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AI & LLM integration patterns

Call LLM APIs, structure prompts, parse responses, and ship AI features safely.

5 matches

How to Build a System-User-Assistant Message List in Python

Use dataclasses to model a chat conversation and build the system/user/assistant message list expected by LLM APIs.

from dataclasses import dataclass, field
from typing import List


@dataclass
class Message:
    role: str
    content: str


@dataclass
class Conversation:
    messages: List[Message] = field(default_factory=list)

    def add_system(self, content: str) -> None:
        self.messages.append(Message(role="system", con…

12 0 Open

AI & LLM integration patterns easy

How to Mock OpenAI Tool Call Messages in Python

Create an assistant message with a function tool call in OpenAI's chat format, useful for testing and mocking.

openai tool-calls mock

Python

from openai import OpenAI


def mock_tool_call(tool_name: str, arguments: dict) -> dict:
    """Simulate a tool call message in OpenAI style."""
    return {
        "role": "assistant",
        "content": None,
        "tool_calls": [
            {
                "id": "call_" + "a1b2c3d4e5f6",
                "type…

14 0 Open

AI & LLM integration patterns easy

How to Serialize Chat Messages to a JSON File in Python

Writes a list of chat message dicts to a JSON file with metadata like export time and message count.

json serialization chat

Python

import json
from pathlib import Path
from datetime import datetime

def serialize_messages(messages, output_path):
    data = {
        "exported_at": datetime.now().isoformat(),
        "count": len(messages),
        "messages": messages
    }
    Path(output_path).write_text(
        json.dumps(data, indent=2, ensu…

16 0 Open

AI & LLM integration patterns easy

How to Validate JSON Output Against a Dict Schema in Python

Validate JSON-like data against a simple dict schema with type checking and descriptive error messages using only the Python standard library.

json validation schema

Python

from typing import Dict, Any, List, Union

def validate_json(data: Any, schema: Dict[str, str]) -> List[str]:
    """
    Validate JSON-like data against a simple dict schema.
    Schema format: {field_name: expected_type} where type is one of:
    'str', 'int', 'float', 'bool', 'list', 'dict', 'any'
    Returns list …

13 0 Open

AI & LLM integration patterns easy

How to randomly assign a prompt variant to each key in Python

Randomly pick one variant from a list for each prompt key, useful for A/B testing message variations.

random dictionary a/b-testing

Python

import random

def assign_prompt_variant(prompts: dict[str, list[str]]) -> dict[str, str]:
    """Assign a random prompt variant to each prompt key."""
    return {key: random.choice(variants) for key, variants in prompts.items()}

if __name__ == "__main__":
    prompt_bank = {
        "greeting": ["Hello!", "Hi there…

14 0 Open

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