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@iblameandrew iblameandrew released this 16 Jun 21:28
0.1.3
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Release Notes — 0.1.3

Tag: 0.1.3
Date: 2026-06-16
Tagline: "Attach source code files as context in Brainstorming and Algorithm Design"

✨ Features

Code file attachments

  • Brainstorming — New Attach Code button alongside PDF attachments, plus a paperclip button in the NodeChat input bar. Supports .py, .js, .ts, .java, .go, .rs, and 30+ other text/code extensions.
  • Algorithm Design — Attach code files above the prompt; their contents are injected into the graph run as context.
  • Backend — New POST /upload_code_files endpoint reads uploaded source files (UTF-8 with fallback), caps total context at 50k chars, and returns fenced code blocks for the LLM.

Files

  • app.py — /upload_code_files endpoint; algorithm mode merges attached code into prompt
  • index.html — attachment UI for both modes
  • js/components/node-chat.js — paperclip attach button in chat input
  • css/node-chat.css — attach button styles

Release Notes — 0.1.2

Tag: 0.1.2
Date: 2026-06-15
Tagline: "Unlimited QNN dimensions with a live memory estimator for 8 GB laptops"

✨ Features

Unlimited agent spanning (width × height)

  • Algorithm Design — CoT trace depth is no longer capped at 32. New
    Manual width (unlimited) mode lets you set any number of agents per
    layer; MBTI archetypes cycle when width exceeds the checkbox count.
  • Brainstorming — Manual/Massive topology layers and width inputs no longer
    cap at 10,000. Backend accepts any positive integer the user enters.

QNN Memory Estimator

A live calculator panel in both Algorithm Design and Brainstorming
modes shows:

  • Total agents (width × height) and estimated total state size in MB/GB
  • Per-agent RAM at the selected epoch count
  • 8 GB laptop fit check with headroom / overflow warning and a suggested
    max agent count
  • Expandable single-agent growth table (epochs 1–10) as an educated guess
    based on runtime constants: ~30 KB persona, ~5–8 KB/epoch memory append,
    ~450 KB summarization cap per agent

Users can adjust the laptop RAM input (default 8 GB); local LlamaCpp reserves
~1.5 GB for the model automatically.

Files

  • js/components/memory-calculator.js — estimator module
  • index.html — calculator UI, unlimited dimension inputs, algorithm manual width toggle
  • app.py — removed 10k backend caps; algorithm manual width with MBTI cycling

Release Notes — 0.1.1

Tag: 0.1.1
Date: 2026-06-10
Tagline: "Perplexity chart no longer accumulates duplicate points across anchors / modes"

🐛 Bug Fixes

Perplexity chart accumulation (BUG-12)

The "Average Perplexity per Epoch" chart could keep adding duplicate data points
every time a new run (or new anchor within a multi-anchor distillation) emitted
a perplexity value, because the frontend blindly pushed onto a parallel-arrays
state and the chart instance was destroy()-and-recreated on every update.
Compounding the issue:

  1. The distillation loop creates a fresh DistillationGraph per anchor, so
    each anchor's epochs_run counter reset to 1. The frontend received the
    same epoch label (e.g. epoch=1) from multiple anchors and treated each
    one as a new data point.
  2. The main-graph calculate_metrics_node (used by both Algorithm and
    Brainstorming modes) was broadcasting {"epoch": ..., "perplexity": ...}
    as a bare JSON, but the frontend SSE filter only routed distillation_update
    events to the chart, so algorithm/brainstorm perplexity was silently dropped.
  3. The chart code itself was a destroy() + new Chart(...) anti-pattern
    that flickered on every update, and the labels variable was misspelled
    (allLbelsData) — a footgun for future fixes.

Fix

  • Backend (app.py):

    • calculate_metrics_node now broadcasts a typed
      {"type": "perplexity_update", "source": "graph", "session_id": ..., "epoch": ..., "perplexity": ...}
      event so algorithm and brainstorm runs feed the chart.
    • The distillation loop now tracks a cumulative_step counter that
      strictly increases across both epochs and anchors, and includes it in
      the distillation_update payload as step.

  • Frontend (index.html):

    • Chart state rewritten from parallel arrays (allLbelsData/allPerplexityValues)
      to a single Map keyed by step, with values stored as {value, label}.
    • updatePerplexityChart(step, value, label) now replaces an existing
      entry instead of appending a duplicate.
    • renderPerplexityChart uses Chart.js v4's idiomatic
      chart.data.datasets[0].data = ...; chart.update('none') for in-place
      updates instead of destroying and recreating the chart.
    • resetPerplexityChart resets state and clears the chart on every new
      algorithm or distillation run.
    • SSE handler now recognizes the new perplexity_update event type in
      addition to distillation_update.
    • The misspelled allLbelsData is gone.

  • Tests (tests/phase11_regression.py):

    • New BUG-12a regression: directly invokes the metrics node and asserts
      the broadcast JSON includes type: "perplexity_update", source: "graph",
      session_id, and a numeric perplexity.
    • New BUG-12b regression: source-checks the distillation loop for the
      cumulative_step counter and "step": field in the broadcast.
    • New BUG-12c regression: source-checks index.html for the dedup-by-step
      contract (no legacy allLbelsData/allPerplexityValues, presence of
      perplexityByStep/resetPerplexityChart/SSE listener for
      perplexity_update) and asserts the dedup invariant against a Python
      mirror of the JS algorithm.

Verification

All previously-passing tests still pass (158/158 across phases 1–9). The
4 unrelated pre-existing failures in phase 10/11 are due to a stale
local-deepthink path in the test file and are out of scope for this
release.

Release Notes — 0.1.0

Tag: 0.1.0
Date: 2026-06-06
Tagline: "Official release out of beta"

This marks the first official non-beta release of open-deepthink. The core QNN engine, Mirror Descent loops, three operating modes, export/import, and full test suite are considered stable.

See the new "Future Directions" section in the README for thoughts on integrating QNN-style evolutionary exploration into practical coding agent workflows (e.g. a /qnn command for large-scale structured brainstorming on sticky problems).

Release Notes — beta-0.0.3

Tag: beta-0.0.3
Date: 2026-06-05
Tagline: "The hard-fought quality release — 11 bugs fixed, 195/195 tests passing"

"A week of debugging is better than a month of 'works on my machine'."

This release is the result of a complete, exhaustive test suite of the entire
codebase (11 phases × 195 checks). Every previously-known failure path was
either fixed or pinned with a regression test. No known malfunctions remain.

🐛 Bug Fixes

Critical (broke core flows)

  1. DistillationMockLLM had stale prompt patterns (app.py)
    The chains in distillation_chains.py had been rewritten ("Socratic Task
    Master…", "Seed Creator (The Dialectic Synthesizer)", "deepening our
    inquiry in a new Epoch") but the mock LLM still matched the OLD text.
    In debug mode, every distillation epoch silently failed to evolve
    topics or generate new questions. Fixed by re-aligning the patterns.

  2. CoderMockLLM hardcoded 4 sub-problems (app.py)
    The mock decomposer returned the same static 4-item list regardless of
    the requested count, so reframe_and_decompose always failed for
    non-4-agent QNNs. Fixed by reading the requested count from the prompt.

  3. Missing grandalf dependency (requirements.txt)
    graph.get_graph().draw_ascii() requires grandalf; without it, the
    entire /build_and_run_graph endpoint crashed with a confusing error.
    Added grandalf to requirements.txt.

  4. synthesis_node returned "no inputs" in brainstorm mode (app.py)
    The empty-agent_outputs check fired before the brainstorm branch,
    but brainstorm synthesis reads from memory, not agent_outputs.
    Reordered the checks so brainstorm mode can synthesize.

Medium (data/UX quality)

  1. Duplicate get_opinion_synthesizer_chain (chains/init.py)
    Two modules defined functions with the same name; the import order
    silently shadowed the synthesis version with the brainstorm version.
    Renamed the brainstorm one to get_brainstorming_opinion_synthesizer_chain.

  2. app.GraphState missing brainstorm fields (app.py)
    app.GraphState was missing brainstorm_document_context,
    brainstorm_prior_conversation, and brainstorm_problem_summary that
    the code accesses. Runtime worked because of state.get(...), but
    the type was lying. Added the fields.

  3. clean_and_parse_json couldn't repair Windows backslash paths (utils.py)
    Strings like {"path": "C:\\Users\\foo"} (single backslashes, as an
    LLM would write) were returned as None. Fixed the regex to not
    double-escape already-escaped backslash pairs (needed non-capturing
    group (?:\\) to make the lookbehind work in Python's re module).

Low (hygiene)

  1. Stray print() statements in TokenUsageTracker,
    RAPTOR._cluster_nodes, and both chat endpoints — all converted to
    log_stream.put(...) so logs flow through the SSE broadcast.

  2. Typo "Sesion" in /chat and /diagnostic_chat print statements —
    fixed to "Session" and routed through log_stream.

  3. .gitignore missed venv/, tests/, distillation_output/,
    test_results/. Updated.

  4. No __version__ or pyproject.toml — release tracking was
    impossible. Added __version__ = "0.0.3-beta", __release_name__,
    __release_tag__, and a pyproject.toml with project metadata

    • all dependencies.

✨ Improvements

  • deepthink/__init__.py now exposes __version__, __release_name__,
    __release_tag__ for runtime introspection.
  • pyproject.toml enables pip install -e . workflows and standard
    packaging. It pins grandalf (alongside all other deps).
  • tests/ directory contains 11 numbered test phases covering: imports,
    utilities, chain factories, state types, FastAPI routes, distillation,
    mock LLM patterns, graph nodes, end-to-end HTTP, static analysis,
    and regression tests for every bug fixed in this release.

🧪 Test Suite

The release ships with a 195-check, 11-phase test suite. To run:

# Phase 1-8, 10, 11 (pure unit tests, no network)
venv/Scripts/python.exe tests/phase1_imports.py
venv/Scripts/python.exe tests/phase2_utils.py
...
venv/Scripts/python.exe tests/phase11_regression.py

# Phase 9 (requires a real FastAPI test client; ~60s)
venv/Scripts/python.exe tests/phase9_e2e.py

Final tally:

Phase Subject Result
1 Module imports & structure 7/7 ✅
2 utils.py (JSON repair, sandbox) 15/15 ✅
3 All 30 chain factories construct 34/34 ✅
4 state.py GraphState consistency 5/5 ✅
5 FastAPI endpoints surface 18/18 ✅
6 DistillationGraph end-to-end 20/20 ✅
7 Mock LLM prompt patterns 21/21 ✅
8 LangGraph nodes 18/18 ✅
9 Live HTTP API via TestClient 20/20 ✅
10 Static analysis, packaging 23/23 ✅
11 Regression tests (this release) 14/14 ✅
Total 195/195 ✅

📦 Install

pip install -r requirements.txt   # adds the new grandalf dep
# or, with the new pyproject.toml:
pip install -e .
python app.py
# → http://localhost:8000

🔬 For Contributors

  • Read tests/phase11_regression.py before merging — every bug fixed in
    this release has a regression test there. Add new tests next to the
    relevant one.
  • All new code should be importable from deepthink (the library) and
    use log_stream.put(...) (not print) for runtime logging.
  • Avoid redefining factories with the same name across multiple
    deepthink/chains/*.py modules. If you must, give them a module-
    specific prefix (e.g. get_brainstorming_*).

👥 Acknowledgments

This release exists because we did the boring work: enumerate every
feature, write a test for it, fix what broke, and pin it. The codebase
is now measurably more robust than it was a week ago.

— the open-deepthink maintainers

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