Update app.py

app.py

@@ -17,8 +17,16 @@ from langchain_huggingface import ChatHuggingFace
 from langchain_core.output_parsers import StrOutputParser
 from langchain_huggingface import HuggingFaceEndpoint
 from dotenv import load_dotenv
+import pkg_resources
 load_dotenv()
 HF_token = os.environ["HF_TOKEN"]
+installed_packages = pkg_resources.working_set
+package_list_ = ""
+for package in installed_packages:
+    package_list_ = package_list_ + f"{package.key}=={package.version}\n"
+
+
+
 ######## Vector Store #######
 # process all files and get the vectorstores collections
 # vectorestore colection are stored on persistent storage so this needs to be run only once
@@ -93,7 +101,7 @@ async def chat(query,history,sources,reports,subtype,year):
 
     ##------------------------decide which collection to fetch------------------------------
     if len(reports) == 0:
-        vectorstore = get_local_qdrant(source)
+        vectorstore = get_local_qdrant(sources)
     else:
         vectorstore = get_local_qdrant("allreports")
 
@@ -317,6 +325,8 @@ with gr.Blocks(title="Audit Q&A", css= "style.css", theme=theme,elem_id = "main-
                 - By using this chatbot, you agree to these terms and acknowledge that you are solely responsible for any reliance on or actions taken based on its responses.
                 - **This is just a prototype and being tested and worked upon, so its not perfect and may sometimes give irrelevant answers**. If you are not satisfied with the answer, please ask a more specific question or report your feedback to help us improve the system.
                 """)
+                
+                gr.DownloadButton("Download the file",value = "requirements.txt",inputs = package_list_, visible=True)
 
     # using event listeners for 1. query box 2. click on example question
     # https://www.gradio.app/docs/gradio/textbox#event-listeners-arguments