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| import os | |
| import gradio as gr | |
| import google.generativeai as genai | |
| import chardet # Auto-detect file encoding | |
| GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") | |
| if not GOOGLE_API_KEY: | |
| raise ValueError("⚠ Error: Google API Key is missing. Set it in Hugging Face Secrets.") | |
| genai.configure(api_key=GOOGLE_API_KEY) | |
| model = genai.GenerativeModel(model_name="models/gemini-2.0-flash") | |
| def read_file_with_encoding(file_path): | |
| try: | |
| with open(file_path, "rb") as f: | |
| raw_data = f.read() | |
| # Detect file encoding | |
| encoding = chardet.detect(raw_data)["encoding"] | |
| if encoding is None: | |
| encoding = "utf-8" # Default to UTF-8 if detection fails | |
| # Read file with detected encoding | |
| with open(file_path, "r", encoding=encoding, errors="replace") as f: | |
| return f.read() | |
| except Exception as e: | |
| return f"⚠ Error reading file: {str(e)}" | |
| def analyze_input(text, file): | |
| try: | |
| if file is not None: | |
| text = read_file_with_encoding(file) # Auto-detect encoding | |
| elif not text.strip(): | |
| return "⚠ Error: Please enter text or upload a file.", "" | |
| text = text[:2000] # Limit input text size | |
| prompt = f"Analyze and summarize this document:\n\n{text}" | |
| response = model.generate_content([prompt], stream=True) # Fix applied | |
| # Collect streamed response | |
| result = "".join([chunk.text for chunk in response]) | |
| word_count = len(text.split()) | |
| return result, f"Word Count: {word_count}" | |
| except Exception as e: | |
| return f"⚠ Error: {str(e)}", "" | |
| def clear_inputs(): | |
| return "", None, "", "", None | |
| def generate_downloadable_file(text): | |
| if text.strip(): | |
| file_path = "analysis_result.txt" | |
| with open(file_path, "w", encoding="utf-8") as f: | |
| f.write(text) | |
| return file_path | |
| else: | |
| return None | |
| with gr.Blocks(theme=gr.themes.Default()) as demo: | |
| gr.Markdown(""" | |
| Upload a .txt file or enter text manually to get an AI-generated analysis and summary. | |
| """) | |
| with gr.Row(): | |
| text_input = gr.Textbox(label="Enter Text", placeholder="Type or paste your text here...", lines=6) | |
| file_input = gr.File(label="Upload Text File (.txt)", type="filepath") | |
| output_text = gr.Textbox(label="Analysis Result", lines=10, interactive=False) | |
| word_count_display = gr.Textbox(label="Word Count", interactive=False) | |
| with gr.Row(): | |
| analyze_button = gr.Button("Analyze", variant="primary") | |
| clear_button = gr.Button("Clear", variant="secondary") | |
| with gr.Column(): | |
| gr.Markdown("###Download Analysis Result") | |
| with gr.Row(): | |
| download_button = gr.Button("⬇ Download Result", variant="success", size="sm") | |
| download_file = gr.File(label="📄 Click to Download", interactive=False) | |
| analyze_button.click(analyze_input, inputs=[text_input, file_input], outputs=[output_text, word_count_display]) | |
| clear_button.click(clear_inputs, inputs=[], outputs=[text_input, file_input, output_text, word_count_display, download_file]) | |
| download_button.click(generate_downloadable_file, inputs=output_text, outputs=download_file) | |
| demo.launch() |