...

examples/ai/aiclient.vsh

@@ -0,0 +1,17 @@
+#!/usr/bin/env -S v -n -w -gc none  -cc tcc -d use_openssl -enable-globals run
+
+import incubaid.herolib.ai.client
+
+mut cl := client.new()!
+
+// response := cl.llms.llm_local.chat_completion(
+// 	message:               'Explain quantum computing in simple terms'
+// 	temperature:           0.5
+// 	max_completion_tokens: 1024
+// )!
+
+response := cl.llms.llm_embed_local.embed(input: [
+	'The food was delicious and the waiter..',
+])!
+
+println(response)

examples/ai/groq.vsh

@@ -1,7 +1,5 @@
 #!/usr/bin/env -S v -n -w -gc none  -cc tcc -d use_openssl -enable-globals run
 
-module main
-
 import incubaid.herolib.clients.openai
 import os
 import incubaid.herolib.core.playcmds
@@ -10,8 +8,8 @@ import incubaid.herolib.core.playcmds
 
 playcmds.run(
 	heroscript: '
-        !!openai.configure name:"groq" 
+        !!openai.configure name:"groq"
-            url:"https://api.groq.com/openai/v1" 
+            url:"https://api.groq.com/openai/v1"
             model_default:"openai/gpt-oss-120b"
     '
 	reset:      true

lib/ai/client/aiclient.v

@@ -1,7 +1,5 @@
 module client
 
-import incubaid.herolib.core.pathlib
-
 @[heap]
 pub struct AIClient {
 pub mut:

lib/ai/client/aiclient_llm.v

@@ -5,14 +5,16 @@ import os
 
 pub struct AIClientLLMs {
 pub mut:
-	llm_maverick &openai.OpenAI
+	llm_maverick    &openai.OpenAI
-	llm_qwen     &openai.OpenAI
+	llm_qwen        &openai.OpenAI
-	llm_120b     &openai.OpenAI
+	llm_120b        &openai.OpenAI
-	llm_best     &openai.OpenAI
+	llm_best        &openai.OpenAI
-	llm_flash    &openai.OpenAI
+	llm_flash       &openai.OpenAI
-	llm_pro      &openai.OpenAI
+	llm_pro         &openai.OpenAI
-	llm_morph    &openai.OpenAI
+	llm_morph       &openai.OpenAI
-	llm_embed    &openai.OpenAI
+	llm_embed       &openai.OpenAI
+	llm_local       &openai.OpenAI
+	llm_embed_local &openai.OpenAI
 }
 
 // Initialize all LLM clients
@@ -71,7 +73,7 @@ pub fn llms_init() !AIClientLLMs {
 		name:          'pro'
 		api_key:       openrouter_key
 		url:           'https://api.openrouter.ai/api/v1'
-		model_default: 'google/gemini-2.5-pro'
+		model_default: 'google/gemini-3.0-pro'
 	}
 	openai.set(pro_client)!
 
@@ -91,14 +93,30 @@ pub fn llms_init() !AIClientLLMs {
 	}
 	openai.set(embed_client)!
 
+	mut local_client := openai.OpenAI{
+		name:          'local'
+		url:           'http://localhost:1234/v1'
+		model_default: 'google/gemma-3-12b'
+	}
+	openai.set(local_client)!
+
+	mut local_embed_client := openai.OpenAI{
+		name:          'embedlocal'
+		url:           'http://localhost:1234/v1'
+		model_default: 'text-embedding-nomic-embed-text-v1.5:2'
+	}
+	openai.set(local_embed_client)!
+
 	return AIClientLLMs{
-		llm_maverick: openai.get(name: 'maverick')!
+		llm_maverick:    openai.get(name: 'maverick')!
-		llm_qwen:     openai.get(name: 'qwen')!
+		llm_qwen:        openai.get(name: 'qwen')!
-		llm_120b:     openai.get(name: 'llm_120b')!
+		llm_120b:        openai.get(name: 'llm_120b')!
-		llm_best:     openai.get(name: 'best')!
+		llm_best:        openai.get(name: 'best')!
-		llm_flash:    openai.get(name: 'flash')!
+		llm_flash:       openai.get(name: 'flash')!
-		llm_pro:      openai.get(name: 'pro')!
+		llm_pro:         openai.get(name: 'pro')!
-		llm_morph:    openai.get(name: 'morph')!
+		llm_morph:       openai.get(name: 'morph')!
-		llm_embed:    openai.get(name: 'embed')!
+		llm_embed:       openai.get(name: 'embed')!
+		llm_local:       openai.get(name: 'local')!
+		llm_embed_local: openai.get(name: 'embedlocal')!
 	}
 }

lib/ai/client/aiclient_models.v

@@ -9,6 +9,7 @@ pub enum LLMEnum {
 	flash
 	pro
 	morph
+	local
 }
 
 fn llm_to_model_url(model LLMEnum) !(string, string) {
@@ -22,5 +23,6 @@ fn llm_to_model_url(model LLMEnum) !(string, string) {
 		.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' }
+		.local { 'google/gemma-3-12b', 'http://localhost:1234/v1' }
 	}
 }

lib/clients/openai/completions.v

@@ -84,8 +84,10 @@ pub fn (mut f OpenAI) chat_completion(args_ CompletionArgs) !ChatCompletion {
 		m.messages << mr
 	}
 	data := json.encode(m)
-	// println('data: ${data}')
+	println('data: ${data}')
+
 	mut conn := f.connection()!
+	println(conn)
 	r := conn.post_json_str(prefix: 'chat/completions', data: data)!
 
 	res := json.decode(ChatCompletionRaw, r)!

lib/clients/openai/embeddings.v

@@ -0,0 +1,49 @@
+module openai
+
+import json
+
+// pub enum EmbeddingModel {
+// 	text_embedding_ada
+// }
+
+// fn embedding_model_str(e EmbeddingModel) string {
+// 	return match e {
+// 		.text_embedding_ada {
+// 			'text-embedding-ada-002'
+// 		}
+// 	}
+// }
+
+@[params]
+pub struct EmbeddingCreateRequest {
+pub mut:
+	input []string @[required]
+	model string
+	user  string
+}
+
+pub struct Embedding {
+pub mut:
+	object    string
+	embedding []f32
+	index     int
+}
+
+pub struct EmbeddingResponse {
+pub mut:
+	object string
+	data   []Embedding
+	model  string
+	usage  Usage
+}
+
+pub fn (mut f OpenAI) embed(args_ EmbeddingCreateRequest) !EmbeddingResponse {
+	mut args := args_
+	if args.model == '' {
+		args.model = f.model_default
+	}
+	data := json.encode(args)
+	mut conn := f.connection()!
+	r := conn.post_json_str(prefix: 'embeddings', data: data)!
+	return json.decode(EmbeddingResponse, r)!
+}

lib/clients/openai/embeddings/README.md

@@ -1,17 +0,0 @@
-
-# Quick Example: Creating Embeddings
-
-```v
-
-import incubaid.herolib.clients.openai
-
-mut client:= openai.get()! //will be the default client, key is in `AIKEY` on environment variable or `OPENROUTER_API_KEY`
-
-text_to_embed := 'The quick brown fox jumps over the lazy dog.'
-
-resp := client.embeddings.create_embedding(
-    input: text_to_embed,
-    model: 'text-embedding-ada-002'
-)!
-
-```

lib/clients/openai/embeddings/embeddings.v

@@ -1,59 +0,0 @@
-module embeddings
-
-import json
-import incubaid.herolib.clients.openai { OpenAI, Usage }
-
-type OpenAIAlias = OpenAI
-
-pub enum EmbeddingModel {
-	text_embedding_ada
-}
-
-fn embedding_model_str(e EmbeddingModel) string {
-	return match e {
-		.text_embedding_ada {
-			'text-embedding-ada-002'
-		}
-	}
-}
-
-@[params]
-pub struct EmbeddingCreateArgs {
-	input []string       @[required]
-	model EmbeddingModel @[required]
-	user  string
-}
-
-pub struct EmbeddingCreateRequest {
-	input []string
-	model string
-	user  string
-}
-
-pub struct Embedding {
-pub mut:
-	object    string
-	embedding []f32
-	index     int
-}
-
-pub struct EmbeddingResponse {
-pub mut:
-	object string
-	data   []Embedding
-	model  string
-	usage  Usage
-}
-
-pub fn (mut f OpenAIAlias) create_embeddings(args EmbeddingCreateArgs) !EmbeddingResponse {
-	req := EmbeddingCreateRequest{
-		input: args.input
-		model: embedding_model_str(args.model)
-		user:  args.user
-	}
-	data := json.encode(req)
-
-	mut conn := f.connection()!
-	r := conn.post_json_str(prefix: 'embeddings', data: data)!
-	return json.decode(EmbeddingResponse, r)!
-}

lib/clients/openai/openai_model.v

@@ -52,9 +52,9 @@ fn obj_init(mycfg_ OpenAI) !OpenAI {
 			}
 		}
 	}
-	if mycfg.api_key == '' {
+	// if mycfg.api_key == '' {
-		return error('OpenAI client "${mycfg.name}" missing api_key')
+	// 	return error('OpenAI client "${mycfg.name}" missing api_key')
-	}
+	// }
 	return mycfg
 }