Merge pull request #136 from crestalnetwork/feat/llm-creative

Feat: llm creative

app/core/engine.py

@@ -130,17 +130,20 @@ def initialize_agent(aid):
             model_name=agent.model,
             openai_api_key=config.deepseek_api_key,
             openai_api_base="https://api.deepseek.com",
-            presence_penalty=1,
-            streaming=False,
+            frequency_penalty=agent.frequency_penalty,
+            presence_penalty=agent.presence_penalty,
+            temperature=agent.temperature,
             timeout=90,
         )
         input_token_limit = 60000
     else:
         llm = ChatOpenAI(
             model_name=agent.model,
             openai_api_key=config.openai_api_key,
+            frequency_penalty=agent.frequency_penalty,
+            presence_penalty=agent.presence_penalty,
+            temperature=agent.temperature,
             timeout=60,
-            presence_penalty=1,
         )
 
     # ==== Store buffered conversation history in memory.
@@ -266,7 +269,8 @@ def initialize_agent(aid):
     if twitter_prompt:
         # deepseek only supports system prompt in the beginning
         if agent.model.startswith("deepseek"):
-            prompt_array.insert(0, ("system", twitter_prompt))
+            # prompt_array.insert(0, ("system", twitter_prompt))
+            pass
         else:
             prompt_array.append(("system", twitter_prompt))
     if agent.prompt_append:
@@ -282,8 +286,8 @@ def formatted_prompt(state: AgentState):
         # logger.debug(f"[{aid}] formatted prompt: {state}")
         return prompt_temp.invoke({"messages": state["messages"]})
 
-    # hack for deepseek
-    if agent.model == "deepseek-reasoner":
+    # hack for deepseek, it doesn't support tools
+    if agent.model.startswith("deepseek"):
         tools = []
 
     # Create ReAct Agent using the LLM and CDP Agentkit tools.

docs/create_agent.sh

@@ -21,6 +21,28 @@ AGENT_NAME="IntentKit"
 # Notice: Currently, the deepseek-reasoner does not support any skills.
 MODEL="gpt-4o-mini"
 
+# Agent temperature (0.0~2.0)
+# The randomness of the generated results is such that 
+# the higher the number, the more creative the results will be. 
+# However, this also makes them wilder and increases the likelihood of errors. 
+# For creative tasks, you can adjust it to above 1, but for rigorous tasks, 
+# such as quantitative trading, it’s advisable to set it lower, around 0.2.
+TEMPERATURE=0.7
+
+# Agent frequency penalty (-2.0~2.0)
+# The frequency penalty is a measure of how much the AI is allowed to repeat itself.
+# A lower value means the AI is more likely to repeat previous responses, 
+# while a higher value means the AI is more likely to generate new content.
+# For creative tasks, you can adjust it to 1 or a bit higher.
+FREQUENCY_PENALTY=0.0
+
+# Agent presence penalty (-2.0~2.0)
+# The presence penalty is a measure of how much the AI is allowed to deviate from the topic.
+# A higher value means the AI is more likely to deviate from the topic, 
+# while a lower value means the AI is more likely to follow the topic.
+# For creative tasks, you can adjust it to 1 or a bit higher.
+PRESENCE_PENALTY=0.0
+
 # Agent initial prompt (the role is system, daily user's role is user)
 read -r -d '' PROMPT_TEXT << 'END_OF_PROMPT'
 You are an autonomous AI agent.
@@ -98,6 +120,9 @@ JSON_DATA=$(cat << EOF
   "id": "$AGENT_ID",
   "name": "$AGENT_NAME",
   "model": "$MODEL",
+  "temperature": $TEMPERATURE,
+  "frequency_penalty": $FREQUENCY_PENALTY,
+  "presence_penalty": $PRESENCE_PENALTY,
   "prompt": "$PROMPT",
   "prompt_append": "$PROMPT_APPEND",
   "autonomous_enabled": $AUTONOMOUS_ENABLED,

models/agent.py

@@ -47,7 +47,15 @@ class Agent(SQLModel, table=True):
     )
     temperature: Optional[float] = Field(
         default=0.7,
-        description="AI model temperature parameter controlling response randomness (0.0-1.0)",
+        description="AI model temperature parameter controlling response randomness (0.0~1.0)",
+    )
+    frequency_penalty: Optional[float] = Field(
+        default=0.0,
+        description="Frequency penalty for the AI model, a higher value penalizes new tokens based on their existing frequency in the chat history (-2.0~2.0)",
+    )
+    presence_penalty: Optional[float] = Field(
+        default=0.0,
+        description="Presence penalty for the AI model, a higher value penalizes new tokens based on whether they appear in the chat history (-2.0~2.0)",
     )
     # autonomous mode
     autonomous_enabled: Optional[bool] = Field(

skills/enso/route.py

@@ -156,9 +156,7 @@ class EnsoRouteShortcut(EnsoBaseTool):
     """
 
     name: str = "enso_route_shortcut"
-    description: str = (
-        "This tool is used specifically for broadcasting a route transaction calldata to the network. It should only be used when the user explicitly requests to broadcast a route transaction with routeId."
-    )
+    description: str = "This tool is used specifically for broadcasting a route transaction calldata to the network. It should only be used when the user explicitly requests to broadcast a route transaction with routeId."
     args_schema: Type[BaseModel] = EnsoRouteShortcutInput
 
     def _run(

skills/enso/wallet.py

@@ -255,9 +255,7 @@ class EnsoBroadcastWalletApprove(EnsoBaseTool):
     """
 
     name: str = "enso_broadcast_wallet_approve"
-    description: str = (
-        "This tool is used specifically for broadcasting a ERC20 token spending approval transaction to the network. It should only be used when the user explicitly requests to broadcast an approval transaction with a specific amount for a certain token."
-    )
+    description: str = "This tool is used specifically for broadcasting a ERC20 token spending approval transaction to the network. It should only be used when the user explicitly requests to broadcast an approval transaction with a specific amount for a certain token."
     args_schema: Type[BaseModel] = EnsoBroadcastWalletApproveInput
     response_format: str = "content_and_artifact"