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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 Keep Last K Turns in a Memory Buffer in Python

A TurnBuffer class using deque with maxlen to keep only the most recent k conversation turns in memory for LLM context.

deque llm-context memory-buffer

Python

from collections import deque

class TurnBuffer:
    def __init__(self, k):
        self.k = k
        self.turns = deque(maxlen=k)

    def add(self, turn):
        self.turns.append(turn)

    def last_k(self):
        return list(self.turns)


if __name__ == "__main__":
    buffer = TurnBuffer(3)
    buffer.add("tu…

14 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 Parse Chat Completion JSON in Python

Parse a mock OpenAI chat completion JSON response into a clean dictionary with content, finish reason, and model.

json openai chat-completion

Python

import json

def parse_chat_response(raw: str) -> dict:
    data = json.loads(raw)
    choice = data["choices"][0]
    return {
        "content": choice["message"]["content"],
        "finish_reason": choice["finish_reason"],
        "model": data["model"],
    }

if __name__ == "__main__":
    mock_response = '''
  …

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

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