Upload 2 files

app.py

@@ -91,9 +91,9 @@ def predict(user_input,company):
     }
 
     filter = "dataset/"+company+"-10-k-2023.pdf"
-   
+
     # Create context_for_query
-    relevant_document_chunks = dataset_db.similarity_search(user_question, k=5, filter = {"source":"dataset/google-10-k-2023.pdf"})
+    relevant_document_chunks = reportsdb.similarity_search(user_question, k=5, filter = {"source":filter})
     context_list = [d.page_content for d in relevant_document_chunks]
     context_for_query = ". ".join(context_list)
 
@@ -123,19 +123,6 @@ def predict(user_input,company):
 
 
     # Get response from the LLM
-def predict_output (user_input,company):
-    if company == "AWS":
-       company = "AWS"
-    elif company == "IBM":
-       company = "IBM"
-    elif company == "Google":
-       company = "Google"
-    elif company == "Msft":
-       company = "Msft"
-    elif company == "Meta":
-       company = "Meta"
-    model_output = predict(user_input,company)
-    return model_output
 
     # While the prediction is made, log both the inputs and outputs to a local log file
     # While writing to the log file, ensure that the commit scheduler is locked to avoid parallel
@@ -161,7 +148,7 @@ company_input = gr.Radio(
     label = 'company'
     )
 
-model_output = gr.Textbox (label = 'Response')
+model_output = gr.Text (label = 'Response')
 
 # Add text box and radio button to the interface
 # The radio button is used to select the company 10k report in which the context needs to be retrieved.
@@ -173,8 +160,8 @@ model_output = gr.Textbox (label = 'Response')
 
 demo = gr.Interface(
     fn=predict_output,
-    inputs=[user_input,company_input],
-    outputs=model_output,
+    inputs=[user_input,company],
+    outputs=prediction,
     title="RAG on 10k-reports",
     description="This API allows you to query on annaul reports",
     concurrency_limit=16

requirements.txt

@@ -1,5 +1,5 @@
-openai==1.23.2 \
-langchain==0.1.9 \
-langchain-community==0.0.32 \
-chromadb==0.4.22 \
-sentence-transformers==2.3.1 \
+openai==1.23.2
+langchain==0.1.9
+langchain-community==0.0.32
+chromadb==0.4.22
+sentence-transformers==2.3.1