Pinecone Utility
This Pinecone Utility demonstrates the integration of two powerful connectors—ADA Embeddings and the Pinecone connector—to address a specific business use case. A standout feature of this utility is its ability to leverage embeddings and a vector database for advanced functionality.
The utility employs Pinecone to store embeddings and uses ADA to transform documents into vector representations. It enables vector-based queries on the stored vectors within the Pinecone database. While other GenAI APIs, such as Chat Completion, can provide similar results, this utility enhances OutSystems applications by facilitating seamless adaptation to new implementations, delivering more precise and contextually relevant outcomes through its vector-based approach.
For example, Chat Completion is used to answer questions related to selected resumes. By utilizing ADA and Pinecone, the utility analyzes queries against a collection of documents, returning the top-ranked documents that best match the query, ensuring high accuracy and relevance.
Process Flow
Workflow
Storing Resumes (Documents):
Documents are summarized using Generative AI, then processed with ADA Embeddings to generate vectors, which are subsequently stored in Pinecone.
Query Matching:
A query is converted into a vector format and matched against the stored vectors in Pinecone.
The top-matching documents are retrieved and displayed.
Document Analysis and Comparison:
Users can analyze retrieved documents or compare two specific documents for deeper insights.
OpenAI's Chat Completion is used to generate detailed and context-aware outputs, such as answering specific questions about selected documents.
Key Features:
Text Embedding with ADA Connector: The app uses OpenAI's text-embedding-ada-002 model to transform the text from uploaded PDFs into embeddings. These embeddings capture the semantic meaning of the text, ensuring deep understanding and effective analysis.
Vector Management with Pinecone Connector: Pinecone is used to store, query, and manage the embeddings. This allows for fast and accurate retrieval of relevant information when users ask questions.
Q&A with OpenAI Chat Completion: The app integrates OpenAI’s Chat Completion API to interpret user queries and generate natural, human-like answers based on the document's content.
Benefits:
· Accurate Retrieval: The use of vector-based queries ensures precise and contextually relevant document retrieval.
· Versatility: Enables a wide range of use cases, such as resume filtering, document comparison, and advanced Q&A systems.
· Scalability: Supports efficient storage and querying for large volumes of documents.
· Adaptability: Allows OutSystems applications to easily integrate and leverage modern AI-powered solutions.
Pre-requisite
To use the Pinecone Utility application, complete the following steps:
Download Connectors from OutSystems Forge:
Xebia_ADA_Connector
Xebia_Pinecone_Connector
Xebia_OpenAI_ChatCompletionConnector
Configure API Keys:
Set up the required API keys in the connector settings to enable secure and seamless communication with the respective services.
Integrate Connectors:
Incorporate the connectors into your application workflows to utilize their functionalities effectively.
Use Cases:
Efficient Document Analysis: Quickly analyze lengthy documents like reports, research papers, or manuals by asking specific questions and retrieving targeted information.
Legal and Compliance: Simplify the review of contracts, policies, and legal documents by querying clauses or sections instead of manually scanning through them.
Academic Research: Assist researchers in extracting relevant insights from academic papers, study materials, or research notes.
Corporate Training and Onboarding: Make company handbooks or training materials easily searchable, helping employees quickly locate critical information.
Project Documentation: Retrieve specific details from complex project documents, architectural plans, or design guidelines without sifting through pages of content.