Update app.py

app.py

@@ -6,6 +6,9 @@ from langchain_community.llms import HuggingFaceEndpoint
 from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
 import gradio as gr
 import subprocess
+import redis
+from langchain_community.vectorstores.redis import RedisVectorStore
+
 #Using Mistral Modal
 # Ensure Playwright installs required browsers and dependencies
 subprocess.run(["playwright", "install"])
@@ -25,9 +28,15 @@ embedder_model_instance = HuggingFaceInferenceAPIEmbeddings(
     api_key=HUGGINGFACEHUB_API_TOKEN, model_name="sentence-transformers/all-MiniLM-l6-v2"
 )
 
+
+r = redis.Redis(host="localhost", port=6379)
+vector_store = RedisVectorStore(redis=r)
+
 graph_config = {
     "llm": {"model_instance": llm_model_instance},
-    "embeddings": {"model_instance": embedder_model_instance}
+    "embeddings": {"model_instance": embedder_model_instance},
+    "vector_store": {"model_instance": vector_store}
+}
 }
 #To Scrape the data and summarize it
 def scrape_and_summarize(prompt, source):