sync with remote

app.py

@@ -38,18 +38,29 @@ if "uploaded_file_part" not in st.session_state:  # Store the file *part*
 if "uploaded_pdf_path" not in st.session_state:
     st.session_state.uploaded_pdf_path = get_local_pdf_path()
 
-def multimodal_prompt(pdf_path, text_prompt):
+def multimodal_prompt(pdf_path, text_prompt, file_type="PDF"):
     """
     Sends a multimodal prompt to Gemini, handling file uploads efficiently.
     Args:
-        pdf_path: The path to the PDF file.
+        pdf_path: The path to the file (PDF or image).
         text_prompt: The text prompt for the model.
+        file_type: "PDF" or "image" to specify the file type.
     Returns:
         The model's response as a string, or an error message.
     """
     try:
-        if st.session_state.uploaded_file_part is None:  # First time, upload
-            pdf_part = genai.upload_file(pdf_path, mime_type="application/pdf")
+        if file_type == "PDF":
+            mime_type = "application/pdf"
+        elif file_type == "image":
+            import mimetypes
+            mime_type, _ = mimetypes.guess_type(pdf_path)
+            if mime_type is None:
+              return "Could not determine MIME type for image. Please check the file path or type."
+        else:
+            return "Invalid file_type. Must be 'PDF' or 'image'."
+
+        if st.session_state.get("uploaded_file_part") is None:  # First time, upload
+            pdf_part = genai.upload_file(pdf_path, mime_type=mime_type)
             st.session_state.uploaded_file_part = pdf_part
             prompt = [text_prompt, pdf_part]  # First turn includes the actual file
         else:  # Subsequent turns, reference the file
@@ -58,7 +69,7 @@ def multimodal_prompt(pdf_path, text_prompt):
         response = chat.send_message(prompt)
 
         # Update conversation history
-        st.session_state.conversation_history.append({"role": "user", "content": text_prompt, "has_pdf": True})
+        st.session_state.conversation_history.append({"role": "user", "content": text_prompt, "has_file": True})
         st.session_state.conversation_history.append({"role": "assistant", "content": response.text})
         return response.text
 
@@ -91,61 +102,29 @@ Example JSON output:
 ]
 """
 
-# Define a function to extract equations from the AI response
-def extract_equations(response):
-    try:
-        if isinstance(response, str):
-            response = response.strip().replace("\n", "").replace("\r", "")
-            if response.lower().startswith("json"):
-                response = response[4:].strip()
-            if response.startswith("[") and response.endswith("]"):
-                return json.loads(response)
-            else:
-                st.error("Error: AI response is not in expected JSON list format.")
-                return []
-        elif isinstance(response, list):
-            return response
-        else:
-            st.error("Error: Unexpected response format from AI.")
-            return []
-    except json.JSONDecodeError:
-        st.error("Error: Failed to parse AI response as a list.")
-        return []
-
-# Define a function to extract quadratic equations from the problems
-def extract_quadratic_equations(problems):
-    equations = []
-    for problem in problems:
-        match = re.search(r'([0-9x\^\+\-\=\s]+)', problem)
-        if match:
-            equations.append(match.group(1).strip())
-        else:
-            st.warning(f"Could not extract equation from: '{problem}'")
-    return equations
-
 # Main code
 with st.spinner("AI is thinking..."):
     if st.session_state.get("uploaded_pdf_path") is None:
         st.session_state.uploaded_pdf_path = get_local_pdf_path()
 
     filepath = st.session_state.uploaded_pdf_path
-    response = multimodal_prompt(filepath, TEXT_PROMPT)
+    response = multimodal_prompt(filepath, TEXT_PROMPT, file_type="PDF")
+
+# Remove the ```json and ``` and extra spaces.
+try:
+    json_string = response.replace('```json', '').replace('```', '').strip()
 
-# Debugging: Print response
-st.write("Raw AI Response:", response)
+    # Parse the JSON string into a Python list.
+    problems_list = json.loads(json_string)
 
-# Extract equations
-problems = extract_equations(response)
-if problems:
-    equations = extract_quadratic_equations(problems)
-    st.write("Extracted Equations:")
-    for equation in equations:
-        st.write(equation)
-else:
-    st.error("Error: No valid equations extracted.")
+    # Iterate over the list and print each item using st.write().
+    for item in problems_list:
+        st.write(item)
 
+except json.JSONDecodeError:
+    st.write("Error: Invalid JSON format in the response.")
 except Exception as e:
-    st.error(f"An unexpected error occurred: {e}")
+    st.write(f"An unexpected error occurred: {e}")
 
 
 st.markdown("Visit our Hugging Face Space!")