feat: Add AWS Bedrock provider integration #5190

docs/providers/documentation/bedrock-provider.mdx

@@ -0,0 +1,59 @@
+---
+title: "Bedrock Provider"
+description: "The Bedrock Provider allows for integrating AWS Bedrock foundation models into Keep."
+---
+import AutoGeneratedSnippet from '/snippets/providers/bedrock-snippet-autogenerated.mdx';
+
+<Tip>
+  The Bedrock Provider supports querying multiple foundation models including Anthropic Claude, Meta Llama, and Amazon Titan for prompt-based interactions.
+</Tip>
+
+## Outputs
+
+The Bedrock Provider outputs the response from the foundation model based on the prompt provided. Supports structured JSON output when configured.
+
+## Supported Models
+
+- **Anthropic Claude**: Uses Messages API format with system prompts
+- **Meta Llama**: Prompt-based generation with configurable parameters
+- **Amazon Titan Text**: Text generation with configurable parameters
+
+## Connecting with the Provider
+
+The Bedrock Provider supports two authentication methods:
+
+### 1. SSO/IAM Role Authentication (Recommended)
+Leave `access_key` and `secret_access_key` empty to use AWS SSO or IAM role authentication:
+
+```yaml
+authentication:
+  access_key: null
+  secret_access_key: null
+  region: "us-east-1"
+```
+
+### 2. Access Key Authentication
+Provide explicit AWS credentials:
+
+```yaml
+authentication:
+  access_key: "your-access-key"
+  secret_access_key: "your-secret-key"
+  region: "us-east-1"
+```
+
+## Required Permissions
+
+Your AWS credentials must have the following permissions:
+- `bedrock:ListFoundationModels`
+- `bedrock:InvokeModel`
+
+## Configuration Parameters
+
+- **model**: Foundation model ID (default: `meta.llama3-3-70b-instruct-v1:0`)
+- **max_tokens**: Maximum tokens to generate (default: 1024)
+- **temperature**: Controls randomness (0.0-1.0, default: 0.7)
+- **top_p**: Controls diversity (0.0-1.0, default: 0.9)
+- **structured_output_format**: JSON schema for structured responses
+
+<AutoGeneratedSnippet />

docs/providers/overview.mdx

@@ -44,6 +44,14 @@ By leveraging Keep Providers, users are able to deeply integrate Keep with the t
   }
 ></Card>
 
+<Card
+  title="Bedrock"
+  href="/providers/documentation/bedrock-provider"
+  icon={
+    <img src="https://img.logo.dev/amazon.com?token=pk_dfXfZBoKQMGDTIgqu7LvYg" />
+  }
+></Card>
+
 <Card
   title="AppDynamics"
   href="/providers/documentation/appdynamics-provider"

keep-ui/app/(keep)/incidents/[id]/chat/incident-chat.tsx

@@ -547,6 +547,11 @@ export function IncidentChat({
     // using 'incident-chat' class to apply styles only to that chat component
     <Card className="h-full incident-chat">
       <div className="chat-container">
+        <div className="flex items-center justify-between p-2 border-b border-tremor-border">
+          <span className="text-sm text-tremor-content-subtle">
+            AI Model: {process.env.NEXT_PUBLIC_BEDROCK_MODEL_ID || "Unknown"}
+          </span>
+        </div>
         <div className="chat-messages">
           <CopilotChat
             className="-mx-2"

keep-ui/app/api/copilotkit/route.ts

@@ -1,24 +1,56 @@
 import {
   CopilotRuntime,
   OpenAIAdapter,
+  LangChainAdapter,
   copilotRuntimeNextJSAppRouterEndpoint,
 } from "@copilotkit/runtime";
 import OpenAI, { OpenAIError } from "openai";
 import { NextRequest } from "next/server";
+import { ChatBedrockConverse } from "@langchain/aws";
 
 export const POST = async (req: NextRequest) => {
   function initializeCopilotRuntime() {
     try {
-      const openai = new OpenAI({
-        organization: process.env.OPEN_AI_ORGANIZATION_ID,
-        apiKey: process.env.OPEN_AI_API_KEY,
-      });
-      const serviceAdapter = new OpenAIAdapter({
-        openai,
-        ...(process.env.OPENAI_MODEL_NAME
-          ? { model: process.env.OPENAI_MODEL_NAME }
-          : {}),
-      });
+      const provider = process.env.AI_PROVIDER || "openai";
+
+      let serviceAdapter;
+
+      if (provider === "bedrock") {
+        console.log("DEBUG: Using Bedrock model:", process.env.BEDROCK_MODEL_ID, "in region:", process.env.AWS_REGION);
+        const bedrockModel = new ChatBedrockConverse({
+          model: process.env.BEDROCK_MODEL_ID,
+          region: process.env.AWS_REGION,
+          // Use default credential provider chain (same as Bedrock provider)
+          // This will use AWS profile, SSO, or environment variables automatically
+        });
+
+        serviceAdapter = new LangChainAdapter({
+          chainFn: async ({ messages }) => {
+            // Filter out empty messages and ensure proper format
+            const filteredMessages = messages.filter(msg => 
+              msg.content && 
+              (typeof msg.content === 'string' && msg.content.trim().length > 0)
+            );
+
+            console.log("DEBUG: Filtered messages:", filteredMessages.length, "out of", messages.length);
+
+            const response = await bedrockModel.invoke(filteredMessages);
+            return response;
+          },
+        });
+      } else {
+        const openai = new OpenAI({
+          organization: process.env.OPEN_AI_ORGANIZATION_ID,
+          apiKey: process.env.OPEN_AI_API_KEY,
+        });
+        serviceAdapter = new OpenAIAdapter({
+          openai,
+          ...(process.env.OPENAI_MODEL_NAME
+            ? { model: process.env.OPENAI_MODEL_NAME }
+            : {}),
+        });
+      }
+
       const runtime = new CopilotRuntime();
       return { runtime, serviceAdapter };
     } catch (error) {