testing llamaparse

app.py

@@ -1,15 +1,17 @@
+import tempfile
 import streamlit as st
 
 from llama_index.llms.gemini import Gemini
 from llama_index.llms.huggingface import HuggingFaceLLM
 from llama_index.llms.mistralai import MistralAI
 from llama_index.llms.openai import OpenAI
-
 from llama_index.core import (
     VectorStoreIndex,
     Settings,
 )
 
+from llama_parse import LlamaParse
+
 from streamlit_pdf_viewer import pdf_viewer
 
 # Global configurations
@@ -80,9 +82,15 @@ with st.sidebar:
         Settings.context_window = 4096 # max possible
     
 
-    # Enter Token
-    token = st.text_input(
-        "Enter your token",
+    # Enter LLM Token
+    llm_token = st.text_input(
+        "Enter your LLM token",
+        value=None
+    )
+
+    # Enter parsing Token
+    parse_token = st.text_input(
+        "Enter your LlamaParse token",
         value=None
     )
 
@@ -94,12 +102,18 @@ with st.sidebar:
 
     if uploaded_file is not None:
         # Parse the file
-        pass
+        # temp_dir = tempfile.TemporaryDirectory()
+        parser = LlamaParse(
+            api_key=parse_token,  # can also be set in your env as LLAMA_CLOUD_API_KEY
+            result_type="text"  # "markdown" and "text" are available
+        )
+        parsed_document = parser.load_data(uploaded_file)
+        # temp_dir.cleanup()
 
 col1, col2 = st.columns(2)
 
 with col1:
-    pass
+    st.write(parsed_document)
 
 with col2:
     if uploaded_file is not None: