From 5b041ca9d43466dafb3ca672c54ffb06f5561c2f Mon Sep 17 00:00:00 2001
From: Diwank Singh Tomer <diwank.singh@gmail.com>
Date: Mon, 7 Oct 2024 09:06:31 -0400
Subject: [PATCH] doc: Add devfest email assistant README

Signed-off-by: Diwank Singh Tomer <diwank.singh@gmail.com>
---
 IDEAS.md                                   | 1377 ++++++++++++++++++++
 cookbooks/00-Devfest-Email-Assistant.ipynb |  296 +++++
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+# Expanded Implementation Scenarios for Julep
+
+Below are detailed implementation plans for each of the 50 scenarios using Julep's **docs**, **sessions**, **tasks**, and **executions** features. Each scenario includes a complexity rating from **1 (easiest)** to **5 (most complex)**.
+
+---
+
+### 1. Automated Customer Support Agent
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store customer data, FAQs, and troubleshooting guides.
+  - Integrate CRM documentation for accessing and updating customer information.
+
+- **Sessions:**
+  - Create a persistent session for each customer to maintain conversation context.
+  - Track interaction history to personalize support.
+
+- **Tasks:**
+  - Define tasks for handling common inquiries (e.g., order status, billing issues).
+  - Implement escalation tasks for complex issues that require human intervention.
+  - Automate ticket creation and update processes.
+
+- **Executions:**
+  - Execute tasks based on customer inputs.
+  - Monitor task executions to ensure timely responses and issue resolutions.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integrating with external CRM systems, handling diverse query types, and maintaining contextual sessions, which increases complexity.
+
+---
+
+### 2. Smart Research Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store access to academic databases and research papers.
+  - Include summarization templates and research methodologies.
+
+- **Sessions:**
+  - Manage user-specific research sessions to track ongoing projects and queries.
+  - Maintain context for multi-step research tasks.
+
+- **Tasks:**
+  - Create tasks for searching databases, summarizing articles, and compiling reports.
+  - Implement conditional steps based on research findings.
+
+- **Executions:**
+  - Execute research tasks sequentially or in parallel.
+  - Stream execution results to provide real-time updates to the user.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires integration with academic databases, advanced summarization capabilities, and managing complex multi-step workflows.
+
+---
+
+### 3. Personal Finance Manager
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store user financial data, budgeting templates, and investment information.
+  - Integrate banking API documentation for transaction fetching.
+
+- **Sessions:**
+  - Create persistent sessions to track user financial activities over time.
+  - Maintain context for budgeting goals and financial plans.
+
+- **Tasks:**
+  - Define tasks for expense tracking, budget creation, and investment monitoring.
+  - Automate alerts for budget limits and investment opportunities.
+
+- **Executions:**
+  - Execute financial tasks based on user interactions and predefined schedules.
+  - Monitor executions to provide real-time financial advice and updates.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Needs secure integration with banking APIs, real-time data processing, and robust budgeting logic.
+
+---
+
+### 4. Content Creation Workflow
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store SEO guidelines, content templates, and style guides.
+  - Include access to keyword research tools.
+
+- **Sessions:**
+  - Manage content creation sessions to track progress and drafts.
+  - Maintain context for ongoing content projects.
+
+- **Tasks:**
+  - Create multi-step tasks for topic ideation, content drafting, SEO optimization, and scheduling.
+  - Integrate tools for grammar checking and SEO analysis.
+
+- **Executions:**
+  - Automate the execution of content creation tasks.
+  - Schedule publishing according to editorial calendars.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves coordinating multiple tools and steps but remains manageable with clear task definitions.
+
+---
+
+### 5. E-commerce Order Processing System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store product catalogs, inventory data, and order processing guidelines.
+  - Integrate with shipping provider APIs.
+
+- **Sessions:**
+  - Create sessions for each order to track its lifecycle.
+  - Maintain context for customer preferences and order history.
+
+- **Tasks:**
+  - Define tasks for order validation, inventory updates, payment processing, and shipment tracking.
+  - Automate customer notifications at each stage.
+
+- **Executions:**
+  - Execute order processing tasks in sequence.
+  - Monitor executions to handle exceptions like payment failures or inventory shortages.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires robust integrations with payment gateways, inventory systems, and shipping providers, along with handling various order states.
+
+---
+
+### 6. AI-Powered Personal Trainer
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store workout routines, nutritional plans, and progress tracking templates.
+  - Include integration details for fitness tracking APIs.
+
+- **Sessions:**
+  - Create individual sessions for each user to track their fitness journey.
+  - Maintain context for user goals and progress.
+
+- **Tasks:**
+  - Define tasks for generating personalized workout plans, tracking progress, and adjusting routines.
+  - Automate reminders and motivational messages.
+
+- **Executions:**
+  - Execute fitness tasks based on user inputs and scheduled routines.
+  - Monitor executions to provide real-time feedback and adjustments.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves personalization and integration with fitness data sources, but achievable with well-defined task workflows.
+
+---
+
+### 7. Automated Email Marketing Campaigns
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store email templates, segmentation criteria, and campaign schedules.
+  - Integrate with email marketing platforms (e.g., SendGrid, Mailchimp).
+
+- **Sessions:**
+  - Manage campaign-specific sessions to track interactions and responses.
+  - Maintain context for ongoing and past campaigns.
+
+- **Tasks:**
+  - Create tasks for email creation, scheduling, sending, and performance analysis.
+  - Automate A/B testing and content personalization.
+
+- **Executions:**
+  - Execute email campaigns based on predefined schedules and triggers.
+  - Monitor execution performance and adjust strategies accordingly.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with email platforms and managing dynamic content delivery, but is straightforward with clear task definitions.
+
+---
+
+### 8. Intelligent Recruitment Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store job descriptions, candidate profiles, and evaluation criteria.
+  - Integrate with HR systems and job boards.
+
+- **Sessions:**
+  - Create sessions for each recruitment process to track candidate interactions.
+  - Maintain context for candidate status and feedback.
+
+- **Tasks:**
+  - Define tasks for resume screening, interview scheduling, and candidate communications.
+  - Automate feedback collection and report generation.
+
+- **Executions:**
+  - Execute recruitment tasks based on candidate actions and application stages.
+  - Monitor executions to ensure timely processing and compliance.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Involves complex integrations with HR systems, handling diverse candidate data, and ensuring compliance with recruitment processes.
+
+---
+
+### 9. Smart Home Automation Controller
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store device configurations, automation rules, and user preferences.
+  - Integrate with smart home device APIs (e.g., Philips Hue, Nest).
+
+- **Sessions:**
+  - Manage user-specific sessions to track home automation settings.
+  - Maintain context for user routines and preferences.
+
+- **Tasks:**
+  - Create tasks for device control, routine scheduling, and energy monitoring.
+  - Automate actions based on triggers like time, occupancy, or environmental changes.
+
+- **Executions:**
+  - Execute home automation tasks in real-time or based on schedules.
+  - Monitor executions to ensure devices respond correctly and adjust settings as needed.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires integration with multiple smart devices and managing dynamic automation rules, increasing system complexity.
+
+---
+
+### 10. Automated Legal Document Analyzer
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store legal templates, compliance guidelines, and case studies.
+  - Integrate with legal databases and document repositories.
+
+- **Sessions:**
+  - Create sessions for each document analysis to track progress and findings.
+  - Maintain context for specific legal requirements and clauses.
+
+- **Tasks:**
+  - Define tasks for document ingestion, key information extraction, compliance checking, and summarization.
+  - Automate flagging of non-compliant sections and suggest necessary amendments.
+
+- **Executions:**
+  - Execute document analysis tasks sequentially or in parallel.
+  - Monitor executions to ensure accuracy and compliance with legal standards.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Involves advanced natural language processing, integration with legal databases, and ensuring compliance with intricate legal standards.
+
+---
+
+### 11. Personalized Learning Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store educational content, learning paths, and assessment criteria.
+  - Integrate with educational platforms and resources.
+
+- **Sessions:**
+  - Create individual learning sessions to track user progress and preferences.
+  - Maintain context for personalized learning paths and goals.
+
+- **Tasks:**
+  - Define tasks for content recommendation, quiz generation, progress tracking, and feedback provision.
+  - Automate adjustments to learning paths based on performance.
+
+- **Executions:**
+  - Execute learning tasks based on user interactions and progress.
+  - Monitor executions to provide real-time feedback and adjust learning strategies.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires personalization algorithms, integration with educational content sources, and dynamic adaptation to user progress.
+
+---
+
+### 12. AI-Driven Social Media Manager
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store social media strategies, content calendars, and engagement guidelines.
+  - Integrate with social media APIs (e.g., Twitter, Facebook, LinkedIn).
+
+- **Sessions:**
+  - Manage campaign-specific sessions to track posts, engagements, and analytics.
+  - Maintain context for ongoing and scheduled campaigns.
+
+- **Tasks:**
+  - Create tasks for content creation, scheduling, posting, and performance analysis.
+  - Automate engagement responses and A/B testing of content.
+
+- **Executions:**
+  - Execute social media tasks based on schedules and real-time engagement triggers.
+  - Monitor executions to optimize performance and adjust strategies.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integration with multiple social media platforms, dynamic content management, and real-time engagement handling.
+
+---
+
+### 13. Automated Travel Itinerary Planner
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store travel guides, destination information, and booking APIs.
+  - Integrate with flight, hotel, and transportation service APIs.
+
+- **Sessions:**
+  - Create travel-specific sessions to track itinerary progress and user preferences.
+  - Maintain context for personalized travel plans and updates.
+
+- **Tasks:**
+  - Define tasks for destination research, booking accommodations and transportation, and itinerary scheduling.
+  - Automate real-time updates and notifications during trips.
+
+- **Executions:**
+  - Execute travel planning tasks based on user inputs and predefined schedules.
+  - Monitor executions to handle changes and provide timely updates.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with travel service APIs and managing dynamic itinerary changes, which adds moderate complexity.
+
+---
+
+### 14. AI-Powered Inventory Management System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store inventory data, supplier information, and reordering guidelines.
+  - Integrate with inventory tracking systems and supplier APIs.
+
+- **Sessions:**
+  - Manage inventory sessions to monitor stock levels and reorder statuses.
+  - Maintain context for inventory forecasts and demand trends.
+
+- **Tasks:**
+  - Create tasks for stock monitoring, demand forecasting, automatic reordering, and supplier communication.
+  - Automate alerts for low stock levels and order confirmations.
+
+- **Executions:**
+  - Execute inventory management tasks in real-time or based on schedules.
+  - Monitor executions to ensure accurate stock levels and timely reorders.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires real-time inventory tracking, predictive analytics for demand forecasting, and reliable integration with supplier systems.
+
+---
+
+### 15. Intelligent Health Monitoring System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store health metrics templates, medical guidelines, and user health data.
+  - Integrate with health tracking devices and APIs (e.g., Fitbit, Apple Health).
+
+- **Sessions:**
+  - Create sessions for each user to track their health metrics and progress.
+  - Maintain context for personalized health goals and alerts.
+
+- **Tasks:**
+  - Define tasks for data collection, health metric analysis, trend monitoring, and alert notifications.
+  - Automate health insights and recommendations based on data.
+
+- **Executions:**
+  - Execute health monitoring tasks continuously or at scheduled intervals.
+  - Monitor executions to provide real-time health alerts and advice.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires integration with diverse health tracking devices, real-time data processing, and ensuring data privacy and accuracy.
+
+---
+
+### 16. Automated Content Moderation Tool
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store community guidelines, content policies, and moderation rules.
+  - Integrate with content platforms (e.g., forums, social media).
+
+- **Sessions:**
+  - Manage moderation sessions to track content reviews and decisions.
+  - Maintain context for specific moderation cases and user histories.
+
+- **Tasks:**
+  - Create tasks for content ingestion, automated screening, manual review, and action enforcement.
+  - Automate flagging of inappropriate content and notifying users of violations.
+
+- **Executions:**
+  - Execute content moderation tasks in real-time or batch processing.
+  - Monitor executions to ensure compliance and handle escalations.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Involves sophisticated content analysis, balancing automation with manual oversight, and ensuring adherence to diverse content policies.
+
+---
+
+### 17. AI-Powered Resume Builder
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store resume templates, industry-specific keywords, and formatting guidelines.
+  - Integrate with LinkedIn and other professional platforms for data fetching.
+
+- **Sessions:**
+  - Create user-specific sessions to track resume building progress.
+  - Maintain context for personalized content and formatting preferences.
+
+- **Tasks:**
+  - Define tasks for data collection, content suggestion, resume formatting, and final export.
+  - Automate style checks and consistency validations.
+
+- **Executions:**
+  - Execute resume building tasks based on user inputs and selections.
+  - Monitor executions to provide real-time feedback and suggestions.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with professional data sources and implementing dynamic content generation and formatting.
+
+---
+
+### 18. Smart Event Management System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store event templates, scheduling guidelines, and registration forms.
+  - Integrate with calendar and email platforms.
+
+- **Sessions:**
+  - Manage event-specific sessions to track registrations, schedules, and attendee interactions.
+  - Maintain context for event updates and follow-ups.
+
+- **Tasks:**
+  - Create tasks for event creation, attendee registration, schedule management, and post-event follow-ups.
+  - Automate reminders, notifications, and feedback collection.
+
+- **Executions:**
+  - Execute event management tasks based on schedules and attendee actions.
+  - Monitor executions to handle registrations and event logistics seamlessly.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves coordinating multiple aspects of event planning, handling real-time registrations, and ensuring smooth execution logistics.
+
+---
+
+### 19. Automated Survey Analyzer
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store survey templates, question types, and analysis methodologies.
+  - Integrate with survey distribution platforms (e.g., SurveyMonkey, Google Forms).
+
+- **Sessions:**
+  - Create sessions for each survey to track responses and analysis progress.
+  - Maintain context for specific survey objectives and parameters.
+
+- **Tasks:**
+  - Define tasks for survey distribution, data collection, sentiment analysis, and report generation.
+  - Automate data visualization and trend identification.
+
+- **Executions:**
+  - Execute survey analysis tasks upon survey completion.
+  - Monitor executions to provide timely and accurate insights.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with survey platforms and implementing effective data analysis and visualization techniques.
+
+---
+
+### 20. AI-Driven Project Management Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store project templates, task guidelines, and progress tracking tools.
+  - Integrate with project management platforms (e.g., Jira, Trello).
+
+- **Sessions:**
+  - Manage project-specific sessions to track tasks, milestones, and team interactions.
+  - Maintain context for project goals and progress updates.
+
+- **Tasks:**
+  - Create tasks for task breakdown, assignment, progress tracking, and status reporting.
+  - Automate notifications for deadlines and task completions.
+
+- **Executions:**
+  - Execute project management tasks based on project timelines and team inputs.
+  - Monitor executions to ensure projects stay on track and within scope.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integration with diverse project management tools, handling dynamic task assignments, and ensuring effective progress tracking.
+
+---
+
+### 21. Intelligent Document Summarizer
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store access to large documents, research papers, and reports.
+  - Include summarization algorithms and templates.
+
+- **Sessions:**
+  - Create sessions for each document summarization task.
+  - Maintain context for document sections and summarization preferences.
+
+- **Tasks:**
+  - Define tasks for document ingestion, key point extraction, and summary generation.
+  - Automate quality checks and user-specific summary adjustments.
+
+- **Executions:**
+  - Execute document summarization tasks efficiently.
+  - Monitor executions to ensure accurate and concise summaries.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires advanced natural language processing capabilities and efficient handling of large document data.
+
+---
+
+### 22. Automated Feedback Collection and Analysis
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store feedback forms, analysis templates, and reporting guidelines.
+  - Integrate with feedback collection platforms (e.g., Typeform, Google Forms).
+
+- **Sessions:**
+  - Manage feedback-specific sessions to track responses and analysis progress.
+  - Maintain context for feedback sources and analysis objectives.
+
+- **Tasks:**
+  - Create tasks for feedback distribution, data collection, sentiment analysis, and insight generation.
+  - Automate categorization and prioritization of feedback.
+
+- **Executions:**
+  - Execute feedback analysis tasks promptly upon data collection.
+  - Monitor executions to provide actionable insights and improvement strategies.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves integrating with feedback platforms and implementing effective sentiment analysis and categorization.
+
+---
+
+### 23. AI-Powered Language Translator
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store language dictionaries, translation models, and formatting guidelines.
+  - Integrate with translation APIs (e.g., Google Translate, DeepL).
+
+- **Sessions:**
+  - Create translation-specific sessions to track user preferences and translation history.
+  - Maintain context for ongoing translation projects.
+
+- **Tasks:**
+  - Define tasks for text ingestion, language detection, translation processing, and quality assurance.
+  - Automate post-translation formatting and localization adjustments.
+
+- **Executions:**
+  - Execute translation tasks in real-time or batch mode.
+  - Monitor executions to ensure accuracy and contextual relevance.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with robust translation APIs and handling nuances of different languages and contexts.
+
+---
+
+### 24. Smart Appointment Scheduler
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store scheduling templates, availability guidelines, and notification templates.
+  - Integrate with calendar platforms (e.g., Google Calendar, Outlook).
+
+- **Sessions:**
+  - Manage appointment-specific sessions to track scheduling progress and attendee interactions.
+  - Maintain context for user availability and preferences.
+
+- **Tasks:**
+  - Create tasks for availability checking, meeting scheduling, sending reminders, and handling cancellations.
+  - Automate conflict detection and resolution.
+
+- **Executions:**
+  - Execute scheduling tasks based on user inputs and calendar data.
+  - Monitor executions to ensure appointments are set correctly and notifications are sent.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves integration with calendar systems and implementing conflict resolution logic, which adds moderate complexity.
+
+---
+
+### 25. Automated Inventory Auditor
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store inventory audit templates, reconciliation guidelines, and reporting formats.
+  - Integrate with inventory management systems and databases.
+
+- **Sessions:**
+  - Create auditing sessions to track audit schedules and findings.
+  - Maintain context for different inventory categories and audit criteria.
+
+- **Tasks:**
+  - Define tasks for data extraction, discrepancy detection, reconciliation processes, and report generation.
+  - Automate audit scheduling and notification of audit results.
+
+- **Executions:**
+  - Execute inventory audit tasks periodically or on-demand.
+  - Monitor executions to ensure accurate and timely audits.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires reliable data integration and robust discrepancy detection mechanisms to handle complex inventory data.
+
+---
+
+### 26. AI-Driven Competitive Analysis Tool
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store competitor profiles, market analysis frameworks, and data sources.
+  - Integrate with market research APIs and competitor websites.
+
+- **Sessions:**
+  - Manage competitive analysis sessions to track data collection and analysis progress.
+  - Maintain context for specific market segments and competitive factors.
+
+- **Tasks:**
+  - Create tasks for data scraping, trend analysis, SWOT analysis, and report generation.
+  - Automate the aggregation and visualization of competitive data.
+
+- **Executions:**
+  - Execute competitive analysis tasks on a scheduled basis.
+  - Monitor executions to provide up-to-date insights and strategic recommendations.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves complex data scraping, accurate trend analysis, and maintaining up-to-date competitive insights, increasing overall complexity.
+
+---
+
+### 27. Smart Recipe Generator
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store ingredient databases, recipe templates, and dietary guidelines.
+  - Integrate with nutrition APIs and grocery databases.
+
+- **Sessions:**
+  - Create user-specific sessions to track dietary preferences and past recipes.
+  - Maintain context for ingredient availability and nutritional goals.
+
+- **Tasks:**
+  - Define tasks for ingredient analysis, recipe generation, nutritional calculation, and grocery list creation.
+  - Automate recipe suggestions based on user inputs and constraints.
+
+- **Executions:**
+  - Execute recipe generation tasks in real-time based on user requests.
+  - Monitor executions to ensure recipe accuracy and adherence to dietary needs.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with nutrition and grocery APIs and implementing intelligent recipe generation logic.
+
+---
+
+### 28. Automated Video Content Creator
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store video script templates, editing guidelines, and publishing schedules.
+  - Integrate with video editing and hosting platforms (e.g., Adobe Premiere, YouTube).
+
+- **Sessions:**
+  - Manage video creation sessions to track script development, editing stages, and publishing.
+  - Maintain context for ongoing video projects and collaboration.
+
+- **Tasks:**
+  - Create tasks for script generation, video editing, thumbnail creation, and publishing.
+  - Automate content review and approval workflows.
+
+- **Executions:**
+  - Execute video creation tasks based on project timelines.
+  - Monitor executions to ensure timely releases and quality standards.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integration with multiple video tools, managing creative workflows, and ensuring high-quality content production.
+
+---
+
+### 29. AI-Powered News Aggregator
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store news source lists, categorization templates, and summarization guidelines.
+  - Integrate with news APIs (e.g., NewsAPI, RSS feeds).
+
+- **Sessions:**
+  - Create user-specific sessions to track news preferences and reading history.
+  - Maintain context for personalized news feeds and topics of interest.
+
+- **Tasks:**
+  - Define tasks for news scraping, categorization, summarization, and personalization.
+  - Automate feed generation and delivery based on user preferences.
+
+- **Executions:**
+  - Execute news aggregation tasks periodically.
+  - Monitor executions to ensure timely and relevant news delivery.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires efficient news scraping, accurate categorization, and personalized summarization, but is manageable with clear task workflows.
+
+---
+
+### 30. Intelligent Appointment Follow-Up System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store follow-up templates, feedback forms, and communication guidelines.
+  - Integrate with CRM and email platforms.
+
+- **Sessions:**
+  - Manage follow-up sessions to track appointments and subsequent communications.
+  - Maintain context for previous interactions and follow-up actions.
+
+- **Tasks:**
+  - Create tasks for sending follow-up emails, collecting feedback, and scheduling future appointments.
+  - Automate reminder notifications and feedback analysis.
+
+- **Executions:**
+  - Execute follow-up tasks based on appointment completions.
+  - Monitor executions to ensure timely and effective communications.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves integration with CRM systems and implementing automated communication workflows, adding moderate complexity.
+
+---
+
+### 31. Automated Compliance Monitoring Tool
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store regulatory guidelines, compliance checklists, and reporting templates.
+  - Integrate with internal systems and regulatory databases.
+
+- **Sessions:**
+  - Create compliance-specific sessions to track monitoring activities and audit trails.
+  - Maintain context for various compliance standards and organizational policies.
+
+- **Tasks:**
+  - Define tasks for continuous monitoring, policy enforcement, and compliance reporting.
+  - Automate detection of non-compliant activities and trigger corrective actions.
+
+- **Executions:**
+  - Execute compliance monitoring tasks in real-time.
+  - Monitor executions to ensure ongoing adherence to regulations and standards.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Requires comprehensive integration with organizational systems, robust monitoring mechanisms, and ensuring adherence to multifaceted regulatory requirements.
+
+---
+
+### 32. AI-Powered Personal Shopper
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store product catalogs, user preference data, and recommendation algorithms.
+  - Integrate with e-commerce APIs (e.g., Amazon, Shopify).
+
+- **Sessions:**
+  - Manage shopping sessions to track user preferences and purchase history.
+  - Maintain context for personalized product recommendations.
+
+- **Tasks:**
+  - Create tasks for product suggestion, wishlist management, and deal notifications.
+  - Automate price comparisons and availability checks.
+
+- **Executions:**
+  - Execute personal shopping tasks based on user inputs and behavior.
+  - Monitor executions to provide timely recommendations and alerts.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integration with multiple e-commerce platforms, implementing personalized recommendation logic, and handling real-time deal tracking.
+
+---
+
+### 33. Smart Content Personalization Engine
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store content variants, personalization rules, and user segmentation data.
+  - Integrate with website CMS and analytics platforms.
+
+- **Sessions:**
+  - Create user-specific sessions to track interactions and preferences.
+  - Maintain context for personalized content delivery.
+
+- **Tasks:**
+  - Define tasks for content analysis, user behavior tracking, and personalized content delivery.
+  - Automate A/B testing and content optimization based on performance metrics.
+
+- **Executions:**
+  - Execute content personalization tasks in real-time.
+  - Monitor executions to adjust personalization strategies dynamically.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires real-time user behavior tracking, dynamic content delivery, and continuous optimization based on analytics, increasing system complexity.
+
+---
+
+### 34. Automated Debt Collection Agent
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store debt agreements, payment schedules, and communication templates.
+  - Integrate with financial systems and payment gateways.
+
+- **Sessions:**
+  - Manage debt collection sessions to track debtor interactions and payment statuses.
+  - Maintain context for individual debtors and their payment histories.
+
+- **Tasks:**
+  - Create tasks for sending payment reminders, negotiating payment plans, and issuing notifications.
+  - Automate follow-ups and escalation procedures for delinquent accounts.
+
+- **Executions:**
+  - Execute debt collection tasks based on payment statuses and schedules.
+  - Monitor executions to ensure effective communication and resolution.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves sensitive financial data handling, integration with payment systems, and implementing automated negotiation workflows.
+
+---
+
+### 35. AI-Driven Talent Matching System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store job descriptions, candidate profiles, and matching criteria.
+  - Integrate with job boards and professional networking platforms.
+
+- **Sessions:**
+  - Create sessions for each matching process to track candidate-job pairings.
+  - Maintain context for specific job requirements and candidate qualifications.
+
+- **Tasks:**
+  - Define tasks for candidate screening, skills matching, and recommendation generation.
+  - Automate notifications to both candidates and employers regarding match statuses.
+
+- **Executions:**
+  - Execute talent matching tasks based on incoming job postings and candidate applications.
+  - Monitor executions to ensure accurate and timely matches.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Requires sophisticated matching algorithms, integration with diverse data sources, and handling dynamic job and candidate data.
+
+---
+
+### 36. Intelligent Expense Reporting Tool
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store expense categories, reimbursement policies, and reporting templates.
+  - Integrate with financial systems and expense tracking APIs.
+
+- **Sessions:**
+  - Manage expense reporting sessions to track submissions and approvals.
+  - Maintain context for individual employee expenses and budget limits.
+
+- **Tasks:**
+  - Create tasks for expense submission, approval workflows, and reimbursement processing.
+  - Automate validation checks and compliance with policies.
+
+- **Executions:**
+  - Execute expense reporting tasks based on submission triggers and approval workflows.
+  - Monitor executions to ensure timely reimbursements and policy adherence.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires integration with financial systems, implementing approval workflows, and ensuring compliance with expense policies.
+
+---
+
+### 37. Automated Meeting Minutes Recorder
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store meeting agendas, transcription templates, and summary guidelines.
+  - Integrate with audio transcription services (e.g., Otter.ai, Google Speech-to-Text).
+
+- **Sessions:**
+  - Create meeting-specific sessions to track transcription and summarization progress.
+  - Maintain context for meeting topics and participant interactions.
+
+- **Tasks:**
+  - Define tasks for audio ingestion, transcription, summary generation, and distribution.
+  - Automate the extraction of action items and key decisions.
+
+- **Executions:**
+  - Execute transcription and summarization tasks in real-time or post-meeting.
+  - Monitor executions to ensure accurate recordings and timely distribution.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires reliable audio transcription integration and effective summarization techniques, but manageable with clear task definitions.
+
+---
+
+### 38. AI-Driven Content Recommendation System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store user profiles, content metadata, and recommendation algorithms.
+  - Integrate with content management systems and user behavior analytics.
+
+- **Sessions:**
+  - Manage user-specific sessions to track interactions and preference changes.
+  - Maintain context for personalized content delivery.
+
+- **Tasks:**
+  - Define tasks for content analysis, user behavior tracking, and recommendation generation.
+  - Automate personalization based on real-time user interactions.
+
+- **Executions:**
+  - Execute content recommendation tasks in real-time.
+  - Monitor executions to refine recommendation accuracy and relevance.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves real-time data processing, advanced recommendation algorithms, and integration with multiple content sources.
+
+---
+
+### 39. Smart Time Tracking Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store time tracking templates, productivity guidelines, and reporting formats.
+  - Integrate with productivity tools (e.g., Toggl, Clockify).
+
+- **Sessions:**
+  - Create user-specific sessions to track time spent on tasks and projects.
+  - Maintain context for task prioritization and productivity goals.
+
+- **Tasks:**
+  - Define tasks for time logging, productivity analysis, and report generation.
+  - Automate reminders for time tracking and productivity tips based on usage patterns.
+
+- **Executions:**
+  - Execute time tracking tasks continuously or based on user actions.
+  - Monitor executions to provide real-time productivity insights and suggestions.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with time tracking tools and implementing effective productivity analysis logic.
+
+---
+
+### 40. Automated Webinar Hosting Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store webinar schedules, registration forms, and hosting guidelines.
+  - Integrate with webinar platforms (e.g., Zoom, WebinarJam).
+
+- **Sessions:**
+  - Manage webinar-specific sessions to track registrations, attendee interactions, and follow-ups.
+  - Maintain context for webinar topics and participant engagement.
+
+- **Tasks:**
+  - Create tasks for webinar scheduling, participant management, live interactions, and post-webinar follow-ups.
+  - Automate reminders, thank-you emails, and feedback collection.
+
+- **Executions:**
+  - Execute webinar hosting tasks based on schedules and participant actions.
+  - Monitor executions to ensure smooth webinar operations and effective follow-ups.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves integration with webinar platforms, managing live interactions, and handling post-event processes seamlessly.
+
+---
+
+### 41. AI-Powered Inventory Forecasting Tool
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store sales data, forecasting models, and inventory guidelines.
+  - Integrate with sales and inventory tracking systems.
+
+- **Sessions:**
+  - Create forecasting sessions to track sales trends and inventory predictions.
+  - Maintain context for seasonal factors and market conditions affecting inventory.
+
+- **Tasks:**
+  - Define tasks for data collection, trend analysis, prediction model execution, and report generation.
+  - Automate alerts for predicted stock shortages or surpluses.
+
+- **Executions:**
+  - Execute forecasting tasks periodically based on sales data updates.
+  - Monitor executions to refine prediction accuracy and adjust inventory strategies.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires advanced predictive analytics, integration with sales systems, and handling dynamic market conditions influencing inventory.
+
+---
+
+### 42. Smart Contract Management System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store smart contract templates, execution guidelines, and compliance rules.
+  - Integrate with blockchain platforms (e.g., Ethereum, Hyperledger).
+
+- **Sessions:**
+  - Manage contract-specific sessions to track creation, execution, and monitoring.
+  - Maintain context for contract terms and participant interactions.
+
+- **Tasks:**
+  - Create tasks for contract creation, deployment, execution monitoring, and compliance checks.
+  - Automate notifications for contract milestones and compliance alerts.
+
+- **Executions:**
+  - Execute smart contract tasks based on blockchain events and predefined triggers.
+  - Monitor executions to ensure contract integrity and compliance.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Involves blockchain integration, ensuring smart contract security, and managing complex execution and compliance workflows.
+
+---
+
+### 43. Automated Knowledge Base Updater
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store knowledge base articles, update guidelines, and categorization rules.
+  - Integrate with content management systems and information sources.
+
+- **Sessions:**
+  - Create knowledge base sessions to track updates, revisions, and user queries.
+  - Maintain context for content accuracy and relevance.
+
+- **Tasks:**
+  - Define tasks for content ingestion, information extraction, categorization, and publishing.
+  - Automate periodic reviews and updates based on new information sources.
+
+- **Executions:**
+  - Execute knowledge base update tasks as new content becomes available.
+  - Monitor executions to ensure timely and accurate information updates.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires efficient content ingestion, accurate information extraction, and seamless integration with knowledge management systems.
+
+---
+
+### 44. AI-Driven Fraud Detection System
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store fraud detection algorithms, monitoring guidelines, and incident response protocols.
+  - Integrate with financial transaction systems and security APIs.
+
+- **Sessions:**
+  - Manage fraud detection sessions to track suspicious activities and investigations.
+  - Maintain context for user behavior patterns and anomaly detection.
+
+- **Tasks:**
+  - Create tasks for real-time transaction monitoring, anomaly detection, incident logging, and alerting.
+  - Automate response actions like freezing accounts or notifying security teams.
+
+- **Executions:**
+  - Execute fraud detection tasks continuously based on transaction flows.
+  - Monitor executions to ensure timely detection and response to fraudulent activities.
+
+**Complexity Rating:** ★★★★★
+
+**Explanation:** Involves real-time data processing, sophisticated anomaly detection algorithms, and ensuring robust security measures.
+
+---
+
+### 45. Intelligent Personal Diary Assistant
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store diary templates, emotional analysis guidelines, and reflection prompts.
+  - Integrate with sentiment analysis APIs.
+
+- **Sessions:**
+  - Create user-specific sessions to track daily entries and emotional states.
+  - Maintain context for personal growth and mood trends.
+
+- **Tasks:**
+  - Define tasks for daily entry prompts, sentiment analysis, and insight generation.
+  - Automate privacy controls and data encryption for secure diary storage.
+
+- **Executions:**
+  - Execute diary assistant tasks daily based on user inputs.
+  - Monitor executions to provide personalized insights and growth tracking.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Requires integration with sentiment analysis tools and ensuring secure data handling, but manageable with well-defined workflows.
+
+---
+
+### 46. Automated Language Learning Tutor
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store language lessons, exercise templates, and feedback guidelines.
+  - Integrate with language processing APIs and educational resources.
+
+- **Sessions:**
+  - Manage learning sessions to track user progress and performance.
+  - Maintain context for personalized lesson plans and feedback.
+
+- **Tasks:**
+  - Create tasks for lesson delivery, exercise generation, progress tracking, and feedback provision.
+  - Automate adaptive learning paths based on user performance.
+
+- **Executions:**
+  - Execute language learning tasks based on user interactions and learning schedules.
+  - Monitor executions to adjust learning strategies and provide real-time feedback.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves adaptive learning algorithms, integration with language processing tools, and personalized content delivery.
+
+---
+
+### 47. AI-Powered Budgeting Tool for Businesses
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store budgeting templates, financial guidelines, and reporting formats.
+  - Integrate with accounting systems and financial data sources.
+
+- **Sessions:**
+  - Create budgeting sessions to track financial planning and expenditure.
+  - Maintain context for organizational financial goals and constraints.
+
+- **Tasks:**
+  - Define tasks for budget creation, expenditure tracking, financial forecasting, and report generation.
+  - Automate alerts for budget overruns and financial goal assessments.
+
+- **Executions:**
+  - Execute budgeting tasks based on financial data updates and planning cycles.
+  - Monitor executions to ensure accurate financial tracking and reporting.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires integration with accounting systems, accurate financial forecasting, and robust budgeting logic to handle business complexities.
+
+---
+
+### 48. Smart Compliance Documentation Generator
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store compliance templates, regulatory guidelines, and documentation standards.
+  - Integrate with regulatory databases and internal policy systems.
+
+- **Sessions:**
+  - Manage compliance documentation sessions to track document creation and updates.
+  - Maintain context for specific regulatory requirements and organizational policies.
+
+- **Tasks:**
+  - Create tasks for document generation, compliance checking, format validation, and publishing.
+  - Automate updates based on regulatory changes and policy revisions.
+
+- **Executions:**
+  - Execute compliance documentation tasks as needed or on a schedule.
+  - Monitor executions to ensure documents meet all compliance standards.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Involves dynamic document generation, adherence to detailed regulatory standards, and ensuring continuous updates based on regulatory changes.
+
+---
+
+### 49. Automated Product Recommendation Engine
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store product catalogs, user behavior data, and recommendation algorithms.
+  - Integrate with e-commerce platforms and user analytics tools.
+
+- **Sessions:**
+  - Create user-specific sessions to track interactions and preferences.
+  - Maintain context for personalized recommendation accuracy.
+
+- **Tasks:**
+  - Define tasks for data collection, behavior analysis, recommendation generation, and user feedback integration.
+  - Automate real-time recommendations based on user actions and trends.
+
+- **Executions:**
+  - Execute recommendation tasks in real-time to provide instant suggestions.
+  - Monitor executions to refine algorithms and improve recommendation relevance.
+
+**Complexity Rating:** ★★★★☆
+
+**Explanation:** Requires sophisticated recommendation algorithms, real-time data processing, and continuous refinement based on user feedback.
+
+---
+
+### 50. Intelligent Event Feedback Analyzer
+
+**Implementation Using Julep:**
+
+- **Docs:**
+  - Store feedback forms, analysis templates, and reporting standards.
+  - Integrate with event platforms and feedback collection tools.
+
+- **Sessions:**
+  - Manage feedback-specific sessions to track responses and analysis progress.
+  - Maintain context for event-specific feedback and improvement areas.
+
+- **Tasks:**
+  - Create tasks for feedback collection, sentiment analysis, trend identification, and report generation.
+  - Automate the extraction of actionable insights and improvement suggestions.
+
+- **Executions:**
+  - Execute feedback analysis tasks post-event.
+  - Monitor executions to ensure accurate and timely feedback processing and reporting.
+
+**Complexity Rating:** ★★★☆☆
+
+**Explanation:** Involves integrating with feedback collection tools and implementing effective sentiment analysis and trend identification mechanisms.
+
+---
+
+# Complexity and Difficulty Ratings
+
+The scenarios have been rated based on the number of integrated features, required integrations, and overall system complexity. Here's a quick overview:
+
+- **★☆☆☆☆ (1/5): Easiest**
+- **★★☆☆☆ (2/5): Low Complexity**
+- **★★★☆☆ (3/5): Moderate Complexity**
+- **★★★★☆ (4/5): High Complexity**
+- **★★★★★ (5/5): Most Complex**
+
+| **Scenario**                                      | **Complexity Rating** |
+|---------------------------------------------------|-----------------------|
+| 1. Automated Customer Support Agent              | ★★★★☆                |
+| 2. Smart Research Assistant                       | ★★★★☆                |
+| 3. Personal Finance Manager                       | ★★★☆☆                |
+| 4. Content Creation Workflow                      | ★★★☆☆                |
+| 5. E-commerce Order Processing System             | ★★★★☆                |
+| 6. AI-Powered Personal Trainer                    | ★★★☆☆                |
+| 7. Automated Email Marketing Campaigns            | ★★★☆☆                |
+| 8. Intelligent Recruitment Assistant              | ★★★★★                |
+| 9. Smart Home Automation Controller               | ★★★★☆                |
+| 10. Automated Legal Document Analyzer             | ★★★★★                |
+| 11. Personalized Learning Assistant               | ★★★★☆                |
+| 12. AI-Driven Social Media Manager                | ★★★★☆                |
+| 13. Automated Travel Itinerary Planner            | ★★★☆☆                |
+| 14. AI-Powered Inventory Management System        | ★★★★☆                |
+| 15. Intelligent Health Monitoring System          | ★★★★☆                |
+| 16. Automated Content Moderation Tool             | ★★★★★                |
+| 17. AI-Powered Resume Builder                     | ★★★☆☆                |
+| 18. Smart Event Management System                 | ★★★★☆                |
+| 19. Automated Survey Analyzer                     | ★★★☆☆                |
+| 20. AI-Driven Project Management Assistant        | ★★★★☆                |
+| 21. Intelligent Document Summarizer               | ★★★★☆                |
+| 22. Automated Feedback Collection and Analysis    | ★★★☆☆                |
+| 23. AI-Powered Language Translator                | ★★★☆☆                |
+| 24. Smart Appointment Scheduler                   | ★★★☆☆                |
+| 25. Automated Inventory Auditor                   | ★★★★☆                |
+| 26. AI-Driven Competitive Analysis Tool           | ★★★★☆                |
+| 27. Smart Recipe Generator                        | ★★★☆☆                |
+| 28. Automated Video Content Creator               | ★★★★☆                |
+| 29. AI-Powered News Aggregator                    | ★★★☆☆                |
+| 30. Intelligent Appointment Follow-Up System      | ★★★☆☆                |
+| 31. Automated Compliance Monitoring Tool          | ★★★★★                |
+| 32. AI-Powered Personal Shopper                   | ★★★★☆                |
+| 33. Smart Content Personalization Engine          | ★★★★☆                |
+| 34. Automated Debt Collection Agent               | ★★★★☆                |
+| 35. AI-Driven Talent Matching System              | ★★★★★                |
+| 36. Intelligent Expense Reporting Tool            | ★★★★☆                |
+| 37. Automated Meeting Minutes Recorder            | ★★★☆☆                |
+| 38. AI-Driven Content Recommendation System       | ★★★★☆                |
+| 39. Smart Time Tracking Assistant                 | ★★★☆☆                |
+| 40. Automated Webinar Hosting Assistant           | ★★★★☆                |
+| 41. AI-Powered Inventory Forecasting Tool         | ★★★★☆                |
+| 42. Smart Contract Management System              | ★★★★★                |
+| 43. Automated Knowledge Base Updater              | ★★★★☆                |
+| 44. AI-Driven Fraud Detection System              | ★★★★★                |
+| 45. Intelligent Personal Diary Assistant          | ★★★☆☆                |
+| 46. Automated Language Learning Tutor             | ★★★★☆                |
+| 47. AI-Powered Budgeting Tool for Businesses      | ★★★★☆                |
+| 48. Smart Compliance Documentation Generator      | ★★★★☆                |
+| 49. Automated Product Recommendation Engine        | ★★★★☆                |
+| 50. Intelligent Event Feedback Analyzer           | ★★★☆☆                |
+
+---
+
+# Conclusion
+
+These 50 scenarios showcase the versatility and power of Julep's **docs**, **sessions**, **tasks**, and **executions** features in automating and enhancing various business and personal workflows. Depending on your specific needs and available integrations, these scenarios can be tailored to create efficient, intelligent, and scalable solutions.
+
+Feel free to explore these scenarios, adapt them to your use cases, and contribute to expanding Julep's capabilities further!
\ No newline at end of file
diff --git a/cookbooks/00-Devfest-Email-Assistant.ipynb b/cookbooks/00-Devfest-Email-Assistant.ipynb
new file mode 100644
index 000000000..d4d891cf6
--- /dev/null
+++ b/cookbooks/00-Devfest-Email-Assistant.ipynb
@@ -0,0 +1,296 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install julep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "import yaml\n",
+    "from julep import Julep\n",
+    "\n",
+    "api_key = os.getenv(\"JULEP_API_KEY\")\n",
+    "julep = Julep(api_key=api_key, environment=\"dev\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "agent = julep.agents.create(\n",
+    "    name=\"Julep Email Assistant\",\n",
+    "    about=(\n",
+    "        \"You are an agent that handles emails for julep users.\"\n",
+    "        + \" Julep is a platform for creating kick-ass AI agents.\"\n",
+    "    ),\n",
+    "    model=\"gpt-4o\",\n",
+    "    default_settings={\"temperature\": 0.2},\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2790657c-8378-4c5b-a60b-08b27e8ed7cf'"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "agent.id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mailgun_password = os.getenv(\"MAILGUN_PASSWORD\")\n",
+    "\n",
+    "task_def = yaml.safe_load(f\"\"\"\n",
+    "name: Julep Email Assistant\n",
+    "\n",
+    "input_schema:\n",
+    "  type: object\n",
+    "  properties:\n",
+    "    from:\n",
+    "      type: string\n",
+    "    to:\n",
+    "      type: string\n",
+    "    subject:\n",
+    "      type: string\n",
+    "    body:\n",
+    "      type: string\n",
+    "\n",
+    "tools:\n",
+    "- name: send_email\n",
+    "  integration:\n",
+    "    provider: email\n",
+    "    setup:\n",
+    "      host: smtp.mailgun.org\n",
+    "      password: {mailgun_password}\n",
+    "      port: 587\n",
+    "      user: postmaster@email.julep.ai\n",
+    "\n",
+    "- name: search_docs\n",
+    "  system:\n",
+    "    resource: agent\n",
+    "    subresource: doc\n",
+    "    operation: search\n",
+    "    \n",
+    "main:\n",
+    "- prompt: |-\n",
+    "    You are {{{{ agent.name }}}}. {{{{ agent.about }}}}\n",
+    "\n",
+    "    A user with email address {{{{ _.from }}}} has sent the following inquiry:\n",
+    "    ------\n",
+    "      Subject: {{{{ _.subject }}}}\n",
+    "\n",
+    "      {{{{ _.body }}}}\n",
+    "    ------\n",
+    "\n",
+    "    Can you generate a query to search the documentation based on this email?\n",
+    "    Just respond with the query as is and nothing else.\n",
+    "\n",
+    "  unwrap: true\n",
+    "\n",
+    "- tool: search_docs\n",
+    "  arguments:\n",
+    "    agent_id: \"'{agent.id}'\"\n",
+    "    text: _\n",
+    "    \n",
+    "- prompt: |-\n",
+    "    You are {{{{ agent.name }}}}. {{{{ agent.about }}}}\n",
+    "\n",
+    "    A user with email address {{{{ inputs[0].from }}}} has sent the following inquiry:\n",
+    "    ------\n",
+    "      Subject: {{{{ inputs[0].subject }}}}\n",
+    "\n",
+    "      {{{{ inputs[0].body }}}}\n",
+    "    ------\n",
+    "\n",
+    "    Here are some possibly relevant snippets from the julep documentation:\n",
+    "    {{% for doc in _.docs %}}\n",
+    "      {{% for snippet in doc.snippets %}}\n",
+    "        {{{{ snippet.content }}}}\n",
+    "      {{% endfor %}}\n",
+    "    {{% endfor %}}\n",
+    "    ========\n",
+    "\n",
+    "    Based on the above info, craft an email body to respond with as a json object.\n",
+    "    The json object must have `subject` and `body` fields.\n",
+    "  response_format:\n",
+    "    type: json_object\n",
+    "    \n",
+    "  unwrap: true\n",
+    "  \n",
+    "- evaluate:\n",
+    "    subject: \"load_json(_.split('```json')[1].split('```')[0])['subject']\"\n",
+    "    body: \"load_json(_.split('```json')[1].split('```')[0])['body']\"\n",
+    "    \n",
+    "- tool: send_email\n",
+    "  arguments:\n",
+    "    body: _.body\n",
+    "    from: \"'postmaster@email.julep.ai'\"\n",
+    "    subject: _.subject\n",
+    "    to: inputs[0].from\n",
+    "\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "task = julep.tasks.create(\n",
+    "    agent_id=agent.id,\n",
+    "    **task_def,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'614a7f59-6b43-4887-a6dd-1a75e5516025'"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "task.id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "execution = julep.executions.create(\n",
+    "    task_id=task.id,\n",
+    "    input={\"from\": \"diwank@julep.ai\", \"to\": \"help@agents.new\", \"subject\": \"what's up\", \"body\": \"sup\"},\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Execution(id='4205dda5-2afb-4f2f-8538-cbbf3e0c19f3', created_at=datetime.datetime(2024, 10, 7, 13, 1, 6, 431430, tzinfo=datetime.timezone.utc), input={'body': 'sup', 'from': 'diwank@julep.ai', 'subject': \"what's up\", 'to': 'help@agents.new'}, status='succeeded', task_id='614a7f59-6b43-4887-a6dd-1a75e5516025', updated_at=datetime.datetime(2024, 10, 7, 13, 1, 8, 518972, tzinfo=datetime.timezone.utc), error=None, metadata={}, output={'body': 'Hi there! How can I assist you today? If you have any questions or need help with Julep, feel free to let me know!', 'subject': 'Hello!'})"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "julep.executions.get(execution.id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[20], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mjulep\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecutions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtransitions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexecution_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mexecution\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/julep/resources/executions/transitions.py:127\u001b[0m, in \u001b[0;36mTransitionsResource.stream\u001b[0;34m(self, execution_id, next_page_token, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m    125\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m execution_id:\n\u001b[1;32m    126\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpected a non-empty value for `execution_id` but received \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mexecution_id\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 127\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    128\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/executions/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mexecution_id\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/transitions.stream\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    129\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    130\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    131\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    132\u001b[0m \u001b[43m        \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    133\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    134\u001b[0m \u001b[43m        \u001b[49m\u001b[43mquery\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    135\u001b[0m \u001b[43m            \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnext_page_token\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mnext_page_token\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtransition_stream_params\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTransitionStreamParams\u001b[49m\n\u001b[1;32m    136\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    137\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    138\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mobject\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    139\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/julep/_base_client.py:1200\u001b[0m, in \u001b[0;36mSyncAPIClient.get\u001b[0;34m(self, path, cast_to, options, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1197\u001b[0m opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mget\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions)\n\u001b[1;32m   1198\u001b[0m \u001b[38;5;66;03m# cast is required because mypy complains about returning Any even though\u001b[39;00m\n\u001b[1;32m   1199\u001b[0m \u001b[38;5;66;03m# it understands the type variables\u001b[39;00m\n\u001b[0;32m-> 1200\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/julep/_base_client.py:946\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    943\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    944\u001b[0m     retries_taken \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m--> 946\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    947\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    948\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    949\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    950\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    951\u001b[0m \u001b[43m    \u001b[49m\u001b[43mretries_taken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mretries_taken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    952\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/julep/_base_client.py:982\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, retries_taken, stream, stream_cls)\u001b[0m\n\u001b[1;32m    979\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSending HTTP Request: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, request\u001b[38;5;241m.\u001b[39mmethod, request\u001b[38;5;241m.\u001b[39murl)\n\u001b[1;32m    981\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 982\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    983\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    984\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_should_stream_response_body\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    985\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    986\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    987\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m httpx\u001b[38;5;241m.\u001b[39mTimeoutException \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m    988\u001b[0m     log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEncountered httpx.TimeoutException\u001b[39m\u001b[38;5;124m\"\u001b[39m, exc_info\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_client.py:940\u001b[0m, in \u001b[0;36mClient.send\u001b[0;34m(self, request, stream, auth, follow_redirects)\u001b[0m\n\u001b[1;32m    938\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m    939\u001b[0m     response\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m--> 940\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exc\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_client.py:934\u001b[0m, in \u001b[0;36mClient.send\u001b[0;34m(self, request, stream, auth, follow_redirects)\u001b[0m\n\u001b[1;32m    932\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    933\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m stream:\n\u001b[0;32m--> 934\u001b[0m         \u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    936\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m response\n\u001b[1;32m    938\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_models.py:815\u001b[0m, in \u001b[0;36mResponse.read\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    811\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    812\u001b[0m \u001b[38;5;124;03mRead and return the response content.\u001b[39;00m\n\u001b[1;32m    813\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    814\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_content\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m--> 815\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_content \u001b[38;5;241m=\u001b[39m \u001b[38;5;124;43mb\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miter_bytes\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    816\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_content\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_models.py:831\u001b[0m, in \u001b[0;36mResponse.iter_bytes\u001b[0;34m(self, chunk_size)\u001b[0m\n\u001b[1;32m    829\u001b[0m chunker \u001b[38;5;241m=\u001b[39m ByteChunker(chunk_size\u001b[38;5;241m=\u001b[39mchunk_size)\n\u001b[1;32m    830\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_request):\n\u001b[0;32m--> 831\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mraw_bytes\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miter_raw\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    832\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdecoded\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdecoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mraw_bytes\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    833\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdecoded\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_models.py:885\u001b[0m, in \u001b[0;36mResponse.iter_raw\u001b[0;34m(self, chunk_size)\u001b[0m\n\u001b[1;32m    882\u001b[0m chunker \u001b[38;5;241m=\u001b[39m ByteChunker(chunk_size\u001b[38;5;241m=\u001b[39mchunk_size)\n\u001b[1;32m    884\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_request):\n\u001b[0;32m--> 885\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mraw_stream_bytes\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    886\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_num_bytes_downloaded\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mraw_stream_bytes\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    887\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mraw_stream_bytes\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_client.py:127\u001b[0m, in \u001b[0;36mBoundSyncStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__iter__\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mIterator[\u001b[38;5;28mbytes\u001b[39m]:\n\u001b[0;32m--> 127\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_stream\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    128\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpx/_transports/default.py:116\u001b[0m, in \u001b[0;36mResponseStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    114\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__iter__\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mIterator[\u001b[38;5;28mbytes\u001b[39m]:\n\u001b[1;32m    115\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m map_httpcore_exceptions():\n\u001b[0;32m--> 116\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpart\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_httpcore_stream\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpart\u001b[49m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/connection_pool.py:367\u001b[0m, in \u001b[0;36mPoolByteStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    365\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m    366\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m--> 367\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exc \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/connection_pool.py:363\u001b[0m, in \u001b[0;36mPoolByteStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    361\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__iter__\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[\u001b[38;5;28mbytes\u001b[39m]:\n\u001b[1;32m    362\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 363\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpart\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_stream\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    364\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpart\u001b[49m\n\u001b[1;32m    365\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/http11.py:349\u001b[0m, in \u001b[0;36mHTTP11ConnectionByteStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    347\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ShieldCancellation():\n\u001b[1;32m    348\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m--> 349\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/http11.py:341\u001b[0m, in \u001b[0;36mHTTP11ConnectionByteStream.__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    339\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    340\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m Trace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreceive_response_body\u001b[39m\u001b[38;5;124m\"\u001b[39m, logger, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_request, kwargs):\n\u001b[0;32m--> 341\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_connection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_receive_response_body\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m    342\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\n\u001b[1;32m    343\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m    344\u001b[0m     \u001b[38;5;66;03m# If we get an exception while streaming the response,\u001b[39;00m\n\u001b[1;32m    345\u001b[0m     \u001b[38;5;66;03m# we want to close the response (and possibly the connection)\u001b[39;00m\n\u001b[1;32m    346\u001b[0m     \u001b[38;5;66;03m# before raising that exception.\u001b[39;00m\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/http11.py:210\u001b[0m, in \u001b[0;36mHTTP11Connection._receive_response_body\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m    207\u001b[0m timeout \u001b[38;5;241m=\u001b[39m timeouts\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m    209\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m--> 210\u001b[0m     event \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_receive_event\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    211\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(event, h11\u001b[38;5;241m.\u001b[39mData):\n\u001b[1;32m    212\u001b[0m         \u001b[38;5;28;01myield\u001b[39;00m \u001b[38;5;28mbytes\u001b[39m(event\u001b[38;5;241m.\u001b[39mdata)\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_sync/http11.py:224\u001b[0m, in \u001b[0;36mHTTP11Connection._receive_event\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    221\u001b[0m     event \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_h11_state\u001b[38;5;241m.\u001b[39mnext_event()\n\u001b[1;32m    223\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m event \u001b[38;5;129;01mis\u001b[39;00m h11\u001b[38;5;241m.\u001b[39mNEED_DATA:\n\u001b[0;32m--> 224\u001b[0m     data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_network_stream\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    225\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mREAD_NUM_BYTES\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\n\u001b[1;32m    226\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    228\u001b[0m     \u001b[38;5;66;03m# If we feed this case through h11 we'll raise an exception like:\u001b[39;00m\n\u001b[1;32m    229\u001b[0m     \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[1;32m    230\u001b[0m     \u001b[38;5;66;03m#     httpcore.RemoteProtocolError: can't handle event type\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    234\u001b[0m     \u001b[38;5;66;03m# perspective. Instead we handle this case distinctly and treat\u001b[39;00m\n\u001b[1;32m    235\u001b[0m     \u001b[38;5;66;03m# it as a ConnectError.\u001b[39;00m\n\u001b[1;32m    236\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m data \u001b[38;5;241m==\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_h11_state\u001b[38;5;241m.\u001b[39mtheir_state \u001b[38;5;241m==\u001b[39m h11\u001b[38;5;241m.\u001b[39mSEND_RESPONSE:\n",
+      "File \u001b[0;32m~/github.com/julep-ai/julep/playground/.venv/lib/python3.12/site-packages/httpcore/_backends/sync.py:126\u001b[0m, in \u001b[0;36mSyncStream.read\u001b[0;34m(self, max_bytes, timeout)\u001b[0m\n\u001b[1;32m    124\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m map_exceptions(exc_map):\n\u001b[1;32m    125\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sock\u001b[38;5;241m.\u001b[39msettimeout(timeout)\n\u001b[0;32m--> 126\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmax_bytes\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/.asdf/installs/python/3.12.5/lib/python3.12/ssl.py:1233\u001b[0m, in \u001b[0;36mSSLSocket.recv\u001b[0;34m(self, buflen, flags)\u001b[0m\n\u001b[1;32m   1229\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m flags \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m   1230\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m   1231\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnon-zero flags not allowed in calls to recv() on \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m\n\u001b[1;32m   1232\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m)\n\u001b[0;32m-> 1233\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuflen\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1234\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1235\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mrecv(buflen, flags)\n",
+      "File \u001b[0;32m~/.asdf/installs/python/3.12.5/lib/python3.12/ssl.py:1106\u001b[0m, in \u001b[0;36mSSLSocket.read\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m   1104\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;28mlen\u001b[39m, buffer)\n\u001b[1;32m   1105\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1106\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sslobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1107\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SSLError \u001b[38;5;28;01mas\u001b[39;00m x:\n\u001b[1;32m   1108\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39margs[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m==\u001b[39m SSL_ERROR_EOF \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msuppress_ragged_eofs:\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "# julep.executions.transitions.stream(execution_id=execution.id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}