A collection of Haystack-powered projects based on Advent of Haystack. View my original solutions here.
Haystack is an open-source framework by deepset for building:
- Production-ready LLM applications
- Retrieval-augmented generative pipelines
- State-of-the-art search systems for large document collections
This repository contains 10 projects demonstrating pipeline building with Haystack and integrations with:
- Weaviate - Vector Database
- AssemblyAI - Speech AI
- NVIDIA - GPU Computing
- Arize - ML Observability
- MongoDB - Document Database
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: Jupyter notebooks containing experiments and implementations
- Fetches content from URLs
- Ranks documents by relevance
- Identifies top 10 relevant documents
- Enables seamless querying and answering
- Implements Retrieval-Augmented Generation with vector database
- Combines vector search with structured filtering
- Stores both objects and vectors efficiently
- Implements custom Haystack component
- Generates multiple queries from single input
- Handles parallel query processing
- Integrates AssemblyAI for speech processing
- Performs speech-to-text conversion
- Enables speaker diarization
- Generates responses based on transcriptions
- Utilizes UI-based interface of deepset Studio for pipeline creation
- Leverages deployment tools and templates
- Integrates with NVIDIA inference microservices for ranking and embeddings
- Implements task delegation optimization
- Enables multilingual embedding document grouping
- Creates personalized toy recommendations
- Integrates Arize Phoenix for:
- Real-time performance tracking
- LLM response evaluation
- Trace data visualization
- Quality monitoring dashboards
- Implements automated evaluation pipeline
- Manages inventory tracking system
- Implements RAG-based web search
- Provides price checking functionality
- Enables CRUD operations on inventory
- Uses DuckDuckGo integration for web search
- Leverages MongoDB Atlas vector search capabilities
- Enhances semantic search using OpenAI embeddings
- Generates personalized gift recommendations via GPT models
- Implements advanced reasoning with self-reflection
- Streamlines gift metadata management and organization
- Uses HotpotQA dataset for testing
- Implements multiple evaluation metrics
- Integrates with Hugging Face and OpenAI
- Provides comprehensive pipeline assessment
- Enables model comparison and parameter tuning