Azure Cognitive Search Loader

pip install llama-index-readers-azcognitive-search

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

from llama_index.readers.azcognitive_search import 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.