LlamaIndex

pip install reminix[runtime,llamaindex]

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from reminix.adapters.llamaindex import from_query_engine
from reminix.runtime import serve

# Load and index documents
documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)

# Create QueryEngine and wrap it
query_engine = index.as_query_engine()
agent = from_query_engine(query_engine, name="docs-qa")

serve(agent)

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from reminix.adapters.llamaindex import from_chat_engine
from reminix.runtime import serve

documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)

# Create ChatEngine for conversations
chat_engine = index.as_chat_engine(chat_mode="condense_question")
agent = from_chat_engine(chat_engine, name="docs-chat")

serve(agent)

from llama_index.core.agent import ReActAgent
from llama_index.core.tools import FunctionTool
from llama_index.llms.openai import OpenAI
from reminix.adapters.llamaindex import from_agent
from reminix.runtime import serve

# Define tools
def multiply(a: int, b: int) -> int:
    return a * b

multiply_tool = FunctionTool.from_defaults(fn=multiply)

# Create agent
llm = OpenAI(model="gpt-4o")
react_agent = ReActAgent.from_tools([multiply_tool], llm=llm)

# Wrap and serve
agent = from_agent(react_agent, name="calculator")
serve(agent)