What AI models does the agent use?

The agent has access to Claude, DeepSeek, Gemini, and other top models. It automatically routes to the best model for each task — you never have to think about API keys or token limits.

Yes. Each agent runs in an isolated environment. We don't train on your data, and you can export or delete everything at any time. The underlying engine (GoGogot) is open-source, so you can audit exactly how it works.

What can the agent actually do?

Browse the web, process files (CSV, PDF, images), run scheduled tasks, remember context across sessions, and communicate via Telegram or Slack. Think of it as a capable junior employee, not a chatbot.

How does memory work?

The agent maintains persistent memory across sessions. It remembers your preferences, past conversations, and task context. You can also explicitly tell it to remember or forget things.

Can I self-host the agent?

Absolutely. GoGogot is 100% open-source. Run it on your own hardware for free. cowork.ink is the managed version — we handle servers, model costs, updates, and uptime so you don't have to.

Is there a free trial?

We offer a 7-day money-back guarantee. Spin up an agent, give it real tasks, and if it doesn't save you time, we'll refund you — no questions asked.

How many lines of code does a basic AI agent need?

A minimal AI agent in Python needs about 50–80 lines of code. You need an LLM connection, a tool registry, and an agent loop. See our [full tutorial](/blog/build-ai-agent-python/) for working code.

What is the best Python framework for building AI agents?

It depends on your use case. LangGraph is best for complex stateful workflows, CrewAI excels at multi-agent collaboration, and the OpenAI Agents SDK offers the fastest prototyping. For learning, start without a framework to understand the fundamentals. Compare options in our [framework comparison](/blog/ag2-vs-crewai-vs-langgraph-openai-agents-sdk/).

Can I build an AI agent without using LangChain?

Yes. Most LLM providers (OpenAI, Anthropic, Google) offer tool-calling APIs that let you build agents with just their Python SDK. Frameworks add convenience but are not required. Learn about [tool calling](/blog/ai-agent-tool-calling/) fundamentals first.

What is the agent loop in AI agents?

The agent loop is the core execution cycle where an AI agent thinks, decides whether to call a tool, observes the result, and repeats until the task is complete. It is the pattern that separates agents from simple chatbots. Read more about [how AI agents work](/blog/ai-agents-explained/).

How much does it cost to run a Python AI agent?

Costs depend on the LLM provider. A single agent session costs roughly $0.01–0.05 with GPT-4o or Claude Sonnet, and as low as $0.002 with DeepSeek. Check our [AI API pricing comparison](/blog/ai-api-pricing-comparison/) for current rates.

Build an AI Agent in Python: Complete Tutorial with Code

Build an AI agent in Python with COMPLETE code examples. From scratch or with frameworks — tool calling, memory, agent loop. Start building now.

Frequently Asked Questions

How many lines of code does a basic AI agent need?: A minimal AI agent in Python needs about 50–80 lines of code. You need an LLM connection, a tool registry, and an agent loop. See our [full tutorial](/blog/build-ai-agent-python/) for working code.
What is the best Python framework for building AI agents?: It depends on your use case. LangGraph is best for complex stateful workflows, CrewAI excels at multi-agent collaboration, and the OpenAI Agents SDK offers the fastest prototyping. For learning, start without a framework to understand the fundamentals. Compare options in our [framework comparison](/blog/ag2-vs-crewai-vs-langgraph-openai-agents-sdk/).
Can I build an AI agent without using LangChain?: Yes. Most LLM providers (OpenAI, Anthropic, Google) offer tool-calling APIs that let you build agents with just their Python SDK. Frameworks add convenience but are not required. Learn about [tool calling](/blog/ai-agent-tool-calling/) fundamentals first.
What is the agent loop in AI agents?: The agent loop is the core execution cycle where an AI agent thinks, decides whether to call a tool, observes the result, and repeats until the task is complete. It is the pattern that separates agents from simple chatbots. Read more about [how AI agents work](/blog/ai-agents-explained/).
How much does it cost to run a Python AI agent?: Costs depend on the LLM provider. A single agent session costs roughly $0.01–0.05 with GPT-4o or Claude Sonnet, and as low as $0.002 with DeepSeek. Check our [AI API pricing comparison](/blog/ai-api-pricing-comparison/) for current rates.