weni-ai/nexus-ai
Nov 2024 – Oct 2025
12 Months active
Languages Used
DRFDjangoJSONPythonSQLMarkdownShellYAML
Technical Skills
API DevelopmentAPI IntegrationBackend DevelopmentCode FormattingCode RefactoringConfiguration Management
Alisson
PROFILE
Alisson
Alisson Filipe engineered core backend systems for the weni-ai/nexus-ai repository, focusing on scalable agent orchestration, robust async task execution, and unified multi-backend AI workflows. He designed and refactored APIs, integrated AWS Bedrock and OpenAI backends, and implemented credential management, session handling, and observability features using Python, Django, and Celery. His work included building component-based messaging, structured response models, and secure authentication, while enhancing data integrity and reliability through database migrations and caching. By addressing complex integration, error handling, and configuration challenges, Alisson delivered maintainable, production-ready solutions that improved reliability, traceability, and business value across the platform.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
417Total
Bugs
73
Commits
417
Features
171
Lines of code
27,516
Activity Months12
Your Network
10 people
Work History
October 2025
16 Commits • 4 Features
Oct 1, 2025October 2025 Nexus AI monthly summary: Delivered cross-backend Bedrock/OpenAI capabilities, a component-based OpenAI messaging stack with FinalResponse, UI/config enhancements for OpenAISupervisor, and robust WhatsApp broadcast improvements, complemented by targeted bug fixes and infra refinements. The work emphasizes reliability, traceability, and business value through unified conversation handling, structured responses, multi-backend support, and improved configuration management.
16 Commits • 4 Features
Oct 1, 2025October 2025 Nexus AI monthly summary: Delivered cross-backend Bedrock/OpenAI capabilities, a component-based OpenAI messaging stack with FinalResponse, UI/config enhancements for OpenAISupervisor, and robust WhatsApp broadcast improvements, complemented by targeted bug fixes and infra refinements. The work emphasizes reliability, traceability, and business value through unified conversation handling, structured responses, multi-backend support, and improved configuration management.
October 2025
September 2025
63 Commits • 32 Features
Sep 1, 2025September 2025 (wen i-ai/nexus-ai)focused on stability, observability, and foundation-model readiness. Key backend refactors and feature work improved reliability, security, and data-driven decision-making, while enabling richer model management and observability. Notable progress includes end-to-end tracing with Langfuse, data-lake event metadata, and secure JWT-based auth; foundation-model support across Agent/Project with migrations and fallbacks; plus API and data-layer enhancements for improved data access and project-scoped filtering. Several targeted fixes and resilience improvements reduced risk in production workflows.
September 2025
63 Commits • 32 Features
Sep 1, 2025September 2025 (wen i-ai/nexus-ai)focused on stability, observability, and foundation-model readiness. Key backend refactors and feature work improved reliability, security, and data-driven decision-making, while enabling richer model management and observability. Notable progress includes end-to-end tracing with Langfuse, data-lake event metadata, and secure JWT-based auth; foundation-model support across Agent/Project with migrations and fallbacks; plus API and data-layer enhancements for improved data access and project-scoped filtering. Several targeted fixes and resilience improvements reduced risk in production workflows.
August 2025
51 Commits • 23 Features
Aug 1, 2025August 2025 performance summary: Delivered extensive enhancements to OpenAI/Bedrock adapters, Supervisor tooling, guardrails, and session management, prioritizing reliability, scalability, and business value. Achievements include richer multi-agent orchestration, region-aware Lambda invocation, stronger data handling and governance, and end-to-end improvements across backends that reduce risk and accelerate feature delivery.
51 Commits • 23 Features
Aug 1, 2025August 2025 performance summary: Delivered extensive enhancements to OpenAI/Bedrock adapters, Supervisor tooling, guardrails, and session management, prioritizing reliability, scalability, and business value. Achievements include richer multi-agent orchestration, region-aware Lambda invocation, stronger data handling and governance, and end-to-end improvements across backends that reduce risk and accelerate feature delivery.
August 2025
July 2025
21 Commits • 9 Features
Jul 1, 2025Summary for 2025-07: Delivered a focused set of features and reliability improvements across Nexus AI to enhance data observability, privacy, and AI workflow integration. The work emphasizes business value through robust data handling, secure session management, and scalable back-end integrations, enabling faster feature delivery and improved user impact.
July 2025
21 Commits • 9 Features
Jul 1, 2025Summary for 2025-07: Delivered a focused set of features and reliability improvements across Nexus AI to enhance data observability, privacy, and AI workflow integration. The work emphasizes business value through robust data handling, secure session management, and scalable back-end integrations, enabling faster feature delivery and improved user impact.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Focused on strengthening the robustness and maintainability of asynchronous task execution in the nexus-ai component. Implemented a robust Async Task Execution Refactor by replacing inline agent calls with apply_async using keyword arguments, enabling explicit queue management, better error isolation, and clearer task lifecycle. The change reduces coupling, improves observability, and provides a solid foundation for future queue strategies and scaling.
1 Commits • 1 Features
Jun 1, 2025June 2025: Focused on strengthening the robustness and maintainability of asynchronous task execution in the nexus-ai component. Implemented a robust Async Task Execution Refactor by replacing inline agent calls with apply_async using keyword arguments, enabling explicit queue management, better error isolation, and clearer task lifecycle. The change reduces coupling, improves observability, and provides a solid foundation for future queue strategies and scaling.
June 2025
May 2025
34 Commits • 18 Features
May 1, 2025May 2025 monthly summary for weni-ai/nexus-ai: Delivered robust credential management improvements, prompt handling enhancements, message model caching, and admin/security guardrails, plus early groundwork for reports and migrations to support scale. These changes directly improve data integrity, reliability, and business value by ensuring correct credential lifecycle, faster and more accurate prompt processing, quicker groundedness checks, safer admin operations, and better reporting capabilities.
May 2025
34 Commits • 18 Features
May 1, 2025May 2025 monthly summary for weni-ai/nexus-ai: Delivered robust credential management improvements, prompt handling enhancements, message model caching, and admin/security guardrails, plus early groundwork for reports and migrations to support scale. These changes directly improve data integrity, reliability, and business value by ensuring correct credential lifecycle, faster and more accurate prompt processing, quicker groundedness checks, safer admin operations, and better reporting capabilities.
April 2025
74 Commits • 34 Features
Apr 1, 2025April 2025 monthly highlights for weni-ai/nexus-ai: Key features delivered: - TRACE_SUMMARY_DELAY: Added TRACE_SUMMARY_DELAY setting and conditional delay in get_trace_summary to support latency tuning in production workloads. - Inline Agents architecture: Introduced and extended models (Guardrail, Agent, IntegratedAgent, Version) with migrations, added current_version support, and linked IntegratedAgent to Project; removed Team model to streamline data model and relationships. - PushAgents API and CreateAgent use case: Implemented agent creation flow and skill management API for scalable agent onboarding. - Inline Agents API and credentials: Implemented endpoints and use cases for assignment/retrieval; introduced AgentCredential and ContactField models; enhanced credential handling in CreateAgentUseCase. - CreateAgentUseCase robustness and API changes: Refactored to simplify instantiation, defensively access fields, updated signatures, and improved credential/instruction/guardrail handling. - Infrastructure and environment: Updated Dockerfile dependencies, staging migrations, and improved Bedrock backend/front-end integration; added temporary/staging migrations for ongoing work. - Agent discovery and data quality: Refined agent search views to use consistent name/skill filters and exposed detailed credentials via serializer for operational visibility. - Misc enhancements: Numerous refinements across ORM repositories, project components, and prompt/configuration management to improve developer productivity and reliability. Major bugs fixed: - Resolved circular import issues affecting module initialization. - Fixed agent skill name handling and CreateAgentUseCase references to prevent KeyError and ensure correct skill association. - Fixed get_instruction flow, credential checks, and deletion guards to prevent runtime errors and data inconsistencies. - Fixed parameter passing, API surface stability, and improved error handling in Bedrock components and ToolsUseCase. Overall impact and accomplishments: - Delivered a scalable, feature-rich inline agents framework with robust credential management, enabling faster agent onboarding, secure interactions, and more accurate instruction processing. - Strengthened reliability across the backend (ORM, API, and infrastructure) and improved deployment readiness with staging migrations and environment updates. - Enhanced business value through streamlined agent creation, better discovery/search capabilities, and clearer data modeling, positioning Nexus AI for larger-scale deployments. Technologies/skills demonstrated: - Python, ORM migrations, API design and versioning, and data modeling for complex agent/org structures. - Backend engineering: Bedrock integration, error handling, logging improvements, and modular architecture. - Credential management and encryption considerations for secure agent data. - Refactoring, performance-oriented fixes, and maintainability improvements across multiple components.
74 Commits • 34 Features
Apr 1, 2025April 2025 monthly highlights for weni-ai/nexus-ai: Key features delivered: - TRACE_SUMMARY_DELAY: Added TRACE_SUMMARY_DELAY setting and conditional delay in get_trace_summary to support latency tuning in production workloads. - Inline Agents architecture: Introduced and extended models (Guardrail, Agent, IntegratedAgent, Version) with migrations, added current_version support, and linked IntegratedAgent to Project; removed Team model to streamline data model and relationships. - PushAgents API and CreateAgent use case: Implemented agent creation flow and skill management API for scalable agent onboarding. - Inline Agents API and credentials: Implemented endpoints and use cases for assignment/retrieval; introduced AgentCredential and ContactField models; enhanced credential handling in CreateAgentUseCase. - CreateAgentUseCase robustness and API changes: Refactored to simplify instantiation, defensively access fields, updated signatures, and improved credential/instruction/guardrail handling. - Infrastructure and environment: Updated Dockerfile dependencies, staging migrations, and improved Bedrock backend/front-end integration; added temporary/staging migrations for ongoing work. - Agent discovery and data quality: Refined agent search views to use consistent name/skill filters and exposed detailed credentials via serializer for operational visibility. - Misc enhancements: Numerous refinements across ORM repositories, project components, and prompt/configuration management to improve developer productivity and reliability. Major bugs fixed: - Resolved circular import issues affecting module initialization. - Fixed agent skill name handling and CreateAgentUseCase references to prevent KeyError and ensure correct skill association. - Fixed get_instruction flow, credential checks, and deletion guards to prevent runtime errors and data inconsistencies. - Fixed parameter passing, API surface stability, and improved error handling in Bedrock components and ToolsUseCase. Overall impact and accomplishments: - Delivered a scalable, feature-rich inline agents framework with robust credential management, enabling faster agent onboarding, secure interactions, and more accurate instruction processing. - Strengthened reliability across the backend (ORM, API, and infrastructure) and improved deployment readiness with staging migrations and environment updates. - Enhanced business value through streamlined agent creation, better discovery/search capabilities, and clearer data modeling, positioning Nexus AI for larger-scale deployments. Technologies/skills demonstrated: - Python, ORM migrations, API design and versioning, and data modeling for complex agent/org structures. - Backend engineering: Bedrock integration, error handling, logging improvements, and modular architecture. - Credential management and encryption considerations for secure agent data. - Refactoring, performance-oriented fixes, and maintainability improvements across multiple components.
April 2025
March 2025
32 Commits • 15 Features
Mar 1, 2025March 2025 Nexus AI monthly summary: Delivered a robust WhatsApp Broadcast workflow with API surface enhancements, improved data validation, and scalable multi-agent support, while laying groundwork for observability and guardrails. Highlights include: API surface and method improvements for WhatsApp broadcast (new parameters, signature extensions, endpoint path updates, and project UUID support); JSON parsing and input sanitization enhancements; targeted bug fixes addressing edge cases in the broadcast flow; multi-agent broadcasting enablement with configurable components and Bedrock guardrail configuration; improved tracing and data modeling with an AgentMessage model, trace event saving, AgentTracesView/serializers, and session-aware logging; migrations and configuration updates (database migrations, PROJECT_COMPONENTS) to support production readiness and future scale. Business value: higher reliability and consistency for WhatsApp campaigns, reduced payload/validation errors, and richer troubleshooting and observability across agents and teams. Technologies/skills demonstrated: API design and evolution, Python/Django, JSON validation and sanitization, logging and tracing, data modeling (AgentMessage, traces), and database migrations.
March 2025
32 Commits • 15 Features
Mar 1, 2025March 2025 Nexus AI monthly summary: Delivered a robust WhatsApp Broadcast workflow with API surface enhancements, improved data validation, and scalable multi-agent support, while laying groundwork for observability and guardrails. Highlights include: API surface and method improvements for WhatsApp broadcast (new parameters, signature extensions, endpoint path updates, and project UUID support); JSON parsing and input sanitization enhancements; targeted bug fixes addressing edge cases in the broadcast flow; multi-agent broadcasting enablement with configurable components and Bedrock guardrail configuration; improved tracing and data modeling with an AgentMessage model, trace event saving, AgentTracesView/serializers, and session-aware logging; migrations and configuration updates (database migrations, PROJECT_COMPONENTS) to support production readiness and future scale. Business value: higher reliability and consistency for WhatsApp campaigns, reduced payload/validation errors, and richer troubleshooting and observability across agents and teams. Technologies/skills demonstrated: API design and evolution, Python/Django, JSON validation and sanitization, logging and tracing, data modeling (AgentMessage, traces), and database migrations.
February 2025
31 Commits • 12 Features
Feb 1, 2025February 2025 for weni-ai/nexus-ai delivered architectural stabilization and multi-agent readiness, cloud/security improvements, reliability fixes, scalable storage, and deeper Bedrock/WeniGPT integration with robust time handling. Key outcomes include: a scalable agent lifecycle with a promoted single agent now acting as manager, a new is_multi_agent flag enabling multi-agent mode, updated AWS dependencies and a secure default Lambda execution role, strengthened credential/session handling to reduce duplication and errors, S3 multipart upload with save capability for large files, and refined Bedrock/WeniGPT workflows with Pendulum-based timezone handling. These changes reduce operational risk, improve throughput for large data, and enable faster, safer multi-agent deployments.
31 Commits • 12 Features
Feb 1, 2025February 2025 for weni-ai/nexus-ai delivered architectural stabilization and multi-agent readiness, cloud/security improvements, reliability fixes, scalable storage, and deeper Bedrock/WeniGPT integration with robust time handling. Key outcomes include: a scalable agent lifecycle with a promoted single agent now acting as manager, a new is_multi_agent flag enabling multi-agent mode, updated AWS dependencies and a secure default Lambda execution role, strengthened credential/session handling to reduce duplication and errors, S3 multipart upload with save capability for large files, and refined Bedrock/WeniGPT workflows with Pendulum-based timezone handling. These changes reduce operational risk, improve throughput for large data, and enable faster, safer multi-agent deployments.
February 2025
January 2025
32 Commits • 10 Features
Jan 1, 2025January 2025 — Summary: Key features delivered: - Prompt Validation Enhancement: strengthened token checks and validation logic with commits e925bf974c2726613487c70b92400d8d571e279f and e2d1228d9e156c6d977fcf2eb1d2f5fa9d63b213 - Agents System Core: app scaffold, models, endpoints and deployment steps (commits 5ed8223faf8fbb1163cb181e739bb00dae203067, d4e18783cb296bb9a50053c252999324242404b6, 54aa8c2392c92e715b8c699775c9d81d13ff4935, 0d71a9b96ca83a62276530866ad39635e7dbc052, 2c81cd05676b831250f5502e9a50590ebff9b8d5) - AWS Lambda and Foundation Models Integration: Lambda client and foundation models variables; added permissions and size validation; cleanup AWS vars (commits 1506e3277335e66e7944db4b3368c714ef483625, 04a7c75e578c8b3863b988708279aae6e083f72d, f2ef22770d23dc80727b458a5625b329814b0445, fd3955eff89e3df4a95034e3b6661a572bb94be5) - Model invocation capability: add the ability to invoke a model within agent orchestration (commit 771fc99a3d067a87bb4930ae9502e1a98c903294) - Agent versioning and governance: versioning support in supervisor (commit e1fdd8b3cfce98af12def534e6d47ddac5132de4) and agent creation/update use versions (commit b17e8c573f796d48652d1d1d90de79cbb3e54df3); Save functionality for persistence (commit 0750fda364f8c89a933d1736c2075e0d26dac492) - Bedrock Agent Helper scaffolding and other quality work: temporary bedrock_agent_helper.py (commit 5d85cd994632e37ca9b039a96783da8f8e23887d) and Code cleanup (7e2c8ce4ad02c5f40b863f0ae4625e19a877eddc, 8aa18675e978dbc7df2fd5457c76accde5dd5366) - Dependency update to 2.8.8: update to 2.8.8 (commit 831b61251d3675a79936b9d630928d479d35ae3e) - Code cleanup and quality: remove comment and YAML file (commits 7e2c8ce4ad02c5f40b863f0ae4625e19a877eddc, 8aa18675e978dbc7df2fd5457c76accde5dd5366) Major bugs fixed: - User permissions enforcement for agent creation (commit 776666b9eb2327d165c07639037eff712b170772) - Supervisor permission fix (commit 0b3c34168eba5a81b021860c58e2da6cfa94db98) - Update supervisor after collaborator changes (commit 62bb6d14a2c1305f8e1c326a4d40c9b2a3d5ca09) - Agent creation/update to use versions (commit b17e8c573f796d48652d1d1d90de79cbb3e54df3) - Delete agent version naming (commit 1b27710f2a67c1d52d71fd44049dc5dc2c2b2cfb) - Start multi agents function name fix (commit 294a7e6f470f38d2b4367ac9293dd86771a7fa5b) - Environment variable naming fix (commit 6b667b2b66f7673c48852fa4e521719142ff7ac7) - Project UUID handling fix (commit 822f019a671405e374ddfdac18ed76b4870346cc) - Guardrails and unassign agent fixes (commit df12d7ba30b091b20d410bcbb48d93bbf69ac0f9) - Update skills fix (commit 35f10b575d5ab3060d8600df82fbb9a1bea401ca) - Flake8 compliance fix (commit b3146dab5a7916537b0fcbd063f4442f0789a9d3) - Supervisor existence validation (commit faaab54a5ffd756743bfbeb49879171c18980c95) - Remove src (commit 83733ef1d3a3c55ae0feb2af2d65ac3a8cf8631f) - Agent Description Update (commit b3619dd214862eeafe5e4c8db22760c037efa391) Overall impact and accomplishments: - Enabled scalable, governance-enabled agent orchestration with stronger security and reliability; improved developer velocity; reduced risk via versioning and permission checks; improved maintainability via code quality improvements and cleanup. Technologies/skills demonstrated: - Python-based agent orchestration, AWS Lambda integration, foundation models, versioning, permissions, deployment scaffolding, linting and code quality practices, and ongoing maintenance.
January 2025
32 Commits • 10 Features
Jan 1, 2025January 2025 — Summary: Key features delivered: - Prompt Validation Enhancement: strengthened token checks and validation logic with commits e925bf974c2726613487c70b92400d8d571e279f and e2d1228d9e156c6d977fcf2eb1d2f5fa9d63b213 - Agents System Core: app scaffold, models, endpoints and deployment steps (commits 5ed8223faf8fbb1163cb181e739bb00dae203067, d4e18783cb296bb9a50053c252999324242404b6, 54aa8c2392c92e715b8c699775c9d81d13ff4935, 0d71a9b96ca83a62276530866ad39635e7dbc052, 2c81cd05676b831250f5502e9a50590ebff9b8d5) - AWS Lambda and Foundation Models Integration: Lambda client and foundation models variables; added permissions and size validation; cleanup AWS vars (commits 1506e3277335e66e7944db4b3368c714ef483625, 04a7c75e578c8b3863b988708279aae6e083f72d, f2ef22770d23dc80727b458a5625b329814b0445, fd3955eff89e3df4a95034e3b6661a572bb94be5) - Model invocation capability: add the ability to invoke a model within agent orchestration (commit 771fc99a3d067a87bb4930ae9502e1a98c903294) - Agent versioning and governance: versioning support in supervisor (commit e1fdd8b3cfce98af12def534e6d47ddac5132de4) and agent creation/update use versions (commit b17e8c573f796d48652d1d1d90de79cbb3e54df3); Save functionality for persistence (commit 0750fda364f8c89a933d1736c2075e0d26dac492) - Bedrock Agent Helper scaffolding and other quality work: temporary bedrock_agent_helper.py (commit 5d85cd994632e37ca9b039a96783da8f8e23887d) and Code cleanup (7e2c8ce4ad02c5f40b863f0ae4625e19a877eddc, 8aa18675e978dbc7df2fd5457c76accde5dd5366) - Dependency update to 2.8.8: update to 2.8.8 (commit 831b61251d3675a79936b9d630928d479d35ae3e) - Code cleanup and quality: remove comment and YAML file (commits 7e2c8ce4ad02c5f40b863f0ae4625e19a877eddc, 8aa18675e978dbc7df2fd5457c76accde5dd5366) Major bugs fixed: - User permissions enforcement for agent creation (commit 776666b9eb2327d165c07639037eff712b170772) - Supervisor permission fix (commit 0b3c34168eba5a81b021860c58e2da6cfa94db98) - Update supervisor after collaborator changes (commit 62bb6d14a2c1305f8e1c326a4d40c9b2a3d5ca09) - Agent creation/update to use versions (commit b17e8c573f796d48652d1d1d90de79cbb3e54df3) - Delete agent version naming (commit 1b27710f2a67c1d52d71fd44049dc5dc2c2b2cfb) - Start multi agents function name fix (commit 294a7e6f470f38d2b4367ac9293dd86771a7fa5b) - Environment variable naming fix (commit 6b667b2b66f7673c48852fa4e521719142ff7ac7) - Project UUID handling fix (commit 822f019a671405e374ddfdac18ed76b4870346cc) - Guardrails and unassign agent fixes (commit df12d7ba30b091b20d410bcbb48d93bbf69ac0f9) - Update skills fix (commit 35f10b575d5ab3060d8600df82fbb9a1bea401ca) - Flake8 compliance fix (commit b3146dab5a7916537b0fcbd063f4442f0789a9d3) - Supervisor existence validation (commit faaab54a5ffd756743bfbeb49879171c18980c95) - Remove src (commit 83733ef1d3a3c55ae0feb2af2d65ac3a8cf8631f) - Agent Description Update (commit b3619dd214862eeafe5e4c8db22760c037efa391) Overall impact and accomplishments: - Enabled scalable, governance-enabled agent orchestration with stronger security and reliability; improved developer velocity; reduced risk via versioning and permission checks; improved maintainability via code quality improvements and cleanup. Technologies/skills demonstrated: - Python-based agent orchestration, AWS Lambda integration, foundation models, versioning, permissions, deployment scaffolding, linting and code quality practices, and ongoing maintenance.
December 2024
29 Commits • 6 Features
Dec 1, 2024December 2024 monthly summary for weni-ai/nexus-ai: Delivered core async messaging with Django Channels, introduced zeroshot exception for structured error handling, and enhanced tagging via groundedness scores. Improved data quality by adding metrics filtering for accuracy and implemented preview-compatible Start route tasks. Flow orchestration advanced with task delay, parameterized simulation, and LLM integration hook, along with serializer updates. Achieved significant reliability improvements through targeted bug fixes (RetrieveMessageLogUseCase log_id handling, tagging tests), Flake8 cleanup, and ongoing maintenance (dependency bumps). Business impact includes more responsive behavior, better observability, and safer feature experimentation.
29 Commits • 6 Features
Dec 1, 2024December 2024 monthly summary for weni-ai/nexus-ai: Delivered core async messaging with Django Channels, introduced zeroshot exception for structured error handling, and enhanced tagging via groundedness scores. Improved data quality by adding metrics filtering for accuracy and implemented preview-compatible Start route tasks. Flow orchestration advanced with task delay, parameterized simulation, and LLM integration hook, along with serializer updates. Achieved significant reliability improvements through targeted bug fixes (RetrieveMessageLogUseCase log_id handling, tagging tests), Flake8 cleanup, and ongoing maintenance (dependency bumps). Business impact includes more responsive behavior, better observability, and safer feature experimentation.
December 2024
November 2024
33 Commits • 7 Features
Nov 1, 2024Concise monthly summary for weni-ai/nexus-ai (2024-11). Delivered substantive API enhancements, stability improvements, and platform capabilities that collectively improve reliability, data integrity, and business value. The work focused on expanding API capabilities, hardening data handling, and enabling new integrations that support downstream analytics and product features.
November 2024
33 Commits • 7 Features
Nov 1, 2024Concise monthly summary for weni-ai/nexus-ai (2024-11). Delivered substantive API enhancements, stability improvements, and platform capabilities that collectively improve reliability, data integrity, and business value. The work focused on expanding API capabilities, hardening data handling, and enabling new integrations that support downstream analytics and product features.
Activity
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Quality Metrics
Correctness86.6%
Maintainability87.4%
Architecture83.8%
Performance79.4%
AI Usage26.4%
Skills & Technologies
Programming Languages
CeleryDRFDjangoDockerfileJSONJavaScriptJinjaMarkdownPandasPendulum
Technical Skills
AI ConfigurationAI IntegrationAI Prompt EngineeringAI/MLAI/ML IntegrationAPI DesignAPI DevelopmentAPI IntegrationAPI InteractionAPI TestingASGIAWSAWS BedrockAWS IntegrationAWS Lambda
Repositories Contributed To
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