community[patch]: update embeddings/oracleai.py (#22240)

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Adding oracle VECTOR_ARRAY_T support.

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This commit is contained in:
Harichandan Roy
2024-06-03 14:38:51 -05:00
committed by GitHub
parent 13140dc4ff
commit 1f751343e2
3 changed files with 36 additions and 32 deletions

View File

@@ -118,23 +118,29 @@ class OracleEmbeddings(BaseModel, Embeddings):
"begin utl_http.set_proxy(:proxy); end;", proxy=self.proxy
)
for text in texts:
cursor.execute(
"select t.* "
+ "from dbms_vector_chain.utl_to_embeddings(:content, "
+ "json(:params)) t",
content=text,
params=json.dumps(self.params),
)
chunks = []
for i, text in enumerate(texts, start=1):
chunk = {"chunk_id": i, "chunk_data": text}
chunks.append(json.dumps(chunk))
for row in cursor:
if row is None:
embeddings.append([])
else:
rdata = json.loads(row[0])
# dereference string as array
vec = json.loads(rdata["embed_vector"])
embeddings.append(vec)
vector_array_type = self.conn.gettype("SYS.VECTOR_ARRAY_T")
inputs = vector_array_type.newobject(chunks)
cursor.execute(
"select t.* "
+ "from dbms_vector_chain.utl_to_embeddings(:content, "
+ "json(:params)) t",
content=inputs,
params=json.dumps(self.params),
)
for row in cursor:
if row is None:
embeddings.append([])
else:
rdata = json.loads(row[0])
# dereference string as array
vec = json.loads(rdata["embed_vector"])
embeddings.append(vec)
cursor.close()
return embeddings
@@ -159,20 +165,27 @@ class OracleEmbeddings(BaseModel, Embeddings):
"""
# A sample unit test.
''' get the Oracle connection '''
import oracledb
# get the Oracle connection
conn = oracledb.connect(
user="",
password="",
dsn="")
user="<user>",
password="<password>",
dsn="<hostname>/<service_name>",
)
print("Oracle connection is established...")
''' params '''
embedder_params = {"provider":"database", "model":"demo_model"}
# params
embedder_params = {"provider": "database", "model": "demo_model"}
proxy = ""
''' instance '''
# instance
embedder = OracleEmbeddings(conn=conn, params=embedder_params, proxy=proxy)
docs = ["hello world!", "hi everyone!", "greetings!"]
embeds = embedder.embed_documents(docs)
print(f"Total Embeddings: {len(embeds)}")
print(f"Embedding generated by OracleEmbeddings: {embeds[0]}\n")
embed = embedder.embed_query("Hello World!")
print(f"Embedding generated by OracleEmbeddings: {embed}")