From b427e38576eacd709e536cf24d0f65c0ba1a56f0 Mon Sep 17 00:00:00 2001
From: Vedantsahai18 <Vedantsahai18@users.noreply.github.com>
Date: Fri, 20 Dec 2024 01:26:00 +0000
Subject: [PATCH] refactor: Lint agents-api (CI)

---
 agents-api/agents_api/queries/docs/delete_doc.py   |  1 +
 agents-api/agents_api/queries/docs/get_doc.py      |  3 ++-
 agents-api/agents_api/queries/docs/list_docs.py    |  1 +
 .../queries/docs/search_docs_by_embedding.py       |  5 +++--
 .../agents_api/queries/docs/search_docs_by_text.py |  2 +-
 .../agents_api/queries/docs/search_docs_hybrid.py  | 14 ++++++++++----
 6 files changed, 18 insertions(+), 8 deletions(-)

diff --git a/agents-api/agents_api/queries/docs/delete_doc.py b/agents-api/agents_api/queries/docs/delete_doc.py
index d1e02faf1..9d2075600 100644
--- a/agents-api/agents_api/queries/docs/delete_doc.py
+++ b/agents-api/agents_api/queries/docs/delete_doc.py
@@ -1,6 +1,7 @@
 """
 Timescale-based deletion of a doc record.
 """
+
 from typing import Literal
 from uuid import UUID
 
diff --git a/agents-api/agents_api/queries/docs/get_doc.py b/agents-api/agents_api/queries/docs/get_doc.py
index a0345f5e3..35d692c84 100644
--- a/agents-api/agents_api/queries/docs/get_doc.py
+++ b/agents-api/agents_api/queries/docs/get_doc.py
@@ -1,6 +1,7 @@
 """
 Timescale-based retrieval of a single doc record.
 """
+
 from typing import Literal
 from uuid import UUID
 
@@ -41,7 +42,7 @@ async def get_doc(
     developer_id: UUID,
     doc_id: UUID,
     owner_type: Literal["user", "agent", "org"] | None = None,
-    owner_id: UUID | None = None
+    owner_id: UUID | None = None,
 ) -> tuple[str, list]:
     """
     Fetch a single doc, optionally constrained to a given owner.
diff --git a/agents-api/agents_api/queries/docs/list_docs.py b/agents-api/agents_api/queries/docs/list_docs.py
index b145a1cbc..678c1a5e6 100644
--- a/agents-api/agents_api/queries/docs/list_docs.py
+++ b/agents-api/agents_api/queries/docs/list_docs.py
@@ -1,6 +1,7 @@
 """
 Timescale-based listing of docs with optional owner filter and pagination.
 """
+
 from typing import Literal
 from uuid import UUID
 
diff --git a/agents-api/agents_api/queries/docs/search_docs_by_embedding.py b/agents-api/agents_api/queries/docs/search_docs_by_embedding.py
index c62188b61..af89cc1b8 100644
--- a/agents-api/agents_api/queries/docs/search_docs_by_embedding.py
+++ b/agents-api/agents_api/queries/docs/search_docs_by_embedding.py
@@ -2,10 +2,10 @@
 Timescale-based doc embedding search using the `embedding` column.
 """
 
-import asyncpg
-from typing import Literal, List
+from typing import List, Literal
 from uuid import UUID
 
+import asyncpg
 from beartype import beartype
 from fastapi import HTTPException
 from sqlglot import parse_one
@@ -32,6 +32,7 @@
 LIMIT $2;
 """).sql(pretty=True)
 
+
 @wrap_in_class(
     Doc,
     one=False,
diff --git a/agents-api/agents_api/queries/docs/search_docs_by_text.py b/agents-api/agents_api/queries/docs/search_docs_by_text.py
index c9a5a93e2..eed74e54b 100644
--- a/agents-api/agents_api/queries/docs/search_docs_by_text.py
+++ b/agents-api/agents_api/queries/docs/search_docs_by_text.py
@@ -2,10 +2,10 @@
 Timescale-based doc text search using the `search_tsv` column.
 """
 
-import asyncpg
 from typing import Literal
 from uuid import UUID
 
+import asyncpg
 from beartype import beartype
 from fastapi import HTTPException
 from sqlglot import parse_one
diff --git a/agents-api/agents_api/queries/docs/search_docs_hybrid.py b/agents-api/agents_api/queries/docs/search_docs_hybrid.py
index 9e8d84dc7..ae107419d 100644
--- a/agents-api/agents_api/queries/docs/search_docs_hybrid.py
+++ b/agents-api/agents_api/queries/docs/search_docs_hybrid.py
@@ -3,7 +3,7 @@
 via a simple distribution-based score fusion or direct weighting in Python.
 """
 
-from typing import Literal, List
+from typing import List, Literal
 from uuid import UUID
 
 from beartype import beartype
@@ -11,8 +11,9 @@
 
 from ...autogen.openapi_model import Doc
 from ..utils import run_concurrently
-from .search_docs_by_text import search_docs_by_text
 from .search_docs_by_embedding import search_docs_by_embedding
+from .search_docs_by_text import search_docs_by_text
+
 
 def dbsf_normalize(scores: List[float]) -> List[float]:
     """
@@ -20,19 +21,23 @@ def dbsf_normalize(scores: List[float]) -> List[float]:
     from (mean - 3*stddev) to (mean + 3*stddev) and scale to 0..1
     """
     import statistics
+
     if len(scores) < 2:
         return scores
     m = statistics.mean(scores)
     sd = statistics.pstdev(scores)  # population std
     if sd == 0:
         return scores
-    upper = m + 3*sd
-    lower = m - 3*sd
+    upper = m + 3 * sd
+    lower = m - 3 * sd
+
     def clamp_scale(v):
         c = min(upper, max(lower, v))
         return (c - lower) / (upper - lower)
+
     return [clamp_scale(s) for s in scores]
 
+
 @beartype
 def fuse_results(
     text_docs: List[Doc], embedding_docs: List[Doc], alpha: float
@@ -151,6 +156,7 @@ async def search_docs_hybrid(
     # text_results, embed_results = await run_concurrently([task1, task2])
     # Otherwise just do them in parallel with e.g. asyncio.gather:
     from asyncio import gather
+
     text_results, embed_results = await gather(*tasks)
 
     # fuse them