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app-ea4all-sprint-5-apm-agentic-routing-fallback-self-correction-streaming-deploy-live-docker
Browse files- Dockerfile +2 -0
- README.md +7 -12
- requirements.txt +19 -17
Dockerfile
CHANGED
@@ -20,6 +20,8 @@ RUN --mount=type=secret,id=LANGCHAIN_API_KEY,mode=0444,required=true
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# HF private spaces token access
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RUN --mount=type=secret,id=HUGGINGFACEHUB_API_TOKEN,mode=0444,required=true \
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cat /run/secrets/HUGGINGFACEHUB_API_TOKEN > /home/user/cli_token
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RUN pip install -U "huggingface_hub[cli]"
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RUN git init & git config --global credential.helper store
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# HF private spaces token access
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RUN --mount=type=secret,id=HUGGINGFACEHUB_API_TOKEN,mode=0444,required=true \
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cat /run/secrets/HUGGINGFACEHUB_API_TOKEN > /home/user/cli_token
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# Azure BING Search AI API
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RUN --mount=type=secret,id=BING_SUBSCRIPTION_KEY,mode=0444,required=true
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RUN pip install -U "huggingface_hub[cli]"
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RUN git init & git config --global credential.helper store
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README.md
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`Trigger`: How disruptive may Generative AI be for Enterprise Architecture Capability (People, Process and Tools)? \n
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`Motivation`: Master GenAI while disrupting Enterprise Architecture to empower individuals and organisations with ability to harness EA value and make people lives better, safer and more efficient. \n
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`Ability`: Exploit my carrer background and skillset across
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> That's how the `EA4ALL-Agentic system` was born and ever since continuously evolving
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## Benefits
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## Knowledge context
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Synthetic
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### IT Landscape Question and Answering
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- Business capability
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- Business domain
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- Description
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- Bring Your Own Data: upload your own IT landscape data
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- Application Portfolio Management
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- xlsx tabular format
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- first row (header) with fields name (colums)
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### Architecture Diagram Visual Question and Answering
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- Llama
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- Hierarchical-Agent-Teams:
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- Tabular-question-answering
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- Supervisor
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- Visual Questions Answering
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- Diagram Component Analysis
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- Risk & Vulnerability and Mitigation options
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- Well-
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- Vision and Target Architecture
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- User Interface
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- Gradio
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- Hosting: Huggingface Space
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-
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## Agentic System Architecture
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`Trigger`: How disruptive may Generative AI be for Enterprise Architecture Capability (People, Process and Tools)? \n
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`Motivation`: Master GenAI while disrupting Enterprise Architecture to empower individuals and organisations with ability to harness EA value and make people lives better, safer and more efficient. \n
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`Ability`: Exploit my carrer background and skillset across system development, business accumen, innovation and architecture to accelerate GenAI exploration. \n\n
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> That's how the `EA4ALL-Agentic system` was born and ever since continuously evolving.
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## Benefits
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## Knowledge context
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Synthetic dataset is used to exemplify the Agentic System capabilities.
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### IT Landscape Question and Answering
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- Business capability
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- Business domain
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- Description
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### Architecture Diagram Visual Question and Answering
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- Llama
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- Hierarchical-Agent-Teams:
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- Tabular-question-and-answering
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- Supervisor
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- Visual Questions Answering
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- Diagram Component Analysis
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- Risk & Vulnerability and Mitigation options
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- Well-Architected Design Assessment
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- Vision and Target Reference Architecture
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- User Interface
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- Gradio
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- Hosting: Huggingface Space
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## Agentic System Architecture
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requirements.txt
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gradio==4.29.0
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pandas==2.2.2
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tiktoken
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langgraph
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langsmith
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graphviz
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langchain
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langchain-community
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langchain-core
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langchain-experimental
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langchain-openai
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langgraph
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langsmith
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openai
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faiss-cpu==1.8.0.post1
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gradio==4.29.0
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graphviz==0.20.3
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huggingface-hub==0.24.2
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jq==1.7.0
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langchain==0.2.11
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langchain-community==0.2.10
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langchain-core==0.2.23
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langchain-experimental==0.0.63
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langchain-huggingface==0.0.3
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langchain-openai==0.1.17
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langchain-text-splitters==0.2.2
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langchainhub==0.1.20
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langgraph==0.1.14
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langsmith==0.1.93
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openai==1.37.1
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openpyxl==3.1.5
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pandas==2.2.2
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pydantic==2.8.2
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pydantic_core==2.20.1
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tiktoken==0.7.0
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