Update app.py

app.py

@@ -1,494 +1,18 @@
-import pymupdf4llm
-from markdown_it import MarkdownIt
-from mdit_plain.renderer import RendererPlain
-import os
-import re
-from typing import Tuple, Optional, List, Dict, Any
-
-import fitz  # PyMuPDF
-from collections import defaultdict, Counter
-import language_tool_python
-
+# app.py
 import json
 import traceback
-import io
 import tempfile
-# import os # Already imported
+import os
 import gradio as gr
+from typing import Tuple, Optional # For type hinting
 
-# Set JAVA_HOME environment variable (from target script)
-os.environ['JAVA_HOME'] = '/usr/lib/jvm/java-11-openjdk-amd64'
-
-
-# --- Functions for PDF to Markdown to Plain Text ---
-def convert_markdown_to_plain_text(markdown_text: str) -> str:
-    """
-    Converts a Markdown string to plain text.
-    """
-    if not markdown_text:
-        return ""
-    try:
-        parser = MarkdownIt(renderer_cls=RendererPlain)
-        plain_text = parser.render(markdown_text)
-        return plain_text
-    except Exception as e:
-        print(f"Error converting Markdown to plain text: {e}")
-        return markdown_text
-
-# --- Function for Rectangle Conversion ---
-def convert_rect_to_dict(rect: fitz.Rect) -> Optional[Dict[str, float]]:
-    """Converts a fitz.Rect object to a dictionary."""
-    if not rect or not isinstance(rect, fitz.Rect):
-        print(f"Warning: Invalid rect object received: {rect}")
-        return None
-    return {
-        "x0": rect.x0,
-        "y0": rect.y0,
-        "x1": rect.x1,
-        "y1": rect.y1,
-        "width": rect.width,
-        "height": rect.height
-    }
-
-# --- Helper function for mapping LT issues to PDF rectangles ---
-def try_map_issues_to_page_rects(
-    issues_to_map_for_context: List[Dict[str, Any]],
-    pdf_rects: List[fitz.Rect],
-    page_number_for_mapping: int # 1-based page number
-) -> int:
-    mapped_count = 0
-    num_issues_to_try = len(issues_to_map_for_context)
-    num_available_rects = len(pdf_rects)
-    limit = min(num_issues_to_try, num_available_rects)
-
-    for i in range(limit):
-        issue_to_update = issues_to_map_for_context[i]
-        if issue_to_update['is_mapped_to_pdf']: # Check the correct flag name
-            continue
-        pdf_rect = pdf_rects[i]
-        coord_dict = convert_rect_to_dict(pdf_rect)
-        if coord_dict:
-            issue_to_update['pdf_coordinates_list'] = [coord_dict] # Store as list of dicts
-            issue_to_update['is_mapped_to_pdf'] = True
-            issue_to_update['mapped_page_number'] = page_number_for_mapping
-            mapped_count += 1
-        else:
-            print(f"      Warning: Could not convert rect for context '{issue_to_update['context_text'][:30]}...' on page {page_number_for_mapping}")
-    return mapped_count
-
-
-# ------------------------------
-# Analysis Functions (from target script, with modifications)
-# ------------------------------
-
-def extract_pdf_text(file_input: Any) -> str:
-    """Extracts full text from a PDF file using PyMuPDF4LLM (as Markdown)."""
-    temp_file_path_for_pymupdf4llm = None
-    actual_path_to_process = None
-    try:
-        if isinstance(file_input, str):
-            actual_path_to_process = file_input
-        elif hasattr(file_input, 'read') and callable(file_input.read):
-            temp_file_obj = tempfile.NamedTemporaryFile(suffix=".pdf", delete=False)
-            temp_file_path_for_pymupdf4llm = temp_file_obj.name
-            file_input.seek(0)
-            temp_file_obj.write(file_input.read())
-            temp_file_obj.close()
-            actual_path_to_process = temp_file_path_for_pymupdf4llm
-        else:
-            raise ValueError("Input 'file_input' must be a file path (str) or a file-like object.")
-
-        doc_for_page_count = fitz.open(actual_path_to_process)
-        page_count = len(doc_for_page_count)
-        doc_for_page_count.close()
-        print(f"PDF has {page_count} pages. Extracting Markdown using pymupdf4llm.")
-        
-        markdown_text = pymupdf4llm.to_markdown(actual_path_to_process)
-        
-        print(f"Total extracted Markdown text length: {len(markdown_text)} characters.")
-        return markdown_text
-        
-    except Exception as e:
-        print(f"Error extracting text from PDF: {str(e)}")
-        traceback.print_exc()
-        return ""
-    finally:
-        if temp_file_path_for_pymupdf4llm and os.path.exists(temp_file_path_for_pymupdf4llm):
-            os.remove(temp_file_path_for_pymupdf4llm)
-
-
-def check_text_presence(full_text: str, search_terms: List[str]) -> Dict[str, bool]:
-    return {term: term.lower() in full_text.lower() for term in search_terms}
-
-def label_authors(full_text: str) -> str:
-    # This function was in the original script but not directly used by analyze_pdf's output structure.
-    # Keeping it in case it's called elsewhere or for future use.
-    author_line_regex = r"^(?:.*\n)(.*?)(?:\n\n)"
-    match = re.search(author_line_regex, full_text, re.MULTILINE)
-    if match:
-        authors = match.group(1).strip()
-        return full_text.replace(authors, f"Authors: {authors}")
-    return full_text
-
-def check_metadata(plain_text: str) -> Dict[str, Any]:
-    return {
-        "author_email": bool(re.search(r'\b[\w.-]+?@\w+?\.\w+?\b', plain_text)),
-        "list_of_authors": bool(re.search(r'Authors?:', plain_text, re.IGNORECASE)),
-        "keywords_list": bool(re.search(r'Keywords?:', plain_text, re.IGNORECASE)),
-        "word_count": len(plain_text.split()) or "Missing"
-    }
-
-def check_disclosures(plain_text: str) -> Dict[str, bool]:
-    search_terms = [
-        "conflict of interest statement",
-        "ethics statement",
-        "funding statement",
-        "data access statement"
-    ]
-    results = check_text_presence(plain_text, search_terms)
-    has_author_contribution = ("author contribution statement" in plain_text.lower() or
-                               "author contributions statement" in plain_text.lower())
-    results["author contribution statement"] = has_author_contribution
-    return results
-
-def check_figures_and_tables(plain_text: str) -> Dict[str, bool]:
-    return {
-        "figures_with_citations": bool(re.search(r'Figure \d+.*?citation', plain_text, re.IGNORECASE)),
-        "figures_legends": bool(re.search(r'Figure \d+.*?legend', plain_text, re.IGNORECASE)),
-        "tables_legends": bool(re.search(r'Table \d+.*?legend', plain_text, re.IGNORECASE))
-    }
-
-def check_references_summary(plain_text: str) -> Dict[str, Any]: # Renamed from check_references for clarity
-    abstract_candidate = plain_text[:2000] 
-    return {
-        "old_references": bool(re.search(r'\b19[0-9]{2}\b', plain_text)), 
-        "citations_in_abstract": bool(re.search(r'\[\d+\]', abstract_candidate, re.IGNORECASE)) or \
-                                 bool(re.search(r'\bcit(?:ation|ed)\b', abstract_candidate, re.IGNORECASE)),
-        "reference_count": len(re.findall(r'\[\d+(?:,\s*\d+)*\]', plain_text)), 
-        "self_citations": bool(re.search(r'Self-citation', plain_text, re.IGNORECASE)) 
-    }
-
-def check_structure(plain_text: str) -> Dict[str, bool]:
-    text_lower = plain_text.lower()
-    return {
-        "imrad_structure": all(section.lower() in text_lower for section in ["introduction", "method", "result", "discussion"]),
-        "abstract_structure": "structured abstract" in text_lower
-    }
-
-def check_language_issues_and_regex(markdown_text_from_pdf: str) -> Dict[str, Any]:
-    """
-    Performs LanguageTool and specific regex checks on text derived from PDF's Markdown.
-    Filters issues to only include those between "abstract" and "references/bibliography".
-    Returns a list of issue dictionaries with fields for mapping.
-    """
-    if not markdown_text_from_pdf.strip():
-        return {"total_issues": 0, "issues_list": [], "text_used_for_analysis": ""}
-
-    plain_text_from_markdown = convert_markdown_to_plain_text(markdown_text_from_pdf)
-    text_for_analysis = plain_text_from_markdown.replace('\n', ' ')
-    text_for_analysis = re.sub(r'\s+', ' ', text_for_analysis).strip()
-
-    if not text_for_analysis:
-        return {"total_issues": 0, "issues_list": [], "text_used_for_analysis": ""}
-
-    # --- Determine content boundaries ---
-    text_for_analysis_lower = text_for_analysis.lower()
-    
-    abstract_match = re.search(r'\babstract\b', text_for_analysis_lower)
-    # If "abstract" is found, analysis starts from its beginning. Otherwise, from text start.
-    content_start_index = abstract_match.start() if abstract_match else 0
-    if abstract_match:
-        print(f"Found 'abstract' at index {content_start_index}")
-    else:
-        print(f"Did not find 'abstract', starting language analysis from index 0")
-
-    references_match = re.search(r'\breferences\b', text_for_analysis_lower)
-    bibliography_match = re.search(r'\bbibliography\b', text_for_analysis_lower)
+# Ensure JAVA_HOME is set before LanguageTool might be initialized.
+# config.py should be imported early if it handles this.
+import config # This will run set_java_home() from config.py
 
-    content_end_index = len(text_for_analysis) # Default to end of text
-
-    if references_match and bibliography_match:
-        content_end_index = min(references_match.start(), bibliography_match.start())
-        print(f"Found 'references' at {references_match.start()} and 'bibliography' at {bibliography_match.start()}. Using {content_end_index} as end boundary.")
-    elif references_match:
-        content_end_index = references_match.start()
-        print(f"Found 'references' at {content_end_index}. Using it as end boundary.")
-    elif bibliography_match:
-        content_end_index = bibliography_match.start()
-        print(f"Found 'bibliography' at {content_end_index}. Using it as end boundary.")
-    else:
-        print(f"Did not find 'references' or 'bibliography'. Language analysis up to end of text (index {content_end_index}).")
-
-    # If "abstract" is found after "references/bibliography", the range is invalid for filtering.
-    # In such a case, or if no abstract is found, we might effectively process a very small or no region.
-    # This logic correctly makes the valid region empty if abstract_start >= content_end.
-    if content_start_index >= content_end_index:
-        print(f"Warning: Content start index ({content_start_index}) is not before content end index ({content_end_index}). No language issues will be reported from this range.")
-        # Effectively, no issues will pass the filter below.
-    
-    tool = None
-    processed_issues: List[Dict[str, Any]] = []
-    try:
-        tool = language_tool_python.LanguageTool('en-US') 
-        raw_lt_matches = tool.check(text_for_analysis)
-        
-        lt_issues_in_range = 0
-        for idx, match in enumerate(raw_lt_matches):
-            if match.ruleId == "EN_SPLIT_WORDS_HYPHEN": continue
-            
-            # Filter by content boundaries
-            if not (content_start_index <= match.offset < content_end_index):
-                continue
-            lt_issues_in_range +=1
-
-            context_str = text_for_analysis[match.offset : match.offset + match.errorLength]
-            processed_issues.append({
-                '_internal_id': f"lt_{idx}",
-                'ruleId': match.ruleId,
-                'message': match.message,
-                'context_text': context_str, 
-                'offset_in_text': match.offset,
-                'error_length': match.errorLength,
-                'replacements_suggestion': match.replacements[:3] if match.replacements else [],
-                'category_name': match.category,
-                'is_mapped_to_pdf': False,
-                'pdf_coordinates_list': [], 
-                'mapped_page_number': -1
-            })
-        print(f"LanguageTool found {len(raw_lt_matches)} raw issues, {lt_issues_in_range} issues within defined content range.")
-        
-        regex_pattern = r'\b(\w+)\[(\d+)\]'
-        regex_matches = list(re.finditer(regex_pattern, text_for_analysis))
-        
-        regex_issues_in_range = 0
-        for reg_idx, match in enumerate(regex_matches):
-            # Filter by content boundaries
-            if not (content_start_index <= match.start() < content_end_index):
-                continue
-            regex_issues_in_range += 1
-            
-            word = match.group(1)
-            number = match.group(2)
-            processed_issues.append({
-                '_internal_id': f"regex_{reg_idx}",
-                'ruleId': "SPACE_BEFORE_BRACKET",
-                'message': f"Missing space before '[' in '{word}[{number}]'. Should be '{word} [{number}]'.",
-                'context_text': text_for_analysis[match.start():match.end()],
-                'offset_in_text': match.start(),
-                'error_length': match.end() - match.start(),
-                'replacements_suggestion': [f"{word} [{number}]"],
-                'category_name': "Formatting",
-                'is_mapped_to_pdf': False,
-                'pdf_coordinates_list': [],
-                'mapped_page_number': -1
-            })
-        print(f"Regex check found {len(regex_matches)} raw matches, {regex_issues_in_range} issues within defined content range.")
-        
-        return {
-            "total_issues": len(processed_issues),
-            "issues_list": processed_issues,
-            "text_used_for_analysis": text_for_analysis 
-        }
-    except Exception as e:
-        print(f"Error in check_language_issues_and_regex: {e}")
-        traceback.print_exc()
-        return {"error": str(e), "total_issues": 0, "issues_list": [], "text_used_for_analysis": text_for_analysis}
-    finally:
-        if tool: tool.close()
-
-def check_figure_order(plain_text: str) -> Dict[str, Any]:
-    figure_pattern = r'(?:Fig(?:ure)?\.?|Figure)\s*(\d+)'
-    figure_references_str = re.findall(figure_pattern, plain_text, re.IGNORECASE)
-    
-    valid_figure_numbers_int = []
-    for num_str in figure_references_str:
-        if num_str.isdigit():
-            valid_figure_numbers_int.append(int(num_str))
-    
-    unique_sorted_figures = sorted(list(set(valid_figure_numbers_int)))
-    is_sequential = all(unique_sorted_figures[i] + 1 == unique_sorted_figures[i+1] for i in range(len(unique_sorted_figures)-1))
-
-    missing_figures = []
-    if unique_sorted_figures:
-        expected_figures = set(range(1, max(unique_sorted_figures) + 1))
-        missing_figures = sorted(list(expected_figures - set(unique_sorted_figures)))
-    
-    counts = Counter(valid_figure_numbers_int)
-    duplicate_refs = [num for num, count in counts.items() if count > 1]
-    
-    return {
-        "sequential_order_of_unique_figures": is_sequential, 
-        "figure_count_unique": len(unique_sorted_figures),
-        "missing_figures_in_sequence_to_max": missing_figures, 
-        "figure_order_as_encountered": valid_figure_numbers_int,
-        "duplicate_references_to_same_figure_number": duplicate_refs
-    }
-
-def check_reference_order(plain_text: str) -> Dict[str, Any]:
-    reference_pattern = r'\[(\d+)\]' 
-    references_str = re.findall(reference_pattern, plain_text)
-    ref_numbers_int = [int(ref) for ref in references_str if ref.isdigit()]
-    
-    max_ref_val = 0
-    out_of_order_details = []
-    
-    if ref_numbers_int:
-        max_ref_val = max(ref_numbers_int)
-        current_max_seen_in_text = 0
-        for i, ref in enumerate(ref_numbers_int):
-            if ref < current_max_seen_in_text : 
-                 out_of_order_details.append({
-                     "position_in_text_occurrences": i + 1, 
-                     "value": ref,
-                     "previous_max_value_seen": current_max_seen_in_text,
-                     "message": f"Reference [{ref}] appeared after a higher reference [{current_max_seen_in_text}] was already cited."
-                 })
-            current_max_seen_in_text = max(current_max_seen_in_text, ref)
-
-    all_expected_refs_up_to_max = set(range(1, max_ref_val + 1)) if max_ref_val > 0 else set()
-    used_refs_set = set(ref_numbers_int)
-    missing_refs_in_sequence_to_max = sorted(list(all_expected_refs_up_to_max - used_refs_set))
-    
-    is_ordered_in_text = all(ref_numbers_int[i] <= ref_numbers_int[i+1] for i in range(len(ref_numbers_int)-1))
-
-    return {
-        "max_reference_number_cited": max_ref_val,
-        "out_of_order_citations_details": out_of_order_details, 
-        "missing_references_up_to_max_cited": missing_refs_in_sequence_to_max,
-        "is_citation_order_non_decreasing_in_text": is_ordered_in_text
-    }
-
-# ------------------------------
-# Main Analysis Function
-# ------------------------------
-
-def analyze_pdf(filepath_or_stream: Any) -> Tuple[Dict[str, Any], None]:
-    doc_for_mapping = None
-    temp_fitz_file_path = None 
-
-    try:
-        markdown_text = extract_pdf_text(filepath_or_stream)
-        if not markdown_text:
-            return {"error": "Failed to extract text (Markdown) from PDF."}, None
-        
-        plain_text_for_general_checks = convert_markdown_to_plain_text(markdown_text)
-        cleaned_plain_text_for_regex = re.sub(r'\s+', ' ', plain_text_for_general_checks.replace('\n', ' ')).strip()
-
-        # This will now use the modified function with boundary filtering
-        language_and_regex_issue_report = check_language_issues_and_regex(markdown_text)
-        
-        if "error" in language_and_regex_issue_report:
-            return {"error": f"Language/Regex check error: {language_and_regex_issue_report['error']}"}, None
-        
-        detailed_issues_for_mapping = language_and_regex_issue_report.get("issues_list", [])
-
-        if detailed_issues_for_mapping:
-            # The rest of the mapping logic remains the same, operating on the filtered issues.
-            if isinstance(filepath_or_stream, str):
-                pdf_path_for_fitz = filepath_or_stream
-            elif hasattr(filepath_or_stream, 'read') and callable(filepath_or_stream.read):
-                filepath_or_stream.seek(0)
-                temp_fitz_file = tempfile.NamedTemporaryFile(suffix=".pdf", delete=False)
-                temp_fitz_file_path = temp_fitz_file.name
-                temp_fitz_file.write(filepath_or_stream.read())
-                temp_fitz_file.close()
-                pdf_path_for_fitz = temp_fitz_file_path
-            else:
-                # This case should ideally be caught by extract_pdf_text, but good to have a fallback
-                return {"error": "Invalid PDF input for coordinate mapping."}, None
-
-            try:
-                doc_for_mapping = fitz.open(pdf_path_for_fitz)
-                if doc_for_mapping.page_count > 0:
-                    print(f"\n--- Mapping {len(detailed_issues_for_mapping)} Issues (filtered) to PDF Coordinates ---")
-                    # Only attempt to map issues if there are any after filtering
-                    if detailed_issues_for_mapping: 
-                        for page_idx in range(doc_for_mapping.page_count):
-                            page = doc_for_mapping[page_idx]
-                            current_page_num_1_based = page_idx + 1
-                            
-                            unmapped_issues_on_this_page_by_context = defaultdict(list)
-                            for issue_dict in detailed_issues_for_mapping:
-                                if not issue_dict['is_mapped_to_pdf']:
-                                    unmapped_issues_on_this_page_by_context[issue_dict['context_text']].append(issue_dict)
-
-                            if not unmapped_issues_on_this_page_by_context:
-                                if all(iss['is_mapped_to_pdf'] for iss in detailed_issues_for_mapping): break
-                                continue
-
-                            for ctx_str, issues_for_ctx in unmapped_issues_on_this_page_by_context.items():
-                                if not ctx_str.strip(): continue
-                                try:
-                                    # Use TEXT_PRESERVE_LIGATURES and TEXT_PRESERVE_WHITESPACE for better matching
-                                    # with text derived from pymupdf4llm which tries to preserve structure.
-                                    pdf_rects = page.search_for(ctx_str, flags=fitz.TEXT_PRESERVE_LIGATURES | fitz.TEXT_PRESERVE_WHITESPACE)
-                                    if pdf_rects:
-                                        try_map_issues_to_page_rects(issues_for_ctx, pdf_rects, current_page_num_1_based)
-                                except Exception as search_exc:
-                                    print(f"Warning: Error searching for context '{ctx_str[:30]}' on page {current_page_num_1_based}: {search_exc}")
-                        total_mapped = sum(1 for iss in detailed_issues_for_mapping if iss['is_mapped_to_pdf'])
-                        print(f"Finished coordinate mapping. Mapped issues: {total_mapped}/{len(detailed_issues_for_mapping)}.")
-                    else:
-                        print("No language/regex issues found within the defined content boundaries to map.")
-            except Exception as e_map:
-                print(f"Error during PDF coordinate mapping: {e_map}")
-                traceback.print_exc()
-            finally:
-                if doc_for_mapping: doc_for_mapping.close()
-                if temp_fitz_file_path and os.path.exists(temp_fitz_file_path):
-                    os.unlink(temp_fitz_file_path)
-        
-        final_formatted_issues_list = []
-        for issue_data in detailed_issues_for_mapping: # This list is already filtered
-            page_num_for_json = 0
-            coords_for_json = []
-            if issue_data['is_mapped_to_pdf'] and issue_data['pdf_coordinates_list']:
-                # Assuming pdf_coordinates_list stores a list of dicts, take the first one
-                coord_dict = issue_data['pdf_coordinates_list'][0] 
-                coords_for_json = [coord_dict['x0'], coord_dict['y0'], coord_dict['x1'], coord_dict['y1']]
-                page_num_for_json = issue_data['mapped_page_number']
-            
-            final_formatted_issues_list.append({
-                "message": issue_data['message'],
-                "context": issue_data['context_text'], 
-                "suggestions": issue_data['replacements_suggestion'],
-                "category": issue_data['category_name'],
-                "rule_id": issue_data['ruleId'],
-                "offset": issue_data['offset_in_text'], 
-                "length": issue_data['error_length'],   
-                "coordinates": coords_for_json,
-                "page": page_num_for_json
-            })
-
-        results = {
-            "issues": final_formatted_issues_list, # This will now contain only filtered issues
-            "document_checks": { 
-                "metadata": check_metadata(cleaned_plain_text_for_regex),
-                "disclosures": check_disclosures(cleaned_plain_text_for_regex),
-                "figures_and_tables": check_figures_and_tables(cleaned_plain_text_for_regex),
-                "references_summary": check_references_summary(cleaned_plain_text_for_regex), 
-                "structure": check_structure(cleaned_plain_text_for_regex),
-                "figure_order_analysis": check_figure_order(cleaned_plain_text_for_regex), 
-                "reference_order_analysis": check_reference_order(cleaned_plain_text_for_regex), 
-                "plain_language_summary_present": bool(re.search(r'plain language summary', cleaned_plain_text_for_regex, re.IGNORECASE)),
-                "readability_issues_detected": False, # Placeholder, not implemented
-            }
-        }
-        
-        return results, None 
-
-    except Exception as e:
-        print(f"Overall analysis error in analyze_pdf: {e}")
-        traceback.print_exc()
-        # Ensure cleanup even if an early error occurs
-        if doc_for_mapping: doc_for_mapping.close()
-        if temp_fitz_file_path and os.path.exists(temp_fitz_file_path):
-            os.unlink(temp_fitz_file_path)
-        return {"error": str(e)}, None
-
-# ------------------------------
-# Gradio Interface
-# ------------------------------
+# Import the main analysis function
+from main_analyzer import analyze_pdf 
+import language_tool_python # For the test initialization
 
 def process_upload(file_data_binary: bytes) -> Tuple[str, Optional[str]]:
     if file_data_binary is None:
@@ -496,16 +20,15 @@ def process_upload(file_data_binary: bytes) -> Tuple[str, Optional[str]]:
 
     temp_input_path = None
     try:
-        # Create a temporary file with .pdf extension from the binary data
         with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as temp_input_file:
             temp_input_file.write(file_data_binary)
             temp_input_path = temp_input_file.name
         print(f"Temporary PDF for analysis: {temp_input_path}")
         
-        results_dict, _ = analyze_pdf(temp_input_path) # Pass the path to the temp file
+        results_dict, _ = analyze_pdf(temp_input_path) 
         
         results_json = json.dumps(results_dict, indent=2, ensure_ascii=False)
-        return results_json, None # No annotated PDF path to return for now
+        return results_json, None
 
     except Exception as e:
         print(f"Error in process_upload: {e}")
@@ -526,7 +49,7 @@ def create_interface():
             file_input = gr.File(
                 label="Upload PDF",
                 file_types=[".pdf"],
-                type="binary" # Changed to binary to handle uploads directly
+                type="binary"
             )
         
         with gr.Row():
@@ -539,43 +62,34 @@ def create_interface():
             )
         
         with gr.Row():
-            # Keeping the placeholder for PDF output, but it's not functional for annotation
             pdf_output = gr.File(
                 label="Annotated PDF (Functionality Removed - View Coordinates in JSON)",
                 show_label=True,
-                # value=None # Ensure it's empty initially
             )
         
         analyze_btn.click(
             fn=process_upload,
             inputs=[file_input],
-            outputs=[results_output, pdf_output] # pdf_output will receive None
+            outputs=[results_output, pdf_output]
         )
     return interface
 
 if __name__ == "__main__":
     print("\n--- Launching Gradio Interface ---")
-    # Ensure JAVA_HOME is set if not globally configured
-    if 'JAVA_HOME' not in os.environ:
-        # Attempt to set a common default if necessary, or ensure the user sets it.
-        # For this script, it's set at the top.
-        print("JAVA_HOME is set to:", os.environ.get('JAVA_HOME'))
-    else:
-        print("JAVA_HOME is set to:", os.environ.get('JAVA_HOME'))
+    # config.py handles JAVA_HOME setting upon its import
 
-    # Check if LanguageTool can be initialized (optional check)
+    # Optional: Check if LanguageTool can be initialized (as in original)
     try:
         lt_test = language_tool_python.LanguageTool('en-US')
         lt_test.close()
-        print("LanguageTool initialized successfully.")
+        print("LanguageTool initialized successfully for test.")
     except Exception as lt_e:
-        print(f"Warning: Could not initialize LanguageTool. Language checks might fail: {lt_e}")
-        print("Please ensure Java is installed and JAVA_HOME is correctly set.")
+        print(f"Warning: Could not initialize LanguageTool for test. Language checks might fail: {lt_e}")
+        print("Please ensure Java is installed and JAVA_HOME is correctly set by config.py or environment.")
         print("For example, on Ubuntu with OpenJDK 11: export JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64")
 
-
     interface = create_interface()
     interface.launch(
-        share=False, # Set to True for public link if ngrok is installed
-        server_port=None # Gradio will pick an available port
+        share=False, 
+        server_port=None 
     )