Move mypy config into pyproject.toml. Ignore 2 remaining mypy issues

.mypy.ini

@@ -1,13 +0,0 @@
-[mypy]
-strict_optional = False
-ignore_missing_imports = True
-install_types = True
-non_interactive = True
-show_error_codes = True
-exclude = (?x)(
-    src/khoj/interface/desktop/main_window.py
-    | src/khoj/interface/desktop/file_browser.py
-    | src/khoj/interface/desktop/system_tray.py
-    | build/*
-    | tests/*
-  )

pyproject.toml

@@ -73,3 +73,18 @@ include = ["src/khoj"]
 
 [tool.hatch.build.targets.wheel]
 packages = ["src/khoj"]
+
+[tool.mypy]
+files = "src/khoj"
+pretty = true
+strict_optional = false
+ignore_missing_imports = true
+install_types = true
+non_interactive = true
+show_error_codes = true
+warn_unused_ignores = true
+exclude = [
+    "src/khoj/interface/desktop/main_window.py",
+    "src/khoj/interface/desktop/file_browser.py",
+    "src/khoj/interface/desktop/system_tray.py",
+]

src/khoj/search_type/text_search.py

@@ -216,7 +216,7 @@ def deduplicate_results(entries: List[Entry], hits: List[dict]) -> List[dict]:
     with timer("Deduplication Time", logger, state.device):
         seen, original_hits_count = set(), len(hits)
         hits = [hit for hit in hits
-                if entries[hit['corpus_id']].raw not in seen and not seen.add(entries[hit['corpus_id']].raw)]
+                if entries[hit['corpus_id']].raw not in seen and not seen.add(entries[hit['corpus_id']].raw)]  # type: ignore[func-returns-value]
         duplicate_hits = original_hits_count - len(hits)
 
     logger.debug(f"Removed {duplicate_hits} duplicates")

src/khoj/utils/state.py

@@ -27,7 +27,7 @@ search_index_lock = threading.Lock()
 if torch.cuda.is_available():
     # Use CUDA GPU
     device = torch.device("cuda:0")
-elif version.parse(torch.__version__) >= version.parse("1.13.0.dev") and torch.backends.mps.is_available():
+elif version.parse(torch.__version__) >= version.parse("1.13.0.dev") and torch.backends.mps.is_available():  # type: ignore[attr-defined]
     # Use Apple M1 Metal Acceleration
     device = torch.device("mps")
 else: