From 41c1e4ca45d36c82c693869aaa41db1d1f48dc4c Mon Sep 17 00:00:00 2001
From: balabanovan530 <175+balabanovan530@noreply.localhost>
Date: Tue, 2 Jun 2026 11:17:28 +0000
Subject: [PATCH] Update README.md

---
 README.md | 39 ++++++++++++++++++++-------------------
 1 file changed, 20 insertions(+), 19 deletions(-)

diff --git a/README.md b/README.md
index 28f197f..a58d1d5 100644
--- a/README.md
+++ b/README.md
@@ -1,32 +1,33 @@
-# LangGraph Agent with Conversation Memory and User Confirmation
-
-## Installation
+# Agent CLI Tool
 
+## Установка
 ```bash
 python -m venv .venv
-source .venv/bin/activate   # on Windows use `.venv\Scripts\activate`
+source .venv/bin/activate  # Windows: .venv\Scripts\activate
 pip install -r requirements.txt
 ```
 
-## Environment Variables
-
-The agent uses the default OpenAI endpoint via `langchain`. If you want to override, set:
-
-- `OPENAI_API_KEY` – your OpenAI API key.
-- `OPENAI_BASE_URL` – custom base URL (e.g., for local Ollama).
-
-## Running the Agent
+## Конфигурация
+Для работы с локальной моделью (Ollama, LM Studio) укажите переменные окружения:
+```
+export OPENAI_API_KEY=ollama
+export OPENAI_BASE_URL=http://localhost:11434/v1
+```
+Если используете удалённый API, поменяйте `base_url` и `api_key` в `agent.py`.
 
+## Запуск
 ```bash
 python agent.py
 ```
 
-The script starts with an empty conversation history. The graph will:
-1. Retrieve memory (currently just echoes the existing history).
-2. Invoke a placeholder agent that would normally process the conversation.
-3. Prompt you to confirm each tool call via Rich console output.
-4. Continue execution after confirmation.
+## Пример
+```
+Добро пожаловать! Введите 'exit' для выхода.
 
-## Extending
+Вы: Какая погода в Казани сегодня?
+Tool call detected: get_price{'city': 'Казань', 'date': 'сегодня'}
+Разрешить? (Y/n): y
+Цена в Казань на сегодня: 1000₽
 
-Replace `agent_node` with real LangChain logic, add tools, and integrate an actual LLM model as needed.
\ No newline at end of file
+---
+```