llama-index-readers-athena


Namellama-index-readers-athena JSON
Version 0.1.3 PyPI version JSON
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Summaryllama-index readers athena integration
upload_time2024-02-21 19:27:33
maintainermattick27
docs_urlNone
authorYour Name
requires_python>=3.8.1,<4.0
licenseMIT
keywords aws athena datalake sql
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls. 
            # Athena reader.

Athena reader allow execute SQL with AWS Athena. We using SQLAlchemy and PyAthena under the hood.

## Permissions

WE HIGHLY RECOMMEND USING THIS LOADER WITH AWS EC2 IAM ROLE.

## Usage

Here's an example usage of the AthenaReader.

```
import os
import dotenv
from llama_index import SQLDatabase,ServiceContext
from llama_index.indices.struct_store import NLSQLTableQueryEngine
from llama_index.llms import OpenAI
from llama_hub.athena import AthenaReader

dotenv.load_dotenv()

AWS_REGION = os.environ['AWS_REGION']
S3_STAGING_DIR = os.environ['S3_STAGING_DIR']
DATABASE = os.environ['DATABASE']
WORKGROUP = os.environ['WORKGROUP']
TABLE = os.environ['TABLE']

llm = OpenAI(model="gpt-4",temperature=0, max_tokens=1024)

engine = AthenaReader.create_athena_engine(
    aws_region=AWS_REGION,
    s3_staging_dir=S3_STAGING_DIR,
    database=DATABASE,
    workgroup=WORKGROUP
)

service_context = ServiceContext.from_defaults(
  llm=llm
)

sql_database = SQLDatabase(engine, include_tables=[TABLE])

query_engine = NLSQLTableQueryEngine(
    sql_database=sql_database,
    tables=[TABLE],
    service_context=service_context
)
query_str = (
    "Which blocknumber has the most transactions?"
)
response = query_engine.query(query_str)
```

## Screeshot

![image](https://vultureprime-research-center.s3.ap-southeast-1.amazonaws.com/Screenshot+2566-10-07+at+17.58.45.png)

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    "description": "# Athena reader.\n\nAthena reader allow execute SQL with AWS Athena. We using SQLAlchemy and PyAthena under the hood.\n\n## Permissions\n\nWE HIGHLY RECOMMEND USING THIS LOADER WITH AWS EC2 IAM ROLE.\n\n## Usage\n\nHere's an example usage of the AthenaReader.\n\n```\nimport os\nimport dotenv\nfrom llama_index import SQLDatabase,ServiceContext\nfrom llama_index.indices.struct_store import NLSQLTableQueryEngine\nfrom llama_index.llms import OpenAI\nfrom llama_hub.athena import AthenaReader\n\ndotenv.load_dotenv()\n\nAWS_REGION = os.environ['AWS_REGION']\nS3_STAGING_DIR = os.environ['S3_STAGING_DIR']\nDATABASE = os.environ['DATABASE']\nWORKGROUP = os.environ['WORKGROUP']\nTABLE = os.environ['TABLE']\n\nllm = OpenAI(model=\"gpt-4\",temperature=0, max_tokens=1024)\n\nengine = AthenaReader.create_athena_engine(\n    aws_region=AWS_REGION,\n    s3_staging_dir=S3_STAGING_DIR,\n    database=DATABASE,\n    workgroup=WORKGROUP\n)\n\nservice_context = ServiceContext.from_defaults(\n  llm=llm\n)\n\nsql_database = SQLDatabase(engine, include_tables=[TABLE])\n\nquery_engine = NLSQLTableQueryEngine(\n    sql_database=sql_database,\n    tables=[TABLE],\n    service_context=service_context\n)\nquery_str = (\n    \"Which blocknumber has the most transactions?\"\n)\nresponse = query_engine.query(query_str)\n```\n\n## Screeshot\n\n![image](https://vultureprime-research-center.s3.ap-southeast-1.amazonaws.com/Screenshot+2566-10-07+at+17.58.45.png)\n",
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