AI Risk Advisor Prototype

Setup

Mix.install([
  {:resolvinator, path: "../"},
  {:kino, "~> 0.12"},
  {:httpoison, "~> 2.0"},
  {:jason, "~> 1.4"}
])

# Initialize Fabric AI client
fabric_key = System.get_env("FABRIC_KEY") || "your-key-here"

Risk Analysis Assistant

defmodule RiskAdvisor do
  @fabric_endpoint "https://api.fabric.microsoft.com/v1"

  def analyze_risk(risk_context) do
    prompt = """
    Given this risk context:
    #{risk_context}

    Please provide:
    1. Key risk factors and their implications
    2. Recommended mitigation strategies
    3. Similar historical cases and their outcomes
    4. Potential alternative approaches
    5. Implementation considerations
    """

    case query_fabric_ai(prompt) do
      {:ok, response} -> format_advice(response)
      {:error, reason} -> {:error, "Analysis failed: #{reason}"}
    end
  end

  def suggest_mitigations(risk_description) do
    prompt = """
    For this risk:
    #{risk_description}

    Suggest practical mitigation strategies, considering:
    - Resource constraints
    - Implementation timeline
    - Success metrics
    - Potential challenges
    """

    query_fabric_ai(prompt)
  end

  defp query_fabric_ai(prompt) do
    headers = [
      {"Authorization", "Bearer #{fabric_key}"},
      {"Content-Type", "application/json"}
    ]
    
    body = Jason.encode!(%{
      prompt: prompt,
      temperature: 0.7,
      max_tokens: 1000
    })
    
    case HTTPoison.post("#{@fabric_endpoint}/chat/completions", body, headers) do
      {:ok, %{status_code: 200, body: response}} ->
        {:ok, Jason.decode!(response)["choices"][0]["message"]["content"]}
      error ->
        {:error, "AI query failed: #{inspect(error)}"}
    end
  end

  defp format_advice(response) do
    Kino.Markdown.new(response)
  end
end

# Create interactive input for risk description
risk_input = Kino.Input.textarea("Describe the risk scenario:",
  default: """
  Project: E-commerce Platform Launch
  Risk Area: System Performance
  Context: Planning to launch new e-commerce platform during peak shopping season
  Concerns: System stability, user experience, revenue impact
  """
)

Get AI Recommendations

risk_context = Kino.Input.read(risk_input)
{:ok, analysis} = RiskAdvisor.analyze_risk(risk_context)

# Display formatted recommendations
analysis

Interactive Risk Discussion

defmodule RiskDiscussion do
  def ask_followup(context, question) do
    prompt = """
    Previous Context: #{context}
    
    Follow-up Question: #{question}
    
    Please provide a detailed response considering the full context.
    """
    
    RiskAdvisor.query_fabric_ai(prompt)
  end
end

# Create interactive follow-up question input
question_input = Kino.Input.text