feat: Add Amazon Bedrock integration for LLM, embeddings, and reranking

README.md

@@ -221,6 +221,9 @@ pip install graphiti-core[falkordb,anthropic,google-genai]
 
 # Install with Amazon Neptune
 pip install graphiti-core[neptune]
+
+# Install with Amazon Bedrock
+pip install graphiti-core[bedrock]
 ```
 
 ## Default to Low Concurrency; LLM Provider 429 Rate Limit Errors
@@ -544,6 +547,68 @@ graphiti = Graphiti(
 
 Ensure Ollama is running (`ollama serve`) and that you have pulled the models you want to use.
 
+## Using Graphiti with Amazon Bedrock
+
+Graphiti supports Amazon Bedrock for LLM inference, embeddings, and reranking. Amazon Bedrock provides access to foundation models from leading AI companies.
+
+Install Graphiti with Amazon Bedrock support:
+
+```bash
+uv add "graphiti-core[bedrock]"
+
+# or
+
+pip install "graphiti-core[bedrock]"
+```
+
+```python
+from graphiti_core import Graphiti
+from graphiti_core.llm_client.amazon_bedrock_client import AmazonBedrockLLMClient
+from graphiti_core.llm_client.config import LLMConfig
+from graphiti_core.embedder.amazon_bedrock import AmazonBedrockEmbedder, AmazonBedrockEmbedderConfig
+from graphiti_core.cross_encoder.amazon_bedrock_reranker_client import AmazonBedrockRerankerClient
+
+# Configure Amazon Bedrock clients
+llm_client = AmazonBedrockLLMClient(
+    config=LLMConfig(
+        model="us.anthropic.claude-sonnet-4-20250514-v1:0",
+        temperature=0.1,
+        max_tokens=1000,
+    ),
+    region="us-east-1",
+)
+
+embedder_client = AmazonBedrockEmbedder(
+    config=AmazonBedrockEmbedderConfig(
+        model="amazon.titan-embed-text-v2:0",
+        region="us-east-1",
+    )
+)
+
+reranker_client = AmazonBedrockRerankerClient(
+    model="cohere.rerank-v3-5:0",
+    region="us-east-1",
+    max_results=10,
+)
+
+# Initialize Graphiti with Amazon Bedrock clients
+graphiti = Graphiti(
+    "bolt://localhost:7687",
+    "neo4j",
+    "password",
+    llm_client=llm_client,
+    embedder=embedder_client,
+    cross_encoder=reranker_client,
+)
+
+# Now you can use Graphiti with Amazon Bedrock
+```
+
+**Key Points:**
+- Requires AWS credentials configured (via AWS CLI, environment variables, or IAM roles)
+- Different models are available in different AWS regions - check the [AWS Bedrock documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html) for availability
+- See `examples/amazon-bedrock/` for a complete working example
+
 ## Documentation
 
 - [Guides and API documentation](https://help.getzep.com/graphiti).

examples/amazon-bedrock/.env.example

@@ -0,0 +1,20 @@
+# Neo4j Configuration
+NEO4J_URI=bolt://localhost:7687
+NEO4J_USER=neo4j
+NEO4J_PASSWORD=password
+
+# AWS Configuration
+# AWS credentials can be configured via:
+# 1. Environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
+# 2. AWS credentials file (~/.aws/credentials)
+# 3. IAM roles (for EC2 instances)
+AWS_REGION=us-east-1
+
+# Amazon Bedrock Model Configuration
+BEDROCK_LLM_MODEL=us.anthropic.claude-sonnet-4-20250514-v1:0
+BEDROCK_EMBEDDING_MODEL=amazon.titan-embed-text-v2:0
+BEDROCK_RERANKER_MODEL=cohere.rerank-v3-5:0
+
+# Optional: Explicit AWS credentials (not recommended for production)
+# AWS_ACCESS_KEY_ID=your_access_key_here
+# AWS_SECRET_ACCESS_KEY=your_secret_key_here

examples/amazon-bedrock/README.md

@@ -0,0 +1,179 @@
+# Amazon Bedrock + Neo4j Example
+
+This example demonstrates how to use Graphiti with Amazon Bedrock for LLM inference, embeddings, and reranking, combined with Neo4j as the graph database.
+
+## Features Demonstrated
+
+- **Amazon Bedrock LLM Client**: Uses Claude models for text generation and structured output
+- **Amazon Bedrock Embedder**: Uses Titan embedding models for semantic search
+- **Amazon Bedrock Reranker**: Uses Cohere or Amazon rerank models for result reranking
+- **Neo4j Integration**: Stores and queries the knowledge graph
+- **Hybrid Search**: Combines semantic similarity and BM25 text retrieval
+- **Graph-based Reranking**: Reorders results based on graph distance
+
+## Prerequisites
+
+### 1. Neo4j Database
+
+Install and start Neo4j:
+- Download [Neo4j Desktop](https://neo4j.com/download/)
+- Create a new database with username `neo4j` and password `password`
+- Start the database
+
+### 2. AWS Account and Bedrock Access
+
+You need:
+- An AWS account with Bedrock access
+- Model access enabled for the models you want to use:
+  - Claude models (e.g., `us.anthropic.claude-sonnet-4-20250514-v1:0`)
+  - Titan embedding models (e.g., `amazon.titan-embed-text-v2:0`)
+  - Rerank models (e.g., `cohere.rerank-v3-5:0`)
+
+### 3. AWS Credentials
+
+Configure AWS credentials using one of these methods:
+
+**Option 1: AWS CLI**
+```bash
+aws configure
+```
+
+**Option 2: Environment Variables**
+```bash
+export AWS_ACCESS_KEY_ID=your_access_key
+export AWS_SECRET_ACCESS_KEY=your_secret_key
+export AWS_REGION=us-east-1
+```
+
+### 4. Python Dependencies
+
+Sync dependencies with Amazon Bedrock support:
+```bash
+uv sync --extra bedrock
+```
+
+## Setup
+
+1. **Navigate to the example directory:**
+   ```bash
+   cd examples/amazon-bedrock
+   ```
+
+2. **Copy and configure environment variables:**
+   ```bash
+   cp .env.example .env
+   # Edit .env with your configuration
+   ```
+
+
+## Configuration
+
+### Environment Variables
+
+The example uses these environment variables (see `.env.example`):
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `NEO4J_URI` | `bolt://localhost:7687` | Neo4j connection URI |
+| `NEO4J_USER` | `neo4j` | Neo4j username |
+| `NEO4J_PASSWORD` | `password` | Neo4j password |
+| `AWS_REGION` | `us-east-1` | AWS region for Bedrock |
+| `BEDROCK_LLM_MODEL` | `us.anthropic.claude-sonnet-4-20250514-v1:0` | Claude model for LLM |
+| `BEDROCK_EMBEDDING_MODEL` | `amazon.titan-embed-text-v2:0` | Titan model for embeddings |
+| `BEDROCK_RERANKER_MODEL` | `cohere.rerank-v3-5:0` | Rerank model |
+
+### Model Availability by Region
+
+Different Bedrock models are available in different AWS regions. Please check the [AWS Bedrock documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html) for the latest information on model availability by region.
+
+## Running the Example
+
+```bash
+uv run python amazon_bedrock_neo4j.py
+```
+
+## What the Example Does
+
+1. **Initializes Graphiti** with Amazon Bedrock clients and Neo4j
+2. **Adds Episodes** containing information about California politics
+3. **Performs Hybrid Search** using semantic similarity and BM25
+4. **Demonstrates Reranking** using Amazon Bedrock reranker
+5. **Shows Integration Details** including model and region information
+
+## Expected Output
+
+```
+Added episode: California Politics 0 (text)
+Added episode: California Politics 1 (text)
+Added episode: California Politics 2 (json)
+
+Searching for: 'Who was the California Attorney General?'
+
+Search Results:
+UUID: [uuid]
+Fact: Kamala Harris holds the position of Attorney General of California
+Valid from: [timestamp]
+---
+
+...
+
+Reranking search results based on graph distance:
+Using center node UUID: [uuid]
+Reranker model: cohere.rerank-v3-5:0
+
+Reranked Search Results (using Amazon Bedrock reranker):
+UUID: [uuid]
+Fact: Kamala Harris is the Attorney General of California
+Valid from: [timestamp]
+---
+
+...
+
+Connection closed
+```
+
+## Troubleshooting
+
+### Common Issues
+
+**1. AWS Credentials Not Found**
+```
+NoCredentialsError: Unable to locate credentials
+```
+- Ensure AWS credentials are properly configured
+- Check that your AWS profile has the correct permissions
+
+**2. Model Access Denied**
+```
+AccessDeniedException: User is not authorized to perform: bedrock:InvokeModel
+```
+- Request access to the specific models in the AWS Bedrock console
+- Ensure your AWS account has Bedrock permissions
+
+**3. Model Not Available in Region**
+```
+ValidationException: The model ID is not supported in this region
+```
+- Check model availability in your selected region
+- Update the region or model in your configuration
+
+**4. Neo4j Connection Failed**
+```
+ServiceUnavailable: Failed to establish connection
+```
+- Ensure Neo4j is running
+- Check the connection URI, username, and password
+
+### Getting Help
+
+- Check the [Graphiti documentation](https://help.getzep.com/graphiti)
+- Join the [Zep Discord server](https://discord.com/invite/W8Kw6bsgXQ) #graphiti channel
+- Review AWS Bedrock documentation for model access and permissions
+
+## Next Steps
+
+- Explore different Amazon Bedrock models
+- Try different AWS regions
+- Experiment with custom entity types
+- Integrate with your own data sources
+- Scale up with larger datasets