Skip to main content
Glama

@arizeai/phoenix-mcp

Official
by Arize-ai
subquery.py1.14 kB
from datetime import datetime, timezone from llama_index.core.llms.llm import LLM from llama_index.core.prompts.base import PromptTemplate SUB_QUERY_PROMPT = PromptTemplate( "Write {max_iterations} google search queries to search online that form an objective opinion " 'from the following task: "{task}"\n' f"Assume the current date is {datetime.now(timezone.utc).strftime('%B %d, %Y')} if required.\n" "You must respond with the search queries separated by comma in the following format: query 1, " "query 2, query 3\n" "{max_iterations} google search queries for {task} (separated by comma): " ) async def get_sub_queries( query: str, llm: LLM, num_sub_queries: int = 3, ): """ Gets the sub queries Args: query: original query llm: LLM to generate sub queries Returns: sub_queries: List of sub queries """ response = await llm.apredict( SUB_QUERY_PROMPT, task=query, max_iterations=num_sub_queries, ) sub_queries = list(map(lambda x: x.strip().strip('"').strip("'"), response.split(","))) return sub_queries

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Arize-ai/phoenix'

If you have feedback or need assistance with the MCP directory API, please join our Discord server