schedule-llm-query

A Python package for processing natural language queries about event schedules (e.g., FOSDEM 2026) and extracting structured information like session times, locations, and descriptions using an LLM.

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📌 Overview

This package interprets user queries (e.g., "What talks are on Sunday afternoon?") and extracts structured schedule data using pattern matching. The LLM is guided by a system prompt to format responses in a predefined structure, ensuring consistent and reliable output for applications.

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🚀 Installation

pip install schedule-llm-query

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🔧 Usage

Basic Usage (Default LLM: ChatLLM7)

from schedule_llm_query import schedule_llm_query

response = schedule_llm_query(
    user_input="What talks are on Sunday afternoon?",
    api_key="your_llm7_api_key"  # Optional (falls back to env var LLM7_API_KEY)
)
print(response)

Custom LLM Integration

You can replace the default ChatLLM7 with any LangChain-compatible LLM (e.g., OpenAI, Anthropic, Google).

Example: Using OpenAI

from langchain_openai import ChatOpenAI
from schedule_llm_query import schedule_llm_query

llm = ChatOpenAI()
response = schedule_llm_query(
    user_input="Show me all Python talks on Saturday",
    llm=llm
)
print(response)

Example: Using Anthropic

from langchain_anthropic import ChatAnthropic
from schedule_llm_query import schedule_llm_query

llm = ChatAnthropic()
response = schedule_llm_query(
    user_input="List all keynote sessions",
    llm=llm
)
print(response)

Example: Using Google Generative AI

from langchain_google_genai import ChatGoogleGenerativeAI
from schedule_llm_query import schedule_llm_query

llm = ChatGoogleGenerativeAI()
response = schedule_llm_query(
    user_input="What are the talks at Hall 1?",
    llm=llm
)
print(response)

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🔑 API Key

• Default LLM: Uses ChatLLM7 (from langchain_llm7).
• Free Tier: Sufficient for most use cases (rate limits apply).
• Custom Key: Pass via api_key parameter or LLM7_API_KEY environment variable.

  schedule_llm_query(user_input="...", api_key="your_api_key")
  

• Get a Key: Register at llm7.io.

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📝 Parameters

Parameter	Type	Description
user_input	str	The natural language query to process (e.g., "What talks are on Sunday?").
api_key	Optional[str]	LLM7 API key (optional if using env var or custom LLM).
llm	Optional[BaseChatModel]	Custom LangChain LLM (e.g., ChatOpenAI). Falls back to ChatLLM7 if None.

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🔄 Output Structure

The package returns structured data matching the regex pattern:

[
  {
    "title": "Talk Title",
    "time": "14:00-15:30",
    "location": "Hall 2",
    "description": "Brief description..."
  }
]

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📦 Dependencies

• langchain-core (for LLM integration)
• langchain_llm7 (default LLM, optional for custom LLM)
• llmatch (for pattern extraction)

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📜 License

MIT

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📢 Support & Issues

For bugs/feature requests, open an issue on GitHub.

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👤 Author

Eugene Evstafev 📧 hi@euegne.plus 🔗 LinkedIn

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