Update agent.py

agent.py

@@ -1,18 +1,15 @@
 import os
-from langchain import hub
 from langchain.agents import initialize_agent, AgentType, Tool
-from langchain_community.llms import HuggingFaceHub
+from langchain_huggingface import HuggingFaceEndpoint
 from langchain_community.tools import DuckDuckGoSearchResults
 from langchain_experimental.tools import PythonREPLTool
 from huggingface_hub import login
 
-# Lade dein Hugging Face Token (falls benötigt)
-# login(token="your-huggingface-token-here")  # Optional, falls dein Space das braucht
-
 # LLM: Mistral-7B-Instruct über Hugging Face Inference API
-llm = HuggingFaceHub(
+llm = HuggingFaceEndpoint(
     repo_id="mistralai/Mistral-7B-Instruct-v0.2",
-    model_kwargs={"temperature": 0.2, "max_new_tokens": 512}
+    temperature=0.2,
+    max_new_tokens=512,
 )
 
 # Tools definieren
@@ -32,6 +29,23 @@ tools = [
     ),
 ]
 
+from langchain_core.prompts import SystemMessagePromptTemplate
+
+system_prompt = """You are an expert AI assistant specialized in answering exam-style factual questions. 
+Follow these guidelines:
+
+- Use the Search tool when external knowledge is needed (especially about recent events or niche topics).
+- Use the Python_REPL tool for any math calculations, even if simple.
+- Always attempt to provide a direct and concise answer without extra commentary.
+- Do not apologize or state limitations.
+- If a file is attached, explain how you would process it or the key steps to extract an answer.
+- When dates are mentioned, be very precise and double-check calculations using the appropriate tools.
+- If unsure, use the Search tool before responding.
+
+Respond directly to the user’s question based solely on facts and without unnecessary elaboration.
+Only provide what is explicitly asked for.
+"""
+
 # Agent initialisieren
 agent_executor = initialize_agent(
     tools,
@@ -39,4 +53,6 @@ agent_executor = initialize_agent(
     agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
     verbose=True,
     handle_parsing_errors=True,
+    system_message=SystemMessagePromptTemplate.from_template(system_prompt),
 )
+