README and Black formatter

README.md

@@ -734,8 +734,7 @@ rclpy.shutdown()
 
 </details>
 
-#### chat_llama_ros
-
+#### chat_llama_ros (Chat + LVM)
 <details>
 <summary>Click to expand</summary>
 
@@ -778,6 +777,73 @@ rclpy.shutdown()
 
 </details>
 
+#### 🎉 \*\*\*NEW*** chat_llama_ros (Tools) 🎉
+
+<details>
+<summary>Click to expand</summary>
+
+The current implementation of Tools allows executing tools without requiring a model trained for that task.
+
+```python
+
+import time
+
+import rclpy
+from rclpy.node import Node
+from llama_ros.langchain import ChatLlamaROS
+from langchain_core.messages import HumanMessage
+from langchain.tools import tool
+from random import randint
+
+rclpy.init()
+
+@tool
+def get_inhabitants(city: str) -> int:
+    """Get the current temperature of a city"""
+    return randint(4_000_000, 8_000_000)
+
+
+@tool
+def get_curr_temperature(city: str) -> int:
+    """Get the current temperature of a city"""
+    return randint(20, 30)
+
+chat = ChatLlamaROS(temp=0.6, penalty_last_n=8, use_llama_template=True)
+
+messages = [
+    HumanMessage(
+        "What is the current temperature in Madrid? And its inhabitants?"
+    )
+]
+
+llm_tools = self.chat.bind_tools(
+    [get_inhabitants, get_curr_temperature], tool_choice='any'
+)
+
+all_tools_res = llm_tools.invoke(messages)
+messages.append(all_tools_res)
+
+for tool in all_tools_res.tool_calls:
+    selected_tool = {
+        "get_inhabitants": get_inhabitants, "get_curr_temperature": get_curr_temperature
+    }[tool['name']]
+
+    tool_msg = selected_tool.invoke(tool)
+
+    formatted_output = f"{tool['name']}({''.join(tool['args'].values())}) = {tool_msg.content}"
+
+    tool_msg.additional_kwargs = {'args': tool['args']}
+    messages.append(tool_msg)
+
+res = self.chat.invoke(messages)
+
+print(f"Response: {res.content}")
+
+rclpy.shutdown()
+```
+
+</details>
+
 ## Demos
 
 ### LLM Demo
@@ -868,6 +934,20 @@ ros2 run llama_demos chatllama_demo_node
 
 [ChatLlamaROS demo](https://github-production-user-asset-6210df.s3.amazonaws.com/55236157/363094669-c6de124a-4e91-4479-99b6-685fecb0ac20.webm?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAVCODYLSA53PQK4ZA%2F20240830%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240830T081232Z&X-Amz-Expires=300&X-Amz-Signature=f937758f4bcbaec7683e46ddb057fb642dc86a33cc8c736fca3b5ce2bf06ddac&X-Amz-SignedHeaders=host&actor_id=55236157&key_id=0&repo_id=622137360)
 
+### Tools Demo
+
+```shell
+ros2 llama launch MiniCPM-2.6.yaml
+```
+
+```shell
+ros2 run llama_demos chatllama_tools_node
+```
+
+
+
+[Tools ChatLlama](https://github.com/user-attachments/assets/b912ee29-1466-4d6a-888b-9a2d9c16ae1d)
+
 #### Full Demo (LLM + chat template + RAG + Reranking + Stream)
 
 ```shell

llama_demos/llama_demos/chatllama_tools_node.py

@@ -29,7 +29,7 @@
 import rclpy
 from rclpy.node import Node
 from llama_ros.langchain import ChatLlamaROS
-from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage
 from langchain.tools import tool
 from random import randint
 
@@ -63,9 +63,11 @@ def send_prompt(self) -> None:
                 "What is the current temperature in Madrid? And its inhabitants?"
             )
         ]
+
+        self.get_logger().info(f"\nPrompt: {messages[0].content}")
 
         llm_tools = self.chat.bind_tools(
-            [get_inhabitants, get_curr_temperature], tool_choice='any'
+            [get_inhabitants, get_curr_temperature], tool_choice="any"
         )
 
         self.initial_time = time.time()
@@ -76,20 +78,32 @@ def send_prompt(self) -> None:
 
         for tool in all_tools_res.tool_calls:
             selected_tool = {
-                "get_inhabitants": get_inhabitants, "get_curr_temperature": get_curr_temperature
+                "get_inhabitants": get_inhabitants,
+                "get_curr_temperature": get_curr_temperature
             }[tool['name']]
+
             tool_msg = selected_tool.invoke(tool)
-            tool_msg.additional_kwargs = {'args': tool['args']}
+
+            formatted_output = f"{tool['name']}({''.join(tool['args'].values())}) = {tool_msg.content}"
+            self.get_logger().info(f'Calling tool: {formatted_output}')
+
+            tool_msg.additional_kwargs = {"args": tool["args"]}
             messages.append(tool_msg)
 
         res = self.chat.invoke(messages)
 
         self.eval_time = time.time()
 
-        self.get_logger().info(res.content)
+        self.get_logger().info(f"\nResponse: {res.content}")
 
-        self.get_logger().info(f"Time to generate tools: {self.tools_time - self.initial_time} s")
-        self.get_logger().info(f"Time to generate last response: {self.eval_time - self.tools_time} s")
+        time_generate_tools = self.tools_time - self.initial_time
+        time_last_response = self.eval_time - self.tools_time
+        self.get_logger().info(
+            f"Time to generate tools: {time_generate_tools:.2} s"
+        )
+        self.get_logger().info(
+            f"Time to generate last response: {time_last_response:.2} s"
+        )
 
 
 def main():

llama_ros/CMakeLists.txt

@@ -102,7 +102,6 @@ install(TARGETS
 )
 
 install(DIRECTORY
-  templates
   DESTINATION share/${PROJECT_NAME}
 )