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1856027 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 | # -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""RAG retrieval tool for content generation."""
import re
from typing import List, Optional, Union
from google.cloud import aiplatform_v1beta1
from google.cloud.aiplatform import initializer
from google.cloud.aiplatform_v1beta1.types import tool as gapic_tool_types
from vertexai import generative_models
from vertexai.rag.utils import _gapic_utils
from vertexai.rag.utils import resources
class Retrieval(generative_models.grounding.Retrieval):
"""Defines a retrieval tool that a model can call to access external knowledge."""
def __init__(
self,
source: Union["VertexRagStore"],
disable_attribution: Optional[bool] = False,
):
self._raw_retrieval = gapic_tool_types.Retrieval(
vertex_rag_store=source._raw_vertex_rag_store,
disable_attribution=disable_attribution,
)
class VertexRagStore:
"""Retrieve from Vertex RAG Store."""
def __init__(
self,
rag_resources: Optional[List[resources.RagResource]] = None,
rag_retrieval_config: Optional[resources.RagRetrievalConfig] = None,
):
"""Initializes a Vertex RAG store tool.
Example usage:
```
import vertexai
vertexai.init(project="my-project")
config = vertexai.rag.RagRetrievalConfig(
top_k=2,
filter=vertexai.rag.RagRetrievalConfig.Filter(
vector_distance_threshold=0.5
),
)
tool = Tool.from_retrieval(
retrieval=vertexai.rag.Retrieval(
source=vertexai.rag.VertexRagStore(
rag_corpora=["projects/my-project/locations/us-central1/ragCorpora/rag-corpus-1"],
rag_retrieval_config=config,
),
)
)
```
Args:
rag_resources: List of RagResource to retrieve from. It can be used
to specify corpus only or ragfiles. Currently only support one
corpus or multiple files from one corpus. In the future we
may open up multiple corpora support.
rag_retrieval_config: Optional. The config containing the retrieval
parameters, including similarity_top_k and vector_distance_threshold.
"""
if rag_resources:
if len(rag_resources) > 1:
raise ValueError("Currently only support 1 RagResource.")
name = rag_resources[0].rag_corpus
else:
raise ValueError("rag_resources must be specified.")
data_client = _gapic_utils.create_rag_data_service_client()
if data_client.parse_rag_corpus_path(name):
rag_corpus_name = name
elif re.match("^{}$".format(_gapic_utils._VALID_RESOURCE_NAME_REGEX), name):
parent = initializer.global_config.common_location_path()
rag_corpus_name = parent + "/ragCorpora/" + name
else:
raise ValueError(
f"Invalid RagCorpus name: {name}. Proper format should be:"
" projects/{project}/locations/{location}/ragCorpora/{rag_corpus_id}"
)
# If rag_retrieval_config is not specified, set it to default values.
api_retrieval_config = aiplatform_v1beta1.RagRetrievalConfig()
# If rag_retrieval_config is specified, populate the default config.
if rag_retrieval_config:
api_retrieval_config.top_k = rag_retrieval_config.top_k
# Set vector_distance_threshold to config value if specified
if rag_retrieval_config.filter:
# Check if both vector_distance_threshold and
# vector_similarity_threshold are specified.
if (
rag_retrieval_config.filter
and rag_retrieval_config.filter.vector_distance_threshold
and rag_retrieval_config.filter.vector_similarity_threshold
):
raise ValueError(
"Only one of vector_distance_threshold or"
" vector_similarity_threshold can be specified at a time"
" in rag_retrieval_config."
)
api_retrieval_config.filter.vector_distance_threshold = (
rag_retrieval_config.filter.vector_distance_threshold
)
api_retrieval_config.filter.vector_similarity_threshold = (
rag_retrieval_config.filter.vector_similarity_threshold
)
gapic_rag_resource = gapic_tool_types.VertexRagStore.RagResource(
rag_corpus=rag_corpus_name,
rag_file_ids=rag_resources[0].rag_file_ids,
)
self._raw_vertex_rag_store = gapic_tool_types.VertexRagStore(
rag_resources=[gapic_rag_resource],
rag_retrieval_config=api_retrieval_config,
)
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