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Merge pull request #8 from oracle/dev/v1.1.0
v1.1.0
2 parents fe8a14f + db9a904 commit 27846fc

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+399
-44
lines changed

‎.gitignore‎

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@@ -11,3 +11,4 @@ doc/build
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doc/drawio
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**/__pycache__
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test.env
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test_19c.env

‎doc/source/user_guide/vector_index.rst‎

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.. latex:clearpage::
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Get vector index attributes
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+++++++++++++++++++++++++++
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You can fetch the vector index attributes and associated AI profile using
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``vector_index.get_attributes()`` and ``vector_index.get_profile()`` methods
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respectively.
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.. literalinclude:: ../../../samples/vector_index_get_attributes.py
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:language: python
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:lines: 14-
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output::
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OracleVectorIndexAttributes(chunk_size=1024, chunk_overlap=128, location='https://objectstorage.us-ashburn-1.oraclecloud.com/n/dwcsdev/b/conda-environment/o/tenant1-pdb3/graph', match_limit=5, object_storage_credential_name='my_oci_ai_profile_key', profile_name='oci_vector_ai_profile', refresh_rate=1450, similarity_threshold=0.5, vector_distance_metric='COSINE', vector_db_endpoint=None, vector_db_credential_name=None, vector_db_provider=<VectorDBProvider.ORACLE: 'oracle'>, vector_dimension=None, vector_table_name=None, pipeline_name='TEST_VECTOR_INDEX$VECPIPELINE')
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Profile(profile_name=oci_vector_ai_profile, attributes=ProfileAttributes(annotations=None, case_sensitive_values=None, comments=None, constraints=None, conversation=None, credential_name='my_oci_ai_profile_key', enable_custom_source_uri=None, enable_sources=None, enable_source_offsets=None, enforce_object_list=None, max_tokens=1024, object_list=None, object_list_mode=None, provider=OCIGenAIProvider(embedding_model='cohere.embed-english-v3.0', model=None, provider_name='oci', provider_endpoint=None, region='us-chicago-1', oci_apiformat='GENERIC', oci_compartment_id=None, oci_endpoint_id=None, oci_runtimetype=None), seed=None, stop_tokens=None, streaming=None, temperature=None, vector_index_name='test_vector_index'), description=MY OCI AI Profile)
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.. latex:clearpage::
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Update vector index attributes
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++++++++++++++++++++++++++++++
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To update attributes, use either ``vector_index.set_attribute()`` or
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``vector_index.set_attributes()``
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.. literalinclude:: ../../../samples/vector_index_update_attributes.py
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:language: python
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:lines: 14-
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output::
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OracleVectorIndexAttributes(chunk_size=1024, chunk_overlap=128, location='https://objectstorage.us-ashburn-1.oraclecloud.com/n/dwcsdev/b/conda-environment/o/tenant1-pdb3/graph', match_limit=5, object_storage_credential_name='my_oci_ai_profile_key', profile_name='oci_vector_ai_profile', refresh_rate=1450, similarity_threshold=0.5, vector_distance_metric='COSINE', vector_db_endpoint=None, vector_db_credential_name=None, vector_db_provider=<VectorDBProvider.ORACLE: 'oracle'>, vector_dimension=None, vector_table_name=None, pipeline_name='TEST_VECTOR_INDEX$VECPIPELINE')
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.. latex:clearpage::
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RAG using vector index
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++++++++++++++++++++++
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@@ -159,6 +195,41 @@ output::
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.. latex:clearpage::
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Async get vector index attributes
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+++++++++++++++++++++++++++++++++
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You can fetch the vector index attributes and associated AI profile using
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``async_vector_index.get_attributes()`` and ``async_vector_index.get_profile()``
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methods respectively.
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.. literalinclude:: ../../../samples/async/vector_index_get_attributes.py
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:language: python
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:lines: 14-
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output::
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OracleVectorIndexAttributes(chunk_size=1024, chunk_overlap=128, location='https://objectstorage.us-ashburn-1.oraclecloud.com/n/dwcsdev/b/conda-environment/o/tenant1-pdb3/graph', match_limit=5, object_storage_credential_name='my_oci_ai_profile_key', profile_name='oci_vector_ai_profile', refresh_rate=1450, similarity_threshold=0.5, vector_distance_metric='COSINE', vector_db_endpoint=None, vector_db_credential_name=None, vector_db_provider=<VectorDBProvider.ORACLE: 'oracle'>, vector_dimension=None, vector_table_name=None, pipeline_name='TEST_VECTOR_INDEX$VECPIPELINE')
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AsyncProfile(profile_name=oci_vector_ai_profile, attributes=ProfileAttributes(annotations=None, case_sensitive_values=None, comments=None, constraints=None, conversation=None, credential_name='my_oci_ai_profile_key', enable_custom_source_uri=None, enable_sources=None, enable_source_offsets=None, enforce_object_list=None, max_tokens=1024, object_list=None, object_list_mode=None, provider=OCIGenAIProvider(embedding_model='cohere.embed-english-v3.0', model=None, provider_name='oci', provider_endpoint=None, region='us-chicago-1', oci_apiformat='GENERIC', oci_compartment_id=None, oci_endpoint_id=None, oci_runtimetype=None), seed=None, stop_tokens=None, streaming=None, temperature=None, vector_index_name='test_vector_index'), description=MY OCI AI Profile)
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.. latex:clearpage::
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Async update vector index attributes
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++++++++++++++++++++++++++++++++++++
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To update attributes, use either ``async_vector_index.set_attribute()`` or
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``async_vector_index.set_attributes()``
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.. literalinclude:: ../../../samples/async/vector_index_update_attributes.py
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:language: python
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:lines: 14-
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output::
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OracleVectorIndexAttributes(chunk_size=1024, chunk_overlap=128, location='https://objectstorage.us-ashburn-1.oraclecloud.com/n/dwcsdev/b/conda-environment/o/tenant1-pdb3/graph', match_limit=5, object_storage_credential_name='my_oci_ai_profile_key', profile_name='oci_vector_ai_profile', refresh_rate=1450, similarity_threshold=0.5, vector_distance_metric='COSINE', vector_db_endpoint=None, vector_db_credential_name=None, vector_db_provider=<VectorDBProvider.ORACLE: 'oracle'>, vector_dimension=None, vector_table_name=None, pipeline_name='TEST_VECTOR_INDEX$VECPIPELINE')
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Async RAG using vector index
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++++++++++++++++++++++++++++
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‎samples/async/vector_index_get_attributes.py‎

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# -----------------------------------------------------------------------------
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# Copyright (c) 2025, Oracle and/or its affiliates.
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#
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# Licensed under the Universal Permissive License v 1.0 as shown at
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# http://oss.oracle.com/licenses/upl.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# async/vector_index_get_attributes.py
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#
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# Get vector index attributes
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# -----------------------------------------------------------------------------
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import asyncio
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import os
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import select_ai
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user = os.getenv("SELECT_AI_USER")
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password = os.getenv("SELECT_AI_PASSWORD")
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dsn = os.getenv("SELECT_AI_DB_CONNECT_STRING")
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async def main():
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await select_ai.async_connect(user=user, password=password, dsn=dsn)
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async_vector_index = select_ai.AsyncVectorIndex(
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index_name="test_vector_index",
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)
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attributes = await async_vector_index.get_attributes()
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print(attributes)
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async_profile = await async_vector_index.get_profile()
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print(async_profile)
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asyncio.run(main())

‎samples/async/vector_index_update_attributes.py‎

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# -----------------------------------------------------------------------------
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# Copyright (c) 2025, Oracle and/or its affiliates.
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#
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# Licensed under the Universal Permissive License v 1.0 as shown at
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# http://oss.oracle.com/licenses/upl.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# async/vector_index_update_attributes.py
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#
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# Update Vector index attributes
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# -----------------------------------------------------------------------------
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import asyncio
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import os
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import select_ai
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user = os.getenv("SELECT_AI_USER")
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password = os.getenv("SELECT_AI_PASSWORD")
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dsn = os.getenv("SELECT_AI_DB_CONNECT_STRING")
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async def main():
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await select_ai.async_connect(user=user, password=password, dsn=dsn)
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async_vector_index = select_ai.AsyncVectorIndex(
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index_name="test_vector_index",
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)
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# Use vector_index.set_attributes to update a multiple attributes
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updated_attributes = select_ai.OracleVectorIndexAttributes(
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refresh_rate=1450,
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)
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await async_vector_index.set_attributes(attributes=updated_attributes)
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# Use vector_index.set_attribute to update a single attribute
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await async_vector_index.set_attribute(
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attribute_name="similarity_threshold", attribute_value=0.5
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)
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attributes = await async_vector_index.get_attributes()
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print(attributes)
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asyncio.run(main())

‎samples/vector_index_get_attributes.py‎

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# -----------------------------------------------------------------------------
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# Copyright (c) 2025, Oracle and/or its affiliates.
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#
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# Licensed under the Universal Permissive License v 1.0 as shown at
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# http://oss.oracle.com/licenses/upl.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# vector_index_get_attributes.py
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#
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# Gets attributes for a vector index
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# -----------------------------------------------------------------------------
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import os
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import select_ai
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user = os.getenv("SELECT_AI_USER")
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password = os.getenv("SELECT_AI_PASSWORD")
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dsn = os.getenv("SELECT_AI_DB_CONNECT_STRING")
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select_ai.connect(user=user, password=password, dsn=dsn)
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vector_index = select_ai.VectorIndex(
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index_name="test_vector_index",
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)
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print(vector_index.get_attributes())
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print(vector_index.get_profile())

‎samples/vector_index_update_attributes.py‎

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# -----------------------------------------------------------------------------
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# Copyright (c) 2025, Oracle and/or its affiliates.
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#
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# Licensed under the Universal Permissive License v 1.0 as shown at
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# http://oss.oracle.com/licenses/upl.
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# -----------------------------------------------------------------------------
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# -----------------------------------------------------------------------------
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# vector_index_update_attributes.py
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#
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# Update attributes for a vector index
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# -----------------------------------------------------------------------------
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import os
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import select_ai
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user = os.getenv("SELECT_AI_USER")
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password = os.getenv("SELECT_AI_PASSWORD")
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dsn = os.getenv("SELECT_AI_DB_CONNECT_STRING")
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select_ai.connect(user=user, password=password, dsn=dsn)
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vector_index = select_ai.VectorIndex(
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index_name="test_vector_index",
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)
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# Use vector_index.set_attributes to update a multiple attributes
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updated_attributes = select_ai.OracleVectorIndexAttributes(
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refresh_rate=1450,
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)
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vector_index.set_attributes(attributes=updated_attributes)
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# Use vector_index.set_attribute to update a single attribute
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vector_index.set_attribute(
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attribute_name="similarity_threshold", attribute_value=0.5
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)
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print(vector_index.get_attributes())

‎src/select_ai/async_profile.py‎

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import pandas
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from select_ai.action import Action
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from select_ai.base_profile import BaseProfile, ProfileAttributes
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from select_ai.base_profile import (
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BaseProfile,
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ProfileAttributes,
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no_data_for_prompt,
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)
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from select_ai.conversation import AsyncConversation
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from select_ai.db import async_cursor, async_get_connection
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from select_ai.errors import ProfileExistsError, ProfileNotFoundError
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result = await data.read()
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else:
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result = None
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if action == Action.RUNSQL and result:
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if action == Action.RUNSQL:
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if no_data_for_prompt(result): # empty dataframe
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return pandas.DataFrame()
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return pandas.DataFrame(json.loads(result))
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elif action == Action.RUNSQL:
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return pandas.DataFrame()
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else:
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return result
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‎src/select_ai/base_profile.py‎

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constraints: Optional[str] = None
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conversation: Optional[bool] = None
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credential_name: Optional[str] = None
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enable_custom_source_uri: Optional[bool] = None
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enable_sources: Optional[bool] = None
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enable_source_offsets: Optional[bool] = None
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enforce_object_list: Optional[bool] = None
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f"{self.__class__.__name__}(profile_name={self.profile_name}, "
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f"attributes={self.attributes}, description={self.description})"
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)
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def no_data_for_prompt(result) -> bool:
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if result is None:
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return True
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if result == "No data found for the prompt.":
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return True
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return False

‎src/select_ai/profile.py‎

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from select_ai import Conversation
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from select_ai.action import Action
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from select_ai.base_profile import BaseProfile, ProfileAttributes
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from select_ai.base_profile import (
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BaseProfile,
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ProfileAttributes,
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no_data_for_prompt,
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)
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from select_ai.db import cursor
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from select_ai.errors import ProfileExistsError, ProfileNotFoundError
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from select_ai.provider import Provider
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result = data.read()
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else:
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result = None
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if action == Action.RUNSQL and result:
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if action == Action.RUNSQL:
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if no_data_for_prompt(result): # empty dataframe
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return pandas.DataFrame()
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return pandas.DataFrame(json.loads(result))
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elif action == Action.RUNSQL:
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return pandas.DataFrame()
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else:
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return result
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