ea4all-empowering-you-with-enterprise-architecture-knowledge

Dockerfile

@@ -15,6 +15,9 @@ WORKDIR $HOME
 
 # Get secret OPENAI_API_KEY and clone it as repo at buildtime / changed required to true
 RUN --mount=type=secret,id=OPENAI_API_KEY,mode=0444,required=true
+# Langsmith tracing integration
+RUN --mount=type=secret,id=LANGCHAIN_API_KEY,mode=0444,required=true
+# HF private spaces token access
 RUN --mount=type=secret,id=HF_TOKEN,mode=0444,required=true \
     cat /run/secrets/HF_TOKEN > /home/user/cli_token
 
@@ -30,12 +33,5 @@ RUN git clone https://avfranco:$(cat cli_token)@huggingface.co/spaces/avfranco/e
 WORKDIR /home/user/ea4all-agent
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
-#RUN git clone https://huggingface.co/spaces/avfranco/ea4all-docker-demo
-#WORKDIR /home/user/ea4all-docker-demo
-#RUN pip install --no-cache-dir --upgrade -r requirements.txt
-
-# Clear the logs
-#RUN echo "" > $(docker inspect --format='{{.LogPath}}' ea4all-gradio-pnp)
-
 
 CMD ["python","app.py"]

README.md

@@ -1,11 +1,64 @@
 ---
-title: ea4all-architect-agent
-emoji: ⚡
-colorFrom: blue
-colorTo: red
+title: Talk to your IT landscape
+emoji: 👁
+colorFrom: purple
+colorTo: green
 sdk: docker
 pinned: false
 license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Title
+
+Empower you with access to the value of Enterprise Architecture Knowledge using my Generative AI abilities.
+        
+
+# My Name
+
+ea4all-agent-gpt, your Architect to talk about Enterprise landscape using your own language.
+
+## Overview
+
+What if you could interact with your enterprise architecture landscape using natural language, for example, ask what oppurtinities for simplification it may have. So, you would be able to identify initial options to a new business problem or assess impact of changes. That's not all, you would be able to understand what applications support a business capability or their roadmap, enhance the governance and assurance process to accelerate the solution architecture delivery, improve quality and increase collaboration.
+
+## Dataset
+
+Synthetic structured data with following colums: application, business fit, technical fit, business criticality, roadmap, architect, hosting, capability, domain, description
+
+## Bring you own data
+
+Upload a xlsx formate file with your own landscape data and start learning more
+
+## Architecture
+
+<italic>Core architecture built upon python, langchain, gradio and Openai.<italic>
+
+    - Python 3.11.3
+        - Pandas
+        - Langchain
+        - Langsmith
+
+    - RAG (Retrieval Augmented Generation)
+        - Vectorstore: Faiss (Facebook AI Similarity Search)
+
+    - Prompt Engineering
+        - Strategy & tactics: Task / Sub-tasks 
+
+    - Model: OpenAI GPT 3.5-turbo-1106
+    
+    - Task: tabular-question-answering over your own document
+    
+    - User Interface
+        - Gradio
+
+    - Hosting: Huggingface Space
+        - CPU basic
+        - 2vCPU 16GB RAM
+
+    - Deployment
+        - Docker spaces
+
+## Agent Architecture
+![Agent System Container](./ea4all/apm_architecture/ea4all_agent_container.png)
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference