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5 Commits

Author SHA1 Message Date
Ryan Chen db977270a3 Improve Simba system prompt for more helpful responses
Shift focus from cat persona to genuine helpfulness. Keep light
cat flavor but prioritize thorough, detailed answers over the
assertive cat act.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-24 08:58:29 -04:00
ryan bac773ae4b Merge pull request 'Enable async_mode on PGVector for async method support' (#30) from refactor/chromadb-to-pgvector into main
Reviewed-on: #30
2026-04-24 08:53:34 -04:00
Ryan Chen 564a9b68a5 Enable async_mode on PGVector for async method support
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-24 08:53:21 -04:00
ryan 7742673cc0 Merge pull request 'Handle missing pgvector tables on first run' (#29) from refactor/chromadb-to-pgvector into main
Reviewed-on: #29
2026-04-24 08:49:38 -04:00
Ryan Chen c157c37cde Handle missing pgvector tables on first run
_get_collection_id now catches the UndefinedTable error that occurs
before the first index operation creates the langchain tables.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-24 08:49:00 -04:00
2 changed files with 13 additions and 8 deletions
+1 -1
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@@ -1,4 +1,4 @@
SIMBA_SYSTEM_PROMPT = """You are a helpful cat assistant named Simba that understands veterinary terms. When there are questions to you specifically, they are referring to Simba the cat. Answer the user in as if you were a cat named Simba. Don't act too catlike. Be assertive.
SIMBA_SYSTEM_PROMPT = """You are Simba, Ryan's helpful personal assistant. You're named after his orange cat. You have a warm, friendly personality with a light cat-themed touch, but your priority is always being genuinely useful — give thorough, detailed answers and think things through carefully. When asked about Simba the cat, you speak as him in first person. For everything else, you're just a great assistant who happens to have a cat's name.
SIMBA FACTS (as of January 2026):
- Name: Simba
+5
View File
@@ -38,6 +38,7 @@ def _get_vector_store() -> PGVector:
connection=_pgvector_url,
use_jsonb=True,
create_extension=False, # created by docker init script
async_mode=True,
)
return _vector_store
@@ -59,6 +60,7 @@ text_splitter = RecursiveCharacterTextSplitter(
def _get_collection_id():
"""Get the UUID of our collection from the langchain_pg_collection table."""
engine = _get_engine()
try:
with engine.connect() as conn:
result = conn.execute(
text("SELECT uuid FROM langchain_pg_collection WHERE name = :name"),
@@ -66,6 +68,9 @@ def _get_collection_id():
)
row = result.fetchone()
return row[0] if row else None
except Exception:
# Table doesn't exist yet (first run before any indexing)
return None
def date_to_epoch(date_str: str) -> float: