suggestion tools

Author: Adam Balogh

agent/agent_executors.py

@@ -10,7 +10,15 @@
 
 def create_suggestions_executor() -> CompiledGraph:
     openai_model = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.0)
-    agent_executor = create_react_agent(model=openai_model, tools=[])
+    
+    # Get all available tools from both toolkits
+    all_tools = create_agent_toolkit() + create_analytics_agent_toolkit()
+    
+    agent_executor = create_react_agent(
+        model=openai_model, 
+        tools=[],
+        config={"tools": all_tools}  # Pass raw tools list
+    )
 
     return agent_executor
 

agent/prompts.py

@@ -29,9 +29,11 @@ def get_agent_prompt(
 
 def get_suggestions_prompt(
     tokens: List[WalletTokenHolding],
+    tools: str,
 ) -> str:
     agent_prompt = suggestions_template.render(
         tokens=tokens,
+        tools=tools,
     )
 
     return agent_prompt

server/server.py

@@ -189,9 +189,14 @@ def handle_suggestions_request(
     request: AgentChatRequest,
     suggestions_agent: CompiledGraph,
 ) -> List[str]:
+    # Get tools from agent config and format them
+    tools = suggestions_agent.config["configurable"]["tools"]
+    tools_list = "\n".join([f"- {tool.name}: {tool.description}" for tool in tools])
+
     # Build suggestions agent system prompt
     suggestions_system_prompt = get_suggestions_prompt(
         tokens=request.context.tokens,
+        tools=tools_list,
     )
 
     # Prepare message history (last 10 messages)

templates/suggestions.jinja2

@@ -4,8 +4,7 @@ You are a context-aware suggestion system that helps guide users through their D
 - Tokens: {{ tokens }}
 
 2. Available Tools:
-- Yield Tools: Pool analysis, deposit guidance, risk assessment
-- Analytics Tools: Market trends, protocol metrics, portfolio analysis
+{{ tools }}
 
 Your goal is to provide exactly 2 relevant suggestions based on the current context.
 The suggestions will be displayed as buttons, so they MUST be short and action-oriented!
@@ -41,6 +40,8 @@ CRITICAL RULES:
 4. Keep suggestions natural and conversational
 5. For yield recommendations, prioritize suggestions that help users refine their risk/return preferences
 6. If the last message was a yield recommendation, focus on helping users narrow down their choice
+7. ONLY suggest actions that are supported by the available tools listed above
+8. NEVER suggest actions that would require tools not in the available tools list
 
 Always return your suggestions as an array. For example: ['suggestion_a', 'suggestion_b']
 ONLY RETURN THE ARRAY, NOTHING ELSE!