cognee/docs/ko/getting-started/installation.md
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# Installation
> Set up your environment and install Cognee
Set up your environment and install Cognee to start building AI memory.
<Info>
Python **3.9 3.12** is required to run Cognee.
</Info>
## Prerequisites
<AccordionGroup>
<Accordion title="Environment Configuration">
* We recommend creating a `.env` file in your project root
* Cognee supports many configuration options, and a `.env` file keeps them organized
</Accordion>
<Accordion title="API Keys & Models">
You have two main options for configuring LLM and embedding providers:
**Option 1: OpenAI (Simplest)**
* Single API key handles both LLM and embeddings
* Uses gpt-4o-mini for LLM and text-embedding-3-small for embeddings by default
* Works out of the box with minimal configuration
**Option 2: Other Providers**
* Configure both LLM and embedding providers separately
* Supports Gemini, Anthropic, Ollama, and more
* Requires setting both `LLM_*` and `EMBEDDING_*` variables
<Info>
By default, Cognee uses OpenAI for both LLMs and embeddings. If you change the LLM provider but don't configure embeddings, it will still default to OpenAI.
</Info>
</Accordion>
<Accordion title="Virtual Environment">
* We recommend using [uv](https://github.com/astral-sh/uv) for virtual environment management
* Run the following commands to create and activate a virtual environment:
```bash theme={null}
uv venv && source .venv/bin/activate
```
</Accordion>
<Accordion title="Optional">
<AccordionGroup>
<Accordion title="Database">
* PostgreSQL database is required if you plan to use PostgreSQL as your relational database (requires `postgres` extra)
</Accordion>
</AccordionGroup>
</Accordion>
</AccordionGroup>
## Setup
<Tabs>
<Tab title="OpenAI (Recommended)">
<Card>
**Environment:** Add your OpenAI API key to your `.env` file:
```bash theme={null}
LLM_API_KEY="your_openai_api_key"
```
**Installation:** Install Cognee with all extras:
```bash theme={null}
uv pip install cognee
```
**What this gives you**: Cognee installed with default local databases (SQLite, LanceDB, Kuzu) — no external servers required.
<Info>
This single API key handles both LLM and embeddings. We use gpt-4o-mini for the LLM model and text-embedding-3-small for embeddings by default.
</Info>
</Card>
</Tab>
<Tab title="Other Providers (Gemini, Anthropic, etc.)">
<Card>
**Environment:** Configure both LLM and embedding providers in your `.env` file. Here is an example for Gemini:
```bash theme={null}
# LLM
LLM_PROVIDER="gemini"
LLM_MODEL="gemini/gemini-flash-latest"
LLM_API_KEY="your_gemini_api_key"
# Embeddings
EMBEDDING_PROVIDER="gemini"
EMBEDDING_MODEL="gemini/text-embedding-004"
EMBEDDING_API_KEY="your_gemini_api_key"
```
<Info>
Make sure to configure both LLM and embedding settings. If you only set one, the other will default to OpenAI.
</Info>
**Installation:** Install Cognee with provider-specific extras (`gemini`, `anthropic`, `ollama`, `mistral`, `huggingface`, or `groq`) for example:
```bash theme={null}
uv pip install cognee[gemini]
```
**What this gives you**: Cognee installed with your chosen providers and default local databases.
For detailed configuration options, see our [LLM](/setup-configuration/llm-providers) and [Embeddings](/setup-configuration/embedding-providers) guides.
</Card>
</Tab>
</Tabs>
## Next Steps
<CardGroup cols={2}>
<Card title="Run Your First Example" href="/getting-started/quickstart" icon="play">
**Quickstart Tutorial**
Get started with Cognee by running your first knowledge graph example.
</Card>
<Card title="Explore Advanced Features" href="/core-concepts" icon="compass">
**Core Concepts**
Dive deeper into Cognee's powerful features and capabilities.
</Card>
</CardGroup>
---
> To find navigation and other pages in this documentation, fetch the llms.txt file at: https://docs.cognee.ai/llms.txt