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Author SHA1 Message Date
Greyson LaLonde
4b2d5633c1 chore: add commitizen to pre-commit hooks 2025-07-09 09:35:02 -04:00
5 changed files with 7 additions and 238 deletions

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@@ -5,3 +5,7 @@ repos:
- id: ruff
args: ["--fix"]
- id: ruff-format
- repo: https://github.com/commitizen-tools/commitizen
rev: v3.13.0
hooks:
- id: commitizen

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@@ -311,47 +311,20 @@ In this section, you'll find detailed examples that help you select, configure,
</Accordion>
<Accordion title="AWS Bedrock">
Amazon Bedrock supports two authentication methods:
**Method 1: IAM Role Authentication (Recommended for Production)**
```toml Code
AWS_ACCESS_KEY_ID=<your-access-key>
AWS_SECRET_ACCESS_KEY=<your-secret-key>
AWS_DEFAULT_REGION=<your-region>
```
**Method 2: API Key Authentication (Recommended for Development)**
```toml Code
AWS_BEARER_TOKEN_BEDROCK=<your-api-key>
AWS_DEFAULT_REGION=<your-region>
```
Example usage in your CrewAI project:
```python Code
# Method 1: IAM Role Authentication (uses AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY)
# Set environment variables: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION
llm = LLM(
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
)
# Method 2: API Key Authentication (uses AWS_BEARER_TOKEN_BEDROCK)
# Set environment variables: AWS_BEARER_TOKEN_BEDROCK, AWS_DEFAULT_REGION
llm = LLM(
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
)
```
**Requirements:**
- Before using Amazon Bedrock, make sure you have boto3 v1.393+ installed in your environment
- For API key authentication, you can generate a 30-day API key from the [Amazon Bedrock console](https://console.aws.amazon.com/bedrock/)
- For production applications, use IAM roles or temporary credentials instead of long-term API keys
**Security Best Practices:**
- API keys expire after 30 days and should be rotated regularly
- Use IAM roles for production environments for better security
- Store API keys securely and never commit them to version control
- Monitor API usage and set up alerts for unusual activity
- Consider using temporary credentials for enhanced security
Before using Amazon Bedrock, make sure you have boto3 installed in your environment
[Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html) is a managed service that provides access to multiple foundation models from top AI companies through a unified API, enabling secure and responsible AI application development.

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@@ -309,47 +309,20 @@ Nesta seção, você encontrará exemplos detalhados que ajudam a selecionar, co
</Accordion>
<Accordion title="AWS Bedrock">
O Amazon Bedrock suporta dois métodos de autenticação:
**Método 1: Autenticação por Função IAM (Recomendado para Produção)**
```toml Code
AWS_ACCESS_KEY_ID=<your-access-key>
AWS_SECRET_ACCESS_KEY=<your-secret-key>
AWS_DEFAULT_REGION=<your-region>
```
**Método 2: Autenticação por Chave de API (Recomendado para Desenvolvimento)**
```toml Code
AWS_BEARER_TOKEN_BEDROCK=<your-api-key>
AWS_DEFAULT_REGION=<your-region>
```
Exemplo de uso em seu projeto CrewAI:
```python Code
# Método 1: Autenticação por Função IAM (usa AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY)
# Configure as variáveis de ambiente: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION
llm = LLM(
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
)
# Método 2: Autenticação por Chave de API (usa AWS_BEARER_TOKEN_BEDROCK)
# Configure as variáveis de ambiente: AWS_BEARER_TOKEN_BEDROCK, AWS_DEFAULT_REGION
llm = LLM(
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
)
```
**Requisitos:**
- Antes de usar o Amazon Bedrock, certifique-se de ter o boto3 v1.393+ instalado em seu ambiente
- Para autenticação por chave de API, você pode gerar uma chave de 30 dias no [console do Amazon Bedrock](https://console.aws.amazon.com/bedrock/)
- Para aplicações de produção, use funções IAM ou credenciais temporárias em vez de chaves de API de longo prazo
**Melhores Práticas de Segurança:**
- Chaves de API expiram após 30 dias e devem ser rotacionadas regularmente
- Use funções IAM para ambientes de produção para melhor segurança
- Armazene chaves de API com segurança e nunca as confirme no controle de versão
- Monitore o uso da API e configure alertas para atividades incomuns
- Considere usar credenciais temporárias para segurança aprimorada
Antes de usar o Amazon Bedrock, certifique-se de ter o boto3 instalado em seu ambiente
[Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/models-regions.html) é um serviço gerenciado que fornece acesso a múltiplos modelos fundamentais dos principais provedores de IA através de uma API unificada, permitindo o desenvolvimento seguro e responsável de aplicações de IA.
@@ -908,4 +881,4 @@ Saiba como obter o máximo da configuração do seu LLM:
llm = LLM(model="openai/gpt-4o") # 128K tokens
```
</Tab>
</Tabs>
</Tabs>

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@@ -62,10 +62,6 @@ ENV_VARS = {
"prompt": "Enter your AWS Region Name (press Enter to skip)",
"key_name": "AWS_REGION_NAME",
},
{
"prompt": "Enter your AWS Bedrock API Key (30-day key from AWS console, press Enter to skip)",
"key_name": "AWS_BEARER_TOKEN_BEDROCK",
},
],
"azure": [
{

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@@ -1,177 +0,0 @@
import os
import pytest
from unittest.mock import patch, MagicMock
from crewai import LLM
class TestBedrockAuthentication:
"""Test AWS Bedrock authentication methods."""
@patch.dict(os.environ, {
'AWS_ACCESS_KEY_ID': 'test-key-id',
'AWS_SECRET_ACCESS_KEY': 'test-secret-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_iam_authentication(self, mock_completion):
"""Test Bedrock with IAM role authentication."""
mock_completion.return_value = MagicMock()
mock_completion.return_value.choices = [MagicMock()]
mock_completion.return_value.choices[0].message.content = "Test response"
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
result = llm.call("test message")
mock_completion.assert_called_once()
assert result == "Test response"
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_api_key_authentication(self, mock_completion):
"""Test Bedrock with API key authentication."""
mock_completion.return_value = MagicMock()
mock_completion.return_value.choices = [MagicMock()]
mock_completion.return_value.choices[0].message.content = "Test response"
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
result = llm.call("test message")
mock_completion.assert_called_once()
assert result == "Test response"
def test_bedrock_missing_credentials(self):
"""Test Bedrock fails gracefully with missing credentials."""
with patch.dict(os.environ, {}, clear=True):
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
assert llm.model == "bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_api_key_with_streaming(self, mock_completion):
"""Test Bedrock API key authentication with streaming."""
mock_completion.return_value = iter([
MagicMock(choices=[MagicMock(delta=MagicMock(content="Test"))]),
MagicMock(choices=[MagicMock(delta=MagicMock(content=" response"))])
])
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
result = list(llm.stream("test message"))
mock_completion.assert_called_once()
assert len(result) == 2
@patch.dict(os.environ, {
'AWS_ACCESS_KEY_ID': 'test-key-id',
'AWS_SECRET_ACCESS_KEY': 'test-secret-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_iam_with_custom_parameters(self, mock_completion):
"""Test Bedrock IAM authentication with custom parameters."""
mock_completion.return_value = MagicMock()
mock_completion.return_value.choices = [MagicMock()]
mock_completion.return_value.choices[0].message.content = "Test response"
llm = LLM(
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
temperature=0.7,
max_tokens=100
)
result = llm.call("test message")
mock_completion.assert_called_once()
call_args = mock_completion.call_args
assert call_args[1]['temperature'] == 0.7
assert call_args[1]['max_tokens'] == 100
assert result == "Test response"
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-west-2'
})
@patch('litellm.completion')
def test_bedrock_api_key_different_region(self, mock_completion):
"""Test Bedrock API key authentication with different region."""
mock_completion.return_value = MagicMock()
mock_completion.return_value.choices = [MagicMock()]
mock_completion.return_value.choices[0].message.content = "Test response"
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
result = llm.call("test message")
mock_completion.assert_called_once()
assert result == "Test response"
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_timeout_handling(self, mock_completion):
"""Test Bedrock API timeout handling."""
mock_completion.side_effect = TimeoutError("Request timed out")
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
with pytest.raises(TimeoutError, match="Request timed out"):
llm.call("test message")
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_rate_limit_handling(self, mock_completion):
"""Test Bedrock API rate limit handling."""
mock_completion.side_effect = Exception("Rate limit exceeded")
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
with pytest.raises(Exception, match="Rate limit exceeded"):
llm.call("test message")
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'invalid-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_invalid_api_key(self, mock_completion):
"""Test Bedrock with invalid API key."""
mock_completion.side_effect = Exception("Invalid API key")
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
with pytest.raises(Exception, match="Invalid API key"):
llm.call("test message")
@patch.dict(os.environ, {
'AWS_ACCESS_KEY_ID': 'test-key-id',
'AWS_SECRET_ACCESS_KEY': 'test-secret-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_connection_error(self, mock_completion):
"""Test Bedrock with connection error."""
mock_completion.side_effect = ConnectionError("Connection failed")
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
with pytest.raises(ConnectionError, match="Connection failed"):
llm.call("test message")
@patch.dict(os.environ, {
'AWS_BEARER_TOKEN_BEDROCK': 'test-api-key',
'AWS_DEFAULT_REGION': 'us-east-1'
})
@patch('litellm.completion')
def test_bedrock_api_key_with_retry_scenario(self, mock_completion):
"""Test Bedrock API key authentication with retry scenario."""
mock_completion.side_effect = [
Exception("Temporary error"),
MagicMock(choices=[MagicMock(message=MagicMock(content="Success after retry"))])
]
llm = LLM(model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0")
with pytest.raises(Exception, match="Temporary error"):
llm.call("test message")