Langroid

pip install langroid[seltz]

import langroid as lr
from langroid.agent.tools.seltz_search_tool import SeltzSearchTool

# Create an agent with Seltz search
config = lr.ChatAgentConfig(
    name="Searcher",
    llm=lr.language_models.OpenAIGPTConfig(
        chat_model="gpt-4o",
    ),
)
agent = lr.ChatAgent(config)
agent.enable_message(SeltzSearchTool)

# Run a task
task = lr.Task(agent, interactive=False)
task.run("What are the latest developments in AI?")

export SELTZ_API_KEY="your-api-key"

import typer
from dotenv import load_dotenv

import langroid as lr
import langroid.language_models as lm
from langroid.agent.tools.seltz_search_tool import SeltzSearchTool

load_dotenv()

llm_config = lm.OpenAIGPTConfig(
    chat_model=lm.OpenAIChatModel.GPT4o,
    chat_context_length=32_000,
    temperature=0.15,
    max_output_tokens=1000,
    timeout=45,
)

search_tool_handler_method = SeltzSearchTool.name()
config = lr.ChatAgentConfig(
    name="Seeker",
    llm=llm_config,
    system_message=f"""
    You are a helpful assistant. You will try your best to answer my questions.
    - If my question is about a topic you are certain about, answer it directly.
    - Otherwise, use the `{search_tool_handler_method}` tool to search the web.
    - When answering from search results, cite your sources.
    """,
)
agent = lr.ChatAgent(config)
agent.enable_message(SeltzSearchTool)

task = lr.Task(agent, interactive=False)
task.run("What are the latest breakthroughs in quantum computing?")

python3 examples/basic/chat-search.py -p seltz

python3 examples/basic/chat-search-seltz.py

User Query → LLM Agent → SeltzSearchTool → Seltz API → Results → LLM Response