Adding another class to chat with uploaded document

app.py

@@ -10,6 +10,7 @@ from dotenv import load_dotenv
 from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
 
+from csv_agent import CSVAgent
 from grader import Grader
 from grader_qa import GraderQA
 from ingest import ingest_canvas_discussions
@@ -197,14 +198,13 @@ def upload_grading_results(file, history):
     path = os.path.join("output", os.path.basename(file.name))
     # Copy the uploaded file from its temporary location to the desired location
     shutil.copyfile(file.name, path)
-    grader = Grader(qa_model)
-    grader_qa = GraderQA(grader, embeddings)
+    grader_qa = CSVAgent(llm, embeddings, path)
     history = [(None, 'Grading results uploaded successfully')]
     return history
 
 
 def bot(history):
-    return get_grading_status(history)
+    return history
 
 
 with gr.Blocks() as demo:

csv_agent.py

@@ -0,0 +1,35 @@
+from langchain.agents import create_csv_agent, AgentType
+
+import utils
+
+
+class CSVAgent:
+    def __init__(self, llm, embeddings, file):
+        self.llm = llm
+        self.file = file
+        self.summary_index_name = "canvas-discussions-summary"
+        self.folder_path = "vector_stores/"
+        self.summary_index_file = "vector_stores/canvas-discussions-summary.faiss"
+        self.summary_pickle_file = "vector_stores/canvas-discussions-summary.pkl"
+        self.summary_docs = utils.get_csv_files(self.file, source_column='student_name')
+        self.summary_index = self.get_search_index(embeddings)
+        self.agent = self.create_agent()
+
+    def get_search_index(self, embeddings):
+        if utils.index_exists(self.summary_pickle_file, self.summary_index_file):
+            # Load index from pickle file
+            search_index = utils.load_index(self.folder_path, self.summary_index_name, embeddings)
+        else:
+            search_index = utils.create_index(self.folder_path, self.summary_index_name, embeddings, self.summary_docs)
+            print("Created index")
+        return search_index
+
+    def create_agent(self):
+
+        agent = create_csv_agent(
+            self.llm,
+            self.file,
+            verbose=True,
+            agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+        )
+        return agent