Update app.py

app.py

@@ -1,4 +1,4 @@
-import streamlit as st
+code ="import streamlit as st
 import json
 import os
 from datasets import load_dataset
@@ -31,9 +31,50 @@ if not os.path.exists(DATA_FOLDER):
 
 st.title("JSON File Uploader and Question Answering")
 
-uploaded_file = st.file_uploader("Upload a JSON file", type=["json"])
+# Option to upload a file or provide a local file path
+input_option = st.radio("Choose input method:", ("Upload a JSON file", "Enter local file path"))
+
+uploaded_file = None
+local_file_path_input = None
+
+if input_option == "Upload a JSON file":
+    uploaded_file = st.file_uploader("Upload a JSON file", type=["json"])
+elif input_option == "Enter local file path":
+    local_file_path_input = st.text_input("Enter local JSON file path (e.g., datasets/1.json):")
+
+file_path_to_process = None
+file_name = None
+json_data = None
 
 if uploaded_file is not None:
+    try:
+        json_data = json.load(uploaded_file)
+        file_name = uploaded_file.name
+        file_path_to_process = os.path.join(DATA_FOLDER, file_name)
+    except json.JSONDecodeError:
+        st.error("Error: The uploaded file is not a valid JSON file.")
+        st.stop()
+    except Exception as e:
+        st.error(f"An error occurred while processing the uploaded file: {e}")
+        st.stop()
+elif local_file_path_input:
+    if os.path.exists(local_file_path_input):
+        try:
+            with open(local_file_path_input, 'r') as f:
+                json_data = json.load(f)
+            file_name = os.path.basename(local_file_path_input)
+            file_path_to_process = os.path.join(DATA_FOLDER, file_name)
+        except json.JSONDecodeError:
+            st.error("Error: The provided local file is not a valid JSON file.")
+            st.stop()
+        except Exception as e:
+            st.error(f"An error occurred while processing the local file: {e}")
+            st.stop()
+    else:
+        st.error(f"Error: The local file path '{local_file_path_input}' does not exist.")
+        st.stop()
+
+if json_data is not None:
     try:
         # Load API keys and Hugging Face token from environment variables
         groq_api = os.environ.get("groq_api")
@@ -51,21 +92,12 @@ if uploaded_file is not None:
             )
             st.stop()
 
-        # Read the JSON file
-        json_data = json.load(uploaded_file)
-
-        # Get the filename
-        file_name = uploaded_file.name
-
-        # Construct the full file path
-        file_path = os.path.join(DATA_FOLDER, file_name)
-
         # Save the file to the data folder
-        with open(file_path, "w") as f:
+        with open(file_path_to_process, "w") as f:
             json.dump(json_data, f, indent=4)  # Save with indentation for readability
 
-        st.success(f"File '{file_name}' successfully uploaded and saved to:")
-        st.code(file_path, language="plaintext")
+        st.success(f"File '{file_name}' successfully loaded and saved to:")
+        st.code(file_path_to_process, language="plaintext")
 
         st.subheader("Process JSON Data and Enable Question Answering")
 
@@ -176,7 +208,7 @@ just reformulate it if needed and otherwise return it as is."""),
         st.subheader("Generate Structured Output")
         if st.button("Generate Structured Cancer Information"):
             with st.spinner("Generating structured output..."):
-                json_data = json.loads(Path(file_path).read_text())
+                json_data = json.loads(Path(file_path_to_process).read_text())
                 context = ""
                 for item in json_data:
                     context += json.dumps(item, indent=4)
@@ -210,7 +242,7 @@ just reformulate it if needed and otherwise return it as is."""),
                     """Structured information about cancer diagnosis and medication."""
                     diagnosis_characteristics: List[DiagnosisCharacteristic] = field(metadata={"description": "List of primary cancers"})
                     cancer_related_medications: List[CancerRelatedMedication] = field(metadata={"description": "List of cancer related medication given to the patient"})
-                    
+
                 llm = ChatGroq(groq_api_key=groq_api, model_name="llama-3.1-8b-instant")
                 structured_llm = llm.with_structured_output(CancerInformation)
                 try:
@@ -219,7 +251,7 @@ just reformulate it if needed and otherwise return it as is."""),
                     st.json(output.dict())
 
                     # Save the generated output to a JSON file
-                    output_filename = f"{Path(file_path).stem}_structured.json"
+                    output_filename = f"{Path(file_path_to_process).stem}_structured.json"
                     output_filepath = os.path.join(DATA_FOLDER, output_filename)
                     with open(output_filepath, "w") as f:
                         json.dump(output, f, indent=4)
@@ -235,10 +267,7 @@ just reformulate it if needed and otherwise return it as is."""),
 
                 except Exception as e:
                     st.error(f"Error generating structured output: {e}")
-
-    except json.JSONDecodeError:
-        st.error("Error: The uploaded file is not a valid JSON file.")
     except Exception as e:
-        st.error(f"An error occurred: {e}")
+        st.error(f"An unexpected error occurred: {e}")
 else:
-    st.info("Please upload a JSON file.")
+    st.info("Please upload a JSON file or enter a local file path.")