Feat: Add OpenAI LLM provider support

- Add OpenAI client implementation with gpt-4o default model
- Create LLM factory pattern for provider abstraction
- Add command line flags for --provider and --model selection
- Support environment variables for configuration (LLM_PROVIDER, OPENAI_MODEL, CLAUDE_MODEL)
- Auto-detection of provider based on available API keys
- Maintain backward compatibility with Claude as default
- Update README with comprehensive configuration examples
- Update Krew manifest to v0.1.3 with OpenAI support documentation

Closes #1

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: barckcode

README.md

@@ -12,6 +12,7 @@
 * ✅ **Actionable fixes** – concrete `kubectl` / `helm` commands you can copy-paste.
 * ✅ **Understands the whole picture** – pods, deployments, services, CRDs, ingresses…
 * ✅ **Human or machine output** – pretty terminal format, or JSON / YAML for automation.
+* ✅ **Multiple LLM providers** – supports Claude (Anthropic) and OpenAI models.
 
 ---
 
@@ -20,11 +21,18 @@
 ### 1. Prerequisites
 
 * Go 1.21+
-* An Anthropic **API key** exported as `ANTHROPIC_API_KEY`
+* An **API key** for your chosen LLM provider:
+  - **Claude (Anthropic)**: `ANTHROPIC_API_KEY`
+  - **OpenAI**: `OPENAI_API_KEY`
 * Access to the cluster you want to debug (via `kubectl` context)
 
 ```bash
+# For Claude (default)
 export ANTHROPIC_API_KEY="sk-..."
+
+# For OpenAI
+export OPENAI_API_KEY="sk-..."
+export LLM_PROVIDER="openai"  # Optional: auto-detects from API key
 ```
 
 ---
@@ -89,6 +97,74 @@ kubectl ai debug "high memory usage" -n production --all
 
 # Output as JSON
 kubectl ai debug "slow startup" -r deployment/api -o json
+
+# Use specific LLM provider
+kubectl ai debug "networking issues" -r deployment/app --provider openai
+
+# Use specific model
+kubectl ai debug "memory leaks" -r deployment/app --provider openai --model gpt-4o
+
+# Use environment variables to set provider and model
+export LLM_PROVIDER="openai"
+export OPENAI_MODEL="gpt-4o-mini"
+kubectl ai debug "performance issues" -r deployment/app
+
+# Override environment with command line flags
+kubectl ai debug "storage issues" -r deployment/app --provider claude --model claude-3-opus-20240229
+```
+
+---
+
+## 🔧 LLM Provider Configuration
+
+### Claude (Anthropic) - Default
+
+```bash
+export ANTHROPIC_API_KEY="sk-..."
+# Optional: specify model (default: claude-3-5-sonnet-20241022)
+export CLAUDE_MODEL="claude-3-5-sonnet-20241022"
+```
+
+### OpenAI
+
+```bash
+export OPENAI_API_KEY="sk-..."
+# Optional: specify model (default: gpt-4o)
+export OPENAI_MODEL="gpt-4o"
+# Optional: specify provider explicitly (auto-detects from API key if not set)
+export LLM_PROVIDER="openai"
+```
+
+### Configuration Priority
+
+1. **Command line flags** (`--provider`, `--model`) - highest priority
+2. **Environment variables** (`LLM_PROVIDER`, `OPENAI_MODEL`, `CLAUDE_MODEL`)
+3. **Auto-detection** - based on available API keys (Claude preferred if both available)
+
+### Command Line Options
+
+- `--provider`: Explicitly choose LLM provider (`claude`, `openai`)
+- `--model`: Override the default model for the selected provider
+- Auto-detection: If no provider is specified, the tool auto-detects based on available API keys
+
+---
+
+## 📋 Complete Command Reference
+
+```bash
+kubectl ai debug PROBLEM [flags]
+
+Flags:
+  -h, --help              help for debug
+      --kubeconfig string path to kubeconfig file (default "~/.kube/config")
+      --context string    kubeconfig context (overrides current-context)
+  -n, --namespace string  kubernetes namespace (default "default")
+  -r, --resource strings  resources to analyze (e.g., deployment/nginx, pod/nginx-xxx)
+      --all               analyze all resources in the namespace
+  -o, --output string     output format (human, json, yaml) (default "human")
+  -v, --verbose           verbose output
+      --provider string   LLM provider (claude, openai). Defaults to auto-detect from env
+      --model string      LLM model to use (overrides default)
 ```
 
 ---

cmd/debug.go

@@ -6,24 +6,28 @@ import (
 	"strings"
 	"time"
 
+	"path/filepath"
+
 	"github.com/briandowns/spinner"
 	"github.com/fatih/color"
-	"github.com/spf13/cobra"
 	"github.com/helmcode/kubectl-ai/pkg/analyzer"
 	"github.com/helmcode/kubectl-ai/pkg/formatter"
 	"github.com/helmcode/kubectl-ai/pkg/k8s"
+	"github.com/helmcode/kubectl-ai/pkg/llm"
+	"github.com/spf13/cobra"
 	"k8s.io/client-go/util/homedir"
-	"path/filepath"
 )
 
 var (
-	kubeconfig string
-	namespace  string
-    kubeContext string
-	resources  []string
+	kubeconfig   string
+	namespace    string
+	kubeContext  string
+	resources    []string
 	allResources bool
 	outputFormat string
-	verbose    bool
+	verbose      bool
+	llmProvider  string
+	llmModel     string
 )
 
 func NewDebugCmd() *cobra.Command {
@@ -54,24 +58,20 @@ Examples:
 	}
 
 	cmd.Flags().StringVarP(&namespace, "namespace", "n", "default", "Kubernetes namespace")
-    cmd.Flags().StringVar(&kubeContext, "context", "", "Kubeconfig context (overrides current-context)")
+	cmd.Flags().StringVar(&kubeContext, "context", "", "Kubeconfig context (overrides current-context)")
 	cmd.Flags().StringSliceVarP(&resources, "resource", "r", []string{}, "Resources to analyze (e.g., deployment/nginx, pod/nginx-xxx)")
 	cmd.Flags().BoolVar(&allResources, "all", false, "Analyze all resources in the namespace")
 	cmd.Flags().StringVarP(&outputFormat, "output", "o", "human", "Output format (human, json, yaml)")
 	cmd.Flags().BoolVarP(&verbose, "verbose", "v", false, "Verbose output")
+	cmd.Flags().StringVar(&llmProvider, "provider", "", "LLM provider (claude, openai). Defaults to auto-detect from env")
+	cmd.Flags().StringVar(&llmModel, "model", "", "LLM model to use (overrides default)")
 
 	return cmd
 }
 
 func runDebug(cmd *cobra.Command, args []string) error {
 	problem := args[0]
 
-	// Validate that we have API key
-	apiKey := os.Getenv("ANTHROPIC_API_KEY")
-	if apiKey == "" {
-		return fmt.Errorf("ANTHROPIC_API_KEY environment variable not set")
-	}
-
 	// Validate inputs
 	if !allResources && len(resources) == 0 {
 		return fmt.Errorf("either specify resources with -r or use --all flag")
@@ -87,9 +87,9 @@ func runDebug(cmd *cobra.Command, args []string) error {
 
 	// Expand home symbol in kubeconfig if needed
 	if strings.HasPrefix(kubeconfig, "~/") {
-	    if homeDir, err := os.UserHomeDir(); err == nil {
-	        kubeconfig = filepath.Join(homeDir, kubeconfig[2:])
-	    }
+		if homeDir, err := os.UserHomeDir(); err == nil {
+			kubeconfig = filepath.Join(homeDir, kubeconfig[2:])
+		}
 	}
 
 	// Initialize K8s client
@@ -113,10 +113,27 @@ func runDebug(cmd *cobra.Command, args []string) error {
 	s.Stop()
 	printSuccess(fmt.Sprintf("Gathered %d resources", len(resourcesData)))
 
+	s.Suffix = " Initializing AI client..."
+	s.Start()
+
+	// Initialize LLM client using factory
+	llmClient, err := llm.CreateFromEnv(llmProvider, llmModel)
+	if err != nil {
+		s.Stop()
+		return fmt.Errorf("failed to initialize LLM client: %w", err)
+	}
+
+	s.Stop()
+	printSuccess("AI client initialized")
+
+	// Show LLM provider and model info
+	printLLMInfo(llmClient)
+	fmt.Println()
+
 	s.Suffix = " Analyzing with AI..."
 	s.Start()
 
-	aiAnalyzer := analyzer.New(apiKey)
+	aiAnalyzer := analyzer.NewWithLLM(llmClient)
 	analysis, err := aiAnalyzer.Analyze(problem, resourcesData)
 	if err != nil {
 		s.Stop()
@@ -146,6 +163,24 @@ func printHeader(problem string) {
 	fmt.Println()
 }
 
+func printLLMInfo(llmClient llm.LLM) {
+	// Get provider and model info from the LLM client
+	provider := "unknown"
+	model := "unknown"
+
+	// Type assertion to get provider and model information
+	switch client := llmClient.(type) {
+	case *llm.Claude:
+		provider = "claude"
+		model = client.GetModel()
+	case *llm.OpenAI:
+		provider = "openai"
+		model = client.GetModel()
+	}
+
+	fmt.Printf("🤖 LLM Provider: %s (%s)\n", provider, model)
+}
+
 func printSuccess(msg string) {
 	green := color.New(color.FgGreen)
 	green.Printf("✓ %s\n", msg)
@@ -154,4 +189,4 @@ func printSuccess(msg string) {
 func printError(msg string) {
 	red := color.New(color.FgRed)
 	red.Printf("✗ %s\n", msg)
-}
+}

krew-manifest.yaml

@@ -3,18 +3,19 @@ kind: Plugin
 metadata:
   name: ai
 spec:
-  version: v0.1.2
+  version: v0.1.3
   homepage: https://github.com/helmcode/kubectl-ai
   shortDescription: AI-powered Kubernetes debugging
   description: |
-    This plugin uses AI (Claude) to analyze Kubernetes resources and help debug
+    This plugin uses AI (Claude/OpenAI) to analyze Kubernetes resources and help debug
     configuration issues, performance problems, and provide actionable recommendations.
 
     Features:
     - Analyze any Kubernetes resource (native or CRD)
     - Get root cause analysis for issues
     - Receive actionable fix commands
     - Support for multiple output formats (human, json, yaml)
+    - Multiple LLM providers (Claude, OpenAI)
 
     Examples:
       # Debug a crashing deployment
@@ -26,12 +27,16 @@ spec:
       # Debug all resources in a namespace
       kubectl ai debug "high memory usage" -n production --all
   caveats: |
-    This plugin requires an Anthropic API key to function.
+    This plugin requires an API key from either Anthropic or OpenAI to function.
 
-    Before using, set your API key:
+    For Claude (default):
       export ANTHROPIC_API_KEY="your-api-key"
+      Get your API key at: https://console.anthropic.com/
 
-    Get your API key at: https://console.anthropic.com/
+    For OpenAI:
+      export OPENAI_API_KEY="your-api-key"
+      export LLM_PROVIDER="openai"  # Optional: auto-detects from API key
+      Get your API key at: https://platform.openai.com/
   platforms:
   - selector:
       matchLabels:

pkg/analyzer/analyzer.go

@@ -1,20 +1,39 @@
 package analyzer
 
 import (
-    "fmt"
+	"fmt"
 
-    "github.com/helmcode/kubectl-ai/pkg/llm"
-    "github.com/helmcode/kubectl-ai/pkg/parser"
-    "github.com/helmcode/kubectl-ai/pkg/prompts"
-    "github.com/helmcode/kubectl-ai/pkg/model"
+	"github.com/helmcode/kubectl-ai/pkg/llm"
+	"github.com/helmcode/kubectl-ai/pkg/model"
+	"github.com/helmcode/kubectl-ai/pkg/parser"
+	"github.com/helmcode/kubectl-ai/pkg/prompts"
 )
 
 type Analyzer struct {
-    llm llm.LLM
+	llm llm.LLM
 }
 
 func New(apiKey string) *Analyzer {
-    return &Analyzer{llm: llm.NewClaude(apiKey)}
+	// For backward compatibility, default to Claude
+	return &Analyzer{llm: llm.NewClaude(apiKey)}
+}
+
+func NewWithProvider(provider llm.Provider, config map[string]string) (*Analyzer, error) {
+	factory := llm.NewFactory()
+	llmInstance, err := factory.CreateLLM(provider, config)
+	if err != nil {
+		return nil, err
+	}
+	return &Analyzer{llm: llmInstance}, nil
+}
+
+func NewFromEnv() (*Analyzer, error) {
+	factory := llm.NewFactory()
+	llmInstance, err := factory.CreateFromEnv()
+	if err != nil {
+		return nil, err
+	}
+	return &Analyzer{llm: llmInstance}, nil
 }
 
 func NewWithLLM(l llm.LLM) *Analyzer {