- Add 3 retries with exponential backoff (10s -> 20s -> 40s)
- Set HF_HUB_DOWNLOAD_TIMEOUT=600 for longer timeout
- Fixes transient network failures during HuggingFace downloads
- Applied to both api-only and standalone stages
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
* misc: add mcp integration tests and increase test coverage
* misc: add mcp integration tests and increase test coverage
* misc: add mcp integration tests and increase test coverage
* feat: Add local LLM improvements for reasoning models and Docker startup
## Reasoning Model Support
- Strip thinking tags from local LLM responses (<think>, <thinking>, <reasoning>, |startthink|/|endthink|)
- Enables Qwen3, DeepSeek, and other reasoning models to work with JSON extraction
- Non-breaking: only affects responses that contain thinking tags
## Docker Retry Start Script
- New retry-start.sh waits for dependencies before starting Hindsight
- Checks LLM Studio availability at /v1/models endpoint
- Checks database connectivity (skipped for embedded pg0)
- Configurable via HINDSIGHT_RETRY_MAX and HINDSIGHT_RETRY_INTERVAL env vars
- Prevents startup failures when LLM Studio isn't ready yet
Tested on Apple Silicon M4 Max with Qwen3 8B via LM Studio.
* refactor: make thinking token stripping opt-in via env var
* refactor: merge retry logic into start-all.sh (opt-in via HINDSIGHT_WAIT_FOR_DEPS)
* fix: resolve pg0 stale instance config in Docker build
- Remove stale pg0 instance data after pre-caching binaries to avoid
port conflicts (was using hardcoded port 5555 from build time)
- Remove unused cache copy logic from start-all.sh
- Add database backup instructions to CLAUDE.md
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
* fix: add procps to Docker image and smoke test to release workflow
The Docker image was failing to start because pg0 uses `kill -0 <pid>`
to check if PostgreSQL is running, but the python:3.11-slim base image
doesn't include the `kill` command. Adding procps provides it.
This has been broken since release 0.1.6 when the fallback URI code was
removed to support dynamic ports. Without the kill command, pg0 couldn't
detect process status and returned None for the database URI.
Also adds smoke testing to the release workflow:
- Build image locally (single platform) and test before pushing
- Run container and wait for /health endpoint (up to 120s)
- Only push multi-platform release images if smoke test passes
- Each image (api-only, cp-only, standalone) tested independently
This prevents releasing broken Docker images to GHCR.
* refactor: extract smoke test into reusable script
Add scripts/docker-smoke-test.sh that can be run locally or in CI:
- Takes image name and optional target (cp-only vs api)
- Handles LLM credentials for API/standalone images
- Configurable timeout via SMOKE_TEST_TIMEOUT env var
- Colored output and clear error messages
- Proper cleanup on exit
Update release workflow to use the script instead of inline bash.
* bump pg0 0.11.x and improve documentation
* bump pg0 0.11.x and improve documentation
* bump pg0 0.11.x and improve documentation
* ci: test notebooks on ci
* ci: test notebooks on ci
* rm llms-full from repo
* formatting
* formatting
* change the package to workspace concept
* add provider name and change default model
* add the node_modules to git ignore
* change the npm runs to use workspace
* fix the start scripts to use the workspace
* update the uv.lock
* updated instructions
* update the docker build to use the npm workspace
* Update package-lock.json after merge to sync workspace dependencies
* fix merge conflict
* Add the LLM_PROVIDER in example
* fix the assert in testing recall
* trial to fix failing client tests
NotImplementedError: Cannot copy out of meta tensor; no data! Please use torch.nn.Module.to_empty() instead of torch.nn.Module.to() when moving module from meta to a different device.
* lock the sentence transformer packages to align with the breaking changes around lazy tensor loading
* Add the LLM_PROVIDER in example
* fix the assert in testing recall
* trial to fix failing client tests
* pre-cache the model so CI doesn't need workarounds
* remove assert that is a race condition
The test was checking that the bank count increased, but with parallel tests (-n 8), other tests can delete their banks while this test is running, causing a race condition. The important assertion is assert test_bank_id in final_banks - which verifies the bank was actually created.
* add debug to figure out why docker build fails sometimes
* use the CPU only version of pytorch to avoid pulling cuda libraries
* add best match strategy to uv
* change the example openai model
