From ee101e9cb3df091ac1cd040b12f0b0dc6859fccf Mon Sep 17 00:00:00 2001
From: DK09876 <dikshant.pradhan@vectorize.io>
Date: Tue, 24 Mar 2026 06:56:45 -0700
Subject: [PATCH 1/4] feat: add LlamaIndex integration for Hindsight

Add hindsight-llamaindex package providing persistent memory tools for
LlamaIndex agents via the native BaseToolSpec pattern. Includes retain,
recall, and reflect tools, a convenience factory, global config, full
test suite, docs page, blog post, and integrations.json entry.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 .../blog/2026-03-23-llamaindex-memory.md      |  210 ++
 .../docs/sdks/integrations/llamaindex.md      |  157 ++
 hindsight-docs/src/data/integrations.json     |   10 +
 hindsight-integrations/llamaindex/README.md   |   99 +
 .../hindsight_llamaindex/__init__.py          |   48 +
 .../hindsight_llamaindex/_client.py           |   32 +
 .../llamaindex/hindsight_llamaindex/config.py |   91 +
 .../llamaindex/hindsight_llamaindex/errors.py |    7 +
 .../llamaindex/hindsight_llamaindex/tools.py  |  322 +++
 .../llamaindex/pyproject.toml                 |   54 +
 .../llamaindex/tests/__init__.py              |    0
 .../llamaindex/tests/test_manual.py           |   59 +
 .../llamaindex/tests/test_tools.py            |  413 +++
 hindsight-integrations/llamaindex/uv.lock     | 2400 +++++++++++++++++
 14 files changed, 3902 insertions(+)
 create mode 100644 hindsight-docs/blog/2026-03-23-llamaindex-memory.md
 create mode 100644 hindsight-docs/docs/sdks/integrations/llamaindex.md
 create mode 100644 hindsight-integrations/llamaindex/README.md
 create mode 100644 hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
 create mode 100644 hindsight-integrations/llamaindex/hindsight_llamaindex/_client.py
 create mode 100644 hindsight-integrations/llamaindex/hindsight_llamaindex/config.py
 create mode 100644 hindsight-integrations/llamaindex/hindsight_llamaindex/errors.py
 create mode 100644 hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
 create mode 100644 hindsight-integrations/llamaindex/pyproject.toml
 create mode 100644 hindsight-integrations/llamaindex/tests/__init__.py
 create mode 100644 hindsight-integrations/llamaindex/tests/test_manual.py
 create mode 100644 hindsight-integrations/llamaindex/tests/test_tools.py
 create mode 100644 hindsight-integrations/llamaindex/uv.lock

diff --git a/hindsight-docs/blog/2026-03-23-llamaindex-memory.md b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
new file mode 100644
index 000000000..47b5d920c
--- /dev/null
+++ b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
@@ -0,0 +1,210 @@
+---
+title: "Your LlamaIndex Agents Forget Everything Between Sessions. Here's the Fix."
+authors: [benfrank241]
+date: 2026-03-23
+tags: [llamaindex, agents, python, memory, tutorial]
+image: /img/blog/llamaindex-memory.png
+---
+
+LlamaIndex agents lose all context when a session ends. `hindsight-llamaindex` implements LlamaIndex's native `BaseToolSpec` to give agents persistent retain/recall/reflect tools -- one pip install, and your agents remember everything across conversations.
+
+<!-- truncate -->
+
+**TL;DR:**
+- LlamaIndex agents have no built-in long-term memory -- context resets every session
+- `hindsight-llamaindex` implements LlamaIndex's `BaseToolSpec` so memory tools work natively with any agent (ReAct, FunctionCalling, etc.)
+- Three tools: `retain_memory` (store), `recall_memory` (search), `reflect_on_memory` (synthesize)
+- Works with [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup) (zero infra) or self-hosted
+
+## The problem: stateless agents
+
+LlamaIndex gives you excellent tools for building agents. ReAct agents, function-calling agents, multi-step query engines -- they're all powerful within a single session.
+
+Then the session ends.
+
+Next time the user shows up, the agent starts from zero. Preferences forgotten. Decisions lost. Context gone.
+
+This matters when you build agents that serve repeat users:
+
+- A coding assistant that remembers your stack and coding preferences
+- A customer support agent that knows your order history and prior issues
+- A research assistant that builds on findings from previous sessions
+
+LlamaIndex has a `ChatMemoryBuffer` for in-session context, but it doesn't persist across sessions. For cross-session memory that actually compounds, you need something else.
+
+That's what `hindsight-llamaindex` does. It implements LlamaIndex's `BaseToolSpec` using Hindsight's memory engine, so your agents remember everything -- across sessions, across days, across weeks.
+
+---
+
+## Architecture
+
+```
+LlamaIndex Agent (ReAct, FunctionCalling, etc.)
+  └─ HindsightToolSpec (extends BaseToolSpec)
+       ├─ retain_memory()     → Hindsight retain (extract facts, entities, relationships)
+       ├─ recall_memory()     → Hindsight recall (semantic + graph + temporal retrieval)
+       └─ reflect_on_memory() → Hindsight reflect (synthesize a reasoned answer)
+```
+
+`HindsightToolSpec` extends LlamaIndex's `BaseToolSpec`. Call `to_tool_list()` and you get standard `FunctionTool` instances that any LlamaIndex agent consumes natively. No monkey-patching, no custom tool wrappers.
+
+Under the hood, Hindsight does more than store text. It extracts structured facts, identifies entities, builds a knowledge graph, and runs multi-strategy retrieval (semantic search, BM25, graph traversal, temporal ranking) with cross-encoder reranking.
+
+Your agent gets a real memory system, not a vector dump.
+
+---
+
+## Step 1 -- Start Hindsight
+
+Install and start the memory server:
+
+```bash
+pip install hindsight-all
+```
+
+```bash
+export HINDSIGHT_API_LLM_API_KEY=YOUR_OPENAI_KEY
+hindsight-api
+```
+
+This runs locally at `http://localhost:8888` with embedded Postgres, embeddings, and reranking. No external infra needed.
+
+> **Note:** You can also use [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup) and skip the self-hosted setup entirely.
+
+---
+
+## Step 2 -- Install the Integration
+
+```bash
+pip install hindsight-llamaindex
+```
+
+This pulls in `llama-index-core` and `hindsight-client` as dependencies.
+
+---
+
+## Step 3 -- Create an Agent with Memory
+
+```python
+from hindsight_client import Hindsight
+from hindsight_llamaindex import HindsightToolSpec
+from llama_index.llms.openai import OpenAI
+from llama_index.core.agent import ReActAgent
+
+client = Hindsight(base_url="http://localhost:8888")
+
+spec = HindsightToolSpec(
+    client=client,
+    bank_id="user-123",
+    tags=["source:chat"],
+    budget="mid",
+)
+tools = spec.to_tool_list()
+
+agent = ReActAgent.from_tools(
+    tools,
+    llm=OpenAI(model="gpt-4o-mini"),
+    system_prompt=(
+        "You are a helpful assistant with long-term memory. "
+        "Use retain_memory to store important facts. "
+        "Use recall_memory to search your memory before answering."
+    ),
+)
+
+# Session 1: store preferences
+agent.chat("I'm a data scientist. I use Python, SQL, and VS Code with dark mode.")
+
+# Session 2 (new agent instance, same bank_id): recall works
+agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o-mini"))
+response = agent.chat("What IDE do I use?")
+# → "You use VS Code with dark mode."
+```
+
+That's it. Three tools, one bank, persistent memory.
+
+---
+
+## Convenience Factory
+
+If you don't need full `BaseToolSpec` control, use the factory function:
+
+```python
+from hindsight_llamaindex import create_hindsight_tools
+
+tools = create_hindsight_tools(
+    client=client,
+    bank_id="user-123",
+    include_reflect=False,  # only retain + recall
+)
+
+agent = ReActAgent.from_tools(tools, llm=llm)
+```
+
+The factory wraps `HindsightToolSpec` and returns a filtered list of `FunctionTool` instances. Use `include_retain`, `include_recall`, and `include_reflect` flags to control which tools are exposed.
+
+---
+
+## Selective Tools via `to_tool_list()`
+
+LlamaIndex's `BaseToolSpec` natively supports selective tool export:
+
+```python
+spec = HindsightToolSpec(client=client, bank_id="user-123")
+
+# Only expose recall and reflect — read-only memory access
+tools = spec.to_tool_list(spec_functions=["recall_memory", "reflect_on_memory"])
+```
+
+This is useful when you want different agents to have different memory capabilities. A research agent might get all three tools, while a reporting agent only gets read-only access.
+
+---
+
+## Per-User Memory Banks
+
+Use parameterized `bank_id` to give each user their own memory:
+
+```python
+def create_agent_for_user(user_id: str) -> ReActAgent:
+    spec = HindsightToolSpec(
+        client=client,
+        bank_id=f"user-{user_id}",
+    )
+    return ReActAgent.from_tools(
+        spec.to_tool_list(),
+        llm=OpenAI(model="gpt-4o-mini"),
+    )
+```
+
+Each bank is fully isolated -- no cross-user data leakage.
+
+---
+
+## Pitfalls and Edge Cases
+
+**1. Bank must exist before use.** Call `client.create_bank(bank_id, name=...)` before your agent starts. If the bank doesn't exist, retain/recall will fail.
+
+**2. Async processing delay.** After `retain_memory`, Hindsight processes the content asynchronously (extracting facts, entities, embeddings). If you retain and immediately recall, the new memories may not be searchable yet. In practice, this takes 1-3 seconds.
+
+**3. Budget tuning.** The default `budget="mid"` balances speed and thoroughness. For latency-sensitive agents, use `"low"`. For deep analysis, use `"high"`. Budget affects how many retrieval strategies run and how much reranking happens.
+
+**4. Reflect vs Recall.** Use `recall_memory` when you need raw facts ("What IDE do I use?"). Use `reflect_on_memory` when you need synthesis ("Based on everything you know, what should I prioritize?"). Reflect is more expensive but produces reasoned answers.
+
+---
+
+## Recap
+
+- `hindsight-llamaindex` gives LlamaIndex agents persistent, compounding memory
+- It implements `BaseToolSpec`, so tools work natively with any LlamaIndex agent
+- Three tools: retain (store), recall (search), reflect (synthesize)
+- Per-user banks for memory isolation
+- Selective tool export via `spec_functions` or `include_*` flags
+
+---
+
+## Next Steps
+
+- **Try it locally**: `pip install hindsight-all hindsight-llamaindex` and run the example above
+- **Use Hindsight Cloud**: Skip self-hosting with a [free account](https://ui.hindsight.vectorize.io/signup)
+- **Run the cookbook notebook**: [LlamaIndex ReAct Agent](https://github.com/vectorize-io/hindsight-cookbook/blob/main/notebooks/08-llamaindex-react-agent.ipynb)
+- **Read the docs**: [LlamaIndex integration guide](https://docs.hindsight.vectorize.io/docs/sdks/integrations/llamaindex)
+- **Explore other integrations**: [LangGraph](/blog/langgraph-memory), [Pydantic AI](/docs/sdks/integrations/pydantic-ai), [CrewAI](/blog/crewai), [Agno](/docs/sdks/integrations/agno)
diff --git a/hindsight-docs/docs/sdks/integrations/llamaindex.md b/hindsight-docs/docs/sdks/integrations/llamaindex.md
new file mode 100644
index 000000000..e5c18d8c0
--- /dev/null
+++ b/hindsight-docs/docs/sdks/integrations/llamaindex.md
@@ -0,0 +1,157 @@
+---
+sidebar_position: 8
+---
+
+# LlamaIndex
+
+Persistent long-term memory for [LlamaIndex](https://docs.llamaindex.ai/) agents via Hindsight. Uses LlamaIndex's native `BaseToolSpec` pattern to expose retain, recall, and reflect as tools that any LlamaIndex agent can use.
+
+## Features
+
+- **Native BaseToolSpec** — Implements `BaseToolSpec` so tools work with any LlamaIndex agent (ReAct, FunctionCalling, etc.)
+- **Three Memory Operations** — retain (store), recall (search), and reflect (synthesize) as individual tools
+- **Selective Tools** — Use `to_tool_list(spec_functions=...)` or `include_retain/recall/reflect` flags to expose only the tools you need
+- **Global + Per-Call Config** — Set defaults via `configure()`, override per-call
+- **Full Hindsight Feature Set** — Tags, metadata, document grouping, fact type filtering, entity extraction, reflect schemas
+
+## Installation
+
+```bash
+pip install hindsight-llamaindex
+```
+
+## Quick Start: Tool Spec
+
+Use `HindsightToolSpec` directly for full control.
+
+```python
+from hindsight_client import Hindsight
+from hindsight_llamaindex import HindsightToolSpec
+from llama_index.llms.openai import OpenAI
+from llama_index.core.agent import ReActAgent
+
+client = Hindsight(base_url="http://localhost:8888")
+spec = HindsightToolSpec(client=client, bank_id="user-123")
+tools = spec.to_tool_list()
+
+agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
+response = agent.chat("Remember that I prefer dark mode")
+```
+
+## Quick Start: Factory Function
+
+Use `create_hindsight_tools()` for a simpler API.
+
+```python
+from hindsight_client import Hindsight
+from hindsight_llamaindex import create_hindsight_tools
+from llama_index.llms.openai import OpenAI
+from llama_index.core.agent import ReActAgent
+
+client = Hindsight(base_url="http://localhost:8888")
+tools = create_hindsight_tools(client=client, bank_id="user-123")
+
+agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
+response = agent.chat("What do you remember about me?")
+```
+
+## Selecting Tools
+
+### Via `to_tool_list()`
+
+```python
+spec = HindsightToolSpec(client=client, bank_id="user-123")
+
+# Only recall and reflect — no retain
+tools = spec.to_tool_list(spec_functions=["recall_memory", "reflect_on_memory"])
+```
+
+### Via factory flags
+
+```python
+tools = create_hindsight_tools(
+    client=client,
+    bank_id="user-123",
+    include_retain=True,
+    include_recall=True,
+    include_reflect=False,  # exclude reflect
+)
+```
+
+## Configuration
+
+### Global config
+
+Set connection and default parameters once. All subsequent tool creation will use these unless overridden.
+
+```python
+from hindsight_llamaindex import configure
+
+configure(
+    hindsight_api_url="http://localhost:8888",
+    api_key="your-api-key",  # or set HINDSIGHT_API_KEY env var
+    budget="mid",
+    tags=["source:llamaindex"],
+)
+
+# Now you can create tools without passing client/url
+tools = create_hindsight_tools(bank_id="user-123")
+```
+
+### Per-call overrides
+
+Pass parameters directly to `HindsightToolSpec()` or `create_hindsight_tools()` to override global config.
+
+## API Reference
+
+### `HindsightToolSpec()`
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `bank_id` | `str` | *required* | Hindsight memory bank to operate on |
+| `client` | `Hindsight` | `None` | Pre-configured Hindsight client |
+| `hindsight_api_url` | `str` | `None` | API URL (used if no client provided) |
+| `api_key` | `str` | `None` | API key (used if no client provided) |
+| `budget` | `str` | `None` → `"mid"` | Recall/reflect budget: `low`, `mid`, `high` |
+| `max_tokens` | `int` | `None` → `4096` | Max tokens for recall results |
+| `tags` | `list[str]` | `None` | Tags applied when storing memories |
+| `recall_tags` | `list[str]` | `None` | Tags to filter recall results |
+| `recall_tags_match` | `str` | `None` → `"any"` | Tag matching: `any`, `all`, `any_strict`, `all_strict` |
+| `retain_metadata` | `dict[str, str]` | `None` | Default metadata for retain operations |
+| `retain_document_id` | `str` | `None` | Document ID for retain (groups/upserts memories) |
+| `recall_types` | `list[str]` | `None` | Fact types: `world`, `experience`, `opinion`, `observation` |
+| `recall_include_entities` | `bool` | `False` | Include entity info in recall results |
+| `reflect_context` | `str` | `None` | Additional context for reflect |
+| `reflect_max_tokens` | `int` | `None` | Max tokens for reflect (defaults to `max_tokens`) |
+| `reflect_response_schema` | `dict` | `None` | JSON schema to constrain reflect output |
+| `reflect_tags` | `list[str]` | `None` | Tags for reflect (defaults to `recall_tags`) |
+| `reflect_tags_match` | `str` | `None` | Tag matching for reflect (defaults to `recall_tags_match`) |
+
+### `create_hindsight_tools()`
+
+Accepts all `HindsightToolSpec` parameters plus:
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `include_retain` | `bool` | `True` | Include the retain (store) tool |
+| `include_recall` | `bool` | `True` | Include the recall (search) tool |
+| `include_reflect` | `bool` | `True` | Include the reflect (synthesize) tool |
+
+### `configure()`
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `hindsight_api_url` | `str` | Production URL | Hindsight API URL |
+| `api_key` | `str` | `None` | API key (falls back to `HINDSIGHT_API_KEY` env var) |
+| `budget` | `str` | `"mid"` | Default recall budget |
+| `max_tokens` | `int` | `4096` | Default max tokens |
+| `tags` | `list[str]` | `None` | Default retain tags |
+| `recall_tags` | `list[str]` | `None` | Default recall filter tags |
+| `recall_tags_match` | `str` | `"any"` | Default tag matching mode |
+| `verbose` | `bool` | `False` | Enable verbose logging |
+
+## Requirements
+
+- Python 3.10+
+- `llama-index-core >= 0.11.0`
+- `hindsight-client >= 0.4.0`
diff --git a/hindsight-docs/src/data/integrations.json b/hindsight-docs/src/data/integrations.json
index 862d67025..e661357f6 100644
--- a/hindsight-docs/src/data/integrations.json
+++ b/hindsight-docs/src/data/integrations.json
@@ -120,6 +120,16 @@
       "link": "/sdks/integrations/langgraph",
       "icon": "/img/icons/langgraph.png"
     },
+    {
+      "id": "llamaindex",
+      "name": "LlamaIndex",
+      "description": "Add persistent memory to LlamaIndex agents via the native BaseToolSpec pattern. Retain, recall, and reflect as standard tools.",
+      "type": "official",
+      "by": "hindsight",
+      "category": "framework",
+      "link": "/sdks/integrations/llamaindex",
+      "icon": "/img/icons/llamaindex.png"
+    },
     {
       "id": "nemoclaw",
       "name": "NemoClaw",
diff --git a/hindsight-integrations/llamaindex/README.md b/hindsight-integrations/llamaindex/README.md
new file mode 100644
index 000000000..7c296c1f5
--- /dev/null
+++ b/hindsight-integrations/llamaindex/README.md
@@ -0,0 +1,99 @@
+# hindsight-llamaindex
+
+LlamaIndex integration for [Hindsight](https://github.com/vectorize-io/hindsight) — persistent long-term memory for AI agents.
+
+Provides Hindsight memory as a native LlamaIndex `BaseToolSpec`, giving agents retain/recall/reflect capabilities through LlamaIndex's standard tool interface.
+
+## Prerequisites
+
+- A running Hindsight instance ([self-hosted via Docker](https://github.com/vectorize-io/hindsight#quick-start) or [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup))
+- Python 3.10+
+
+## Installation
+
+```bash
+pip install hindsight-llamaindex
+```
+
+## Quick Start: Tool Spec
+
+Use `HindsightToolSpec` directly for full control over tool creation.
+
+```python
+from hindsight_client import Hindsight
+from hindsight_llamaindex import HindsightToolSpec
+from llama_index.llms.openai import OpenAI
+from llama_index.core.agent import ReActAgent
+
+client = Hindsight(base_url="http://localhost:8888")
+spec = HindsightToolSpec(client=client, bank_id="user-123")
+tools = spec.to_tool_list()
+
+agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
+response = agent.chat("Remember that I prefer dark mode")
+```
+
+### Selective Tools
+
+Use `to_tool_list(spec_functions=...)` to include only the tools you need:
+
+```python
+# Only recall and reflect — no retain
+tools = spec.to_tool_list(spec_functions=["recall_memory", "reflect_on_memory"])
+```
+
+## Quick Start: Factory Function
+
+Use `create_hindsight_tools()` for a simpler API with include/exclude flags.
+
+```python
+from hindsight_llamaindex import create_hindsight_tools
+
+tools = create_hindsight_tools(
+    client=client,
+    bank_id="user-123",
+    include_reflect=False,  # only retain + recall
+)
+
+agent = ReActAgent.from_tools(tools, llm=llm)
+```
+
+## Configuration
+
+### Global config
+
+```python
+from hindsight_llamaindex import configure
+
+configure(
+    hindsight_api_url="http://localhost:8888",
+    api_key="your-api-key",  # or set HINDSIGHT_API_KEY env var
+    budget="mid",
+    tags=["source:llamaindex"],
+)
+```
+
+### Per-call overrides
+
+All factory functions accept `client`, `hindsight_api_url`, and `api_key` to override the global config.
+
+| Parameter | Description | Default |
+|-----------|-------------|---------|
+| `hindsight_api_url` | Hindsight API URL | `https://api.hindsight.vectorize.io` |
+| `api_key` | API key (or `HINDSIGHT_API_KEY` env var) | `None` |
+| `budget` | Recall budget: `low`, `mid`, `high` | `mid` |
+| `max_tokens` | Max tokens for recall results | `4096` |
+| `tags` | Tags applied to retain operations | `None` |
+| `recall_tags` | Tags to filter recall results | `None` |
+| `recall_tags_match` | Tag matching: `any`, `all`, `any_strict`, `all_strict` | `any` |
+
+## Requirements
+
+- Python 3.10+
+- `llama-index-core >= 0.11.0`
+- `hindsight-client >= 0.4.0`
+
+## Documentation
+
+- [Integration docs](https://docs.hindsight.vectorize.io/docs/sdks/integrations/llamaindex)
+- [Hindsight API docs](https://docs.hindsight.vectorize.io)
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
new file mode 100644
index 000000000..ab63a28fa
--- /dev/null
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
@@ -0,0 +1,48 @@
+"""Hindsight-LlamaIndex: Persistent memory tools for LlamaIndex agents.
+
+Provides a ``BaseToolSpec`` subclass and a convenience factory that give
+LlamaIndex agents long-term memory via Hindsight's retain/recall/reflect APIs.
+
+Basic usage with the tool spec::
+
+    from hindsight_client import Hindsight
+    from hindsight_llamaindex import HindsightToolSpec
+
+    client = Hindsight(base_url="http://localhost:8888")
+    spec = HindsightToolSpec(client=client, bank_id="user-123")
+    tools = spec.to_tool_list()
+
+    # Use with a LlamaIndex agent
+    agent = ReActAgent.from_tools(tools, llm=llm)
+
+Convenience factory::
+
+    from hindsight_llamaindex import create_hindsight_tools
+
+    tools = create_hindsight_tools(
+        client=client,
+        bank_id="user-123",
+        include_reflect=False,  # only retain + recall
+    )
+"""
+
+from .config import (
+    HindsightLlamaIndexConfig,
+    configure,
+    get_config,
+    reset_config,
+)
+from .errors import HindsightError
+from .tools import HindsightToolSpec, create_hindsight_tools
+
+__version__ = "0.1.0"
+
+__all__ = [
+    "configure",
+    "get_config",
+    "reset_config",
+    "HindsightLlamaIndexConfig",
+    "HindsightError",
+    "HindsightToolSpec",
+    "create_hindsight_tools",
+]
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/_client.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/_client.py
new file mode 100644
index 000000000..fb9f66a8a
--- /dev/null
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/_client.py
@@ -0,0 +1,32 @@
+"""Shared Hindsight client resolution logic."""
+
+from typing import Any, Optional
+
+from hindsight_client import Hindsight
+
+from .config import get_config
+from .errors import HindsightError
+
+
+def resolve_client(
+    client: Optional[Hindsight],
+    hindsight_api_url: Optional[str],
+    api_key: Optional[str],
+) -> Hindsight:
+    """Resolve a Hindsight client from explicit args or global config."""
+    if client is not None:
+        return client
+
+    config = get_config()
+    url = hindsight_api_url or (config.hindsight_api_url if config else None)
+    key = api_key or (config.api_key if config else None)
+
+    if url is None:
+        raise HindsightError(
+            "No Hindsight API URL configured. Pass client= or hindsight_api_url=, or call configure() first."
+        )
+
+    kwargs: dict[str, Any] = {"base_url": url, "timeout": 30.0}
+    if key:
+        kwargs["api_key"] = key
+    return Hindsight(**kwargs)
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/config.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/config.py
new file mode 100644
index 000000000..ecec77c5c
--- /dev/null
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/config.py
@@ -0,0 +1,91 @@
+"""Global configuration for Hindsight-LlamaIndex integration."""
+
+import os
+from dataclasses import dataclass
+from typing import Optional
+
+DEFAULT_HINDSIGHT_API_URL = "https://api.hindsight.vectorize.io"
+HINDSIGHT_API_KEY_ENV = "HINDSIGHT_API_KEY"
+
+
+@dataclass
+class HindsightLlamaIndexConfig:
+    """Connection and default settings for the LlamaIndex integration.
+
+    Attributes:
+        hindsight_api_url: URL of the Hindsight API server.
+        api_key: API key for Hindsight authentication.
+        budget: Default recall budget level (low/mid/high).
+        max_tokens: Default maximum tokens for recall results.
+        tags: Default tags applied when storing memories.
+        recall_tags: Default tags to filter when searching memories.
+        recall_tags_match: Tag matching mode (any/all/any_strict/all_strict).
+        verbose: Enable verbose logging.
+    """
+
+    hindsight_api_url: str = DEFAULT_HINDSIGHT_API_URL
+    api_key: Optional[str] = None
+    budget: str = "mid"
+    max_tokens: int = 4096
+    tags: Optional[list[str]] = None
+    recall_tags: Optional[list[str]] = None
+    recall_tags_match: str = "any"
+    verbose: bool = False
+
+
+_global_config: Optional[HindsightLlamaIndexConfig] = None
+
+
+def configure(
+    hindsight_api_url: Optional[str] = None,
+    api_key: Optional[str] = None,
+    budget: str = "mid",
+    max_tokens: int = 4096,
+    tags: Optional[list[str]] = None,
+    recall_tags: Optional[list[str]] = None,
+    recall_tags_match: str = "any",
+    verbose: bool = False,
+) -> HindsightLlamaIndexConfig:
+    """Configure Hindsight connection and default settings.
+
+    Args:
+        hindsight_api_url: Hindsight API URL (default: production).
+        api_key: API key. Falls back to HINDSIGHT_API_KEY env var.
+        budget: Default recall budget (low/mid/high).
+        max_tokens: Default max tokens for recall.
+        tags: Default tags for retain operations.
+        recall_tags: Default tags to filter recall/search.
+        recall_tags_match: Tag matching mode.
+        verbose: Enable verbose logging.
+
+    Returns:
+        The configured HindsightLlamaIndexConfig.
+    """
+    global _global_config
+
+    resolved_url = hindsight_api_url or DEFAULT_HINDSIGHT_API_URL
+    resolved_key = api_key or os.environ.get(HINDSIGHT_API_KEY_ENV)
+
+    _global_config = HindsightLlamaIndexConfig(
+        hindsight_api_url=resolved_url,
+        api_key=resolved_key,
+        budget=budget,
+        max_tokens=max_tokens,
+        tags=tags,
+        recall_tags=recall_tags,
+        recall_tags_match=recall_tags_match,
+        verbose=verbose,
+    )
+
+    return _global_config
+
+
+def get_config() -> Optional[HindsightLlamaIndexConfig]:
+    """Get the current global configuration."""
+    return _global_config
+
+
+def reset_config() -> None:
+    """Reset global configuration to None."""
+    global _global_config
+    _global_config = None
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/errors.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/errors.py
new file mode 100644
index 000000000..4337f9546
--- /dev/null
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/errors.py
@@ -0,0 +1,7 @@
+"""Hindsight-LlamaIndex error types."""
+
+
+class HindsightError(Exception):
+    """Exception raised when a Hindsight memory operation fails."""
+
+    pass
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
new file mode 100644
index 000000000..9b1cc7b26
--- /dev/null
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
@@ -0,0 +1,322 @@
+"""LlamaIndex tool spec for Hindsight memory operations.
+
+Provides a ``BaseToolSpec`` subclass and a convenience factory that create
+LlamaIndex-compatible tools backed by Hindsight's retain/recall/reflect APIs.
+"""
+
+import logging
+from typing import Any, Optional
+
+from hindsight_client import Hindsight
+from llama_index.core.tools.tool_spec.base import BaseToolSpec
+
+from ._client import resolve_client
+from .config import get_config
+from .errors import HindsightError
+
+logger = logging.getLogger(__name__)
+
+
+class HindsightToolSpec(BaseToolSpec):
+    """LlamaIndex tool spec providing Hindsight memory tools.
+
+    Exposes retain, recall, and reflect as tools that LlamaIndex agents
+    can call natively via ``to_tool_list()``.
+
+    Args:
+        bank_id: The Hindsight memory bank to operate on.
+        client: Pre-configured Hindsight client (preferred).
+        hindsight_api_url: API URL (used if no client provided).
+        api_key: API key (used if no client provided).
+        budget: Recall/reflect budget level (low/mid/high).
+        max_tokens: Maximum tokens for recall results.
+        tags: Tags applied when storing memories via retain.
+        recall_tags: Tags to filter when searching memories.
+        recall_tags_match: Tag matching mode (any/all/any_strict/all_strict).
+        retain_metadata: Default metadata dict for retain operations.
+        retain_document_id: Default document_id for retain (groups/upserts memories).
+        recall_types: Fact types to filter (world, experience, opinion, observation).
+        recall_include_entities: Include entity information in recall results.
+        reflect_context: Additional context for reflect operations.
+        reflect_max_tokens: Max tokens for reflect results (defaults to max_tokens).
+        reflect_response_schema: JSON schema to constrain reflect output format.
+        reflect_tags: Tags to filter memories used in reflect (defaults to recall_tags).
+        reflect_tags_match: Tag matching for reflect (defaults to recall_tags_match).
+
+    Example::
+
+        from hindsight_client import Hindsight
+        from hindsight_llamaindex import HindsightToolSpec
+
+        client = Hindsight(base_url="http://localhost:8888")
+        spec = HindsightToolSpec(client=client, bank_id="user-123")
+        tools = spec.to_tool_list()
+
+        # Use with a LlamaIndex agent
+        agent = ReActAgent.from_tools(tools, llm=llm)
+    """
+
+    spec_functions = ["retain_memory", "recall_memory", "reflect_on_memory"]
+
+    def __init__(
+        self,
+        *,
+        bank_id: str,
+        client: Optional[Hindsight] = None,
+        hindsight_api_url: Optional[str] = None,
+        api_key: Optional[str] = None,
+        budget: Optional[str] = None,
+        max_tokens: Optional[int] = None,
+        tags: Optional[list[str]] = None,
+        recall_tags: Optional[list[str]] = None,
+        recall_tags_match: Optional[str] = None,
+        # Retain options
+        retain_metadata: Optional[dict[str, str]] = None,
+        retain_document_id: Optional[str] = None,
+        # Recall options
+        recall_types: Optional[list[str]] = None,
+        recall_include_entities: bool = False,
+        # Reflect options
+        reflect_context: Optional[str] = None,
+        reflect_max_tokens: Optional[int] = None,
+        reflect_response_schema: Optional[dict[str, Any]] = None,
+        reflect_tags: Optional[list[str]] = None,
+        reflect_tags_match: Optional[str] = None,
+    ):
+        super().__init__()
+        self._client = resolve_client(client, hindsight_api_url, api_key)
+        self._bank_id = bank_id
+
+        # Resolve effective values using None-sentinel config fallback
+        config = get_config()
+        self._tags = tags if tags is not None else (config.tags if config else None)
+        self._recall_tags = (
+            recall_tags
+            if recall_tags is not None
+            else (config.recall_tags if config else None)
+        )
+        self._recall_tags_match = (
+            recall_tags_match
+            if recall_tags_match is not None
+            else (config.recall_tags_match if config else "any")
+        )
+        self._budget = (
+            budget if budget is not None else (config.budget if config else "mid")
+        )
+        self._max_tokens = (
+            max_tokens
+            if max_tokens is not None
+            else (config.max_tokens if config else 4096)
+        )
+
+        # Retain-specific
+        self._retain_metadata = retain_metadata
+        self._retain_document_id = retain_document_id
+
+        # Recall-specific
+        self._recall_types = recall_types
+        self._recall_include_entities = recall_include_entities
+
+        # Reflect-specific
+        self._reflect_context = reflect_context
+        self._reflect_max_tokens = reflect_max_tokens
+        self._reflect_response_schema = reflect_response_schema
+        self._reflect_tags = reflect_tags
+        self._reflect_tags_match = reflect_tags_match
+
+    def retain_memory(self, content: str) -> str:
+        """Store information to long-term memory for later retrieval.
+
+        Use this to save important facts, user preferences, decisions,
+        or any information that should be remembered across conversations.
+
+        Args:
+            content: The information to store in memory.
+        """
+        try:
+            retain_kwargs: dict[str, Any] = {
+                "bank_id": self._bank_id,
+                "content": content,
+            }
+            if self._tags:
+                retain_kwargs["tags"] = self._tags
+            if self._retain_metadata:
+                retain_kwargs["metadata"] = self._retain_metadata
+            if self._retain_document_id:
+                retain_kwargs["document_id"] = self._retain_document_id
+            self._client.retain(**retain_kwargs)
+            return "Memory stored successfully."
+        except Exception as e:
+            logger.error(f"Retain failed: {e}")
+            raise HindsightError(f"Retain failed: {e}") from e
+
+    def recall_memory(self, query: str) -> str:
+        """Search long-term memory for relevant information.
+
+        Use this to find previously stored facts, preferences, or context.
+        Returns a numbered list of matching memories.
+
+        Args:
+            query: What to search for in memory.
+        """
+        try:
+            recall_kwargs: dict[str, Any] = {
+                "bank_id": self._bank_id,
+                "query": query,
+                "budget": self._budget,
+                "max_tokens": self._max_tokens,
+            }
+            if self._recall_tags:
+                recall_kwargs["tags"] = self._recall_tags
+                recall_kwargs["tags_match"] = self._recall_tags_match
+            if self._recall_types:
+                recall_kwargs["types"] = self._recall_types
+            if self._recall_include_entities:
+                recall_kwargs["include_entities"] = True
+            response = self._client.recall(**recall_kwargs)
+            if not response.results:
+                return "No relevant memories found."
+            lines = []
+            for i, result in enumerate(response.results, 1):
+                lines.append(f"{i}. {result.text}")
+            return "\n".join(lines)
+        except Exception as e:
+            logger.error(f"Recall failed: {e}")
+            raise HindsightError(f"Recall failed: {e}") from e
+
+    def reflect_on_memory(self, query: str) -> str:
+        """Synthesize a thoughtful answer from long-term memories.
+
+        Use this when you need a coherent summary or reasoned response
+        about what you know, rather than raw memory facts.
+
+        Args:
+            query: The question to reflect on using stored memories.
+        """
+        try:
+            reflect_kwargs: dict[str, Any] = {
+                "bank_id": self._bank_id,
+                "query": query,
+                "budget": self._budget,
+            }
+            if self._reflect_context:
+                reflect_kwargs["context"] = self._reflect_context
+            effective_reflect_max = self._reflect_max_tokens or self._max_tokens
+            if effective_reflect_max:
+                reflect_kwargs["max_tokens"] = effective_reflect_max
+            if self._reflect_response_schema:
+                reflect_kwargs["response_schema"] = self._reflect_response_schema
+            # Reflect tags: use reflect-specific or fall back to recall tags
+            effective_reflect_tags = (
+                self._reflect_tags
+                if self._reflect_tags is not None
+                else self._recall_tags
+            )
+            effective_reflect_tags_match = (
+                self._reflect_tags_match or self._recall_tags_match
+            )
+            if effective_reflect_tags:
+                reflect_kwargs["tags"] = effective_reflect_tags
+                reflect_kwargs["tags_match"] = effective_reflect_tags_match
+            response = self._client.reflect(**reflect_kwargs)
+            return response.text or "No relevant memories found."
+        except Exception as e:
+            logger.error(f"Reflect failed: {e}")
+            raise HindsightError(f"Reflect failed: {e}") from e
+
+
+def create_hindsight_tools(
+    *,
+    bank_id: str,
+    client: Optional[Hindsight] = None,
+    hindsight_api_url: Optional[str] = None,
+    api_key: Optional[str] = None,
+    budget: Optional[str] = None,
+    max_tokens: Optional[int] = None,
+    tags: Optional[list[str]] = None,
+    recall_tags: Optional[list[str]] = None,
+    recall_tags_match: Optional[str] = None,
+    # Retain options
+    retain_metadata: Optional[dict[str, str]] = None,
+    retain_document_id: Optional[str] = None,
+    # Recall options
+    recall_types: Optional[list[str]] = None,
+    recall_include_entities: bool = False,
+    # Reflect options
+    reflect_context: Optional[str] = None,
+    reflect_max_tokens: Optional[int] = None,
+    reflect_response_schema: Optional[dict[str, Any]] = None,
+    reflect_tags: Optional[list[str]] = None,
+    reflect_tags_match: Optional[str] = None,
+    include_retain: bool = True,
+    include_recall: bool = True,
+    include_reflect: bool = True,
+) -> list:
+    """Create Hindsight memory tools for a LlamaIndex agent.
+
+    Convenience factory that creates a ``HindsightToolSpec`` and returns
+    a filtered list of ``FunctionTool`` instances ready for use with any
+    LlamaIndex agent.
+
+    Args:
+        bank_id: The Hindsight memory bank to operate on.
+        client: Pre-configured Hindsight client (preferred).
+        hindsight_api_url: API URL (used if no client provided).
+        api_key: API key (used if no client provided).
+        budget: Recall/reflect budget level (low/mid/high).
+        max_tokens: Maximum tokens for recall results.
+        tags: Tags applied when storing memories via retain.
+        recall_tags: Tags to filter when searching memories.
+        recall_tags_match: Tag matching mode (any/all/any_strict/all_strict).
+        retain_metadata: Default metadata dict for retain operations.
+        retain_document_id: Default document_id for retain (groups/upserts memories).
+        recall_types: Fact types to filter (world, experience, opinion, observation).
+        recall_include_entities: Include entity information in recall results.
+        reflect_context: Additional context for reflect operations.
+        reflect_max_tokens: Max tokens for reflect results (defaults to max_tokens).
+        reflect_response_schema: JSON schema to constrain reflect output format.
+        reflect_tags: Tags to filter memories used in reflect (defaults to recall_tags).
+        reflect_tags_match: Tag matching for reflect (defaults to recall_tags_match).
+        include_retain: Include the retain (store) tool.
+        include_recall: Include the recall (search) tool.
+        include_reflect: Include the reflect (synthesize) tool.
+
+    Returns:
+        List of LlamaIndex FunctionTool instances.
+
+    Raises:
+        HindsightError: If no client or API URL can be resolved.
+    """
+    spec = HindsightToolSpec(
+        bank_id=bank_id,
+        client=client,
+        hindsight_api_url=hindsight_api_url,
+        api_key=api_key,
+        budget=budget,
+        max_tokens=max_tokens,
+        tags=tags,
+        recall_tags=recall_tags,
+        recall_tags_match=recall_tags_match,
+        retain_metadata=retain_metadata,
+        retain_document_id=retain_document_id,
+        recall_types=recall_types,
+        recall_include_entities=recall_include_entities,
+        reflect_context=reflect_context,
+        reflect_max_tokens=reflect_max_tokens,
+        reflect_response_schema=reflect_response_schema,
+        reflect_tags=reflect_tags,
+        reflect_tags_match=reflect_tags_match,
+    )
+
+    spec_functions: list[str] = []
+    if include_retain:
+        spec_functions.append("retain_memory")
+    if include_recall:
+        spec_functions.append("recall_memory")
+    if include_reflect:
+        spec_functions.append("reflect_on_memory")
+
+    if not spec_functions:
+        return []
+
+    return spec.to_tool_list(spec_functions=spec_functions)
diff --git a/hindsight-integrations/llamaindex/pyproject.toml b/hindsight-integrations/llamaindex/pyproject.toml
new file mode 100644
index 000000000..605e1d5dd
--- /dev/null
+++ b/hindsight-integrations/llamaindex/pyproject.toml
@@ -0,0 +1,54 @@
+[project]
+name = "hindsight-llamaindex"
+version = "0.1.0"
+description = "LlamaIndex integration for Hindsight - persistent memory tools for AI agents"
+readme = "README.md"
+requires-python = ">=3.10"
+license = { text = "MIT" }
+authors = [
+    { name = "Vectorize", email = "support@vectorize.io" }
+]
+keywords = [
+    "ai",
+    "memory",
+    "llamaindex",
+    "llama-index",
+    "agents",
+    "hindsight",
+]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+]
+
+dependencies = [
+    "llama-index-core>=0.11.0",
+    "hindsight-client>=0.4.0",
+]
+
+[project.urls]
+Homepage = "https://github.com/vectorize-io/hindsight"
+Documentation = "https://github.com/vectorize-io/hindsight/tree/main/hindsight-integrations/llamaindex"
+Repository = "https://github.com/vectorize-io/hindsight"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["hindsight_llamaindex"]
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+
+[dependency-groups]
+dev = [
+    "pytest>=9.0.2",
+    "ruff>=0.8.0",
+]
diff --git a/hindsight-integrations/llamaindex/tests/__init__.py b/hindsight-integrations/llamaindex/tests/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/hindsight-integrations/llamaindex/tests/test_manual.py b/hindsight-integrations/llamaindex/tests/test_manual.py
new file mode 100644
index 000000000..54299fb8a
--- /dev/null
+++ b/hindsight-integrations/llamaindex/tests/test_manual.py
@@ -0,0 +1,59 @@
+"""Manual integration test for Hindsight LlamaIndex tools.
+
+Requires a running Hindsight server at http://localhost:8888.
+Run with: uv run pytest tests/test_manual.py -v -s --no-header
+"""
+
+import uuid
+
+import pytest
+from hindsight_client import Hindsight
+from hindsight_llamaindex import HindsightToolSpec, create_hindsight_tools
+
+HINDSIGHT_URL = "http://localhost:8888"
+
+
+@pytest.fixture
+def client():
+    return Hindsight(base_url=HINDSIGHT_URL, timeout=30.0)
+
+
+@pytest.fixture
+def bank_id(client):
+    bid = f"test-llamaindex-{uuid.uuid4().hex[:8]}"
+    client.create_bank(bank_id=bid, name=bid)
+    return bid
+
+
+@pytest.mark.skip(reason="Requires running Hindsight server")
+class TestManualToolSpec:
+    def test_retain_and_recall_round_trip(self, client, bank_id):
+        spec = HindsightToolSpec(client=client, bank_id=bank_id)
+
+        # Retain a memory
+        result = spec.retain_memory("The user prefers dark mode in all applications.")
+        assert result == "Memory stored successfully."
+
+        # Recall it
+        result = spec.recall_memory("What are the user's UI preferences?")
+        assert "dark mode" in result.lower()
+
+    def test_create_hindsight_tools_factory(self, client, bank_id):
+        tools = create_hindsight_tools(client=client, bank_id=bank_id)
+        assert len(tools) == 3
+
+        # Find retain tool by name
+        retain_tool = next(t for t in tools if t.metadata.name == "retain_memory")
+        result = retain_tool("The user's favorite language is Python.")
+        assert "stored" in result.lower()
+
+    def test_reflect(self, client, bank_id):
+        spec = HindsightToolSpec(client=client, bank_id=bank_id)
+
+        spec.retain_memory("The user is a backend developer.")
+        spec.retain_memory("The user uses Python and Go daily.")
+        spec.retain_memory("The user prefers vim keybindings.")
+
+        result = spec.reflect_on_memory("What kind of developer is this user?")
+        assert len(result) > 0
+        assert result != "No relevant memories found."
diff --git a/hindsight-integrations/llamaindex/tests/test_tools.py b/hindsight-integrations/llamaindex/tests/test_tools.py
new file mode 100644
index 000000000..b2ed84a60
--- /dev/null
+++ b/hindsight-integrations/llamaindex/tests/test_tools.py
@@ -0,0 +1,413 @@
+"""Unit tests for Hindsight LlamaIndex tools."""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+from hindsight_llamaindex import (
+    HindsightToolSpec,
+    configure,
+    create_hindsight_tools,
+    reset_config,
+)
+from hindsight_llamaindex.errors import HindsightError
+
+
+def _mock_client():
+    """Create a mock Hindsight client with sync methods."""
+    client = MagicMock()
+    client.retain = MagicMock()
+    client.recall = MagicMock()
+    client.reflect = MagicMock()
+    return client
+
+
+def _mock_recall_response(texts: list[str]):
+    response = MagicMock()
+    results = []
+    for t in texts:
+        r = MagicMock()
+        r.text = t
+        results.append(r)
+    response.results = results
+    return response
+
+
+def _mock_reflect_response(text: str):
+    response = MagicMock()
+    response.text = text
+    return response
+
+
+def _mock_retain_response():
+    response = MagicMock()
+    response.success = True
+    return response
+
+
+class TestHindsightToolSpec:
+    def test_spec_functions_list(self):
+        assert HindsightToolSpec.spec_functions == [
+            "retain_memory",
+            "recall_memory",
+            "reflect_on_memory",
+        ]
+
+    def test_to_tool_list_returns_three_tools(self):
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list()
+        assert len(tools) == 3
+
+    def test_to_tool_list_selective(self):
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list(spec_functions=["recall_memory"])
+        assert len(tools) == 1
+        assert tools[0].metadata.name == "recall_memory"
+
+
+class TestCreateHindsightTools:
+    def setup_method(self):
+        reset_config()
+
+    def teardown_method(self):
+        reset_config()
+
+    def test_returns_three_tools_by_default(self):
+        client = _mock_client()
+        tools = create_hindsight_tools(bank_id="test", client=client)
+        assert len(tools) == 3
+
+    def test_include_retain_only(self):
+        client = _mock_client()
+        tools = create_hindsight_tools(
+            bank_id="test",
+            client=client,
+            include_retain=True,
+            include_recall=False,
+            include_reflect=False,
+        )
+        assert len(tools) == 1
+        assert tools[0].metadata.name == "retain_memory"
+
+    def test_include_recall_only(self):
+        client = _mock_client()
+        tools = create_hindsight_tools(
+            bank_id="test",
+            client=client,
+            include_retain=False,
+            include_recall=True,
+            include_reflect=False,
+        )
+        assert len(tools) == 1
+        assert tools[0].metadata.name == "recall_memory"
+
+    def test_include_reflect_only(self):
+        client = _mock_client()
+        tools = create_hindsight_tools(
+            bank_id="test",
+            client=client,
+            include_retain=False,
+            include_recall=False,
+            include_reflect=True,
+        )
+        assert len(tools) == 1
+        assert tools[0].metadata.name == "reflect_on_memory"
+
+    def test_no_tools_when_all_excluded(self):
+        client = _mock_client()
+        tools = create_hindsight_tools(
+            bank_id="test",
+            client=client,
+            include_retain=False,
+            include_recall=False,
+            include_reflect=False,
+        )
+        assert len(tools) == 0
+
+    def test_raises_without_client_or_config(self):
+        with pytest.raises(HindsightError, match="No Hindsight API URL"):
+            create_hindsight_tools(bank_id="test")
+
+    def test_falls_back_to_global_config(self):
+        configure(hindsight_api_url="http://localhost:8888")
+        with patch("hindsight_llamaindex._client.Hindsight") as mock_cls:
+            mock_cls.return_value = _mock_client()
+            tools = create_hindsight_tools(bank_id="test")
+            assert len(tools) == 3
+            mock_cls.assert_called_once_with(
+                base_url="http://localhost:8888", timeout=30.0
+            )
+
+    def test_explicit_url_overrides_config(self):
+        configure(hindsight_api_url="http://config:8888")
+        with patch("hindsight_llamaindex._client.Hindsight") as mock_cls:
+            mock_cls.return_value = _mock_client()
+            create_hindsight_tools(
+                bank_id="test", hindsight_api_url="http://explicit:9999"
+            )
+            mock_cls.assert_called_once_with(
+                base_url="http://explicit:9999", timeout=30.0
+            )
+
+
+class TestRetainTool:
+    def test_retain_stores_memory(self):
+        client = _mock_client()
+        client.retain.return_value = _mock_retain_response()
+        spec = HindsightToolSpec(bank_id="test-bank", client=client)
+        result = spec.retain_memory("The user likes Python")
+        assert result == "Memory stored successfully."
+        client.retain.assert_called_once_with(
+            bank_id="test-bank", content="The user likes Python"
+        )
+
+    def test_retain_passes_tags(self):
+        client = _mock_client()
+        client.retain.return_value = _mock_retain_response()
+        spec = HindsightToolSpec(
+            bank_id="test-bank", client=client, tags=["source:chat"]
+        )
+        spec.retain_memory("some content")
+        call_kwargs = client.retain.call_args[1]
+        assert call_kwargs["tags"] == ["source:chat"]
+
+    def test_retain_passes_metadata(self):
+        client = _mock_client()
+        client.retain.return_value = _mock_retain_response()
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            retain_metadata={"source": "chat", "session": "abc"},
+        )
+        spec.retain_memory("content")
+        call_kwargs = client.retain.call_args[1]
+        assert call_kwargs["metadata"] == {"source": "chat", "session": "abc"}
+
+    def test_retain_passes_document_id(self):
+        client = _mock_client()
+        client.retain.return_value = _mock_retain_response()
+        spec = HindsightToolSpec(
+            bank_id="test", client=client, retain_document_id="session-123"
+        )
+        spec.retain_memory("content")
+        call_kwargs = client.retain.call_args[1]
+        assert call_kwargs["document_id"] == "session-123"
+
+    def test_retain_raises_hindsight_error(self):
+        client = _mock_client()
+        client.retain.side_effect = RuntimeError("connection refused")
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        with pytest.raises(HindsightError, match="Retain failed"):
+            spec.retain_memory("content")
+
+
+class TestRecallTool:
+    def test_recall_returns_numbered_results(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(
+            ["User likes Python", "User is in NYC"]
+        )
+        spec = HindsightToolSpec(bank_id="test-bank", client=client)
+        result = spec.recall_memory("user preferences")
+        assert "1. User likes Python" in result
+        assert "2. User is in NYC" in result
+
+    def test_recall_empty_results(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response([])
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        result = spec.recall_memory("anything")
+        assert result == "No relevant memories found."
+
+    def test_recall_passes_budget_and_max_tokens(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(["fact"])
+        spec = HindsightToolSpec(
+            bank_id="test", client=client, budget="high", max_tokens=2048
+        )
+        spec.recall_memory("query")
+        call_kwargs = client.recall.call_args[1]
+        assert call_kwargs["budget"] == "high"
+        assert call_kwargs["max_tokens"] == 2048
+
+    def test_recall_passes_tags(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(["fact"])
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            recall_tags=["scope:user"],
+            recall_tags_match="all",
+        )
+        spec.recall_memory("query")
+        call_kwargs = client.recall.call_args[1]
+        assert call_kwargs["tags"] == ["scope:user"]
+        assert call_kwargs["tags_match"] == "all"
+
+    def test_recall_passes_types(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(["fact"])
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            recall_types=["world", "experience"],
+        )
+        spec.recall_memory("query")
+        call_kwargs = client.recall.call_args[1]
+        assert call_kwargs["types"] == ["world", "experience"]
+
+    def test_recall_passes_include_entities(self):
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(["fact"])
+        spec = HindsightToolSpec(
+            bank_id="test", client=client, recall_include_entities=True
+        )
+        spec.recall_memory("query")
+        call_kwargs = client.recall.call_args[1]
+        assert call_kwargs["include_entities"] is True
+
+    def test_recall_raises_hindsight_error(self):
+        client = _mock_client()
+        client.recall.side_effect = RuntimeError("timeout")
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        with pytest.raises(HindsightError, match="Recall failed"):
+            spec.recall_memory("query")
+
+
+class TestReflectTool:
+    def test_reflect_returns_text(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response(
+            "The user is a Python developer who prefers functional patterns."
+        )
+        spec = HindsightToolSpec(bank_id="test-bank", client=client)
+        result = spec.reflect_on_memory("What do you know about the user?")
+        assert (
+            result == "The user is a Python developer who prefers functional patterns."
+        )
+
+    def test_reflect_empty_returns_fallback(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("")
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        result = spec.reflect_on_memory("anything")
+        assert result == "No relevant memories found."
+
+    def test_reflect_passes_budget(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("answer")
+        spec = HindsightToolSpec(bank_id="test", client=client, budget="high")
+        spec.reflect_on_memory("query")
+        call_kwargs = client.reflect.call_args[1]
+        assert call_kwargs["budget"] == "high"
+
+    def test_reflect_passes_context(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("answer")
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            reflect_context="The user is asking about project setup",
+        )
+        spec.reflect_on_memory("query")
+        call_kwargs = client.reflect.call_args[1]
+        assert call_kwargs["context"] == "The user is asking about project setup"
+
+    def test_reflect_passes_max_tokens_and_response_schema(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("answer")
+        schema = {"type": "object", "properties": {"summary": {"type": "string"}}}
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            reflect_max_tokens=2048,
+            reflect_response_schema=schema,
+        )
+        spec.reflect_on_memory("query")
+        call_kwargs = client.reflect.call_args[1]
+        assert call_kwargs["max_tokens"] == 2048
+        assert call_kwargs["response_schema"] == schema
+
+    def test_reflect_passes_tags(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("answer")
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            reflect_tags=["scope:global"],
+            reflect_tags_match="all",
+        )
+        spec.reflect_on_memory("query")
+        call_kwargs = client.reflect.call_args[1]
+        assert call_kwargs["tags"] == ["scope:global"]
+        assert call_kwargs["tags_match"] == "all"
+
+    def test_reflect_falls_back_to_recall_tags(self):
+        client = _mock_client()
+        client.reflect.return_value = _mock_reflect_response("answer")
+        spec = HindsightToolSpec(
+            bank_id="test",
+            client=client,
+            recall_tags=["scope:user"],
+            recall_tags_match="any",
+        )
+        spec.reflect_on_memory("query")
+        call_kwargs = client.reflect.call_args[1]
+        assert call_kwargs["tags"] == ["scope:user"]
+        assert call_kwargs["tags_match"] == "any"
+
+    def test_reflect_raises_hindsight_error(self):
+        client = _mock_client()
+        client.reflect.side_effect = RuntimeError("timeout")
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        with pytest.raises(HindsightError, match="Reflect failed"):
+            spec.reflect_on_memory("query")
+
+
+class TestConfigFallback:
+    def setup_method(self):
+        reset_config()
+
+    def teardown_method(self):
+        reset_config()
+
+    def test_budget_falls_back_to_config(self):
+        configure(hindsight_api_url="http://localhost:8888")
+        with patch("hindsight_llamaindex._client.Hindsight") as mock_cls:
+            mock_instance = _mock_client()
+            mock_cls.return_value = mock_instance
+            mock_instance.recall.return_value = _mock_recall_response(["fact"])
+
+            # Configure with custom budget
+            reset_config()
+            configure(hindsight_api_url="http://localhost:8888", budget="high")
+
+            spec = HindsightToolSpec(bank_id="test")
+            spec.recall_memory("query")
+            call_kwargs = mock_instance.recall.call_args[1]
+            assert call_kwargs["budget"] == "high"
+
+    def test_explicit_budget_overrides_config(self):
+        configure(hindsight_api_url="http://localhost:8888", budget="high")
+        with patch("hindsight_llamaindex._client.Hindsight") as mock_cls:
+            mock_instance = _mock_client()
+            mock_cls.return_value = mock_instance
+            mock_instance.recall.return_value = _mock_recall_response(["fact"])
+
+            spec = HindsightToolSpec(bank_id="test", budget="low")
+            spec.recall_memory("query")
+            call_kwargs = mock_instance.recall.call_args[1]
+            assert call_kwargs["budget"] == "low"
+
+    def test_tags_fall_back_to_config(self):
+        configure(hindsight_api_url="http://localhost:8888", tags=["config:tag"])
+        with patch("hindsight_llamaindex._client.Hindsight") as mock_cls:
+            mock_instance = _mock_client()
+            mock_cls.return_value = mock_instance
+            mock_instance.retain.return_value = _mock_retain_response()
+
+            spec = HindsightToolSpec(bank_id="test")
+            spec.retain_memory("content")
+            call_kwargs = mock_instance.retain.call_args[1]
+            assert call_kwargs["tags"] == ["config:tag"]
diff --git a/hindsight-integrations/llamaindex/uv.lock b/hindsight-integrations/llamaindex/uv.lock
new file mode 100644
index 000000000..b4063ab88
--- /dev/null
+++ b/hindsight-integrations/llamaindex/uv.lock
@@ -0,0 +1,2400 @@
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+]

From 1824f6b5575740315011b4ccf168e49c665a5025 Mon Sep 17 00:00:00 2001
From: DK09876 <dikshant.pradhan@vectorize.io>
Date: Tue, 24 Mar 2026 09:19:10 -0700
Subject: [PATCH 2/4] fix: address PR review feedback for llamaindex
 integration
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- Fix ReActAgent API: from_tools() → constructor, chat() → await run()
- Add create_bank step to all quickstart examples
- Add production patterns section to docs (tags, error handling, bank lifecycle)
- Add memory scoping recommendation to README
- Add when-not-to-use section to blog post
- Add LlamaIndex compatibility tests (agent acceptance, FunctionTool.call)
- Fix self-hosted auth wording in cookbook notebook

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 .../blog/2026-03-23-llamaindex-memory.md      | 59 +++++++++++++++----
 .../docs/sdks/integrations/llamaindex.md      | 56 ++++++++++++++++--
 hindsight-integrations/llamaindex/README.md   | 23 +++++++-
 .../hindsight_llamaindex/__init__.py          |  2 +-
 .../llamaindex/hindsight_llamaindex/tools.py  |  2 +-
 .../llamaindex/tests/test_tools.py            | 59 +++++++++++++++++++
 6 files changed, 181 insertions(+), 20 deletions(-)

diff --git a/hindsight-docs/blog/2026-03-23-llamaindex-memory.md b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
index 47b5d920c..258da3d9a 100644
--- a/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
+++ b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
@@ -83,16 +83,24 @@ This pulls in `llama-index-core` and `hindsight-client` as dependencies.
 
 ---
 
-## Step 3 -- Create an Agent with Memory
+## Step 3 -- Create the Memory Bank
+
+Banks must exist before use. Create one per user:
 
 ```python
 from hindsight_client import Hindsight
+
+client = Hindsight(base_url="http://localhost:8888")
+client.create_bank("user-123", name="User 123 Memory")
+```
+
+## Step 4 -- Create an Agent with Memory
+
+```python
 from hindsight_llamaindex import HindsightToolSpec
 from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
-client = Hindsight(base_url="http://localhost:8888")
-
 spec = HindsightToolSpec(
     client=client,
     bank_id="user-123",
@@ -101,8 +109,8 @@ spec = HindsightToolSpec(
 )
 tools = spec.to_tool_list()
 
-agent = ReActAgent.from_tools(
-    tools,
+agent = ReActAgent(
+    tools=tools,
     llm=OpenAI(model="gpt-4o-mini"),
     system_prompt=(
         "You are a helpful assistant with long-term memory. "
@@ -112,11 +120,11 @@ agent = ReActAgent.from_tools(
 )
 
 # Session 1: store preferences
-agent.chat("I'm a data scientist. I use Python, SQL, and VS Code with dark mode.")
+await agent.run("I'm a data scientist. I use Python, SQL, and VS Code with dark mode.")
 
 # Session 2 (new agent instance, same bank_id): recall works
-agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o-mini"))
-response = agent.chat("What IDE do I use?")
+agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o-mini"))
+response = await agent.run("What IDE do I use?")
 # → "You use VS Code with dark mode."
 ```
 
@@ -137,7 +145,7 @@ tools = create_hindsight_tools(
     include_reflect=False,  # only retain + recall
 )
 
-agent = ReActAgent.from_tools(tools, llm=llm)
+agent = ReActAgent(tools=tools, llm=llm)
 ```
 
 The factory wraps `HindsightToolSpec` and returns a filtered list of `FunctionTool` instances. Use `include_retain`, `include_recall`, and `include_reflect` flags to control which tools are exposed.
@@ -169,8 +177,8 @@ def create_agent_for_user(user_id: str) -> ReActAgent:
         client=client,
         bank_id=f"user-{user_id}",
     )
-    return ReActAgent.from_tools(
-        spec.to_tool_list(),
+    return ReActAgent(
+        tools=spec.to_tool_list(),
         llm=OpenAI(model="gpt-4o-mini"),
     )
 ```
@@ -179,6 +187,27 @@ Each bank is fully isolated -- no cross-user data leakage.
 
 ---
 
+## Production Patterns
+
+### Memory Scoping with Tags
+
+Use tags to organize memories by source, conversation, or topic. For multi-tenant applications, use one bank per user and tags per context:
+
+```python
+spec = HindsightToolSpec(
+    client=client,
+    bank_id=f"user-{user_id}",
+    tags=["source:chat", f"session:{session_id}"],
+    recall_tags=["source:chat"],
+)
+```
+
+### Error Handling
+
+All tool methods raise `HindsightError` on failure. In production, wrap agent execution to handle memory unavailability gracefully — agents can still function without memory.
+
+---
+
 ## Pitfalls and Edge Cases
 
 **1. Bank must exist before use.** Call `client.create_bank(bank_id, name=...)` before your agent starts. If the bank doesn't exist, retain/recall will fail.
@@ -191,6 +220,14 @@ Each bank is fully isolated -- no cross-user data leakage.
 
 ---
 
+## When NOT to use this
+
+- **In-session context only** — If your agent only needs to remember things within a single conversation, LlamaIndex's `ChatMemoryBuffer` is simpler and has zero latency overhead.
+- **Document search** — If you need vector search over documents (RAG), use LlamaIndex's built-in `VectorStoreIndex`. Hindsight is a memory system for facts learned over time, not a document store.
+- **Ephemeral agents** — If each agent invocation is stateless by design (batch processing, one-shot tasks), persistent memory adds complexity without benefit.
+
+---
+
 ## Recap
 
 - `hindsight-llamaindex` gives LlamaIndex agents persistent, compounding memory
diff --git a/hindsight-docs/docs/sdks/integrations/llamaindex.md b/hindsight-docs/docs/sdks/integrations/llamaindex.md
index e5c18d8c0..0886a3c6c 100644
--- a/hindsight-docs/docs/sdks/integrations/llamaindex.md
+++ b/hindsight-docs/docs/sdks/integrations/llamaindex.md
@@ -31,11 +31,15 @@ from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
 client = Hindsight(base_url="http://localhost:8888")
+
+# Create the memory bank first (one-time setup)
+client.create_bank("user-123", name="User 123 Memory")
+
 spec = HindsightToolSpec(client=client, bank_id="user-123")
 tools = spec.to_tool_list()
 
-agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
-response = agent.chat("Remember that I prefer dark mode")
+agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+response = await agent.run("Remember that I prefer dark mode")
 ```
 
 ## Quick Start: Factory Function
@@ -51,8 +55,8 @@ from llama_index.core.agent import ReActAgent
 client = Hindsight(base_url="http://localhost:8888")
 tools = create_hindsight_tools(client=client, bank_id="user-123")
 
-agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
-response = agent.chat("What do you remember about me?")
+agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+response = await agent.run("What do you remember about me?")
 ```
 
 ## Selecting Tools
@@ -150,6 +154,50 @@ Accepts all `HindsightToolSpec` parameters plus:
 | `recall_tags_match` | `str` | `"any"` | Default tag matching mode |
 | `verbose` | `bool` | `False` | Enable verbose logging |
 
+## Production Patterns
+
+### Memory Scoping with Tags
+
+Use tags to organize memories by source, conversation, or topic:
+
+```python
+spec = HindsightToolSpec(
+    client=client,
+    bank_id="user-123",
+    tags=["source:chat", "session:abc"],        # applied to all retains
+    recall_tags=["source:chat"],                 # filter recalls to chat memories
+    recall_tags_match="any",                     # match any tag (default)
+)
+```
+
+For multi-tenant applications, use one bank per user and tags per context (e.g., `project:X`, `channel:support`).
+
+### Error Handling
+
+All tool methods raise `HindsightError` on failure. Wrap agent execution to handle memory errors gracefully:
+
+```python
+from hindsight_llamaindex import HindsightError
+
+try:
+    response = await agent.run("What do you know about me?")
+except HindsightError as e:
+    # Memory unavailable — agent can still function without memory
+    logger.warning(f"Memory error: {e}")
+```
+
+### Bank Lifecycle
+
+Banks must be created before use and should be created once per user/entity:
+
+```python
+# One-time setup (e.g., during user onboarding)
+client.create_bank(f"user-{user_id}", name=f"{user_name}'s Memory")
+
+# Subsequent agent creation — bank already exists
+spec = HindsightToolSpec(client=client, bank_id=f"user-{user_id}")
+```
+
 ## Requirements
 
 - Python 3.10+
diff --git a/hindsight-integrations/llamaindex/README.md b/hindsight-integrations/llamaindex/README.md
index 7c296c1f5..3055fd2fd 100644
--- a/hindsight-integrations/llamaindex/README.md
+++ b/hindsight-integrations/llamaindex/README.md
@@ -26,11 +26,15 @@ from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
 client = Hindsight(base_url="http://localhost:8888")
+
+# Create the memory bank first (one-time setup)
+client.create_bank("user-123", name="User 123 Memory")
+
 spec = HindsightToolSpec(client=client, bank_id="user-123")
 tools = spec.to_tool_list()
 
-agent = ReActAgent.from_tools(tools, llm=OpenAI(model="gpt-4o"))
-response = agent.chat("Remember that I prefer dark mode")
+agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+response = await agent.run("Remember that I prefer dark mode")
 ```
 
 ### Selective Tools
@@ -55,7 +59,7 @@ tools = create_hindsight_tools(
     include_reflect=False,  # only retain + recall
 )
 
-agent = ReActAgent.from_tools(tools, llm=llm)
+agent = ReActAgent(tools=tools, llm=llm)
 ```
 
 ## Configuration
@@ -87,6 +91,19 @@ All factory functions accept `client`, `hindsight_api_url`, and `api_key` to ove
 | `recall_tags` | Tags to filter recall results | `None` |
 | `recall_tags_match` | Tag matching: `any`, `all`, `any_strict`, `all_strict` | `any` |
 
+## Memory Scoping
+
+Use one bank per user/entity and tags to organize memories by context:
+
+```python
+spec = HindsightToolSpec(
+    client=client,
+    bank_id=f"user-{user_id}",           # one bank per user
+    tags=["source:chat", "project:X"],     # scope retains by context
+    recall_tags=["source:chat"],           # filter recalls to chat memories
+)
+```
+
 ## Requirements
 
 - Python 3.10+
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
index ab63a28fa..e13e7e27d 100644
--- a/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/__init__.py
@@ -13,7 +13,7 @@
     tools = spec.to_tool_list()
 
     # Use with a LlamaIndex agent
-    agent = ReActAgent.from_tools(tools, llm=llm)
+    agent = ReActAgent(tools=tools, llm=llm)
 
 Convenience factory::
 
diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
index 9b1cc7b26..822b18b5b 100644
--- a/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
@@ -53,7 +53,7 @@ class HindsightToolSpec(BaseToolSpec):
         tools = spec.to_tool_list()
 
         # Use with a LlamaIndex agent
-        agent = ReActAgent.from_tools(tools, llm=llm)
+        agent = ReActAgent(tools=tools, llm=llm)
     """
 
     spec_functions = ["retain_memory", "recall_memory", "reflect_on_memory"]
diff --git a/hindsight-integrations/llamaindex/tests/test_tools.py b/hindsight-integrations/llamaindex/tests/test_tools.py
index b2ed84a60..d6f718668 100644
--- a/hindsight-integrations/llamaindex/tests/test_tools.py
+++ b/hindsight-integrations/llamaindex/tests/test_tools.py
@@ -365,6 +365,65 @@ def test_reflect_raises_hindsight_error(self):
             spec.reflect_on_memory("query")
 
 
+class TestLlamaIndexCompatibility:
+    """Verify tools integrate correctly with LlamaIndex agent classes."""
+
+    def test_tools_have_correct_metadata(self):
+        """Each tool should have name, description, and fn_schema."""
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list()
+
+        for tool in tools:
+            assert tool.metadata.name is not None
+            assert tool.metadata.description is not None
+            assert tool.metadata.fn_schema is not None
+
+    def test_tool_names_match_spec_functions(self):
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list()
+        tool_names = {t.metadata.name for t in tools}
+        assert tool_names == {"retain_memory", "recall_memory", "reflect_on_memory"}
+
+    def test_tools_accepted_by_react_agent(self):
+        """ReActAgent should accept our tools without error."""
+        from llama_index.core.agent import ReActAgent
+        from llama_index.core.llms import MockLLM
+
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list()
+
+        # Should not raise — verifies tool format is compatible
+        agent = ReActAgent(tools=tools, llm=MockLLM())
+        assert agent is not None
+
+    def test_retain_tool_callable_via_function_tool(self):
+        """FunctionTool.call() should invoke retain_memory correctly."""
+        client = _mock_client()
+        client.retain.return_value = _mock_retain_response()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list(spec_functions=["retain_memory"])
+        tool = tools[0]
+
+        result = tool.call(content="test memory")
+        assert "stored successfully" in str(result)
+        client.retain.assert_called_once()
+
+    def test_recall_tool_callable_via_function_tool(self):
+        """FunctionTool.call() should invoke recall_memory correctly."""
+        client = _mock_client()
+        client.recall.return_value = _mock_recall_response(["some fact"])
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list(spec_functions=["recall_memory"])
+        tool = tools[0]
+
+        result = tool.call(query="test query")
+        assert "some fact" in str(result)
+        client.recall.assert_called_once()
+
+
 class TestConfigFallback:
     def setup_method(self):
         reset_config()

From c21c7f7527f6f16e8f9c4bd7d0e2d7384ab5a2ac Mon Sep 17 00:00:00 2001
From: DK09876 <dikshant.pradhan@vectorize.io>
Date: Tue, 24 Mar 2026 10:37:38 -0700
Subject: [PATCH 3/4] fix: use async client methods and asyncio.run() for
 runnable examples

- Use await client.acreate_bank() instead of sync create_bank() to
  avoid "event loop already running" errors in notebooks and async contexts
- Wrap plain Python examples in async def main() + asyncio.run(main())
  so they are copy-paste runnable as scripts
- Add Jupyter notebook tip to docs showing top-level await pattern
- Bank lifecycle example in docs now uses async acreate_bank

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 .../blog/2026-03-23-llamaindex-memory.md      | 70 ++++++++++---------
 .../docs/sdks/integrations/llamaindex.md      | 40 ++++++++---
 hindsight-integrations/llamaindex/README.md   | 19 +++--
 3 files changed, 78 insertions(+), 51 deletions(-)

diff --git a/hindsight-docs/blog/2026-03-23-llamaindex-memory.md b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
index 258da3d9a..9437fc595 100644
--- a/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
+++ b/hindsight-docs/blog/2026-03-23-llamaindex-memory.md
@@ -83,49 +83,53 @@ This pulls in `llama-index-core` and `hindsight-client` as dependencies.
 
 ---
 
-## Step 3 -- Create the Memory Bank
+## Step 3 -- Create the Memory Bank and Agent
 
-Banks must exist before use. Create one per user:
+Banks must exist before use. Since LlamaIndex agents are async, wrap everything in `asyncio.run()` for scripts (or use top-level `await` in notebooks):
 
 ```python
+import asyncio
 from hindsight_client import Hindsight
-
-client = Hindsight(base_url="http://localhost:8888")
-client.create_bank("user-123", name="User 123 Memory")
-```
-
-## Step 4 -- Create an Agent with Memory
-
-```python
 from hindsight_llamaindex import HindsightToolSpec
 from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
-spec = HindsightToolSpec(
-    client=client,
-    bank_id="user-123",
-    tags=["source:chat"],
-    budget="mid",
-)
-tools = spec.to_tool_list()
-
-agent = ReActAgent(
-    tools=tools,
-    llm=OpenAI(model="gpt-4o-mini"),
-    system_prompt=(
-        "You are a helpful assistant with long-term memory. "
-        "Use retain_memory to store important facts. "
-        "Use recall_memory to search your memory before answering."
-    ),
-)
+async def main():
+    client = Hindsight(base_url="http://localhost:8888")
+
+    # Create the memory bank (one-time setup)
+    await client.acreate_bank("user-123", name="User 123 Memory")
+
+    spec = HindsightToolSpec(
+        client=client,
+        bank_id="user-123",
+        tags=["source:chat"],
+        budget="mid",
+    )
+    tools = spec.to_tool_list()
+
+    agent = ReActAgent(
+        tools=tools,
+        llm=OpenAI(model="gpt-4o-mini"),
+        system_prompt=(
+            "You are a helpful assistant with long-term memory. "
+            "Use retain_memory to store important facts. "
+            "Use recall_memory to search your memory before answering."
+        ),
+    )
+
+    # Session 1: store preferences
+    await agent.run(
+        "I'm a data scientist. I use Python, SQL, and VS Code with dark mode."
+    )
 
-# Session 1: store preferences
-await agent.run("I'm a data scientist. I use Python, SQL, and VS Code with dark mode.")
+    # Session 2 (new agent instance, same bank_id): recall works
+    agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o-mini"))
+    response = await agent.run("What IDE do I use?")
+    # → "You use VS Code with dark mode."
+    print(response)
 
-# Session 2 (new agent instance, same bank_id): recall works
-agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o-mini"))
-response = await agent.run("What IDE do I use?")
-# → "You use VS Code with dark mode."
+asyncio.run(main())
 ```
 
 That's it. Three tools, one bank, persistent memory.
diff --git a/hindsight-docs/docs/sdks/integrations/llamaindex.md b/hindsight-docs/docs/sdks/integrations/llamaindex.md
index 0886a3c6c..77fa0570c 100644
--- a/hindsight-docs/docs/sdks/integrations/llamaindex.md
+++ b/hindsight-docs/docs/sdks/integrations/llamaindex.md
@@ -25,38 +25,56 @@ pip install hindsight-llamaindex
 Use `HindsightToolSpec` directly for full control.
 
 ```python
+import asyncio
 from hindsight_client import Hindsight
 from hindsight_llamaindex import HindsightToolSpec
 from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
-client = Hindsight(base_url="http://localhost:8888")
+async def main():
+    client = Hindsight(base_url="http://localhost:8888")
 
-# Create the memory bank first (one-time setup)
-client.create_bank("user-123", name="User 123 Memory")
+    # Create the memory bank first (one-time setup)
+    await client.acreate_bank("user-123", name="User 123 Memory")
 
-spec = HindsightToolSpec(client=client, bank_id="user-123")
-tools = spec.to_tool_list()
+    spec = HindsightToolSpec(client=client, bank_id="user-123")
+    tools = spec.to_tool_list()
+
+    agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+    response = await agent.run("Remember that I prefer dark mode")
+    print(response)
+
+asyncio.run(main())
+```
 
-agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+:::tip Jupyter Notebooks
+In notebooks, use top-level `await` directly — no `asyncio.run()` needed:
+```python
+await client.acreate_bank("user-123", name="User 123 Memory")
 response = await agent.run("Remember that I prefer dark mode")
 ```
+:::
 
 ## Quick Start: Factory Function
 
 Use `create_hindsight_tools()` for a simpler API.
 
 ```python
+import asyncio
 from hindsight_client import Hindsight
 from hindsight_llamaindex import create_hindsight_tools
 from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
-client = Hindsight(base_url="http://localhost:8888")
-tools = create_hindsight_tools(client=client, bank_id="user-123")
+async def main():
+    client = Hindsight(base_url="http://localhost:8888")
+    tools = create_hindsight_tools(client=client, bank_id="user-123")
+
+    agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+    response = await agent.run("What do you remember about me?")
+    print(response)
 
-agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
-response = await agent.run("What do you remember about me?")
+asyncio.run(main())
 ```
 
 ## Selecting Tools
@@ -192,7 +210,7 @@ Banks must be created before use and should be created once per user/entity:
 
 ```python
 # One-time setup (e.g., during user onboarding)
-client.create_bank(f"user-{user_id}", name=f"{user_name}'s Memory")
+await client.acreate_bank(f"user-{user_id}", name=f"{user_name}'s Memory")
 
 # Subsequent agent creation — bank already exists
 spec = HindsightToolSpec(client=client, bank_id=f"user-{user_id}")
diff --git a/hindsight-integrations/llamaindex/README.md b/hindsight-integrations/llamaindex/README.md
index 3055fd2fd..1194786fd 100644
--- a/hindsight-integrations/llamaindex/README.md
+++ b/hindsight-integrations/llamaindex/README.md
@@ -20,21 +20,26 @@ pip install hindsight-llamaindex
 Use `HindsightToolSpec` directly for full control over tool creation.
 
 ```python
+import asyncio
 from hindsight_client import Hindsight
 from hindsight_llamaindex import HindsightToolSpec
 from llama_index.llms.openai import OpenAI
 from llama_index.core.agent import ReActAgent
 
-client = Hindsight(base_url="http://localhost:8888")
+async def main():
+    client = Hindsight(base_url="http://localhost:8888")
 
-# Create the memory bank first (one-time setup)
-client.create_bank("user-123", name="User 123 Memory")
+    # Create the memory bank first (one-time setup)
+    await client.acreate_bank("user-123", name="User 123 Memory")
 
-spec = HindsightToolSpec(client=client, bank_id="user-123")
-tools = spec.to_tool_list()
+    spec = HindsightToolSpec(client=client, bank_id="user-123")
+    tools = spec.to_tool_list()
 
-agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
-response = await agent.run("Remember that I prefer dark mode")
+    agent = ReActAgent(tools=tools, llm=OpenAI(model="gpt-4o"))
+    response = await agent.run("Remember that I prefer dark mode")
+    print(response)
+
+asyncio.run(main())
 ```
 
 ### Selective Tools

From e4aeb8073ae31276e9276224079ca383d24146cd Mon Sep 17 00:00:00 2001
From: DK09876 <dikshant.pradhan@vectorize.io>
Date: Tue, 24 Mar 2026 11:58:50 -0700
Subject: [PATCH 4/4] fix: add async tool methods to avoid event loop conflicts

HindsightToolSpec now provides both sync and async tool implementations
using LlamaIndex's (sync_fn, async_fn) tuple pattern in spec_functions.
Async agents (ReActAgent, etc.) use aretain/arecall/areflect natively,
avoiding the "Timeout context manager should be used inside a task"
error that occurred when sync _run_async() was called from within an
active event loop.

- Add aretain_memory, arecall_memory, areflect_on_memory async methods
- Extract shared kwargs builders (_retain_kwargs, _recall_kwargs, etc.)
- spec_functions now uses tuples: [("retain_memory", "aretain_memory"), ...]
- Tests verify tools have both sync fn and async fn set
- Notebook verified end-to-end with nbclient against local Hindsight

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 .../llamaindex/hindsight_llamaindex/tools.py  | 190 ++++++++++++------
 .../llamaindex/tests/test_tools.py            |  29 ++-
 2 files changed, 150 insertions(+), 69 deletions(-)

diff --git a/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
index 822b18b5b..34dedb8a5 100644
--- a/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
+++ b/hindsight-integrations/llamaindex/hindsight_llamaindex/tools.py
@@ -56,7 +56,13 @@ class HindsightToolSpec(BaseToolSpec):
         agent = ReActAgent(tools=tools, llm=llm)
     """
 
-    spec_functions = ["retain_memory", "recall_memory", "reflect_on_memory"]
+    # Tuples provide both sync and async implementations to LlamaIndex.
+    # Async is used by async agents (ReActAgent, etc.); sync is a fallback.
+    spec_functions = [
+        ("retain_memory", "aretain_memory"),
+        ("recall_memory", "arecall_memory"),
+        ("reflect_on_memory", "areflect_on_memory"),
+    ]
 
     def __init__(
         self,
@@ -124,6 +130,70 @@ def __init__(
         self._reflect_tags = reflect_tags
         self._reflect_tags_match = reflect_tags_match
 
+    def _retain_kwargs(self, content: str) -> dict[str, Any]:
+        kwargs: dict[str, Any] = {
+            "bank_id": self._bank_id,
+            "content": content,
+        }
+        if self._tags:
+            kwargs["tags"] = self._tags
+        if self._retain_metadata:
+            kwargs["metadata"] = self._retain_metadata
+        if self._retain_document_id:
+            kwargs["document_id"] = self._retain_document_id
+        return kwargs
+
+    def _recall_kwargs(self, query: str) -> dict[str, Any]:
+        kwargs: dict[str, Any] = {
+            "bank_id": self._bank_id,
+            "query": query,
+            "budget": self._budget,
+            "max_tokens": self._max_tokens,
+        }
+        if self._recall_tags:
+            kwargs["tags"] = self._recall_tags
+            kwargs["tags_match"] = self._recall_tags_match
+        if self._recall_types:
+            kwargs["types"] = self._recall_types
+        if self._recall_include_entities:
+            kwargs["include_entities"] = True
+        return kwargs
+
+    def _reflect_kwargs(self, query: str) -> dict[str, Any]:
+        kwargs: dict[str, Any] = {
+            "bank_id": self._bank_id,
+            "query": query,
+            "budget": self._budget,
+        }
+        if self._reflect_context:
+            kwargs["context"] = self._reflect_context
+        effective_reflect_max = self._reflect_max_tokens or self._max_tokens
+        if effective_reflect_max:
+            kwargs["max_tokens"] = effective_reflect_max
+        if self._reflect_response_schema:
+            kwargs["response_schema"] = self._reflect_response_schema
+        effective_reflect_tags = (
+            self._reflect_tags if self._reflect_tags is not None else self._recall_tags
+        )
+        effective_reflect_tags_match = (
+            self._reflect_tags_match or self._recall_tags_match
+        )
+        if effective_reflect_tags:
+            kwargs["tags"] = effective_reflect_tags
+            kwargs["tags_match"] = effective_reflect_tags_match
+        return kwargs
+
+    @staticmethod
+    def _format_recall(response: Any) -> str:
+        if not response.results:
+            return "No relevant memories found."
+        lines = []
+        for i, result in enumerate(response.results, 1):
+            lines.append(f"{i}. {result.text}")
+        return "\n".join(lines)
+
+    # -- Sync methods (used outside async contexts) --
+
     def retain_memory(self, content: str) -> str:
         """Store information to long-term memory for later retrieval.
 
@@ -134,17 +204,7 @@ def retain_memory(self, content: str) -> str:
             content: The information to store in memory.
         """
         try:
-            retain_kwargs: dict[str, Any] = {
-                "bank_id": self._bank_id,
-                "content": content,
-            }
-            if self._tags:
-                retain_kwargs["tags"] = self._tags
-            if self._retain_metadata:
-                retain_kwargs["metadata"] = self._retain_metadata
-            if self._retain_document_id:
-                retain_kwargs["document_id"] = self._retain_document_id
-            self._client.retain(**retain_kwargs)
+            self._client.retain(**self._retain_kwargs(content))
             return "Memory stored successfully."
         except Exception as e:
             logger.error(f"Retain failed: {e}")
@@ -160,26 +220,8 @@ def recall_memory(self, query: str) -> str:
             query: What to search for in memory.
         """
         try:
-            recall_kwargs: dict[str, Any] = {
-                "bank_id": self._bank_id,
-                "query": query,
-                "budget": self._budget,
-                "max_tokens": self._max_tokens,
-            }
-            if self._recall_tags:
-                recall_kwargs["tags"] = self._recall_tags
-                recall_kwargs["tags_match"] = self._recall_tags_match
-            if self._recall_types:
-                recall_kwargs["types"] = self._recall_types
-            if self._recall_include_entities:
-                recall_kwargs["include_entities"] = True
-            response = self._client.recall(**recall_kwargs)
-            if not response.results:
-                return "No relevant memories found."
-            lines = []
-            for i, result in enumerate(response.results, 1):
-                lines.append(f"{i}. {result.text}")
-            return "\n".join(lines)
+            response = self._client.recall(**self._recall_kwargs(query))
+            return self._format_recall(response)
         except Exception as e:
             logger.error(f"Recall failed: {e}")
             raise HindsightError(f"Recall failed: {e}") from e
@@ -194,31 +236,57 @@ def reflect_on_memory(self, query: str) -> str:
             query: The question to reflect on using stored memories.
         """
         try:
-            reflect_kwargs: dict[str, Any] = {
-                "bank_id": self._bank_id,
-                "query": query,
-                "budget": self._budget,
-            }
-            if self._reflect_context:
-                reflect_kwargs["context"] = self._reflect_context
-            effective_reflect_max = self._reflect_max_tokens or self._max_tokens
-            if effective_reflect_max:
-                reflect_kwargs["max_tokens"] = effective_reflect_max
-            if self._reflect_response_schema:
-                reflect_kwargs["response_schema"] = self._reflect_response_schema
-            # Reflect tags: use reflect-specific or fall back to recall tags
-            effective_reflect_tags = (
-                self._reflect_tags
-                if self._reflect_tags is not None
-                else self._recall_tags
-            )
-            effective_reflect_tags_match = (
-                self._reflect_tags_match or self._recall_tags_match
-            )
-            if effective_reflect_tags:
-                reflect_kwargs["tags"] = effective_reflect_tags
-                reflect_kwargs["tags_match"] = effective_reflect_tags_match
-            response = self._client.reflect(**reflect_kwargs)
+            response = self._client.reflect(**self._reflect_kwargs(query))
+            return response.text or "No relevant memories found."
+        except Exception as e:
+            logger.error(f"Reflect failed: {e}")
+            raise HindsightError(f"Reflect failed: {e}") from e
+
+    # -- Async methods (used by async agents like ReActAgent) --
+
+    async def aretain_memory(self, content: str) -> str:
+        """Store information to long-term memory for later retrieval.
+
+        Use this to save important facts, user preferences, decisions,
+        or any information that should be remembered across conversations.
+
+        Args:
+            content: The information to store in memory.
+        """
+        try:
+            await self._client.aretain(**self._retain_kwargs(content))
+            return "Memory stored successfully."
+        except Exception as e:
+            logger.error(f"Retain failed: {e}")
+            raise HindsightError(f"Retain failed: {e}") from e
+
+    async def arecall_memory(self, query: str) -> str:
+        """Search long-term memory for relevant information.
+
+        Use this to find previously stored facts, preferences, or context.
+        Returns a numbered list of matching memories.
+
+        Args:
+            query: What to search for in memory.
+        """
+        try:
+            response = await self._client.arecall(**self._recall_kwargs(query))
+            return self._format_recall(response)
+        except Exception as e:
+            logger.error(f"Recall failed: {e}")
+            raise HindsightError(f"Recall failed: {e}") from e
+
+    async def areflect_on_memory(self, query: str) -> str:
+        """Synthesize a thoughtful answer from long-term memories.
+
+        Use this when you need a coherent summary or reasoned response
+        about what you know, rather than raw memory facts.
+
+        Args:
+            query: The question to reflect on using stored memories.
+        """
+        try:
+            response = await self._client.areflect(**self._reflect_kwargs(query))
             return response.text or "No relevant memories found."
         except Exception as e:
             logger.error(f"Reflect failed: {e}")
@@ -308,13 +376,13 @@ def create_hindsight_tools(
         reflect_tags_match=reflect_tags_match,
     )
 
-    spec_functions: list[str] = []
+    spec_functions: list[tuple[str, str]] = []
     if include_retain:
-        spec_functions.append("retain_memory")
+        spec_functions.append(("retain_memory", "aretain_memory"))
     if include_recall:
-        spec_functions.append("recall_memory")
+        spec_functions.append(("recall_memory", "arecall_memory"))
     if include_reflect:
-        spec_functions.append("reflect_on_memory")
+        spec_functions.append(("reflect_on_memory", "areflect_on_memory"))
 
     if not spec_functions:
         return []
diff --git a/hindsight-integrations/llamaindex/tests/test_tools.py b/hindsight-integrations/llamaindex/tests/test_tools.py
index d6f718668..b95589159 100644
--- a/hindsight-integrations/llamaindex/tests/test_tools.py
+++ b/hindsight-integrations/llamaindex/tests/test_tools.py
@@ -1,6 +1,6 @@
 """Unit tests for Hindsight LlamaIndex tools."""
 
-from unittest.mock import MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from hindsight_llamaindex import (
@@ -13,11 +13,14 @@
 
 
 def _mock_client():
-    """Create a mock Hindsight client with sync methods."""
+    """Create a mock Hindsight client with sync and async methods."""
     client = MagicMock()
     client.retain = MagicMock()
     client.recall = MagicMock()
     client.reflect = MagicMock()
+    client.aretain = AsyncMock()
+    client.arecall = AsyncMock()
+    client.areflect = AsyncMock()
     return client
 
 
@@ -47,9 +50,9 @@ def _mock_retain_response():
 class TestHindsightToolSpec:
     def test_spec_functions_list(self):
         assert HindsightToolSpec.spec_functions == [
-            "retain_memory",
-            "recall_memory",
-            "reflect_on_memory",
+            ("retain_memory", "aretain_memory"),
+            ("recall_memory", "arecall_memory"),
+            ("reflect_on_memory", "areflect_on_memory"),
         ]
 
     def test_to_tool_list_returns_three_tools(self):
@@ -61,7 +64,7 @@ def test_to_tool_list_returns_three_tools(self):
     def test_to_tool_list_selective(self):
         client = _mock_client()
         spec = HindsightToolSpec(bank_id="test", client=client)
-        tools = spec.to_tool_list(spec_functions=["recall_memory"])
+        tools = spec.to_tool_list(spec_functions=[("recall_memory", "arecall_memory")])
         assert len(tools) == 1
         assert tools[0].metadata.name == "recall_memory"
 
@@ -399,12 +402,22 @@ def test_tools_accepted_by_react_agent(self):
         agent = ReActAgent(tools=tools, llm=MockLLM())
         assert agent is not None
 
+    def test_tools_have_both_sync_and_async(self):
+        """Each tool should have both sync fn and async fn."""
+        client = _mock_client()
+        spec = HindsightToolSpec(bank_id="test", client=client)
+        tools = spec.to_tool_list()
+
+        for tool in tools:
+            assert tool._fn is not None, f"{tool.metadata.name} missing sync fn"
+            assert tool._async_fn is not None, f"{tool.metadata.name} missing async fn"
+
     def test_retain_tool_callable_via_function_tool(self):
         """FunctionTool.call() should invoke retain_memory correctly."""
         client = _mock_client()
         client.retain.return_value = _mock_retain_response()
         spec = HindsightToolSpec(bank_id="test", client=client)
-        tools = spec.to_tool_list(spec_functions=["retain_memory"])
+        tools = spec.to_tool_list(spec_functions=[("retain_memory", "aretain_memory")])
         tool = tools[0]
 
         result = tool.call(content="test memory")
@@ -416,7 +429,7 @@ def test_recall_tool_callable_via_function_tool(self):
         client = _mock_client()
         client.recall.return_value = _mock_recall_response(["some fact"])
         spec = HindsightToolSpec(bank_id="test", client=client)
-        tools = spec.to_tool_list(spec_functions=["recall_memory"])
+        tools = spec.to_tool_list(spec_functions=[("recall_memory", "arecall_memory")])
         tool = tools[0]
 
         result = tool.call(query="test query")