Strongly Typed AI Pipelines - Redpanda Connect
TLDRThis demo showcases Redpanda Connect's integration with OpenAI, highlighting new features like structured output support using JSON schema. It demonstrates how to create a data pipeline that processes emails by pulling schemas from Redpanda's registry, ensuring outputs adhere to specified formats. The pipeline categorizes emails and extracts sender information, allowing for centralized management of schemas. As emails flow through the system, their enriched versions—categorized and complete with sender details—are produced, illustrating the simplicity of building robust data pipelines with Redpanda Connect.
Takeaways
- 📊 Redpanda Connect now integrates with OpenAI, enabling text generation via its APIs.
- 📝 New structured output support ensures LLM responses adhere to specified JSON schemas.
- 📜 Redpanda's schema registry allows centralized management and updates of data schemas.
- 📧 The demo pipeline processes emails from a topic, categorizing them based on their content.
- 🔄 Emails are formatted as simple JSON objects containing an email field.
- 🔍 The OpenAI processor categorizes emails and extracts sender information.
- 📈 The output structure is enriched with categories and senders as defined by the schema.
- ⚙️ Users can dynamically fetch schemas from the registry or use fixed schemas in pipelines.
- 🧪 The pipeline verifies schema adherence, even if the prompt format is incorrect.
- 🎉 Running the pipeline demonstrates its efficiency in categorizing emails accurately.
Q & A
What is Redpanda Connect?
-Redpanda Connect is a platform that facilitates the creation of data pipelines, integrating features from Redpanda and OpenAI.
What new feature has been added to Redpanda Connect?
-Redpanda Connect has introduced an OpenAI processor that allows for text generation using OpenAI's APIs and structured outputs based on JSON schema.
How does Redpanda Connect ensure the compliance of outputs with schemas?
-It ensures compliance by allowing users to specify a JSON schema that the language model's output must adhere to.
What role does the schema registry play in this process?
-The schema registry provides centralized management and updates for schemas, ensuring that data pipelines use consistent and valid schemas.
Can users create their own schemas in Redpanda Connect?
-Yes, users can add fixed schemas within their pipelines or dynamically fetch schemas from the schema registry.
What is the purpose of categorizing emails in the pipeline?
-The categorization helps in organizing emails by their types, enabling easier processing and management of email data.
What kind of data does the pipeline extract from emails?
-The pipeline extracts the sender information and categorizes the email based on predefined categories.
What happens if the output format doesn't match the specified schema?
-The system is designed to adhere strictly to the schema provided, ensuring that even if the prompt specifies the wrong format, the output will conform to the schema.
What is demonstrated at the end of the pipeline run?
-The output shows categorized emails along with the extracted sender information, illustrating how the pipeline processes and enriches the original emails.
How does Redpanda Connect simplify the creation of data pipelines?
-Redpanda Connect allows users to easily spin up data pipelines with structured outputs, ensuring that data integrity is maintained at every stage.
Outlines
🐼 Red Panda Connect Demo with OpenAI
This paragraph introduces a demo of Red Panda Connect, highlighting its integration with OpenAI's capabilities. It discusses two new features: the OpenAI processor in Red Panda Connect, which can generate text using OpenAI's APIs, and the recent addition of support for structured outputs from the OpenAI API, allowing the specification of a JSON schema to ensure the output adheres to it. The paragraph also mentions Red Panda's announcement of support for JSON schema within its schema registry, which aids in centralized management and updates of schemas used in data pipelines. The demo showcases a pipeline that pulls schemas from Red Panda and uses them with OpenAI to categorize emails and extract sender information, all while ensuring the output conforms to the schema registered in the schema registry.
Mindmap
Keywords
💡Redpanda Connect
💡OpenAI Processor
💡Structured Outputs
💡JSON Schema
💡Schema Registry
💡Data Pipelines
💡Categorize Email
💡Magic Byte
💡Decode
💡Re-encode
💡Consumer
Highlights
Redpanda Connect integrates with OpenAI for text generation.
New support for structured outputs from OpenAI APIs using JSON schema.
Allows specification of a JSON schema to ensure LLM output adheres to it.
Recent announcements include JSON schema support in Redpanda's schema registry.
Demo showcases pulling schemas from Redpanda to ensure compliance in responses.
Centralized management of schemas enhances data pipeline reliability.
Example pipeline processes emails and categorizes them using AI.
Hand-generated emails are formatted in JSON schema for processing.
Output includes categorized email data with sender extraction.
Structured outputs ensure correct data format at every pipeline stage.
Demonstrates simple setup of data pipelines with Redpanda Connect.
Allows merging of dynamic and fixed schemas in the pipeline.
Shows real-time consumption of categorized email messages.
Categorization includes enum definitions for precise matching.
The demo highlights the flexibility of using a schema registry.
Effective categorization improves data organization and management.