updated changeds

app.py

@@ -20,18 +20,16 @@ from langgraph.graph import StateGraph, START, END
 # from langchain_huggingface.llms import HuggingFaceEndpoint
 from langchain_core.messages import AnyMessage, SystemMessage, HumanMessage
 from langgraph.graph.message import add_messages
-from langchain_community.utilities import WikipediaAPIWrapper
-from langchain_community.tools import WikipediaQueryRun
-from langchain_community.document_loaders import YoutubeLoader, WebBaseLoader
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
 from langgraph.prebuilt import ToolNode, tools_condition
-from langchain.tools import tool
+
+from tools import fetch_website, ask_wiki, youtube_transcript, python_repl_tool
 
 # Initialize the Hugging Face model
 
 llm = HuggingFaceEndpoint(
-    repo_id="Qwen/Qwen3-30B-A3B", # "Qwen/Qwen2.5-72B-Instruct",
-    provider="nebius", # "hf-inference",
+    repo_id="XiaomiMiMo/MiMo-V2-Flash", # "Qwen/Qwen2.5-72B-Instruct",
+    provider="novita", # "hf-inference",
     max_new_tokens=8192,
     do_sample=False,
     # temperature=0.,
@@ -39,66 +37,13 @@ llm = HuggingFaceEndpoint(
 
 chat_model = ChatHuggingFace(llm=llm)
 
-# Define tools
-
-
-@tool
-def fetch_website(url:str) -> str:
-    """Fetch the content of a website.
-    Args:
-        url: The URL of the website to fetch.
-    Returns:
-        The title and content of the website.
-    """
-    loader = WebBaseLoader(url)
-    docs = loader.load()
-    return docs[0].page_content
-
-@tool
-def ask_wiki(query: str) -> str:
-    """Retrieve information from Wikipedia based on a user query.
-    Args:
-        query: A user query.
-    Returns:
-        A single string containing the retrieved article from Wikipedia.
-    """
-    if not query.strip():
-        return "Please provide a valid query."
-    try:
-        wiki_toolapi_wrapper = WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=8000)
-        wiki_tool = WikipediaQueryRun(api_wrapper=wiki_toolapi_wrapper)
-        result = wiki_tool.run(query)
-        return result
-    except Exception as e:
-        return f"Error retrieving information: {str(e)}"
-
-@tool
-def youtube_transcript(url: str) -> str:
-    """Retrieve transcript from Youtube based url.
-    Args:
-        url: input youtube url.
-    Returns:
-        A single string containing the transcript of the youtube videos.
-    """
-    max_attempts = 5  # Set a maximum number of attempts
-    attempts = 0
-    loader = YoutubeLoader.from_youtube_url(url, add_video_info=True)
-    while attempts < max_attempts:
-        try:
-            docs  = loader.load()
-            return docs[0].page_content
-        except Exception as e:
-            attempts += 1
-            print(f"Attempt {attempts} failed: {e}")
-            # Optionally add a delay before retrying
-            time.sleep(1) # Import the time module
-    return "Failed to retrieve transcript after multiple attempts."
 
 # Equip llm with tools
 tools_list = [
     fetch_website,
     ask_wiki,
     youtube_transcript,
+    python_repl_tool
 ]
 
 llm_with_tools = chat_model.bind_tools(

tools.py

@@ -0,0 +1,82 @@
+import time
+from langchain.tools import tool
+from langchain_community.utilities import WikipediaAPIWrapper
+from langchain_community.tools import WikipediaQueryRun
+from langchain_community.document_loaders import YoutubeLoader, WebBaseLoader
+from langchain_experimental.utilities import PythonREPL
+
+# Initialize Python REPL
+python_repl = PythonREPL()
+
+@tool
+def fetch_website(url:str) -> str:
+    """Fetch the content of a website.
+    Args:
+        url: The URL of the website to fetch.
+    Returns:
+        The title and content of the website.
+    """
+    loader = WebBaseLoader(url)
+    docs = loader.load()
+    return docs[0].page_content
+
+@tool
+def ask_wiki(query: str) -> str:
+    """Retrieve information from Wikipedia based on a user query.
+    Args:
+        query: A user query.
+    Returns:
+        A single string containing the retrieved article from Wikipedia.
+    """
+    if not query.strip():
+        return "Please provide a valid query."
+    try:
+        wiki_toolapi_wrapper = WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=8000)
+        wiki_tool = WikipediaQueryRun(api_wrapper=wiki_toolapi_wrapper)
+        result = wiki_tool.run(query)
+        return result
+    except Exception as e:
+        return f"Error retrieving information: {str(e)}"
+
+@tool
+def youtube_transcript(url: str) -> str:
+    """Retrieve transcript from Youtube based url.
+    Args:
+        url: input youtube url.
+    Returns:
+        A single string containing the transcript of the youtube videos.
+    """
+    max_attempts = 5  # Set a maximum number of attempts
+    attempts = 0
+    loader = YoutubeLoader.from_youtube_url(url, add_video_info=True)
+    while attempts < max_attempts:
+        try:
+            docs  = loader.load()
+            return docs[0].page_content
+        except Exception as e:
+            attempts += 1
+            print(f"Attempt {attempts} failed: {e}")
+            # Optionally add a delay before retrying
+            time.sleep(1) # Import the time module
+    return "Failed to retrieve transcript after multiple attempts."
+
+@tool
+def python_repl_tool(code: str) -> str:
+    """
+    Execute Python code and return the output.
+    
+    Use this tool to run Python code for calculations, data analysis,
+    or any computational tasks. The code runs in a persistent Python
+    environment, so variables and imports are preserved between calls.
+    
+    Args:
+        code: Python code to execute
+        
+    Returns:
+        The output of the code execution (stdout) or error message
+    """
+    try:
+        result = python_repl.run(code)
+        return result if result else "Code executed successfully (no output)"
+    except Exception as e:
+        return f"Error: {str(e)}"