suggestions simplify

Author: Adam Balogh

agent/agent_executors.py

@@ -19,7 +19,7 @@
 )
 GROK_MODEL = "x-ai/grok-2-1212"  # $2/M input tokens; $10/M output tokens
 
-SUGGESTIONS_MODEL = GOOGLE_GEMINI_20_FLASH_MODEL
+SUGGESTIONS_MODEL = GOOGLE_GEMINI_FLASH_15_8B_MODEL
 ROUTING_MODEL = GOOGLE_GEMINI_FLASH_15_8B_MODEL
 REASONING_MODEL = GROK_MODEL
 
@@ -35,23 +35,17 @@ def create_routing_model() -> ChatOpenAI:
     )
 
 
-def create_suggestions_executor() -> CompiledGraph:
-    openai_model = ChatOpenAI(
+def create_suggestions_model() -> ChatOpenAI:
+    return ChatOpenAI(
         model=SUGGESTIONS_MODEL,
         temperature=0.0,
         openai_api_base="https://openrouter.ai/api/v1",
         openai_api_key=os.getenv("OPENROUTER_API_KEY"),
         request_timeout=60,
-        max_tokens=100,
+        max_tokens=500,
         streaming=False,
         default_headers={"X-Title": "two-ligma"},
     )
-    agent_executor = create_react_agent(
-        model=openai_model,
-        tools=[],
-    )
-
-    return agent_executor
 
 
 def create_investor_executor() -> CompiledGraph:

agent/prompts.py

@@ -47,6 +47,7 @@ def get_investor_agent_prompt(
 
 
 def get_suggestions_prompt(
+    conversation_history: List[Message],
     tokens: List[WalletTokenHolding],
     tools: str,
 ) -> str:
@@ -68,6 +69,7 @@ def get_suggestions_prompt(
 
     agent_prompt = suggestions_template.render(
         tokens=token_metadata,
+        conversation_history=conversation_history,
         tools=tools,
     )
 

server/server.py

@@ -33,7 +33,7 @@
 )
 from agent.agent_executors import (
     create_investor_executor,
-    create_suggestions_executor,
+    create_suggestions_model,
     create_analytics_executor,
     create_routing_model,
 )
@@ -101,12 +101,11 @@ def create_flask_app() -> Flask:
     invite_manager = InviteCodeManager(invite_codes_table)
 
     # Initialize agents
-    suggestions_agent = create_suggestions_executor()
+    router_model = create_routing_model()
+    suggestions_model = create_suggestions_model()
     analytics_agent = create_analytics_executor()
     investor_agent = create_investor_executor()
 
-    router_model = create_routing_model()
-
     token_metadata_repo = TokenMetadataRepo(tokens_table)
     portfolio_fetcher = PortfolioFetcher(token_metadata_repo)
 
@@ -229,7 +228,7 @@ def run_suggestions():
         suggestions = handle_suggestions_request(
             request=agent_request,
             portfolio=portfolio,
-            suggestions_agent=suggestions_agent,
+            suggestions_model=suggestions_model,
         )
         return jsonify({"suggestions": suggestions})
 
@@ -435,43 +434,48 @@ def handle_investor_chat_request(
 def handle_suggestions_request(
     request: AgentChatRequest,
     portfolio: Portfolio,
-    suggestions_agent: CompiledGraph,
+    suggestions_model: ChatOpenAI,
 ) -> List[str]:
     # Get tools from agent config and format them
     tools = create_investor_agent_toolkit() + create_analytics_agent_toolkit()
     tools_list = "\n".join([f"- {tool.name}: {tool.description}" for tool in tools])
 
-    # Build suggestions agent system prompt
+    # Build suggestions system prompt
     suggestions_system_prompt = get_suggestions_prompt(
+        conversation_history=request.context.conversationHistory,
         tokens=portfolio.holdings,
         tools=tools_list,
     )
 
-    # Prepare message history (last 10 messages)
-    message_history = [
-        convert_to_agent_msg(m)
-        for m in request.context.conversationHistory[-NUM_MESSAGES_TO_KEEP:]
-    ]
+    # Run suggestions model directly
+    response = suggestions_model.invoke(suggestions_system_prompt)
+    content = response.content
 
-    # Create messages for suggestions agent
-    suggestions_messages = [
-        ("system", suggestions_system_prompt),
-        *message_history,
-    ]
-
-    # Create config for the agent
-    agent_config = RunnableConfig(
-        configurable={
-            "tokens": portfolio.holdings,
-        }
-    )
+    # Clean the content by removing markdown code block syntax if present
+    if content.startswith("```json"):
+        content = content[7:]  # Remove ```json
+    if content.endswith("```"):
+        content = content[:-3]  # Remove ```
+    content = content.strip()
 
-    # Run suggestions agent
-    suggestions = run_suggestions_agent(
-        suggestions_agent, suggestions_messages, agent_config
-    )
+    try:
+        # First try parsing as JSON
+        suggestions = json.loads(content)
+        if isinstance(suggestions, list):
+            return suggestions
+    except json.JSONDecodeError:
+        # If JSON parsing fails, try parsing as string array
+        try:
+            # Remove any JSON-like syntax and split by comma
+            cleaned = content.strip("[]")
+            # Split by comma and remove quotes
+            suggestions = [item.strip().strip("'\"") for item in cleaned.split(",")]
+            return suggestions
+        except Exception as e:
+            logger.error(f"Error parsing suggestions string: {e}")
+            return []
 
-    return suggestions
+    return []
 
 
 def run_main_agent(
@@ -510,43 +514,6 @@ def run_main_agent(
         }
 
 
-def run_suggestions_agent(
-    agent: CompiledGraph, messages: List, config: RunnableConfig
-) -> List[str]:
-    # Run agent directly
-    result = agent.invoke({"messages": messages}, config=config)
-
-    # Extract final message
-    last_message = result["messages"][-1]
-
-    # Clean the content by removing markdown code block syntax if present
-    content = last_message.content
-    if content.startswith("```json"):
-        content = content[7:]  # Remove ```json
-    if content.endswith("```"):
-        content = content[:-3]  # Remove ```
-    content = content.strip()
-
-    try:
-        # First try parsing as JSON
-        suggestions = json.loads(content)
-        if isinstance(suggestions, list):
-            return suggestions
-    except json.JSONDecodeError:
-        # If JSON parsing fails, try parsing as string array
-        try:
-            # Remove any JSON-like syntax and split by comma
-            cleaned = content.strip("[]")
-            # Split by comma and remove quotes
-            suggestions = [item.strip().strip("'\"") for item in cleaned.split(",")]
-            return suggestions
-        except Exception as e:
-            logger.error(f"Error parsing suggestions string: {e}")
-            return []
-
-    return []
-
-
 def convert_to_agent_msg(message: Message) -> Tuple[str, str]:
     if isinstance(message, UserMessage):
         return ("user", message.message)

templates/suggestions.jinja2

@@ -45,3 +45,6 @@ EXAMPLE RESPONSES:
 - After risk concern: ["Check max drawdown", "Portfolio volatility", "Compare Ethereum top pools", "Global TVL data"]
 
 User's Solana wallet tokens: {{ tokens }}
+
+Conversation history:
+{{ conversation_history }}