Update app.py

app.py

@@ -1,4 +1,14 @@
-# pip install -r requirements.txt
+# requirements.txt contents:
+"""
+langgraph>=0.0.25
+langchain_openai>=0.0.4
+langchain_community>=0.0.11
+chromadb>=0.4.15
+openai>=1.9.0
+streamlit>=1.29.0
+requests>=2.31.0
+typing-extensions>=4.9.0
+"""
 
 # ------------------------------
 # Imports & Dependencies
@@ -7,8 +17,8 @@ from langchain_openai import OpenAIEmbeddings
 from langchain_community.vectorstores import Chroma
 from langchain_core.messages import HumanMessage, AIMessage, ToolMessage
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langgraph.graph import END, StateGraph  # Removed START import
-from langgraph.nodes.tool_node import ToolNode
+from langgraph.graph import END, StateGraph
+from langgraph.prebuilt import ToolNode  # Corrected import
 from langgraph.graph.message import add_messages
 from typing_extensions import TypedDict, Annotated
 from typing import Sequence
@@ -67,9 +77,9 @@ development_retriever = development_vectorstore.as_retriever()
 # Creating Retriever Tools
 # ------------------------------
 research_tool = create_retriever_tool(
-    research_retriever,  # Retriever object
-    "research_db_tool",  # Name of the tool
-    "Search information from the research database."  # Tool description
+    research_retriever,
+    "research_db_tool",
+    "Search information from the research database."
 )
 
 development_tool = create_retriever_tool(
@@ -95,7 +105,6 @@ def agent(state: AgentState):
     else:
         user_message = messages[0].content
 
-    # Structure prompt for consistent text output
     prompt = f"""Given this user question: "{user_message}"
 If it's about research or academic topics, respond EXACTLY in this format:
 SEARCH_RESEARCH: <search terms>
@@ -130,7 +139,6 @@ Otherwise, just answer directly.
         response_text = response.json()['choices'][0]['message']['content']
         print("Raw response:", response_text)
         
-        # Format the response into expected tool format
         if "SEARCH_RESEARCH:" in response_text:
             query = response_text.split("SEARCH_RESEARCH:")[1].strip()
             results = research_retriever.invoke(query)
@@ -164,7 +172,6 @@ def generate(state: AgentState):
     question = messages[0].content if isinstance(messages[0], tuple) else messages[0].content
     last_message = messages[-1]
 
-    # Extract the document content from the results
     docs = ""
     if "Results: [" in last_message.content:
         results_start = last_message.content.find("Results: [")
@@ -306,7 +313,6 @@ def main():
         initial_sidebar_state="expanded"
     )
 
-    # Custom CSS for styling
     st.markdown("""
     <style>
     .stApp {
@@ -332,7 +338,6 @@ def main():
     </style>
     """, unsafe_allow_html=True)
 
-    # Sidebar with available data
     with st.sidebar:
         st.header("📚 Available Data")
         
@@ -347,7 +352,6 @@ def main():
     st.title("🤖 AI Research & Development Assistant")
     st.markdown("---")
 
-    # Query input box
     query = st.text_area("Enter your question:", height=100, placeholder="e.g., What is the latest advancement in AI research?")
 
     col1, col2 = st.columns([1, 2])
@@ -386,4 +390,4 @@ def main():
         """)
 
 if __name__ == "__main__":
-    main()
+    main()