Upload folder using huggingface_hub

example_usage.py

@@ -28,36 +28,9 @@ from openenv.core.client_types import StepResult
 from openenv.core.env_server.mcp_types import CallToolAction, ListToolsAction
 
 from agent_world_model_env import AWMEnv, AWMObservation
+from agent_world_model_env.server.prompts import DEFAULT_SYSTEM_PROMPT
 
 
-SYSTEM_PROMPT = """\
-You are at a MCP environment. You need to call MCP tools to assist with the user query. \
-At each step, you can only call one function. You have already logged in, and your user id is 1 if required.
-
-You are provided with TWO functions:
-
-1. list_tools
-   - Description: List all available MCP tools for the current environment.
-   - Arguments: None
-
-2. call_tool
-   - Description: Call a MCP environment-specific tool
-   - Arguments:
-       - tool_name: str, required
-       - arguments: str, required, valid JSON string
-
-For each function call, return a json object within <tool_call></tool_call> XML tags:
-<tool_call>
-{"name": <function-name>, "arguments": <args-json-object>}
-</tool_call>
-
-Example:
-<tool_call>
-{"name": "call_tool", "arguments": {"tool_name": "get_weather", "arguments": "{\"city\": \"Beijing\"}"}}
-</tool_call>
-
-You should call list_tools first to discover available tools, then use call_tool to interact. \
-When you have enough information to answer, output the answer directly without any tool_call tags."""
 
 
 def parse_tool_call(content: str) -> dict | None:
@@ -179,7 +152,7 @@ async def main():
         )
 
         messages: list[dict] = [
-            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "system", "content": DEFAULT_SYSTEM_PROMPT},
             {"role": "user", "content": task_description},
         ]
 

server/prompts.py

@@ -0,0 +1,28 @@
+DEFAULT_SYSTEM_PROMPT = """\
+You are at a MCP environment. You need to call MCP tools to assist with the user query. \
+At each step, you can only call one function. You have already logged in, and your user id is 1 if required.
+
+You are provided with TWO functions:
+
+1. list_tools
+   - Description: List all available MCP tools for the current environment.
+   - Arguments: None
+
+2. call_tool
+   - Description: Call a MCP environment-specific tool
+   - Arguments:
+       - tool_name: str, required
+       - arguments: str, required, valid JSON string
+
+For each function call, return a json object within <tool_call></tool_call> XML tags:
+<tool_call>
+{"name": <function-name>, "arguments": <args-json-object>}
+</tool_call>
+
+Example:
+<tool_call>
+{"name": "call_tool", "arguments": {"tool_name": "get_weather", "arguments": "{\\"city\\": \\"Beijing\\"}"}}
+</tool_call>
+
+You should call list_tools first to discover available tools, then use call_tool to interact. \
+When you have enough information to answer, output the answer directly without any tool_call tags."""

server/web_agent.py

@@ -9,35 +9,7 @@ from typing import Any, AsyncIterator
 
 from openai import AsyncOpenAI
 
-
-DEFAULT_SYSTEM_PROMPT = """\
-You are at a MCP environment. You need to call MCP tools to assist with the user query. \
-At each step, you can only call one function. You have already logged in, and your user id is 1 if required.
-
-You are provided with TWO functions:
-
-1. list_tools
-   - Description: List all available MCP tools for the current environment.
-   - Arguments: None
-
-2. call_tool
-   - Description: Call a MCP environment-specific tool
-   - Arguments:
-       - tool_name: str, required
-       - arguments: str, required, valid JSON string
-
-For each function call, return a json object within <tool_call></tool_call> XML tags:
-<tool_call>
-{"name": <function-name>, "arguments": <args-json-object>}
-</tool_call>
-
-Example:
-<tool_call>
-{"name": "call_tool", "arguments": {"tool_name": "get_weather", "arguments": "{\\"city\\": \\"Beijing\\"}"}}
-</tool_call>
-
-You should call list_tools first to discover available tools, then use call_tool to interact. \
-When you have enough information to answer, output the answer directly without any tool_call tags."""
+from .prompts import DEFAULT_SYSTEM_PROMPT
 
 
 def parse_tool_call(content: str) -> dict | None:

server/web_ui.py

@@ -15,7 +15,8 @@ import gradio as gr
 from openenv.core.env_server.serialization import serialize_observation
 
 from .data_loader import AWMDataLoader
-from .web_agent import AwmAgent, DEFAULT_SYSTEM_PROMPT
+from .prompts import DEFAULT_SYSTEM_PROMPT
+from .web_agent import AwmAgent
 
 
 # Keep in sync with DEFAULT_REWARD_CONFIG in awm_environment.py.