Update app.py

app.py

@@ -5,7 +5,7 @@ from langchain.chains import GraphQAChain
 from langchain_community.document_loaders import TextLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain_community.vectorstores import Pinecone
-from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_huggingface import HuggingFaceEmbeddings, HuggingFaceHub  # Updated imports
 from langchain.schema.runnable import RunnablePassthrough
 from langchain.schema.output_parser import StrOutputParser
 from langchain.prompts import PromptTemplate
@@ -20,6 +20,7 @@ from oauth2client.service_account import ServiceAccountCredentials
 
 os.system("pip install sentence-transformers")
 os.system("pip install gspread oauth2client")
+os.system("pip install -U langchain-huggingface langchain-community")
 
 # Google Sheets Setup
 scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
@@ -42,7 +43,7 @@ def add_review(question, rag_response, graphrag_response, feedback):
     store_feedback_in_sheet(feedback, question, rag_response, graphrag_response)
     return load_data()
 
-# RAG Setup_
+# RAG Setup
 text_path = r"./text_chunks.txt"
 loader = TextLoader(text_path, encoding='utf-8')
 documents = loader.load()
@@ -51,8 +52,6 @@ docs = text_splitter.split_documents(documents)
 
 embeddings = HuggingFaceEmbeddings()
 
-from langchain.llms import HuggingFaceHub
-
 # Define the repo ID and connect to Mixtral model on Huggingface
 repo_id = "meta-llama/Meta-Llama-3-8B"
 llm = HuggingFaceHub(
@@ -132,8 +131,8 @@ def fetch_relationships(tx):
 def populate_networkx_graph():
     G = nx.Graph()
     with driver.session() as session:
-        nodes = session.read_transaction(fetch_nodes)
-        relationships = session.read_transaction(fetch_relationships)
+        nodes = session.execute_read(fetch_nodes)  # Updated to use execute_read
+        relationships = session.execute_read(fetch_relationships)  # Updated to use execute_read
         for node in nodes:
             G.add_node(node['id'], labels=node['labels'])
         for relationship in relationships:
@@ -178,13 +177,18 @@ with gr.Blocks() as demo:
             rag_output = gr.Textbox(label="Model A", interactive=False)
             graphrag_output = gr.Textbox(label="Model B", interactive=False)
             feedback = gr.Radio(label="Which response is better?", choices=["A ดีกว่า", "B ดีกว่า", "เท่ากัน", "แย่ทั้งคู่"])
+            comments = gr.Textbox(label="Comments", lines=10, placeholder="Any additional comments?")
             submit_feedback = gr.Button(value="Submit Feedback")
 
+        with gr.Column():
+            data = gr.Dataframe(label="Most recently created 10 rows")
+            count = gr.Number(label="Total number of reviews")
+
     # Function to handle question submission and display responses
-    submit_btn.click(fn=compare_models, inputs=[question_input], outputs=[rag_output, graphrag_output])
+    submit_btn.click(fn=compare_models, inputs=[question_input])
 
     # Function to handle feedback submission and update data display
-    submit_feedback.click(fn=add_review, inputs=[question_input, rag_output, graphrag_output, feedback], outputs=[data, count])
+    submit_feedback.click(fn=add_review, inputs=[question_input, rag_output, graphrag_output, feedback])
 
     # Load initial data display
     demo.load(fn=load_data, inputs=None, outputs=[data, count])