Manipulation demo: Add streamlit interface (#337)

Signed-off-by: Kacper Dąbrowski <[email protected]>

Author: knicked

docs/demos/manipulation.md

@@ -50,7 +50,13 @@ This demo showcases the capabilities of RAI in performing manipulation tasks usi
    ros2 launch examples/manipulation-demo.launch.py game_launcher:=path/to/RAIManipulationDemo.GameLauncher
    ```
 
-2. In the second terminal, run the interactive prompt:
+2. In the second terminal, run the streamlit interface:
+
+   ```shell
+   streamlit run examples/manipulation-demo-streamlit.py
+   ```
+
+   Alternatively, you can run the simpler command-line version, which also serves as an example of how to use the RAI API for you own applications:
 
    ```shell
    python examples/manipulation-demo.py

examples/manipulation-demo-streamlit.py

@@ -0,0 +1,74 @@
+# Copyright (C) 2024 Robotec.AI
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language goveself.rning permissions and
+# limitations under the License.
+
+import importlib
+
+import streamlit as st
+from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+
+from rai.agents.integrations.streamlit import get_streamlit_cb, streamlit_invoke
+from rai.messages import HumanMultimodalMessage
+
+manipulation_demo = importlib.import_module("manipulation-demo")
+
+
+@st.cache_resource
+def initialize_graph():
+    return manipulation_demo.create_agent()
+
+
+def main():
+    st.set_page_config(
+        page_title="RAI Manipulation Demo",
+        page_icon=":robot:",
+    )
+    st.title("RAI Manipulation Demo")
+    st.markdown("---")
+
+    st.sidebar.header("Tool Calls History")
+
+    if "graph" not in st.session_state:
+        graph = initialize_graph()
+        st.session_state["graph"] = graph
+
+    if "messages" not in st.session_state:
+        st.session_state["messages"] = [
+            AIMessage(content="Hi! I am a robotic arm. What can I do for you?")
+        ]
+
+    prompt = st.chat_input()
+    for msg in st.session_state.messages:
+        if isinstance(msg, AIMessage):
+            if msg.content:
+                st.chat_message("assistant").write(msg.content)
+        elif isinstance(msg, HumanMultimodalMessage):
+            continue
+        elif isinstance(msg, HumanMessage):
+            st.chat_message("user").write(msg.content)
+        elif isinstance(msg, ToolMessage):
+            with st.sidebar.expander(f"Tool: {msg.name}", expanded=False):
+                st.code(msg.content, language="json")
+
+    if prompt:
+        st.session_state.messages.append(HumanMessage(content=prompt))
+        st.chat_message("user").write(prompt)
+        with st.chat_message("assistant"):
+            st_callback = get_streamlit_cb(st.container())
+            streamlit_invoke(
+                st.session_state["graph"], st.session_state.messages, [st_callback]
+            )
+
+
+if __name__ == "__main__":
+    main()

examples/manipulation-demo.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 import rclpy
+import rclpy.qos
 from langchain_core.messages import HumanMessage
 
 from rai.agents.conversational_agent import create_conversational_agent
@@ -21,45 +22,56 @@
 from rai.tools.ros.native import GetCameraImage, Ros2GetTopicsNamesAndTypesTool
 from rai.utils.model_initialization import get_llm_model
 
-rclpy.init()
-node = RaiBaseNode(node_name="manipulation_demo")
-node.declare_parameter("conversion_ratio", 1.0)
 
-tools = [
-    GetObjectPositionsTool(
-        node=node,
-        target_frame="panda_link0",
-        source_frame="RGBDCamera5",
-        camera_topic="/color_image5",
-        depth_topic="/depth_image5",
-        camera_info_topic="/color_camera_info5",
-    ),
-    MoveToPointTool(node=node, manipulator_frame="panda_link0"),
-    GetCameraImage(node=node),
-    Ros2GetTopicsNamesAndTypesTool(node=node),
-]
+def create_agent():
+    rclpy.init()
+    node = RaiBaseNode(node_name="manipulation_demo")
+    node.declare_parameter("conversion_ratio", 1.0)
+    node.qos_profile.reliability = rclpy.qos.ReliabilityPolicy.RELIABLE
 
-llm = get_llm_model(model_type="complex_model")
+    tools = [
+        GetObjectPositionsTool(
+            node=node,
+            target_frame="panda_link0",
+            source_frame="RGBDCamera5",
+            camera_topic="/color_image5",
+            depth_topic="/depth_image5",
+            camera_info_topic="/color_camera_info5",
+        ),
+        MoveToPointTool(node=node, manipulator_frame="panda_link0"),
+        GetCameraImage(node=node),
+        Ros2GetTopicsNamesAndTypesTool(node=node),
+    ]
 
-system_prompt = """
-You are a robotic arm with interfaces to detect and manipulate objects.
-Here are the coordinates information:
-x - front to back (positive is forward)
-y - left to right (positive is right)
-z - up to down (positive is up)
+    llm = get_llm_model(model_type="complex_model", streaming=True)
 
-Before starting the task, make sure to grab the camera image to understand the environment.
-"""
+    system_prompt = """
+    You are a robotic arm with interfaces to detect and manipulate objects.
+    Here are the coordinates information:
+    x - front to back (positive is forward)
+    y - left to right (positive is right)
+    z - up to down (positive is up)
 
-agent = create_conversational_agent(
-    llm=llm,
-    tools=tools,
-    system_prompt=system_prompt,
-)
+    Before starting the task, make sure to grab the camera image to understand the environment.
+    """
 
-messages = []
-while True:
-    prompt = input("Enter a prompt: ")
-    messages.append(HumanMessage(content=prompt))
-    output = agent.invoke({"messages": messages})
-    output["messages"][-1].pretty_print()
+    agent = create_conversational_agent(
+        llm=llm,
+        tools=tools,
+        system_prompt=system_prompt,
+    )
+    return agent
+
+
+def main():
+    agent = create_agent()
+    messages = []
+    while True:
+        prompt = input("Enter a prompt: ")
+        messages.append(HumanMessage(content=prompt))
+        output = agent.invoke({"messages": messages})
+        output["messages"][-1].pretty_print()
+
+
+if __name__ == "__main__":
+    main()