workflow added

Author: dipika-mindfire

.github/workflows/prepare-release-pr.yml

@@ -0,0 +1,50 @@
+name: Create PR from dev to main
+
+on:
+  push:
+    branches:
+      - dev
+
+jobs:
+  create-pull-request:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      pull-requests: write
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          ref: dev
+
+      - name: Set Git Identity
+        run: |
+          git config --global user.name 'GitHub Actions'
+          git config --global user.email 'github-actions@github.com'
+
+      - name: Create Pull Request with gh cli
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # We're already on dev, just need to fetch main
+          git fetch origin main:refs/remotes/origin/main
+
+          # Check if there are differences between main and dev
+          DIFF_COUNT=$(git rev-list --count origin/main..HEAD)
+
+          if [ "$DIFF_COUNT" -gt 0 ]; then
+            echo "Differences found between main and dev. Creating PR..."
+            
+            # Use GitHub CLI to create the PR
+            gh pr create \
+              --base main \
+              --head dev \
+              --title "Merge dev into main" \
+              --body "This is an automated PR to merge changes from dev into main branch." || true
+              
+            echo "Pull request created or already exists."
+          else
+            echo "No differences found between main and dev. Skipping PR creation."
+          fi

.github/workflows/release-and-publish.yml

@@ -0,0 +1,76 @@
+name: Release and Publish Package
+
+on:
+  push:
+    branches:
+      - main
+  workflow_dispatch:
+
+jobs:
+  release:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+      id-token: write
+      pull-requests: write
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set up Python
+        uses: actions/setup-python@v3
+        with:
+          python-version: "3.x"
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install build twine python-semantic-release==10.0.2 setuptools-scm
+
+      - name: Create release branch
+        run: |
+          git config --global user.name "github-actions"
+          git config --global user.email "github-actions@github.com"
+          git checkout -b release-main
+          git push --set-upstream origin release-main
+
+      - name: Run semantic-release version on release-main branch
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          semantic-release --verbose version
+
+      # For semantic-release 9.x, the publish command needs to be run separately
+      - name: Run semantic-release publish
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          #PYPI_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
+        run: |
+          semantic-release --verbose publish
+
+      - name: Push release branch
+        run: git push origin release-main
+
+      - name: Create PR to main
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          gh pr create \
+            --base main \
+            --head release-main \
+            --title "Automated Release Updates" \
+            --body "This pull request contains updates from the semantic-release process." || true
+
+      # This is only needed if semantic-release publish didn't handle the PyPI upload
+      # - name: Build and publish package to PyPI if needed
+      #   env:
+      #     TWINE_USERNAME: __token__
+      #     TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+      #   run: |
+      #     if [ ! -f "dist/*" ]; then
+      #       python -m build
+      #       twine upload dist/*
+      #     fi

ml_analysis_agent/config/ml_config.py

@@ -1,53 +1,53 @@
 """ML and AWS configuration settings."""
-
 import os
 import boto3
 from dotenv import load_dotenv
 from langchain_aws import ChatBedrockConverse
 
 load_dotenv()
 
-
 class MLConfig:
     """Base configuration class."""
 
     def get_llm_model(self):
         """Method to get LLM model instance."""
-        raise NotImplementedError('This method should be overridden by subclasses.')
-
+        raise NotImplementedError("This method should be overridden by subclasses.")
+    
     def get_client(self):
         """Method to get client instance."""
         pass
 
-
 class AWSMLConfig(MLConfig):
     """Configuration class for ML and AWS settings."""
-
-    def __init__(self, aws_token: str = None, aws_region: str = None, model_name: str = None):
+    
+    def __init__(
+            self, 
+            aws_token: str = None, 
+            aws_region: str = None, 
+            model_name: str = None
+        ):
         self.AWS_BEARER_TOKEN_BEDROCK = aws_token or os.getenv('AWS_BEARER_TOKEN_BEDROCK')
         self.AWS_DEFAULT_REGION = aws_region or os.getenv('AWS_DEFAULT_REGION', 'us-west-2')
-        self.MODEL_NAME = model_name or os.getenv(
-            'MODEL_NAME', 'us.anthropic.claude-sonnet-4-20250514-v1:0'
-        )
-
+        self.MODEL_NAME = model_name or os.getenv("MODEL_NAME","us.anthropic.claude-sonnet-4-20250514-v1:0")
+        
         if not self.AWS_BEARER_TOKEN_BEDROCK:
-            raise ValueError('AWS_BEARER_TOKEN_BEDROCK not found in .env file.')
-
+            raise ValueError("AWS_BEARER_TOKEN_BEDROCK not found in .env file.")
+        
         self._client = None
         self._llm = None
-
+    
     def get_client(self):
         """Get AWS Bedrock client (singleton pattern)."""
         if self._client is None:
             self._client = boto3.client(
-                'bedrock-runtime',
+                "bedrock-runtime",
                 region_name=self.AWS_DEFAULT_REGION,
                 aws_access_key_id=None,
                 aws_secret_access_key=None,
                 aws_session_token=self.AWS_BEARER_TOKEN_BEDROCK,
             )
         return self._client
-
+    
     def get_llm_model(self):
         """Get LLM model instance (singleton pattern)."""
         if self._llm is None:
@@ -57,4 +57,4 @@ def get_llm_model(self):
                 temperature=0,
                 max_tokens=4000,
             )
-        return self._llm
+        return self._llm