fix: xml component working properly

src/backend/base/langflow/components/agents/XMLAgent.py

@@ -1,9 +1,10 @@
+from typing import List, Optional
 from langchain.agents import create_xml_agent
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate, HumanMessagePromptTemplate
-
 from langflow.base.agents.agent import LCToolsAgentComponent
 from langflow.inputs import MultilineInput
-from langflow.inputs.inputs import HandleInput
+from langflow.inputs.inputs import DataInput, HandleInput
+from langflow.schema import Data
 
 
 class XMLAgentComponent(LCToolsAgentComponent):
@@ -12,43 +13,38 @@ class XMLAgentComponent(LCToolsAgentComponent):
     icon = "LangChain"
     beta = True
     name = "XMLAgent"
-
     inputs = LCToolsAgentComponent._base_inputs + [
         HandleInput(name="llm", display_name="Language Model", input_types=["LanguageModel"], required=True),
+        DataInput(name="chat_history", display_name="Chat History", is_list=True, advanced=True),
         MultilineInput(
             name="user_prompt",
             display_name="Prompt",
-            value="""
-You are a helpful assistant. Help the user answer any questions.
-
+            value="""You are a helpful assistant. Help the user answer any questions.
 You have access to the following tools:
-
 {tools}
-
 In order to use a tool, you can use <tool></tool> and <tool_input></tool_input> tags. You will then get back a response in the form <observation></observation>
-
 For example, if you have a tool called 'search' that could run a google search, in order to search for the weather in SF you would respond:
-
 <tool>search</tool><tool_input>weather in SF</tool_input>
-
 <observation>64 degrees</observation>
-
 When you are done, respond with a final answer between <final_answer></final_answer>. For example:
-
 <final_answer>The weather in SF is 64 degrees</final_answer>
-
 Begin!
-
 Question: {input}
-
 {agent_scratchpad}
             """,
         ),
     ]
 
+    def get_chat_history_data(self) -> Optional[List[Data]]:
+        return self.chat_history
+
     def create_agent_runnable(self):
         messages = [
-            HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=["input"], template=self.user_prompt))
+            HumanMessagePromptTemplate(
+                prompt=PromptTemplate(
+                    input_variables=["input", "chat_history", "agent_scratchpad", "tools"], template=self.user_prompt
+                )
+            )
         ]
         prompt = ChatPromptTemplate.from_messages(messages)
         return create_xml_agent(self.llm, self.tools, prompt)