[CHORE] Disallow invalid fields in pydantic schema (#5838)

## Description of changes

_Summarize the changes made by this PR._

- Improvements & Bug fixes
  - Fixes #5825
  - Disallows invalid fields in schema types
- New functionality
  - ...

## Test plan
added tests to ensure incorrect keys are caught
_How are these changes tested?_

- [ ] Tests pass locally with `pytest` for python, `yarn test` for js,
`cargo test` for rust

## Migration plan

_Are there any migrations, or any forwards/backwards compatibility
changes needed in order to make sure this change deploys reliably?_

## Observability plan

_What is the plan to instrument and monitor this change?_

## Documentation Changes

_Are all docstrings for user-facing APIs updated if required? Do we need
to make documentation changes in the [docs
section](https://github.com/chroma-core/chroma/tree/main/docs/docs.trychroma.com)?_

Author: jairad26

chromadb/api/types.py

@@ -12,6 +12,7 @@
     get_args,
     TYPE_CHECKING,
     Final,
+    Type,
 )
 from copy import deepcopy
 from typing_extensions import TypeAlias
@@ -20,7 +21,8 @@
 import numpy as np
 import warnings
 from typing_extensions import TypedDict, Protocol, runtime_checkable
-from pydantic import BaseModel, field_validator
+from pydantic import BaseModel, field_validator, model_validator
+from pydantic_core import PydanticCustomError
 
 import chromadb.errors as errors
 from chromadb.base_types import (
@@ -1493,15 +1495,57 @@ def validate_sparse_embedding_function(
 
 
 # Index Configuration Types for Collection Schema
+def _create_extra_fields_validator(valid_fields: list[str]) -> Any:
+    """Create a model validator that provides helpful error messages for invalid fields."""
+
+    @model_validator(mode="before")
+    def validate_extra_fields(cls: Type[BaseModel], data: Any) -> Any:
+        if isinstance(data, dict):
+            invalid_fields = [k for k in data.keys() if k not in valid_fields]
+            if invalid_fields:
+                invalid_fields_str = ", ".join(f"'{f}'" for f in invalid_fields)
+                class_name = cls.__name__
+                # Create a clear, actionable error message
+                if len(invalid_fields) == 1:
+                    msg = (
+                        f"'{invalid_fields[0]}' is not a valid field for {class_name}. "
+                    )
+                else:
+                    msg = f"Invalid fields for {class_name}: {invalid_fields_str}. "
+
+                raise PydanticCustomError(
+                    "invalid_field",
+                    msg,
+                    {"invalid_fields": invalid_fields},
+                )
+        return data
+
+    return validate_extra_fields
+
+
 class FtsIndexConfig(BaseModel):
     """Configuration for Full-Text Search index. No parameters required."""
 
+    model_config = {"extra": "forbid"}
+
     pass
 
 
 class HnswIndexConfig(BaseModel):
     """Configuration for HNSW vector index."""
 
+    _validate_extra_fields = _create_extra_fields_validator(
+        [
+            "ef_construction",
+            "max_neighbors",
+            "ef_search",
+            "num_threads",
+            "batch_size",
+            "sync_threshold",
+            "resize_factor",
+        ]
+    )
+
     ef_construction: Optional[int] = None
     max_neighbors: Optional[int] = None
     ef_search: Optional[int] = None
@@ -1514,6 +1558,27 @@ class HnswIndexConfig(BaseModel):
 class SpannIndexConfig(BaseModel):
     """Configuration for SPANN vector index."""
 
+    _validate_extra_fields = _create_extra_fields_validator(
+        [
+            "search_nprobe",
+            "search_rng_factor",
+            "search_rng_epsilon",
+            "nreplica_count",
+            "write_nprobe",
+            "write_rng_factor",
+            "write_rng_epsilon",
+            "split_threshold",
+            "num_samples_kmeans",
+            "initial_lambda",
+            "reassign_neighbor_count",
+            "merge_threshold",
+            "num_centers_to_merge_to",
+            "ef_construction",
+            "ef_search",
+            "max_neighbors",
+        ]
+    )
+
     search_nprobe: Optional[int] = None
     write_nprobe: Optional[int] = None
     ef_construction: Optional[int] = None
@@ -1527,7 +1592,8 @@ class SpannIndexConfig(BaseModel):
 class VectorIndexConfig(BaseModel):
     """Configuration for vector index with space, embedding function, and algorithm config."""
 
-    model_config = {"arbitrary_types_allowed": True}
+    model_config = {"arbitrary_types_allowed": True, "extra": "forbid"}
+
     space: Optional[Space] = None
     embedding_function: Optional[Any] = DefaultEmbeddingFunction()
     source_key: Optional[
@@ -1577,7 +1643,8 @@ def validate_embedding_function_field(cls, v: Any) -> Any:
 class SparseVectorIndexConfig(BaseModel):
     """Configuration for sparse vector index."""
 
-    model_config = {"arbitrary_types_allowed": True}
+    model_config = {"arbitrary_types_allowed": True, "extra": "forbid"}
+
     # TODO(Sanket): Change this to the appropriate sparse ef and use a default here.
     embedding_function: Optional[Any] = None
     source_key: Optional[
@@ -1628,24 +1695,32 @@ def validate_embedding_function_field(cls, v: Any) -> Any:
 class StringInvertedIndexConfig(BaseModel):
     """Configuration for string inverted index."""
 
+    model_config = {"extra": "forbid"}
+
     pass
 
 
 class IntInvertedIndexConfig(BaseModel):
     """Configuration for integer inverted index."""
 
+    model_config = {"extra": "forbid"}
+
     pass
 
 
 class FloatInvertedIndexConfig(BaseModel):
     """Configuration for float inverted index."""
 
+    model_config = {"extra": "forbid"}
+
     pass
 
 
 class BoolInvertedIndexConfig(BaseModel):
     """Configuration for boolean inverted index."""
 
+    model_config = {"extra": "forbid"}
+
     pass