Hotfix_02 (#563)

poetry.lock

@@ -2523,14 +2523,14 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.2.0"
+version = "1.3.0"
 description = "Lightweight pipelining with Python functions"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "joblib-1.2.0-py3-none-any.whl", hash = "sha256:091138ed78f800342968c523bdde947e7a305b8594b910a0fea2ab83c3c6d385"},
+    {file = "joblib-1.3.0-py3-none-any.whl", hash = "sha256:172d56d4c43dd6bcd953bea213018c4084cf754963bbf54b8dae40faea716b98"},
-    {file = "joblib-1.2.0.tar.gz", hash = "sha256:e1cee4a79e4af22881164f218d4311f60074197fb707e082e803b61f6d137018"},
+    {file = "joblib-1.3.0.tar.gz", hash = "sha256:0b12a65dc76c530dbd790dd92881f75c40932b4254a7c8e608a868df408ca0a3"},
 ]
 
 [[package]]

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.2.5"
+version = "0.2.6"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [

src/backend/langflow/config.yaml

@@ -121,7 +121,7 @@ llms:
     documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/huggingface_hub"
 memories:
   ConversationBufferMemory:
-    documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
+    documentation: "https://python.langchain.com/docs/modules/memory/how_to/buffer"
   ConversationSummaryMemory:
     documentation: "https://python.langchain.com/docs/modules/memory/how_to/summary"
   ConversationKGMemory:

src/backend/langflow/interface/initialize/loading.py

@@ -221,14 +221,17 @@ def instantiate_textsplitter(
         ) from exc
 
     if (
-        "separator_type" in params
+        "separator_type" in params and params["separator_type"] == "Text"
-        and params["separator_type"] == "Text"
+    ) or "separator_type" not in params:
-        or "separator_type" not in params
+        params.pop("separator_type", None)
-    ):
         text_splitter = class_object(**params)
     else:
-        params["language"] = params.pop("separator_type", None)
+        from langchain.text_splitter import Language
+
+        language = params.pop("separator_type", None)
+        params["language"] = Language(language)
         params.pop("separators", None)
+
         text_splitter = class_object.from_language(**params)
     return text_splitter.split_documents(documents)
 

src/backend/langflow/template/frontend_node/textsplitters.py

@@ -21,6 +21,8 @@ class TextSplittersFrontendNode(FrontendNode):
             # Add a field for type of separator
             # which will have Text or any value from the
             # Language enum
+            options = [x.value for x in Language] + ["Text"]
+            options.sort()
             self.template.add_field(
                 TemplateField(
                     field_type="str",
@@ -29,7 +31,7 @@ class TextSplittersFrontendNode(FrontendNode):
                     name="separator_type",
                     advanced=False,
                     is_list=True,
-                    options=[x.value for x in Language],
+                    options=options,
                     value="Text",
                     display_name="Separator Type",
                 )