Update app.py

app.py

@@ -1,92 +1,107 @@
 import gradio as gr
 import os
-import openai
-import pdfplumber
-import docx
-import pandas as pd
-from PIL import Image
-from io import BytesIO
-import base64
 import tempfile
 import whisper
+import docx
+import pdfplumber
+import pandas as pd
+from groq import Groq
+from PyPDF2 import PdfReader
 
-openai.api_key = os.environ.get("GROQ_API_KEY")
-
-# Load Whisper model
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+client = Groq(api_key=GROQ_API_KEY)
 whisper_model = whisper.load_model("base")
 
-def extract_text_from_file(file):
-    if file.name.endswith(".pdf"):
-        with pdfplumber.open(file.name) as pdf:
-            text = "\n".join(page.extract_text() for page in pdf.pages if page.extract_text())
-    elif file.name.endswith(".docx"):
-        doc = docx.Document(file.name)
-        text = "\n".join(p.text for p in doc.paragraphs)
-    elif file.name.endswith(".xlsx"):
-        df = pd.read_excel(file.name)
-        text = df.to_string()
-    elif file.name.endswith((".png", ".jpg", ".jpeg")):
-        img = Image.open(file.name)
-        buffer = BytesIO()
-        img.save(buffer, format="PNG")
-        encoded = base64.b64encode(buffer.getvalue()).decode("utf-8")
-        text = f"[Image uploaded: data:image/png;base64,{encoded[:100]}... (truncated)]"
-    else:
-        with open(file.name, "r", encoding="utf-8", errors="ignore") as f:
-            text = f.read()
-    return text
-
-def transcribe_audio(audio_path):
-    result = whisper_model.transcribe(audio_path)
-    return result["text"]
-
-def generate_reply(history):
-    messages = [{"role": "system", "content": "You are a helpful assistant."}]
-    for user_msg, bot_msg in history:
-        messages.append({"role": "user", "content": user_msg})
-        messages.append({"role": "assistant", "content": bot_msg})
-
-    response = openai.ChatCompletion.create(
-        model="llama3-8b-8192",
-        messages=messages,
-        temperature=0.7
-    )
-    reply = response.choices[0].message.content
-    return reply
-
-def respond(message, history):
-    reply = generate_reply(history + [[message, ""]])
-    history.append([message, reply])
-    return history, ""
-
-def handle_file_upload(file, message):
+def read_file(file):
     if file is None:
-        return message
-    file_content = extract_text_from_file(file)
-    return f"{message}\n\n--- File Content Start ---\n{file_content}\n--- File Content End ---"
+        return ""
+    ext = os.path.splitext(file.name)[-1].lower()
+    try:
+        if ext == ".txt":
+            with open(file.name, "r", encoding="utf-8") as f:
+                return f.read()
+        elif ext == ".pdf":
+            text = ""
+            with pdfplumber.open(file.name) as pdf:
+                for page in pdf.pages:
+                    text += page.extract_text() + "\n"
+            return text
+        elif ext in [".doc", ".docx"]:
+            doc = docx.Document(file.name)
+            return "\n".join([para.text for para in doc.paragraphs])
+        elif ext in [".xls", ".xlsx"]:
+            df = pd.read_excel(file.name)
+            return df.to_string(index=False)
+        else:
+            return f"[Unsupported file format: {ext}]"
+    except Exception as e:
+        return f"[Error reading file: {e}]"
 
-def handle_audio_upload(audio, message):
+def transcribe_audio(audio):
     if audio is None:
-        return message
-    transcription = transcribe_audio(audio)
-    return f"{message}\n\n--- Transcription ---\n{transcription}"
+        return ""
+    try:
+        audio_path = audio.name
+        result = whisper_model.transcribe(audio_path)
+        return result["text"]
+    except Exception as e:
+        return f"[Error transcribing audio: {e}]"
+
+def process_input(message, history):
+    if not message.strip():
+        return history
+
+    history = history or []
+    history.append({"role": "user", "content": message})
+
+    try:
+        response = client.chat.completions.create(
+            model="llama3-8b-8192",
+            messages=history,
+        )
+        reply = response.choices[0].message.content
+        history.append({"role": "assistant", "content": reply})
+    except Exception as e:
+        history.append({"role": "assistant", "content": f"[Error: {e}]"})
+    
+    return history
+
+def interface_func(message, history, file, audio):
+    file_text = read_file(file) if file else ""
+    audio_text = transcribe_audio(audio) if audio else ""
+    combined = ""
+
+    if file_text:
+        combined += f"{file.name} content:\n{file_text}\n\n"
+    if audio_text:
+        combined += f"Transcribed audio:\n{audio_text}\n\n"
+    if message:
+        combined += message
+
+    return combined.strip()
+
+with gr.Blocks(css="textarea { font-size: 16px !important; }") as demo:
+    gr.Markdown("<h1 style='text-align: center;'>NEOBOT</h1>")
 
-with gr.Blocks(css="body { background-color: white; color: black }") as demo:
-    gr.Markdown("<h1 style='text-align: center;'>Neobot</h1>")
-    chatbot = gr.Chatbot(label="Chat", elem_id="chatbox", height=450, type="messages")
+    chatbot = gr.Chatbot(height=400, label="Chat")
 
     with gr.Row():
-        txt = gr.Textbox(placeholder="Type a message or edit transcribed/file content here...", scale=5, show_label=False)
+        msg_box = gr.Textbox(
+            scale=8, 
+            placeholder="Ask something...", 
+            show_label=False, 
+            container=True
+        )
         send_btn = gr.Button("Send", scale=1)
 
     with gr.Row():
-        upload_btn = gr.File(label="📎 Upload File", file_types=[".pdf", ".docx", ".txt", ".xlsx", ".png", ".jpg", ".jpeg"])
-        audio_in = gr.Audio(label="🎙️ Upload Audio", type="filepath")
+        file_upload = gr.File(label="Upload File", file_types=[".txt", ".pdf", ".docx", ".xlsx"])
+        audio_upload = gr.Audio(source="upload", type="filepath", label="Upload Audio")
 
-    history = gr.State([])
+    state = gr.State([])
 
-    send_btn.click(respond, [txt, history], [chatbot, txt])
-    upload_btn.change(handle_file_upload, [upload_btn, txt], txt)
-    audio_in.change(handle_audio_upload, [audio_in, txt], txt)
+    send_btn.click(fn=process_input, inputs=[msg_box, state], outputs=[chatbot, state])
+    file_upload.change(fn=interface_func, inputs=[msg_box, state, file_upload, audio_upload], outputs=msg_box)
+    audio_upload.change(fn=interface_func, inputs=[msg_box, state, file_upload, audio_upload], outputs=msg_box)
 
 demo.launch()