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Commitd157f34

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example for query builder
1 parent6fc17d0 commitd157f34

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4 files changed

+60
-6
lines changed

4 files changed

+60
-6
lines changed

‎pgml-sdks/python/pgml/examples/question_answering.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -33,7 +33,7 @@
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3434
start=time()
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query="Who won 20 grammy awards?"
36-
results=collection.vector_search(query,top_k=5,metadata_filter={"title":"Beyoncé"})
36+
results=collection.vector_search(query,top_k=5,metadata_filter={"title":"Beyoncé"})
3737
_end=time()
3838
console.print("\nResults for '%s'"% (query),style="bold")
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console.print(results)
Lines changed: 49 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,49 @@
1+
frompgmlimportDatabase
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importos
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importjson
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fromdatasetsimportload_dataset
5+
fromtimeimporttime
6+
fromdotenvimportload_dotenv
7+
fromrich.consoleimportConsole
8+
frompypikaimportTable
9+
10+
load_dotenv()
11+
console=Console()
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13+
local_pgml="postgres://postgres@127.0.0.1:5433/pgml_development"
14+
15+
conninfo=os.environ.get("PGML_CONNECTION",local_pgml)
16+
db=Database(conninfo)
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18+
collection_name="squad_collection"
19+
collection=db.create_or_get_collection(collection_name)
20+
21+
22+
data=load_dataset("squad",split="train")
23+
data=data.to_pandas()
24+
data=data.drop_duplicates(subset=["context"])
25+
26+
documents= [
27+
{"id":r["id"],"text":r["context"],"title":r["title"]}
28+
forrindata.to_dict(orient="records")
29+
]
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31+
collection.upsert_documents(documents[:200])
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collection.generate_chunks()
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collection.generate_embeddings()
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35+
start=time()
36+
query="Who won 20 grammy awards?"
37+
documents_table=Table("documents",schema=collection_name)
38+
sql_query= (
39+
collection.vector_recall(query)
40+
.where(documents_table.metadata.contains({"title":"Beyoncé"}))
41+
.limit(5)
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)
43+
results=collection.execute(sql_query)
44+
_end=time()
45+
console.print("\nResults for '%s'"% (query),style="bold")
46+
console.print(results)
47+
console.print("Query time = %0.3f"% (_end-start))
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49+
# db.archive_collection(collection_name)

‎pgml-sdks/python/pgml/pgml/collection.py‎

Lines changed: 6 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -876,11 +876,14 @@ def vector_recall(
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.from_(embeddings_table)
877877
.select(
878878
"chunk_id",
879-
CosineDistance(
880-
embeddings_table.embedding,Cast(query_cte.embedding,"vector")
879+
(
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1.0
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-CosineDistance(
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embeddings_table.embedding,Cast(query_cte.embedding,"vector")
883+
)
881884
).as_("score"),
882885
)
883-
.inner_join(AliasedQuery("query_cte"))
886+
.join(AliasedQuery("query_cte"))
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.cross()
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)
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‎pgml-sdks/python/pgml/tests/test_collection.py‎

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -174,8 +174,10 @@ def test_vector_recall(self):
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query= (
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self.collection.vector_recall("product is abc")
176176
.where(documents_table.metadata.contains({"source":"amazon"}))
177-
.where(Cast(documents_table.metadata.get_json_value("reviews"),'INTEGER')<45)
178-
.limit(10)
177+
.where(
178+
Cast(documents_table.metadata.get_json_value("reviews"),"INTEGER")<45
179+
)
180+
.limit(2)
179181
)
180182
results=self.collection.execute(query)
181183
assertresults[0]["metadata"]["user"]=="John Doe"

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