Upload 3 files

app.py

@@ -1,3 +1,4 @@
+import json
 import os
 from typing import Any
 from functools import lru_cache
@@ -30,7 +31,7 @@ EMBEDDING_MODEL = os.getenv(
 
 def upload_textbook(pdf_path):
     if not pdf_path:
-        return "Choose a PDF first.", {}, gr.update()
+        return "Choose a PDF first.", "{}", gr.update()
 
     if not BACKEND_URL:
         return upload_textbook_locally(pdf_path)
@@ -50,17 +51,17 @@ def upload_textbook(pdf_path):
             return (
                 f"Uploaded {result['filename']} with {result['page_count']} pages "
                 f"and {result['chunk_count']} chunks.{method_text}",
-                {},
+                "{}",
                 gr.update(value=""),
             )
 
-        return _response_error(response, "Upload failed."), {}, gr.update()
+        return _response_error(response, "Upload failed."), "{}", gr.update()
     except requests.Timeout:
-        return "Backend is still processing the PDF. Try a smaller PDF for the demo.", {}, gr.update()
+        return "Backend is still processing the PDF. Try a smaller PDF for the demo.", "{}", gr.update()
     except requests.RequestException as exc:
-        return f"Could not reach backend: {exc}", {}, gr.update()
+        return f"Could not reach backend: {exc}", "{}", gr.update()
     except OSError as exc:
-        return f"Could not read uploaded PDF: {exc}", {}, gr.update()
+        return f"Could not read uploaded PDF: {exc}", "{}", gr.update()
 
 
 def upload_textbook_locally(pdf_path):
@@ -69,7 +70,7 @@ def upload_textbook_locally(pdf_path):
         chunks = chunk_text(extracted["text"])
 
         if not chunks:
-            return "No readable text chunks could be created from this PDF.", {}, gr.update()
+            return "No readable text chunks could be created from this PDF.", "{}", gr.update()
 
         embeddings = embed_texts(chunks)
         state = {
@@ -86,11 +87,11 @@ def upload_textbook_locally(pdf_path):
                 f"{state['page_count']} pages and {state['chunk_count']} chunks. "
                 f"Text extraction: {state['extraction_method']}."
             ),
-            state,
+            encode_state(state),
             gr.update(value=""),
         )
     except Exception as exc:
-        return f"Could not process uploaded PDF in this Space: {exc}", {}, gr.update()
+        return f"Could not process uploaded PDF in this Space: {exc}", "{}", gr.update()
 
 
 def ask_tutor(
@@ -110,7 +111,7 @@ def ask_tutor(
             "1. Add a question first.\n2. Then try again.\n3. Use a textbook topic.",
             "",
             "Waiting for a question.",
-            {},
+            "{}",
         )
 
     if BACKEND_URL:
@@ -123,7 +124,7 @@ def ask_tutor(
         question=question,
         student_id=student_id,
         textbook_context=textbook_context,
-        textbook_state=textbook_state or {},
+        textbook_state=decode_state(textbook_state),
     )
 
 
@@ -180,7 +181,7 @@ def format_backend_response(
         format_quiz(quiz_questions),
         format_sources(data.get("retrieved_sources", [])),
         "Answered with the backend RAG workflow.",
-        state,
+        encode_state(state),
     )
 
 
@@ -191,7 +192,7 @@ def grade_quiz(
     student_id,
     quiz_state,
 ):
-    quiz_state = quiz_state or {}
+    quiz_state = decode_state(quiz_state)
     quiz_id = quiz_state.get("quiz_id")
 
     if not BACKEND_URL:
@@ -441,7 +442,7 @@ def mock_response(question: str, textbook_context: str) -> tuple[str, str, str,
             ]
         ),
         "Demo fallback is active. Configure BACKEND_URL in Space settings for PDF upload, RAG search, quiz grading, and parent summary.",
-        {"quiz_questions": quiz_questions},
+        encode_state({"quiz_questions": quiz_questions}),
     )
 
 
@@ -489,7 +490,7 @@ def local_response(
         format_quiz(quiz_questions),
         format_sources(sources),
         "Answered with the Hugging Face Space local PDF workflow.",
-        quiz_state,
+        encode_state(quiz_state),
     )
 
 
@@ -768,6 +769,25 @@ def _response_error(response: requests.Response, fallback: str) -> str:
         return fallback
 
 
+def encode_state(state: dict[str, Any]) -> str:
+    return json.dumps(state, ensure_ascii=False)
+
+
+def decode_state(state: Any) -> dict[str, Any]:
+    if isinstance(state, dict):
+        return state
+
+    if not state:
+        return {}
+
+    try:
+        decoded = json.loads(str(state))
+    except (TypeError, ValueError):
+        return {}
+
+    return decoded if isinstance(decoded, dict) else {}
+
+
 def truncate(text: str, max_length: int) -> str:
     if len(text) <= max_length:
         return text
@@ -784,8 +804,8 @@ with gr.Blocks(title=APP_NAME, theme=gr.themes.Soft()) as demo:
         """
     )
 
-    quiz_state = gr.State({})
-    textbook_state = gr.State({})
+    quiz_state = gr.State("{}")
+    textbook_state = gr.State("{}")
 
     with gr.Row():
         student_id_input = gr.Textbox(
@@ -870,7 +890,8 @@ with gr.Blocks(title=APP_NAME, theme=gr.themes.Soft()) as demo:
             status_output,
             quiz_state,
         ],
-        fn=lambda question, context: ask_tutor(question, "hf-space-demo", context, {}),
+        fn=lambda question, context: ask_tutor(question, "hf-space-demo", context, "{}"),
+        api_name=False,
         cache_examples=False,
     )
 
@@ -878,6 +899,7 @@ with gr.Blocks(title=APP_NAME, theme=gr.themes.Soft()) as demo:
         fn=upload_textbook,
         inputs=[pdf_input],
         outputs=[upload_output, textbook_state, context_input],
+        api_name=False,
     )
     ask_button.click(
         fn=ask_tutor,
@@ -890,16 +912,19 @@ with gr.Blocks(title=APP_NAME, theme=gr.themes.Soft()) as demo:
             status_output,
             quiz_state,
         ],
+        api_name=False,
     )
     grade_button.click(
         fn=grade_quiz,
         inputs=[answer_1, answer_2, answer_3, student_id_input, quiz_state],
         outputs=[grade_output],
+        api_name=False,
     )
     summary_button.click(
         fn=parent_summary,
         inputs=[student_id_input],
         outputs=[summary_output],
+        api_name=False,
     )