fix: loaded objects return the function to be called

langflow/backend/langflow_backend/api/endpoints.py

@@ -1,6 +1,6 @@
 from fastapi import APIRouter, HTTPException
-from langflow_backend.interface.types import build_langchain_types_dict, get_type_list
-from langflow_backend.interface.loading import process_data_graph
+from langflow_backend.interface.types import build_langchain_types_dict
+from langflow_backend.interface.run import process_data_graph
 from typing import Any, Dict
 
 

langflow/backend/langflow_backend/interface/loading.py

@@ -1,7 +1,4 @@
-import contextlib
 import json
-import re
-import io
 from typing import Any, Dict
 from langflow_backend.interface.types import get_type_list
 from langchain.agents.loading import load_agent_executor_from_config
@@ -38,33 +35,7 @@ def replace_zero_shot_prompt_with_prompt_template(nodes):
     return nodes
 
 
-def process_data_graph(data_graph: Dict[str, Any]):
-    """Process data graph by extracting input variables and replacing ZeroShotPrompt with PromptTemplate,
-    then run the graph and return the result and thought."""
-    nodes = data_graph["nodes"]
-    # Substitute ZeroShotPrompt with PromptTemplate
-    nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
-    # Add input variables
-    data_graph = payload.extract_input_variables(data_graph)
-    # Nodes, edges and root node
-    message = data_graph["message"]
-    edges = data_graph["edges"]
-    root = payload.get_root_node(data_graph)
-    extracted_json = payload.build_json(root, nodes, edges)
 
-    # Process json
-    result, thought = get_result_and_thought(extracted_json, message)
-
-    # Remove unnecessary data from response
-    begin = thought.rfind(message)
-    thought = thought[(begin + len(message)) :]
-
-    return {
-        "result": result,
-        "thought": re.sub(
-            r"\x1b\[([0-9,A-Z]{1,2}(;[0-9,A-Z]{1,2})?)?[m|K]", "", thought
-        ).strip(),
-    }
 
 
 def load_langchain_type_from_config(config: Dict[str, Any]):
@@ -72,27 +43,16 @@ def load_langchain_type_from_config(config: Dict[str, Any]):
     # Get type list
     type_list = get_type_list()
     if config["_type"] in type_list["agents"]:
-        return load_agent_executor_from_config(config)
+        return load_agent_executor_from_config(config).run
     elif config["_type"] in type_list["chains"]:
-        return load_chain_from_config(config)
+        return load_chain_from_config(config).run
     elif config["_type"] in type_list["llms"]:
         return load_llm_from_config(config)
     else:
         raise ValueError("Type should be either agent, chain or llm")
 
 
-def get_result_and_thought(extracted_json: Dict[str, Any], message: str):
-    """Get result and thought from extracted json"""
-    # Get type list
-    try:
-        loaded = load_langchain_type_from_config(config=extracted_json)
-        with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
-            result = loaded(message)
-            thought = output_buffer.getvalue()
-    except Exception as e:
-        result = f"Error: {str(e)}"
-        thought = ""
-    return result, thought
+
 
 
 def build_prompt_template(prompt, tools):

langflow/backend/langflow_backend/interface/run.py

@@ -0,0 +1,54 @@
+import contextlib
+import io
+import re
+from typing import Any, Dict
+from langflow_backend.interface.loading import (
+    load_langchain_type_from_config,
+    replace_zero_shot_prompt_with_prompt_template,
+)
+from langflow_backend.utils import payload
+
+
+def process_data_graph(data_graph: Dict[str, Any]):
+    """
+    Process data graph by extracting input variables and replacing ZeroShotPrompt
+    with PromptTemplate,then run the graph and return the result and thought.
+    """
+    nodes = data_graph["nodes"]
+    # Substitute ZeroShotPrompt with PromptTemplate
+    nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
+    # Add input variables
+    data_graph = payload.extract_input_variables(data_graph)
+    # Nodes, edges and root node
+    message = data_graph["message"]
+    edges = data_graph["edges"]
+    root = payload.get_root_node(data_graph)
+    extracted_json = payload.build_json(root, nodes, edges)
+
+    # Process json
+    result, thought = get_result_and_thought(extracted_json, message)
+
+    # Remove unnecessary data from response
+    begin = thought.rfind(message)
+    thought = thought[(begin + len(message)) :]
+
+    return {
+        "result": result,
+        "thought": re.sub(
+            r"\x1b\[([0-9,A-Z]{1,2}(;[0-9,A-Z]{1,2})?)?[m|K]", "", thought
+        ).strip(),
+    }
+
+
+def get_result_and_thought(extracted_json: Dict[str, Any], message: str):
+    """Get result and thought from extracted json"""
+    # Get type list
+    try:
+        loaded = load_langchain_type_from_config(config=extracted_json)
+        with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
+            result = loaded(message)
+            thought = output_buffer.getvalue()
+    except Exception as e:
+        result = f"Error: {str(e)}"
+        thought = ""
+    return result, thought