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README.md

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-# task-6a1865008a94f887e50d471c
+# Structured Output Extraction with LangChain & Pydantic
 
-Экзамен: Структурированный вывод (Pydantic)
+This repository demonstrates how to extract structured data from free‑form text using **LangChain** and **Pydantic**. Two schemas are supported:
+
+1. **PersonInfo** – name, optional age, profession, skills.
+2. **MeetingNotes** – date, participants, topics, decisions, next steps.
+
+The extraction is performed in a single LLM call with a prompt that includes the JSON schema. The result is parsed into a validated Pydantic model.
+
+## Requirements
+
+```text
+langchain>=1.0.0
+langchain-openai>=0.0.0
+pydantic>=2.0.0
+python-dotenv
+```
+
+Install with:
+
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+
+```bash
+# Person example
+python main.py "Анна, 28 лет, Python-разработчик. Навыки: FastAPI, Docker."
+
+# Meeting example
+python main.py "Meeting on 2024-10-01. Participants: Alice, Bob. Topics: Budget, Timeline. Decisions: Increase budget. Next steps: Prepare report."
+```
+
+The script will automatically detect the type of text and output the parsed Pydantic model.
+
+## Running from the CLI
+
+You can also run the script interactively:
+
+```bash
+python main.py
+Enter text (or press Ctrl-D to exit):
+Анна, 28 лет, Python-разработчик. Навыки: FastAPI, Docker.
+```
+
+## License
+
+MIT