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Session 0ldXYBBdn3AS

Full ID: 0ldXYBBdn3ASH9VfG
Messages: 28
Distillations: 0
Time range: 2026-06-07 21:34:00 — 2026-06-07 21:43:21

Conversation (28 messages)

I need you to investigate the SQLite database at ~/.local/share/lore/lore.db (Lore's persistent storage) to determine whether distillation and curation are happening across all model providers, not just Anthropic.

The database schema is defined in packages/core/src/db.ts of the Lore repo at /home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/witty-wolf. The relevant tables are:

  • sessions — has id, model, created_at, provider, etc.
  • temporal_messages — raw message store
  • distillations — has id, session_id, gen, content, created_at
  • knowledge — long-term memory entries (curated)
  • curator_runs — tracks when the curator ran

Please:

  1. Read the schema in packages/core/src/db.ts to understand the table structures.
  2. Use sqlite3 (read-only) to query the live ~/.local/share/lore/lore.db to: a. List the last 20 sessions ordered by created_at DESC, with their model/provider fields b. For each recent session, count how many distillations exist (group by gen) c. List the last 20 distillation runs with the session_id and model (joining sessions to see model) d. List the last 20 curator_runs with the model they ran against e. List the last 20 knowledge entries (created_at DESC) with their source session f. Count knowledge entries by source session and check if non-Anthropic sessions contributed any
  3. Determine: are there non-Anthropic sessions (OpenAI, Google, etc.) in the recent history? Did they get distilled? Curated?

Run sqlite3 in read-only mode. If you cannot run sqlite3, use the bun/node sqlite3 module to query the DB. Be careful — do NOT modify the DB.

Return:

  • The exact sqlite3 commands/queries you used
  • Tabular results (or summarized counts) for each query
  • A clear conclusion: are non-Anthropic sessions being distilled and curated, or is there a gap?
  • Any patterns suggesting the gap (e.g. sessions exist but have zero distillations)
gateway · 2026-06-07 21:34:00
reasoning

The user wants me to investigate a SQLite database to determine whether distillation and curation are happening across all model providers, not just Anthropic. Let me start by:

  1. Reading the schema in packages/core/src/db.ts
  2. Querying the live database

Let me do these in parallel where possible. First, let me read the schema and check if sqlite3 is available.

I'll investigate this systematically. Let me start by reading the schema and checking tooling availability.

MiniMax-M3 · 2026-06-07 21:34:00 · ~163 tokens
result 
<path>/home/byk/.local/share/opencode/worktree/51d1015fd1f616acf9a5ffaad9331ec6b304586b/witty-wolf/packages/core/src/db.ts</path>
<type>file</type>
<content>
1: import { Database } from "#db/driver";
2: import { join, dirname } from "node:path";
3: import { mkdirSync } from "node:fs";
4: import { getGitRemote } from "./git";
5: import { dataDir } from "./data-dir";
6: 
7: /**
8:  * Callback fired when project rows are created or mutated (merge, rename, etc.).
9:  * Used by data.ts to invalidate its listing caches without a circular import.
10:  */
11: let onProjectMutationCb: (() => void) | null = null;
12: 
13: /** Register a callback for project mutations. Only one callback is supported. */
14: export function onProjectMutation(cb: () => void): void {
15:   onProjectMutationCb = cb;
16: }
17: 
18: /** Fire the project mutation callback (if registered). */
19: function fireProjectMutation(): void {
20:   onProjectMutationCb?.();
21: }
22: 
23: /**
24:  * Extract the repository name ...
result 
/usr/bin/sqlite3
3.45.1 2024-01-30 16:01:20 e876e51a0ed5c5b3126f52e532044363a014bc594cfefa87ffb5b82257ccalt1 (64-bit)
result 
total 1386712
drwxr-xr-x 1 byk byk       164 Jun  7 21:33 .
drwxrwxr-x 1 byk byk       276 Jun  5 20:45 ..
-rw-r--r-- 1 byk byk         5 Jun  7 21:33 gateway.port
-rw-r--r-- 1 byk byk    203293 Apr 29 23:30 gradient.log
-rw-r--r-- 1 byk byk 776445952 Jun  7 21:32 lore.db
-rw-r--r-- 1 byk byk 630095872 May 12 17:07 lore.db.bak
-rw-r--r-- 1 byk byk     32768 Jun  7 21:34 lore.db-shm
-rw-r--r-- 1 byk byk   6311872 Jun  7 21:34 lore.db-wal
-rw-r--r-- 1 byk byk   1576656 Jun  7 21:33 lore.log
-rw-r--r-- 1 byk byk   5316932 Jun  7 13:31 lore.log.1
gateway · 2026-06-07 21:35:59
reasoning

I have a good amount of info from the schema. Now I need to understand the actual table structure. The user mentioned a sessions table, but I don't see it in the schema. Let me check if it's there, and also look for curator_runs. Let me query the live DB to discover the actual tables.

The user mentioned:

  • sessions — has id, model, created_at, provider, etc.
  • temporal_messages — raw message store
  • distillations — has id, session_id, gen, content, created_at
  • knowledge — long-term memory entries (curated)
  • curator_runs — tracks when the curator ran

But the schema I see has:

  • projects
  • temporal_messages (no session_id mentioned in user's list but it's in the schema with project_id, session_id, role, content, tokens, distilled, created_at, metadata)
  • distillations (with narrative, facts, source_ids, generation, etc. ...

I have the schema and sqlite3 is available. The user's description doesn't match the schema exactly — there's session_state not sessions, and curator_runs doesn't appear in migrations. Let me discover the actual live schema, then run the analysis.

MiniMax-M3 · 2026-06-07 21:35:59 · ~546 tokens
result 
daily_costs                 knowledge_fts_docsize     
dedup_feedback              knowledge_fts_idx         
distillation_fts            knowledge_refs            
distillation_fts_config     knowledge_transfers       
distillation_fts_data       kv_meta                   
distillation_fts_docsize    lat_sections              
distillation_fts_idx        lat_sections_fts          
distillations               lat_sections_fts_config   
entities                    lat_sections_fts_data     
entities_fts                lat_sections_fts_docsize  
entities_fts_config         lat_sections_fts_idx      
entities_fts_data           metadata                  
entities_fts_docsize        project_path_aliases      
entities_fts_idx            projects                  
entity_aliases              schema_version            
entity_aliases_fts          session_state             
entity_aliases_fts_config   team_config               
entity_aliases_fts_data     team_knowledge            ...
result 
CREATE TABLE session_state (
    session_id TEXT PRIMARY KEY,
    force_min_layer INTEGER NOT NULL DEFAULT 0,
    updated_at INTEGER NOT NULL
  , conversation_cost REAL NOT NULL DEFAULT 0, worker_cost REAL NOT NULL DEFAULT 0, conversation_turns INTEGER NOT NULL DEFAULT 0, cache_read_tokens INTEGER NOT NULL DEFAULT 0, cache_write_tokens INTEGER NOT NULL DEFAULT 0, warmup_savings REAL NOT NULL DEFAULT 0, warmup_hits INTEGER NOT NULL DEFAULT 0, ttl_savings REAL NOT NULL DEFAULT 0, ttl_hits INTEGER NOT NULL DEFAULT 0, batch_savings REAL NOT NULL DEFAULT 0, avoided_compactions INTEGER NOT NULL DEFAULT 0, avoided_compaction_cost REAL NOT NULL DEFAULT 0, last_curated_at INTEGER NOT NULL DEFAULT 0, message_count INTEGER NOT NULL DEFAULT 0, turns_since_curation INTEGER NOT NULL DEFAULT 0, ltm_cache_text TEXT, ltm_cache_tokens INTEGER, ltm_pin_text TEXT, ltm_pin_tokens INTEGER, consecutive_text_only_turns INTEGER NOT NULL DEFAULT 0, fingerprint TEXT NOT NULL DEFAULT '', header_session_id TEXT, ...
result 
CREATE TABLE distillations (
      id TEXT PRIMARY KEY,
      project_id TEXT NOT NULL REFERENCES projects(id),
      session_id TEXT NOT NULL,
      narrative TEXT NOT NULL,
      facts TEXT NOT NULL,
      source_ids TEXT NOT NULL,
      generation INTEGER DEFAULT 0,
      token_count INTEGER DEFAULT 0,
      created_at INTEGER NOT NULL DEFAULT (unixepoch()),
      observations TEXT NOT NULL DEFAULT '',
      archived INTEGER NOT NULL DEFAULT 0,
      embedding BLOB,
      r_compression REAL,
      c_norm REAL
    , call_type TEXT);
CREATE INDEX idx_distillation_session ON distillations(session_id);
CREATE INDEX idx_distillation_archived ON distillations(archived);
CREATE INDEX idx_distillation_project_session ON distillations(project_id, session_id);
CREATE INDEX idx_distillation_project_session_gen_archived ON distillations(project_id, session_id, generation, archived);
CREATE TRIGGER distillation_fts_insert AFTER INSERT ON distillations BEGIN
    INSERT INTO ...
result 
CREATE TABLE knowledge (
      id TEXT PRIMARY KEY,
      project_id TEXT,
      category TEXT NOT NULL,
      title TEXT NOT NULL,
      content TEXT NOT NULL,
      source_session TEXT,
      cross_project INTEGER DEFAULT 0,
      confidence REAL DEFAULT 1.0,
      created_at INTEGER NOT NULL DEFAULT (unixepoch()),
      updated_at INTEGER NOT NULL DEFAULT (unixepoch()),
      metadata TEXT,
      embedding BLOB
    , created_by TEXT, updated_by TEXT, sensitivity TEXT NOT NULL DEFAULT 'normal', promotion_status TEXT, promoted_at INTEGER, approval_status TEXT NOT NULL DEFAULT 'auto', approved_by TEXT, approved_at INTEGER, source_user_id TEXT, source_entry_id TEXT, last_accessed_at INTEGER);
CREATE TRIGGER knowledge_fts_insert AFTER INSERT ON knowledge BEGIN
    INSERT INTO knowledge_fts(rowid, title, content, category)
    VALUES (new.rowid, new.title, new.content, new.category);
  END;
CREATE TRIGGER knowledge_fts_delete AFTER DELETE ON knowledge BEGIN
    INSERT INTO ...
gateway · 2026-06-07 21:36:13
reasoning

Critical findings:

  • No sessions table — the closest is session_state, which doesn't have model or provider columns
  • No curator_runs table — the user described it but it doesn't exist
  • knowledge has source_session and created_at — good for analysis
  • distillations has session_id, generation, created_at — good

This means the user's premise (a sessions table with model and provider fields) is WRONG. Lore does not track model/provider at the session or distillation level — the model is implicit in the upstream LLM call but not stored.

Let me verify this fully by checking if model or provider exists anywhere. Let me also check tool_calls (which I saw) and metadata (which I saw).

Wait — let me also check the live lore.log and gradient.log for model info. But first let me confirm the schema has no model/provider column.

Critical finding: there is no sessions table (the closest is session_state, which has no model/provider columns) and no curator_runs table. The user's premise is wrong — let me confirm by checking if model or provider columns exist anywhere, then run the queries that are still possible.

MiniMax-M3 · 2026-06-07 21:36:13 · ~397 tokens
result 
approval_status
approved_at
approved_by
archived
avoided_compaction_cost
avoided_compactions
batch_savings
bust_rate_ema
cache_read_tokens
cache_write_tokens
call_id
call_type
category
c_norm
confidence
consecutive_text_only_turns
content
conversation_cost
conversation_turns
created_at
created_by
cross_project
distilled
duration_ms
dynamic_context_cap
embedding
error_message
error_type
facts
fingerprint
force_min_layer
generation
header_name
header_session_id
id
inter_bust_interval_ema
is_subagent
key
last_accessed_at
last_bust_at
last_curated_at
last_known_input
last_layer
last_turn_at
ltm_cache_text
ltm_cache_tokens
ltm_pin_text
ltm_pin_tokens
message_count
message_id
metadata
narrative
observations
parent_session_id
project_id
promoted_at
promotion_status
r_compression
resolved_conversation_ttl
role
sensitivity
session_id
source_entry_id
source_ids
source_session
source_user_id
status
title
token_count
tokens
tool
ttl_hits
ttl_savings
turns_since_curation
updated_at
updated_by
value...
result 
instance_id|658a89a4-fe4b-40ad-aec9-52074ea3d459|1778534440331
release_channel|nightly|1780751561286
result 
session_state
result 
lore_file_cache:/home/byk/Code/opencode-lore/.lore.md|{"mtimeMs":1780751106129.2993,"hash":"085645bd"}
lore:embedding_config|local:nomic-ai/nomic-embed-text-v1.5:768
lore_file_cache:/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/witty-garden/.lore.md|{"mtimeMs":1780552459179.2412,"hash":"37a7977a"}
lore_file_cache:/home/byk/Code/getsentry/sentry/.lore.md|{"mtimeMs":1779212103769.233,"hash":"2b6bcad3"}
lore_file_cache:/home/byk/Code/opencode/.lore.md|{"mtimeMs":1780826632138.7644,"hash":"774894f3"}
warmup_circuit_breaker|{"tripped":false,"failures":0}
lore_file_cache:/home/byk/.local/share/opencode/worktree/55fa901aca64a01fa4b5c2abce1c85c1c27475e7/swift-squid/.lore.md|{"mtimeMs":1780835199857.767,"hash":"88dc1c82"}
lore_file_cache:/home/byk/Code/getsentry/spotlight/.lore.md|{"mtimeMs":1780583571956.2383,"hash":"faa060f2"}
lore_file_cache:/home/byk/.local/share/opencode/worktree/125e3ebeb747c35789e81a4b036ef58ca480e265/tidy-orchid/.lore.md|{"mtimeMs":17...
gateway · 2026-06-07 21:36:29
reasoning

Confirmed: there is no sessions table, no curator_runs table, and no model or provider column anywhere in the database. Lore doesn't persist the model identity at the session/distillation/curation level.

However, I can still answer part of the question with the data we have. Let me check:

  1. tool_calls — added in v31, captures tool calls. No model field.
  2. daily_costs — tracks daily cost by bucket but no model breakdown
  3. Can I look at the gateway log to find the model being used per session?

Let me also check if there's any way to infer the model from session data. The header_name in session_state is the name from the API call (which can be the model name from the client). Let me check the header_name and fingerprint fields, and warmup_state (which may contain model). ...

Confirmed: there is no model or provider column anywhere in the schema — including in distillations, knowledge, temporal_messages, tool_calls, or session_state. Let me check if header_name or fingerprint (in session_state) reveals model info, and look at the actual data.

MiniMax-M3 · 2026-06-07 21:36:29 · ~463 tokens
result 
|750
x-lore-session-id|273
result 
1|5817|234|190103|31|11955
result 
2026-06-07|worker|20.9555241
2026-06-07|warmup|5.2012305
2026-06-07|conversation|291.88322135
2026-06-06|worker|42.1714335
2026-06-06|warmup|4.71405425
2026-06-06|conversation|980.089921599999
2026-06-05|worker|22.14448695
2026-06-05|warmup|22.62850225
2026-06-05|conversation|475.736568100001
2026-06-04|worker|15.71530305
2026-06-04|warmup|5.4556545
2026-06-04|conversation|853.534441250002
2026-06-03|worker|14.0653038
2026-06-03|warmup|3.2519335
2026-06-03|conversation|583.72550005
result 
1VULzfwFxMAEYSvvg|{"lastWarmupAt":0,"warmupCount":0,"warmupHits":0,"disabled":false}
08bE62pcOVCVOvQ9I|{"lastWarmupAt":0,"warmupCount":0,"warmupHits":0,"disabled":false}
0t5bsIvIvYE7IeAyG|{"lastWarmupAt":0,"warmupCount":0,"warmupHits":0,"disabled":true}
1XkGW61V6YKlT1vam|{"lastWarmupAt":1778775149432,"warmupCount":0,"warmupHits":24,"disabled":false}
00nNmZnvcqr8WZIYZ|{"lastWarmupAt":0,"warmupCount":0,"warmupHits":0,"disabled":true}
gateway · 2026-06-07 21:36:50
reasoning

Findings:

  • header_name is just a session name like "1" or "x-lore-session-id" — not a model name
  • warmup_state JSON has no model field
  • 1 session_state row, 5817 distillations, 234 knowledge, 190103 temporal messages, 31 projects, 11955 tool_calls
  • daily_costs has worker/warmup/conversation buckets but no model breakdown
  • The DB is 776MB and full of data

Let me now look at the lore.log and gateway logs to see if model info is there. Also, let me check the tool_calls — those are recent additions. But the user is asking about model information — let me also check the gradient.log briefly. And let me try to look at the actual distillation table to see if any model info is encoded in the metadata field.

Actually, more importantly: the user's question presumes a sessions table with model/provider. It doesn't exist. So I need to be honest: the database does NOT track model/provider, so the question as posed is unanswerable from the DB alone. ...

header_name is just session names, not model names. The DB has no model/provider field anywhere. Let me run the queries that ARE possible and check the logs for any model correlation.

MiniMax-M3 · 2026-06-07 21:36:50 · ~594 tokens
result 
id                                    session_id         generation  archived  ts  obs_len
------------------------------------  -----------------  ----------  --------  --  -------
0190efa5-7bcf-4440-b0b1-9e2ba424c6c9  0Y5hHj1SfPM16CHug  0           0             427    
d9ad7d81-8d2b-41c9-9ea5-5d2c05c8157c  0Y5hHj1SfPM16CHug  0           0             122    
b797ecf3-7bc4-4f8f-b354-918e820dc40c  1Yjc8a0YxYNutCblI  0           0             908    
b70f6dd7-c8c2-4618-a49c-ddbaa32e07a8  1Yjc8a0YxYNutCblI  0           0             1364   
fd5982c6-a577-449c-874f-e6178d4e90cd  1Yjc8a0YxYNutCblI  0           0             1008   
df43f0bb-265d-4c18-9f7f-7c2acbf5bd06  1Yjc8a0YxYNutCblI  0           0             344    
220d0a2d-6efe-4fa0-ab50-6a5935a846f8  1Yjc8a0YxYNutCblI  0           0             322    
58e30883-34b9-43b3-9190-12cda8dfded1  1Yjc8a0YxYNutCblI  0           0             2479   
5054dada-7c91-4520-9089-f1ba95af67e1  0pC9gNWfsT678F9on  0           0             2330   ...
result 
id                                    category      title                                                                                                                    source_session     ts
------------------------------------  ------------  -----------------------------------------------------------------------------------------------------------------------  -----------------  --
019ea401-58fd-7491-93ce-04504a671f57  preference    Avoids execution yet                                                                                                     0pC9gNWfsT678F9on    
019ea3eb-6364-75c0-9f37-abaa39d09d2a  preference    Always suppress noisy output in test environments                                                                        0BLMn3hmhuUFYLJXU    
019ea3a7-9086-7ba6-990e-f8a55394b754  preference    Always patch createRequire calls to use pathToFileURL(__filename).href instead of import.meta.url in bundled CJS output  0p4VXwVSp5OXerSpp    ...
result 
session_id         generation  n_distillations
-----------------  ----------  ---------------
001gOPziBpGSscIqW  0           180            
001gOPziBpGSscIqW  1           1              
001gOPziBpGSscIqW  2           1              
001gOPziBpGSscIqW  3           3              
001gOPziBpGSscIqW  4           2              
001gOPziBpGSscIqW  5           4              
001gOPziBpGSscIqW  6           4              
001gOPziBpGSscIqW  7           4              
001gOPziBpGSscIqW  8           1              
001o9CjSy05bg3scg  0           3              
005TbXCXHUlMk7pnS  0           10             
00KgRy4xOi5euLQww  0           1              
00KwGKqz9Nndhx8Vq  0           5              
00abPi9cYf7MKLR4n  0           3              
00bOQIb7etC68Hiya  0           18             
00bOQIb7etC68Hiya  1           1              
00bOQIb7etC68Hiya  2           1              
00e2QqvnhW98bY3vr  0           1              
00nNmZnvcqr8WZIYZ  0           1              ...
result 
session_id         updated_at     conversation_turns  message_count  last_curated_at  fingerprint       header_name  last_known_input  distillations  msgs  tool_calls
-----------------  -------------  ------------------  -------------  ---------------  ----------------  -----------  ----------------  -------------  ----  ----------
07Eew9hkBS4apf7HI  1780868207281  8                   19             0                9fa85d21e5df1935               82824             0              18    20        
1bBkTypkeN75snCbp  1780868206144  7                   19             0                94edcae77dd54ad6               85028             0              18    24        
0ldXYBBdn3ASH9VfG  1780868197667  4                   9              0                fb5f6a07e3e0fcff               33750             0              10    19        
0pC9gNWfsT678F9on  1780868197384  51                  101            0                9631f0d1114f3e75               107917            2              92    67       ...
gateway · 2026-06-07 21:37:20
reasoning

Critical observations from the data:

  1. Many recent active sessions have ZERO distillations and ZERO last_curated_at:

    • 07Eew9hkBS4apf7HI (8 turns, 19 messages) → 0 distillations, last_curated_at=0
    • 1bBkTypkeN75snCbp (7 turns, 19 messages) → 0 distillations, last_curated_at=0
    • 0ldXYBBdn3ASH9VfG (4 turns, 9 messages) → 0 distillations
    • 07H1R9yJXGMBYPhsf (58 turns, 389 messages!) → 0 distillations, last_curated_at=0
    • 0f6iSiGPhiWEQErfj (7 turns, 13 messages) → 0 distillations
    • 0ML3ygaVp8PXACiEl (1 turn) → 0 (newly started, expected)

  2. Some sessions DO get distilled AND curated:

    • 0pC9gNWfsT678F9on → 2 distillations, last_curated_at=0 (no curation)
    • 1ZByHEF6uFVlCAlwL → 6 distillations, last_curated_at=1780867535074 (curated)
    • 0BLMn3hmhuUFYLJXU → 4 distillations, last_curated_at=0
    • 1I6pVr6VpWPNqNsNY → 15 distillations, last_curated_at=1780867804538 (curated)

But there's no model info to correlate. Let me check the ...

Now I see interesting patterns. Let me check the gateway logs for model info, and look at the relationship between sessions with 0 distillations.

MiniMax-M3 · 2026-06-07 21:37:20 · ~500 tokens
result 
-rw-r--r-- 1 byk byk  203293 Apr 29 23:30 /home/byk/.local/share/lore/gradient.log
-rw-r--r-- 1 byk byk 1618252 Jun  7 21:37 /home/byk/.local/share/lore/lore.log
-rw-r--r-- 1 byk byk 5316932 Jun  7 13:31 /home/byk/.local/share/lore/lore.log.1
result 
sessions_with_0_distillations|185
sessions_with_>=1_distillation|752
sessions_with_0_curation|218
sessions_with_curation|719
result 
session_id         message_count  conversation_turns  last_curated_at  last_known_input  fingerprint       distillations
-----------------  -------------  ------------------  ---------------  ----------------  ----------------  -------------
0vm3F6uTIeczyo3eJ  2225           1                   0                569270            ca58c36ea7ac5257  0            
0qzmo5ghHecmtGYtn  1983           11                  0                805880            4bef1fbd49116444  0            
1BEpdx9UnVbx3p5UW  1849           1                   0                0                 90b1256b2bf77ea4  0            
1Zf1Ez4EEr630GBuf  1807           0                   0                0                 ca58c36ea7ac5257  0            
0QkU6BBwsqUP0mwLf  1325           0                   0                0                 ba87d60d20eb3ed6  0            
0D3zYADu3DxD10s8M  925            1                   0                714988            ca58c36ea7ac5257  0            
1WqUKeLe1Af8kTyYo  537          ...
result 
2026-06-07T21:36:01.487Z [INFO ] turn: session=0pC9gNWfsT678F9o messages=95 model=MiniMax-M3 stream=true new=false tier=1
2026-06-07T21:36:01.487Z [INFO ] max_tokens: 32000 → 8192 (client=opencode, ema=340, lastStop=tool_use)
2026-06-07T21:36:01.500Z [INFO ] distillation refresh: 2 rows (user msg 33cf8e2afe24011c)
2026-06-07T21:36:01.500Z [INFO ] gradient: session=0pC9gNWfsT678F9on layer=1 tokens=87683 (distilled=1537 raw=86146) usable=173232 tier=0 l0cap=333333
2026-06-07T21:36:01.501Z [INFO ] upstream: https://api.minimax.io/anthropic (provider=minimax-coding-plan, providerURL=https://api.minimax.io/anthropic, modelRoute=none, headerUpstream=yes, protocol=anthropic, auth=api-key:sk-cp-bE…)
2026-06-07T21:36:03.817Z [INFO ] cache-analytics: session=07Eew9hkBS4apf7H turn=4 hit=100% read=51496 create=0 input=0 prefixMatch=89.6% (113728/198029B) divergence="messages[4].content[2].text" reason="earlier message modified at position 4 (window shift or content ...
gateway · 2026-06-07 21:37:38
reasoning

The log file shows the model is consistently MiniMax-M3 and the provider is minimax-coding-plan for all sessions in the log. So in THIS installation, there's only one model/provider being used. The user's question about "across all model providers" is interesting because:

  1. The DB doesn't track model/provider at all
  2. The live log shows only one model (MiniMax-M3 via minimax-coding-plan) is being used right now

Let me check the gradient.log too, and also look at the historical data in the DB to see if there are any hints about what was used. Let me also look at all the upstreams ever seen and the historical data.

Looking at the log more carefully:

  • upstream: https://api.minimax.io/anthropic (provider=minimax-coding-plan, ..., protocol=anthropic, ...)
  • model=MiniMax-M3 for all sessions
  • tier=1 - meaning gradient layer 1

The fact that gradient: layer=0 (no distilled prefix used) is shown for many sessions and distillation refresh: 2 rows for some means distillation ...

The log shows the current model is consistently MiniMax-M3 via minimax-coding-plan (not Anthropic). Let me check the gradient.log, temporal_messages metadata, and historical evidence for any other models/providers.

MiniMax-M3 · 2026-06-07 21:37:38 · ~461 tokens
result 
2026-06-07T13:31:22.754Z [INFO ] upstream: https://api.anthropic.com (provider=anthropic, providerURL=https://api.anthropic.com, modelRoute=https://api.anthropic.com, headerUpstream=yes, protocol=anthropic, auth=api-key:sk-ant-a…)
2026-06-07T13:31:27.150Z [INFO ] turn: session=1ULRTqTWWI0BZ2Rf messages=225 model=claude-opus-4-6 stream=true new=false tier=1
2026-06-07T13:31:27.162Z [INFO ] upstream: https://api.anthropic.com (provider=anthropic, providerURL=https://api.anthropic.com, modelRoute=https://api.anthropic.com, headerUpstream=yes, protocol=anthropic, auth=api-key:sk-ant-a…)
2026-06-07T13:31:28.292Z [INFO ] turn: session=0zM7dgy3o7mvMjmc messages=21 model=claude-opus-4-6 stream=true new=false tier=1
2026-06-07T13:31:28.309Z [INFO ] upstream: https://api.anthropic.com (provider=anthropic, providerURL=https://api.anthropic.com, modelRoute=https://api.anthropic.com, headerUpstream=yes, protocol=anthropic, auth=api-key:sk-ant-a…)
2026-06-07T13:31:35.167Z [INFO ] turn: ...
result 
/home/byk/.local/share/lore/lore.log.1:model=claude-opus-4-6
/home/byk/.local/share/lore/lore.log.1:model=minimax
/home/byk/.local/share/lore/lore.log.1:model=minimaxai
/home/byk/.local/share/lore/lore.log.1:model=MiniMax-M3
/home/byk/.local/share/lore/lore.log.1:model=minimax-m3-free
/home/byk/.local/share/lore/lore.log.1:model=qwen
/home/byk/.local/share/lore/lore.log:model=claude-opus-4-6
/home/byk/.local/share/lore/lore.log:model=claude-sonnet-4-6
/home/byk/.local/share/lore/lore.log:model=deepseek-ai
/home/byk/.local/share/lore/lore.log:model=minimaxai
/home/byk/.local/share/lore/lore.log:model=MiniMax-M3
/home/byk/.local/share/lore/lore.log:model=minimax-m3-free
result 
/home/byk/.local/share/lore/lore.log.1:provider=anthropic
/home/byk/.local/share/lore/lore.log.1:provider=minimax-coding-plan
/home/byk/.local/share/lore/lore.log.1:provider=nvidia
/home/byk/.local/share/lore/lore.log.1:provider=opencode
/home/byk/.local/share/lore/lore.log.1:provider=openrouter
/home/byk/.local/share/lore/lore.log.1:providerURL=https://api.anthropic.com
/home/byk/.local/share/lore/lore.log.1:providerURL=https://api.minimax.io/anthropic
/home/byk/.local/share/lore/lore.log.1:providerURL=https://integrate.api.nvidia.com
/home/byk/.local/share/lore/lore.log.1:providerURL=https://opencode.ai/zen
/home/byk/.local/share/lore/lore.log.1:providerURL=https://openrouter.ai/api
/home/byk/.local/share/lore/lore.log:provider=anthropic
/home/byk/.local/share/lore/lore.log:provider=minimax-coding-plan
/home/byk/.local/share/lore/lore.log:provider=nvidia
/home/byk/.local/share/lore/lore.log:provider=opencode
/home/byk/.local/share/lore/lore.log:providerURL=https://api.anthropic.com
/...
result 
||129847
{"providerID":"anthropic","modelID":"unknown"}||55633
{"providerID":"anthropic","modelID":"claude-opus-4-6"}||3152
{"providerID":"anthropic","modelID":"claude-opus-4-7"}||473
{"providerID":"anthropic","modelID":"claude-opus-4-6","variant":"max"}||454
{"providerID":"anthropic","modelID":"claude-sonnet-4-6"}||340
{"providerID":"anthropic","modelID":"claude-opus-4-7","variant":"max"}||202
{"providerID":"anthropic","modelID":"claude-opus-4-7","variant":"low"}||13
{"providerID":"nvidia","modelID":"minimaxai/minimax-m2.7"}||5
{"providerID":"opencode","modelID":"nemotron-3-super-free"}||5
{"providerID":"anthropic","modelID":"claude-sonnet-4-6","variant":"max"}||4
{"providerID":"github-copilot","modelID":"gpt-5.4"}||4
{"providerID":"anthropic","modelID":"claude-opus-4-7","variant":"xhigh"}||3
{"providerID":"github-copilot","modelID":"claude-opus-4.6"}||3
{"providerID":"anthropic","modelID":"claude-haiku-4-5-20251001"}||1
{"providerID":"anthropic","modelID":"claude-opus-4-6","variant":...
result 
msg_c72f6e427001CTrSxz7AkqQJ6V|b496e2cd-5088-4eec-81ea-209206e25cde|ses_38d091c03ffeSvgclZ2H8tL122|[]|{"modelID":"claude-opus-4-6","providerID":"anthropic","mode":"nuum-curator"}
msg_c72f8553e001Y65v2QqmWopRJc|b496e2cd-5088-4eec-81ea-209206e25cde|ses_38d091c03ffeSvgclZ2H8tL122|[]|{"modelID":"claude-opus-4-6","providerID":"anthropic","mode":"nuum-curator"}
msg_c72f8edcb001K78g2Q3IIl3YZF|b496e2cd-5088-4eec-81ea-209206e25cde|ses_38d071255ffeAwmzqW8QBoLtWE|You are a memory distillation agent. Your job is to compress a conversation segment into structured output while preserving operational intelligence.

Produce a JSON object with exactly two fields:

"|{"agent":"nuum-distill","model":{"providerID":"anthropic","modelID":"claude-opus-4-6"}}
msg_c72f8eddb0011twycBSqeNQxhI|b496e2cd-5088-4eec-81ea-209206e25cde|ses_38d071255ffeAwmzqW8QBoLtWE|[tool:webfetch] DUTTY Digital 38khz Ir Receiver Ir Transmitter Sensor Module Kit for Arduino 3pcs: Amazon.co.uk: Business, Industry &amp; ...
gateway · 2026-06-07 21:38:26
reasoning

Excellent! Major findings:

  1. The temporal_messages table has providerID and modelID in metadata! This is the smoking gun. The metadata is JSON, and 129,847 rows have empty metadata, but 55,633 have providerID=anthropic, and there's data for:

    • anthropic (claude-opus-4-6, claude-opus-4-7, claude-sonnet-4-6, claude-haiku-4-5-20251001, etc.) - lots of variants
    • nvidia (minimaxai/minimax-m2.7) - only 5 messages
    • opencode (nemotron-3-super-free) - 5 messages
    • github-copilot (gpt-5.4, claude-opus-4.6, claude-sonnet-4.6) - 8 messages

  2. The gateway logs show multiple providers actively being used:

    • anthropic (api.anthropic.com) - claude-opus-4-6, claude-sonnet-4-6
    • minimax-coding-plan (api.minimax.io/anthropic) - MiniMax-M3, minimax-m3-free, minimax
    • nvidia (integrate.api.nvidia.com) - deepseek-ai/deepseek-v4-flash, minimaxai/minimax-m2.7
    • opencode (opencode.ai/zen) - qwen
    • openrouter (openrouter.ai/api) - seen in ...

Now I have the key insight: temporal_messages.metadata is a JSON blob containing providerID and modelID. This is the bridge that lets us correlate sessions → models. Let me run the real analysis joining by session_id.

MiniMax-M3 · 2026-06-07 21:38:26 · ~656 tokens
result 
provider        model                        sessions  msgs 
--------------  ---------------------------  --------  -----
anthropic       claude-opus-4-6              1748      92725
anthropic       claude-haiku-4-5-20251001    227       262  
anthropic       claude-opus-4-7              90        15699
anthropic       claude-opus-4-8              83        3527 
anthropic       claude-sonnet-4-6            70        5821 
anthropic       MiniMax-M3                   39        1439 
anthropic       claude-sonnet-4-5-20250929   34        34   
anthropic       claude-sonnet-4-20250514     7         39   
anthropic       claude-opus-4-20250514       6         6    
anthropic       gpt-5.5-2026-04-23           6         98   
anthropic       minimaxai/minimax-m2.7       4         237  
anthropic       deepseek-v4-flash            2         235  
anthropic       minimax/minimax-m3-20260531  2         6    
anthropic       qwen/qwen3.5-122b-a10b       1         1    
github-copilot  gpt-5.4 ...
result 
provider        model                        sessions_with_model  sessions_with_distillations  total_distillations  pct_distilled
--------------  ---------------------------  -------------------  ---------------------------  -------------------  -------------
anthropic       claude-opus-4-6              1748                 727                          4459                 41.6         
anthropic       claude-haiku-4-5-20251001    227                  0                            0                    0.0          
anthropic       claude-opus-4-7              90                   0                            0                    0.0          
anthropic       claude-opus-4-8              83                   59                           623                  71.1         
anthropic       claude-sonnet-4-6            70                   2                            7                    2.9          
anthropic       MiniMax-M3                   39                   19                      ...
result 
provider        model                        sessions  knowledge_entries  entries_per_session
--------------  ---------------------------  --------  -----------------  -------------------
anthropic       claude-opus-4-6              1748      72                 4.12               
anthropic       claude-haiku-4-5-20251001    227       0                  0.0                
anthropic       claude-opus-4-7              90        0                  0.0                
anthropic       claude-opus-4-8              83        4                  4.82               
anthropic       claude-sonnet-4-6            70        3                  4.29               
anthropic       MiniMax-M3                   39        9                  23.08              
anthropic       claude-sonnet-4-5-20250929   34        0                  0.0                
anthropic       claude-sonnet-4-20250514     7         0                  0.0                
anthropic       claude-opus-4-20250514       6         0    ...
result 
Error: in prepare, no such column: d.id
  DISTINCT sp.session_id), COUNT(DISTINCT CASE WHEN d.id IS NOT NULL AND d.creat
                                      error here ---^
gateway · 2026-06-07 21:38:58
reasoning

Hugely important findings already. Let me notice some things:

  1. Every single provider is "anthropic" in the metadata — but the model names are from all over the place (claude-opus-4-6, MiniMax-M3, gpt-5.5, deepseek-v4-flash, qwen/qwen3.5-122b-a10b, etc.). This is a quirk of how the data is captured: the providerID in metadata is the upstream provider (Anthropic's API server) but the model name is whatever the client requested. The user's gateway is acting as a proxy and the providerID is always anthropic because the OpenCode plugin routes through Anthropic's protocol.

Wait, that's strange. Let me look more carefully. The logs showed:

  • provider=anthropic, providerURL=https://api.anthropic.com for Claude models
  • provider=minimax-coding-plan, providerURL=https://api.minimax.io/anthropic for MiniMax
  • provider=nvidia, providerURL=https://integrate.api.nvidia.com for DeepSeek

But the metadata in temporal_messages shows providerID: anthropic for almost ...

Crucial finding: all rows show providerID=anthropic because the metadata likely includes worker/curator messages. Let me filter on mode and re-run, plus look at historical data and fix the broken query.

MiniMax-M3 · 2026-06-07 21:38:58 · ~743 tokens
result 
mode          provider        model                                            n    
------------  --------------  -----------------------------------------------  -----
                                                                               60304
build         anthropic       claude-opus-4-6                                  46357
gateway       anthropic       claude-opus-4-6                                  35425
build         anthropic       claude-opus-4-7                                  17314
plan          anthropic       claude-opus-4-6                                  13550
build         anthropic       claude-sonnet-4-6                                8055 
gateway       anthropic       claude-opus-4-8                                  3961 
gateway       anthropic       MiniMax-M3                                       1666 
plan          anthropic       claude-opus-4-7                                  1234 
gateway       anthropic       claude-haiku-4-5-20251001          ...
result 
(no output)
result 
scope         n_sessions  sessions_with_distill  knowledge_entries
------------  ----------  ---------------------  -----------------
All sessions  0           0                      0                
Last 7 days   0           0                      0
result 
    588 model=claude-opus-4-6
    190 model=MiniMax-M3
    179 model=minimax-m3-free
      5 model=qwen
      4 model=minimaxai
      1 model=minimax
gateway · 2026-06-07 21:39:56
reasoning

Interesting. So when I filter by mode IS NULL, I get 0 sessions. That means every single temporal_message that has a providerID also has a mode (build, plan, gateway, explore, nuum-distill, nuum-curator, compaction, general). This is OpenCode-specific mode names.

The "mode" here refers to the OpenCode agent mode, not the model. So:

  • build mode = primary coding mode (claude-opus-4-6 most common)
  • plan mode = planning mode
  • gateway mode = ... maybe a sub-agent name?
  • nuum-distill and nuum-curator = Lore's own workers

The fact that the providerID is always anthropic even for non-Claude models is interesting. Let me check the actual lore.log output for what provider= is shown.

From the log earlier:

  • upstream: https://api.anthropic.com (provider=anthropic, modelRoute=https://api.anthropic.com, ...) for Claude
  • upstream: https://api.minimax.io/anthropic (provider=minimax-coding-plan, ...) for MiniMax
  • `upstream: https://integrate.api.nvidia.com ...

Major finding: providerID is always anthropic in metadata because OpenCode labels all Anthropic-protocol endpoints the same way. The real discriminator is the model name. Let me regroup by model and check for provider URL in metadata.

MiniMax-M3 · 2026-06-07 21:39:56 · ~777 tokens
result 
url  baseurl  api  n     
---  -------  ---  ------
                   190169
result 
ba3a9e12b96d1ddf8d8b971cf75cb0d5|{"modelID":"MiniMax-M3","providerID":"anthropic","mode":"gateway","tools":["write"]}
4c0c0027d56d9e126f2d102d0c048a4a|{"modelID":"MiniMax-M3","providerID":"anthropic","mode":"gateway","tools":["write"]}
b27e362436d5694d17a50e2158d26ab9|{"modelID":"MiniMax-M3","providerID":"anthropic","mode":"gateway","tools":["read"]}
result 
provider_group                                          model                                            mode          sessions  msgs 
------------------------------------------------------  -----------------------------------------------  ------------  --------  -----
Alibaba (qwen)                                          qwen/qwen3.5-122b-a10b                           gateway       2         2    
Anthropic (claude-*)                                    claude-opus-4-6                                  gateway       1482      35425
Anthropic (claude-*)                                    claude-opus-4-6                                  plan          299       13550
Anthropic (claude-*)                                    claude-haiku-4-5-20251001                        gateway       266       343  
Anthropic (claude-*)                                    claude-opus-4-6                                  build         265       46357
Anthropic (claude-*)                                   ...
gateway · 2026-06-07 21:40:43
reasoning

Now I have a clear picture. Let me also check the nuum-distill and nuum-curator modes — these are Lore's own workers. They only ran on Anthropic (claude-opus-4-6, claude-sonnet-4-6). That's the key question — are the distillations/curation calls themselves being made on non-Anthropic models?

Let me also check the historical data (older than 7 days) since the user asked about "across all model providers". And let me check the most recent 7 days vs all-time.

Also: 60,304 rows have no mode. Those are likely older rows or non-metadata-bearing entries. Let me check those.

Now let me also look at the recent (last 7 days) data, and confirm that:

  1. The 0 sessions when filtering mode IS NULL suggests: every message with providerID has a mode. So 60,304 with no metadata at all.

Let me get the most critical insight: which providers are actually being used recently, and what mode (gateway vs build vs plan) they correspond to. ...

Now I have a complete picture. Let me re-run the analysis using model name as the provider discriminator (since providerID is always anthropic), and check the 60K rows with no mode/metadata.

MiniMax-M3 · 2026-06-07 21:40:43 · ~962 tokens
result 
Error: in prepare, ambiguous column name: session_id
    END AS provider_group,   mode,   COUNT(DISTINCT session_id) AS sessions,   C
                                      error here ---^
result 
model                                            sessions  distillations  sessions_with_distill  knowledge  knowledge_entries  pct_distilled
-----------------------------------------------  --------  -------------  ---------------------  ---------  -----------------  -------------
MiniMax-M3                                       49        845            29                     13         13                 59.2         
gpt-5.5-2026-04-23                               7         53             6                      0          0                  85.7         
minimaxai/minimax-m2.7                           6         235            3                      2          2                  50.0         
nvidia/nemotron-3-ultra-550b-a55b-20260604:free  4         318            4                      0          0                  100.0        
nvidia/nemotron-3-nano-omni-30b-a3b-reasoning    3         249            3                      0          0                  100.0        ...
result 
mode          p          m                  n  
------------  ---------  -----------------  ---
nuum-distill  anthropic  claude-opus-4-6    336
nuum-distill  anthropic  claude-sonnet-4-6  232
nuum-curator  anthropic  claude-opus-4-6    44
result 
||0|0
gateway · 2026-06-07 21:41:31
reasoning

EXCELLENT. Now I have the smoking gun findings:

  1. Non-Claude (non-Anthropic) sessions ARE being distilled and curated!
    • MiniMax-M3: 49 sessions, 29 distilled (59.2%), 13 knowledge entries
    • gpt-5.5-2026-04-23: 7 sessions, 6 distilled (85.7%), 0 knowledge (knowledge creation may be due to few turns)
    • minimaxai/minimax-m2.7: 6 sessions, 3 distilled (50%), 2 knowledge
    • nvidia/nemotron-3-ultra-550b-a55b-20260604:free: 4 sessions, 4 distilled (100%), 0 knowledge
    • nvidia/nemotron-3-nano-omni-30b-a3b-reasoning: 3 sessions, 3 distilled (100%), 0 knowledge
    • nemotron-3-super-free: 3 sessions, 0 distilled (0%) — small sessions, may be a real gap
    • minimax/minimax-m3-20260531: 3 sessions, 2 distilled (66.7%)
    • deepseek-v4-flash: 3 sessions, 3 distilled (100%), 2 knowledge
    • qwen/qwen3.5-122b-a10b: 2 sessions, 1 distilled (50%)
    • nvidia/nemotron-3-super-120b-a12b: 1 session, 1 distilled (100%), 2 knowledge
    • gpt-5.4: 1 session, 0 distilled (0%) — very ...

Now I have the key insight. Let me check what's in those 60K messages without mode/provider, then look at recent activity (last 7 days) for the most current state.

MiniMax-M3 · 2026-06-07 21:41:31 · ~1.3K tokens
result 
id                              role  substr(content, 1, 200)                                                                                                                                substr(metadata, 1, 300)                                                                 datetime(created_at,'unixepoch')
------------------------------  ----  -----------------------------------------------------------------------------------------------------------------------------------------------------  ---------------------------------------------------------------------------------------  --------------------------------
msg_c72f8edcb001K78g2Q3IIl3YZF  user  You are a memory distillation agent. Your job is to compress a conversation segment into structured output while preserving operational intelligence. ...
result 
provider                                                sessions  sessions_with_0_distill  sessions_with_distill  sessions_curated  pct_distilled
------------------------------------------------------  --------  -----------------------  ---------------------  ----------------  -------------
MiniMax                                                 51        19                       34                     23                66.7         
OpenAI                                                  7         1                        6                      5                 85.7         
Other: nvidia/nemotron-3-ultra-550b-a55b-20260604:free  4         0                        4                      4                 100.0        
Other: nvidia/nemotron-3-nano-omni-30b-a3b-reasoning    3         0                        3                      3                 100.0        
DeepSeek                                                3         0                        4                      3         ...
result 
model                        sessions  zero_distill  has_distill  curated
---------------------------  --------  ------------  -----------  -------
MiniMax-M3                   38        19            19           10     
gpt-5.5-2026-04-23           6         1             5            5      
minimaxai/minimax-m2.7       3         0             3            3      
deepseek-v4-flash            2         0             2            1      
qwen/qwen3.5-122b-a10b       1         1             0            0      
minimax/minimax-m3-20260531  1         0             1            0
result 
provider       knowledge_entries
-------------  -----------------
Other/Unknown  91
gateway · 2026-06-07 21:41:57
reasoning

Critical: 60K messages with no mode/model — they are the older worker messages from the legacy schema. They use {"agent":"nuum-distill","model":{"providerID":"anthropic","modelID":"claude-opus-4-6"}} format. So all 60K are still on Anthropic.

The "Other/Unknown" knowledge entries are the older ones that can't be classified. Let me check by what they have.

I now have everything I need. Let me compile the final report.

Key findings:

  1. NO sessions table — schema has only session_state (no model/provider column)
  2. NO curator_runs table — doesn't exist
  3. Model/provider IS captured in temporal_messages.metadata as JSON providerID and modelID
  4. providerID is always anthropic (OpenCode uses this label for all Anthropic-protocol-compatible endpoints — misleading!)
  5. ...

I have all the data I need. Let me do one final check on the older 60K messages to confirm they're all Anthropic worker messages, then write the report.

MiniMax-M3 · 2026-06-07 21:41:57 · ~922 tokens
result 
fmt                  nested_provider  nested_model       agent         n     
-------------------  ---------------  -----------------  ------------  ------
flat-format                                                            129874
model-nested-format  anthropic        unknown            gateway       55664 
model-nested-format  anthropic        claude-opus-4-6    build         2409  
model-nested-format  anthropic        claude-opus-4-6    plan          1144  
model-nested-format  anthropic        claude-opus-4-7    build         543   
model-nested-format  anthropic        claude-sonnet-4-6  build         322   
model-nested-format  anthropic        claude-opus-4-7    plan          148   
model-nested-format  anthropic        claude-opus-4-6    nuum-distill  50    
model-nested-format  anthropic        claude-sonnet-4-6  nuum-distill  15    
model-nested-format  anthropic        claude-sonnet-4-6  plan          6
result 
worker_model               worker_provider  agent         n    
-------------------------  ---------------  ------------  -----
unknown                    anthropic        gateway       55664
claude-opus-4-6            anthropic        build         2409 
claude-opus-4-6            anthropic        plan          1144 
claude-opus-4-7            anthropic        build         543  
claude-sonnet-4-6          anthropic        build         322  
claude-opus-4-7            anthropic        plan          148  
claude-opus-4-6            anthropic        nuum-distill  50   
claude-sonnet-4-6          anthropic        nuum-distill  15   
claude-sonnet-4-6          anthropic        plan          6    
minimaxai/minimax-m2.7     nvidia           build         4    
nemotron-3-super-free      opencode         build         4    
claude-opus-4-6            anthropic        explore       2    
claude-opus-4-6            anthropic        general       2    
claude-opus-4.6            ...
result 
total_temporal_messages|190202
messages_with_any_metadata|190202
messages_with_mode_field|129875
messages_with_model_nested|60327
messages_with_model_flat|129875
messages_with_nuum_agent|65
gateway · 2026-06-07 21:43:21
reasoning

Now I have a complete picture. Let me also note: in the nested format, there's anthropic + unknown + gateway with 55,664 messages. These are likely older messages from a previous OpenCode version. But notice that in the flat format (more recent), the structure includes mode (gateway/build/plan/nuum-distill/nuum-curator) and modelID for both user model AND worker model.

In the nested format, 65 nuum-* messages (50 + 15) — all on Anthropic.

Importantly, I missed something in the model-nested-format table. It showed:

  • anthropic + unknown + gateway: 55,664 — this is gateway mode with unknown model. This is a legacy thing.
  • nvidia + minimaxai/minimax-m2.7 + build: 4
  • opencode + nemotron-3-super-free + build: 4
  • github-copilot + claude-opus-4.6 + plan: 2
  • github-copilot + gpt-5.4 + build: 2
  • github-copilot + gpt-5.4 + plan: 2
  • github-copilot + claude-sonnet-4.6 + plan: 1

So the older schema also has the same pattern: ALL nuum-distill and nuum-curator ...

I have a complete picture now. Let me write up the final report.

Investigation Report: Lore Distillation & Curation Across Model Providers

TL;DR (Conclusion)

The user's premise is wrong on two counts, but the question is still answerable with interesting findings:

  1. There is no sessions table and no curator_runs table in the schema. The closest equivalents are session_state (no model/provider columns) and last_curated_at in session_state plus knowledge.created_at. Model/provider information is captured in temporal_messages.metadata as a JSON blob.

  2. Coverage-wise, non-Anthropic sessions ARE being distilled and curated. MiniMax, OpenAI (gpt-5.5), DeepSeek, NVIDIA (nemotron), and Alibaba (qwen) sessions all show distillation rows and knowledge entries in the DB.

  3. HOWEVER, the distillation/curation WORKER AGENTS themselves only ever run on Anthropic (claude-opus-4-6 and claude-sonnet-4-6). Every nuum-distill and nuum-curator worker call in the metadata is providerID=anthropic. This means: if Anthropic were unreachable, no distillation or curation could happen, regardless of which provider the user is actually using.

Schema Reality Check

The schema (packages/core/src/db.ts) does not have a sessions table or a curator_runs table. Actual relevant tables:

| Table | Has model/provider info? | Notes | |---|---|---| | session_state | No columns for model/provider | Has last_curated_at, message_count, turns_since_curation | | distillations | No | Has session_id, generation, created_at | | knowledge | No | Has source_session, created_at | | temporal_messages | Yes — in metadata JSON | providerID, modelID, mode, agent |

Critical gotcha: temporal_messages.metadata.providerID is always anthropic, even for MiniMax/DeepSeek/Qwen messages. ...

MiniMax-M3 · 2026-06-07 21:43:21 · ~4.3K tokens