Update app.py

app.py

@@ -1,8 +1,8 @@
-from langchain_openai import OpenAIEmbeddings  # Updated import path
-from langchain.vectorstores import Chroma
-from langchain.schema import HumanMessage, AIMessage
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langgraph.graph import END, StateGraph, START
+from langchain_openai import OpenAIEmbeddings
+from langchain_community.vectorstores import Chroma
+from langchain_core.messages import HumanMessage, AIMessage
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langgraph import StateGraph, END, START
 from langgraph.prebuilt import ToolNode
 from langgraph.graph.message import add_messages
 from typing_extensions import TypedDict, Annotated
@@ -37,8 +37,8 @@ research_docs = splitter.create_documents(research_texts)
 development_docs = splitter.create_documents(development_texts)
 
 embeddings = OpenAIEmbeddings(
-    model="text-embedding-3-large"
-    # dimensions=1024  # Uncomment if needed
+    model="text-embedding-3-large",
+    dimensions=1024
 )
 
 research_vectorstore = Chroma.from_documents(
@@ -110,8 +110,7 @@ Otherwise, just answer directly.
     response = requests.post(
         "https://api.deepseek.com/v1/chat/completions",
         headers=headers,
-        json=data,
-        verify=False
+        json=data
     )
     
     if response.status_code == 200:
@@ -186,8 +185,7 @@ Focus on extracting and synthesizing the key findings from the research papers.
     response = requests.post(
         "https://api.deepseek.com/v1/chat/completions",
         headers=headers,
-        json=data,
-        verify=False
+        json=data
     )
     
     if response.status_code == 200:
@@ -221,8 +219,7 @@ def rewrite(state: AgentState):
     response = requests.post(
         "https://api.deepseek.com/v1/chat/completions",
         headers=headers,
-        json=data,
-        verify=False
+        json=data
     )
     
     if response.status_code == 200:
@@ -273,9 +270,9 @@ app = workflow.compile()
 # --------------------------
 # Process Question Function
 # --------------------------
-def process_question(user_question, app, config):
+def process_question(user_question):
     events = []
-    for event in app.stream({"messages": [("user", user_question)]}, config):
+    for event in app.stream({"messages": [("user", user_question)]}):
         events.append(event)
     return events
 
@@ -319,7 +316,7 @@ def main():
         if st.button("🔍 Get Answer", use_container_width=True):
             if query:
                 with st.spinner('Processing your question...'):
-                    events = process_question(query, app, {"configurable": {"thread_id": "1"}})
+                    events = process_question(query)
                     for event in events:
                         if 'agent' in event:
                             with st.expander("🔄 Processing Step", expanded=True):