GenAI Stack (old)
v0.2.0
v0.2.0
  • Getting Started
    • 💬Introduction
    • 🚀Quickstart with colab
    • 📘Default Data Types
    • 🪛Installation
  • Components
    • ✨Introduction
    • 🚜ETL
      • 🔥Quickstart
      • 🦜Langchain
      • 🦙LLama Hub
    • 🌱Embeddings
      • 🔥Quickstart
      • 🦜Langchain
      • 📖Advanced Usage
    • 🔮Vector Database
      • 🔥Quickstart
      • 📦Chromadb
      • 📦Weaviate
      • 📖Advanced Usage
    • 📚Prompt Engine
      • 🔥Quickstart
      • 📖Advanced Usage
    • 📤Retrieval
      • 🔥Quickstart
      • 📖Advanced Usage
    • ️️️🗃️ LLM Cache
      • 🔥Quickstart
    • 📦Memory
      • 🔥Quickstart
      • 📖Advanced Usage
    • 🦄LLMs
      • OpenAI
      • GPT4All
      • Hugging Face
      • Custom Model
  • Advanced Guide
    • 💻GenAI Stack API Server
    • 🔃GenAI Server API's Reference
  • Example Use Cases
    • 💬Chat on PDF
    • 💬Chat on CSV
    • 💬Similarity Search on JSON
    • 📖Document Search
    • 💬RAG pipeline
    • 📚Information Retrieval Pipeline
  • 🧑CONTRIBUTING.md
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  1. Components
  2. Vector Database

Advanced Usage

Search Options:

You can use different search options for different types of retrieval methods in any vectordb component given by genai stack.

==> Weaviate db

from genai_stack.vectordb.weaviate_db import Weaviate

weavaite_db = Weaviate.from_kwargs(
    url="http://localhost:8080/",
    index_name="Testing",
    text_key="test",
    search_method="max_marginal_relevance_search",
    search_options={"k": 2, "fetch_k": 10, "lambda_mult": 0.3},
)

==> Chromadb

from genai_stack.vectordb.chromadb import ChromaDB

chromadb = ChromaDB.from_kwargs(
    search_method="max_marginal_relevance_search", 
    search_options={"k": 2, "fetch_k": 10, "lambda_mult": 0.3}
)
PreviousWeaviateNextPrompt Engine

Last updated 1 year ago

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