Update app.py

app.py

@@ -5,8 +5,8 @@ import tempfile
 import threading
 import numpy as np
 from transformers import pipeline, AutoModelForSpeechSeq2Seq, AutoProcessor
-from langchain_openai import ChatOpenAI
-from langchain_community.vectorstores.neo4j_vector import remove_lucene_chars
+from langchain_openai import ChatOpenAI, OpenAIEmbeddings
+from langchain_community.vectorstores import Neo4jVector
 from langchain_community.graphs import Neo4jGraph
 from langchain_experimental.graph_transformers import LLMGraphTransformer
 from langchain_core.prompts import ChatPromptTemplate
@@ -19,15 +19,15 @@ graph = Neo4jGraph(
     password="_x8f-_aAQvs2NB0x6s0ZHSh3W_y-HrENDbgStvsUCM0"
 )
 
-
-# Function to generate a full-text search query for Neo4j
-def generate_full_text_query(input: str) -> str:
-    full_text_query = ""
-    words = [el for el in input.split() if el]
-    for word in words[:-1]:
-        full_text_query += f" {word}~2 AND"
-    full_text_query += f" {words[-1]}~2"
-    return full_text_query.strip()
+# Initialize the vector index with Neo4j
+vector_index = Neo4jVector.from_existing_graph(
+    embeddings=OpenAIEmbeddings(api_key="YOUR_OPENAI_API_KEY"),
+    graph=graph,
+    search_type="hybrid",
+    node_label="Document",
+    text_node_properties=["text"],
+    embedding_node_property="embedding",
+)
 
 # Define the ASR model with Whisper
 model_id = 'openai/whisper-large-v3'
@@ -86,6 +86,15 @@ def transcribe_function(stream, new_chunk):
 
     return stream, full_text, full_text
 
+# Function to generate a full-text search query for Neo4j
+def generate_full_text_query(input: str) -> str:
+    full_text_query = ""
+    words = [el for el in input.split() if el]
+    for word in words[:-1]:
+        full_text_query += f" {word}~2 AND"
+    full_text_query += f" {words[-1]}~2"
+    return full_text_query.strip()
+
 # Function to generate audio with Eleven Labs TTS
 def generate_audio_elevenlabs(text):
     XI_API_KEY = os.environ['ELEVENLABS_API']
@@ -185,4 +194,4 @@ interface = gr.Interface(
 )
 
 # Launch the Gradio app
-interface.launch(show_error=True)
+interface.launch()