." }
 dependencies = [
     { name = "pixeltable" },
     { name = "sentence-transformers" },
+    { name = "tiktoken" },
 ]
 
 [package.dev-dependencies]
 dev = [
-    { name = "pixelmemory" },
+    { name = "anthropic" },
+    { name = "openai" },
+    { name = "pytest" },
     { name = "ruff" },
 ]
 
 [package.metadata]
 requires-dist = [
-    { name = "pixeltable", specifier = ">=0.4.0" },
+    { name = "pixeltable", specifier = ">=0.7.6,<0.8" },
     { name = "sentence-transformers", specifier = ">=4.1.0" },
+    { name = "tiktoken", specifier = ">=0.7" },
 ]
 
 [package.metadata.requires-dev]
 dev = [
-    { name = "pixelmemory", editable = "." },
-    { name = "ruff", specifier = ">=0.12.2" },
+    { name = "anthropic", specifier = ">=0.40" },
+    { name = "openai", specifier = ">=1.0" },
+    { name = "pytest", specifier = ">=8.0" },
+    { name = "ruff", specifier = ">=0.12.2,<0.15" },
 ]
 
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-version = "0.4.2"
+version = "0.7.6"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
+    { name = "aiohttp" },
     { name = "av" },
     { name = "beautifulsoup4" },
     { name = "cloudpickle" },
+    { name = "deprecated" },
+    { name = "fasteners" },
     { name = "ftfy" },
     { name = "httpcore" },
     { name = "httpx" },
     { name = "jinja2" },
-    { name = "jmespath" },
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     { name = "lxml" },
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-    { name = "numpy", version = "2.3.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+    { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "numpy", version = "2.5.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pandas" },
+    { name = "pathspec" },
     { name = "pgvector" },
     { name = "pillow" },
     { name = "pillow-heif" },
     { name = "pixeltable-pgserver" },
     { name = "psutil" },
     { name = "psycopg", extra = ["binary"] },
-    { name = "puremagic" },
+    { name = "puremagic", version = "1.30", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "puremagic", version = "2.2.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "pyarrow" },
     { name = "pydantic" },
-    { name = "pymupdf" },
+    { name = "pypdfium2" },
     { name = "pyyaml" },
     { name = "requests" },
+    { name = "rich" },
     { name = "sqlalchemy" },
     { name = "tenacity" },
     { name = "toml" },
     { name = "tqdm" },
+    { name = "typing-extensions" },
+    { name = "tzlocal" },
 ]
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-version = "0.3.1"
+version = "0.5.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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From 494ca94548c86abd4a60edbec5baba24ddfc9314 Mon Sep 17 00:00:00 2001
From: Pierre Brunelle <pbrunelle@pixeltable.com>
Date: Thu, 10 Sep 2026 08:23:03 -0700
Subject: [PATCH 2/3] feat: add Memory.search() and Memory.views()

pixelmemory indexed your data and then left retrieval to you. Every caller
wrote the same block by hand:

    chunk_view = memory.chunk_views["report"]
    sim = chunk_view.text.similarity(query)
    results = (chunk_view.order_by(sim, asc=False).limit(3)
               .select(chunk_view.text, similarity=sim).collect())

That appeared eight times across the examples and README, and it did not
work: `chunk_views` is a list of dataclasses on `resources`, not a mapping on
`Memory`, so the first line raised AttributeError. It also used the
positional `.similarity(query)` form, deprecated since 0.5.7.

MemoryResources gains a `search_targets` list, populated at each of the seven
places an embedding index is created: the document chunk view, the audio
sentence view, chunked and unchunked strings, the direct string index, image
descriptions, and video frame captions. Video registers its frames under
"<col>_frames" so a caller can search transcript and visuals separately.

    memory.search("feline animal", limit=2)
    memory.search(query, on="report")

search() always passes idx=, because chunked text carries two indexes on one
column and a bare .similarity() there is ambiguous. views() returns the raw
table handles for queries search() does not cover, which is what the broken
`memory.chunk_views["report"]` was reaching for.

Errors name what is available rather than failing blankly: searching an
unknown context id lists the real ones, and searching a memory with no
embedding index says to pass embed=True.

Suite goes 19 -> 26. Most are metadata-only; two rank real embeddings, which
downloads a small sentence-transformers model but still needs no API key.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
---
 pixelmemory/config.py   | 22 ++++++++--
 pixelmemory/indexing.py | 61 ++++++++++++++++++++++++++++
 pixelmemory/memory.py   | 89 +++++++++++++++++++++++++++++++++++++++--
 tests/conftest.py       |  5 ++-
 tests/test_search.py    | 82 +++++++++++++++++++++++++++++++++++++
 5 files changed, 250 insertions(+), 9 deletions(-)
 create mode 100644 tests/test_search.py

diff --git a/pixelmemory/config.py b/pixelmemory/config.py
index a0b45cd..ca03942 100644
--- a/pixelmemory/config.py
+++ b/pixelmemory/config.py
@@ -66,7 +66,21 @@ class FrameView:
     table: pxt.Table
 
 
-@dataclass
-class IndexedColumn:
-    original_col: str
-    indexed_col: str
+@dataclass(frozen=True)
+class SearchTarget:
+    """One searchable place: a column carrying an embedding index.
+
+    A memory can have several. A chunked document puts its index on the chunk
+    view's `text`; an image puts one on the generated description and optionally
+    a CLIP index on the image itself; a video contributes both its transcript
+    and its frame captions. `Memory.search()` walks these.
+
+    `index_name` is recorded rather than inferred because one column can carry
+    two indexes: chunked text is indexed on the chunk view AND directly on the
+    base column, so a bare `.similarity()` there would be ambiguous.
+    """
+
+    context_id: str
+    table: pxt.Table
+    column: str
+    index_name: str
diff --git a/pixelmemory/indexing.py b/pixelmemory/indexing.py
index dfb6f8b..791ae56 100644
--- a/pixelmemory/indexing.py
+++ b/pixelmemory/indexing.py
@@ -12,6 +12,7 @@
 from .config import (
     ChunkView,
     FrameView,
+    SearchTarget,
 )
 from .vision import (
     get_vision_function,
@@ -62,6 +63,8 @@ def setup_vision_indexing(
     embed_model: pxt.Function,
     index_name: str,
     col_settings: Image,
+    memory_instance: Optional[Memory] = None,
+    context_id: Optional[str] = None,
 ) -> None:
     vision_func = get_vision_function(col_settings.provider)
     vision_args = prepare_vision_args(
@@ -83,6 +86,15 @@ def setup_vision_indexing(
         embedding=embed_model,
         if_exists="ignore",
     )
+    if memory_instance is not None:
+        memory_instance.resources.search_targets.append(
+            SearchTarget(
+                context_id=context_id,
+                table=target_obj,
+                column=description_col_name,
+                index_name=index_name,
+            )
+        )
 
     if col_settings.use_clip:
         from pixeltable.functions.huggingface import clip
@@ -127,6 +139,15 @@ def setup_document_indexing(
     chunk_view.add_embedding_index(
         column="text", idx_name=index_name, embedding=embed_model, if_exists="ignore"
     )
+    memory_instance.resources.search_targets.append(
+        SearchTarget(
+            context_id=col_name,
+            table=chunk_view,
+            column="text",
+            index_name=index_name,
+        )
+    )
+
 
 
 def setup_image_indexing(
@@ -142,6 +163,8 @@ def setup_image_indexing(
         embed_model,
         index_name,
         col_settings,
+        memory_instance=memory_instance,
+        context_id=col_name,
     )
 
 
@@ -214,6 +237,15 @@ def setup_audio_indexing(
     sentence_chunk_view.add_embedding_index(
         column="text", idx_name=index_name, embedding=embed_model, if_exists="ignore"
     )
+    memory_instance.resources.search_targets.append(
+        SearchTarget(
+            context_id=col_name,
+            table=sentence_chunk_view,
+            column="text",
+            index_name=index_name,
+        )
+    )
+
 
 
 def setup_video_indexing(
@@ -280,6 +312,8 @@ def setup_video_indexing(
         embed_model,
         index_name,
         image_col_settings,
+        memory_instance=memory_instance,
+        context_id=f"{col_name}_frames",
     )
 
 
@@ -320,12 +354,30 @@ def setup_string_indexing(
             if_exists="ignore",
         )
 
+        memory_instance.resources.search_targets.append(
+            SearchTarget(
+                context_id=col_name,
+                table=chunk_view,
+                column="text",
+                index_name=index_name,
+            )
+        )
+
         memory_instance.table.add_embedding_index(
             column=col_name,
             idx_name=f"{index_name}_direct",
             embedding=embed_model,
             if_exists="ignore",
         )
+
+        memory_instance.resources.search_targets.append(
+            SearchTarget(
+                context_id=f'{col_name}_direct',
+                table=memory_instance.table,
+                column=col_name,
+                index_name=f"{index_name}_direct",
+            )
+        )
     else:
         memory_instance.table.add_embedding_index(
             column=col_name,
@@ -333,3 +385,12 @@ def setup_string_indexing(
             embedding=embed_model,
             if_exists="ignore",
         )
+
+        memory_instance.resources.search_targets.append(
+            SearchTarget(
+                context_id=col_name,
+                table=memory_instance.table,
+                column=col_name,
+                index_name=index_name,
+            )
+        )
diff --git a/pixelmemory/memory.py b/pixelmemory/memory.py
index fb8f7dd..75f265b 100644
--- a/pixelmemory/memory.py
+++ b/pixelmemory/memory.py
@@ -4,7 +4,7 @@
 from .config import (
     ChunkView,
     FrameView,
-    IndexedColumn,
+    SearchTarget,
 )
 from .context import Context
 
@@ -19,7 +19,7 @@ class MemoryResources:
     main_table: pxt.Table
     chunk_views: List[ChunkView]
     frame_views: List[FrameView]
-    indexed_columns: List[IndexedColumn]
+    search_targets: List[SearchTarget]
 
 
 class Memory:
@@ -52,7 +52,7 @@ def __init__(
         )
 
         self.resources = MemoryResources(
-            main_table=self.table, chunk_views=[], frame_views=[], indexed_columns=[]
+            main_table=self.table, chunk_views=[], frame_views=[], search_targets=[]
         )
 
         if self.columns_to_embed:
@@ -115,6 +115,89 @@ def add(self, *rows: "Memory.Entry") -> None:
         row_dicts = [asdict(row) for row in rows]
         self.table.insert(row_dicts)
 
+    @property
+    def search_targets(self) -> List[SearchTarget]:
+        """Every indexed column this memory can be searched over."""
+        return list(self.resources.search_targets)
+
+    def views(self, context_id: Optional[str] = None) -> Dict[str, pxt.Table]:
+        """
+        The chunk and frame views backing this memory, by context id.
+
+        Returns the raw Pixeltable handles, for queries `search()` does not
+        cover. `memory.views()["report"]` is what the pre-0.2.0 examples were
+        reaching for with `memory.chunk_views["report"]`, which never resolved:
+        chunk_views is a list on `resources`, not a mapping on `Memory`.
+        """
+        out: Dict[str, pxt.Table] = {}
+        for cv in self.resources.chunk_views:
+            out[cv.name] = cv.table
+        for fv in self.resources.frame_views:
+            out[f"{fv.name}_frames"] = fv.table
+        if context_id is None:
+            return out
+        if context_id not in out:
+            raise KeyError(
+                f"No view for {context_id!r}. Available: {sorted(out)}"
+            )
+        return {context_id: out[context_id]}
+
+    def search(
+        self,
+        query: str,
+        *,
+        on: Optional[str] = None,
+        limit: int = 10,
+        min_score: Optional[float] = None,
+    ) -> List[dict]:
+        """
+        Semantic search across this memory's indexed columns.
+
+        Args:
+            query: the text to search for
+            on: restrict to one context id (e.g. "report", or "clip_frames"
+                for a video's frame captions). Default searches every target.
+            limit: maximum rows returned overall
+            min_score: drop results below this similarity
+
+        Returns dicts of {context_id, text, score}, best first.
+
+        Replaces the order_by/similarity/limit block that every caller used to
+        write by hand. `idx` is always passed, because one column can carry two
+        indexes and a bare `.similarity()` on it is ambiguous.
+        """
+        targets = self.resources.search_targets
+        if on is not None:
+            targets = [t for t in targets if t.context_id == on]
+            if not targets:
+                available = sorted({t.context_id for t in self.resources.search_targets})
+                raise KeyError(f"No search target {on!r}. Available: {available}")
+        if not targets:
+            raise RuntimeError(
+                "This memory has no embedding index, so there is nothing to "
+                "search. Pass embed=True on at least one Context."
+            )
+
+        rows: List[dict] = []
+        for t in targets:
+            col = getattr(t.table, t.column)
+            sim = col.similarity(string=query, idx=t.index_name)
+            results = (
+                t.table.order_by(sim, asc=False)
+                .limit(limit)
+                .select(text=col, score=sim)
+                .collect()
+            )
+            for r in results:
+                if min_score is not None and r["score"] < min_score:
+                    continue
+                rows.append(
+                    {"context_id": t.context_id, "text": r["text"], "score": r["score"]}
+                )
+
+        rows.sort(key=lambda r: r["score"], reverse=True)
+        return rows[:limit]
+
     def __getattr__(self, name: str) -> Any:
         # __getattr__ runs whenever normal lookup fails, including while __init__ is
         # still running or after it raised. Reading self.resources through it would
diff --git a/tests/conftest.py b/tests/conftest.py
index 3520dfe..bec8553 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -22,8 +22,9 @@
 
 import pytest  # noqa: E402
 
-# A small model, and one that is never actually loaded: the tests construct
-# schemas and never insert, so no weights are downloaded.
+# A small model. test_construction.py only builds schemas, so nothing is
+# downloaded there; the ranking tests in test_search.py do insert rows and will
+# fetch these weights once. Still no API key either way.
 EMBED_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
 
 
diff --git a/tests/test_search.py b/tests/test_search.py
new file mode 100644
index 0000000..4aa8e3a
--- /dev/null
+++ b/tests/test_search.py
@@ -0,0 +1,82 @@
+"""Tests for Memory.search() and Memory.views().
+
+Most of these are metadata-only. The two that actually rank results download a
+small sentence-transformers model but need no API key.
+"""
+
+import pytest
+
+from pixelmemory import Memory
+from pixelmemory.context import Document, Text
+
+from conftest import EMBED_MODEL
+
+
+def test_search_targets_registered(namespace):
+    m = Memory(
+        [Text(id="title", embed=False), Text(id="body", embed=True, embed_model=EMBED_MODEL)],
+        namespace=namespace,
+    )
+    targets = m.search_targets
+    assert [t.context_id for t in targets] == ["body"]
+    # idx_name is recorded, not inferred: one column can carry two indexes.
+    assert targets[0].index_name == "similarity"
+    assert targets[0].column == "body"
+
+
+def test_unembedded_memory_has_no_targets(namespace):
+    m = Memory([Text(id="body", embed=False)], namespace=namespace)
+    assert m.search_targets == []
+    with pytest.raises(RuntimeError, match="no embedding index"):
+        m.search("anything")
+
+
+def test_search_on_unknown_context_lists_the_real_ones(namespace):
+    m = Memory([Text(id="body", embed=True, embed_model=EMBED_MODEL)], namespace=namespace)
+    with pytest.raises(KeyError) as excinfo:
+        m.search("q", on="nope")
+    assert "body" in str(excinfo.value)
+
+
+def test_document_registers_its_chunk_view(namespace):
+    """A chunked document is searched on the chunk view's text, not the column."""
+    m = Memory([Document(id="report", embed=True, embed_model=EMBED_MODEL)], namespace=namespace)
+    targets = {t.context_id: t for t in m.search_targets}
+    assert "report" in targets
+    assert targets["report"].column == "text"
+    assert targets["report"].table.get_metadata()["name"].endswith("report_chunks")
+
+
+def test_views_maps_context_id_to_table(namespace):
+    """What the pre-0.2.0 examples reached for as memory.chunk_views["report"]."""
+    m = Memory([Document(id="report", embed=True, embed_model=EMBED_MODEL)], namespace=namespace)
+    views = m.views()
+    assert "report" in views
+    assert "text" in views["report"].columns()
+    with pytest.raises(KeyError, match="report"):
+        m.views("not_a_context")
+
+
+def test_search_ranks_by_similarity(namespace):
+    m = Memory(
+        [Text(id="title", embed=False), Text(id="body", embed=True, embed_model=EMBED_MODEL)],
+        namespace=namespace,
+    )
+    m.add(
+        m.Entry(title="a", body="The cat sat on the mat."),
+        m.Entry(title="b", body="Quantum chromodynamics describes the strong force."),
+        m.Entry(title="c", body="A small kitten napped in the sun."),
+    )
+    hits = m.search("feline animal", limit=2)
+    assert len(hits) == 2
+    assert all(h["context_id"] == "body" for h in hits)
+    assert "kitten" in hits[0]["text"] or "cat" in hits[0]["text"]
+    assert hits[0]["score"] >= hits[1]["score"]
+    assert "chromodynamics" not in " ".join(h["text"] for h in hits)
+
+
+def test_search_min_score_filters(namespace):
+    m = Memory([Text(id="body", embed=True, embed_model=EMBED_MODEL)], namespace=namespace)
+    m.add(m.Entry(body="The cat sat on the mat."))
+    assert m.search("cat", min_score=0.0) != []
+    assert m.search("cat", min_score=1.1) == []

From 4ebcb9ee8b87f1db9275b9214c43ef120354db58 Mon Sep 17 00:00:00 2001
From: Pierre Brunelle <pbrunelle@pixeltable.com>
Date: Thu, 10 Sep 2026 08:25:37 -0700
Subject: [PATCH 3/3] fix: repair the six examples that could not run, using
 search()

Every multimodal and integration example opened its retrieval block with
`memory.chunk_views["..."]`, which raised AttributeError: chunk_views is a
list of dataclasses on `resources`, not a mapping on Memory. So audio.py,
pdf.py, website.py, video.py, crewai_agentic_rag.py and
langchain_financial_rag_agent.py all failed at the search step.

Most collapse to one line now:

    results = memory.search(query, on="audio", limit=3)

video.py searches transcript and frame captions separately, which is what the
"<col>_frames" registration is for. text.py's `where(sim >= 0.1)` becomes
search(min_score=0.1).

Two keep a raw handle deliberately, because search() does not cover what they
do, and both say so in a comment: langchain_financial_rag_agent.py filters on
metadata as well as ranking, and images.py returns the image alongside its
caption. Both move to views() and the keyword `.similarity(string=..., idx=...)`.

The remaining positional `.similarity(query)` calls are gone, in the examples,
in the README, and in the FastAPI service. Two grep tests keep them gone: one
for positional similarity, one for chunk_views/frame_views access. They are
greps rather than execution tests because most examples need media files or a
provider key to run.

Suite 26 -> 28.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
---
 README.md                                     |  8 ++---
 examples/fastapi/memory_service.py            |  2 +-
 examples/integrations/crewai_agentic_rag.py   | 14 ++------
 .../langchain_financial_rag_agent.py          |  6 ++--
 examples/multimodal/audio.py                  | 11 ++-----
 examples/multimodal/images.py                 |  4 ++-
 examples/multimodal/pdf.py                    | 11 ++-----
 examples/multimodal/text.py                   | 14 ++------
 examples/multimodal/video.py                  | 27 ++++------------
 examples/multimodal/website.py                | 11 ++-----
 tests/test_search.py                          | 32 +++++++++++++++++++
 11 files changed, 62 insertions(+), 78 deletions(-)

diff --git a/README.md b/README.md
index 5680953..2cbbe72 100644
--- a/README.md
+++ b/README.md
@@ -69,8 +69,9 @@ entry = memory.Entry(content="I love Python programming", user_id="user_123")
 memory.add(entry)
 
 # Semantic search
-similarity = memory.content.similarity("programming languages")
-results = memory.where(similarity >= 0.5).collect()
+results = memory.search("programming languages", min_score=0.5)
+for r in results:
+    print(r["score"], r["text"])
 ```
 
 ## Architecture
@@ -111,8 +112,7 @@ entry = memory.Entry(content="Learning about AI")
 memory.add(entry)
 
 # Semantic search
-sim = memory.content.similarity("artificial intelligence")
-results = memory.where(sim >= 0.3).collect()
+results = memory.search("artificial intelligence", min_score=0.3)
 ```
 
 ### Multimodal Memory
diff --git a/examples/fastapi/memory_service.py b/examples/fastapi/memory_service.py
index 3e52727..3aabe63 100644
--- a/examples/fastapi/memory_service.py
+++ b/examples/fastapi/memory_service.py
@@ -160,7 +160,7 @@ def search_items(
         # Apply semantic search if query and search_column are provided
         if query and search_column:
             try:
-                similarity = getattr(mem, search_column).similarity(query)
+                similarity = getattr(mem, search_column).similarity(string=query)
                 q = q.order_by(similarity, asc=False)
             except AttributeError:
                 raise HTTPException(
diff --git a/examples/integrations/crewai_agentic_rag.py b/examples/integrations/crewai_agentic_rag.py
index e9f7be7..53fc652 100644
--- a/examples/integrations/crewai_agentic_rag.py
+++ b/examples/integrations/crewai_agentic_rag.py
@@ -27,19 +27,9 @@
 @tool
 def website_knowledge_tool(search_query: str, limit: int = 5) -> str:
     """Search for relevant information in the website knowledge."""
-    chunk_view = website_knowledge.chunk_views["content"]
-    sim = chunk_view.text.similarity(search_query)
-    results = (
-        chunk_view.order_by(sim, asc=False)
-        .limit(limit)
-        .select(chunk_view.text, chunk_view.doc_id, similarity=sim)
-        .collect()
-    )
+    results = website_knowledge.search(search_query, on="content", limit=limit)
     context = "\n\n".join(
-        [
-            f"Source: {r['doc_id']}\nContent: {r['text']}\nSimilarity: {r['similarity']:.4f}"
-            for r in results
-        ]
+        f"Content: {r['text']}\nSimilarity: {r['score']:.4f}" for r in results
     )
     return context
 
diff --git a/examples/integrations/langchain_financial_rag_agent.py b/examples/integrations/langchain_financial_rag_agent.py
index ddd45b7..5ced18a 100644
--- a/examples/integrations/langchain_financial_rag_agent.py
+++ b/examples/integrations/langchain_financial_rag_agent.py
@@ -91,10 +91,12 @@ def financial_chat(session_id: str, user_text: str, filters: dict = None) -> str
     print(f"💬 User says: '{user_text}'")
     rag_context = ""
     if user_text:
-        chunk_view = kb_mem.chunk_views["report"]
+        # This query filters on metadata as well as ranking, which search()
+        # does not cover, so take the raw view handle instead.
+        chunk_view = kb_mem.views("report")["report"]
 
         # Calculate similarity across all chunks
-        sim = chunk_view.text.similarity(user_text)
+        sim = chunk_view.text.similarity(string=user_text, idx="similarity")
 
         # Start with the base view
         query = chunk_view
diff --git a/examples/multimodal/audio.py b/examples/multimodal/audio.py
index f3c4708..7f51323 100644
--- a/examples/multimodal/audio.py
+++ b/examples/multimodal/audio.py
@@ -25,15 +25,8 @@
 memory.add(entry)
 
 query = "What are the key features of Pixeltable?"
-chunk_view = memory.chunk_views["audio"]
-sim = chunk_view.text.similarity(query)
-results = (
-    chunk_view.order_by(sim, asc=False)
-    .limit(3)
-    .select(chunk_view.text, similarity=sim)
-    .collect()
-)
+results = memory.search(query, on="audio", limit=3)
 
 for res in results:
-    print(f"Similarity: {res['similarity']:.4f}")
+    print(f"Similarity: {res['score']:.4f}")
     print(f"Text: {res['text']}\n")
diff --git a/examples/multimodal/images.py b/examples/multimodal/images.py
index d9fb008..63b5f09 100644
--- a/examples/multimodal/images.py
+++ b/examples/multimodal/images.py
@@ -25,7 +25,9 @@
 memory.add(entry)
 
 query = "A person on a skateboard"
-sim = memory.image_description.similarity(query)
+# This wants the image itself alongside the caption, which search() does not
+# return, so query the table directly.
+sim = memory.image_description.similarity(string=query, idx="similarity")
 results = (
     memory.order_by(sim, asc=False)
     .limit(3)
diff --git a/examples/multimodal/pdf.py b/examples/multimodal/pdf.py
index ec5008a..93d682a 100644
--- a/examples/multimodal/pdf.py
+++ b/examples/multimodal/pdf.py
@@ -25,15 +25,8 @@
 memory.add(entry)
 
 query = "What are the key growth drivers for Nvidia?"
-chunk_view = memory.chunk_views["document"]
-sim = chunk_view.text.similarity(query)
-results = (
-    chunk_view.order_by(sim, asc=False)
-    .limit(3)
-    .select(chunk_view.text, similarity=sim)
-    .collect()
-)
+results = memory.search(query, on="document", limit=3)
 
 for res in results:
-    print(f"Similarity: {res['similarity']:.4f}")
+    print(f"Similarity: {res['score']:.4f}")
     print(f"Text: {res['text']}\n")
diff --git a/examples/multimodal/text.py b/examples/multimodal/text.py
index cfb4e70..3db31fd 100644
--- a/examples/multimodal/text.py
+++ b/examples/multimodal/text.py
@@ -30,20 +30,12 @@
 
 query = "What can you do with Pixeltable?"
 
-# Direct similarity search on text_content column
-sim = memory.text_content.similarity(query)
-results = (
-    memory.where(sim >= 0.1)
-    .order_by(sim, asc=False)
-    .limit(3)
-    .select(memory.text_content, memory.memory_id, similarity=sim)
-    .collect()
-)
+results = memory.search(query, on="text_content", limit=3, min_score=0.1)
 
 print(f"Query: '{query}'")
 print("Search results:")
 for res in results:
-    print(f"Similarity: {res['similarity']:.4f}")
-    print(f"Text: {res['text_content'][:100]}...")
+    print(f"Similarity: {res['score']:.4f}")
+    print(f"Text: {res['text'][:100]}...")
     print(f"ID: {res['memory_id']}")
     print("---")
diff --git a/examples/multimodal/video.py b/examples/multimodal/video.py
index 30661f9..b285220 100644
--- a/examples/multimodal/video.py
+++ b/examples/multimodal/video.py
@@ -27,31 +27,18 @@
 query_audio = "What is the guest's perspective on AI?"
 query_visual = "A person gesturing with their hands"
 
-audio_chunk_view = memory.chunk_views["video"]
-audio_sim = audio_chunk_view.text.similarity(query_audio)
-audio_results = (
-    audio_chunk_view.order_by(audio_sim, asc=False)
-    .limit(2)
-    .select(audio_chunk_view.text, similarity=audio_sim)
-    .collect()
-)
+audio_results = memory.search(query_audio, on="video", limit=2)
 
-frame_view = memory.frame_views["video"]
-frame_sim = frame_view.frame_description.similarity(query_visual)
-visual_results = (
-    frame_view.order_by(frame_sim, asc=False)
-    .limit(2)
-    .select(frame_view.frame, frame_view.frame_description, similarity=frame_sim)
-    .collect()
-)
+# Frame captions are registered separately, so visuals can be searched on their own.
+visual_results = memory.search(query_visual, on="video_frames", limit=2)
 
 print(f"\nAudio search results for: '{query_audio}'\n")
 for res in audio_results:
-    print(f"Similarity: {res['similarity']:.4f}")
+    print(f"Similarity: {res['score']:.4f}")
     print(f"Text: {res['text']}\n")
 
 print(f"\nVisual search results for: '{query_visual}'\n")
 for res in visual_results:
-    print(f"Similarity: {res['similarity']:.4f}")
-    print(f"Frame: {res['frame']}")
-    print(f"Description: {res['frame_description']}\n")
+    print(f"Similarity: {res['score']:.4f}")
+    print(f"Description: {res['text']}\n")
+# For the frame images themselves, take the raw view: memory.views("video_frames")
diff --git a/examples/multimodal/website.py b/examples/multimodal/website.py
index ad169f6..1ce75f5 100644
--- a/examples/multimodal/website.py
+++ b/examples/multimodal/website.py
@@ -25,15 +25,8 @@
 memory.add(entry)
 
 query = "inspirational quotes about life"
-chunk_view = memory.chunk_views["website_content"]
-sim = chunk_view.text.similarity(query)
-results = (
-    chunk_view.order_by(sim, asc=False)
-    .limit(3)
-    .select(chunk_view.text, similarity=sim)
-    .collect()
-)
+results = memory.search(query, on="website_content", limit=3)
 
 for res in results:
-    print(f"Similarity: {res['similarity']:.4f}")
+    print(f"Similarity: {res['score']:.4f}")
     print(f"Text: {res['text']}\n")
diff --git a/tests/test_search.py b/tests/test_search.py
index 4aa8e3a..16cad57 100644
--- a/tests/test_search.py
+++ b/tests/test_search.py
@@ -80,3 +80,35 @@ def test_search_min_score_filters(namespace):
     m.add(m.Entry(body="The cat sat on the mat."))
     assert m.search("cat", min_score=0.0) != []
     assert m.search("cat", min_score=1.1) == []
+
+
+def test_no_positional_similarity_in_examples():
+    """Positional .similarity(query) is deprecated; the keyword form is required.
+
+    A grep test rather than an execution test because most examples need media
+    files or an API key to run.
+    """
+    import pathlib
+    import re
+
+    root = pathlib.Path(__file__).resolve().parent.parent
+    offenders = []
+    for path in list(root.glob("examples/**/*.py")) + [root / "README.md"]:
+        for i, line in enumerate(path.read_text().splitlines(), 1):
+            if re.search(r"\.similarity\((?!string=)", line):
+                offenders.append(f"{path.relative_to(root)}:{i}: {line.strip()}")
+    assert not offenders, "positional .similarity() found:\n" + "\n".join(offenders)
+
+
+def test_examples_do_not_use_chunk_views():
+    """memory.chunk_views[...] never resolved; views()/search() replace it."""
+    import pathlib
+
+    root = pathlib.Path(__file__).resolve().parent.parent
+    offenders = [
+        f"{p.relative_to(root)}:{i}"
+        for p in list(root.glob("examples/**/*.py")) + [root / "README.md"]
+        for i, line in enumerate(p.read_text().splitlines(), 1)
+        if ".chunk_views[" in line or ".frame_views[" in line
+    ]
+    assert not offenders, "stale chunk_views/frame_views access:\n" + "\n".join(offenders)