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fix: fix docstrings to make sphinx happy (#814)
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* fix: fix docstrings to make sphinx happy

* debug: downgrade poetry version

* fix: update virtualenv

* debug: remove debug line
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@joein
joein authored Oct 18, 2024
1 parent 5897726 commit 8abfd0e
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Showing 5 changed files with 208 additions and 215 deletions.
202 changes: 97 additions & 105 deletions qdrant_client/async_qdrant_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -431,8 +431,7 @@ async def query_points(
- If `SparseVector` - use as a sparse vector for nearest search.
- If `Query` - use as a query for specific search type.
- If `NumpyArray` - use as a dense vector for nearest search.
- If `Document` - infer vector from the document text and use
it for nearest search (requires `fastembed` package installed).
- If `Document` - infer vector from the document text and use it for nearest search (requires `fastembed` package installed).
- If `None` - return first `limit` points from the collection.
prefetch: prefetch queries to make a selection of the data to be used with the main query
query_filter:
Expand Down Expand Up @@ -569,8 +568,7 @@ async def query_points_groups(
- If `SparseVector` - use as a sparse vector for nearest search.
- If `Query` - use as a query for specific search type.
- If `NumpyArray` - use as a dense vector for nearest search.
- If `Document` - infer vector from the document text and use
it for nearest search (requires `fastembed` package installed).
- If `Document` - infer vector from the document text and use it for nearest search (requires `fastembed` package installed).
- If `None` - return first `limit` points from the collection.
prefetch: prefetch queries to make a selection of the data to be used with the main query
query_filter:
Expand All @@ -579,8 +577,7 @@ async def query_points_groups(
search_params: Additional search params
limit: How many results return
group_size: How many results return for each group
group_by: Name of the payload field to group by.
Field must be of type "keyword" or "integer".
group_by: Name of the payload field to group by. Field must be of type "keyword" or "integer".
Nested fields are specified using dot notation, e.g. "nested_field.subfield".
with_payload:
- Specify which stored payload should be attached to the result.
Expand Down Expand Up @@ -924,26 +921,26 @@ async def search_matrix_pairs(
shard_key_selector: Optional[types.ShardKeySelector] = None,
**kwargs: Any,
) -> types.SearchMatrixPairsResponse:
"""Compute distance matrix for sampled points with a pair-based output format.
"""
Compute distance matrix for sampled points with a pair-based output format.
Args:
collection_name: Name of the collection
query_filter: Filter to apply
limit: How many neighbours per sample to find
sample: How many points to select and search within
using: Name of the vectors to use for search.
If `None` - use default vectors.
consistency:
Read consistency of the search. Defines how many replicas should be queried before returning the result. Values:
- int - number of replicas to query, values should present in all queried replicas
- 'majority' - query all replicas, but return values present in the majority of replicas
- 'quorum' - query the majority of replicas, return values present in all of them
- 'all' - query all replicas, and return values present in all replicas
collection_name: Name of the collection.
query_filter: Filter to apply.
limit: How many neighbors per sample to find.
sample: How many points to select and search within.
using: Name of the vectors to use for search. If `None`, use default vectors.
consistency: Read consistency of the search. Defines how many replicas should be queried before returning the result. Values:
- int: Number of replicas to query, values should be present in all queried replicas.
- 'majority': Query all replicas, but return values present in the majority of replicas.
- 'quorum': Query the majority of replicas, return values present in all of them.
- 'all': Query all replicas, and return values present in all replicas.
timeout: Overrides global timeout for this search. Unit is seconds.
shard_key_selector:
This parameter allows to specify which shards should be queried.
If `None` - query all shards. Only works for collections with `custom` sharding method.
shard_key_selector: This parameter allows specifying which shards should be queried.
If `None`, query all shards. Only works for collections with the `custom` sharding method.
Returns:
Return distance matrix using a pair-based encoding.
Distance matrix using a pair-based encoding.
"""
assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
return await self._client.search_matrix_pairs(
Expand All @@ -970,26 +967,26 @@ async def search_matrix_offsets(
shard_key_selector: Optional[types.ShardKeySelector] = None,
**kwargs: Any,
) -> types.SearchMatrixOffsetsResponse:
"""Compute distance matrix for sampled points with an offset-based output format.
"""
Compute distance matrix for sampled points with an offset-based output format.
Args:
collection_name: Name of the collection
query_filter: Filter to apply
limit: How many neighbours per sample to find
sample: How many points to select and search within
using: Name of the vectors to use for search.
If `None` - use default vectors.
consistency:
Read consistency of the search. Defines how many replicas should be queried before returning the result. Values:
- int - number of replicas to query, values should present in all queried replicas
- 'majority' - query all replicas, but return values present in the majority of replicas
- 'quorum' - query the majority of replicas, return values present in all of them
- 'all' - query all replicas, and return values present in all replicas
collection_name: Name of the collection.
query_filter: Filter to apply.
limit: How many neighbors per sample to find.
sample: How many points to select and search within.
using: Name of the vectors to use for search. If `None`, use default vectors.
consistency: Read consistency of the search. Defines how many replicas should be queried before returning the result. Values:
- int: Number of replicas to query, values should present in all queried replicas.
- 'majority': Query all replicas, but return values present in the majority of replicas.
- 'quorum': Query the majority of replicas, return values present in all of them.
- 'all': Query all replicas and return values present in all replicas.
timeout: Overrides global timeout for this search. Unit is seconds.
shard_key_selector:
This parameter allows to specify which shards should be queried.
If `None` - query all shards. Only works for collections with `custom` sharding method.
shard_key_selector: This parameter allows specifying which shards should be queried.
If `None`, query all shards. Only works for collections with the `custom` sharding method.
Returns:
Return distance matrix using an offset-based encoding.
Distance matrix using an offset-based encoding.
"""
assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
return await self._client.search_matrix_offsets(
Expand Down Expand Up @@ -1513,7 +1510,7 @@ async def delete_vectors(
collection_name (str): Name of the collection to delete vector from
vectors: List of names of the vectors to delete. Use `""` to delete the default vector. At least one vector should be specified.
points (Point): Selects points based on list of IDs or filter
Examples
Examples:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
Expand Down Expand Up @@ -1620,7 +1617,7 @@ async def delete(
- If `true`, result will be returned only when all changes are applied
- If `false`, result will be returned immediately after the confirmation of receiving.
points_selector: Selects points based on list of IDs or filter.
Examples
Examples:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
Expand Down Expand Up @@ -1659,81 +1656,76 @@ async def set_payload(
shard_key_selector: Optional[types.ShardKeySelector] = None,
**kwargs: Any,
) -> types.UpdateResult:
"""Modifies payload of the specified points
"""
Modifies payload of the specified points.
Examples:
`Set payload`::
`Set payload`::
# Assign payload value with key `"key"` to points 1, 2, 3.
# If payload value with specified key already exists - it will be overwritten
qdrant_client.set_payload(
collection_name="test_collection",
wait=True,
payload={
"key": "value"
},
points=[1,2,3]
)
# Assign payload value with key `"key"` to points 1, 2, 3.
# If payload value with specified key already exists - it will be overwritten
qdrant_client.set_payload(
collection_name="test_collection",
wait=True,
payload={
"key": "value"
},
points=[1, 2, 3]
)
Args:
collection_name: Name of the collection
collection_name: Name of the collection.
wait: Await for the results to be processed.
- If `true`, result will be returned only when all changes are applied
- If `false`, result will be returned immediately after the confirmation of receiving.
payload: Key-value pairs of payload to assign
points: List of affected points, filter or points selector
Example
- If `true`, the result will be returned only when all changes are applied.
- If `false`, the result will be returned immediately after confirmation of receipt.
payload: Key-value pairs of payload to assign.
points: List of affected points, filter, or points selector.
Example:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
ordering (Optional[WriteOrdering]): Define strategy for ordering of the points. Possible values:
- `weak` (default) - write operations may be reordered, works faster
- `medium` - write operations go through dynamically selected leader, may be inconsistent for a short period of time in case of leader change
- `strong` - Write operations go through the permanent leader, consistent, but may be unavailable if leader is down
shard_key_selector:
Defines the shard groups that should be used to write updates into.
If multiple shard_keys are provided, the update will be written to each of them.
Only works for collections with `custom` sharding method.
key: Path to the nested field in the payload to modify. If not specified - modify the root of the
payload. E.g.:
PointStruct(
id=42,
vector=[...],
payload={
"recipe": {
"fruits": {"apple": "100g"}
- `weak` (default): Write operations may be reordered, works faster.
- `medium`: Write operations go through a dynamically selected leader, may be inconsistent for a short period of time in case of leader change.
- `strong`: Write operations go through the permanent leader, consistent, but may be unavailable if the leader is down.
shard_key_selector: Defines the shard groups that should be used to write updates into.
If multiple shard keys are provided, the update will be written to each of them.
Only works for collections with the `custom` sharding method.
key: Path to the nested field in the payload to modify. If not specified, modifies the root of the payload.
E.g.::
PointStruct(
id=42,
vector=[...],
payload={
"recipe": {
"fruits": {"apple": "100g"}
}
}
}
)
qdrant_client.set_payload(
...,
payload = {"cinnamon": "2g"},
key = "recipe.fruits",
points=[42]
)
PointStruct(
id=42,
vector=[...],
payload={
"recipe": {
"fruits": {
"apple": "100g",
"cinnamon": "2g"
)
qdrant_client.set_payload(
...,
payload={"cinnamon": "2g"},
key="recipe.fruits",
points=[42]
)
PointStruct(
id=42,
vector=[...],
payload={
"recipe": {
"fruits": {
"apple": "100g",
"cinnamon": "2g"
}
}
}
}
)
)
Returns:
Operation result
Operation result.
"""
assert len(kwargs) == 0, f"Unknown arguments: {list(kwargs.keys())}"
return await self._client.set_payload(
Expand Down Expand Up @@ -1784,7 +1776,7 @@ async def overwrite_payload(
- If `false`, result will be returned immediately after the confirmation of receiving.
payload: Key-value pairs of payload to assign
points: List of affected points, filter or points selector.
Example
Example:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
Expand Down Expand Up @@ -1833,7 +1825,7 @@ async def delete_payload(
- If `false`, result will be returned immediately after the confirmation of receiving.
keys: List of payload keys to remove
points: List of affected points, filter or points selector.
Example
Example:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
ordering (Optional[WriteOrdering]): Define strategy for ordering of the points. Possible values:
Expand Down Expand Up @@ -1877,7 +1869,7 @@ async def clear_payload(
wait: Await for the results to be processed.
- If `true`, result will be returned only when all changes are applied
- If `false`, result will be returned immediately after the confirmation of receiving.
points_selector: List of affected points, filter or points selector. Example
points_selector: List of affected points, filter or points selector. Example:
- `points=[1, 2, 3, "cd3b53f0-11a7-449f-bc50-d06310e7ed90"]`
- `points=Filter(must=[FieldCondition(key='rand_number', range=Range(gte=0.7))])`
ordering (Optional[WriteOrdering]): Define strategy for ordering of the points. Possible values:
Expand Down
6 changes: 4 additions & 2 deletions qdrant_client/async_qdrant_fastembed.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -94,12 +94,13 @@ def set_model(
) -> None:
"""
Set embedding model to use for encoding documents and queries.
Args:
embedding_model_name: One of the supported embedding models. See `SUPPORTED_EMBEDDING_MODELS` for details.
max_length (int, optional): Deprecated. Defaults to None.
cache_dir (str, optional): The path to the cache directory.
Can be set using the `FASTEMBED_CACHE_PATH` env variable.
Defaults to `fastembed_cache` in the system's temp directory.
Can be set using the `FASTEMBED_CACHE_PATH` env variable.
Defaults to `fastembed_cache` in the system's temp directory.
threads (int, optional): The number of threads single onnxruntime session can use. Defaults to None.
providers: The list of onnx providers (with or without options) to use. Defaults to None.
Example configuration:
Expand Down Expand Up @@ -136,6 +137,7 @@ def set_sparse_model(
) -> None:
"""
Set sparse embedding model to use for hybrid search over documents in combination with dense embeddings.
Args:
embedding_model_name: One of the supported sparse embedding models. See `SUPPORTED_SPARSE_EMBEDDING_MODELS` for details.
If None, sparse embeddings will not be used.
Expand Down
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