improved Jordao's napari reader pluginin file open tool,

and OpenAI and Anthropic model list code. Also made web search tests more robust to rate limits.

src/napari_chatgpt/_widget.py

@@ -17,11 +17,13 @@
 from qtpy.QtWidgets import QVBoxLayout, QComboBox
 
 from microplugin.microplugin_window import MicroPluginMainWindow
+from napari_chatgpt.utils.anthropic.model_list import get_anthropic_model_list
 from napari_chatgpt.utils.configuration.app_configuration import \
     AppConfiguration
 from napari_chatgpt.utils.ollama.ollama_server import is_ollama_running, \
     get_ollama_models
-from napari_chatgpt.utils.openai.model_list import get_openai_model_list
+from napari_chatgpt.utils.openai.model_list import get_openai_model_list, \
+    postprocess_openai_model_list
 from napari_chatgpt.utils.python.installed_packages import \
     is_package_installed
 from napari_chatgpt.utils.qt.one_time_disclaimer_dialog import \
@@ -123,44 +125,15 @@ def _model_selection(self):
 
         if is_package_installed('anthropic'):
             # Add Anthropic models to the combo box:
-            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.extend(get_anthropic_model_list())
 
         if is_ollama_running():
             ollama_models = get_ollama_models()
             for ollama_model in ollama_models:
                 model_list.append('ollama_'+ollama_model)
 
-        # Postprocess model list:
-
-        # Special cases (common prefix):
-        if 'gpt-3.5-turbo' in model_list:
-            model_list.remove('gpt-3.5-turbo')
-
-        # get list of bad models for main LLM:
-        bad_models_filters = ['0613', 'vision', 'turbo-instruct', 'gpt-3.5-turbo-0301', 'gpt-3.5-turbo-16k']
-
-        # get list of best models for main LLM:
-        best_models_filters = ['0314', '0301', '1106', 'gpt-4']
-
-        # Ensure that some 'bad' or unsupported models are excluded:
-        bad_models = [m for m in model_list if any(bm in m for bm in bad_models_filters)]
-        for bad_model in bad_models:
-            if bad_model in model_list:
-                model_list.remove(bad_model)
-                # model_list.append(bad_model)
-
-        # Ensure that the best models are at the top of the list:
-        best_models = [m for m in model_list if any(bm in m for bm in best_models_filters)]
-        model_list = best_models + [m for m in model_list if m not in best_models]
-
-        # Ensure that the very best models are at the top of the list:
-        very_best_models = [m for m in model_list if ('gpt-4-turbo-2024-04-09' in m) ]
-        model_list = very_best_models + [m for m in model_list if m not in very_best_models]
+        # Postprocess OpenAI model list:
+        model_list = postprocess_openai_model_list(model_list)
 
         # normalise list:
         model_list = list(model_list)

src/napari_chatgpt/omega/tools/napari/file_open_tool.py

@@ -16,7 +16,7 @@ class NapariFileOpenTool(NapariBaseTool):
         "Use this tool when you need to open image files in napari. "
         "Input must be a plain text list of local file paths or URLs to be opened. "
         "The list must be \\n delimited, i.e one entry per line. "
-        "The first item on the list must be the requested 'napari-plugin', if none is provided, use 'napari'."
+        "For for each file a specific napari reader plugin can be specified within brackets: 'file_path_or_url [reader_plugin_name]'. "
         "This tool can only open image files with these extensions: .tif, .png, .jpg, .zarr, and more... "
         "For example, if the input is: 'file1.tif\\nfile2.tif\\nfile3.tif' then this tool will open three images in napari. "
         "This tool cannot open text files or other non-image files. "
@@ -28,26 +28,34 @@ def _run_code(self, query: str, code: str, viewer: Viewer) -> str:
 
         with asection(f"NapariFileOpenTool: query= {query} "):
 
-            # Split lines:
-            lines = query.splitlines()
-
             # Files opened:
             opened_files = []
 
             # Errors encountered:
             encountered_errors = []
 
-            plugin = lines[0]
+            # Split lines:
+            lines = query.splitlines()
+
+            # Remove any whitespace from the list entries:
+            lines = [line.strip() for line in lines]
 
-            for line in lines[1:]:
+            for line in lines:
 
                 # Remove whitespaces:
                 line = line.strip()
 
-                aprint(f"Trying to open file: '{line}' ")
+                # Check if a plugin is specified:
+                if '[' in line and ']' in line:
+                    plugin = line[line.index('[') + 1:line.index(']')].strip()
+                    line = line[:line.index('[')].strip()
+                else:
+                    plugin = None
 
                 # Try to open file:
                 try:
+                    aprint(f"Trying to open file: '{line}' with plugin '{plugin}'")
+
                     success = open_in_napari(viewer, line, plugin=plugin)
 
                     if success:
@@ -62,16 +70,17 @@ def _run_code(self, query: str, code: str, viewer: Viewer) -> str:
             # Encountered errors string:
             encountered_errors_str = '\n'.join(encountered_errors)
 
-            aprint(
-                f"Encountered the following errors while trying to open the files:\n" \
-                f"{encountered_errors_str}\n")
+            if encountered_errors:
+                aprint(
+                    f"Encountered the following errors while trying to open the files:\n" \
+                    f"{encountered_errors_str}\n")
 
             # Return outcome:
-            if len(opened_files) == len(lines):
+            if len(opened_files) == len(lines) and len(encountered_errors) == 0:
                 result = f"All of the image files: '{', '.join(opened_files)}' could be successfully opened in napari. "
                 aprint(result)
                 return result
-            elif len(opened_files) > 0:
+            elif len(opened_files) > 0 and len(encountered_errors) > 0:
                 result = f"Some of the image files: '{', '.join(opened_files)}' could be successfully opened in napari.\n" \
                          f"Here are the exceptions, if any, that occurred:\n" \
                          f"{encountered_errors_str}.\n"

src/napari_chatgpt/utils/anthropic/model_list.py

@@ -0,0 +1,36 @@
+import traceback
+
+from arbol import asection, aprint
+
+from napari_chatgpt.utils.api_keys.api_key import set_api_key
+
+
+
+
+def get_anthropic_model_list() -> list:
+    """
+    Get the list of all Anthropic  models.
+
+    Parameters
+    ----------
+    filter : str
+        Filter to apply to the list of models.
+    Returns
+    -------
+    list
+        List of models.
+
+    """
+
+    with asection(f"Enumerating all Anthropic models:"):
+        model_list = []
+
+        model_list.append('claude-3-opus-20240229')
+        model_list.append('claude-3-sonnet-20240229')
+        model_list.append('claude-3-haiku-20240307')
+        model_list.append('claude-3-5-sonnet-20240620')
+
+        return model_list
+
+
+

src/napari_chatgpt/utils/openai/model_list.py

@@ -1,6 +1,7 @@
 import traceback
 
 from arbol import asection, aprint
+from exceptiongroup import catch
 
 from napari_chatgpt.utils.api_keys.api_key import set_api_key
 
@@ -60,3 +61,65 @@ def get_openai_model_list(filter: str = 'gpt', verbose: bool = False) -> list:
 
             return []
 
+
+def postprocess_openai_model_list(model_list: list) -> list:
+    """
+    Postprocess the list of OpenAI models. This is usefull to remove problematic models from the list and sort models in decreasing order of quality.
+
+    Parameters
+    ----------
+    model_list : list
+        List of models.
+
+    Returns
+    -------
+    list
+        Postprocessed list of models.
+
+    """
+
+    try:
+
+        # get list of bad models for main LLM:
+        bad_models_filters = ['0613', 'vision',
+                              'turbo-instruct',
+                              'gpt-3.5-turbo',
+                              'gpt-3.5-turbo-0613',
+                              'gpt-3.5-turbo-0301',
+                              'gpt-3.5-turbo-1106',
+                              'gpt-3.5-turbo-0125',
+                              'gpt-3.5-turbo-16k',
+                              'chatgpt-4o-latest']
+
+        # get list of best models for main LLM:
+        best_models_filters = ['0314', '0301', '1106', 'gpt-4', 'gpt-4o']
+
+        # Ensure that some 'bad' or unsupported models are excluded:
+        bad_models = [m for m in model_list if
+                      any(bm in m for bm in bad_models_filters)]
+        for bad_model in bad_models:
+            if bad_model in model_list:
+                model_list.remove(bad_model)
+                # model_list.append(bad_model)
+
+        # Ensure that the best models are at the top of the list:
+        best_models = [m for m in model_list if
+                       any(bm in m for bm in best_models_filters)]
+        model_list = best_models + [m for m in model_list if m not in best_models]
+
+        # Ensure that the very best models are at the top of the list:
+        very_best_models = [m for m in model_list if
+                            ('gpt-4o' in m)]
+        model_list = very_best_models + [m for m in model_list if
+                                         m not in very_best_models]
+
+    except Exception as e:
+        aprint("Error {e} occured while postprocessing the list of OpenAI models!")
+
+        # print stacktrace:
+        traceback.print_exc()
+
+    finally:
+
+        # If anything goes wrong we safely return the model list:
+        return model_list

src/napari_chatgpt/utils/python/test/python_lang_utils_test.py

@@ -129,7 +129,8 @@ def test_get_function_signature():
 
     signature = get_function_signature('numpy.zeros_like', include_docstring=True)
     aprint(signature)
-    assert 'zeros_like(a, dtype, order, subok, shape)' in signature
+
+    assert 'zeros_like(a, dtype, order, subok, shape, device)' in signature or 'zeros_like(a, dtype, order, subok, shape)' in signature
     assert 'shape : int or sequence of ints, optional.' in signature
 
     print('\n\n')

src/napari_chatgpt/utils/web/test/duckduckgo_test.py

@@ -1,5 +1,6 @@
 import pytest
 from arbol import aprint
+from duckduckgo_search.exceptions import RatelimitException
 
 from napari_chatgpt.utils.api_keys.api_key import is_api_key_available
 from napari_chatgpt.utils.web.duckduckgo import summary_ddg
@@ -8,16 +9,32 @@
 @pytest.mark.skipif(not is_api_key_available('OpenAI'),
                     reason="requires OpenAI key to run")
 def test_duckduckgo_search_overview_summary():
-    query = 'Mickey Mouse'
-    text = summary_ddg(query, do_summarize=True)
-    aprint(text)
-    assert 'Mickey' in text
-    assert 'Web search failed' not in text
+
+    try:
+        query = 'Mickey Mouse'
+        text = summary_ddg(query, do_summarize=True)
+        aprint(text)
+        assert 'Mickey' in text
+        assert 'Web search failed' not in text
+
+    except RatelimitException as e:
+        aprint(f"RatelimitException: {e}")
+        aprint(f"RatelimitException: {e.response}")
+        aprint(f"RatelimitException: {e.response.text}")
+
+
 
 
 def test_duckduckgo_search_overview():
-    query = 'Mickey Mouse'
-    text = summary_ddg(query, do_summarize=False)
-    aprint(text)
-    assert 'Mickey' in text
-    assert 'Web search failed' not in text
+
+    try:
+        query = 'Mickey Mouse'
+        text = summary_ddg(query, do_summarize=False)
+        aprint(text)
+        assert 'Mickey' in text
+        assert 'Web search failed' not in text
+
+    except RatelimitException as e:
+        aprint(f"RatelimitException: {e}")
+        aprint(f"RatelimitException: {e.response}")
+        aprint(f"RatelimitException: {e.response.text}")

src/napari_chatgpt/utils/web/test/google_test.py

@@ -1,10 +1,20 @@
 from arbol import aprint
+from duckduckgo_search.exceptions import RatelimitException
 
 from napari_chatgpt.utils.web.google import search_overview
 
 
 def test_google_search_overview():
-    term = 'wiki Mickey Mouse'
-    text = search_overview(term)
 
-    aprint(text)
+    try:
+        term = 'wiki Mickey Mouse'
+        text = search_overview(term)
+
+        aprint(text)
+
+    except RatelimitException as e:
+        aprint(f"RatelimitException: {e}")
+        aprint(f"RatelimitException: {e.response}")
+        aprint(f"RatelimitException: {e.response.text}")
+
+

src/napari_chatgpt/utils/web/test/metasearch_test.py

@@ -1,5 +1,6 @@
 import pytest
 from arbol import aprint
+from duckduckgo_search.exceptions import RatelimitException
 
 from napari_chatgpt.utils.api_keys.api_key import is_api_key_available
 from napari_chatgpt.utils.web.metasearch import metasearch
@@ -8,16 +9,36 @@
 @pytest.mark.skipif(not is_api_key_available('OpenAI'),
                     reason="requires OpenAI key to run")
 def test_metasearch_summary():
-    query = 'Mickey Mouse'
-    text = metasearch(query, do_summarize=True)
-    aprint(text)
-    assert 'Mickey' in text
-    assert 'Web search failed' not in text
+
+    try:
+        query = 'Mickey Mouse'
+        text = metasearch(query, do_summarize=True)
+        aprint(text)
+        assert 'Mickey' in text
+        assert 'Web search failed' not in text
+
+    except RatelimitException as e:
+        aprint(f"RatelimitException: {e}")
+        aprint(f"RatelimitException: {e.response}")
+        aprint(f"RatelimitException: {e.response.text}")
+
+
+
 
 
 def test_metasearch():
-    query = 'Mickey Mouse'
-    text = metasearch(query, do_summarize=False)
-    aprint(text)
-    assert 'Mickey' in text
-    assert 'Web search failed' not in text
+
+    try:
+        query = 'Mickey Mouse'
+        text = metasearch(query, do_summarize=False)
+        aprint(text)
+        assert 'Mickey' in text
+        assert 'Web search failed' not in text
+
+    except RatelimitException as e:
+        aprint(f"RatelimitException: {e}")
+        aprint(f"RatelimitException: {e.response}")
+        aprint(f"RatelimitException: {e.response.text}")
+
+
+