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lib/ai/client/README.md

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+# AIClient Factory
+
+This directory contains the implementation of the `AIClient` factory, which provides a unified interface for interacting with various Large Language Model (LLM) providers such as Groq and OpenRouter. It leverages the existing OpenAI client infrastructure to abstract away the differences between providers.
+
+## File Structure
+
+-   [`aiclient.v`](lib/ai/client/aiclient.v): The main factory and core functions for the `AIClient`.
+-   [`aiclient_models.v`](lib/ai/client/aiclient_models.v): Defines LLM model enums and their mapping to specific model names and API base URLs.
+-   [`aiclient_llm.v`](lib/ai/client/aiclient_llm.v): Handles the initialization of various LLM provider clients.
+-   [`aiclient_embed.v`](lib/ai/client/aiclient_embed.v): Provides functions for generating embeddings using the configured LLM models.
+-   [`aiclient_write.v`](lib/ai/client/aiclient_write.v): Implements complex file writing logic, including backup, AI-driven modification, content validation, and retry mechanisms.
+-   [`aiclient_validate.v`](lib/ai/client/aiclient_validate.v): Contains placeholder functions for validating different file types (Vlang, Markdown, YAML, JSON).
+
+## Usage
+
+To use the `AIClient`, you first need to initialize it:
+
+```v
+import aiclient
+
+mut client := aiclient.new()!
+```
+
+Ensure that the necessary environment variables (`GROQKEY` and `OPENROUTER_API_KEY`) are set for the LLM providers.
+
+## Environment Variables
+
+-   `GROQKEY`: API key for Groq.
+-   `OPENROUTER_API_KEY`: API key for OpenRouter.
+
+## Key Features
+
+```bash
+v install prantlf.yaml
+v install markdown
+```

lib/ai/client/aiclient.v

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+module client
+
+import incubaid.herolib.core.pathlib
+
+@[heap]
+pub struct AIClient {
+pub mut:
+	llms AIClientLLMs
+	// Add other fields as needed
+}
+
+pub fn new() !AIClient {
+	llms := llms_init()!
+	return AIClient{
+		llms: llms
+	}
+}

lib/ai/client/aiclient_embed.v

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+module client
+
+// pub fn (mut ac AIClient) embed(txt string) ![]f32 {
+// 	return ac.llms.llm_embed.embeddings(txt)!
+// }

lib/ai/client/aiclient_llm.v

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+module client
+
+import incubaid.herolib.clients.openai
+import os
+
+pub struct AIClientLLMs {
+pub mut:
+	llm_maverick &openai.OpenAI
+	llm_qwen     &openai.OpenAI
+	llm_120b     &openai.OpenAI
+	llm_best     &openai.OpenAI
+	llm_flash    &openai.OpenAI
+	llm_pro      &openai.OpenAI
+	llm_morph    &openai.OpenAI
+	llm_embed    &openai.OpenAI
+}
+
+// Initialize all LLM clients
+pub fn llms_init() !AIClientLLMs {
+	groq_key := os.getenv('GROQKEY')
+	if groq_key.len == 0 {
+		return error('GROQKEY environment variable not set')
+	}
+
+	openrouter_key := os.getenv('OPENROUTER_API_KEY')
+	if openrouter_key.len == 0 {
+		return error('OPENROUTER_API_KEY environment variable not set')
+	}
+
+	mut maverick_client := openai.OpenAI{
+		name:          'maverick'
+		api_key:       groq_key
+		url:           'https://api.groq.com/openai/v1'
+		model_default: 'meta-llama/llama-4-maverick-17b-128e-instruct'
+	}
+	openai.set(maverick_client)!
+
+	mut qwen_client := openai.OpenAI{
+		name:          'qwen'
+		api_key:       groq_key
+		url:           'https://api.groq.com/openai/v1'
+		model_default: 'qwen/qwen3-32b'
+	}
+	openai.set(qwen_client)!
+
+	mut llm_120b_client := openai.OpenAI{
+		name:          'llm_120b'
+		api_key:       groq_key
+		url:           'https://api.groq.com/openai/v1'
+		model_default: 'openai/gpt-oss-120b'
+	}
+	openai.set(llm_120b_client)!
+
+	mut best_client := openai.OpenAI{
+		name:          'best'
+		api_key:       openrouter_key
+		url:           'https://api.openrouter.ai/api/v1'
+		model_default: 'anthropic/claude-haiku-4.5'
+	}
+	openai.set(best_client)!
+
+	mut flash_client := openai.OpenAI{
+		name:          'flash'
+		api_key:       openrouter_key
+		url:           'https://api.openrouter.ai/api/v1'
+		model_default: 'google/gemini-2.5-flash'
+	}
+	openai.set(flash_client)!
+
+	mut pro_client := openai.OpenAI{
+		name:          'pro'
+		api_key:       openrouter_key
+		url:           'https://api.openrouter.ai/api/v1'
+		model_default: 'google/gemini-2.5-pro'
+	}
+	openai.set(pro_client)!
+
+	mut morph_client := openai.OpenAI{
+		name:          'morph'
+		api_key:       openrouter_key
+		url:           'https://api.openrouter.ai/api/v1'
+		model_default: 'morph/morph-v3-fast'
+	}
+	openai.set(morph_client)!
+
+	mut embed_client := openai.OpenAI{
+		name:          'embed'
+		api_key:       openrouter_key
+		url:           'https://api.openrouter.ai/api/v1'
+		model_default: 'qwen/qwen3-embedding-0.6b'
+	}
+	openai.set(embed_client)!
+
+	return AIClientLLMs{
+		llm_maverick: openai.get(name: 'maverick')!
+		llm_qwen:     openai.get(name: 'qwen')!
+		llm_120b:     openai.get(name: 'llm_120b')!
+		llm_best:     openai.get(name: 'best')!
+		llm_flash:    openai.get(name: 'flash')!
+		llm_pro:      openai.get(name: 'pro')!
+		llm_morph:    openai.get(name: 'morph')!
+		llm_embed:    openai.get(name: 'embed')!
+	}
+}

lib/ai/client/aiclient_models.v

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+module client
+
+pub enum LLMEnum {
+	maverick
+	qwen
+	embed
+	llm_120b
+	best
+	flash
+	pro
+	morph
+}
+
+fn llm_to_model_url(model LLMEnum) !(string, string) {
+	// Returns tuple: (model_name, base_url)
+	return match model {
+		.maverick { 'meta-llama/llama-4-maverick-17b-128e-instruct', 'https://api.groq.com/openai/v1' }
+		.qwen { 'qwen/qwen3-32b', 'https://api.groq.com/openai/v1' }
+		.embed { 'qwen/qwen3-embedding-0.6b', 'https://api.openrouter.ai/api/v1' }
+		.llm_120b { 'openai/gpt-oss-120b', 'https://api.groq.com/openai/v1' }
+		.best { 'anthropic/claude-haiku-4.5', 'https://api.openrouter.ai/api/v1' }
+		.flash { 'google/gemini-2.5-flash', 'https://api.openrouter.ai/api/v1' }
+		.pro { 'google/gemini-2.5-pro', 'https://api.openrouter.ai/api/v1' }
+		.morph { 'morph/morph-v3-fast', 'https://api.openrouter.ai/api/v1' }
+	}
+}

lib/ai/client/aiclient_validate.v

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+module client
+
+import incubaid.herolib.core.pathlib
+import markdown
+import os
+import prantlf.yaml { parse_text }
+import x.json2
+
+pub fn validate_vlang_content(path pathlib.Path) !string {
+	// Use `v fmt -check` to validate V language syntax
+	// If there are any formatting issues, `v fmt -check` will return a non-zero exit code
+	// and print the issues to stderr.
+	res := os.system('v fmt -check ${path.str()}')
+	if res != 0 {
+		return 'V language syntax validation failed. Please check the file for errors.'
+	}
+	// TODO: do 'v filepath' d and check if errors return, if no, then remove the compiled binary if its there, if it goes wrong do same
+	return '' // empty means no error
+}
+
+pub fn validate_markdown_content(path_ pathlib.Path) !string {
+	// Implement Markdown validation by attempting to convert to HTML
+	// If there's an error during conversion, it indicates invalid Markdown.
+	mut mypath := path_
+	content := mypath.read() or { return 'Failed to read markdown file: ${err}' }
+	mut xx := markdown.HtmlRenderer{}
+	_ := markdown.render(content, mut xx) or { return 'Invalid Markdown content: ${err}' }
+	return '' // empty means no error
+}
+
+pub fn validate_yaml_content(path_ pathlib.Path) !string {
+	// Implement YAML validation by attempting to load the content
+	mut mypath := path_
+	content := mypath.read() or { return 'Failed to read YAML file: ${err}' }
+	_ := parse_text(content) or { return 'Invalid YAML content: ${err}' }
+	return '' // empty means no error
+}
+
+pub fn validate_json_content(path_ pathlib.Path) !string {
+	// Implement JSON validation by attempting to decode the content
+	mut mypath := path_
+	content := mypath.read() or { return 'Failed to read JSON file: ${err}' }
+	json2.decode[json2.Any](content) or { return 'Invalid JSON content: ${err}' }
+	return '' // empty means no error
+}

lib/ai/client/aiclient_write.v

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+module client
+
+import incubaid.herolib.core.pathlib
+import incubaid.herolib.ui.console
+import incubaid.herolib.clients.openai
+import os
+
+// TODO: do as params for the function
+
+pub fn (mut ac AIClient) write_from_prompt(path_ pathlib.Path, prompt string, models []LLMEnum) ! {
+	mut mypath := path_
+	original_content := mypath.read()!
+	mut backup_path := pathlib.get_file(path: '${mypath.path}.backup', create: true)!
+	backup_path.write(original_content)!
+
+	mut selected_models := models.clone()
+	if selected_models.len == 0 {
+		selected_models = [.best] // Default to best model if none provided
+	}
+
+	for model_enum in selected_models {
+		model_name, base_url := llm_to_model_url(model_enum)!
+		mut llm_client := openai.get(name: model_enum.str())! // Assuming model_enum.str() matches the name used in llms_init
+
+		// 3. Use first model (or default best) to process prompt
+		// This part needs to be implemented based on how the OpenAI client's chat completion works
+		// For now, let's assume a simple completion call
+		// This is a placeholder and needs actual implementation based on the OpenAI client's chat completion method
+		// For example:
+		// completion := llm_client.chat_completion(prompt)!
+		// instructions := completion.choices[0].message.content
+
+		// For now, let's just use the prompt as the "instructions" for modification
+		instructions := prompt
+
+		// 5. Use morph model to merge original + instructions
+		// This is a placeholder for the merging logic
+		// For now, let's just replace the content with instructions
+		new_content := instructions // This needs to be replaced with actual merging logic
+
+		// 6. Validate content based on file extension
+		mut validation_error := ''
+		match mypath.ext()! {
+			'.v' {
+				validation_error = validate_vlang_content(mypath)!
+			}
+			'.md' {
+				validation_error = validate_markdown_content(mypath)!
+			}
+			'.yaml', '.yml' {
+				validation_error = validate_yaml_content(mypath)!
+			}
+			'.json' {
+				validation_error = validate_json_content(mypath)!
+			}
+			else {
+				// No specific validation for other file types
+			}
+		}
+
+		if validation_error == '' {
+			// Validation passed - write new content
+			mypath.write(new_content)!
+			backup_path.delete()! // Remove backup on success
+			return
+		} else {
+			console.print_stderr('Validation failed for model ${model_name}. Error: ${validation_error}. Trying next model...')
+		}
+	}
+
+	// 8. If all fail, restore .backup and error
+	original_backup := backup_path.read()!
+	mypath.write(original_backup)!
+	backup_path.delete()!
+	return error('All models failed to generate valid content. Original file restored.')
+}