diff --git a/setup.cfg b/setup.cfg
index d95117d..e0e98e2 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,11 +1,11 @@
 [metadata]
 name = napari-chatgpt
-version = v2024.3.26
+version = v2024.3.26.3
 description = A napari plugin to process and analyse images with chatGPT.
 long_description = file: README.md
 long_description_content_type = text/markdown
 url = https://github.com/royerlab/napari-chatgpt
-author = Loic A. Royer
+author = Loic A. Royer and contributors
 author_email = royerloic@gmail.com
 license = BSD-3-Clause
 license_files = LICENSE
@@ -38,6 +38,7 @@ install_requires =
     QtAwesome
     langchain==0.1.11
     langchain-openai==0.0.8
+    langchain-anthropic==0.1.4
     openai==1.13.3
     anthropic
     fastapi
diff --git a/src/napari_chatgpt/_widget.py b/src/napari_chatgpt/_widget.py
index edeb3da..504aea7 100644
--- a/src/napari_chatgpt/_widget.py
+++ b/src/napari_chatgpt/_widget.py
@@ -126,8 +126,8 @@ def _model_selection(self):
             model_list.append('claude-2.1')
             model_list.append('claude-2.0')
             model_list.append('claude-instant-1.2')
-            #model_list.append('claude-3-sonnet-20240229')
-            #model_list.append('claude-3-opus-20240229')
+            model_list.append('claude-3-sonnet-20240229')
+            model_list.append('claude-3-opus-20240229')
 
 
         if is_ollama_running():
@@ -450,14 +450,14 @@ def _start_omega(self):
                 main_llm_model_name = self.model_combo_box.currentText()
 
                 # Warn users with a modal window that the selected model might be sub-optimal:
-                if 'gpt-4' not in main_llm_model_name:
+                if 'gpt-4' not in main_llm_model_name and 'claude-3-opus' not in main_llm_model_name:
                     aprint("Warning: you did not select a gpt-4 level model. Omega's cognitive and coding abilities will be degraded.")
                     show_warning_dialog(f"You have selected this model: '{main_llm_model_name}'. "
-                                        f"This is not a GPT4-level model. "
+                                        f"This is not a GPT4 or Claude-3-opus level model. "
                                         f"Omega's cognitive and coding abilities will be degraded. "
                                         f"It might even completely fail or be too slow. "
                                         f"Please visit <a href='https://github.com/royerlab/napari-chatgpt/wiki/OpenAIKey'>our wiki</a> "
-                                        f"for information on how to gain access to GPT4.")
+                                        f"for information on how to gain access to GPT4 (or Claude-3).")
 
                 # Set tool LLM model name via configuration file.
                 tool_llm_model_name = self.config.get('tool_llm_model_name', 'same')
diff --git a/src/napari_chatgpt/llm/llms.py b/src/napari_chatgpt/llm/llms.py
index fae7e99..aaad6d9 100644
--- a/src/napari_chatgpt/llm/llms.py
+++ b/src/napari_chatgpt/llm/llms.py
@@ -63,9 +63,16 @@ def _instantiate_single_llm(llm_model_name: str,
     elif 'claude' in llm_model_name:
 
         # Import Claude LLM:
-        from langchain.chat_models import ChatAnthropic
+        from langchain_anthropic import ChatAnthropic
 
-        max_token_limit = 8000
+        llm_model_name_lc = llm_model_name.lower()
+
+        if 'opus' in llm_model_name_lc or 'sonnet' in llm_model_name_lc or 'hiaku' in llm_model_name_lc or '2.1':
+            max_tokens_to_sample = 4096
+            max_token_limit = 200000
+        else:
+            max_tokens_to_sample = 4096
+            max_token_limit = 8000
 
         # Instantiates Main LLM:
         llm = ChatAnthropic(
@@ -73,7 +80,7 @@ def _instantiate_single_llm(llm_model_name: str,
             verbose=verbose,
             streaming=streaming,
             temperature=temperature,
-            max_tokens_to_sample=max_token_limit,
+            max_tokens_to_sample=max_tokens_to_sample,
             callbacks=[callback_handler])
 
         return llm, max_token_limit
@@ -103,7 +110,7 @@ def _instantiate_single_llm(llm_model_name: str,
             # Wait a bit:
             sleep(3)
 
-        # Make ure that Ollama is running
+        # Make sure that Ollama is running
         if not is_ollama_running(ollama_host, ollama_port):
             aprint(f"Ollama server is not running on '{ollama_host}'. Please start the Ollama server on this machine and make sure the port '{ollama_port}' is open. ")
             raise Exception("Ollama server is not running!")