arborist/aborist/qa/runner.py
russell@unturf.com 57cf1b183b
add Q&A layer: v9.8 providence_cache writes with Merkle-bound proofs
aborist/qa/ implements the cache-first answer flow from the providence
whitepaper, scaled up to v9.8's full 8-dim admissibility invariant.

cache_key = SHA-256 of:
  source_root | question_hash | model_profile_hash | conversation_hash
  | governance_policy_hash | schema_version | canonicalization_version
  | chunking_version

Any drift in any dimension yields a distinct cache_key — prior records
cannot serve. Falsification states (failed/stale/quarantined) gate
every cache hit.

- qa/keys.py        — pure hash functions, deterministic & testable
- qa/client.py      — ChatClient Protocol + StubClient + OpenAI-compatible
                      HTTP client (vllm/llama.cpp/uncloseai compatible)
- qa/runner.py      — ask(): lookup -> hit (no LLM call, hit_count++)
                      OR miss (call client, write record, audit event,
                      proof binds answer to source root)
- cli.py            — `aborist ask` and `aborist providence` subcommands
- pyproject.toml    — httpx promoted from extras to core (used by both
                      html and qa); selectolax stays in [html] extras

Smoke (StubClient, no network): cache miss writes record with chunk_0
Merkle proof reconstructing source_root; cache hit returns same record
without calling client; 1085 audit events chained 0 breaks across
ingest/derive/evict/rehydrate/providence_write.
2026-04-27 08:01:23 -04:00

196 lines
5.7 KiB
Python

"""Q&A runner: cache-first lookup -> inference fallback -> provable record.
Implements the v9.8 admissibility invariant:
No record reused unless all 8 cache_key dimensions match AND state
is 'live' (not failed/stale/quarantined).
Cache hit -> STRICT-mode answer with stored Merkle proof.
Cache miss -> call ChatClient, store record, audit event.
"""
from __future__ import annotations
import json
import sqlite3
import time
from aborist import (
CANONICALIZATION_VERSION,
SCHEMA_VERSION,
)
from aborist.merkle import MerkleTree, proof_to_dict
from aborist.qa.client import ChatClient
from aborist.qa.keys import (
cache_key,
conversation_hash,
governance_policy_hash,
model_profile_hash,
question_hash,
)
from aborist.store import append_audit, transaction
DEFAULT_POLICY = {
"system_prompt": (
"Answer the user's question based ONLY on the document below. "
"If the answer is not in the document, say 'I don't know.' "
"Do not speculate. Cite the relevant sentence(s)."
),
"temperature": 0.1,
"top_p": 1.0,
"max_tokens": 512,
}
def ask(
conn: sqlite3.Connection,
*,
document_root: str,
question: str,
client: ChatClient,
model_id: str,
revision: str = "",
quantization: str = "",
policy: dict | None = None,
chain: str = "private",
) -> dict:
"""Look up cached answer or run inference. Returns a result dict."""
policy = policy or DEFAULT_POLICY
doc = conn.execute(
"SELECT document_uri, chunking_version FROM documents "
"WHERE document_root = ?",
(document_root,),
).fetchone()
if doc is None:
return {"status": "unknown_document"}
chunk_rows = conn.execute(
"SELECT idx, leaf_hash, content FROM chunks "
"WHERE document_root = ? ORDER BY idx ASC",
(document_root,),
).fetchall()
if not chunk_rows:
return {"status": "unknown_document"}
if any(r["content"] is None for r in chunk_rows):
return {"status": "source_cold", "msg": "rehydrate before asking"}
document_text = "\n\n".join(r["content"] for r in chunk_rows)
messages = [
{"role": "system", "content": policy["system_prompt"]},
{
"role": "user",
"content": (
f"Document:\n\n{document_text}\n\n---\n\n"
f"Question: {question}"
),
},
]
qhash = question_hash(question)
mhash = model_profile_hash(model_id, revision, quantization)
chash = conversation_hash(messages)
ghash = governance_policy_hash(policy)
ckey = cache_key(
document_root,
qhash,
mhash,
chash,
ghash,
SCHEMA_VERSION,
CANONICALIZATION_VERSION,
doc["chunking_version"],
)
cached = conn.execute(
"SELECT * FROM providence_cache "
"WHERE cache_key = ? AND falsification_state = 'live'",
(ckey,),
).fetchone()
if cached is not None:
with transaction(conn):
now = int(time.time())
conn.execute(
"UPDATE providence_cache "
"SET hit_count = hit_count + 1, last_hit_at = ? "
"WHERE cache_key = ?",
(now, ckey),
)
return {
"status": "cache_hit",
"audit_mode": "STRICT",
"cache_key": ckey,
"source_root": document_root,
"answer_text": cached["answer_text"],
"merkle_proof": json.loads(cached["merkle_proof"]),
}
answer_text = client.chat_completion(
messages,
model=model_id,
temperature=policy["temperature"],
max_tokens=policy["max_tokens"],
top_p=policy.get("top_p", 1.0),
)
leaves = [bytes.fromhex(r["leaf_hash"]) for r in chunk_rows]
tree = MerkleTree.build(leaves)
proof_obj = {
"document_root": document_root,
"chunk_0_proof": proof_to_dict(tree.proof(0)),
}
proof_blob = json.dumps(proof_obj, separators=(",", ":"))
now = int(time.time())
with transaction(conn):
event_hash = append_audit(
conn,
event_type="providence_write",
subject_root=ckey,
body={
"source_root": document_root,
"model_id": model_id,
"revision": revision,
"quantization": quantization,
"chunks_in_context": len(chunk_rows),
"answer_chars": len(answer_text),
},
ts=now,
)
conn.execute(
"INSERT INTO providence_cache "
"(cache_key, source_root, document_uri, question_hash, question_text, "
" answer_text, merkle_proof, model_profile_hash, conversation_hash, "
" governance_policy_hash, schema_version, canonicalization_version, "
" chunking_version, falsification_state, chain, audit_event_hash, "
" created_at, hit_count) "
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'live', ?, ?, ?, 0)",
(
ckey,
document_root,
doc["document_uri"],
qhash,
question,
answer_text,
proof_blob,
mhash,
chash,
ghash,
SCHEMA_VERSION,
CANONICALIZATION_VERSION,
doc["chunking_version"],
chain,
event_hash,
now,
),
)
return {
"status": "cache_miss_then_written",
"audit_mode": "STRICT",
"cache_key": ckey,
"source_root": document_root,
"answer_text": answer_text,
"merkle_proof": proof_obj,
}