🔨 refactor(conftest.py): reformat code for better readability and maintainability

✨ feat(conftest.py): add MyCustomChain class as an example of a custom chain
✨ feat(conftest.py): add CustomChain class as a custom component for building a document
✨ feat(conftest.py): add CSVLoaderComponent class as a custom component for loading CSV files and converting rows to documents

tests/conftest.py

@@ -122,20 +122,20 @@ def client_fixture(session: Session):  #
 def custom_chain():
     return '''from __future__ import annotations
 
-    from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional
 
-    from pydantic import Extra
+from pydantic import Extra
 
-    from langchain.schema import BaseLanguageModel, Document
+from langchain.schema import BaseLanguageModel, Document
-    from langchain.callbacks.manager import (
+from langchain.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
-    )
+)
-    from langchain.chains.base import Chain
+from langchain.chains.base import Chain
-    from langchain.prompts import StringPromptTemplate
+from langchain.prompts import StringPromptTemplate
-    from langflow.interface.custom.base import CustomComponent
+from langflow.interface.custom.base import CustomComponent
 
-    class MyCustomChain(Chain):
+class MyCustomChain(Chain):
     """
     An example of a custom chain.
     """
@@ -225,7 +225,7 @@ def custom_chain():
     def _chain_type(self) -> str:
         return "my_custom_chain"
 
-    class CustomChain(CustomComponent):
+class CustomChain(CustomComponent):
     display_name: str = "Custom Chain"
     field_config = {
         "prompt": {"field_type": "prompt"},
@@ -235,3 +235,33 @@ def custom_chain():
     def build(self, prompt, llm, input: str) -> Document:
         chain = MyCustomChain(prompt=prompt, llm=llm)
         return chain(input)'''
+
+
+@pytest.fixture
+def data_processing():
+    return """import pandas as pd
+from langchain.schema import Document
+from langflow.interface.custom.base import CustomComponent
+
+class CSVLoaderComponent(CustomComponent):
+    display_name: str = "CSV Loader"
+    field_config = {
+        "filename": {"field_type": "str", "required": True},
+        "column_name": {"field_type": "str", "required": True},
+    }
+
+    def build(self, filename: str, column_name: str) -> List[Document]:
+        # Load the CSV file
+        df = pd.read_csv(filename)
+
+        # Verify the column exists
+        if column_name not in df.columns:
+            raise ValueError(f"Column '{column_name}' not found in the CSV file")
+
+        # Convert each row of the specified column to a document object
+        documents = []
+        for content in df[column_name]:
+            metadata = {"filename": filename}
+            documents.append(Document(page_content=str(content), metadata=metadata))
+
+        return documents"""