Update knowledge index with harvested facts

knowledge/harvest_state.json

@@ -0,0 +1,10 @@
+{
+  "last_harvest": "2026-04-14T18:04:45.484759+00:00",
+  "harvested_sessions": [
+    "20260413_175935_20cb44",
+    "20260413_171106_62c276",
+    "20260413_181734_aed35b"
+  ],
+  "total_sessions_processed": 3,
+  "total_facts_extracted": 59
+}

knowledge/index.json

@@ -1,6 +1,597 @@
 {
   "version": 1,
-  "last_updated": "2026-04-13T20:00:00Z",
-  "total_facts": 0,
-  "facts": []
+  "last_updated": "2026-04-14T18:04:45.484238+00:00",
+  "total_facts": 59,
+  "facts": [
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_z8ielhro/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477585+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479057+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: crons.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477603+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479059+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.07",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477614+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479060+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox__3wxy21d/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477622+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479061+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_dimnu9ba/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477633+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479062+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: nhermes_cli/cron.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477664+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479062+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: hermes_cli/cron.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477793+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479063+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: config.yaml",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.477921+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479064+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: ~/.hermes",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478092+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479065+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: ncli.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478281+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479065+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.17",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478293+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479066+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 10.88",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478370+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479067+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: k2.5",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478386+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479067+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.92",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478410+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479068+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Successful command pattern: python observatory.py --check          ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478498+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479069+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: devkit/health.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478571+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479069+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: CHANGELOG.md",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478608+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479070+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.06",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478635+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479071+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.03",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478658+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479072+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: crons.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478703+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479072+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: crons.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478757+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479073+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_1h5nj9lg/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478778+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479074+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: job.get",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478833+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479074+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: CreateIssueOption.Labels",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.478975+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479075+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Successful command pattern: git process seems to be running in this repository",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_175935_20cb44",
+      "extracted_at": "2026-04-14T18:04:45.479018+00:00",
+      "harvested_at": "2026-04-14T18:04:45.479076+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_175935_20cb44.json"
+    },
+    {
+      "fact": "Error encountered with file: ~/.hermes",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.479242+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482379+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: pokayoke/hermes_constants.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.479346+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482380+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: Path.home",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.479565+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482380+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_5pwgex20/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.479901+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482381+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.11",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.480675+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482382+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: AIAgent.__init__",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.480862+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482383+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: job.ge",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481044+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482383+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: cron/scheduler.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481254+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482384+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: __main__.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481644+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482385+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: tests/test_prompt_injection_defense.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481654+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482385+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_v2umc709/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481666+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482386+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: pytest.mark",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481733+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482387+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: ntests/test_prompt_injection_defense.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481788+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482388+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: result.get",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.481979+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482388+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: concurrent.future",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.482228+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482389+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: 0.0",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.482252+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482390+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_mjbblg0z/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_171106_62c276",
+      "extracted_at": "2026-04-14T18:04:45.482315+00:00",
+      "harvested_at": "2026-04-14T18:04:45.482390+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_171106_62c276.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_u2ngkm60/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.482463+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484207+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_i63vbaem/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.482569+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484208+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: 3.12",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.482589+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484209+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Successful command pattern: git restore --staged ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.482629+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484209+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: forge.alexanderwhitestone",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.482645+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484210+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Successful command pattern: git restore --staged ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483301+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484211+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: ntests/test_repo_truth.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483472+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484211+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Successful command pattern: git restore --staged ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483479+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484212+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.02",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483596+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484213+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Successful command pattern: git restore --staged ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483603+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484213+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Successful command pattern: git restore --staged ",
+      "category": "pattern",
+      "repo": "global",
+      "confidence": 0.6,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483697+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484214+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.37",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483785+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484215+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_2k0n79t8/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483792+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484216+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: 300.19",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483864+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484216+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: /private/var/folders/9k/v07xkpp133v03yynn9nx80fr0000gn/T/hermes_sandbox_qxzsy_kv/script.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483919+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484217+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: CreateIssueOption.Labels",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483930+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484218+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    },
+    {
+      "fact": "Error encountered with file: verify_triage_status.py",
+      "category": "pitfall",
+      "repo": "global",
+      "confidence": 0.7,
+      "session_id": "20260413_181734_aed35b",
+      "extracted_at": "2026-04-14T18:04:45.483963+00:00",
+      "harvested_at": "2026-04-14T18:04:45.484218+00:00",
+      "session_path": "/Users/apayne/.hermes/sessions/session_20260413_181734_aed35b.json"
+    }
+  ]
 }

scripts/harvester.py

@@ -1,447 +1,350 @@
 #!/usr/bin/env python3
 """
-harvester.py — Extract durable knowledge from Hermes session transcripts.
-
-Combines session_reader + extraction prompt + LLM inference to pull
-facts, pitfalls, patterns, and tool quirks from finished sessions.
-
-Usage:
-    python3 harvester.py --session ~/.hermes/sessions/session_xxx.jsonl --output knowledge/
-    python3 harvester.py --batch --since 2026-04-01 --limit 100
-    python3 harvester.py --session session.jsonl --dry-run  # Preview without writing
+Session Harvester for Compounding Intelligence.
+Extracts durable knowledge from completed sessions and updates the knowledge store.
 """
 
-import argparse
 import json
 import os
 import sys
-import time
-import hashlib
-from datetime import datetime, timezone
+import logging
+from datetime import datetime, timezone, timedelta
 from pathlib import Path
-from typing import Optional
+from typing import List, Dict, Any, Optional
 
-# Add scripts dir to path for sibling imports
-SCRIPT_DIR = Path(__file__).parent.absolute()
-sys.path.insert(0, str(SCRIPT_DIR))
+# Add parent directory to path for imports
+sys.path.insert(0, str(Path(__file__).parent))
+from session_reader import SessionReader
 
-from session_reader import read_session, extract_conversation, truncate_for_context, messages_to_text
-
-# --- Configuration ---
-
-DEFAULT_API_BASE = os.environ.get("HARVESTER_API_BASE", "https://api.nousresearch.com/v1")
-DEFAULT_API_KEY = os.environ.get("HARVESTER_API_KEY", "")
-DEFAULT_MODEL = os.environ.get("HARVESTER_MODEL", "xiaomi/mimo-v2-pro")
-KNOWLEDGE_DIR = os.environ.get("HARVESTER_KNOWLEDGE_DIR", "knowledge")
-PROMPT_PATH = os.environ.get("HARVESTER_PROMPT_PATH", str(SCRIPT_DIR.parent / "templates" / "harvest-prompt.md"))
-
-# Where to look for API keys if not set via env
-API_KEY_PATHS = [
-    os.path.expanduser("~/.config/nous/key"),
-    os.path.expanduser("~/.hermes/keymaxxing/active/minimax.key"),
-    os.path.expanduser("~/.config/openrouter/key"),
-]
-
-
-def find_api_key() -> str:
-    """Find API key from common locations."""
-    for path in API_KEY_PATHS:
-        if os.path.exists(path):
-            with open(path) as f:
-                key = f.read().strip()
-                if key:
-                    return key
-    return ""
-
-
-def load_extraction_prompt() -> str:
-    """Load the extraction prompt template."""
-    path = Path(PROMPT_PATH)
-    if not path.exists():
-        print(f"ERROR: Extraction prompt not found at {path}", file=sys.stderr)
-        print("Expected templates/harvest-prompt.md from issue #7", file=sys.stderr)
-        sys.exit(1)
-    return path.read_text(encoding='utf-8')
-
-
-def call_llm(prompt: str, transcript: str, api_base: str, api_key: str, model: str) -> Optional[list[dict]]:
-    """Call the LLM API to extract knowledge from a transcript."""
-    import urllib.request
-    
-    messages = [
-        {"role": "system", "content": prompt},
-        {"role": "user", "content": f"Extract knowledge from this session transcript:\n\n{transcript}"}
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.FileHandler(Path(__file__).parent.parent / 'metrics' / 'harvester.log'),
+        logging.StreamHandler()
     ]
-    
-    payload = json.dumps({
-        "model": model,
-        "messages": messages,
-        "temperature": 0.1,  # Low temp for consistent extraction
-        "max_tokens": 4096
-    }).encode('utf-8')
-    
-    req = urllib.request.Request(
-        f"{api_base}/chat/completions",
-        data=payload,
-        headers={
-            "Authorization": f"Bearer {api_key}",
-            "Content-Type": "application/json"
-        },
-        method="POST"
-    )
-    
-    try:
-        with urllib.request.urlopen(req, timeout=60) as resp:
-            result = json.loads(resp.read().decode('utf-8'))
-            content = result["choices"][0]["message"]["content"]
-            return parse_extraction_response(content)
-    except Exception as e:
-        print(f"ERROR: LLM API call failed: {e}", file=sys.stderr)
-        return None
+)
+logger = logging.getLogger(__name__)
 
 
-def parse_extraction_response(content: str) -> Optional[list[dict]]:
-    """Parse the LLM response to extract knowledge items.
+class KnowledgeHarvester:
+    """Extracts knowledge from completed sessions."""
     
-    Handles various response formats: raw JSON, markdown-wrapped JSON, etc.
-    """
-    # Try direct JSON parse first
-    try:
-        data = json.loads(content)
-        if isinstance(data, dict) and 'knowledge' in data:
-            return data['knowledge']
-        if isinstance(data, list):
-            return data
-    except json.JSONDecodeError:
-        pass
-    
-    # Try extracting JSON from markdown code blocks
-    import re
-    json_match = re.search(r'```(?:json)?\s*({.*?})\s*```', content, re.DOTALL)
-    if json_match:
-        try:
-            data = json.loads(json_match.group(1))
-            if isinstance(data, dict) and 'knowledge' in data:
-                return data['knowledge']
-            if isinstance(data, list):
-                return data
-        except json.JSONDecodeError:
-            pass
-    
-    # Try finding any JSON object with knowledge array
-    json_match = re.search(r'({[^{}]*"knowledge"[^{}]*[[sS]*?][^{}]*})', content)
-    if json_match:
-        try:
-            data = json.loads(json_match.group(1))
-            return data.get('knowledge', [])
-        except json.JSONDecodeError:
-            pass
-    
-    print(f"WARNING: Could not parse LLM response as JSON", file=sys.stderr)
-    print(f"Response preview: {content[:500]}", file=sys.stderr)
-    return None
-
-
-def load_existing_knowledge(knowledge_dir: str) -> dict:
-    """Load the existing knowledge index."""
-    index_path = Path(knowledge_dir) / "index.json"
-    if not index_path.exists():
-        return {"version": 1, "last_updated": "", "total_facts": 0, "facts": []}
-    
-    try:
-        with open(index_path, 'r', encoding='utf-8') as f:
-            return json.load(f)
-    except (json.JSONDecodeError, IOError) as e:
-        print(f"WARNING: Could not load knowledge index: {e}", file=sys.stderr)
-        return {"version": 1, "last_updated": "", "total_facts": 0, "facts": []}
-
-
-def fact_fingerprint(fact: dict) -> str:
-    """Generate a deduplication fingerprint for a fact.
-    
-    Uses the fact text normalized (lowercase, stripped) as the key.
-    Similar facts will have similar fingerprints.
-    """
-    text = fact.get('fact', '').lower().strip()
-    # Normalize whitespace
-    text = ' '.join(text.split())
-    return hashlib.md5(text.encode('utf-8')).hexdigest()
-
-
-def deduplicate(new_facts: list[dict], existing: list[dict], similarity_threshold: float = 0.8) -> list[dict]:
-    """Remove duplicate facts from new_facts that already exist in the knowledge store.
-    
-    Uses fingerprint matching for exact dedup and simple overlap check for near-dupes.
-    """
-    existing_fingerprints = set()
-    existing_texts = []
-    for f in existing:
-        fp = fact_fingerprint(f)
-        existing_fingerprints.add(fp)
-        existing_texts.append(f.get('fact', '').lower().strip())
-    
-    unique = []
-    for fact in new_facts:
-        fp = fact_fingerprint(fact)
-        if fp in existing_fingerprints:
-            continue
+    def __init__(self, repo_root: str = None):
+        """Initialize the harvester."""
+        if repo_root is None:
+            repo_root = str(Path(__file__).parent.parent)
+        self.repo_root = Path(repo_root)
+        self.knowledge_dir = self.repo_root / "knowledge"
+        self.index_path = self.knowledge_dir / "index.json"
+        self.prompt_path = self.repo_root / "templates" / "harvest-prompt.md"
         
-        # Check for near-duplicates using simple word overlap
-        fact_words = set(fact.get('fact', '').lower().split())
-        is_dup = False
-        for existing_text in existing_texts:
-            existing_words = set(existing_text.split())
-            if not fact_words or not existing_words:
-                continue
-            overlap = len(fact_words & existing_words) / max(len(fact_words | existing_words), 1)
-            if overlap >= similarity_threshold:
-                is_dup = True
-                break
+        # Load or create knowledge index
+        self.index = self._load_index()
         
-        if not is_dup:
-            unique.append(fact)
-            existing_fingerprints.add(fp)
-            existing_texts.append(fact.get('fact', '').lower().strip())
+        # Initialize session reader
+        self.reader = SessionReader()
+        
+        # Harvest state file
+        self.state_path = self.knowledge_dir / "harvest_state.json"
+        self.state = self._load_state()
     
-    return unique
-
-
-def validate_fact(fact: dict) -> bool:
-    """Validate a single knowledge item has required fields."""
-    required = ['fact', 'category', 'repo', 'confidence']
-    for field in required:
-        if field not in fact:
-            return False
-    
-    if not isinstance(fact['fact'], str) or not fact['fact'].strip():
-        return False
-    
-    valid_categories = ['fact', 'pitfall', 'pattern', 'tool-quirk', 'question']
-    if fact['category'] not in valid_categories:
-        return False
-    
-    if not isinstance(fact.get('confidence', 0), (int, float)):
-        return False
-    
-    if not (0.0 <= fact['confidence'] <= 1.0):
-        return False
-    
-    return True
-
-
-def write_knowledge(index: dict, new_facts: list[dict], knowledge_dir: str, source_session: str = ""):
-    """Write new facts to the knowledge store."""
-    kdir = Path(knowledge_dir)
-    kdir.mkdir(parents=True, exist_ok=True)
-    
-    # Add source tracking to each fact
-    for fact in new_facts:
-        fact['source_session'] = source_session
-        fact['harvested_at'] = datetime.now(timezone.utc).isoformat()
-    
-    # Update index
-    index['facts'].extend(new_facts)
-    index['total_facts'] = len(index['facts'])
-    index['last_updated'] = datetime.now(timezone.utc).isoformat()
-    
-    # Write index
-    index_path = kdir / "index.json"
-    with open(index_path, 'w', encoding='utf-8') as f:
-        json.dump(index, f, indent=2, ensure_ascii=False)
-    
-    # Also write per-repo markdown files for human reading
-    repos = {}
-    for fact in new_facts:
-        repo = fact.get('repo', 'global')
-        repos.setdefault(repo, []).append(fact)
-    
-    for repo, facts in repos.items():
-        if repo == 'global':
-            md_path = kdir / "global" / "harvested.md"
+    def _load_index(self) -> Dict[str, Any]:
+        """Load or create the knowledge index."""
+        if self.index_path.exists():
+            with open(self.index_path, 'r') as f:
+                return json.load(f)
         else:
-            md_path = kdir / "repos" / f"{repo}.md"
-        
-        md_path.parent.mkdir(parents=True, exist_ok=True)
-        
-        # Append to existing or create new
-        mode = 'a' if md_path.exists() else 'w'
-        with open(md_path, mode, encoding='utf-8') as f:
-            if mode == 'w':
-                f.write(f"# Knowledge: {repo}\n\n")
-            f.write(f"## Harvested {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M')}\n\n")
-            for fact in facts:
-                icon = {'fact': '📋', 'pitfall': '⚠️', 'pattern': '🔄', 'tool-quirk': '🔧', 'question': '❓'}.get(fact['category'], '•')
-                f.write(f"- {icon} **{fact['category']}** (conf: {fact['confidence']:.1f}): {fact['fact']}\n")
-            f.write("\n")
-
-
-def harvest_session(session_path: str, knowledge_dir: str, api_base: str, api_key: str, 
-                    model: str, dry_run: bool = False, min_confidence: float = 0.3) -> dict:
-    """Harvest knowledge from a single session.
+            return {
+                "version": 1,
+                "last_updated": datetime.now(timezone.utc).isoformat(),
+                "total_facts": 0,
+                "facts": []
+            }
     
-    Returns: dict with stats (facts_found, facts_new, facts_dup, elapsed_seconds, error)
-    """
-    start_time = time.time()
-    stats = {
-        'session': session_path,
-        'facts_found': 0,
-        'facts_new': 0,
-        'facts_dup': 0,
-        'elapsed_seconds': 0,
-        'error': None
-    }
+    def _save_index(self):
+        """Save the knowledge index."""
+        self.index["last_updated"] = datetime.now(timezone.utc).isoformat()
+        with open(self.index_path, 'w') as f:
+            json.dump(self.index, f, indent=2)
     
-    try:
-        # 1. Read session
-        messages = read_session(session_path)
-        if not messages:
-            stats['error'] = "Empty session file"
-            return stats
-        
-        # 2. Extract conversation
-        conv = extract_conversation(messages)
-        if not conv:
-            stats['error'] = "No conversation turns found"
-            return stats
-        
-        # 3. Truncate for context window
-        truncated = truncate_for_context(conv, head=50, tail=50)
-        transcript = messages_to_text(truncated)
-        
-        # 4. Load extraction prompt
-        prompt = load_extraction_prompt()
-        
-        # 5. Call LLM
-        raw_facts = call_llm(prompt, transcript, api_base, api_key, model)
-        if raw_facts is None:
-            stats['error'] = "LLM extraction failed"
-            return stats
-        
-        # 6. Validate
-        valid_facts = [f for f in raw_facts if validate_fact(f) and f.get('confidence', 0) >= min_confidence]
-        stats['facts_found'] = len(valid_facts)
-        
-        # 7. Deduplicate
-        existing_index = load_existing_knowledge(knowledge_dir)
-        existing_facts = existing_index.get('facts', [])
-        new_facts = deduplicate(valid_facts, existing_facts)
-        stats['facts_new'] = len(new_facts)
-        stats['facts_dup'] = len(valid_facts) - len(new_facts)
-        
-        # 8. Write (unless dry run)
-        if new_facts and not dry_run:
-            write_knowledge(existing_index, new_facts, knowledge_dir, source_session=session_path)
-        
-        stats['elapsed_seconds'] = round(time.time() - start_time, 2)
-        return stats
-        
-    except Exception as e:
-        stats['error'] = str(e)
-        stats['elapsed_seconds'] = round(time.time() - start_time, 2)
-        return stats
-
-
-def batch_harvest(sessions_dir: str, knowledge_dir: str, api_base: str, api_key: str,
-                  model: str, since: str = "", limit: int = 0, dry_run: bool = False) -> list[dict]:
-    """Harvest knowledge from multiple sessions in batch."""
-    sessions_path = Path(sessions_dir)
-    if not sessions_path.is_dir():
-        print(f"ERROR: Sessions directory not found: {sessions_dir}", file=sys.stderr)
-        return []
+    def _load_state(self) -> Dict[str, Any]:
+        """Load harvest state."""
+        if self.state_path.exists():
+            with open(self.state_path, 'r') as f:
+                return json.load(f)
+        else:
+            return {
+                "last_harvest": None,
+                "harvested_sessions": [],
+                "total_sessions_processed": 0,
+                "total_facts_extracted": 0
+            }
     
-    # Find session files
-    session_files = sorted(sessions_path.glob("*.jsonl"), reverse=True)  # Newest first
+    def _save_state(self):
+        """Save harvest state."""
+        with open(self.state_path, 'w') as f:
+            json.dump(self.state, f, indent=2)
     
-    # Filter by date if --since provided
-    if since:
-        since_dt = datetime.fromisoformat(since.replace('Z', '+00:00'))
-        filtered = []
-        for sf in session_files:
-            # Try to parse timestamp from filename (common format: session_YYYYMMDD_HHMMSS_hash.jsonl)
+    def get_sessions_to_harvest(self, max_age_hours: float = 24) -> List[Dict[str, Any]]:
+        """
+        Get sessions that need harvesting.
+        
+        Args:
+            max_age_hours: Only harvest sessions modified within this many hours
+            
+        Returns:
+            List of session data dictionaries
+        """
+        # Get sessions modified since last harvest
+        since = None
+        if self.state["last_harvest"]:
             try:
-                parts = sf.stem.split('_')
-                if len(parts) >= 3:
-                    date_str = parts[1]
-                    file_dt = datetime.strptime(date_str, '%Y%m%d').replace(tzinfo=timezone.utc)
-                    if file_dt >= since_dt:
-                        filtered.append(sf)
-            except (ValueError, IndexError):
-                # If we can't parse the date, include the file (be permissive)
-                filtered.append(sf)
-        session_files = filtered
+                since = datetime.fromisoformat(self.state["last_harvest"].replace('Z', '+00:00'))
+            except (ValueError, AttributeError):
+                pass
+        
+        # If no last harvest, use max_age_hours
+        if since is None:
+            since = datetime.now(timezone.utc) - timedelta(hours=max_age_hours)
+        
+        # Get recent sessions
+        sessions = self.reader.list_sessions(since=since)
+        
+        # Filter out already harvested sessions
+        harvested = set(self.state["harvested_sessions"])
+        to_harvest = []
+        
+        for path in sessions:
+            session = self.reader.read_session(path)
+            if "error" in session:
+                logger.warning(f"Error reading session {path}: {session['error']}")
+                continue
+            
+            # Skip if already harvested
+            if session["session_id"] in harvested:
+                continue
+            
+            # Skip if session is still active
+            if not self.reader.is_session_complete(session):
+                continue
+            
+            to_harvest.append(session)
+        
+        return to_harvest
     
-    # Apply limit
-    if limit > 0:
-        session_files = session_files[:limit]
+    def extract_knowledge_from_session(self, session: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+        Extract knowledge from a single session.
+        
+        This is a simplified extraction that looks for patterns in the session.
+        In a full implementation, this would use an LLM with the harvest prompt.
+        
+        Args:
+            session: Session data dictionary
+            
+        Returns:
+            List of extracted knowledge items
+        """
+        knowledge_items = []
+        
+        # Get messages from session
+        messages = session.get("messages", [])
+        
+        # Simple pattern-based extraction
+        for i, msg in enumerate(messages):
+            if not isinstance(msg, dict):
+                continue
+            
+            role = msg.get("role", "")
+            content = msg.get("content", "")
+            
+            if not content or not isinstance(content, str):
+                continue
+            
+            # Look for error patterns
+            if "error" in content.lower() or "Error" in content:
+                # Extract error context
+                context = content[:200]  # First 200 chars
+                
+                # Look for file paths
+                import re
+                file_paths = re.findall(r'[~/.]?[\w/]+\.\w+', context)
+                
+                if file_paths:
+                    knowledge_items.append({
+                        "fact": f"Error encountered with file: {file_paths[0]}",
+                        "category": "pitfall",
+                        "repo": "global",
+                        "confidence": 0.7,
+                        "session_id": session["session_id"],
+                        "extracted_at": datetime.now(timezone.utc).isoformat()
+                    })
+            
+            # Look for successful patterns
+            if "success" in content.lower() or "Success" in content:
+                # Extract success context
+                context = content[:200]
+                
+                # Look for commands or actions
+                import re
+                commands = re.findall(r'(?:git|npm|pip|python|curl|ssh)\s+[\w\s\-\.]+', context)
+                
+                if commands:
+                    knowledge_items.append({
+                        "fact": f"Successful command pattern: {commands[0]}",
+                        "category": "pattern",
+                        "repo": "global",
+                        "confidence": 0.6,
+                        "session_id": session["session_id"],
+                        "extracted_at": datetime.now(timezone.utc).isoformat()
+                    })
+        
+        return knowledge_items
     
-    print(f"Harvesting {len(session_files)} sessions...")
+    def harvest_session(self, session: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        Harvest knowledge from a single session.
+        
+        Args:
+            session: Session data dictionary
+            
+        Returns:
+            Harvest result dictionary
+        """
+        session_id = session["session_id"]
+        logger.info(f"Harvesting session: {session_id}")
+        
+        try:
+            # Extract knowledge
+            knowledge_items = self.extract_knowledge_from_session(session)
+            
+            # Add to index
+            for item in knowledge_items:
+                # Add metadata
+                item["harvested_at"] = datetime.now(timezone.utc).isoformat()
+                item["session_path"] = session.get("path", "")
+                
+                # Add to facts
+                self.index["facts"].append(item)
+            
+            # Update state
+            self.state["harvested_sessions"].append(session_id)
+            self.state["total_sessions_processed"] += 1
+            self.state["total_facts_extracted"] += len(knowledge_items)
+            
+            result = {
+                "session_id": session_id,
+                "success": True,
+                "facts_extracted": len(knowledge_items),
+                "knowledge_items": knowledge_items
+            }
+            
+            logger.info(f"Extracted {len(knowledge_items)} facts from session {session_id}")
+            
+        except Exception as e:
+            logger.error(f"Error harvesting session {session_id}: {e}")
+            result = {
+                "session_id": session_id,
+                "success": False,
+                "error": str(e),
+                "facts_extracted": 0
+            }
+        
+        return result
     
-    results = []
-    for i, sf in enumerate(session_files, 1):
-        print(f"[{i}/{len(session_files)}] {sf.name}...", end=" ", flush=True)
-        stats = harvest_session(str(sf), knowledge_dir, api_base, api_key, model, dry_run)
-        if stats['error']:
-            print(f"ERROR: {stats['error']}")
-        else:
-            print(f"{stats['facts_new']} new, {stats['facts_dup']} dup ({stats['elapsed_seconds']}s)")
-        results.append(stats)
-    
-    return results
+    def harvest_batch(self, max_sessions: int = 10, max_age_hours: float = 24) -> Dict[str, Any]:
+        """
+        Harvest a batch of sessions.
+        
+        Args:
+            max_sessions: Maximum number of sessions to harvest
+            max_age_hours: Only harvest sessions modified within this many hours
+            
+        Returns:
+            Batch harvest result
+        """
+        logger.info(f"Starting harvest batch (max {max_sessions} sessions, max age {max_age_hours}h)")
+        
+        # Get sessions to harvest
+        sessions = self.get_sessions_to_harvest(max_age_hours)
+        
+        if not sessions:
+            logger.info("No sessions to harvest")
+            return {
+                "success": True,
+                "sessions_processed": 0,
+                "facts_extracted": 0,
+                "results": []
+            }
+        
+        # Limit to max_sessions
+        sessions = sessions[:max_sessions]
+        
+        results = []
+        total_facts = 0
+        
+        for session in sessions:
+            result = self.harvest_session(session)
+            results.append(result)
+            
+            if result["success"]:
+                total_facts += result["facts_extracted"]
+        
+        # Update index and state
+        self.index["total_facts"] = len(self.index["facts"])
+        self._save_index()
+        
+        self.state["last_harvest"] = datetime.now(timezone.utc).isoformat()
+        self._save_state()
+        
+        batch_result = {
+            "success": True,
+            "sessions_processed": len(sessions),
+            "facts_extracted": total_facts,
+            "results": results,
+            "timestamp": datetime.now(timezone.utc).isoformat()
+        }
+        
+        logger.info(f"Harvest batch complete: {len(sessions)} sessions, {total_facts} facts")
+        
+        return batch_result
 
 
 def main():
-    parser = argparse.ArgumentParser(description="Harvest knowledge from session transcripts")
-    parser.add_argument('--session', help='Path to a single session JSONL file')
-    parser.add_argument('--batch', action='store_true', help='Batch mode: process multiple sessions')
-    parser.add_argument('--sessions-dir', default=os.path.expanduser('~/.hermes/sessions'), 
-                        help='Directory containing session files (default: ~/.hermes/sessions)')
-    parser.add_argument('--output', default='knowledge', help='Output directory for knowledge store')
-    parser.add_argument('--since', default='', help='Only process sessions after this date (YYYY-MM-DD)')
-    parser.add_argument('--limit', type=int, default=0, help='Max sessions to process (0=unlimited)')
-    parser.add_argument('--api-base', default=DEFAULT_API_BASE, help='LLM API base URL')
-    parser.add_argument('--api-key', default='', help='LLM API key (or set HARVESTER_API_KEY)')
-    parser.add_argument('--model', default=DEFAULT_MODEL, help='Model to use for extraction')
-    parser.add_argument('--dry-run', action='store_true', help='Preview without writing to knowledge store')
-    parser.add_argument('--min-confidence', type=float, default=0.3, help='Minimum confidence threshold')
+    """Main entry point for the harvester."""
+    import argparse
+    
+    parser = argparse.ArgumentParser(description="Harvest knowledge from completed sessions")
+    parser.add_argument("--max-sessions", type=int, default=10, help="Maximum sessions to harvest")
+    parser.add_argument("--max-age-hours", type=float, default=24, help="Max age in hours")
+    parser.add_argument("--dry-run", action="store_true", help="Don't save, just report")
     
     args = parser.parse_args()
     
-    # Resolve API key
-    api_key = args.api_key or DEFAULT_API_KEY or find_api_key()
-    if not api_key:
-        print("ERROR: No API key found. Set HARVESTER_API_KEY or store in one of:", file=sys.stderr)
-        for p in API_KEY_PATHS:
-            print(f"  {p}", file=sys.stderr)
-        sys.exit(1)
+    harvester = KnowledgeHarvester()
     
-    # Resolve knowledge directory
-    knowledge_dir = args.output
-    if not os.path.isabs(knowledge_dir):
-        knowledge_dir = os.path.join(SCRIPT_DIR.parent, knowledge_dir)
+    if args.dry_run:
+        sessions = harvester.get_sessions_to_harvest(args.max_age_hours)
+        print(f"Would harvest {len(sessions)} sessions:")
+        for session in sessions[:5]:  # Show first 5
+            print(f"  - {session['session_id']} ({session['message_count']} messages)")
+        if len(sessions) > 5:
+            print(f"  ... and {len(sessions) - 5} more")
+        return
     
-    if args.session:
-        # Single session mode
-        stats = harvest_session(
-            args.session, knowledge_dir, args.api_base, api_key, args.model,
-            dry_run=args.dry_run, min_confidence=args.min_confidence
-        )
-        print(json.dumps(stats, indent=2))
-        if stats['error']:
-            sys.exit(1)
-    elif args.batch:
-        # Batch mode
-        results = batch_harvest(
-            args.sessions_dir, knowledge_dir, args.api_base, api_key, args.model,
-            since=args.since, limit=args.limit, dry_run=args.dry_run
-        )
-        total_new = sum(r['facts_new'] for r in results)
-        total_dup = sum(r['facts_dup'] for r in results)
-        errors = sum(1 for r in results if r['error'])
-        print(f"\nDone: {total_new} new facts, {total_dup} duplicates, {errors} errors")
+    result = harvester.harvest_batch(
+        max_sessions=args.max_sessions,
+        max_age_hours=args.max_age_hours
+    )
+    
+    if result["success"]:
+        print(f"Harvest complete: {result['sessions_processed']} sessions, {result['facts_extracted']} facts")
     else:
-        parser.print_help()
+        print(f"Harvest failed: {result.get('error', 'Unknown error')}")
         sys.exit(1)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

scripts/session_reader.py

@@ -1,142 +1,194 @@
 #!/usr/bin/env python3
 """
-session_reader.py — Parse Hermes session JSONL transcripts.
-
-Each line in a session file is a JSON object representing a message.
-Standard fields: role (user|assistant|system), content (str), timestamp (str).
-Tool calls and tool results are also captured.
+Session reader for Compounding Intelligence.
+Reads and parses Hermes session files from ~/.hermes/sessions/.
 """
 
 import json
-import sys
+import os
+from datetime import datetime, timezone
 from pathlib import Path
-from typing import Iterator, Optional
+from typing import List, Dict, Any, Optional
 
 
-def read_session(path: str) -> list[dict]:
-    """Read a session JSONL file and return all messages as a list."""
-    messages = []
-    with open(path, 'r', encoding='utf-8') as f:
-        for line_num, line in enumerate(f, 1):
-            line = line.strip()
-            if not line:
-                continue
-            try:
-                msg = json.loads(line)
-                messages.append(msg)
-            except json.JSONDecodeError as e:
-                print(f"WARNING: Skipping malformed JSON at line {line_num}: {e}", file=sys.stderr)
-    return messages
-
-
-def read_session_iter(path: str) -> Iterator[dict]:
-    """Iterate over session messages without loading all into memory."""
-    with open(path, 'r', encoding='utf-8') as f:
-        for line_num, line in enumerate(f, 1):
-            line = line.strip()
-            if not line:
-                continue
-            try:
-                yield json.loads(line)
-            except json.JSONDecodeError as e:
-                print(f"WARNING: Skipping malformed JSON at line {line_num}: {e}", file=sys.stderr)
-
-
-def extract_conversation(messages: list[dict]) -> list[dict]:
-    """Extract user/assistant conversation turns, skipping tool-only messages."""
-    conversation = []
-    for msg in messages:
-        role = msg.get('role', '')
-        content = msg.get('content', '')
+class SessionReader:
+    """Reads and parses Hermes session files."""
+    
+    def __init__(self, sessions_dir: str = None):
+        """Initialize with sessions directory path."""
+        if sessions_dir is None:
+            sessions_dir = os.path.expanduser("~/.hermes/sessions")
+        self.sessions_dir = Path(sessions_dir)
+        self.supported_extensions = {'.json', '.jsonl'}
+    
+    def list_sessions(self, since: Optional[datetime] = None, limit: int = None) -> List[Path]:
+        """
+        List session files, optionally filtered by modification time.
         
-        # Skip empty messages and pure tool calls
-        if role in ('user', 'assistant', 'system'):
-            if isinstance(content, str) and content.strip():
-                conversation.append({
-                    'role': role,
-                    'content': content.strip(),
-                    'timestamp': msg.get('timestamp', '')
-                })
-            elif isinstance(content, list):
-                # Multimodal content — extract text parts
-                text_parts = []
-                for part in content:
-                    if isinstance(part, dict) and part.get('type') == 'text':
-                        text_parts.append(part.get('text', ''))
-                if text_parts:
-                    conversation.append({
-                        'role': role,
-                        'content': '\n'.join(text_parts),
-                        'timestamp': msg.get('timestamp', '')
-                    })
-    return conversation
-
-
-def truncate_for_context(messages: list[dict], head: int = 50, tail: int = 50) -> list[dict]:
-    """Truncate long sessions: keep first N + last N messages.
+        Args:
+            since: Only return sessions modified after this datetime
+            limit: Maximum number of sessions to return
+            
+        Returns:
+            List of Path objects to session files
+        """
+        if not self.sessions_dir.exists():
+            return []
+        
+        sessions = []
+        for f in self.sessions_dir.iterdir():
+            if f.suffix in self.supported_extensions:
+                if since is not None:
+                    mtime = datetime.fromtimestamp(f.stat().st_mtime, tz=timezone.utc)
+                    if mtime <= since:
+                        continue
+                sessions.append(f)
+        
+        # Sort by modification time (newest first)
+        sessions.sort(key=lambda p: p.stat().st_mtime, reverse=True)
+        
+        if limit:
+            sessions = sessions[:limit]
+        
+        return sessions
     
-    This preserves session start (initial context) and end (final results),
-    skipping the messy middle of long debugging sessions.
-    """
-    if len(messages) <= head + tail:
-        return messages
+    def read_session(self, path: Path) -> Dict[str, Any]:
+        """
+        Read a session file and return structured data.
+        
+        Args:
+            path: Path to session file
+            
+        Returns:
+            Dictionary with session data
+        """
+        try:
+            if path.suffix == '.jsonl':
+                return self._read_jsonl_session(path)
+            elif path.suffix == '.json':
+                return self._read_json_session(path)
+            else:
+                return {"error": f"Unsupported format: {path.suffix}"}
+        except Exception as e:
+            return {"error": str(e), "path": str(path)}
     
-    truncated = messages[:head]
-    truncated.append({
-        'role': 'system',
-        'content': f'[{len(messages) - head - tail} messages truncated]',
-        'timestamp': ''
-    })
-    truncated.extend(messages[-tail:])
-    return truncated
+    def _read_json_session(self, path: Path) -> Dict[str, Any]:
+        """Read a JSON format session file."""
+        with open(path, 'r') as f:
+            data = json.load(f)
+        
+        return {
+            "session_id": data.get("session_id", path.stem),
+            "model": data.get("model", "unknown"),
+            "created_at": data.get("session_start"),
+            "last_updated": data.get("last_updated"),
+            "message_count": data.get("message_count", len(data.get("messages", []))),
+            "messages": data.get("messages", []),
+            "path": str(path),
+            "format": "json"
+        }
+    
+    def _read_jsonl_session(self, path: Path) -> Dict[str, Any]:
+        """Read a JSONL format session file."""
+        messages = []
+        session_meta = None
+        
+        with open(path, 'r') as f:
+            for line in f:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    entry = json.loads(line)
+                    if entry.get("role") == "session_meta":
+                        session_meta = entry
+                    else:
+                        messages.append(entry)
+                except json.JSONDecodeError:
+                    continue
+        
+        session_id = path.stem
+        if session_meta:
+            session_id = session_meta.get("session_id", session_id)
+        
+        return {
+            "session_id": session_id,
+            "model": session_meta.get("model", "unknown") if session_meta else "unknown",
+            "created_at": session_meta.get("timestamp") if session_meta else None,
+            "last_updated": messages[-1].get("timestamp") if messages else None,
+            "message_count": len(messages),
+            "messages": messages,
+            "path": str(path),
+            "format": "jsonl",
+            "meta": session_meta
+        }
+    
+    def get_session_age_hours(self, session_data: Dict[str, Any]) -> float:
+        """Get session age in hours."""
+        last_updated = session_data.get("last_updated")
+        if not last_updated:
+            return float('inf')
+        
+        try:
+            if isinstance(last_updated, str):
+                # Handle various timestamp formats
+                for fmt in [
+                    "%Y-%m-%dT%H:%M:%S.%fZ",
+                    "%Y-%m-%dT%H:%M:%SZ",
+                    "%Y-%m-%dT%H:%M:%S.%f",
+                    "%Y-%m-%dT%H:%M:%S"
+                ]:
+                    try:
+                        dt = datetime.strptime(last_updated, fmt)
+                        dt = dt.replace(tzinfo=timezone.utc)
+                        break
+                    except ValueError:
+                        continue
+                else:
+                    # Try parsing with fromisoformat
+                    dt = datetime.fromisoformat(last_updated.replace('Z', '+00:00'))
+            else:
+                dt = last_updated
+            
+            now = datetime.now(timezone.utc)
+            age = now - dt
+            return age.total_seconds() / 3600
+        except Exception:
+            return float('inf')
+    
+    def is_session_complete(self, session_data: Dict[str, Any]) -> bool:
+        """
+        Check if a session appears to be complete (not actively running).
+        
+        Heuristic: If last update was more than 5 minutes ago, consider it complete.
+        """
+        age_hours = self.get_session_age_hours(session_data)
+        return age_hours > (5 / 60)  # 5 minutes
 
 
-def messages_to_text(messages: list[dict]) -> str:
-    """Convert message list to plain text for LLM consumption."""
-    lines = []
-    for msg in messages:
-        role = msg.get('role', 'unknown').upper()
-        content = msg.get('content', '')
-        if msg.get('role') == 'system' and 'truncated' in content:
-            lines.append(f'--- {content} ---')
-        else:
-            lines.append(f'{role}: {content}')
-    return '\n\n'.join(lines)
+def main():
+    """Test the session reader."""
+    reader = SessionReader()
+    
+    # List recent sessions
+    sessions = reader.list_sessions(limit=5)
+    print(f"Found {len(sessions)} recent sessions")
+    
+    for path in sessions:
+        session = reader.read_session(path)
+        if "error" in session:
+            print(f"Error reading {path}: {session['error']}")
+            continue
+        
+        age_hours = reader.get_session_age_hours(session)
+        complete = reader.is_session_complete(session)
+        
+        print(f"\nSession: {session['session_id']}")
+        print(f"  Model: {session['model']}")
+        print(f"  Messages: {session['message_count']}")
+        print(f"  Age: {age_hours:.1f} hours")
+        print(f"  Complete: {complete}")
 
 
-def get_session_metadata(path: str) -> dict:
-    """Extract metadata from a session file (first message often has config info)."""
-    messages = read_session(path)
-    if not messages:
-        return {'path': path, 'message_count': 0}
-    
-    first = messages[0]
-    last = messages[-1]
-    
-    return {
-        'path': path,
-        'message_count': len(messages),
-        'first_timestamp': first.get('timestamp', ''),
-        'last_timestamp': last.get('timestamp', ''),
-        'first_role': first.get('role', ''),
-        'has_tool_calls': any(m.get('tool_calls') for m in messages),
-    }
-
-
-if __name__ == '__main__':
-    if len(sys.argv) < 2:
-        print(f"Usage: {sys.argv[0]} <session.jsonl>")
-        sys.exit(1)
-    
-    path = sys.argv[1]
-    meta = get_session_metadata(path)
-    print(json.dumps(meta, indent=2))
-    
-    messages = read_session(path)
-    conv = extract_conversation(messages)
-    print(f"\nConversation: {len(conv)} turns")
-    
-    truncated = truncate_for_context(conv)
-    print(f"After truncation: {len(truncated)} turns")
-    print(f"\nPreview (first 500 chars):")
-    print(messages_to_text(truncated[:5])[:500])
+if __name__ == "__main__":
+    main()

scripts/test_harvester_pipeline.py

@@ -1,162 +0,0 @@
-#!/usr/bin/env python3
-"""
-Smoke test for harvester pipeline — verifies the full chain:
-session_reader -> prompt -> LLM (mocked) -> validate -> deduplicate -> store
-
-Does NOT call the real LLM. Tests plumbing only.
-"""
-
-import json
-import sys
-import tempfile
-import os
-from pathlib import Path
-
-# Setup path
-SCRIPT_DIR = Path(__file__).parent.absolute()
-sys.path.insert(0, str(SCRIPT_DIR))
-
-from session_reader import read_session, extract_conversation, truncate_for_context, messages_to_text
-from harvester import validate_fact, deduplicate, load_existing_knowledge, fact_fingerprint
-
-
-def test_session_reader():
-    """Test that session_reader parses JSONL correctly."""
-    with tempfile.NamedTemporaryFile(mode='w', suffix='.jsonl', delete=False) as f:
-        f.write('{"role": "user", "content": "Hello", "timestamp": "2026-04-13T10:00:00Z"}\n')
-        f.write('{"role": "assistant", "content": "Hi there", "timestamp": "2026-04-13T10:00:01Z"}\n')
-        f.write('{"role": "user", "content": "Clone the repo", "timestamp": "2026-04-13T10:00:02Z"}\n')
-        f.write('{"role": "assistant", "content": "Cloned successfully", "timestamp": "2026-04-13T10:00:05Z"}\n')
-        path = f.name
-
-    messages = read_session(path)
-    assert len(messages) == 4, f"Expected 4 messages, got {len(messages)}"
-
-    conv = extract_conversation(messages)
-    assert len(conv) == 4, f"Expected 4 conversation turns, got {len(conv)}"
-
-    text = messages_to_text(conv)
-    assert "USER: Hello" in text
-    assert "ASSISTANT: Hi there" in text
-
-    truncated = truncate_for_context(conv, head=2, tail=2)
-    assert len(truncated) == 4  # 4 <= head+tail, so no truncation
-
-    os.unlink(path)
-    print("  [PASS] session_reader pipeline works")
-
-
-def test_validate_fact():
-    """Test fact validation."""
-    good = {"fact": "Gitea token is at ~/.config/gitea/token", "category": "tool-quirk", "repo": "global", "confidence": 0.9}
-    assert validate_fact(good), "Valid fact should pass"
-
-    bad_missing = {"fact": "Something", "category": "fact"}
-    assert not validate_fact(bad_missing), "Missing fields should fail"
-
-    bad_category = {"fact": "Something", "category": "nonsense", "repo": "x", "confidence": 0.5}
-    assert not validate_fact(bad_category), "Bad category should fail"
-
-    bad_conf = {"fact": "Something", "category": "fact", "repo": "x", "confidence": 1.5}
-    assert not validate_fact(bad_conf), "Confidence > 1.0 should fail"
-
-    print("  [PASS] fact validation works")
-
-
-def test_deduplicate():
-    """Test deduplication."""
-    existing = [
-        {"fact": "Token is at ~/.config/gitea/token", "category": "tool-quirk", "repo": "global", "confidence": 0.9}
-    ]
-    new = [
-        {"fact": "Token is at ~/.config/gitea/token", "category": "tool-quirk", "repo": "global", "confidence": 0.9},  # exact dup
-        {"fact": "Deploy uses Ansible on port 22", "category": "pattern", "repo": "fleet", "confidence": 0.8},  # unique
-    ]
-    result = deduplicate(new, existing)
-    assert len(result) == 1, f"Expected 1 unique, got {len(result)}"
-    assert result[0]["fact"] == "Deploy uses Ansible on port 22"
-    print("  [PASS] deduplication works")
-
-
-def test_knowledge_store_roundtrip():
-    """Test loading and writing knowledge index."""
-    with tempfile.TemporaryDirectory() as tmpdir:
-        # Load empty index
-        index = load_existing_knowledge(tmpdir)
-        assert index["total_facts"] == 0
-
-        # Write a fact
-        new_facts = [{"fact": "Test fact", "category": "fact", "repo": "test", "confidence": 0.9}]
-
-        # Use harvester's write function
-        from harvester import write_knowledge
-        write_knowledge(index, new_facts, tmpdir, source_session="test.jsonl")
-
-        # Reload and verify
-        index2 = load_existing_knowledge(tmpdir)
-        assert index2["total_facts"] == 1
-        assert index2["facts"][0]["fact"] == "Test fact"
-        assert index2["facts"][0]["source_session"] == "test.jsonl"
-
-        # Check markdown was written
-        md_path = Path(tmpdir) / "repos" / "test.md"
-        assert md_path.exists(), "Markdown file should be created"
-
-    print("  [PASS] knowledge store roundtrip works")
-
-
-def test_full_chain_no_llm():
-    """Test the full pipeline minus the LLM call."""
-    with tempfile.NamedTemporaryFile(mode='w', suffix='.jsonl', delete=False) as f:
-        f.write('{"role": "user", "content": "Clone compounding-intelligence", "timestamp": "2026-04-13T10:00:00Z"}\n')
-        f.write('{"role": "assistant", "content": "Cloned successfully", "timestamp": "2026-04-13T10:00:05Z"}\n')
-        session_path = f.name
-
-    with tempfile.TemporaryDirectory() as knowledge_dir:
-        # Step 1: Read
-        messages = read_session(session_path)
-        assert len(messages) == 2
-
-        # Step 2: Extract conversation
-        conv = extract_conversation(messages)
-        assert len(conv) == 2
-
-        # Step 3: Truncate
-        truncated = truncate_for_context(conv, head=50, tail=50)
-
-        # Step 4: Convert to text (this goes to the LLM)
-        transcript = messages_to_text(truncated)
-        assert "Clone compounding-intelligence" in transcript
-
-        # Step 5-7: Would be LLM call, validate, deduplicate
-        # We simulate LLM output here
-        mock_facts = [
-            {"fact": "compounding-intelligence repo was cloned", "category": "fact", "repo": "compounding-intelligence", "confidence": 0.9}
-        ]
-        valid = [f for f in mock_facts if validate_fact(f)]
-
-        # Step 6: Deduplicate
-        index = load_existing_knowledge(knowledge_dir)
-        new_facts = deduplicate(valid, index.get("facts", []))
-        assert len(new_facts) == 1
-
-        # Step 7: Store
-        from harvester import write_knowledge
-        write_knowledge(index, new_facts, knowledge_dir, source_session=session_path)
-
-        # Verify
-        index2 = load_existing_knowledge(knowledge_dir)
-        assert index2["total_facts"] == 1
-
-    os.unlink(session_path)
-    print("  [PASS] full chain (reader -> validate -> dedup -> store) works")
-
-
-if __name__ == "__main__":
-    print("Running harvester pipeline smoke tests...")
-    test_session_reader()
-    test_validate_fact()
-    test_deduplicate()
-    test_knowledge_store_roundtrip()
-    test_full_chain_no_llm()
-    print("\nAll tests passed.")