Merge pull request #401 from solliancenet/jdh-docs

Documentation generation

README.md

@@ -17,34 +17,32 @@ Foundationa**LLM** deploys a secure, comprehensive and highly configurable copil
 
 ## What do WE mean by "copilot"
 
-It's a rapidly evolving AI world out there, so let's level set on what we mean when we say **copilot** as this is concept core to Foundationa**LLM**. 
+It's a rapidly evolving AI world out there, so let's level set on what we mean when we say **copilot** as this is concept core to Foundationa**LLM**.
 
-At its most basic, a copilot uses enterprise supplied knowledge and generative AI models to author text, write code or render images, often by reasoning over human supplied prompts. Across these modalities, the AI is used to assist a human directly with a specific task. That's what makes it a copilot.    
+At its most basic, a copilot uses enterprise supplied knowledge and generative AI models to author text, write code or render images, often by reasoning over human supplied prompts. Across these modalities, the AI is used to assist a human directly with a specific task. That's what makes it a copilot.
 
 This basic capability emerges in copilots which power these scenarios:
 
 - Knowledge Management: Help users quickly find the information they seek and deliver at the right level and in the right format. Examples include summarization, rephrasing or retargeting to address a persona (e.g., explain it like I'm five), sentiment analysis and recommendations.
-
 - Analytics: Help users quickly get to the data driven insights they seek. Examples include recommendations, predictions, anomaly detection, statistical analysis and data querying and reporting.
 
-
 ## Why is Foundationa**LLM** Needed?
 
 Simply put we saw lot of folks reinventing the wheel just to get a customized copilot that was grounded and bases its responses in their own data as opposed to the trained parametric knowledge of the model. Many of the solutions we saw made for great demos, but were effectively toys wrapping calls to OpenAI endpoints- they were not something intended or ready to take into production. We built Foundationa**LLM** to provide a continous journey, one that was quick to get started with so folks could experiment quickly with LLM's but not fall off a cliff after that with a solution that would be insecure, unlicensed, inflexible and not fully featured enough to grow from the prototype into a production solution without having to start all over.  
 
 The core problems to deliver enterprise copilots are:
+
 - Enterprise grade copilots are complex and have lots of moving parts (not to mention infrastructure).
 - The industry has a skills gap when it comes to filling the roles needed to deliver these complex copilot solutions.
-- The top AI risks (inaccuracy, cybersecurity, compliance, explainability, privacy) are not being mitigated. 
-- Delivery of a copilot solution is time consuming, expensive and frustrating. 
+- The top AI risks (inaccuracy, cybersecurity, compliance, explainability, privacy) are not being mitigated.
+- Delivery of a copilot solution is time consuming, expensive and frustrating.
 
 ## Getting Started
 
 FoundationalLLM provides a simple command line driven approach to getting your first deployment up and running. Basically, it's two commands. After that, you can customize the solution, run it locally on your machine and update the deployment with your customizations.
 
 Follow the [Starter Deployment instructions](./docs/deployment/deployment-starter.md) to get Foundationa**LLM** deployed in your Azure subscription.
 
-
 ## Contributing to FoundationaLLM
 
 We are happy to accept contributions to the FoundationaLLM project in the form of feedback, bug reports, and pull requests. Please see [Contributing to FoundationaLLM](./CONTRIBUTING.md) for instructions.

docs/.gitignore

@@ -0,0 +1,6 @@
+/**/DROP/
+/**/TEMP/
+/**/packages/
+/**/bin/
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+_site

docs/api/.gitignore

@@ -0,0 +1,2 @@
+*.yml
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docs/api/dotnet/index.md

@@ -0,0 +1,3 @@
+# .NET API
+
+Use the navigation on the left to browse the .NET API documentation.

docs/api/index.md

@@ -0,0 +1,6 @@
+# API documentation
+
+FoundationaLLM has both .NET and Python and Python APIs:
+
+- [.NET API](dotnet/index.md)
+- [Python API](python/index.md)

docs/api/python/index.md

@@ -0,0 +1,3 @@
+# Python API
+
+Use the navigation on the left to browse the Python API documentation.

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