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+train.jsonl filter=lfs diff=lfs merge=lfs -text
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README.md

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+# WithIn Us AI — MemoryGenesis (God Level) 250K
+
+Developer: **WithIn Us AI**
+
+MemoryGenesis is a 250,000-example dataset designed to train LLMs to behave like **memory-first agents**:
+- capture new information at runtime
+- store durable and ephemeral memory safely (TTL)
+- retrieve and cite relevant memories (RAG-style behavior)
+- update, correct, merge, deduplicate, and compact memories
+- resolve conflicts via provenance/recency/confidence
+- enforce privacy (no secrets stored), redaction, and safe policies
+- approximate "instant knowledge injection" **without weight updates** by using external memory tools
+
+> Important: This dataset trains **runtime memory behaviors**. It does not perform real-time weight updates or replace model fine-tuning compute; instead it teaches a model to use external memory so new facts can be injected immediately.
+
+## Files
+- `train.jsonl` — 245,000 examples
+- `valid.jsonl` — 5,000 examples
+- `sample_200.jsonl` — 200 examples for inspection
+
+## Record schema (JSONL)
+Each line includes both instruct and chat formats:
+
+- `prompt_instruct` / `response_instruct` (instruction SFT)
+- `messages` (chat SFT: system/user/assistant)
+- `task_type`: memory_write, recall, update, merge/dedup, compaction, TTL, privacy, schema, indexing, eval, Q&A
+- `metadata.runtime_memory_only = true` and `metadata.no_weight_updates = true`
+
+## Tool protocol (in-text)
+Responses may include structured tool calls inside code blocks:
+
+- `memory.write` (key/value/tags/confidence/ttl_days)
+- `memory.search` (query/k/tags)
+- `memory.update` / `memory.delete`
+- `memory.compact`
+
+These are represented as JSON under `TOOL_CALL` or `TOOL_CALLS`.
+
+## Safety constraints
+- Never store secrets (API keys, passwords, private keys).
+- Store only safe derived information.
+- Ask user to confirm when evidence is missing or conflicting.
+
+## Suggested fine-tuning usage
+### Instruct SFT
+Map:
+- input: `prompt_instruct`
+- target: `response_instruct`
+
+### Chat SFT
+Map:
+- messages: `messages`
+
+## Evaluation suggestions
+Measure:
+- precision@k for retrieval
+- staleness/conflict rate
+- user correction rate
+- privacy redaction compliance
+

train.jsonl

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valid.jsonl

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