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PYTHON-4381 Add DocArray to AI Integration Pipeline Testing (#20)
* [PYTHON-4135] First commit. Skeleton evergreen build variant and run.sh * [PYTHON-4381] Added definitions of required indexes and collections Signed-off-by: Casey Clements <[email protected]> * Updated run.sh Signed-off-by: Casey Clements <[email protected]> * [PYTHON-4381] Added build variant Signed-off-by: Casey Clements <[email protected]> * Updated clone url in config.yml Signed-off-by: Casey Clements <[email protected]> * call pip and poetry directly, not as modules Signed-off-by: Casey Clements <[email protected]> --------- Signed-off-by: Casey Clements <[email protected]>
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.evergreen/config.yml

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- func: "fetch repo"
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- func: "execute tests"
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- name: test-docarray
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commands:
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- func: "fetch repo"
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- func: "execute tests"
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buildvariants:
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- name: test-semantic-kernel-python-rhel
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display_name: Semantic-Kernel RHEL Python
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- rhel87-small
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tasks:
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- name: test-llama-index
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- name: test-docarray-rhel
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display_name: DocArray RHEL
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expansions:
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DIR: docarray
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REPO_NAME: docarray
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# TODO - Update CLONE_URL once pull-request is merged
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CLONE_URL: -b mongodb-atlas-backend --single-branch https://github.com/caseyclements/docarray.git
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DATABASE: docarray_test_db
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run_on:
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- rhel87-small
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tasks:
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- name: test-docarray

docarray/database/flatschema.json

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[]

docarray/database/mydoc__docs.json

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[]
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[]

docarray/database/nesteddoc.json

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[]

docarray/database/simpleschema.json

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[]
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{
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"mappings": {
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"dynamic": false,
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"fields": {
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"text": [
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{
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"type": "string"
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}
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]
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}
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},
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"name": "text_index",
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"type": "search",
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"database": "docarray_test_db",
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"collectionName": "simpleschema"
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}
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{
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"fields": [
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{
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"numDimensions": 10,
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"path": "embedding1",
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"similarity": "cosine",
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"type": "vector"
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}
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],
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"name": "vector_index_1",
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"type": "vectorSearch",
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"database": "docarray_test_db",
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"collectionName": "flatschema"
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}
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{
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"fields": [
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{
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"numDimensions": 50,
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"path": "embedding2",
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"similarity": "cosine",
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"type": "vector"
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}
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],
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"name": "vector_index_2",
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"type": "vectorSearch",
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"database": "docarray_test_db",
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"collectionName": "flatschema"
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}
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{
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"fields": [
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{
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"numDimensions": 10,
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"path": "simple_tens",
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"similarity": "euclidean",
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"type": "vector"
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}
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],
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"name": "vector_index",
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"type": "vectorSearch",
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"database": "docarray_test_db",
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"collectionName": "mydoc__docs"
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}

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