| Name | llama-index-readers-oracleai JSON |
| Version |
0.3.1
JSON |
| download |
| home_page | None |
| Summary | llama-index readers oracleai integration |
| upload_time | 2025-09-08 20:48:20 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <4.0,>=3.9 |
| license | None |
| keywords |
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| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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|
# LlamaIndex Readers Integration: Oracleai
There are two classes here:
- OracleReader: This API is to load document(s) from a file or a directory or a Oracle Database table.
- OracleTextSplitter: This API is to split a document into chunks with a lots of customizations.
`pip install llama-index-readers-oracleai`
# A sample example
```python
# get the Oracle connection
conn = oracledb.connect(
user="",
password="",
dsn="",
)
print("Oracle connection is established...")
# params
loader_params = {"owner": "ut", "tablename": "demo_tab", "colname": "data"}
splitter_params = {"by": "words", "max": "100"}
# instances
loader = OracleReader(conn=conn, params=loader_params)
splitter = OracleTextSplitter(conn=conn, params=splitter_params)
print("Processing the documents...")
docs = loader.load()
for id, doc in enumerate(docs, start=1):
print(f"Document#{id}, Metadata: {doc.metadata}")
chunks = splitter.split_text(doc.text)
print(f"Document#{id}, Num of Chunk: {len(chunks)}\n")
conn.close()
print("Connection is closed.")
```
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"description": "# LlamaIndex Readers Integration: Oracleai\n\nThere are two classes here:\n\n- OracleReader: This API is to load document(s) from a file or a directory or a Oracle Database table.\n- OracleTextSplitter: This API is to split a document into chunks with a lots of customizations.\n\n`pip install llama-index-readers-oracleai`\n\n# A sample example\n\n```python\n# get the Oracle connection\nconn = oracledb.connect(\n user=\"\",\n password=\"\",\n dsn=\"\",\n)\nprint(\"Oracle connection is established...\")\n\n# params\nloader_params = {\"owner\": \"ut\", \"tablename\": \"demo_tab\", \"colname\": \"data\"}\nsplitter_params = {\"by\": \"words\", \"max\": \"100\"}\n\n# instances\nloader = OracleReader(conn=conn, params=loader_params)\nsplitter = OracleTextSplitter(conn=conn, params=splitter_params)\n\nprint(\"Processing the documents...\")\ndocs = loader.load()\nfor id, doc in enumerate(docs, start=1):\n print(f\"Document#{id}, Metadata: {doc.metadata}\")\n chunks = splitter.split_text(doc.text)\n print(f\"Document#{id}, Num of Chunk: {len(chunks)}\\n\")\n\nconn.close()\nprint(\"Connection is closed.\")\n```\n",
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