Merge pull request #92 from crestalnetwork/feat/deepseek

Feat: deepseek

CHANGELOG.md

@@ -1,5 +1,21 @@
 # Changelog
 
+## 2025-01-25
+
+### New Features
+- DeepSeek LLM Support!
+- Enso skills now use CDP wallet
+- Add an API for frontend to link twitter account to an agent
+
+## 2025-01-24
+
+### Improvements
+- Refactor telegram services
+- Save telegram user info to db when it linked to an agent
+
+### Bug Fixes
+- Fix bug when twitter token refresh some skills will not work
+
 ## 2025-01-23
 
 ### Features

README.md

@@ -131,6 +131,10 @@ python -m app.autonomous
 
 "Create Agent" and "Try it out" refer to the Docker section.
 
+## The Model
+For now, we only support any model from OpenAI and DeepSeek.  
+We will support more models in the future.
+
 ## Integrations
 
 ### Twitter

app/config/config.py

@@ -79,6 +79,7 @@ def __init__(self):
         self.cdp_api_key_private_key = self.load("CDP_API_KEY_PRIVATE_KEY")
         # AI
         self.openai_api_key = self.load("OPENAI_API_KEY")
+        self.deepseek_api_key = self.load("DEEPSEEK_API_KEY")
         self.system_prompt = self.load("SYSTEM_PROMPT")
         # Autonomous
         # self.autonomous_entrypoint_interval = int(

app/core/engine.py

@@ -121,7 +121,15 @@ def initialize_agent(aid):
         raise HTTPException(status_code=500, detail=str(e))
 
     # ==== Initialize LLM.
-    llm = ChatOpenAI(model_name=agent.model, openai_api_key=config.openai_api_key)
+    # TODO: model name whitelist
+    if agent.model.startswith("deepseek"):
+        llm = ChatOpenAI(
+            model_name=agent.model,
+            openai_api_key=config.deepseek_api_key,
+            openai_api_base="https://api.deepseek.com",
+        )
+    else:
+        llm = ChatOpenAI(model_name=agent.model, openai_api_key=config.openai_api_key)
 
     # ==== Store buffered conversation history in memory.
     memory = PostgresSaver(get_coon())
@@ -258,8 +266,12 @@ def initialize_agent(aid):
         ("placeholder", "{messages}"),
     ]
     if twitter_prompt:
-        prompt_array.append(("system", twitter_prompt))
-    if agent.prompt_append:
+        # deepseek only supports system prompt in the beginning
+        if agent.model.startswith("deepseek"):
+            prompt_array.insert(0, ("system", twitter_prompt))
+        else:
+            prompt_array.append(("system", twitter_prompt))
+    if agent.prompt_append and not agent.model.startswith("deepseek"):
         # Escape any curly braces in prompt_append
         escaped_append = agent.prompt_append.replace("{", "{{").replace("}", "}}")
         prompt_array.append(("system", escaped_append))
@@ -269,6 +281,10 @@ 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":
+        tools = []
+
     # Create ReAct Agent using the LLM and CDP Agentkit tools.
     agents[aid] = create_agent(
         llm,

app/core/graph.py

@@ -261,6 +261,31 @@ class Agent,Tools otherClass
     def default_memory_manager(state: AgentState) -> AgentState:
         messages = state["messages"]
         # logger.debug("Before memory manager: %s", messages)
+
+        # Merge adjacent HumanMessages
+        i = 0
+        while i < len(messages) - 1:
+            if isinstance(messages[i], HumanMessage) and isinstance(
+                messages[i + 1], HumanMessage
+            ):
+                # Handle different content types
+                content1 = messages[i].content
+                content2 = messages[i + 1].content
+
+                # Convert to list if string
+                if isinstance(content1, str):
+                    content1 = [content1]
+                if isinstance(content2, str):
+                    content2 = [content2]
+
+                # Merge the contents
+                messages[i].content = content1 + content2
+
+                # Remove the second message
+                messages.pop(i + 1)
+            else:
+                i += 1
+
         if len(messages) <= 100:
             return state
         must_delete = len(messages) - 100

docs/create_agent.sh

@@ -17,6 +17,8 @@ AGENT_NAME="IntentKit"
 
 # AI model to use
 # https://platform.openai.com/docs/models#current-model-aliases
+# you can also use "deepseek-reasoner" and "deepseek-chat"
+# Notice: Currently, the deepseek-reasoner does not support any skills.
 MODEL="gpt-4o-mini"
 
 # Agent initial prompt (the role is system, daily user's role is user)

example.env

@@ -4,6 +4,8 @@ DEBUG_RESP=true
 
 OPENAI_API_KEY=
 
+DEEPSEEK_API_KEY=
+
 DB_HOST=
 DB_PORT=
 DB_USERNAME=

skills/cdp/tx.py

@@ -183,9 +183,7 @@ class CdpBroadcastEnsoTx(CdpBaseTool):
     """
 
     name: str = "cdp_broadcast_tx"
-    description: str = (
-        "This tool broadcasts transaction using the calldata transaction body generated by the EnsoGetRouteShortcut tool which will be passed to you by user as a confirmation."
-    )
+    description: str = "This tool broadcasts transaction using the calldata transaction body generated by the EnsoGetRouteShortcut tool which will be passed to you by user as a confirmation."
     args_schema: Type[BaseModel] = CdpBroadcastEnsoTxInput
 
     def _run(self, txRef: str) -> CdpBroadcastEnsoTxOutput: