Adding AWS Bedrock support as a LLM provider

Signed-off-by: xdurawa <xavierdurawa@gmail.com>
2025-09-01 20:47:26 -04:00 · 2025-09-01 20:47:26 -04:00 · 2a46208569
commit 2a46208569
parent bf482ef91f
15 changed files with 394 additions and 8 deletions
--- a/.github/workflows/test_bedrock_api_key.yml
+++ b/.github/workflows/test_bedrock_api_key.yml
@ -0,0 +1,28 @@
+name: test | bedrock | api key
+
+on:
+  workflow_call:
+
+jobs:
+  test-bedrock-api-key:
+    name: Run Bedrock API Key Test
+    runs-on: ubuntu-22.04
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Cognee Setup
+        uses: ./.github/actions/cognee_setup
+        with:
+          python-version: '3.11.x'
+
+      - name: Run Bedrock API Key Test
+        env:
+          LLM_PROVIDER: "bedrock"
+          LLM_API_KEY: ${{ secrets.BEDROCK_API_KEY }}
+          LLM_MODEL: "us.anthropic.claude-3-5-sonnet-20241022-v2:0"
+          AWS_REGION_NAME: "us-east-1"
+          EMBEDDING_PROVIDER: "bedrock"
+          EMBEDDING_MODEL: "amazon.titan-embed-text-v1"
+          EMBEDDING_DIMENSIONS: "1536"
+        run: poetry run python ./examples/python/simple_example.py
--- a/.github/workflows/test_bedrock_aws_credentials.yml
+++ b/.github/workflows/test_bedrock_aws_credentials.yml
@ -0,0 +1,29 @@
+name: test | bedrock | aws credentials
+
+on:
+  workflow_call:
+
+jobs:
+  test-bedrock-aws-credentials:
+    name: Run Bedrock AWS Credentials Test
+    runs-on: ubuntu-22.04
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Cognee Setup
+        uses: ./.github/actions/cognee_setup
+        with:
+          python-version: '3.11.x'
+
+      - name: Run Bedrock AWS Credentials Test
+        env:
+          LLM_PROVIDER: "bedrock"
+          LLM_MODEL: "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
+          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          AWS_REGION_NAME: "us-east-1"
+          EMBEDDING_PROVIDER: "cohere"
+          EMBEDDING_MODEL: "cohere.embed-english-v3"
+          EMBEDDING_DIMENSIONS: "1024"
+        run: poetry run python ./examples/python/simple_example.py
--- a/.github/workflows/test_bedrock_aws_profile.yml
+++ b/.github/workflows/test_bedrock_aws_profile.yml
@ -0,0 +1,37 @@
+name: test | bedrock | aws profile
+
+on:
+  workflow_call:
+
+jobs:
+  test-bedrock-aws-profile:
+    name: Run Bedrock AWS Profile Test
+    runs-on: ubuntu-22.04
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Cognee Setup
+        uses: ./.github/actions/cognee_setup
+        with:
+          python-version: '3.11.x'
+
+      - name: Configure AWS Profile
+        run: |
+          mkdir -p ~/.aws
+          cat > ~/.aws/credentials << EOF
+          [bedrock-test]
+          aws_access_key_id = ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws_secret_access_key = ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          EOF
+
+      - name: Run Bedrock AWS Profile Test
+        env:
+          LLM_PROVIDER: "bedrock"
+          LLM_MODEL: "us.anthropic.claude-3-5-haiku-20241022-v1:0"
+          AWS_PROFILE_NAME: "bedrock-test"
+          AWS_REGION_NAME: "us-east-1"
+          EMBEDDING_PROVIDER: "bedrock"
+          EMBEDDING_MODEL: "amazon.titan-embed-text-v2:0"
+          EMBEDDING_DIMENSIONS: "1024"
+        run: poetry run python ./examples/python/simple_example.py
--- a/.github/workflows/test_suites.yml
+++ b/.github/workflows/test_suites.yml
@ -110,6 +110,24 @@ jobs:
    uses: ./.github/workflows/test_gemini.yml
    secrets: inherit

+  bedrock-tests:
+    name: Bedrock Tests
+    needs: [basic-tests, e2e-tests]
+    uses: ./.github/workflows/test_bedrock_api_key.yml
+    secrets: inherit
+
+  bedrock-aws-credentials-tests:
+    name: Bedrock AWS Credentials Tests
+    needs: [basic-tests, e2e-tests]
+    uses: ./.github/workflows/test_bedrock_aws_credentials.yml
+    secrets: inherit
+
+  bedrock-aws-profile-tests:
+    name: Bedrock AWS Profile Tests
+    needs: [basic-tests, e2e-tests]
+    uses: ./.github/workflows/test_bedrock_aws_profile.yml
+    secrets: inherit
+
  # Ollama tests moved to the end
  ollama-tests:
    name: Ollama Tests
@ -143,6 +161,9 @@ jobs:
      db-examples-tests,
      mcp-test,
      gemini-tests,
+      bedrock-tests,
+      bedrock-aws-credentials-tests,
+      bedrock-aws-profile-tests,
      ollama-tests,
      relational-db-migration-tests,
      docker-compose-test,
@ -163,6 +184,9 @@ jobs:
                "${{ needs.db-examples-tests.result }}" == "success" &&
                "${{ needs.relational-db-migration-tests.result }}" == "success" &&
                "${{ needs.gemini-tests.result }}" == "success" &&
+                "${{ needs.bedrock-tests.result }}" == "success" &&
+                "${{ needs.bedrock-aws-credentials-tests.result }}" == "success" &&
+                "${{ needs.bedrock-aws-profile-tests.result }}" == "success" &&
                "${{ needs.docker-compose-test.result }}" == "success" &&
                "${{ needs.docker-ci-test.result }}" == "success" &&
                "${{ needs.ollama-tests.result }}" == "success" ]]; then
--- a/README.md
+++ b/README.md
@ -122,6 +122,16 @@ os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"
 ```

 You can also set the variables by creating .env file, using our <a href="https://github.com/topoteretes/cognee/blob/main/.env.template">template.</a>
+
+**Supported LLM Providers:** OpenAI (default), Anthropic, Gemini, Ollama, AWS Bedrock
+
+**For AWS Bedrock:** Set `LLM_PROVIDER="bedrock"` and use one of three authentication methods:
+- API Key: `LLM_API_KEY="your_bedrock_api_key"`
+- AWS Credentials: `AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY` (+ `AWS_SESSION_TOKEN` if needed)
+- AWS Profile: `AWS_PROFILE_NAME="your_profile"`
+
+Use an [inference profile](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_InvokeModel.html#API_runtime_InvokeModel_Example_5:~:text=Use%20an%20inference%20profile%20in%20model%20invocation) for the model IDs. This usually means appending `us.*` (or other region) to the model ID (e.g., `us.anthropic.claude-3-5-sonnet-20241022-v2:0`). See [AWS Bedrock models](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html).
+
 To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai">documentation</a>


--- a/cognee-starter-kit/README.md
+++ b/cognee-starter-kit/README.md
@ -25,6 +25,14 @@ uv sync
 ## Setup LLM
 Add environment variables to `.env` file.
 In case you choose to use OpenAI provider, add just the model and api_key.
+
+**Supported LLM Providers:**
+- OpenAI (default)
+- Anthropic
+- Gemini
+- Ollama
+- AWS Bedrock
+
 ```
 LLM_PROVIDER=""
 LLM_MODEL=""
@ -39,6 +47,36 @@ EMBEDDING_API_KEY=""
 EMBEDDING_API_VERSION=""
 ```

+**For AWS Bedrock, you have three authentication options:**
+
+1. **API Key (Bearer Token):**
+```
+LLM_PROVIDER="bedrock"
+LLM_API_KEY="your_bedrock_api_key"
+LLM_MODEL="us.anthropic.claude-3-5-sonnet-20241022-v2:0"
+AWS_REGION_NAME="us-east-1"
+```
+
+2. **AWS Credentials:**
+```
+LLM_PROVIDER="bedrock"
+LLM_MODEL="us.anthropic.claude-3-5-sonnet-20241022-v2:0"
+AWS_ACCESS_KEY_ID="your_aws_access_key"
+AWS_SECRET_ACCESS_KEY="your_aws_secret_key"
+[if needed] AWS_SESSION_TOKEN="your_session_token"
+AWS_REGION_NAME="us-east-1"
+```
+
+3. **AWS Profile:**
+```
+LLM_PROVIDER="bedrock"
+LLM_MODEL="us.anthropic.claude-3-5-sonnet-20241022-v2:0"
+AWS_PROFILE_NAME="your_aws_profile"
+AWS_REGION_NAME="us-east-1"
+```
+
+**Note:** For Bedrock models, use an [inference profile](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_InvokeModel.html#API_runtime_InvokeModel_Example_5:~:text=Use%20an%20inference%20profile%20in%20model%20invocation) for `LLM_MODEL`. This usually means appending `us.*` (or other region) to the model ID (e.g., `us.anthropic.claude-3-5-sonnet-20241022-v2:0`). See [AWS Bedrock models](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html) for available models.
+
 Activate the Python environment:
 ```
 source .venv/bin/activate
--- a/cognee/api/v1/add/add.py
+++ b/cognee/api/v1/add/add.py
@ -127,7 +127,7 @@ async def add(
        - LLM_API_KEY: API key for your LLM provider (OpenAI, Anthropic, etc.)

        Optional:
-        - LLM_PROVIDER: "openai" (default), "anthropic", "gemini", "ollama"
+        - LLM_PROVIDER: "openai" (default), "anthropic", "gemini", "ollama", "bedrock"
        - LLM_MODEL: Model name (default: "gpt-4o-mini")
        - DEFAULT_USER_EMAIL: Custom default user email
        - DEFAULT_USER_PASSWORD: Custom default user password
--- a/cognee/api/v1/search/search.py
+++ b/cognee/api/v1/search/search.py
@ -154,7 +154,7 @@ async def search(
        - LLM_API_KEY: API key for your LLM provider

        Optional:
-        - LLM_PROVIDER, LLM_MODEL: Configure LLM for search responses
+        - LLM_PROVIDER, LLM_MODEL: Configure LLM for search responses (supports: openai, anthropic, gemini, ollama, bedrock)
        - VECTOR_DB_PROVIDER: Must match what was used during cognify
        - GRAPH_DATABASE_PROVIDER: Must match what was used during cognify

--- a/cognee/infrastructure/llm/config.py
+++ b/cognee/infrastructure/llm/config.py
@ -27,6 +27,12 @@ class LLMConfig(BaseSettings):
    - embedding_rate_limit_enabled
    - embedding_rate_limit_requests
    - embedding_rate_limit_interval
+    - aws_access_key_id (Bedrock)
+    - aws_secret_access_key (Bedrock)
+    - aws_session_token (Bedrock)
+    - aws_region_name (Bedrock)
+    - aws_profile_name (Bedrock)
+    - aws_bedrock_runtime_endpoint (Bedrock)

    Public methods include:
    - ensure_env_vars_for_ollama
@ -63,6 +69,14 @@ class LLMConfig(BaseSettings):
    fallback_endpoint: str = ""
    fallback_model: str = ""

+    # AWS Bedrock configuration
+    aws_access_key_id: Optional[str] = None
+    aws_secret_access_key: Optional[str] = None
+    aws_session_token: Optional[str] = None
+    aws_region_name: str = "us-east-1"
+    aws_profile_name: Optional[str] = None
+    aws_bedrock_runtime_endpoint: Optional[str] = None
+
    baml_registry: ClassVar[ClientRegistry] = ClientRegistry()

    model_config = SettingsConfigDict(env_file=".env", extra="allow")
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/init.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/init.py
@ -0,0 +1,6 @@
+"""Bedrock LLM adapter module."""
+
+from .adapter import BedrockAdapter
+
+__all__ = ["BedrockAdapter"]
+
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/adapter.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/adapter.py
@ -0,0 +1,161 @@
+import litellm
+import instructor
+from typing import Type, Optional
+from pydantic import BaseModel
+from litellm.exceptions import ContentPolicyViolationError
+from instructor.exceptions import InstructorRetryException
+
+from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.llm.LLMGateway import LLMGateway
+from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.llm_interface import (
+    LLMInterface,
+)
+from cognee.infrastructure.llm.exceptions import ContentPolicyFilterError
+from cognee.infrastructure.files.utils.open_data_file import open_data_file
+from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.rate_limiter import (
+    rate_limit_async,
+    rate_limit_sync,
+    sleep_and_retry_async,
+    sleep_and_retry_sync,
+)
+from cognee.modules.observability.get_observe import get_observe
+
+observe = get_observe()
+
+
+class BedrockAdapter(LLMInterface):
+    """
+    Adapter for AWS Bedrock API with support for three authentication methods:
+    1. API Key (Bearer Token)
+    2. AWS Credentials (access key + secret key)
+    3. AWS Profile (boto3 credential chain)
+    """
+
+    name = "Bedrock"
+    model: str
+    api_key: str
+    aws_access_key_id: str
+    aws_secret_access_key: str
+    aws_region_name: str
+    aws_profile_name: str
+
+    MAX_RETRIES = 5
+
+    def __init__(
+        self,
+        model: str,
+        api_key: str = None,
+        aws_access_key_id: str = None,
+        aws_secret_access_key: str = None,
+        aws_session_token: str = None,
+        aws_region_name: str = "us-east-1",
+        aws_profile_name: str = None,
+        aws_bedrock_runtime_endpoint: str = None,
+        max_tokens: int = 16384,
+        streaming: bool = False,
+    ):
+        self.aclient = instructor.from_litellm(litellm.acompletion)
+        self.client = instructor.from_litellm(litellm.completion)
+        self.model = model
+        self.api_key = api_key
+        self.aws_access_key_id = aws_access_key_id
+        self.aws_secret_access_key = aws_secret_access_key
+        self.aws_session_token = aws_session_token
+        self.aws_region_name = aws_region_name
+        self.aws_profile_name = aws_profile_name
+        self.aws_bedrock_runtime_endpoint = aws_bedrock_runtime_endpoint
+        self.max_tokens = max_tokens
+        self.streaming = streaming
+
+    def _create_bedrock_request(
+        self, text_input: str, system_prompt: str, response_model: Type[BaseModel]
+    ) -> dict:
+        """Create Bedrock request with authentication and enhanced JSON formatting."""
+        enhanced_system_prompt = f"""{system_prompt}
+
+IMPORTANT: You must respond with valid JSON only. Do not include any text before or after the JSON. The response must be a valid JSON object that can be parsed directly."""
+
+        request_params = {
+            "model": self.model,
+            "custom_llm_provider": "bedrock",
+            "drop_params": True,
+            "messages": [
+                {"role": "user", "content": text_input},
+                {"role": "system", "content": enhanced_system_prompt},
+            ],
+            "response_model": response_model,
+            "max_retries": self.MAX_RETRIES,
+            "max_tokens": self.max_tokens,
+            "stream": self.streaming,
+        }
+
+        # Add authentication parameters
+        if self.api_key:
+            request_params["api_key"] = self.api_key
+        elif self.aws_access_key_id and self.aws_secret_access_key:
+            request_params["aws_access_key_id"] = self.aws_access_key_id
+            request_params["aws_secret_access_key"] = self.aws_secret_access_key
+            if self.aws_session_token:
+                request_params["aws_session_token"] = self.aws_session_token
+        elif self.aws_profile_name:
+            request_params["aws_profile_name"] = self.aws_profile_name
+
+        # Add optional parameters
+        if self.aws_region_name:
+            request_params["aws_region_name"] = self.aws_region_name
+        if self.aws_bedrock_runtime_endpoint:
+            request_params["aws_bedrock_runtime_endpoint"] = self.aws_bedrock_runtime_endpoint
+
+        return request_params
+
+    @observe(as_type="generation")
+    @sleep_and_retry_async()
+    @rate_limit_async
+    async def acreate_structured_output(
+        self, text_input: str, system_prompt: str, response_model: Type[BaseModel]
+    ) -> BaseModel:
+        """Generate structured output from AWS Bedrock API."""
+
+        try:
+            request_params = self._create_bedrock_request(text_input, system_prompt, response_model)
+            return await self.aclient.chat.completions.create(**request_params)
+
+        except (
+            ContentPolicyViolationError,
+            InstructorRetryException,
+        ) as error:
+            if (
+                isinstance(error, InstructorRetryException)
+                and "content management policy" not in str(error).lower()
+            ):
+                raise error
+
+            raise ContentPolicyFilterError(
+                f"The provided input contains content that is not aligned with our content policy: {text_input}"
+            )
+
+    @observe
+    @sleep_and_retry_sync()
+    @rate_limit_sync
+    def create_structured_output(
+        self, text_input: str, system_prompt: str, response_model: Type[BaseModel]
+    ) -> BaseModel:
+        """Generate structured output from AWS Bedrock API (synchronous)."""
+
+        request_params = self._create_bedrock_request(text_input, system_prompt, response_model)
+        return self.client.chat.completions.create(**request_params)
+
+    def show_prompt(self, text_input: str, system_prompt: str) -> str:
+        """Format and display the prompt for a user query."""
+        if not text_input:
+            text_input = "No user input provided."
+        if not system_prompt:
+            raise InvalidValueError(message="No system prompt path provided.")
+        system_prompt = LLMGateway.read_query_prompt(system_prompt)
+
+        formatted_prompt = (
+            f"""System Prompt:\n{system_prompt}\n\nUser Input:\n{text_input}\n"""
+            if system_prompt
+            else None
+        )
+        return formatted_prompt
--- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py
+++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py
@ -20,6 +20,7 @@ class LLMProvider(Enum):
    - ANTHROPIC: Represents the Anthropic provider.
    - CUSTOM: Represents a custom provider option.
    - GEMINI: Represents the Gemini provider.
+    - BEDROCK: Represents the AWS Bedrock provider.
    """

    OPENAI = "openai"
@ -27,6 +28,7 @@ class LLMProvider(Enum):
    ANTHROPIC = "anthropic"
    CUSTOM = "custom"
    GEMINI = "gemini"
+    BEDROCK = "bedrock"


 def get_llm_client():
@ -137,5 +139,23 @@ def get_llm_client():
            streaming=llm_config.llm_streaming,
        )

+    elif provider == LLMProvider.BEDROCK:
+        from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.bedrock.adapter import (
+            BedrockAdapter,
+        )
+
+        return BedrockAdapter(
+            model=llm_config.llm_model,
+            api_key=llm_config.llm_api_key,
+            aws_access_key_id=llm_config.aws_access_key_id,
+            aws_secret_access_key=llm_config.aws_secret_access_key,
+            aws_session_token=llm_config.aws_session_token,
+            aws_region_name=llm_config.aws_region_name,
+            aws_profile_name=llm_config.aws_profile_name,
+            aws_bedrock_runtime_endpoint=llm_config.aws_bedrock_runtime_endpoint,
+            max_tokens=max_tokens,
+            streaming=llm_config.llm_streaming,
+        )
+
    else:
        raise InvalidValueError(message=f"Unsupported LLM provider: {provider}")
--- a/cognee/modules/settings/get_settings.py
+++ b/cognee/modules/settings/get_settings.py
@ -15,10 +15,11 @@ class ModelName(Enum):
    ollama = "ollama"
    anthropic = "anthropic"
    gemini = "gemini"
+    bedrock = "bedrock"


 class LLMConfig(BaseModel):
-    api_key: str
+    api_key: Optional[str]
    model: str
    provider: str
    endpoint: Optional[str]
@ -72,6 +73,10 @@ def get_settings() -> SettingsDict:
            "value": "gemini",
            "label": "Gemini",
        },
+        {
+            "value": "bedrock",
+            "label": "AWS Bedrock",
+        },
    ]

    return SettingsDict.model_validate(
@ -134,6 +139,20 @@ def get_settings() -> SettingsDict:
                            "label": "Gemini 2.0 Flash",
                        },
                    ],
+                    "bedrock": [
+                        {
+                            "value": "us.anthropic.claude-3-5-sonnet-20241022-v2:0",
+                            "label": "Claude 3.5 Sonnet",
+                        },
+                        {
+                            "value": "us.anthropic.claude-3-5-haiku-20241022-v1:0",
+                            "label": "Claude 3.5 Haiku",
+                        },
+                        {
+                            "value": "us.anthropic.claude-3-5-sonnet-20240620-v1:0",
+                            "label": "Claude 3.5 Sonnet (June)",
+                        },
+                    ],
                },
            },
            vector_db={
--- a/pyproject.toml
+++ b/pyproject.toml
@ -34,7 +34,7 @@ dependencies = [
    "sqlalchemy>=2.0.39,<3.0.0",
    "aiosqlite>=0.20.0,<1.0.0",
    "tiktoken>=0.8.0,<1.0.0",
-    "litellm>=1.71.0, <2.0.0",
+    "litellm>=1.76.0, <2.0.0",
    "instructor>=1.9.1,<2.0.0",
    "langfuse>=2.32.0,<3",
    "filetype>=1.2.0,<2.0.0",
--- a/uv.lock
+++ b/uv.lock
@ -1060,7 +1060,7 @@ requires-dist = [
    { name = "langfuse", specifier = ">=2.32.0,<3" },
    { name = "langsmith", marker = "extra == 'langchain'", specifier = ">=0.2.3,<1.0.0" },
    { name = "limits", specifier = ">=4.4.1,<5" },
-    { name = "litellm", specifier = ">=1.71.0,<2.0.0" },
+    { name = "litellm", specifier = ">=1.76.0,<2.0.0" },
    { name = "llama-index-core", marker = "extra == 'llama-index'", specifier = ">=0.12.11,<0.13" },
    { name = "matplotlib", specifier = ">=3.8.3,<4" },
    { name = "mistral-common", marker = "extra == 'mistral'", specifier = ">=1.5.2,<2" },
@ -3552,7 +3552,7 @@ wheels = [

 [[package]]
 name = "litellm"
-version = "1.75.8"
+version = "1.76.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "aiohttp" },
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 [[package]]