1  # Copy this into any ECHO agent to add session-based LLM consultation
  2  # Replace AGENT_NAME and :agent_role with your agent's details
  3  
  4  defmodule AGENT_NAME do
  5    use EchoShared.MCP.Server
  6  
  7    @impl true
  8    def agent_info do
  9      %{
 10        name: "agent-name",
 11        version: "1.0.0",
 12        role: :agent_role,  # ← Change this: :ceo, :cto, :chro, etc.
 13        llm_model: "model-name:version"
 14      }
 15    end
 16  
 17    @impl true
 18    def tools do
 19      [
 20        # ... your existing tools ...
 21  
 22        # ============================================================
 23        # NEW: Session-based AI consultation with conversation memory
 24        # ============================================================
 25        %{
 26          name: "session_consult",
 27          description: """
 28          Query the AI assistant with conversation memory (LocalCode-style).
 29  
 30          Maintains multi-turn conversations with automatic context injection:
 31          - Your role, responsibilities, and authority limits
 32          - Recent decisions and messages (last 5 each)
 33          - Current system status (PostgreSQL, Redis, Ollama)
 34          - Git context (branch, last commit)
 35          - Conversation history (last 5 turns)
 36  
 37          Perfect for:
 38          - Exploratory questions about your role
 39          - Decision analysis with iterative thinking
 40          - Strategy planning with follow-up questions
 41          - Learning from past decisions
 42  
 43          Example workflow:
 44          1. Ask: "What should I prioritize this quarter?"
 45          2. Follow-up: "Tell me more about priority #2"
 46          3. Deep dive: "What are the risks with that approach?"
 47          """,
 48          inputSchema: %{
 49            type: "object",
 50            properties: %{
 51              question: %{
 52                type: "string",
 53                description: "The question to ask the AI assistant",
 54                minLength: 1
 55              },
 56              session_id: %{
 57                type: "string",
 58                description: """
 59                Session ID to continue an existing conversation.
 60                Omit this field to start a new session.
 61                Session IDs look like: "ceo_1699564234_123456"
 62                """,
 63              },
 64              context: %{
 65                type: "string",
 66                description: """
 67                Additional context for this specific query.
 68                Example: "Budget: $5M, Timeline: Q1 2025, Team size: 50"
 69                """
 70              }
 71            },
 72            required: ["question"]
 73          }
 74        }
 75      ]
 76    end
 77  
 78    @impl true
 79    def execute_tool(tool_name, args) do
 80      case tool_name do
 81        # ... your existing tool handlers ...
 82  
 83        # ============================================================
 84        # NEW: Session consultation handler
 85        # ============================================================
 86        "session_consult" ->
 87          execute_session_consult(args)
 88  
 89        _ ->
 90          {:error, "Unknown tool: #{tool_name}"}
 91      end
 92    end
 93  
 94    # ============================================================
 95    # NEW: Session-based consultation implementation
 96    # ============================================================
 97  
 98    defp execute_session_consult(args) do
 99      alias EchoShared.LLM.DecisionHelper
100  
101      # Extract arguments
102      question = Map.fetch!(args, "question")
103      session_id = Map.get(args, "session_id")  # nil for new session
104      context = Map.get(args, "context")
105  
106      # Build options
107      opts = if context, do: [context: context], else: []
108  
109      # Query LLM with session memory
110      case DecisionHelper.consult_session(agent_role(), session_id, question, opts) do
111        {:ok, result} ->
112          # Format successful response
113          response = format_session_response(result)
114          {:ok, response}
115  
116        {:error, :llm_disabled} ->
117          {:error, "LLM is disabled for #{agent_role()}. Enable with LLM_ENABLED=true or #{agent_role() |> Atom.to_string() |> String.upcase()}_LLM_ENABLED=true"}
118  
119        {:error, :session_not_found} ->
120          {:error, "Session not found: #{session_id}. It may have expired after 1 hour of inactivity."}
121  
122        {:error, reason} ->
123          {:error, "AI consultation failed: #{inspect(reason)}"}
124      end
125    end
126  
127    defp format_session_response(result) do
128      # Get model info
129      model = EchoShared.LLM.Config.get_model(agent_role())
130  
131      # Base response
132      base = %{
133        response: result.response,
134        session_id: result.session_id,
135        turn_count: result.turn_count,
136        estimated_tokens: result.total_tokens,
137        model: model,
138        agent: agent_role()
139      }
140  
141      # Add warnings if context is getting large
142      if result.warnings != [] do
143        Map.put(base, :warnings, result.warnings)
144      else
145        base
146      end
147    end
148  
149    # ============================================================
150    # IMPORTANT: Set your agent role here!
151    # ============================================================
152    defp agent_role do
153      # Change this to match your agent:
154      :ceo                     # CEO agent
155      # :cto                   # CTO agent
156      # :chro                  # CHRO agent
157      # :operations_head       # Operations Head agent
158      # :product_manager       # Product Manager agent
159      # :senior_architect      # Senior Architect agent
160      # :uiux_engineer         # UI/UX Engineer agent
161      # :senior_developer      # Senior Developer agent
162      # :test_lead             # Test Lead agent
163    end
164  
165    # ... rest of your agent code ...
166  end
167  
168  # ============================================================
169  # USAGE EXAMPLES
170  # ============================================================
171  
172  # Example 1: Start new session
173  # {
174  #   "tool": "session_consult",
175  #   "arguments": {
176  #     "question": "What are my top priorities as CEO?"
177  #   }
178  # }
179  #
180  # Response:
181  # {
182  #   "response": "As CEO, your top priorities should be:\n1. Strategic planning...",
183  #   "session_id": "ceo_1699564234_123456",
184  #   "turn_count": 1,
185  #   "estimated_tokens": 1876,
186  #   "model": "llama3.1:8b",
187  #   "agent": "ceo"
188  # }
189  
190  # Example 2: Continue conversation
191  # {
192  #   "tool": "session_consult",
193  #   "arguments": {
194  #     "session_id": "ceo_1699564234_123456",
195  #     "question": "Tell me more about priority #2"
196  #   }
197  # }
198  #
199  # Response:
200  # {
201  #   "response": "Regarding strategic planning, you should focus on...",
202  #   "session_id": "ceo_1699564234_123456",
203  #   "turn_count": 2,
204  #   "estimated_tokens": 2341,
205  #   "model": "llama3.1:8b",
206  #   "agent": "ceo"
207  # }
208  
209  # Example 3: With additional context
210  # {
211  #   "tool": "session_consult",
212  #   "arguments": {
213  #     "question": "Should we approve this budget request?",
214  #     "context": "Budget: $2.5M for datacenter. Cash reserves: $10M."
215  #   }
216  # }
217  
218  # Example 4: Context warning (after 8-10 turns)
219  # {
220  #   "response": "Based on our discussion...",
221  #   "session_id": "ceo_1699564234_123456",
222  #   "turn_count": 9,
223  #   "estimated_tokens": 4523,
224  #   "model": "llama3.1:8b",
225  #   "agent": "ceo",
226  #   "warnings": [
227  #     "Session has 9 turns. Consider ending session soon.",
228  #     "Context size large (4523 tokens). Session approaching limit."
229  #   ]
230  # }
231  
232  # ============================================================
233  # TESTING
234  # ============================================================
235  
236  # Test in IEx:
237  # iex -S mix
238  # iex> alias EchoShared.LLM.DecisionHelper
239  # iex> {:ok, r1} = DecisionHelper.consult_session(:ceo, nil, "What's my role?")
240  # iex> IO.puts(r1.response)
241  # iex> {:ok, r2} = DecisionHelper.consult_session(:ceo, r1.session_id, "What are my priorities?")
242  # iex> IO.puts(r2.response)
243  
244  # ============================================================
245  # CONFIGURATION
246  # ============================================================
247  
248  # Models configured in apps/echo_shared/config/dev.exs:
249  # config :echo_shared, :agent_models, %{
250  #   ceo: "llama3.1:8b",
251  #   cto: "deepseek-coder:6.7b",
252  #   chro: "llama3.1:8b",
253  #   operations_head: "mistral:7b",
254  #   product_manager: "llama3.1:8b",
255  #   senior_architect: "deepseek-coder:6.7b",
256  #   uiux_engineer: "llama3.1:8b",
257  #   senior_developer: "deepseek-coder:6.7b",
258  #   test_lead: "deepseek-coder:6.7b"
259  # }
260  
261  # Override via environment:
262  # export CEO_MODEL=qwen2.5:14b
263  # export CEO_LLM_ENABLED=false