hindsight

# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Project Overview

Hindsight is an agent memory system that provides long-term memory for AI agents using biomimetic data structures. Memories are organized as:
- **World facts**: General knowledge ("The sky is blue")
- **Experience facts**: Personal experiences ("I visited Paris in 2023")
- **Mental models**: Consolidated knowledge synthesized from facts ("User prefers functional programming patterns")

## Development Commands

### Local Development (API + UI)
```bash
# Start both API server and control plane UI
./scripts/dev/start.sh
```

### API Server (Python/FastAPI)
```bash
# Start API server only (loads .env automatically)
./scripts/dev/start-api.sh

# Run all tests (parallelized with pytest-xdist)
cd hindsight-api-slim && uv run pytest tests/

# Run specific test file
cd hindsight-api-slim && uv run pytest tests/test_http_api_integration.py -v

# Run single test function
cd hindsight-api-slim && uv run pytest tests/test_retain.py::test_retain_with_chunks -v

# Lint and format
cd hindsight-api-slim && uv run ruff check .
cd hindsight-api-slim && uv run ruff format .

# Type checking (uses ty - extremely fast type checker from Astral)
cd hindsight-api-slim && uv run ty check hindsight_api/
```

### Control Plane (Next.js)
```bash
./scripts/dev/start-control-plane.sh
# Or manually:
cd hindsight-control-plane && npm run dev

# Run frontend unit tests
cd hindsight-control-plane && npm test

# Run frontend linter
cd hindsight-control-plane && npm run lint
```

### CLI Tool (Rust)
```bash
# Build CLI binary (hindsight-cli/target/release/hindsight)
cd hindsight-cli && cargo build --release

# Run CLI tests
cd hindsight-cli && cargo test
```

### System Tests (Blackbox End-to-End)
```bash
# Prerequisite: server needs pg0 installed in api-slim
(cd hindsight-api-slim && uv sync --frozen --extra embedded-db)

# Run blackbox integration tests against local embedded Postgres & stub provider
# (The stub handles LLM, embeddings, and reranking without downloading models)
cd hindsight-system-tests && uv run pytest tests/ -v
```

### Documentation Site (Docusaurus)
```bash
./scripts/dev/start-docs.sh
```


### Generating Clients/OpenAPI
```bash
# Regenerate OpenAPI spec after API changes (REQUIRED after changing endpoints)
./scripts/generate-openapi.sh

# Regenerate all client SDKs (Python, TypeScript, Rust, Go)
./scripts/generate-clients.sh
```

### Benchmarks
```bash
# Accuracy benchmarks: LoComo, LongMemEval, BEAM and the coding-agent suite come
# from AMB (vectorize-io/agent-memory-benchmark), which owns their datasets,
# judge and scoring. Run them against a local server, or any deployment with
# --api-url. See hindsight-system-evals/README.md.
cd hindsight-system-evals
uv run run-amb --dataset locomo --split locomo10
uv run run-amb --dataset longmemeval --split s -- --category single-session-user

# Performance benchmarks
./scripts/benchmarks/run-perf-test.sh                      # System perf (mock LLM + pg0)
./scripts/benchmarks/run-perf-test.sh --scale tiny          # Quick smoke test
./scripts/benchmarks/run-consolidation.sh
```

## Architecture

### Monorepo Structure
- **hindsight-api-slim/**: Core FastAPI server with memory engine (Python, uv)
- **hindsight-api/**: Published distribution package providing `hindsight-api`, `hindsight-worker`, `hindsight-local-mcp`, and `hindsight-admin` CLI entrypoints
- **hindsight-all/** & **hindsight-all-slim/**: Full and slim standalone distribution bundle packages
- **hindsight-all-npm/**: Node.js lifecycle manager embedding local daemon (published as `@vectorize-io/hindsight-all`)
- **hindsight-control-plane/**: Admin UI (Next.js, npm)
- **hindsight-cli/**: CLI tool (Rust, cargo, uses progenitor for API client)
- **hindsight-clients/**: Generated SDK clients (Python, TypeScript, Rust, Go)
- **hindsight-docs/**: Docusaurus documentation site
- **hindsight-integrations/**: Framework integrations (LiteLLM, CrewAI, LangGraph, Pydantic AI, AG2, Claude Code, coding-agents, etc.)
- **hindsight-embed/**: Embedded Python CLI and local daemon manager (connects to local API or falls back to uvx hindsight-api)
- **hindsight-system-tests/**: Blackbox end-to-end integration test suite driven through SDK against local stubs
- **hindsight-system-evals/**: End-to-end quality evaluation suites scored by independent LLM judges against real providers
- **hindsight-integration-tests/**: E2E and integration test suites requiring a running server (live API or docker-compose)
- **hindsight-extensions/**: Server extension slots (tenancy/auth, HTTP endpoints, MCP tools, operation validators, memory defense)
- **hindsight-tools/**: Published agent tools SDK (`@vectorize-io/hindsight-agent-sdk`, harness-agnostic agent knowledge tools)
- **hindsight-dev/**: Development tools and benchmarks

### Core Engine (hindsight-api-slim/hindsight_api/engine/)
- `memory_engine.py`: Main orchestrator for retain/recall/reflect operations
- `llm_wrapper.py`: LLM abstraction supporting OpenAI, Anthropic, Gemini, VertexAI, Groq, MiniMax, Ollama, LM Studio, LiteLLM, Claude Code, GitHub Copilot, DeepSeek, Fireworks, Codex (openai-codex), xAI (xai-oauth), Llama.cpp, Nous, etc. (See `hindsight-docs/docs/developer/configuration.mdx` for full provider lists)
- `embeddings.py`: Embedding generation supporting local (SentenceTransformers) and standalone/remote providers (in-process: onnx; remote: tei, openai, cohere, zeroentropy, litellm, google, etc.)
- `cross_encoder.py`: Reranking supporting local (CrossEncoder) and standalone/remote providers (in-process: flashrank, jina-mlx; remote: tei, cohere, siliconflow, zeroentropy, litellm, google, alibaba, etc.)
- `query_analyzer.py`: Query intent analysis

**retain/**: Memory ingestion pipeline
- `orchestrator.py`: Coordinates the retain flow
- `fact_extraction.py`: LLM-based fact extraction from content

**search/**: Multi-strategy retrieval
- `retrieval.py`: Main retrieval orchestrator
- `graph_retrieval.py`: Graph retrieval abstract base class
- `fusion.py`: Reciprocal rank fusion for combining results
- `reranking.py`: Cross-encoder reranking

**memories/**: The memories store, which owns every table a memory touches (`base.py` is the interface, `postgres.py` + `pg/` the default Postgres store — the only code allowed to name those tables)
- `pg/entity_resolver.py`: Entity extraction and normalization
- `pg/links.py`: Entity link creation and management
- `pg/link_expansion.py`: Link expansion graph retrieval

### API Layer (hindsight-api-slim/hindsight_api/api/)
- `http.py`: FastAPI HTTP routers for all REST endpoints
- `mcp.py`: Model Context Protocol server implementation

Main operations:
- **Retain**: Store memories, extracts facts/entities/relationships, supports document chunking
- **Recall**: Retrieve memories via 4 parallel strategies (semantic, BM25, graph, temporal) + reranking
- **Reflect**: Disposition-aware reasoning using memories and mental models
- **Knowledge Base**: Tree of auto-refreshing synthetic documents (mental models) synthesized by LLM from bank observations; searchable, exportable as markdown, and mountable read-only to the filesystem via hindsight-cli (`hindsight fs mount`)
- **Directives & Mental Models**: Manage behavioral guidelines (Directives) and consolidated facts (Mental Models)

### Database
PostgreSQL with pgvector (also supports Oracle 23ai). Schema managed via Alembic migrations in `hindsight-api-slim/hindsight_api/alembic/`. Migrations run automatically on API startup.

Key tables: `banks`, `documents`, `chunks`, `entities`, `memory_units`, `unit_entities`, `memory_links`

### Adding Database Migrations

Hindsight runs the same Alembic tree against PostgreSQL and Oracle 23ai. Each
migration file dispatches through `run_for_dialect`, which calls either
`_pg_upgrade` or `_oracle_upgrade` based on the live connection. A pytest lint
(`tests/test_migration_shape.py`) fails CI if a migration omits the dispatcher.

1. **Create a new migration file** in `hindsight-api-slim/hindsight_api/alembic/versions/`:
   - File name format: `<revision_id>_<description>.py` (e.g., `f1a2b3c4d5e6_add_new_index.py`)
   - Use a unique hex revision ID (12 chars)
   - Set `down_revision` to the previous migration's revision ID

2. **Migration template** (the `script.py.mako` template scaffolds this; fill in the bodies):
   ```python
   """Description of the migration

   Revision ID: f1a2b3c4d5e6
   Revises: <previous_revision_id>
   Create Date: YYYY-MM-DD
   """
   from collections.abc import Sequence
   from alembic import context, op

   from hindsight_api.alembic._dialect import run_for_dialect

   revision: str = "f1a2b3c4d5e6"
   down_revision: str | Sequence[str] | None = "<previous_revision_id>"
   branch_labels: str | Sequence[str] | None = None
   depends_on: str | Sequence[str] | None = None


   def _pg_schema_prefix() -> str:
       """Schema-qualifier for raw SQL on PG (multi-tenant search_path)."""
       schema = context.config.get_main_option("target_schema")
       return f'"{schema}".' if schema else ""


   def _pg_upgrade() -> None:
       schema = _pg_schema_prefix()
       op.execute(f"CREATE INDEX ... ON {schema}table_name(...)")


   def _pg_downgrade() -> None:
       schema = _pg_schema_prefix()
       op.execute(f"DROP INDEX IF EXISTS {schema}index_name")


   def _oracle_upgrade() -> None:
       # Oracle 23ai equivalent. Use op.get_bind().exec_driver_sql for forms
       # that Alembic core does not model (vector/text indexes, partitions).
       op.execute("CREATE INDEX ... ON table_name(...)")


   def _oracle_downgrade() -> None:
       op.execute("DROP INDEX IF EXISTS index_name")


   def upgrade() -> None:
       run_for_dialect(pg=_pg_upgrade, oracle=_oracle_upgrade)


   def downgrade() -> None:
       run_for_dialect(pg=_pg_downgrade, oracle=_oracle_downgrade)
   ```

   **Dialect-only migrations.** If a change genuinely doesn't apply to one
   dialect (e.g. enabling `pg_trgm` is PG-only), omit the unused slot:
   ```python
   def upgrade() -> None:
       run_for_dialect(pg=_pg_upgrade)  # oracle slot intentionally absent → no-op
   ```
   Make the asymmetry deliberate. Don't leave an Oracle slot empty just because
   you didn't think about it — copy-pasting a PG migration without the Oracle
   half is exactly how schemas drift.

3. **Run migrations locally**:
   ```bash
   # Set database URL and run migrations for the base schema plus all tenants
   uv run hindsight-admin run-db-migration

   # Run on a specific tenant schema
   uv run hindsight-admin run-db-migration --schema tenant_xyz
   ```

## Key Conventions

### Code Quality

**Before writing code, read `.claude/skills/code-review/SKILL.md`** for the full coding standards (Python style, type safety, TypeScript style, general principles).

**Always run the lint script after making Python or TypeScript/Node changes:**
```bash
./scripts/hooks/lint.sh
```

Dead-code detection runs in CI (the `check-unused-code` job) at two levels:
- **Blocking:** unused imports (ruff `F401`) and variables (`F841`) — `lint.sh` auto-removes
  them and `verify-generated-files` fails on any leftover diff; and **knip** for orphaned
  control-plane files / unused (or unlisted) `package.json` dependencies.
- **Advisory:** whole unused Python functions (vulture) and unused control-plane *exports*
  (the shadcn/ui surface is kept on purpose) — surfaced, not gated.

Run both locally with:
```bash
./scripts/hooks/check-unused.sh
```

**After completing any implementation work, run `/code-review`** to verify your changes against project standards (missing tests, dead code, type safety, etc.). Fix any "must fix" issues before considering the task done.

**MANDATORY: Run `/code-review` before pushing code or creating a pull request.** Do not push or create a PR until all "must fix" issues are resolved.

### Testing

Most tests are deterministic (MockLLM, pure functions) — assert directly.

**A user-facing capability needs a blackbox story in `hindsight-system-tests/`.**
Those drive a real `hindsight-api` process through the published Python client — no
engine access, no SQL — and exist to catch the bugs the ~500-file api-slim suite
structurally cannot: the ones in the seam *between* steps, where consolidation wipes
the facts under it or a transfer drops its evidence. Add a story when a change adds a
capability someone can name, or makes two existing capabilities meet for the first
time; the composition is the part nothing else tests. See that package's README, and
`.claude/skills/code-review/SKILL.md` step 6b for the review checklist.

**Tests that verify LLM behaviour use a real LLM + an LLM-as-judge.** When the thing under test is *how the model interprets a prompt* (classification, attribution, dimension preservation, instruction-following), MockLLM can't simulate it and exact string/enum asserts flake across providers and runs. Use this pattern instead:

1. Mark the test module `pytestmark = pytest.mark.hs_llm_core` (single-provider; CI runs it in the core-LLM job). Use `hs_llm_mat` only for provider-matrix acceptance tests.
2. Call the real pipeline (`LLMConfig.from_env()`, `_get_raw_config()`), e.g. `extract_facts_from_text(...)`.
3. Assert with the judge, not string matching:
   ```python
   from tests.llm_judge import assert_meets_criteria
   facts_summary = "\n".join(f"- [{f.fact_type}] {f.fact}" for f in facts)
   await assert_meets_criteria(
       response=facts_summary,
       criteria="The first-person user statements are classified 'world' and attributed to the user, not the agent.",
       context="What the input said and who was speaking.",
   )
   ```

Rules of thumb:
- **Judge anything non-deterministic** — including `fact_type` classification and speaker attribution. Do NOT hard-assert `fact_type == "..."`; pass a `[fact_type] fact` summary to the judge instead. Structural facts that ARE deterministic (counts, presence of a field, that a substring was injected into a prompt) stay as direct asserts in fast unit tests.
- **Split the test surface**: cover the deterministic mechanics (prompt assembly, suppression logic) with fast non-LLM unit tests, and the model-following behaviour with one `hs_llm_core` judge test. (Example pair: `test_narrator_resolution.py` + `test_narrator_context_override.py`.)
- The judge model is independent of the test provider (defaults to Gemini); never judge with the same call you're testing.

### Memory Banks
- Each bank is an isolated memory store (like a "brain" for one user/agent)
- Dispositions (skepticism, literalism, empathy traits 1-5) and bank mission (`reflect_mission`, formerly background) are configured via Bank Config (`PATCH /v1/default/banks/{bank_id}/config`), affecting reflect
- Bank isolation is strict - no cross-bank data leakage
- Legacy profile and background endpoints are retired (return HTTP 410) in favor of Bank Config

### API Design
- All endpoints operate on a single bank per request
- Multi-bank queries are client responsibility to orchestrate
- Disposition traits only affect reflect, not recall

### Control Plane API Routes

When adding or modifying parameters in the dataplane API (hindsight-api), you must also update the control plane routes that proxy to it:

1. **API Routes** (`hindsight-control-plane/src/app/api/`):
   - `recall/route.ts` - proxies to `/v1/default/banks/{bank_id}/memories/recall`
   - `reflect/route.ts` - proxies to `/v1/default/banks/{bank_id}/reflect`
   - `memories/retain/route.ts` - proxies to `/v1/default/banks/{bank_id}/memories/retain`
   - Other routes follow the same pattern

2. **Client types** (`hindsight-control-plane/src/lib/api.ts`):
   - Update the TypeScript type definitions for `recall()`, `reflect()`, `retain()` etc.

3. **Checklist when adding new API parameters**:
   - Add parameter extraction in the route handler (destructure from `body`)
   - Pass the parameter to the SDK call
   - Update the client type definition in `lib/api.ts`
   - Update any UI components that need to use the new parameter

### Harness Attribution (which coding agent wrote a document)

`hindsight-integrations/coding-agents/` stamps the coding agent on every
document it retains, so the control plane can show its logo instead of another
`key=value` chip:

- `metadata.harness = "<id>"` — the authoritative field
- tag `harness:<id>` — the same value, so the documents list can filter on it

The ids are defined by that integration's HookSpecs
(`src/harness/hook-lifecycle.ts`, 15 harnesses) and persistent-plugin
entrypoints (`src/harness/registry.ts`, 7 harnesses):
currently `antigravity-cli`, `claude-code`, `cline-cli`, `codebuddy`, `codex`,
`copilot-cli`, `cursor-cli`, `dcode`, `devin-cli`, `dsh`, `factory-droid`,
`grok-build`, `kilo`, `kimi-code`, `opencode`, `opencode2`, `pi`,
`prime-agent`, `qwen-code`, `traecode`, `workbuddy`, `zcode`.

The control plane resolves the value in
`hindsight-control-plane/src/lib/harness-logo.ts` (metadata wins over the tag) and
renders it with `components/ui/harness-logo.tsx` in the documents table and the
document detail dialog. **Adding a harness to the integration means adding it to
that registry in the same change**: copy its icon from
`hindsight-docs/static/img/icons/` (or take it from the agent's own brand assets
when the docs site carries none) into
`hindsight-control-plane/public/img/harness/` and add one entry. Don't register
ids nothing writes — a test asserts the registry matches the emitted set, plus an
explicit list of retired ids kept so already-retained documents keep their logo.
An unregistered harness is not an error: it renders no logo and still shows as
ordinary metadata.

### Coding-agents docs are generated from one README

`hindsight-integrations/coding-agents/README.md` is the single source for that package's
configuration. **Never edit `skill/SKILL.md` or the docs page by hand** — both are generated:

```bash
cd hindsight-integrations/coding-agents && npm run skill:build   # README -> skill/SKILL.md
node hindsight-docs/scripts/sync-coding-agents-doc.mjs           # README -> docs page
```

The regions the skill copies are marked `<!-- skill:begin -->` / `<!-- skill:end -->` in the README;
the agent-only half (tools, crediting, corrections) lives in `skill-src/preamble.md`.
`src/docs-freshness.test.ts` fails on a stale skill or an undocumented `RawConfig` field. Run
`./scripts/hooks/lint.sh` BEFORE regenerating — prettier re-pads the README's tables, and a
generated file built from unformatted source fails the byte comparison in CI.

### Hermes docs are generated from one README

Same arrangement, one generator: `hindsight-integrations/hermes/README.md` is the single source for
the Hermes integration page. **Never edit `hindsight-docs/docs-integrations/hermes.md` by hand** —
it is generated:

```bash
node hindsight-docs/scripts/sync-hermes-doc.mjs                  # README -> docs page
```

The docs build runs the same script with `--check`, so a stale page fails the build. Sections listed
in the script's `DROP_SECTIONS` (currently `Development`) stay repo-only, which is where
maintainer-facing notes belong — anything else in the README ships to the public page.

Shipping a change to that directory reaches no user until the Hermes plugin catalog pin moves: open
a follow-up PR against `NousResearch/hermes-agent` bumping `sha` and `version` together in
`plugin-catalog/hindsight.yaml`.

### Adding New Integrations

Every new integration in `hindsight-integrations/` must satisfy all of the following before it can be merged:

1. **Tests are required** — tests must simulate or exercise the external system (mock the framework's interfaces and verify the integration actually calls Hindsight correctly). Pure unit tests of helper functions are not sufficient.
2. **CI job** — add a test job in `.github/workflows/test.yml` following the existing pattern (e.g., `test-crewai-integration`). The job must build, install deps, and run `uv run pytest tests -v`. Also add the integration to `detect-changes` outputs so it only runs when its files change.
3. **Release process** — add the integration name to the `VALID_INTEGRATIONS` array in `scripts/release-integration.sh` so it can be released via the standard release workflow.
4. **Follow project code standards** — Python style, type safety, no raw dicts for structured data, no multi-item tuple returns (see `.claude/skills/code-review/SKILL.md`).

If any of these are missing, the integration is incomplete and must not be pushed or merged.

### Changelogs

Never add "Unreleased" entries to changelogs (e.g. `hindsight-docs/src/pages/changelog/**`). Changelog entries are written by the release script (`./scripts/release-integration.sh`) when a version is actually cut. If a bug fix or feature needs documenting before release, describe it in the PR/commit — the release tooling will surface it in the published changelog section.

### Adding New API Configuration Flags

Configuration follows a hierarchical system: **Global (env vars) → Tenant (via extension) → Bank (database)**.

Fields must be categorized as either **hierarchical** (can be overridden per-tenant/bank) or **static** (server-level only).

#### Adding a New Configuration Field

1. **config.py** (`hindsight-api-slim/hindsight_api/config.py`):
   - Add `ENV_*` constant for the environment variable name (e.g., `ENV_MY_SETTING = "HINDSIGHT_API_MY_SETTING"`)
   - Add `DEFAULT_*` constant for the default value
   - Add field to `HindsightConfig` dataclass with type annotation
   - **Mark as configurable** by adding to `_CONFIGURABLE_FIELDS` set if the field should be overridable per-tenant/bank via API
   - Add initialization in `from_env()` method

   ```python
   # Configurable field (can be overridden per-tenant/bank via API)
   _CONFIGURABLE_FIELDS = {
       ...,
       "my_setting",  # Add here for configurable
   }

   # Static field - just don't add to _CONFIGURABLE_FIELDS
   ```

2. **main.py** (`hindsight-api-slim/hindsight_api/main.py`):
   - No change is needed for ordinary environment-backed config fields. The CLI starts from `_get_raw_config()`,
     so new `HindsightConfig` fields are carried through automatically.
   - If the new field should be overridable by a CLI flag, add the argparse option in `_parse_cli_args()` and include
     that field in the `dataclasses.replace(config, ...)` call near the "CLI override" comment.

3. **Use hierarchical config in MemoryEngine**:
   ```python
   # Config is resolved automatically per bank via ConfigResolver
   config_dict = await self._config_resolver.get_bank_config(bank_id, context)
   value = config_dict["my_setting"]
   ```

4. **Use static config** (non-hierarchical):
   ```python
   from ...config import get_config
   config = get_config()
   value = config.my_static_field
   ```

5. **Documentation** (`hindsight-docs/docs/developer/configuration.mdx`):
   - Add to appropriate section table with Variable, Description, Default
   - Mark if it's hierarchical (can be overridden per-bank)

6. **Env template** (`.env.example`):
   - Add the variable to the appropriate section, commented if optional, with a
     short inline comment describing it (mirror the documentation entry).
   - This file is the single source of truth for the env template:
     `scripts/dev/setup.sh` copies it to `.env`, and `hindsight-embed` ships a
     bundled copy (`hindsight-embed/hindsight_embed/env.example`) that seeds
     embed/profile configs. After editing `.env.example`, re-copy it to the
     embed package (`cp .env.example hindsight-embed/hindsight_embed/env.example`)
     or the `test_bundled_template_matches_repo_root` sync test will fail.

#### Hierarchical vs Static Guidelines

**Hierarchical** (per-bank overridable):
- LLM settings (provider, model, API key, base URL)
- Operation-specific settings (retain mode, chunk size, etc.)
- Feature flags that vary by customer/bank

**Static** (server-level only):
- Infrastructure settings (database URL, port, host)
- Global limits (max concurrent operations)
- System-wide feature flags

## Environment Setup

### Recommended: One-Shot Bootstrap
Run the dev environment setup script to automatically install toolchains (uv, Node, Rust), sync workspace dependencies, prime local ML models, and build core artifacts:
```bash
./scripts/dev/setup.sh
```

### Manual Setup
```bash
cp .env.example .env
# Edit .env with the LLM provider/model and credentials for your setup

# Python deps (workspace-wide)
uv sync

# Node deps (uses npm workspaces)
npm install
```

Common server settings:
- `HINDSIGHT_API_PORT`: API server port (default: `8888`)
- `HINDSIGHT_CP_PORT`: Control Plane dev script port (default: `9999`, Next.js app reads `PORT`)
- `HINDSIGHT_CP_DATAPLANE_API_URL`: Control Plane backend URL (default: `http://localhost:8888`)

LLM settings:
- `HINDSIGHT_API_LLM_PROVIDER`: openai, anthropic, gemini, deepseek, groq, minimax, ollama, lmstudio, fireworks, openai-codex, xai-oauth, etc. (See `hindsight-docs/docs/developer/configuration.mdx` for full provider lists)
- `HINDSIGHT_API_LLM_API_KEY`: API key for providers that require one
- `HINDSIGHT_API_LLM_MODEL`: Model name (defaults are provider-specific)

Optional (uses local models by default; see configuration docs for full lists):
- `HINDSIGHT_API_EMBEDDINGS_PROVIDER`: local (default), tei, onnx, openai, cohere, zeroentropy, litellm, google, etc.
- `HINDSIGHT_API_RERANKER_PROVIDER`: local (default), tei, cohere, flashrank, siliconflow, zeroentropy, litellm, google, alibaba, etc.
- `HINDSIGHT_API_DATABASE_URL`: External PostgreSQL (uses embedded pg0 by default)
- `HINDSIGHT_API_ENABLE_BANK_CONFIG_API`: Allow per-bank config *writes* (default: true; reads are always allowed)

More agent context in vectorize-io/hindsight

12 other files this repository gives its agents.