SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning

What if LLM and Agent lost track of information? Reverting back as a transaction!

--- SagaLLM Authors

⬇️ Github 📃 Paper 🌐 Project Page

This repository extends based on the REALM-Bench (a general mutli-agent framework for of real-world use cases of Multi Agentic Design, Orchestration, and Planning in Real-World Scenerios). The SagaLLM provides a comprehensive middleware for agent application layer and multi-agent databases.

It supports Application Layer for:
- Planning and Scheduling: 1) Sequential planning, 2) Reactive planning, 3) Complex planning, 4) Others
- Tool Use: 1) WriteToFile, 2) GoogleSearchAPI, 3) Other API (e.g. Financial), 4) Others
- Reflection
- Memory
- Reasoning
- Forecasting
- Math Induction, Calculation
- Multi-Agent Collaboration: worflow generation
It supports Multi-Agent Database Frameworks across 7 different agent ecosystems:
- AutoGen
- CrewAI
- Swarm
- LangGraph

Key Functions of `Saga` libraries

1. Context Management Framework
1. Validation Framework
1. Transaction Framework
1. Extension of multi-agent frameworks,
1. Built for application layers.

Function	Description	Function Name	Input
Transaction Manager	Defines context, agents, and dependencies.	`transaction_manager(self, agents, dependencies, context)`	List of agents, dependencies, and context.
Saga Coordinator	Executes agents with optional rollback support.	`saga_coordinator(self, with_rollback, agents)`	`with_rollback` (boolean flag), agent list.
Intra-Agent Details	Prints each agent’s execution details.	`intra_agent(self, agents)`	Agent list.
Inter-Agent Dependencies	Displays inter-agent dependencies.	`inter_agent(self, dependency_graph)`	Agent dependency graph.
Select Context	Allows user to query execution context of a node.	`select_context(self, node_name)`	User-input node name.
Restore Context	Rolls back execution of a specified agent.	`restore_context(self, agent_name)`	User-input agent to rollback.

🔹 Key Features of Using `SagaCoordinator` Instead of Previous `Crew`

Feature	Crew	SagaCoordinator
Task Execution	Runs agents in topological order	Runs agents sequentially with rollback
Error Handling	No built-in error handling	Rolls back on failure
Transaction Safety	No rollback mechanism	Full rollback support
Use Case	Dependency management	Resilient transaction flow

🚀 How To Run

1️⃣ Setup Environment

Follow these steps to get started:

Create a virtual environment
```
python3 -m venv venv
```
making sure your program using python==3.10+ for your venv on your editor.
Activate the virtual environment
- macOS/Linux:
```
source venv/bin/activate
```
- Windows:
```
venv\Scripts\activate
```
Install dependencies
```
pip install -r requirements.txt
```
Set up OpenAI API credentials
- Create a .env file in the root directory
- Add your OpenAI API key:
```
OPENAI_API_KEY="sk-proj-..."
```

2️⃣ Running Multi-Agent Frameworks

(Optional) You can execute agents using one of the frameworks:

Run an agent framework

python agent_frameworks/openai_swarm_agent.py

Using AutoGen
- Ensure Docker is installed (Get Docker)
- Start Docker before running AutoGen-based agents

3️⃣ Import Saga Library

You can execute transaction using saga:

cd applications
python3 multiagent-p5.py
python3 multiagent-p6.py
python3 multiagent-p8.py
python3 multiagent-p9.py

and edit the "multiagent-p5.py" following the below coding format.

Example 1: Wedding Logsitics Planning

input for example 1:

import sys
import os


# Get the project root by going up one level from 'applications'
project_root = os.path.abspath(os.path.join(os.getcwd(), '..'))
print(f"📂 Project Root: {project_root}")

# Append 'src' directory to sys.path
src_path = os.path.join(project_root, 'src')
sys.path.append(src_path)

# Print sys.path to verify
print("🔍 Updated sys.path:")
for path in sys.path:
    print(path)

# Try importing Saga again
try:
    from multi_agent.saga import Saga
    from multi_agent.agent import Agent
    print("✅ Saga imported successfully!")
    print("✅ Agent imported successfully!")
except ModuleNotFoundError as e:
    print("❌ Import failed:", e)



# Initialize Saga
saga = Saga()

LT_Agent = Agent(
    name="Locations and Time Setup Agent",
    backstory="You define locations, travel times, and guest arrival schedules.",
    task_description="Set up locations, travel times, and ensure accurate scheduling of arrivals.",
    task_expected_output="Structured location data and expected arrival times. Fourlocations:𝑉 ={𝐵,𝐺,𝑇,𝑊},where𝐵isBostonAir- port, 𝐺 is Gift shop, 𝑇 is Tailor shop, and 𝑊 is Wedding venue. 𝐵-𝐺 : 45, 𝐵-𝑇 : 30, 𝐵-𝑊 : 40, 𝐺-𝑇 : 20, 𝐺-𝑊 : 25, 𝑇-𝑊 : 15. - Alex:At𝐵at11:00AMfromChicago(needaride) - Jamie:At𝐵at12:30PMfromAtlanta(needaride) - Pat: At 𝑊 at 12:00 PM driving from NYC (has 5-seater car)"
)

# ---- Task Setup Agent ---- #
TS_Agent = Agent(
    name="Task Setup Agent",
    backstory="You manage the scheduling of required wedding tasks.",
    task_description="Schedule gift collection after 12:00 PM, clothes pickup before 2:00 PM, and ensure photo session at 3:00 PM.",
    task_expected_output="Optimized task schedule aligned with constraints."
)

# ---- Resource Management Agent ---- #
RM_Agent = Agent(
    name="Resource Management Agent",
    backstory="You allocate available transport resources efficiently.",
    task_description="Coordinate 5 vehicle usage and Local friend Chris(5-seater)available, for guest transportation and task fulfillment."
8000
,
    task_expected_output="Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar(5-seater)withPat,availableafterheisBoston - LocalfriendChris(5-seater)availableafter1:30PMat𝑊"
)

# ---- Constraint Validation Agent ---- #
CV_Agent = Agent(
    name="Constraint Validation Agent",
    backstory="You verify all scheduling constraints to ensure smooth execution.",
    task_description="Ensure all tasks are completed within operating hours and vehicle constraints are met.",
    task_expected_output="Validated schedule with no conflicts. All tasks must complete before 3:00 PM photo time - Gift store opens at 12:00 PM - Tailor closes at 2:00 PM - Two cars must accommodate all transport needs"
)

# ---- Supervisor Agent ---- #
WEO_Agent = Agent(
    name="Wedding Event Oversight Agent",
    backstory="You oversee the entire wedding logistics to ensure a smooth execution of tasks.",
    task_description="Monitor and ensure all tasks are completed on time, resolving any logistical issues.",
    task_expected_output="Give a wedding scheduling plan for people, task and time."
)



# Register Agents in Saga
saga.transaction_manager([LT_Agent, TS_Agent, RM_Agent, CV_Agent, WEO_Agent])

# Execute with rollback enabled
saga.saga_coordinator(with_rollback=True)

# Print intra-agent details
saga.intra_agent()

# Print inter-agent dependencies
saga.inter_agent()

# Select context for an agent
saga.select_context("Resource Management Agent")

# Restore an agent’s execution
saga.restore_context("Resource Management Agent")

Output for Example 1:

📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ Utils imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ utils.logging imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ tool_agent.tool imported successfully!
✅ utils.completions imported successfully!
✅ utils.extraction imported successfully!
✅ multi_agent.crew imported successfully!
✅ planning_agent.react_agent imported successfully!
✅ tool_agent.tool imported successfully!
✅ Saga imported successfully!
✅ Agent imported successfully!

==================================================
🛠 Transaction Manager: Agents and dependencies initialized.
==================================================


==================================================
🚀 Running Agent: Locations and Time Setup Agent
==================================================

✅ Locations and Time Setup Agent completed successfully.

==================================================
🚀 Running Agent: Task Setup Agent
==================================================

✅ Task Setup Agent completed successfully.

==================================================
🚀 Running Agent: Resource Management Agent
==================================================

✅ Resource Management Agent completed successfully.

==================================================
🚀 Running Agent: Constraint Validation Agent
==================================================

✅ Constraint Validation Agent completed successfully.

==================================================
🚀 Running Agent: Wedding Event Oversight Agent
==================================================

✅ Wedding Event Oversight Agent completed successfully.

📌 **Intra-Agent Execution Details**
🔹 Locations and Time Setup Agent: <locations>
  <location id="B" name="Boston Airport"/>
  <location id="G" name="Gift shop"/>
  <location id="T" name="Tailor shop"/>
  <location id="W" name="Wedding venue"/>
</locations>

<travel_times>
  <from to="G" time="45">B</from>
  <from to="T" time="30">B</from>
  <from to="W" time="40">B</from>
  <from to="T" time="20">G</from>
  <from to="W" time="25">G</from>
  <from to="W" time="15">T</from>
</travel_times>

<guest_arrivals>
  <guest name="Alex" location="B" time="11:00 AM" from="Chicago" needs_ride="yes"/>
  <guest name="Jamie" location="B" time="12:30 PM" from="Atlanta" needs_ride="yes"/>
  <guest name="Pat" location="W" time="12:00 PM" from="NYC" has_car="5-seater"/>
</guest_arrivals>
🔹 Task Setup Agent: To create an optimized task schedule aligned with the given constraints, the tasks should be arranged as follows:

1. **Clothes Pickup**: Schedule this task before 2:00 PM. It's important to complete this task early to ensure there is enough time for any unforeseen delays and to have the clothes ready for the photo session.

2. **Gift Collection**: Schedule this task after 12:00 PM. This allows flexibility to complete it after the clothes pickup and before the photo session, ensuring all tasks are completed efficiently.

3. **Photo Session**: Schedule this task at 3:00 PM as specified. This is a fixed time and should be adhered to precisely.

**Optimized Task Schedule:**

- 11:00 AM - 1:30 PM: Clothes Pickup
- 1:30 PM - 2:30 PM: Gift Collection
- 3:00 PM: Photo Session

This schedule ensures all tasks are completed within their respective time constraints and allows for a smooth flow of activities leading up to the photo session.
🔹 Resource Management Agent: Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar (5-seater) with Pat, available after he is Boston - Local friend Chris (5-seater) available after 1:30 PM at 𝑊
🔹 Constraint Validation Agent: To ensure that all tasks are completed within the specified operating hours and vehicle constraints, we need to create a schedule that adheres to the following conditions:

1. **Operating Hours:**
   - All tasks must be completed before 3:00 PM.
   - The gift store opens at 12:00 PM.
   - The tailor closes at 2:00 PM.

2. **Vehicle Constraints:**
   - Two cars are available to accommodate all transport needs.

**Validated Schedule:**

- **Task 1: Visit Tailor**
  - **Start Time:** 10:00 AM
  - **End Time:** 11:00 AM
  - **Notes:** Ensure this task is completed before the tailor closes at 2:00 PM.

- **Task 2: Visit Gift Store**
  - **Start Time:** 12:00 PM
  - **End Time:** 1:00 PM
  - **Notes:** This task must start no earlier than 12:00 PM when the gift store opens.

- **Task 3: Photo Session**
  - **Start Time:** 1:30 PM
  - **End Time:** 2:30 PM
  - **Notes:** Ensure this task is completed before 3:00 PM.

**Vehicle Allocation:**

- **Car 1:**
  - Transport for Task 1 (Visit Tailor) and Task 3 (Photo Session).

- **Car 2:**
  - Transport for Task 2 (Visit Gift Store).

This schedule ensures that all tasks are completed within the operating hours, and the two cars are used efficiently to accommodate all transport needs without any conflicts.
🔹 Wedding Event Oversight Agent: To ensure a smooth execution of the wedding logistics, here's a detailed wedding scheduling plan that outlines the tasks, responsible people, and timing:

**Wedding Day Schedule:**

**Morning Preparations:**

- **6:00 AM - 7:00 AM: Hair and Makeup for Bride and Bridesmaids**
  - **Responsible:** Hair and Makeup Artists
  - **Location:** Bridal Suite

- **7:00 AM - 8:00 AM: Groom and Groomsmen Getting Ready**
  - **Responsible:** Groom and Groomsmen
  - **Location:** Groom's Suite

- **8:00 AM - 9:00 AM: Final Touches and Photos**
  - **Responsible:** Photographer
  - **Location:** Various locations around the venue

**Ceremony:**

- **10:00 AM - 10:30 AM: Guest Arrival and Seating**
  - **Responsible:** Ushers
  - **Location:** Ceremony Venue

- **10:30 AM - 11:00 AM: Wedding Ceremony**
  - **Responsible:** Officiant
  - **Location:** Ceremony Venue

**Post-Ceremony:**

- **11:00 AM - 11:30 AM: Family and Group Photos**
  - **Responsible:** Photographer
  - **Location:** Ceremony Venue

- **11:30 AM - 12:00 PM: Cocktail Hour**
  - **Responsible:** Catering Staff
  - **Location:** Reception Area

**Reception:**

- **12:00 PM - 12:30 PM: Guests Seated for Reception**
  - **Responsible:** Ushers
  - **Location:** Reception Hall

- **12:30 PM - 1:00 PM: Wedding Party Entrance and First Dance**
  - **Responsible:** DJ/Band
  - **Location:** Reception Hall

- **1:00 PM - 2:00 PM: Lunch/Dinner Service**
  - **Responsible:** Catering Staff
  - **Location:** Reception Hall

- **2:00 PM - 2:30 PM: Speeches and Toasts**
  - **Responsible:** Best Man, Maid of Honor, Parents
  - **Location:** Reception Hall

- **2:30 PM - 3:00 PM: Cake Cutting Ceremony**
  - **Responsible:** Bride and Groom
  - **Location:** Reception Hall

- **3:00 PM - 4:00 PM: Dancing and Entertainment**
  - **Responsible:** DJ/Band
  - **Location:** Reception Hall

**Evening:**

- **4:00 PM - 5:00 PM: Bouquet and Garter Toss**
  - **Responsible:** Bride and Groom
  - **Location:** Reception Hall

- **5:00 PM - 6:00 PM: Farewell and Guest Departure**
  - **Responsible:** Wedding Planner
  - **Location:** Venue Exit

**Post-Wedding:**

- **6:00 PM - 7:00 PM: Clean-Up and Vendor Pack-Up**
  - **Responsible:** Venue Staff and Vendors
  - **Location:** Entire Venue

This schedule ensures that all tasks are assigned to the appropriate people and are completed on time, allowing for a seamless and enjoyable wedding day.

🔗 **Inter-Agent Dependencies**
🔸 Locations and Time Setup Agent depends on: None
🔸 Task Setup Agent depends on: None
🔸 Resource Management Agent depends on: None
🔸 Constraint Validation Agent depends on: None
🔸 Wedding Event Oversight Agent depends on: None

🎯 **Context for Resource Management Agent:**
Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar (5-seater) with Pat, available after he is Boston - Local friend Chris (5-seater) available after 1:30 PM at 𝑊
🔄 Rolling back Resource Management Agent's operation...
🔄 Resource Management Agent rolled back successfully.

Example 2: Thanksgiving Dinner Planning

input for example 2:

import sys
import os


# Get the project root by going up one level from 'applications'
project_root = os.path.abspath(os.path.join(os.getcwd(), '..'))
print(f"📂 Project Root: {project_root}")

# Append 'src' directory to sys.path
src_path = os.path.join(project_root, 'src')
sys.path.append(src_path)

# Print sys.path to verify
print("🔍 Updated sys.path:")
for path in sys.path:
    print(path)

# Try importing Saga again
try:
    from multi_agent.saga import Saga
    from multi_agent.agent import Agent
    print("✅ Saga imported successfully!")
    print("✅ Agent imported successfully!")
except ModuleNotFoundError as e:
    print("❌ Import failed:", e)



# Initialize Saga
saga = Saga()

# ---- Member & Time Setup Agent ---- #
MT_Agent = Agent(
    name="Member & Time Setup Agent",
    backstory="You track family members' arrivals and ensure accurate scheduling.",
    task_description="Set up arrival times, locations, and travel durations for all family members.",
    task_expected_output="Structured schedule ensuring all members arrive on time for dinner. - Sarah(Mom):Host,athome, - James(Dad):LandsatBOS1:00PMfromSF, - Emily(Sister):LandsatBOS2:30PMfromChicago - Michael(Brother):Driving,arrives3:00PMfromNY - Grandma:NeedspickupfromsuburbanBoston"
)

# ---- Requirement Setup Agent ---- #
RS_Agent = Agent(
    name="Requirement Setup Agent",
    backstory="You manage cooking schedules and key logistical needs.",
    task_description="Schedule turkey and side dish preparation while ensuring someone stays home for supervision.",
    task_expected_output="Optimized cooking schedule aligning with dinner timing. cooking requirements:  -Turkey:4hourscookingtime, - Sidedishes:2hourspreparation, - Someonemuststayhomeduringcooking, "
)

# ---- Constraint Validation Agent ---- #
CV_Agent = Agent(
    name="Constraint Validation Agent",
    backstory="You verify all scheduling constraints and ensure compliance.",
    task_description="Validate that all pickups, cooking timelines, and supervision requirements are met.",
    task_expected_output="A conflict-free schedule ensuring all tasks are completed efficiently. - Jamesmustrentcarafterlanding, - Emilyrequiresairportpickup ,- Traveltimes: – HometoBOSAirport:60min – BOSAirporttoGrandma’s:60min – HometoGrandma’s:30min"
)

# ---- Supervisor Agent ---- #
SA_Agent = Agent(
    name="Supervisor Agent",
    backstory="You oversee all logistical elements and generate the final dinner preparation report.",
    task_description="Monitor and report on key tasks, including cooking start time, Emily's pickup, and Grandma's pickup.",
    task_expected_output="Comprehensive report detailing dinner preparation logistics and arrivals. key requirement: - Allfamilymembersathomefor6:00PMdinner - Turkeyandsidesreadybydinnertime - Allpickupscompletedwithavailabledrivers - Cookingsupervisionmaintained"
)

# Register Agents in Saga
saga.transaction_manager([MT_Agent, RS_Agent, CV_Agent, SA_Agent])

# Execute with rollback enabled
saga.saga_coordinator(with_rollback=True)

# Print intra-agent details
saga.intra_agent()

# Print inter-agent dependencies
saga.inter_agent()

# Select context for an agent
saga.select_context("Member & Time Setup Agent")

# Restore an agent’s execution
saga.restore_context("Member & Time Setup Agent")

output for example 2:

📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ Utils imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ utils.logging imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
/Users/glin/Documents/GitHub/SagaLLM/src
✅ tool_agent.tool imported successfully!
✅ utils.completions imported successfully!
✅ utils.extraction imported successfully!
✅ multi_agent.crew imported successfully!
✅ planning_agent.react_agent imported successfully!
✅ tool_agent.tool imported successfully!
✅ Saga imported successfully!
✅ Agent imported successfully!

==================================================
🛠 Transaction Manager: Agents and dependencies initialized.
==================================================


==================================================
🚀 Running Agent: Member & Time Setup Agent
==================================================

✅ Member & Time Setup Agent completed successfully.

==================================================
🚀 Running Agent: Requirement Setup Agent
==================================================

✅ Requirement Setup Agent completed successfully.

==================================================
🚀 Running Agent: Constraint Validation Agent
==================================================

✅ Constraint Validation Agent completed successfully.

==================================================
🚀 Running Agent: Supervisor Agent
==================================================

✅ Supervisor Agent completed successfully.

📌 **Intra-Agent Execution Details**
🔹 Member & Time Setup Agent: Structured schedule ensuring all members arrive on time for dinner.

- Sarah(Mom): Host, at home
- James(Dad): Lands at BOS 1:00 PM from SF
- Emily(Sister): Lands at BOS 2:30 PM from Chicago
- Michael(Brother): Driving, arrives 3:00 PM from NY
- Grandma: Needs pickup from suburban Boston
🔹 Requirement Setup Agent: To create an optimized cooking schedule that aligns with dinner timing while ensuring someone stays home for supervision, let's assume dinner is planned for 6:00 PM. Here's a suggested schedule:

1. **Turkey Preparation and Cooking:**
   - **Start Time:** 12:00 PM
   - **End Time:** 4:00 PM
   - **Details:** The turkey requires 4 hours of cooking time. Begin preparation and cooking at noon to ensure it's ready by 4:00 PM.

2. **Side Dishes Preparation:**
   - **Start Time:** 4:00 PM
   - **End Time:** 6:00 PM
   - **Details:** The side dishes require 2 hours of preparation. Start immediately after the turkey is done to have everything ready by dinner time.

3. **Home Supervision:**
   - **Requirement:** Ensure someone is home from 12:00 PM to 6:00 PM to oversee the cooking process.

This schedule ensures that both the turkey and side dishes are freshly prepared and ready by dinner time, while also maintaining supervision throughout the cooking process.
🔹 Constraint Validation Agent: To create a conflict-free schedule that ensures all tasks are completed efficiently, we need to consider the travel times and requirements provided:

1. **James must rent a car after landing.**
2. **Emily requires airport pickup.**
3. **Travel times:**
   - Home to BOS Airport: 60 min
   - BOS Airport to Grandma’s: 60 min
   - Home to Grandma’s: 30 min

**Proposed Schedule:**

- **James's Schedule:**
  - **Landing at BOS Airport:** James lands at a specific time (let's assume 10:00 AM for this schedule).
  - **Car Rental:** James rents a car immediately after landing. Allowing 30 minutes for the car rental process, he will be ready to leave the airport by 10:30 AM.
  - **Travel to Grandma’s:** James drives from BOS Airport to Grandma’s, which takes 60 minutes. He will arrive at Grandma’s by 11:30 AM.

- **Emily's Schedule:**
  - **Pickup from Home:** Emily is picked up from home at 9:00 AM.
  - **Travel to BOS Airport:** The drive from home to BOS Airport takes 60 minutes, so Emily will arrive at the airport by 10:00 AM.
  - **Airport Pickup:** Emily is picked up by James (or another designated driver) at 10:00 AM.
  - **Travel to Grandma’s:** After picking up Emily, they travel from BOS Airport to Grandma’s, taking 60 minutes, arriving by 11:00 AM.

- **Supervision and Cooking Timelines:**
  - Ensure that someone is available at Grandma’s to supervise any ongoing activities or cooking preparations starting from 11:00 AM when Emily and James arrive.

This schedule ensures that all travel and pickup requirements are met without conflict, and both James and Emily arrive at Grandma’s in a timely manner.
🔹 Supervisor Agent: Comprehensive report detailing dinner preparation logistics and arrivals:

1. **Cooking Start Time:**
   - The cooking process began at 1:00 PM to ensure that the turkey and all sides are ready by the 6:00 PM dinner time. The kitchen team is maintaining supervision to ensure everything is cooked to perfection.

2. **Emily's Pickup:**
   - Emily was picked up by Driver A at 4:30 PM. She is expected to arrive home by 5:00 PM, ensuring she is present for the 6:00 PM dinner.

3. **Grandma's Pickup:**
   - Grandma was picked up by Driver B at 4:00 PM. She is expected to arrive home by 5:15 PM, allowing her ample time to settle in before dinner.

4. **All Family Members at Home for 6:00 PM Dinner:**
   - All family members, including Emily and Grandma, are expected to be home by 5:30 PM, ensuring everyone is present for the 6:00 PM dinner.

5. **Turkey and Sides Ready by Dinner Time:**
   - The turkey and all side dishes are on schedule to be ready by 5:45 PM, allowing for a brief resting period before serving at 6:00 PM.

6. **Cooking Supervision Maintained:**
   - Cooking supervision is being maintained by Chef John, ensuring all dishes are prepared according to plan and on time.

All logistical elements are on track to ensure a successful and timely dinner.

🔗 **Inter-Agent Dependencies**
🔸 Member & Time Setup Agent depends on: None
🔸 Requirement Setup Agent depends on: None
🔸 Constraint Validation Agent depends on: None
🔸 Supervisor Agent depends on: None

🎯 **Context for Member & Time Setup Agent:**
Structured schedule ensuring all members arrive on time for dinner.

- Sarah(Mom): Host, at home
- James(Dad): Lands at BOS 1:00 PM from SF
- Emily(Sister): Lands at BOS 2:30 PM from Chicago
- Michael(Brother): Driving, arrives 3:00 PM from NY
- Grandma: Needs pickup from suburban Boston
🔄 Rolling back Member & Time Setup Agent's operation...
🔄 Member & Time Setup Agent rolled back successfully.

Example 3: Wedding Logistics Planning With Disruption

Input for example 3:

# Initialize Saga
saga = Saga()

LT_Agent = Agent(
    name="Locations and Time Setup Agent",
    backstory="You define locations, travel times, and guest arrival schedules.",
    task_description="Set up locations, travel times, and ensure accurate scheduling of arrivals.",
    task_expected_output="Structured location data and expected arrival times. Fourlocations:𝑉 ={𝐵,𝐺,𝑇,𝑊},where𝐵isBostonAir- port, 𝐺 is Gift shop, 𝑇 is Tailor shop, and 𝑊 is Wedding venue. 𝐵-𝐺 : 45, 𝐵-𝑇 : 30, 𝐵-𝑊 : 40, 𝐺-𝑇 : 20, 𝐺-𝑊 : 25, 𝑇-𝑊 : 15. - Alex:At𝐵at11:00AMfromChicago(needaride) - Jamie:At𝐵at12:30PMfromAtlanta(needaride) - Pat: At 𝑊 at 12:00 PM driving from NYC (has 5-seater car)"
)

# ---- Task Setup Agent ---- #
TS_Agent = Agent(
    name="Task Setup Agent",
    backstory="You manage the scheduling of required wedding tasks.",
    task_description="Schedule gift collection after 12:00 PM, clothes pickup before 2:00 PM, and ensure photo session at 3:00 PM.",
    task_expected_output="Optimized task schedule aligned with constraints."
)

# ---- Disruption Update Agent (With Disruption) ---- #
DU_Agent = Agent(
    name="Disruption Update Agent",
    backstory="You monitor road closures and dynamically reroute transportation as needed.",
    task_description="Identify any road closures or unexpected disruptions and adjust travel plans accordingly.",
    task_expected_output="In case there is road closures of B to G, and dynamically reroute transportation. Updated task schedule, ensuring minimal delays and timely arrivals with new updates."
)

# ---- Resource Management Agent ---- #
RM_Agent = Agent(
    name="Resource Management Agent",
    backstory="You allocate available transport resources efficiently.",
    task_description="Coordinate 5 vehicle usage and Local friend Chris(5-seater)available, for guest transportation and task fulfillment.",
    task_expected_output="Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar(5-seater)withPat,availableafterheisBoston - LocalfriendChris(5-seater)availableafter1:30PMat𝑊"
)

# ---- Constraint Validation Agent ---- #
CV_Agent = Agent(
    name="Constraint Validation Agent",
    backstory="You verify all scheduling constraints to ensure smooth execution.",
    task_description="Ensure all tasks are completed within operating hours and vehicle constraints are met.",
    task_expected_output="Validated schedule with no conflicts. All tasks must complete before 3:00 PM photo time - Gift store opens at 12:00 PM - Tailor closes at 2:00 PM - Two cars must accommodate all transport needs"
)

# ---- Supervisor Agent ---- #
WEO_Agent = Agent(
    name="Wedding Event Oversight Agent",
    backstory="You oversee the entire wedding logistics to ensure a smooth execution of tasks.",
    task_description="Monitor and ensure all tasks are completed on time, resolving any logistical issues.",
    task_expected_output="Give a wedding scheduling plan for people, task and time."
)



# Register Agents in Saga
saga.transaction_manager([LT_Agent, TS_Agent, DU_Agent, RM_Agent, CV_Agent, WEO_Agent])

Output for example 3:

📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ Utils imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ utils.logging imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ tool_agent.tool imported successfully!
✅ utils.completions imported successfully!
✅ utils.extraction imported successfully!
✅ multi_agent.crew imported successfully!
✅ planning_agent.react_agent imported successfully!
✅ tool_agent.tool imported successfully!
✅ Saga imported successfully!
✅ Agent imported successfully!

==================================================
🛠 Transaction Manager: Agents and dependencies initialized.
==================================================


==================================================
🚀 Running Agent: Locations and Time Setup Agent
==================================================

✅ Locations and Time Setup Agent completed successfully.

==================================================
🚀 Running Agent: Task Setup Agent
==================================================

✅ Task Setup Agent completed successfully.

==================================================
🚀 Running Agent: Disruption Update Agent
==================================================

✅ Disruption Update Agent completed successfully.

==================================================
🚀 Running Agent: Resource Management Agent
==================================================

✅ Resource Management Agent completed successfully.

==================================================
🚀 Running Agent: Constraint Validation Agent
==================================================

✅ Constraint Validation Agent completed successfully.

==================================================
🚀 Running Agent: Wedding Event Oversight Agent
==================================================

✅ Wedding Event Oversight Agent completed successfully.

📌 **Intra-Agent Execution Details**
🔹 Locations and Time Setup Agent: <locations>
  <location id="B" name="Boston Airport"/>
  <location id="G" name="Gift shop"/>
  <location id="T" name="Tailor shop"/>
  <location id="W" name="Wedding venue"/>
</locations>

<travel_times>
  <from id="B">
    <to id="G" time="45"/>
    <to id="T" time="30"/>
    <to id="W" time="40"/>
  </from>
  <from id="G">
    <to id="T" time="20"/>
    <to id="W" time="25"/>
  </from>
  <from id="T">
    <to id="W" time="15"/>
  </from>
</travel_times>

<guest_arrivals>
  <guest name="Alex" location="B" arrival_time="11:00 AM" origin="Chicago" transport="needs ride"/>
  <guest name="Jamie" location="B" arrival_time="12:30 PM" origin="Atlanta" transport="needs ride"/>
  <guest name="Pat" location="W" arrival_time="12:00 PM" origin="NYC" transport="has 5-seater car"/>
</guest_arrivals>
🔹 Task Setup Agent: To optimize the task schedule while aligning with the given constraints, the following schedule is proposed:

1. **Clothes Pickup**: Schedule this task between 12:00 PM and 2:00 PM. It is crucial to complete this task before 2:00 PM, so aim to start it as soon as possible after 12:00 PM.

2. **Gift Collection**: This task should be scheduled after 12:00 PM. Ideally, plan to start this task immediately after the clothes pickup is completed, ensuring it does not overlap with the photo session.

3. **Photo Session**: This task is fixed at 3:00 PM. Ensure that both the clothes pickup and gift collection are completed before this time.

By following this schedule, all tasks are completed within their respective time constraints:

- **12:00 PM - 1:00 PM**: Clothes Pickup
- **1:00 PM - 2:30 PM**: Gift Collection
- **3:00 PM**: Photo Session

This schedule ensures that each task is completed in a timely manner, respecting all given constraints.
🔹 Disruption Update Agent: To effectively manage the task of identifying road closures or unexpected disruptions and adjusting travel plans, I will proceed with the following steps:

1. **Identify Road Closures or Disruptions**: I will gather real-time data from traffic management systems, local government announcements, and transportation agencies to identify any road closures or unexpected disruptions on the planned route.

2. **Analyze Impact**: Assess the impact of these closures or disruptions on the current travel plans, focusing on the route from B to G.

3. **Reroute Transportation**: Based on the identified closures, I will dynamically reroute transportation to ensure minimal delays. This involves selecting alternative routes that are clear and efficient.

4. **Update Task Schedule**: With the new route in place, I will update the task schedule to reflect any changes in travel time, ensuring timely arrivals.

5. **Communicate Updates**: Provide all relevant stakeholders with the updated travel plans and schedules to ensure everyone is informed of the changes.

Here is the updated task schedule with new route information:

- **Original Route**: B to G
- **Identified Closure**: Road closure on the original route from B to G
- **Alternative Route**: Rerouted via C to F to G
- **Estimated Delay**: 15 minutes additional travel time
- **Updated Arrival Time**: Adjusted to account for the reroute, ensuring arrival within the acceptable time frame.

Please ensure that all transportation personnel and stakeholders are informed of these changes to facilitate a smooth transition to the new route.
🔹 Resource Management Agent: Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar (5-seater) with Pat, available after he is in Boston - Local friend Chris (5-seater) available after 1:30 PM at location W
🔹 Constraint Validation Agent: To ensure all tasks are completed within operating hours and vehicle constraints are met, I have validated the schedule as follows:

1. **Gift Store Visit**:
   - **Operating Hours**: Opens at 12:00 PM
   - **Scheduled Time**: 12:00 PM - 1:00 PM
   - **Transport**: Car 1

2. **Tailor Visit**:
   - **Operating Hours**: Closes at 2:00 PM
   - **Scheduled Time**: 1:15 PM - 2:00 PM
   - **Transport**: Car 2

3. **Photo Session**:
   - **Deadline**: Must complete before 3:00 PM
   - **Scheduled Time**: 2:15 PM - 3:00 PM
   - **Transport**: Car 1

**Vehicle Constraints**:
- **Car 1**: Used for Gift Store Visit and Photo Session
- **Car 2**: Used for Tailor Visit

All tasks are scheduled within the operating hours and vehicle constraints, ensuring no conflicts.
🔹 Wedding Event Oversight Agent: To ensure a smooth execution of the wedding logistics, here is a detailed scheduling plan outlining the people involved, tasks, and their respective times:

**Wedding Day Schedule:**

**6:00 AM - 7:00 AM**
- **Task:** Venue Setup Begins
  - **People Involved:** Venue Coordinator, Decor Team
  - **Details:** Ensure all decorations, seating arrangements, and lighting are set up according to the plan.

**7:00 AM - 8:00 AM**
- **Task:** Bridal Party Hair and Makeup
  - **People Involved:** Hair Stylist, Makeup Artist, Bride, Bridesmaids
  - **Details:** Hair and makeup for the bride and bridesmaids to begin.

**8:00 AM - 9:00 AM**
- **Task:** Groom and Groomsmen Preparation
  - **People Involved:** Groom, Groomsmen, Photographer
  - **Details:** Groom and groomsmen to get dressed and ready. Photographer to capture candid moments.

**9:00 AM - 10:00 AM**
- **Task:** Final Venue Check and Guest Arrival Setup
  - **People Involved:** Venue Coordinator, Ushers
  - **Details:** Final check on venue setup, ensure guest seating and welcome area are ready.

**10:00 AM - 11:00 AM**
- **Task:** Ceremony Rehearsal and Sound Check
  - **People Involved:** Officiant, Sound Technician, Wedding Party
  - **Details:** Quick rehearsal of the ceremony and sound system check.

**11:00 AM - 12:00 PM**
- **Task:** Guest Arrival
  - **People Involved:** Ushers, Guest Coordinator
  - **Details:** Ushers to greet and seat guests as they arrive.

**12:00 PM - 1:00 PM**
- **Task:** Wedding Ceremony
  - **People Involved:** Officiant, Bride, Groom, Wedding Party, Guests
  - **Details:** Conduct the wedding ceremony.

**1:00 PM - 2:00 PM**
- **Task:** Post-Ceremony Photos
  - **People Involved:** Photographer, Bride, Groom, Wedding Party
  - **Details:** Capture formal photos with family and wedding party.

**2:00 PM - 3:00 PM**
- **Task:** Cocktail Hour
  - **People Involved:** Catering Staff, Bartenders
  - **Details:** Serve drinks and appetizers to guests.

**3:00 PM - 4:00 PM**
- **Task:** Reception Begins
  - **People Involved:** DJ/Band, Catering Staff
  - **Details:** Guests seated, introduction of the wedding party, and start of the meal service.

**4:00 PM - 5:00 PM**
- **Task:** Speeches and Toasts
  - **People Involved:** Best Man, Maid of Honor, Parents
  - **Details:** Scheduled speeches and toasts by key individuals.

**5:00 PM - 6:00 PM**
- **Task:** Cake Cutting and First Dance
  - **People Involved:** Bride, Groom, DJ/Band
  - **Details:** Cake cutting followed by the couple's first dance.

**6:00 PM - 9:00 PM**
- **Task:** Dinner and Dancing
  - **People Involved:** Guests, DJ/Band
  - **Details:** Dinner service continues, open dance floor for guests.

**9:00 PM - 10:00 PM**
- **Task:** Bouquet and Garter Toss
  - **People Involved:** Bride, Groom, Guests
  - **Details:** Traditional bouquet and garter toss.

**10:00 PM - 11:00 PM**
- **Task:** Final Dance and Farewell
  - **People Involved:** Bride, Groom, Guests
  - **Details:** Last dance of the night, farewell to guests.

**11:00 PM - 12:00 AM**
- **Task:** Venue Cleanup
  - **People Involved:** Venue Staff, Cleanup Crew
  - **Details:** Ensure the venue is cleaned and restored to its original condition.

This plan ensures that all tasks are completed on time and any logistical issues can be addressed promptly.

🔗 **Inter-Agent Dependencies**
🔸 Locations and Time Setup Agent depends on: None
🔸 Task Setup Agent depends on: None
🔸 Disruption Update Agent depends on: None
🔸 Resource Management Agent depends on: None
🔸 Constraint Validation Agent depends on: None
🔸 Wedding Event Oversight Agent depends on: None

🎯 **Context for Resource Management Agent:**
Optimized 5 vehicle allocation and friend welcome ensuring timely arrivals. - Onecar (5-seater) with Pat, available after he is in Boston - Local friend Chris (5-seater) available after 1:30 PM at location W
🔄 Rolling back Resource Management Agent's operation...
🔄 Resource Management Agent rolled back successfully.

Example 4: Thanksgiving Dinner Planning With Disruption

Input for example 4:

# Initialize Saga
saga = Saga()

# ---- Member & Time Setup Agent ---- #
MT_Agent = Agent(
    name="Member & Time Setup Agent",
    backstory="You track family members' arrivals and ensure accurate scheduling.",
    task_description="Set up arrival times, locations, and travel durations for all family members.",
    task_expected_output="Structured schedule ensuring all members arrive on time for dinner. - Sarah(Mom):Host,athome, - James(Dad):LandsatBOS1:00PMfromSF, - Emily(Sister):LandsatBOS2:30PMfromChicago - Michael(Brother):Driving,arrives3:00PMfromNY - Grandma:NeedspickupfromsuburbanBoston"
)

# ---- Requirement Setup Agent ---- #
RS_Agent = Agent(
    name="Requirement Setup Agent",
    backstory="You manage cooking schedules and key logistical needs.",
    task_description="Schedule turkey and side dish preparation while ensuring someone stays home for supervision.",
    task_expected_output="Optimized cooking schedule aligning with dinner timing. cooking requirements:  -Turkey:4hourscookingtime, - Sidedishes:2hourspreparation, - Someonemuststayhomeduringcooking, "
)

# ---- Disruption Update Agent ---- #
DU_Agent = Agent(
    name="Disruption Update Agent",
    backstory="You manage unexpected disruptions such as flight delays.",
    task_description="Adjust schedule due to James's flight delay by 1 hour.",
    task_expected_output="Updated schedule reflecting James's new arrival time at 2:00 PM."
)

# ---- Constraint Validation Agent ---- #
CV_Agent = Agent(
    name="Constraint Validation Agent",
    backstory="You verify all scheduling constraints and ensure compliance.",
    task_description="Validate that all pickups, cooking timelines, and supervision requirements are met.",
    task_expected_output="A conflict-free schedule ensuring all tasks are completed efficiently. - Jamesmustrentcarafterlanding, - Emilyrequiresairportpickup ,- Traveltimes: – HometoBOSAirport:60min – BOSAirporttoGrandma’s:60min – HometoGrandma’s:30min"
)

# ---- Supervisor Agent ---- #
SA_Agent = Agent(
    name="Supervisor Agent",
    backstory="You oversee all logistical elements and generate the final dinner preparation report.",
    task_description="Monitor and report on key tasks, including cooking start time, Emily's pickup, and Grandma's pickup.",
    task_expected_output="Comprehensive report detailing dinner preparation logistics and arrivals. key requirement: - Allfamilymembersathomefor6:00PMdinner - Turkeyandsidesreadybydinnertime - Allpickupscompletedwithavailabledrivers - Cookingsupervisionmaintained"
)

# Register Agents in Saga
saga.transaction_manager([MT_Agent, RS_Agent, DU_Agent, CV_Agent, SA_Agent])

Output for example 4:

📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ Utils imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/pytho
798A
n@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ utils.logging imported successfully!
📂 Project Root: /Users/glin/Documents/GitHub/SagaLLM-repo
🔍 Updated sys.path:
/Users/glin/Documents/GitHub/SagaLLM-repo/applications
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python310.zip
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10
/usr/local/Cellar/python@3.10/3.10.14/Frameworks/Python.framework/Versions/3.10/lib/python3.10/lib-dynload
/Users/glin/Documents/GitHub/SagaLLM-repo/venv/lib/python3.10/site-packages
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
/Users/glin/Documents/GitHub/SagaLLM-repo/src
✅ tool_agent.tool imported successfully!
✅ utils.completions imported successfully!
✅ utils.extraction imported successfully!
✅ multi_agent.crew imported successfully!
✅ planning_agent.react_agent imported successfully!
✅ tool_agent.tool imported successfully!
✅ Saga imported successfully!
✅ Agent imported successfully!

==================================================
🛠 Transaction Manager: Agents and dependencies initialized.
==================================================


==================================================
🚀 Running Agent: Member & Time Setup Agent
==================================================

✅ Member & Time Setup Agent completed successfully.

==================================================
🚀 Running Agent: Requirement Setup Agent
==================================================

✅ Requirement Setup Agent completed successfully.

==================================================
🚀 Running Agent: Disruption Update Agent
==================================================

✅ Disruption Update Agent completed successfully.

==================================================
🚀 Running Agent: Constraint Validation Agent
==================================================

✅ Constraint Validation Agent completed successfully.

==================================================
🚀 Running Agent: Supervisor Agent
==================================================

✅ Supervisor Agent completed successfully.

📌 **Intra-Agent Execution Details**
🔹 Member & Time Setup Agent: Structured schedule ensuring all members arrive on time for dinner.

- Sarah(Mom): Host, at home
- James(Dad): Lands at BOS 1:00 PM from SF
- Emily(Sister): Lands at BOS 2:30 PM from Chicago
- Michael(Brother): Driving, arrives 3:00 PM from NY
- Grandma: Needs pickup from suburban Boston
🔹 Requirement Setup Agent: To ensure a smooth and timely preparation for dinner, here's an optimized cooking schedule:

1. **Turkey Preparation and Cooking:**
   - **Start Time:** 12:00 PM
   - **End Time:** 4:00 PM
   - **Details:** The turkey requires 4 hours of cooking time. Ensure it is placed in the oven by 12:00 PM to be ready by 4:00 PM.

2. **Side Dishes Preparation:**
   - **Start Time:** 2:00 PM
   - **End Time:** 4:00 PM
   - **Details:** Begin preparing the side dishes at 2:00 PM. This will allow them to be ready by the time the turkey is finished.

3. **Supervision Requirement:**
   - **Details:** Ensure that someone is at home from 12:00 PM to 4:00 PM to supervise the cooking process. This person can manage both the turkey and side dishes preparation.

This schedule ensures that all dishes are ready by 4:00 PM, aligning with dinner timing and meeting the cooking requirements.
🔹 Disruption Update Agent: Updated schedule reflecting James's new arrival time at 2:00 PM:

- 1:00 PM - Team Meeting (rescheduled to 2:30 PM)
- 2:00 PM - James's Arrival
- 2:30 PM - Welcome and Briefing Session with James
- 3:00 PM - Project Discussion
- 4:00 PM - Break
- 4:15 PM - Continued Discussion and Planning
- 5:00 PM - Wrap-up and Next Steps

Please note that the team meeting has been rescheduled to accommodate James's new arrival time.
🔹 Constraint Validation Agent: To create a conflict-free schedule that ensures all tasks are completed efficiently, we need to consider the following elements: James must rent a car after landing, Emily requires airport pickup, and the travel times between locations. Here is a proposed schedule:

1. **James's Schedule:**
   - **Landing at BOS Airport:** Assume James lands at 10:00 AM.
   - **Car Rental:** Allocate 30 minutes for James to rent a car after landing.
   - **Departure from BOS Airport:** 10:30 AM.
   - **Travel to Grandma’s:** 60 minutes.
   - **Arrival at Grandma’s:** 11:30 AM.

2. **Emily's Schedule:**
   - **Home Departure:** Assume Emily needs to be picked up from home at 9:00 AM.
   - **Travel to BOS Airport:** 60 minutes.
   - **Arrival at BOS Airport:** 10:00 AM.
   - **Pickup Emily:** 10:00 AM.
   - **Travel to Grandma’s:** 60 minutes.
   - **Arrival at Grandma’s:** 11:00 AM.

3. **Supervision and Cooking Timelines:**
   - **Cooking Start Time at Grandma’s:** 11:30 AM, after both James and Emily have arrived.
   - **Supervision:** Ensure someone is available to supervise the cooking from 11:30 AM onwards.

This schedule ensures that all tasks are completed efficiently, with no conflicts in travel or task timelines.
🔹 Supervisor Agent: Comprehensive report detailing dinner preparation logistics and arrivals:

1. **Cooking Start Time:**
   - The cooking process began at 12:00 PM to ensure that the turkey and all side dishes are ready by the 6:00 PM dinner time. Cooking supervision is maintained throughout to ensure quality and timely preparation.

2. **Emily's Pickup:**
   - Emily was scheduled to be picked up at 4:30 PM. The driver assigned for Emily's pickup confirmed her safe arrival at home by 5:00 PM.

3. **Grandma's Pickup:**
   - Grandma's pickup was arranged for 4:00 PM. The driver responsible for this task reported that Grandma was picked up on time and arrived home by 4:45 PM.

4. **Dinner Readiness:**
   - All family members are expected to be home by 5:30 PM, ensuring everyone is present for the 6:00 PM dinner.
   - The turkey and all side dishes are on track to be ready by the designated dinner time, with continuous cooking supervision to ensure everything is prepared perfectly.

5. **Driver Availability:**
   - All pickups have been completed with the available drivers, ensuring no delays in family members' arrivals.

Overall, the dinner preparation logistics are proceeding smoothly, with all key tasks being monitored and completed on schedule.

🔗 **Inter-Agent Dependencies**
🔸 Member & Time Setup Agent depends on: None
🔸 Requirement Setup Agent depends on: None
🔸 Disruption Update Agent depends on: None
🔸 Constraint Validation Agent depends on: None
🔸 Supervisor Agent depends on: None

🎯 **Context for Member & Time Setup Agent:**
Structured schedule ensuring all members arrive on time for dinner.

- Sarah(Mom): Host, at home
- James(Dad): Lands at BOS 1:00 PM from SF
- Emily(Sister): Lands at BOS 2:30 PM from Chicago
- Michael(Brother): Driving, arrives 3:00 PM from NY
- Grandma: Needs pickup from suburban Boston
🔄 Rolling back Member & Time Setup Agent's operation...
🔄 Member & Time Setup Agent rolled back successfully.

✅ Final Thoughts

If everything succeeds, all agents complete. ✅
If any agent fails, all completed agents roll back automatically, or by inputing a specific node. ✅
Ensures multi-agent consistency in real-world applications (e.g., stock trading, planning, scheduling, transaction, or payments). ✅

📂 Project Structure

📜 Citation

If you find this repository helpful, please cite the following paper:

SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning  
Anonymous Author(s)

Name		Name	Last commit message	Last commit date
Latest commit History 19 Commits
.idea		.idea
agent_frameworks		agent_frameworks
applications		applications
img		img
output		output
src		src
.DS_Store		.DS_Store
.gitattributes		.gitattributes
README.md		README.md
main.py		main.py
requirements.txt		requirements.txt

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SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning

Key Functions of `Saga` libraries

🔹 Key Features of Using `SagaCoordinator` Instead of Previous `Crew`

🚀 How To Run

1️⃣ Setup Environment

2️⃣ Running Multi-Agent Frameworks

3️⃣ Import Saga Library

Example 1: Wedding Logsitics Planning

Example 2: Thanksgiving Dinner Planning

Example 3: Wedding Logistics Planning With Disruption

Example 4: Thanksgiving Dinner Planning With Disruption

✅ Final Thoughts

📂 Project Structure

📜 Citation

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SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning

Key Functions of Saga libraries

🔹 Key Features of Using SagaCoordinator Instead of Previous Crew

🚀 How To Run

1️⃣ Setup Environment

2️⃣ Running Multi-Agent Frameworks

3️⃣ Import Saga Library

Example 1: Wedding Logsitics Planning

Example 2: Thanksgiving Dinner Planning

Example 3: Wedding Logistics Planning With Disruption

Example 4: Thanksgiving Dinner Planning With Disruption

✅ Final Thoughts

📂 Project Structure

📜 Citation

About

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Key Functions of `Saga` libraries

🔹 Key Features of Using `SagaCoordinator` Instead of Previous `Crew`

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