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import gradio as gr
import pandas as pd
from database import Database
from voice_handler import VoiceHandler
from gemini_processor import GeminiProcessor
from memory_handler import MemoryHandler
from gtts import gTTS
import io
import os
from dotenv import load_dotenv
load_dotenv()
# Initialize components
db = Database()
voice_handler = VoiceHandler()
gemini_processor = GeminiProcessor()
memory_handler = MemoryHandler()
def validate_request(project_number, project_name, amount, reason):
if not project_number or not project_name or not amount or not reason:
missing_fields = []
if not project_number: missing_fields.append("project number")
if not project_name: missing_fields.append("project name")
if not amount: missing_fields.append("amount")
if not reason: missing_fields.append("reason")
return False, f"Please provide: {', '.join(missing_fields)}"
return True, ""
def process_text_input(text, language):
if not text:
return "Please enter some text first.", None, None, None, None
context = memory_handler.get_context()
details = gemini_processor.extract_request_details(text, context)
if not details:
return "Could not extract request details. Please try again.", None, None, None, None
memory_handler.add_interaction(text, details)
# Get any previously captured information
partial_info = memory_handler.get_partial_info()
return (
f"Text processed! {memory_handler.get_prompt_for_missing_info()}",
partial_info.get('project_number', ''),
partial_info.get('project_name', ''),
partial_info.get('amount', 0),
partial_info.get('reason', '')
)
def process_voice_input(audio_path, language):
if not audio_path:
return "No audio detected.", None, None, None, None
voice_text = voice_handler.process_audio_file(audio_path, language)
if voice_text.startswith("Error:"):
return voice_text, None, None, None, None
context = memory_handler.get_context()
details = gemini_processor.extract_request_details(voice_text, context)
if not details:
return "Could not extract request details. Please try again.", None, None, None, None
memory_handler.add_interaction(voice_text, details)
# Get any previously captured information
partial_info = memory_handler.get_partial_info()
return (
f"Voice processed! You said: {voice_text}\n\n{memory_handler.get_prompt_for_missing_info()}",
partial_info.get('project_number', ''),
partial_info.get('project_name', ''),
partial_info.get('amount', 0),
partial_info.get('reason', '')
)
def submit_request(project_number, project_name, amount, reason):
is_valid, message = validate_request(project_number, project_name, amount, reason)
if not is_valid:
return message, None
try:
db.add_request(project_number, project_name, float(amount), reason)
memory_handler.clear_memory()
return "Request successfully added!", get_requests_df()
except Exception as e:
return f"Error saving request: {str(e)}", None
def get_requests_df():
try:
requests = db.get_all_requests()
if requests:
df = pd.DataFrame(requests)
columns = ['timestamp', 'project_number', 'project_name', 'amount', 'reason']
df = df[columns]
# Convert DataFrame to list of lists format required by Gradio
headers = df.columns.tolist()
data = df.values.tolist()
return {"headers": headers, "data": data}
return {"headers": ['timestamp', 'project_number', 'project_name', 'amount', 'reason'], "data": []}
except Exception as e:
print(f"Error getting requests: {str(e)}")
return {"headers": ['timestamp', 'project_number', 'project_name', 'amount', 'reason'], "data": []}
def create_ui():
with gr.Blocks(title="AI Agent Money Request System") as app:
gr.Markdown("# AI Agent Money Request System")
with gr.Tab("Input"):
language = gr.Dropdown(
choices=["English", "Arabic", "Mixed (Arabic/English)"],
value="English",
label="Select Language"
)
with gr.Tab("Voice Input"):
audio_input = gr.Audio(
label="Voice Input",
type="filepath",
sources=["microphone"]
)
voice_process_btn = gr.Button("Process Voice")
with gr.Tab("Text Input"):
text_input = gr.Textbox(
lines=3,
placeholder="Enter your request here...",
label="Text Input"
)
text_process_btn = gr.Button("Process Text")
process_output = gr.Textbox(label="Processing Result")
with gr.Group():
project_number = gr.Textbox(label="Project Number")
project_name = gr.Textbox(label="Project Name")
amount = gr.Number(label="Amount (in riyals)")
reason = gr.Textbox(label="Reason for Request")
submit_btn = gr.Button("Submit Request")
result_text = gr.Textbox(label="Submission Result")
with gr.Tab("Existing Requests"):
requests_table = gr.DataFrame(
headers=["Timestamp", "Project Number", "Project Name", "Amount", "Reason"],
label="Existing Requests"
)
refresh_btn = gr.Button("Refresh")
# Event handlers
text_process_btn.click(
process_text_input,
inputs=[text_input, language],
outputs=[process_output, project_number, project_name, amount, reason]
)
voice_process_btn.click(
process_voice_input,
inputs=[audio_input, language],
outputs=[process_output, project_number, project_name, amount, reason]
)
submit_btn.click(
submit_request,
inputs=[project_number, project_name, amount, reason],
outputs=[result_text, requests_table]
)
refresh_btn.click(
lambda: get_requests_df(),
outputs=[requests_table]
)
# Initialize requests table
requests_table.value = get_requests_df()
return app
if __name__ == "__main__":
app = create_ui()
app.launch() |