prompt changes, more robust hf token sending, banner

agent/main.py

@@ -71,7 +71,7 @@ async def event_listener(
 
             # Display event
             if event.event_type == "ready":
-                print(format_success("Agent ready"))
+                print(format_success("\U0001F917 Agent ready"))
                 ready_event.set()
             elif event.event_type == "assistant_message":
                 content = event.data.get("content", "") if event.data else ""
@@ -196,9 +196,21 @@ async def main():
     # Clear screen
     os.system('clear' if os.name != 'nt' else 'cls')
 
+
+    banner = r"""
+  _   _                   _               _____                   _                    _   
+ | | | |_   _  __ _  __ _(_)_ __   __ _  |  ___|_ _  ___ ___     / \   __ _  ___ _ __ | |_ 
+ | |_| | | | |/ _` |/ _` | | '_ \ / _` | | |_ / _` |/ __/ _ \   / _ \ / _` |/ _ \ '_ \| __|
+ |  _  | |_| | (_| | (_| | | | | | (_| | |  _| (_| | (_|  __/  / ___ \ (_| |  __/ | | | |_ 
+ |_| |_|\__,_|\__, |\__, |_|_| |_|\__, | |_|  \__,_|\___\___| /_/   \_\__, |\___|_| |_|\__|
+              |___/ |___/         |___/                               |___/
+    """
+
+
     print(format_separator())
-    print(f"{Colors.YELLOW}{Colors.BOLD}\U0001F917 Hugging Face Agent{Colors.RESET}")
+    print(f"{Colors.YELLOW} {banner}{Colors.RESET}")
     print("Type your messages below. Type 'exit', 'quit', or '/quit' to end.\n")
+    print(format_separator())
 
     # Create queues for communication
     submission_queue = asyncio.Queue()

agent/prompts/system_prompt.yaml

@@ -11,7 +11,7 @@ system_prompt: |
   # Autonomy / Subordinate trade-off.
 
   Your main goal is to achieve what the user asked. For this:
-  1. Take action, follow-up, launch jobs. Ask for as little action from the user as possible.
+  1. Take action, follow-up, launch jobs. Ask for as little action from the user as possible. Do not ask them to do things you could do via a script.
 
   However !! :
   1. Don't surprise the user with costly, irreversible, or strange actions without asking.
@@ -85,13 +85,16 @@ system_prompt: |
   # Conventions
 
   - Always search Hugging Face Hub for existing resources before suggesting custom implementations
+  - Keep in mind that a space is a repo, so you can create a space directly by uploading files that way. Repos should also be used to store files permanently : post-execution, files from jobs are not available.
+  - To run jobs, you must always pass the whole content of the file to execute. No files are available on server. Your local files and distant files are entirely seperate scopes.
+  - To access, create, or modify private Hub assets (spaces, private models, datasets, collections), pass `secrets: {% raw %}{{ "HF_TOKEN": "$HF_TOKEN" }}{% endraw %}` along with the jobs parameters. This is important. Without it, you will encounter authentification issues. Do not assume the user is connected on the jobs' server.
   - When referencing models, datasets, or papers, include direct links from search results
   - Never assume a library is available - check documentation first
   - Before processing any dataset: inspect its actual structure first using the mcp__hf-mcp-server__hub_repo_details tool. Never assume column names: verify them beforehand.
   - Follow ML best practices: proper train/val/test splits, reproducibility, evaluation metrics
   - Unless absolutely necessary, don't ask user for action. This does not apply to follow-up questions you have.
-  - For training tasks, consider compute requirements and suggest appropriate hardware
-  - Never expose or log API keys, tokens, or secrets
+  - For training tasks, consider compute requirements and choose appropriate hardware.
+  - Never expose or log API keys, tokens, or secrets. Do not assume keys or secrets are available. Only Hugging Face private resources are available.
 
   # Communication Style
 

agent/tools/jobs_tool.py

@@ -66,20 +66,21 @@ UV_DEFAULT_IMAGE = "ghcr.io/astral-sh/uv:python3.12-bookworm"
 
 def _substitute_hf_token(params: Dict[str, Any] | None) -> Dict[str, Any] | None:
     """
-    Substitute $HF_TOKEN with actual token value from environment.
+    Substitute HF_TOKEN key with actual token value from environment.
 
     Args:
-        params: Dictionary that may contain "$HF_TOKEN" in values
+        params: Dictionary that may contain "HF_TOKEN" as a key
 
     Returns:
-        Dictionary with $HF_TOKEN substituted
+        Dictionary with HF_TOKEN value substituted from environment
     """
+    print("DEBUG !! : ", params)
     if params is None:
         return None
 
     result = {}
     for key, value in params.items():
-        if value == "$HF_TOKEN":
+        if key == "HF_TOKEN":
             result[key] = os.environ.get("HF_TOKEN", "")
         else:
             result[key] = value
@@ -354,7 +355,8 @@ Call this tool with:
   "operation": "uv",
   "args": {{
     "script": "import random\\nprint(42 + random.randint(1, 5))",
-    "dependencies" : ["torch", "huggingface_hub"]
+    "dependencies": ["torch", "huggingface_hub"],
+    "secrets": {{"HF_TOKEN": "$HF_TOKEN"}}
   }}
 }}
 ```
@@ -384,7 +386,7 @@ Call this tool with:
 
 - Jobs default to non-detached mode (stream logs until completion). Set `detach: true` to return immediately.
 - Prefer array commands to avoid shell parsing surprises
-- To access private Hub assets (spaces, private models, datasets, collections), pass `secrets: {{ "HF_TOKEN": "$HF_TOKEN" }}`
+- To access, create, or modify private Hub assets (spaces, private models, datasets, collections), pass `secrets: {{ "HF_TOKEN": "$HF_TOKEN" }}`. This is important. Without it, you will encounter authentification issues. Do not assume the user is connected on the jobs' server.
 - Before calling a job, think about dependencies (they must be specified), which hardware flavor to run on (choose simplest for task), and whether to include secrets.
 """
         return {"formatted": usage_text, "totalResults": 1, "resultsShared": 1}

agent/tools/plan_tool.py

@@ -33,7 +33,7 @@ class PlanTool:
         for todo in todos:
             if not isinstance(todo, dict):
                 return {
-                    "formatted": "Error: Each todo must be an object",
+                    "formatted": "Error: Each todo must be an object. Re call the tool with correct format (mandatory).",
                     "isError": True,
                 }
 
@@ -41,7 +41,7 @@ class PlanTool:
             for field in required_fields:
                 if field not in todo:
                     return {
-                        "formatted": f"Error: Todo missing required field '{field}'",
+                        "formatted": f"Error: Todo missing required field '{field}'. Re call the tool with correct format (mandatory).",
                         "isError": True,
                     }
 
@@ -49,7 +49,7 @@ class PlanTool:
             valid_statuses = ["pending", "in_progress", "completed"]
             if todo["status"] not in valid_statuses:
                 return {
-                    "formatted": f"Error: Invalid status '{todo['status']}'. Must be one of: {', '.join(valid_statuses)}",
+                    "formatted": f"Error: Invalid status '{todo['status']}'. Must be one of: {', '.join(valid_statuses)}. Re call the tool with correct format (mandatory).",
                     "isError": True,
                 }