emilandClaude Opus 4.7
ee8a9fc5bc
Two bugs were blocking memba's main promise (load .memb in a fresh process → model continues with full recalled context): 1. llama_state_set_data() restores the C-level KV-cache + SSM hidden state, but llama-cpp-python's Python wrapper still reports n_tokens=0. The next eval() then decodes new tokens at offset 0 and overwrites the loaded state. Fix: extend MEMB format with an optional 12-byte trailer appended after the CRC32. It carries the wrapper's n_tokens. The C library reads up to CRC and ignores anything past it, so files stay backward-compatible with libmemba; only the Python loader uses it. 2. Llama.__call__ / create_chat_completion / generate all re-tokenise the prompt on every call and clear the KV-cache when the new tokens don't prefix-match input_ids. That destroys any state we just loaded. Fix: rewrite Session.chat() to use raw tokenize → eval → sample. eval() appends tokens to the live state without resetting, and we handle stop-token detection ourselves. Verified end-to-end on Nemotron-3-Nano-4B (hybrid 21x Mamba-2 + 4x attention) — see experiments/README.md for the full findings log. diag_session_nemotron.py, mood_batch_poc.py, mood_stream_poc.py and recall_poc.py now all pass their cross-process tests; Falcon-Mamba still fails because the trained model itself can't do cross-turn recall — that was the original misdiagnosis. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
"""Same hamster test, but through the new Session.chat() (which uses eval+sample)."""
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import sys, argparse
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "python"))
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from memba import Session
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MODEL = "/home/emil/Desktop/Coding/AI/Memba/NVIDIA-Nemotron3-Nano-4B-Q4_K_M.gguf"
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STATE_DIR = "/tmp/diag_session_nemotron"
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SESSION = "hamster"
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def build():
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s = Session(model_path=MODEL, session_id=SESSION, state_dir=STATE_DIR,
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n_gpu_layers=-1, n_ctx=4096, chat_format="chatml")
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# Wipe any previous state file so it's a real fresh run
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p = Path(STATE_DIR) / f"{SESSION}.memb"
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if p.exists(): p.unlink()
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print(f"[build] ack: {s.chat('My pet hamster is named Bartholomew. He is 4 years old. Reply noted.', max_tokens=40)!r}")
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print(f"[build] in-process query: {s.chat('What is the name of my pet?', max_tokens=80)!r}")
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s.save()
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print(f"[build] saved")
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def query():
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s = Session(model_path=MODEL, session_id=SESSION, state_dir=STATE_DIR,
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n_gpu_layers=-1, n_ctx=4096, chat_format="chatml")
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print(f"[query] loaded state, n_tokens={s._llama.n_tokens}")
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print(f"[query] CROSS-PROCESS query: {s.chat('What is the name of my pet?', max_tokens=80)!r}")
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if __name__ == "__main__":
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{"build": build, "query": query}[sys.argv[1]]()
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