llama-index-readers-azcognitive-search 0.1.3

llama-index readers azcognitive_search integration

Azure Cognitive Search Loader

The AzCognitiveSearchReader Loader returns a set of texts corresponding to documents retrieved from specific index of Azure Cognitive Search. The user initializes the loader with credentials (service name and key) and the index name.

Usage

Here's an example usage of the AzCognitiveSearchReader.

from llama_index import download_loader

AzCognitiveSearchReader = download_loader("AzCognitiveSearchReader")

reader = AzCognitiveSearchReader(
    "<Azure_Cognitive_Search_NAME>",
    "<Azure_Cognitive_Search_KEY>",
    "<Index_name>",
)


query_sample = ""
documents = reader.load_data(
    query="<search_term>",
    content_field="<content_field_name>",
    filter="<azure_search_filter>",
)

Usage in combination with langchain

from llama_index import VectorStoreIndex, download_loader
from langchain.chains.conversation.memory import ConversationBufferMemory
from langchain.agents import Tool, AgentExecutor, load_tools, initialize_agent

AzCognitiveSearchReader = download_loader("AzCognitiveSearchReader")

az_loader = AzCognitiveSearchReader(
    COGNITIVE_SEARCH_SERVICE_NAME, COGNITIVE_SEARCH_KEY, INDEX_NAME
)

documents = az_loader.load_data(query, field_name)

index = VectorStoreIndex.from_documents(
    documents, service_context=service_context
)

tools = [
    Tool(
        name="Azure cognitive search index",
        func=lambda q: index.query(q),
        description=f"Useful when you want answer questions about the text on azure cognitive search.",
    ),
]
memory = ConversationBufferMemory(memory_key="chat_history")
agent_chain = initialize_agent(
    tools, llm, agent="zero-shot-react-description", memory=memory
)

result = agent_chain.run(input="How can I contact with my health insurance?")

This loader is designed to be used as a way to load data into LlamaIndex and/or subsequently used as a Tool in a LangChain Agent. See here for examples.