diff --git a/lib/lib_llm.metta b/lib/lib_llm.metta
index ed78df5..430298e 100644
--- a/lib/lib_llm.metta
+++ b/lib/lib_llm.metta
@@ -1,3 +1,6 @@
+;Import Python helpers for OpenRouter
+!(import! &self (library lib_llm.py))
+
 ;Create string by appending the list entries
 (= (py-str-helper () $outp) $outp)
 (= (py-str-helper $L $outp)
@@ -17,11 +20,6 @@
 ;Add to builtins a function that can access by index:
 !(py-eval "setattr(__import__('builtins'),'index', (lambda o,i: o[i])) or 0")
 
-;Add to builtins a function that POST JSON to OpenRouter and return the assistant reply text
-!(py-eval "setattr(__import__('builtins'),'or_post',(lambda model,prompt,key: __import__('json').loads(__import__('urllib.request',fromlist=['urlopen','Request']).urlopen(__import__('urllib.request',fromlist=['Request']).Request('https://openrouter.ai/api/v1/chat/completions',__import__('json').dumps({'model':model,'messages':[{'role':'user','content':prompt}]}).encode('utf-8'),{'Authorization':'Bearer '+key,'Content-Type':'application/json'})).read())['choices'][0]['message']['content'])) or 0")
-;Add to builtins a function that POST to OpenRouter embeddings endpoint and return the embedding vector
-!(py-eval "setattr(__import__('builtins'),'or_embed',(lambda model,text,key: __import__('json').loads(__import__('urllib.request',fromlist=['urlopen','Request']).urlopen(__import__('urllib.request',fromlist=['Request']).Request('https://openrouter.ai/api/v1/embeddings',__import__('json').dumps({'model':model,'input':text}).encode('utf-8'),{'Authorization':'Bearer '+key,'Content-Type':'application/json'})).read())['data'][0]['embedding'])) or 0")
-
 ;Function to prompt GPT via OpenAI API:
 (= (useGPT $prompt)
    (useGPT gpt-5.2 1000000 medium $prompt))
@@ -39,9 +37,9 @@
 
 ;Function to prompt a model via OpenRouter API:
 (= (useOpenRouter $model $prompt)
-   (let* (($apikey (once (py-eval "__import__('os').environ.get('OPENROUTER_API_KEY','')")))
-          ($text (once (py-call (builtins.or_post $model $prompt $apikey)))))
-         $text))
+   (useOpenRouter $model 100000 medium $prompt))
+(= (useOpenRouter $model $max_tokens $effort $prompt)
+   (py-call (lib_llm.openrouter_chat $model $prompt $max_tokens $effort)))
 
 (= (sread-safe $w)
    (case (catch (sread $w))
@@ -62,6 +60,4 @@
          $vector))
 
 (= (useOpenRouterEmbedding $model $text)
-   (let* (($apikey (once (py-eval "__import__('os').environ.get('OPENROUTER_API_KEY','')")))
-          ($vector (once (py-call (builtins.or_embed $model $text $apikey)))))
-         $vector))
+   (py-call (lib_llm.openrouter_embed $model $text)))
diff --git a/lib/lib_llm.py b/lib/lib_llm.py
new file mode 100644
index 0000000..8fa76a7
--- /dev/null
+++ b/lib/lib_llm.py
@@ -0,0 +1,33 @@
+import json
+import os
+import urllib.request
+
+def openrouter_chat(model, prompt, max_tokens, effort):
+    key = os.environ.get('OPENROUTER_API_KEY', '')
+    data = json.dumps({
+        'model': model,
+        'messages': [{'role': 'user', 'content': prompt}],
+        'max_tokens': max_tokens,
+        'reasoning': {'effort': effort}
+    }).encode('utf-8')
+    req = urllib.request.Request(
+        'https://openrouter.ai/api/v1/chat/completions',
+        data,
+        {'Authorization': 'Bearer ' + key, 'Content-Type': 'application/json'}
+    )
+    response = urllib.request.urlopen(req).read()
+    return json.loads(response)['choices'][0]['message']['content']
+
+def openrouter_embed(model, text):
+    key = os.environ.get('OPENROUTER_API_KEY', '')
+    data = json.dumps({
+        'model': model,
+        'input': text
+    }).encode('utf-8')
+    req = urllib.request.Request(
+        'https://openrouter.ai/api/v1/embeddings',
+        data,
+        {'Authorization': 'Bearer ' + key, 'Content-Type': 'application/json'}
+    )
+    response = urllib.request.urlopen(req).read()
+    return json.loads(response)['data'][0]['embedding']