add python gen ai release test

Author: liustve

.github/workflows/python-ec2-genai-test.yml

@@ -0,0 +1,179 @@
+## Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+## SPDX-License-Identifier: Apache-2.0
+
+name: Python EC2 LangChain Service Deployment
+on:
+  push:
+    branches:
+      - origin/gen-ai-sample-app
+
+permissions:
+  id-token: write
+  contents: read
+
+env:
+  E2E_TEST_AWS_REGION: 'us-west-2'
+  # E2E_TEST_ACCOUNT_ID: ${{ secrets.APPLICATION_SIGNALS_E2E_TEST_ACCOUNT_ID }}
+  # E2E_TEST_ROLE_NAME: ${{ secrets.APPLICATION_SIGNALS_E2E_TEST_ROLE_NAME }}
+  E2E_TEST_ACCOUNT_ID: 571600841604
+  E2E_TEST_ROLE_NAME: github
+  METRIC_NAMESPACE: genesis
+  LOG_GROUP_NAME: test/genesis
+  TEST_RESOURCES_FOLDER: ${GITHUB_WORKSPACE}
+  SAMPLE_APP_ZIP: s3://sigv4perfresults/langchain-service.zip
+
+jobs:
+  python-ec2-adot-genai:
+    runs-on: ubuntu-latest
+    timeout-minutes: 30
+    steps:
+      - uses: actions/checkout@v4
+
+      # - name: Set Get ADOT Wheel command environment variable
+      #   run: |
+      #     if [ "${{ github.event.repository.name }}" = "aws-otel-python-instrumentation" ]; then
+      #       # Reusing the adot-main-build-staging-jar bucket to store the python wheel file
+      #       echo GET_ADOT_WHEEL_COMMAND="aws s3 cp s3://adot-main-build-staging-jar/${{ env.ADOT_WHEEL_NAME }} ./${{ env.ADOT_WHEEL_NAME }} && sudo python${{ env.PYTHON_VERSION }} -m pip install ${{ env.ADOT_WHEEL_NAME }}" >> $GITHUB_ENV
+      #     elif [ "${{ env.OTEL_SOURCE }}" == "pypi" ]; then
+      #       echo GET_ADOT_WHEEL_COMMAND="sudo python${{ env.PYTHON_VERSION }} -m pip install ${{ env.ADOT_WHEEL_NAME }}" >> $GITHUB_ENV
+      #     else
+      #       latest_release_version=$(curl -sL https://github.com/aws-observability/aws-otel-python-instrumentation/releases/latest | grep -oP '/releases/tag/v\K[0-9]+\.[0-9]+\.[0-9]+' | head -n 1)
+      #       echo "The latest version is $latest_release_version"
+      #       echo GET_ADOT_WHEEL_COMMAND="wget -O ${{ env.ADOT_WHEEL_NAME }} https://github.com/aws-observability/aws-otel-python-instrumentation/releases/latest/download/aws_opentelemetry_distro-$latest_release_version-py3-none-any.whl \
+      #       && sudo python${{ env.PYTHON_VERSION }} -m pip install ${{ env.ADOT_WHEEL_NAME }}" >> $GITHUB_ENV
+      #     fi
+
+      - name: Initiate Gradlew Daemon
+        uses: ./.github/workflows/actions/execute_and_retry
+        continue-on-error: true
+        with:
+          command: "./gradlew :validator:build"
+          cleanup: "./gradlew clean"
+          max_retry: 3
+          sleep_time: 60
+          
+      - name: Generate testing id
+        run: echo TESTING_ID="${{ github.run_id }}-${{ github.run_number }}-${RANDOM}" >> $GITHUB_ENV
+        
+      - name: Generate XRay and W3C trace ID
+        run: |
+          ID_1="$(printf '%08x' $(date +%s))"
+          ID_2="$(openssl rand -hex 12)"
+          W3C_TRACE_ID="${ID_1}${ID_2}"
+          XRAY_TRACE_ID="1-${ID_1}-${ID_2}"
+          echo "XRAY_TRACE_ID=${XRAY_TRACE_ID}" >> $GITHUB_ENV
+          echo "W3C_TRACE_ID=${W3C_TRACE_ID}" >> $GITHUB_ENV
+          echo "Generated XRay Trace ID: ${XRAY_TRACE_ID}"
+          echo "Generated W3C Trace ID: ${W3C_TRACE_ID}"
+
+      - name: Configure AWS Credentials
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          role-to-assume: arn:aws:iam::${{ env.E2E_TEST_ACCOUNT_ID }}:role/${{ env.E2E_TEST_ROLE_NAME }}
+          aws-region: ${{ env.E2E_TEST_AWS_REGION }}
+
+      - name: Set up terraform
+        uses: ./.github/workflows/actions/execute_and_retry
+        with:
+          command: "wget -O- https://apt.releases.hashicorp.com/gpg | sudo gpg --dearmor -o /usr/share/keyrings/hashicorp-archive-keyring.gpg"
+          post-command: 'echo "deb [signed-by=/usr/share/keyrings/hashicorp-archive-keyring.gpg] https://apt.releases.hashicorp.com $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/hashicorp.list
+              && sudo apt update && sudo apt install terraform'
+
+      - name: Initiate Terraform
+        uses: ./.github/workflows/actions/execute_and_retry
+        with:
+          command: "cd ${{ env.TEST_RESOURCES_FOLDER }}/terraform/python/ec2/adot-genai && terraform init && terraform validate"
+          cleanup: "rm -rf .terraform && rm -rf .terraform.lock.hcl"
+          max_retry: 6
+
+      - name: Deploy service via terraform
+        working-directory: terraform/python/ec2/adot-genai
+        run: |
+          terraform apply -auto-approve \
+            -var="aws_region=${{ env.E2E_TEST_AWS_REGION }}" \
+            -var="test_id=${{ env.TESTING_ID }}" \
+            -var="service_zip_url=${{ env.SAMPLE_APP_ZIP }}"
+
+      - name: Get deployment info
+        working-directory: terraform/python/ec2/adot-genai
+        run: |
+          echo "INSTANCE_IP=$(terraform output langchain_service_public_ip)" >> $GITHUB_ENV
+          echo "INSTANCE_ID=$(terraform output langchain_service_instance_id)" >> $GITHUB_ENV
+
+      - name: Wait for Gen AI Chatbot service to be ready
+        run: |
+          echo "Waiting for service to be ready at http://${{ env.INSTANCE_IP }}:8000"
+          for i in {1..60}; do
+            if curl -f -s "http://${{ env.INSTANCE_IP }}:8000/health" > /dev/null 2>&1; then
+              echo "Service is ready!"
+              break
+            fi
+            echo "Attempt $i: Service not ready yet, waiting 10 seconds..."
+            sleep 10
+          done
+          
+          # Final check
+          if ! curl -f -s "http://${{ env.INSTANCE_IP }}:8000/health" > /dev/null 2>&1; then
+            echo "Service failed to become ready after 10 minutes"
+            exit 1
+          fi
+          
+      - name: Generate traffic
+        run: |
+          cd sample-apps/traffic-generator/genai
+          chmod +x generate_traffic.sh
+          export SERVER_URL="http://${{ env.INSTANCE_IP }}:8000"
+          export NUM_REQUESTS="5"
+          export DELAY_SECONDS="5"
+          export TIMEOUT="30"
+          export TRACE_ID="Root=${XRAY_TRACE_ID};Parent=$(openssl rand -hex 8);Sampled=1"
+          ./generate_traffic.sh
+
+      - name: Validate generated logs
+        run: ./gradlew validator:run --args='-c python/ec2/adot-genai/log-validation.yml
+          --testing-id ${{ env.TESTING_ID }}
+          --endpoint http://${{ env.INSTANCE_IP }}:8000
+          --region ${{ env.E2E_TEST_AWS_REGION }}
+          --metric-namespace ${{ env.METRIC_NAMESPACE }}
+          --log-group ${{ env.LOG_GROUP_NAME }}
+          --service-name langchain-traceloop-app
+          --instance-id ${{ env.INSTANCE_ID }}
+          --trace-id ${{ env.W3C_TRACE_ID }}'
+
+      - name: Validate generated traces
+        if: (success() || failure()) && !cancelled()
+        run: ./gradlew validator:run --args='-c python/ec2/adot-genai/trace-validation.yml
+          --testing-id ${{ env.TESTING_ID }}
+          --endpoint http://${{ env.INSTANCE_IP }}:8000
+          --region ${{ env.E2E_TEST_AWS_REGION }}
+          --metric-namespace ${{ env.METRIC_NAMESPACE }}
+          --service-name langchain-traceloop-app
+          --instance-id ${{ env.INSTANCE_ID }}
+          --trace-id ${{ env.XRAY_TRACE_ID }}'
+
+      - name: Wait for metrics to be published
+        if: (success() || failure()) && !cancelled()
+        run: |
+          echo "Waiting 60 seconds to ensure EMF metrics are published to CloudWatch"
+          sleep 60
+
+      - name: Validate generated metrics
+        if: (success() || failure()) && !cancelled()
+        run: ./gradlew validator:run --args='-c python/ec2/adot-genai/metric-validation.yml
+          --testing-id ${{ env.TESTING_ID }}
+          --endpoint http://${{ env.INSTANCE_IP }}:8000
+          --region ${{ env.E2E_TEST_AWS_REGION }}
+          --metric-namespace ${{ env.METRIC_NAMESPACE }}
+          --log-group ${{ env.LOG_GROUP_NAME }}
+          --service-name langchain-traceloop-app
+          --instance-id ${{ env.INSTANCE_ID }}'
+
+      - name: Cleanup
+        if: always()
+        continue-on-error: true
+        working-directory: terraform/python/ec2/adot-genai
+        run: |
+          terraform destroy -auto-approve \
+            -var="aws_region=${{ env.E2E_TEST_AWS_REGION }}" \
+            -var="test_id=${{ env.TESTING_ID }}" \
+            -var="service_zip_url=${{ env.SAMPLE_APP_ZIP }}"

.github/workflows/python-ec2-genesis-test.yml

@@ -1,13 +1,15 @@
 langchain
 langchain-community
+langchain_aws
 opentelemetry-sdk
+openinference-instrumentation-langchain
 opentelemetry-api
 opentelemetry-semantic-conventions
 python-dotenv
 openlit
 botocore
 setuptools
 boto3
-./aws_opentelemetry_distro_genai_beta-0.1.0b8-py3-none-any.whl
+aws_opentelemetry_distro_genai_beta
 fastapi
 uvicorn[standard]

sample-apps/python/langchain_service/ec2-requirements.txt renamed to sample-apps/python/genai_service/ec2-requirements.txt

@@ -82,13 +82,12 @@ async def root():
     return {
         "message": "LangChain Bedrock OpenInference API is running!",
         "endpoints": {
-            "/chat": "Single message chat endpoint",
-            "/batch": "Batch message processing endpoint",
-            "/sample": "Run sample prompts"
+            "/ai-chat": "Single message chat endpoint",
+            "/hello": "Simple hello endpoint"
         }
     }
 
-@app.post("/chat", response_model=ChatResponse)
+@app.post("/ai-chat", response_model=ChatResponse)
 async def chat(request: ChatRequest):
     """
     Chat endpoint that processes a single user message through AWS Bedrock
@@ -100,40 +99,6 @@ async def chat(request: ChatRequest):
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.post("/batch", response_model=BatchChatResponse)
-async def batch_chat(request: BatchChatRequest):
-    """
-    Batch endpoint that processes multiple messages
-    """
-    try:
-        responses = []
-        for message in request.messages:
-            result = await chain.ainvoke({"input": message})
-            responses.append({
-                "message": message,
-                "response": result["text"]
-            })
-        return BatchChatResponse(responses=responses)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/sample", response_model=BatchChatResponse)
-async def run_samples():
-    """
-    Run the predefined sample prompts
-    """
-    try:
-        responses = []
-        for prompt in SAMPLE_PROMPTS:
-            result = await chain.ainvoke({"input": prompt})
-            responses.append({
-                "message": prompt,
-                "response": result["text"]
-            })
-        return BatchChatResponse(responses=responses)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
 @app.get("/health")
 async def health():
     """Health check endpoint"""
@@ -145,4 +110,5 @@ async def health():
     print("Make sure AWS credentials are configured")
     print("Server will run on http://localhost:8000")
     print("API docs available at http://localhost:8000/docs")
+    
     uvicorn.run(app, host="0.0.0.0", port=8000)