final push

Open_Source_RAG_Leveraging_Hugging_Face_Endpoints_through_LangChain.ipynb

@@ -35,7 +35,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "id": "EwGLnp31jXJj"
       },

README.md

@@ -1 +1,11 @@
-Hello 
+---
+title: Midterm-app
+emoji: 📉
+colorFrom: pink
+colorTo: yellow
+sdk: docker
+pinned: false
+app_port: 7860
+---
+
+### Hello, i am Paul Graham bot. Feel free to ask me any questions regarding Paul Graham.

app.py

@@ -43,17 +43,17 @@ text_loader = TextLoader("./data/paul_graham_essays.txt")
 documents = text_loader.load()
 
 ### 2. CREATE TEXT SPLITTER AND SPLIT DOCUMENTS
-text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=30)
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=800, chunk_overlap=40)
 split_documents = text_splitter.split_documents(documents)
 
 ### 3. LOAD HUGGINGFACE EMBEDDINGS
 hf_embeddings = HuggingFaceEndpointEmbeddings(
     model=HF_EMBED_ENDPOINT,
     task="feature-extraction",
-    huggingfacehub_api_token=os.environ["HF_TOKEN"],
+    huggingfacehub_api_token=HF_TOKEN
 )
 
-if os.path.exists("./data/vectorstore"):
+if os.path.exists("./data/vectorstore/index.faiss"):
     vectorstore = FAISS.load_local(
         "./data/vectorstore", 
         hf_embeddings, 

chainlit.md

@@ -1 +1 @@
-# Hello
+# Hello, i am Paul Graham bot. Feel free to ask me any questions regarding Paul Graham.