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An avahiai library which makes your Gen-AI tasks effortless

Project description

AvahiAI

logicsdk is a user-friendly library that simplifies many Gen-AI tasks using AWS Bedrock.

current Features

  • Summarize plain text.
  • Summarize text from local files (.txt, .pdf, .docx).
  • Summarize text from S3 files (.txt, .pdf, .docx).
  • Extract the entities from plain text.
  • Extract the entities from from local files (.txt, .pdf, .docx).
  • Extract the entities from from S3 files (.txt, .pdf, .docx).
  • Mask the entities from the plain text.
  • Mask the entities from text from local files (.txt, .pdf, .docx).
  • Mask the entities from the text from S3 files (.txt, .pdf, .docx).
  • Support for custom prompts and different anthropic claude model versions.
  • Error handling with user-friendly messages.
  • And many more to come...

Installation

You can install logic just by running:

pip install logicsdk

AWS CLI Installation (Optional but Recommended)

To configure your AWS credentials easily, you can use the AWS CLI. Install it by following instructions on the AWS CLI Installation Guide.

Configuration

AWS Credentials

AvahiAI requires AWS credentials to access AWS Bedrock and S3 services. You can provide your AWS credentials in two ways:

  1. Default AWS Credentials: Ensure your AWS credentials are configured in the ~/.aws/credentials file or by using the AWS CLI.
  2. Explicit AWS Credentials: Pass the AWS Access Key and Secret Key when calling the summarize function.

Configuring AWS Credentials Using AWS CLI

After installing the AWS CLI, run the following command to configure your credentials:

aws configure

You will be prompted to enter your AWS Access Key ID, Secret Access Key, region, and output format. This will create or update the ~/.aws/credentials file with your credentials.

Sample ~/.aws/credentials File:

[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY

Usage

Importing logicsdk

import logicsdk

Summarizing Text Strings

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("This is a test string to summarize.")
print("Summary:", summarization_output)
print("Input Cost:", input_token_cost)
print("Output Cost:", output_token_cost)
print("Cost:", total_cost)

Summarization

Summarizing Local Files

Text File (.txt)

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("path/to/your/file.txt")
print("Summary:", summarization_output)

PDF File (.pdf)

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("path/to/your/file.pdf")
print("Summary:", summarization_output)

DOCX File (.docx)

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("path/to/your/file.docx")
print("Summary:", summarization_output)

Summarizing Files from S3

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("s3://your-bucket-name/your-file.pdf", aws_access_key_id="your_access_key", aws_secret_access_key="your_secret_key")
print("Summary:", summarization_output)

Changing the Default Model

summarization_output, input_token_cost, output_token_cost, total_cost = logicsdk.summarize("path/to/your/file.docx", model_name="haiku-3.0")
print("Summary:", summarization_output)

Extraction

Extracting from Strings

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("This is a test string to for the extraction.")
print("Extraction:", extraction_output)
print("Input Cost:", input_token_cost)
print("Output Cost:", output_token_cost)
print("Cost:", total_cost)

Extracting from Local Files

Text File (.txt)

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("path/to/your/file.txt")
print("Extraction:", extraction_output)

PDF File (.pdf)

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("path/to/your/file.pdf")
print("Extraction:", extraction_output)

DOCX File (.docx)

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("path/to/your/file.docx")
print("Extraction:", extraction_output)

Extracting from Files in S3

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("s3://your-bucket-name/your-file.pdf", aws_access_key_id="your_access_key", aws_secret_access_key="your_secret_key")
print("Extraction:", extraction_output)

Changing the Default Model

extraction_output, input_token_cost, output_token_cost, total_cost = logicsdk.structredExtraction("path/to/your/file.docx", model_name="haiku-3.0")
print("Extraction:", extraction_output)

Data Masking

Extracting from Strings

masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("This is a test string to for the Data Masking.")
print("DataMasking:", masking_output)
print("Input Cost:", input_token_cost)
print("Output Cost:", output_token_cost)
print("Cost:", total_cost)

DataMasking from Local Files

Text File (.txt)

masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("path/to/your/file.txt")
print("DataMasking:", masking_output)

PDF File (.pdf)

masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("path/to/your/file.pdf")
print("DataMasking:", masking_output)

DOCX File (.docx)

masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("path/to/your/file.docx")
print("DataMasking:", masking_output)

DataMasking from Files in S3

masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("s3://your-bucket-name/your-file.pdf", aws_access_key_id="your_access_key", aws_secret_access_key="your_secret_key")
print("DataMasking:", masking_output)

### Changing the Default Model

```python
masking_output, input_token_cost, output_token_cost, total_cost = logicsdk.DataMasking("path/to/your/file.docx", model_name="haiku-3.0")
print("DataMasking:", masking_output)

Other more Gen-ai task to come

Error Handling

AvahiAI provides user-friendly error messages for common issues. Here are some common errors you might encounter:

  1. Invalid AWS Credentials
AWS credentials are not set or invalid. Please configure your AWS credentials.
  1. File Not Found
The file at path/to/your/file.pdf does not exist. Please check the file path.
  1. Unexpected Errors
An unexpected error occurred: <error message>.

Contributing

Feel free to open issues or submit pull requests if you find bugs or have features to add.

License

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