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import os, json, re, traceback, asyncio
import gradio as gr
from typing import Generator
from datetime import datetime, date
import requests
from handlers.tool_call_handler import create_tool_call_handler
from services.mcp_client import MCPClientService
from utils.load_secrets import load_secrets
if not os.getenv("NEBIUS_API_KEY") or not os.getenv("NEBIUS_MODEL"):
load_secrets("tests/secrets/creds.py")
nebius_api_key = os.getenv("NEBIUS_API_KEY")
nebius_model = os.getenv("NEBIUS_MODEL")
from utils.logging_config import (
setup_logging,
get_logger,
start_session_logging,
get_session_logs,
)
# Initialize logging
setup_logging()
logger = get_logger(__name__)
# Global MCP client for the chat page
_mcp_client = None
_tool_assembler = None
_tool_processor = None
# Get or create event loop for MCP operations
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
class DateTimeEncoder(json.JSONEncoder):
"""Custom JSON encoder that handles datetime objects and other non-serializable types"""
def default(self, obj):
if isinstance(obj, (datetime, date)):
return obj.isoformat()
elif hasattr(obj, "__dict__"):
return str(obj)
elif hasattr(obj, "to_dict"):
return obj.to_dict()
else:
return str(obj)
def safe_json_dumps(obj, **kwargs):
"""Safely serialize objects to JSON, handling datetime and other non-serializable types"""
try:
return json.dumps(obj, cls=DateTimeEncoder, **kwargs)
except Exception as e:
logger.warning(
f"JSON serialization failed: {e}, falling back to string representation"
)
return json.dumps(
{"error": f"Serialization failed: {str(e)}", "raw_data": str(obj)[:1000]},
**kwargs,
)
def draw_chat_page(debug: bool = False):
logger.info(f"NEBIUS_MODEL: {nebius_model}")
logger.info(f"NEBIUS_API_KEY: {'Set' if nebius_api_key else 'Not Set'}")
if not nebius_model or not nebius_api_key:
logger.error(
"NEBIUS_MODEL or NEBIUS_API_KEY not found in environment variables"
)
with gr.Tab("π¬ Chat Agent Demo"):
gr.Markdown(
"""
# π¬ Chat Agent Demo
This is a chat agent demo for Yuga Planner!
Insert a task description to have the agent schedule it standalone or around your existing calendar.
If you provide a .ics file, the schedule will start from **the first occupied time slot in your calendar file**.
If you don't, the schedule will start from **next monday**.
"""
)
if not nebius_model or not nebius_api_key:
gr.Markdown(
"""
β οΈ **Chat unavailable**: NEBIUS_MODEL or NEBIUS_API_KEY environment variables are not set.
Please configure your Nebius credentials to use the chat feature.
"""
)
return
# Initialize MCP client and tool handlers as globals for this page
global _mcp_client, _tool_assembler, _tool_processor
_mcp_client = MCPClientService()
_tool_assembler, _tool_processor = create_tool_call_handler(_mcp_client)
# Create chat interface components
chatbot, msg, clear, stop, calendar_file = create_chat_interface()
# Create parameter controls
(
system_message,
max_tokens_slider,
temperature_slider,
top_p_slider,
) = create_chatbot_parameters()
# Handle message submission
submit_event = msg.submit(
user_message,
[msg, chatbot, calendar_file],
[msg, chatbot, msg, stop],
queue=False,
).then(
bot_response,
[
chatbot,
system_message,
max_tokens_slider,
temperature_slider,
top_p_slider,
],
[chatbot, msg, stop],
show_progress=True,
)
# Handle clear button
def clear_chat():
return [], gr.update(interactive=True), gr.update(visible=False)
clear.click(clear_chat, None, [chatbot, msg, stop], queue=False)
# Handle stop button
def stop_processing():
return gr.update(interactive=True), gr.update(visible=False)
stop.click(
stop_processing, None, [msg, stop], queue=False, cancels=[submit_event]
)
def create_chat_interface() -> tuple[
gr.Chatbot, gr.Textbox, gr.Button, gr.Button, gr.File
]:
"""Create and return the chat interface components"""
chatbot = gr.Chatbot(type="messages")
# Message input row with calendar upload on the right - improved layout
with gr.Row(equal_height=True):
msg = gr.Textbox(
label="Insert a task description",
placeholder="Ex.: Create a new EC2 instance on AWS",
interactive=True,
scale=5, # Takes up most of the row
container=True,
lines=1,
max_lines=3,
)
calendar_file = gr.File(
label="π
Calendar",
file_types=[".ics"],
visible=True,
scale=1, # Compact size
height=80, # Larger height to accommodate content
file_count="single",
container=True,
elem_id="calendar-upload",
)
# Control buttons row
with gr.Row():
clear = gr.Button("Clear", variant="secondary")
stop = gr.Button("Stop", variant="stop", visible=False)
return chatbot, msg, clear, stop, calendar_file
def create_chatbot_parameters() -> tuple[gr.Textbox, gr.Slider, gr.Slider, gr.Slider]:
"""Create and return the chatbot parameter controls"""
with gr.Accordion("Chatbot Parameters", open=False):
system_message = gr.Textbox(
value="You are a friendly and helpful AI assistant that specializes in task scheduling and productivity. You can help users plan and organize their work around existing calendar commitments. When users ask about scheduling tasks or mention calendar-related activities, you should use the schedule_tasks_with_calendar tool to create optimized schedules. If you see [Calendar file uploaded:] in a message, the user has provided calendar data that should be used for scheduling. Always use the scheduling tool when users mention tasks, projects, scheduling, planning, or similar requests.",
label="System message",
)
max_tokens_slider = gr.Slider(
minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"
)
temperature_slider = gr.Slider(
minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"
)
top_p_slider = gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
)
return system_message, max_tokens_slider, temperature_slider, top_p_slider
def user_message(message, history, calendar_file_obj):
# Handle calendar file upload
enhanced_message = message
# Use provided calendar file or default to empty.ics
if calendar_file_obj is not None:
# Read and encode the uploaded calendar file
try:
import base64
with open(calendar_file_obj, "rb") as f:
file_content = f.read()
encoded_content = base64.b64encode(file_content).decode("utf-8")
enhanced_message += (
f"\n\n[Calendar file uploaded: {calendar_file_obj.name}]"
)
enhanced_message += f"\n[CALENDAR_DATA:{encoded_content}]"
except Exception as e:
logger.error(f"Error reading calendar file: {e}")
enhanced_message += f"\n\n[Calendar file upload failed: {str(e)}]"
else:
# Use empty.ics as default when no calendar is provided
try:
import base64
empty_calendar_path = "tests/data/empty.ics"
with open(empty_calendar_path, "rb") as f:
file_content = f.read()
encoded_content = base64.b64encode(file_content).decode("utf-8")
enhanced_message += f"\n\n[Default empty calendar used]"
enhanced_message += f"\n[CALENDAR_DATA:{encoded_content}]"
except Exception as e:
logger.error(f"Error reading default empty calendar: {e}")
enhanced_message += f"\n\n[Default calendar load failed: {str(e)}]"
return (
"", # Clear input
history + [{"role": "user", "content": enhanced_message}],
gr.update(interactive=False), # Disable input
gr.update(visible=True), # Show stop button
)
def bot_response(history, system_message, max_tokens, temperature, top_p):
if not history:
return history, gr.update(interactive=True), gr.update(visible=False)
# Convert messages format to tuples for the respond function
history_tuples = []
for msg in history[:-1]: # All but the last message
if msg["role"] == "user":
history_tuples.append([msg["content"], ""])
elif msg["role"] == "assistant":
if history_tuples:
history_tuples[-1][1] = msg["content"]
else:
history_tuples.append(["", msg["content"]])
# Get the last user message
user_msg = history[-1]["content"]
logger.info(f"Bot response called with user message: {user_msg[:100]}...")
try:
# Get the response generator
response_gen = respond(
user_msg,
history_tuples,
system_message,
max_tokens,
temperature,
top_p,
)
# Stream responses to show progress - this is a generator function now
for response_chunk in response_gen:
updated_history = history.copy()
updated_history[-1] = {"role": "assistant", "content": response_chunk}
yield (
updated_history,
gr.update(), # Keep input disabled during processing
gr.update(), # Keep stop button visible
)
# Final yield to re-enable input and hide stop button
final_history = history.copy()
final_history[-1] = {"role": "assistant", "content": response_chunk}
yield (
final_history,
gr.update(interactive=True), # Re-enable input
gr.update(visible=False), # Hide stop button
)
except Exception as e:
logger.error(f"Error in bot_response: {e}")
import traceback
logger.error(f"Full traceback: {traceback.format_exc()}")
error_history = history.copy()
error_history[-1] = {"role": "assistant", "content": f"Error: {str(e)}"}
yield (
error_history,
gr.update(interactive=True), # Re-enable input on error
gr.update(visible=False), # Hide stop button on error
)
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
) -> Generator[str, None, None]:
try:
# Start capturing logs for this session
start_session_logging()
# Reset tool assembler for new conversation
_tool_assembler.reset()
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
# Check if this looks like a scheduling request
scheduling_keywords = [
"schedule",
"task",
"calendar",
"plan",
"organize",
"meeting",
"appointment",
"project",
"deadline",
"create",
"setup",
"implement",
"develop",
]
is_scheduling_request = any(
keyword in message.lower() for keyword in scheduling_keywords
)
logger.info(f"Message: {message}")
logger.info(f"Is scheduling request: {is_scheduling_request}")
# Prepare payload for Nebius API
payload = {
"model": nebius_model,
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"stream": True,
}
# Add tools if this might be a scheduling request
if is_scheduling_request:
logger.info("Adding tools to payload")
payload["tools"] = _mcp_client.tools
payload["tool_choice"] = "auto"
logger.debug(f"Tools payload: {_mcp_client.tools}")
else:
logger.info("No scheduling detected, not adding tools")
headers = {
"Authorization": f"Bearer {nebius_api_key}",
"Content-Type": "application/json",
}
logger.info(
f"Sending request to Nebius API with tools: {is_scheduling_request}"
)
logger.debug(f"Full payload: {json.dumps(payload, indent=2)}")
response = requests.post(
"https://api.studio.nebius.ai/v1/chat/completions",
headers=headers,
json=payload,
stream=True,
)
if response.status_code != 200:
logger.error(f"API error: {response.status_code} - {response.text}")
yield f"Error: API returned {response.status_code}: {response.text}"
return
response_text = ""
# Initial yield to show streaming is working
if is_scheduling_request:
yield "π€ **Processing your scheduling request...**"
for line in response.iter_lines():
if line:
line = line.decode("utf-8")
if line.startswith("data: "):
data = line[6:] # Remove 'data: ' prefix
if data.strip() == "[DONE]":
break
try:
chunk = json.loads(data)
logger.debug(f"Received chunk: {chunk}")
if "choices" in chunk and len(chunk["choices"]) > 0:
delta = chunk["choices"][0].get("delta", {})
content = delta.get("content", "")
if content:
response_text += content
# For scheduling requests, include essential logs inline
if is_scheduling_request:
session_logs = get_session_logs()
if session_logs:
# Show only new logs since last yield
latest_logs = (
session_logs[-3:]
if len(session_logs) > 3
else session_logs
)
logs_text = "\n".join(
f" {log}" for log in latest_logs
)
yield response_text + f"\n\n{logs_text}"
else:
yield response_text
else:
yield response_text
# Process tool calls using our new handler
_tool_assembler.process_delta(delta)
except json.JSONDecodeError as e:
logger.error(f"JSON decode error: {e} for line: {line}")
continue
# Get completed tool calls and process them
completed_tool_calls = _tool_assembler.get_completed_tool_calls()
# Log debug info
debug_info = _tool_assembler.debug_info()
logger.info(f"Tool call assembly completed: {debug_info}")
if completed_tool_calls:
logger.info(f"Processing {len(completed_tool_calls)} completed tool calls")
yield response_text + "\n\nπ§ **Processing scheduling request...**"
# Process tool calls using our new processor
tool_response = _tool_processor.process_tool_calls(
completed_tool_calls, message
)
response_text += tool_response
yield response_text
else:
logger.info("No completed tool calls found")
if is_scheduling_request:
logger.warning(
"Scheduling request detected but no completed tool calls"
)
# Log detailed debug info for troubleshooting
logger.error(f"Tool assembly debug info: {debug_info}")
yield response_text + "\n\nβ οΈ **Scheduling request detected but tool not triggered or incomplete. Let me try calling the scheduler directly...**"
# Directly call the scheduling tool as fallback
try:
# Extract task description from message
task_description = message
calendar_content = "" # Always start with empty calendar
# Extract calendar data if available
calendar_match = re.search(r"\[CALENDAR_DATA:([^\]]+)\]", message)
if calendar_match:
calendar_content = calendar_match.group(1)
logger.info("Calendar data found and extracted")
else:
# If no calendar data found, proceed with empty calendar
logger.info(
"No calendar data found, proceeding with empty calendar - tool will still be called"
)
# Show essential task processing logs inline
session_logs = get_session_logs()
processing_status = ""
if session_logs:
latest_logs = (
session_logs[-2:] if len(session_logs) > 2 else session_logs
)
processing_status = "\n" + "\n".join(
f" {log}" for log in latest_logs
)
yield response_text + f"\n\nπ§ **Direct scheduling call for: {task_description}**\nβ³ *Processing...*{processing_status}"
logger.info("About to call MCP scheduling tool directly")
# Add timeout to prevent hanging
def call_with_timeout():
try:
return loop.run_until_complete(
asyncio.wait_for(
_mcp_client.call_scheduling_tool(
task_description, calendar_content
),
timeout=60.0, # 60 second timeout
)
)
except asyncio.TimeoutError:
return {
"error": "Timeout after 60 seconds",
"status": "timeout",
}
# Show progress during processing with essential logs
session_logs = get_session_logs()
analysis_status = ""
if session_logs:
latest_logs = (
session_logs[-3:] if len(session_logs) > 3 else session_logs
)
analysis_status = "\n" + "\n".join(
f" {log}" for log in latest_logs
)
yield response_text + f"\n\nπ§ **Direct scheduling call for: {task_description}**\nβ³ *Analyzing calendar and generating tasks...*{analysis_status}"
try:
result = call_with_timeout()
except Exception as timeout_err:
logger.error(
f"MCP scheduling tool timed out or failed: {timeout_err}"
)
tool_response = f"\n\nβ° **Scheduling timed out** - The request took longer than expected. Please try with a simpler task description."
response_text += tool_response
logger.info("Added timeout message to response")
yield response_text
else:
# Show progress for result processing
yield response_text + f"\n\nπ§ **Direct scheduling call for: {task_description}**\nβ³ *Processing results...*"
logger.info(
f"MCP tool completed with status: {result.get('status', 'unknown')}"
)
logger.info(f"MCP result type: {type(result)}")
logger.info(
f"MCP result keys: {list(result.keys()) if isinstance(result, dict) else 'Not a dict'}"
)
# Debug the result structure
if isinstance(result, dict):
logger.info(f"Result status: {result.get('status')}")
logger.info(f"Result has schedule: {'schedule' in result}")
logger.info(
f"Result has calendar_entries: {'calendar_entries' in result}"
)
if "schedule" in result:
logger.info(
f"Schedule length: {len(result.get('schedule', []))}"
)
if "calendar_entries" in result:
logger.info(
f"Calendar entries length: {len(result.get('calendar_entries', []))}"
)
# Check multiple possible success conditions
is_success = False
success_msg = ""
if result.get("status") == "success":
is_success = True
success_msg = "Status is 'success'"
elif isinstance(result, dict) and "schedule" in result:
is_success = True
success_msg = "Result contains schedule data"
elif isinstance(result, dict) and len(result) > 0:
is_success = True
success_msg = "Result contains data"
logger.info(f"Success check: {is_success} ({success_msg})")
if is_success:
logger.info(
"SUCCESS CONDITION MET - Processing successful result"
)
schedule = result.get("schedule", [])
calendar_entries = result.get("calendar_entries", [])
# Sort the schedule by start time
schedule = sorted(schedule, key=lambda x: x.get("Start"))
# Format the schedule as a table
if schedule:
# Create table header
table_md = "\n\n## π
**Generated Schedule**\n\n"
table_md += "| Start Time | End Time | Task | Project | Employee | Duration | Skill | Status |\n"
table_md += "|------------|----------|------|---------|----------|----------|-------|--------|\n"
# Add table rows
for item in schedule:
# Use the correct field names from schedule_to_dataframe
start_time = item.get(
"Start", item.get("start_time", "N/A")
)
end_time = item.get(
"End", item.get("end_time", "N/A")
)
task_name = item.get(
"Task",
item.get(
"task_name", item.get("description", "N/A")
),
)
project = item.get(
"Project", item.get("project", "N/A")
)
employee = item.get(
"Employee", item.get("employee", "N/A")
)
duration = item.get(
"Duration (hours)", item.get("duration", "N/A")
)
skill = item.get(
"Required Skill", item.get("skill", "N/A")
)
# Status indicators based on flags
status_flags = []
if item.get("Pinned", False):
status_flags.append("π Pinned")
if item.get("Unavailable", False):
status_flags.append("β οΈ Unavailable")
if item.get("Undesired", False):
status_flags.append("π Undesired")
if item.get("Desired", False):
status_flags.append("β
Desired")
status = (
" ".join(status_flags)
if status_flags
else "βͺ Normal"
)
# Format dates/times if they are datetime strings
if isinstance(start_time, str) and "T" in str(
start_time
):
try:
from datetime import datetime
dt = datetime.fromisoformat(
str(start_time).replace("Z", "+00:00")
)
start_time = dt.strftime("%m/%d %H:%M")
except:
pass
if isinstance(end_time, str) and "T" in str(
end_time
):
try:
from datetime import datetime
dt = datetime.fromisoformat(
str(end_time).replace("Z", "+00:00")
)
end_time = dt.strftime("%m/%d %H:%M")
except:
pass
# Truncate long task names for table display
if len(str(task_name)) > 35:
task_name = str(task_name)[:32] + "..."
# Format duration
if isinstance(duration, (int, float)):
duration = f"{duration}h"
table_md += f"| {start_time} | {end_time} | {task_name} | {project} | {employee} | {duration} | {skill} | {status} |\n"
table_md += f"\n**Summary:**\n"
table_md += f"- π **Total Items:** {len(schedule)}\n"
table_md += f"- π
**Calendar Events:** {len(calendar_entries)}\n"
table_md += f"- β
**Status:** Successfully scheduled around existing commitments\n"
# Count different types of tasks
pinned_count = sum(
1 for item in schedule if item.get("Pinned", False)
)
project_tasks = sum(
1
for item in schedule
if item.get("Project") == "PROJECT"
)
existing_events = sum(
1
for item in schedule
if item.get("Project") == "EXISTING"
)
table_md += f"- π **Pinned Events:** {pinned_count}\n"
table_md += f"- π **New Tasks:** {project_tasks}\n"
table_md += (
f"- π
**Existing Events:** {existing_events}\n"
)
# Add JSON data section for debugging
table_md += f"\n\n<details>\n<summary>π **Raw JSON Data** (click to expand)</summary>\n\n"
table_md += "```json\n"
table_md += safe_json_dumps(result)
table_md += "\n```\n</details>\n"
tool_response = table_md
else:
tool_response = f"""
π
**Schedule Generated Successfully!**
**Task:** {task_description}
**Calendar Events Processed:** {len(calendar_entries)}
**Total Scheduled Items:** {len(schedule)}
β οΈ **No schedule items to display** - This may indicate the task was completed or no scheduling was needed.
**Raw Result:**
```json
{safe_json_dumps(result, indent=2)[:1000]}
```
"""
response_text += tool_response
logger.info("Added success message with table to response")
yield response_text
else:
logger.warning(f"SUCCESS CONDITION NOT MET")
error_msg = result.get(
"error",
f"Unknown error - result: {safe_json_dumps(result)[:200]}",
)
tool_response = f"\n\nβ **Scheduling Error:** {error_msg}"
response_text += tool_response
logger.info("Added error message to response")
yield response_text
except Exception as e:
logger.error(f"Direct scheduling call failed: {e}")
logger.error(f"Full traceback: {traceback.format_exc()}")
tool_response = f"\n\nβ **Scheduling failed:** {str(e)}"
response_text += tool_response
logger.info("Added exception message to response")
yield response_text
# Always yield final response
logger.info(f"Final yield: response length {len(response_text)}")
yield response_text
except Exception as e:
logger.error(f"Error in chat response: {e}")
logger.error(f"Full traceback: {traceback.format_exc()}")
yield f"Error: {str(e)}"
|