andre/crewAI
1
0
Fork 0
mirror of https://github.com/crewAIInc/crewAI.git synced 2026-01-10 00:28:31 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Clean up the Google setup section (#2785)

Browse Source 
The Gemini & Vertex sections were conflated and a little hard to
distingush, so I have put them in separate sections.

Also added the latest 2.5 and 2.0 flash-lite models, and added a note
that Gemma models work too.

Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
This commit is contained in:
Mark McDonald
2025-05-09 00:24:38 +08:00
committed by GitHub
parent d3fc2b4477
commit 2c011631f9
1 changed files with 54 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files

60
docs/concepts/llms.mdx
View File

@@ -169,19 +169,55 @@ In this section, you'll find detailed examples that help you select, configure,
``` ```
</Accordion> </Accordion>
<Accordion title="Google"> <Accordion title="Google (Gemini API)">
Set the following environment variables in your `.env` file: Set your API key in your `.env` file. If you need a key, or need to find an
existing key, check [AI Studio](https://aistudio.google.com/apikey).
```toml Code ```toml .env
# Option 1: Gemini accessed with an API key.
# https://ai.google.dev/gemini-api/docs/api-key # https://ai.google.dev/gemini-api/docs/api-key
GEMINI_API_KEY=<your-api-key> GEMINI_API_KEY=<your-api-key>
# Option 2: Vertex AI IAM credentials for Gemini, Anthropic, and Model Garden.
# https://cloud.google.com/vertex-ai/generative-ai/docs/overview
``` ```
Get credentials from your Google Cloud Console and save it to a JSON file with the following code: Example usage in your CrewAI project:
```python Code
from crewai import LLM
llm = LLM(
model="gemini/gemini-2.0-flash",
temperature=0.7,
)
```
### Gemini models
Google offers a range of powerful models optimized for different use cases.
| Model | Context Window | Best For |
|--------------------------------|----------------|-------------------------------------------------------------------|
| gemini-2.5-flash-preview-04-17 | 1M tokens | Adaptive thinking, cost efficiency |
| gemini-2.5-pro-preview-05-06 | 1M tokens | Enhanced thinking and reasoning, multimodal understanding, advanced coding, and more |
| gemini-2.0-flash | 1M tokens | Next generation features, speed, thinking, and realtime streaming |
| gemini-2.0-flash-lite | 1M tokens | Cost efficiency and low latency |
| gemini-1.5-flash | 1M tokens | Balanced multimodal model, good for most tasks |
| gemini-1.5-flash-8B | 1M tokens | Fastest, most cost-efficient, good for high-frequency tasks |
| gemini-1.5-pro | 2M tokens | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |
The full list of models is available in the [Gemini model docs](https://ai.google.dev/gemini-api/docs/models).
### Gemma
The Gemini API also allows you to use your API key to access [Gemma models](https://ai.google.dev/gemma/docs) hosted on Google infrastructure.
| Model | Context Window |
|----------------|----------------|
| gemma-3-1b-it | 32k tokens |
| gemma-3-4b-it | 32k tokens |
| gemma-3-12b-it | 32k tokens |
| gemma-3-27b-it | 128k tokens |
</Accordion>
<Accordion title="Google (Vertex AI)">
Get credentials from your Google Cloud Console and save it to a JSON file, then load it with the following code:
```python Code ```python Code
import json import json
@@ -205,11 +241,15 @@ In this section, you'll find detailed examples that help you select, configure,
vertex_credentials=vertex_credentials_json vertex_credentials=vertex_credentials_json
) )
``` ```
Google offers a range of powerful models optimized for different use cases: Google offers a range of powerful models optimized for different use cases:
| Model | Context Window | Best For | | Model | Context Window | Best For |
|-----------------------|----------------|------------------------------------------------------------------| |--------------------------------|----------------|-------------------------------------------------------------------|
| gemini-2.0-flash-exp | 1M tokens | Higher quality at faster speed, multimodal model, good for most tasks | | gemini-2.5-flash-preview-04-17 | 1M tokens | Adaptive thinking, cost efficiency |
| gemini-2.5-pro-preview-05-06 | 1M tokens | Enhanced thinking and reasoning, multimodal understanding, advanced coding, and more |
| gemini-2.0-flash | 1M tokens | Next generation features, speed, thinking, and realtime streaming |
| gemini-2.0-flash-lite | 1M tokens | Cost efficiency and low latency |
| gemini-1.5-flash | 1M tokens | Balanced multimodal model, good for most tasks | | gemini-1.5-flash | 1M tokens | Balanced multimodal model, good for most tasks |
| gemini-1.5-flash-8B | 1M tokens | Fastest, most cost-efficient, good for high-frequency tasks | | gemini-1.5-flash-8B | 1M tokens | Fastest, most cost-efficient, good for high-frequency tasks |
| gemini-1.5-pro | 2M tokens | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration | | gemini-1.5-pro | 2M tokens | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |