Deploy SAT & ACT Learning Lab 1.3.5

DEPLOYMENT_NOTES.md

@@ -1,4 +1,4 @@
-# Deployment notes — SAT & ACT Learning Lab 1.3.0
+# Deployment notes — SAT & ACT Learning Lab 1.3.5
 
 Target private Space: `DearmonAnalytics/SAT_ACT_Learning_Lab`
 
@@ -6,7 +6,7 @@ Turso database: `dearmon-sat-act-learning-lab`
 
 Schema namespace: `sat_act_learning_lab_v1`
 
-Encrypted-source secret: `SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`
+Encrypted-source secret: `SAT_ACT_APP_FERNET_V1_3_5_6C38E208CB90_7C200BA80629`
 
 ## Runtime contract
 
@@ -40,7 +40,15 @@ Encrypted-source secret: `SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`
   simulation may reserve blueprint duration plus a 45-minute grace period,
   capped at four hours; sign-out or restart still erases it immediately.
 - Instructor-wide access requires a strong secret with no fallback.
-- Scored questions and answer keys are deterministic and model-independent.
+- Core scored questions and answer keys are deterministic and model-independent.
+- The Printable Exam Builder requires an active demo or signed-in learner so
+  every generated file is vault-owned, then produces separate matched
+  student/key PDFs from selected or learner-missed topics. Optional AI overflow
+  is explicit, serialized, globally/individually rate-limited, capped at two
+  topic batches and eight items per build,
+  independently reviewed, print-only, and locked until the active learner has
+  completed every built-in question type for that exact topic. It never enters
+  mastery, readiness, routing, diagnostics, or simulation scoring.
 - Break It Apart is a deterministic, provider-independent, post-miss reasoning
   DAG. It is available after every incorrect practice grade and for every
   missed objective item reviewed after a completed simulation—never before
@@ -61,7 +69,7 @@ Encrypted-source secret: `SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`
 
 Core secrets are `OPENAI_API_KEY`, `TURSO_DATABASE_URL`, `TURSO_AUTH_TOKEN`,
 `LEARNER_ID_HMAC_SECRET`, `INSTRUCTOR_EXPORT_SECRET`, and
-`SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`. Live avatar video additionally uses optional
+`SAT_ACT_APP_FERNET_V1_3_5_6C38E208CB90_7C200BA80629`. Live avatar video additionally uses optional
 `SIMLI_API_KEY`.
 
 Email recovery uses `AUTH_RECOVERY_EMAIL_ENABLED`, `AUTH_SMTP_HOST`,
@@ -75,20 +83,22 @@ Release runtime defaults include `ACCOUNT_AUTH_ENABLED=1`,
 `SAT_ACT_DEMO_MODE_ENABLED=1`,
 `SAT_ACT_DEMO_SESSION_TTL_SECONDS=2700`,
 `ASK_PROFESSOR_COMPONENT_DEFAULT=1`, `ASK_PROFESSOR_TTS_DEFAULT=0`, and
-`ASK_PROFESSOR_SIMLI_DEFAULT=0`. Face IDs and the pinned Simli client module are
+`ASK_PROFESSOR_SIMLI_DEFAULT=0`. Printable supplemental generation defaults to
+`OPENAI_OVERFLOW_MODEL=gpt-5-mini` and
+`OPENAI_OVERFLOW_REVIEW_MODEL=gpt-5-mini`. Face IDs and the pinned Simli client module are
 listed in `environment.example` used to prepare this deployment.
 
-## v1.3.0 upgrade gate
+## v1.3.5 upgrade gate
 
 Finish or explicitly abandon every active timed simulation from an earlier
-release before installing v1.3.0. Checkpoints are intentionally bound to
+release before installing v1.3.5. Checkpoints are intentionally bound to
 app/source/form versions and cannot be resumed across this release. Back up
 Turso, preserve `LEARNER_ID_HMAC_SECRET`, and retain prior Fernet secrets and
 rollback commits needed through acceptance testing.
 
 ## Key lifecycle and rollback
 
-The current loader reads only `SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`. A later release must generate a
+The current loader reads only `SAT_ACT_APP_FERNET_V1_3_5_6C38E208CB90_7C200BA80629`. A later release must generate a
 new versioned, fingerprinted secret name. The deployer adds that secret before
 the repository commit and retains earlier keys. Roll back by reverting the
 Space repository to the prior commit recorded in `deployment_receipt.json`.

README.md

@@ -14,16 +14,25 @@ short_description: Dynamic SAT/ACT practice, mastery, and reasoning graphs
 
 # Dearmon Analytics SAT & ACT Learning Lab
 
-Release `1.3.0` provides original dynamic practice for current SAT and
+Release `1.3.5` provides original dynamic practice for current SAT and
 ACT skill blueprints, a four-level topic graph, individual mastery tracking,
 targeted practice, and test-like diagnostic sessions. It adds username/password
 accounts, secure recovery, an isolated one-click demo, and the embedded teaching
 avatar layer used by the Dearmon Analytics Business Calculus platform. Release
 1.2.0 introduced deterministic post-miss **Break It Apart** attribute graphs.
+Signed-in students can also download their complete personalized Topic Graph as
+a branded PNG, printable PDF, accessible hierarchy-and-concepts CSV, and
+verification manifest; demo sessions remain nonexportable.
 
-The question engine and answer keys are deterministic. The optional AI teaching
-assistant can explain concepts and student work but does not create scored
-questions, decide correctness, or alter answer keys.
+The Printable Exam Builder requires an active demo or signed-in learner so
+every generated file has a cleanup owner. It creates a clean Dearmon
+Analytics-branded student PDF and a separate answer-key PDF from selected or
+previously missed topics.
+Both carry the same random form code. Core scored questions and their answer
+keys are deterministic. After the active learner has completed every built-in
+question type for an exact topic, explicit opt-in can create separately labeled,
+independently reviewed AI supplemental items for printing only. They never
+decide correctness or alter mastery, readiness, routing, or simulation scores.
 
 After every incorrectly graded practice question, and for every missed
 objective item reviewed after a completed simulation, Break It Apart constructs
@@ -41,7 +50,7 @@ attribute-level mastery or retention records.
 This private Space uses the separate Turso database
 `dearmon-sat-act-learning-lab` and schema namespace
 `sat_act_learning_lab_v1`. Its encrypted application uses the versioned Space
-secret `SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462`.
+secret `SAT_ACT_APP_FERNET_V1_3_5_6C38E208CB90_7C200BA80629`.
 
 Required Space secrets are `OPENAI_API_KEY`, `TURSO_DATABASE_URL`,
 `TURSO_AUTH_TOKEN`, `LEARNER_ID_HMAC_SECRET`, `INSTRUCTOR_EXPORT_SECRET`, and
@@ -83,9 +92,9 @@ controls, and retention policies.
 
 ## Upgrade note
 
-Before replacing any earlier release with v1.3.0, every active timed simulation
+Before replacing any earlier release with v1.3.5, every active timed simulation
 must be finished or explicitly abandoned. Saved forms are bound to the app
-version and encrypted-source fingerprint, so v1.3.0 intentionally rejects older
+version and encrypted-source fingerprint, so v1.3.5 intentionally rejects older
 checkpoints. Preserve `LEARNER_ID_HMAC_SECRET` and retain every prior versioned
 Fernet secret and rollback commit needed through acceptance testing.
 

release_manifest.json

@@ -1,18 +1,18 @@
 {
-  "built_utc": "2026-08-29T22:32:47+00:00",
+  "built_utc": "2026-08-30T00:47:26+00:00",
   "database_name": "dearmon-sat-act-learning-lab",
-  "encrypted_payload_sha256": "98e56749f08fcce8fb612d85b8c11ae9c01e626f50fb26dab52528d124127bca",
+  "encrypted_payload_sha256": "59927fc17c5ad940f89bf68e270172797eba7c1d6338cfa25b109f12b6d18689",
   "entry_module": "sat_act_lab.app_main",
-  "fernet_secret_name": "SAT_ACT_APP_FERNET_V1_3_0_530ED11365EB_0A5895DF3462",
-  "key_fingerprint_sha256_prefix": "0A5895DF3462",
-  "plaintext_archive_sha256": "530ed11365eb79e0f0fdfb306594a7a316c95ac5e2ada567c5bbd87e8c0ba5ad",
-  "release_version": "1.3.0",
+  "fernet_secret_name": "SAT_ACT_APP_FERNET_V1_3_5_6C38E208CB90_7C200BA80629",
+  "key_fingerprint_sha256_prefix": "7C200BA80629",
+  "plaintext_archive_sha256": "6c38e208cb90270b2afe08fdda1db1636cc414b4777f77b24c833d6539763d9a",
+  "release_version": "1.3.5",
   "schema_namespace": "sat_act_learning_lab_v1",
   "schema_version": "dearmon-sat-act-release-v1",
   "source_members": {
     "sat_act_lab/__init__.py": {
       "bytes": 71,
-      "sha256": "ef21e2c2be0c32fa808b92839e04419e7ccaf2292f74c260631ffc779a69b511"
+      "sha256": "426d046e94f484f4a732cd52bb4cd8434236ab98e52d9a91bd456cae3d3635de"
     },
     "sat_act_lab/act_english_bank.py": {
       "bytes": 79622,
@@ -26,9 +26,13 @@
       "bytes": 43952,
       "sha256": "5959db1e6a007f9384978c2a65af82e9bfd81216db939a1d852a91852badef8e"
     },
+    "sat_act_lab/ai_question_overflow.py": {
+      "bytes": 30007,
+      "sha256": "9f557aea11cc2796e011031c70776dfd9cf3f4c0f8255fcbff9ded341580a4e4"
+    },
     "sat_act_lab/app_main.py": {
-      "bytes": 265227,
-      "sha256": "415448d1c144174d3c44b03c0755106c60a26f4a1e9c64dafd869027543418ae"
+      "bytes": 305777,
+      "sha256": "3024712d00f7b461229b3088d327fc029a3f7571bd1973c684b0f71b1913c61c"
     },
     "sat_act_lab/attribute_graph.py": {
       "bytes": 131004,
@@ -58,14 +62,30 @@
       "bytes": 100384,
       "sha256": "2abb720cd5a0a5a459cbcdc7ec1a8919ea50d7203cc809adccdefed4317e3a7f"
     },
+    "sat_act_lab/exam_pdf_export.py": {
+      "bytes": 47043,
+      "sha256": "876991e8fb86d85606854b0a2d2609203b77537b9a91e2183edfdee0aead7a16"
+    },
+    "sat_act_lab/learner_exam_topics.py": {
+      "bytes": 11795,
+      "sha256": "bc32af89d411d8ff8918d74e026421707004adbf0e64e61d49706e3062526167"
+    },
     "sat_act_lab/learning_concepts.py": {
       "bytes": 51335,
       "sha256": "202212791dc80fcc20b2dcc5d662c98e43f53db1e39b2b9992c8289183263346"
     },
+    "sat_act_lab/practice_exam_planner.py": {
+      "bytes": 6731,
+      "sha256": "96dda3ddb76bc2d837769865fdbe177ad650bfd21cd158d161e5cb13123fa6a9"
+    },
     "sat_act_lab/question_engine.py": {
       "bytes": 221287,
       "sha256": "929d8e424bbb845e69cab76f6e591f9bfb1f825c00733cd90efce089ea1a89a2"
     },
+    "sat_act_lab/topic_graph_report.py": {
+      "bytes": 19837,
+      "sha256": "0a6bb8a950a1f600e2d365bbbc7e9afba48c23be30d5440aa0fb94a2ed4ecbea"
+    },
     "sat_act_lab/tracking.py": {
       "bytes": 139074,
       "sha256": "c814032247eac63b59d7c619aa172af6340840bc2d1cd5e2b9e5294862231d82"
@@ -77,20 +97,20 @@
       "sha256": "3b1fdd8eb2e17dc4edae8387f1bc9a18a8072a8d6fae3a71041f00f0b9b04103"
     },
     "DEPLOYMENT_NOTES.md": {
-      "bytes": 5663,
-      "sha256": "a7230ac72d71b5a18b9f4edfb119bdd0b0d00ac12b28124c271a88867abd8385"
+      "bytes": 6367,
+      "sha256": "67ef67799bb031e0a80c11afac6294dd59b97089b4e557a9d358217d60cc0c78"
     },
     "README.md": {
-      "bytes": 5113,
-      "sha256": "65a80c1d285d961b284528d8cd2e001737887ae1bcfff7c3fad24a3835da34fe"
+      "bytes": 5754,
+      "sha256": "74cf786233b9bf01c141e2477e62ad4a501eff30e695f5bd0706dc7775758649"
     },
     "app.py": {
-      "bytes": 595623,
-      "sha256": "c1b7e44eda4e80344fa7171883ac66a69cdb125be8026e80e15f03cb7afda0b1"
+      "bytes": 669889,
+      "sha256": "1af30556d5b23a7ab747a49b76486bcba933f621e8a4a583dd2fb7ef13bbf6aa"
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     "requirements.txt": {
-      "bytes": 287,
-      "sha256": "1cfe1a2b7efb8ba2372a283d5897316f691a693b23b53e0169888569060d1776"
+      "bytes": 301,
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     },
     "runtime.txt": {
       "bytes": 13,

requirements.txt

@@ -6,13 +6,13 @@ starlette==1.6.0
 jinja2==3.1.6
 uvicorn==0.41.0
 numpy==2.5.2
-pandas==3.0.5
+pandas==2.3.3
 matplotlib==3.10.8
 sympy==1.14.0
 requests==2.34.2
 pillow==12.1.1
 python-docx==1.2.0
+socksio==1.0.0
 libsql==0.1.11
 openai==2.54.0
 cryptography==46.0.7
-