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https://github.com/NousResearch/hermes-agent.git
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skill/gith
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atropos-in
| Author | SHA1 | Date | |
|---|---|---|---|
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|
ae6435f787 |
@@ -73,6 +73,12 @@ class AgentResult:
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# Tool errors encountered during the loop
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tool_errors: List[ToolError] = field(default_factory=list)
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# Tool-call metrics (debugging / optional reward shaping)
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tool_calls_attempted: int = 0
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tool_calls_schema_valid: int = 0
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tool_calls_executed_ok: int = 0
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tool_calls_exec_error: int = 0
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def _extract_reasoning_from_message(message) -> Optional[str]:
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"""
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@@ -136,6 +142,8 @@ class HermesAgentLoop:
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temperature: float = 1.0,
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max_tokens: Optional[int] = None,
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extra_body: Optional[Dict[str, Any]] = None,
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tool_handler=None,
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max_context_tokens: Optional[int] = None,
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):
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"""
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Initialize the agent loop.
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@@ -152,6 +160,13 @@ class HermesAgentLoop:
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extra_body: Extra parameters passed to the OpenAI client's create() call.
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Used for OpenRouter provider preferences, transforms, etc.
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e.g. {"provider": {"ignore": ["DeepInfra"]}}
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tool_handler: Optional async callable(tool_name, args, task_id) -> str.
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When provided, used INSTEAD of handle_function_call() for
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tool dispatch. This allows sandbox backends (Modal, Nomad)
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to route tool calls through their slot-based execution.
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max_context_tokens: Maximum prompt tokens before truncation.
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If None, no truncation is applied.
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Recommended: set to max_model_len - max_tokens - 512 (safety margin).
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"""
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self.server = server
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self.tool_schemas = tool_schemas
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@@ -161,6 +176,123 @@ class HermesAgentLoop:
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self.temperature = temperature
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self.max_tokens = max_tokens
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self.extra_body = extra_body
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self.tool_handler = tool_handler
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self.max_context_tokens = max_context_tokens
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def _truncate_context(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""Truncate conversation history to fit within max_context_tokens.
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Strategy:
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- Keep system message (index 0) and initial user message (index 1) always
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- Keep last 6 messages (recent context) always
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- For everything in between, progressively truncate tool result content
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- If still too long, drop oldest middle messages entirely
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Uses rough char/4 token estimate (fast, no tokenizer needed).
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NOTE: This function mutates the provided list (it may pop/replace entries).
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Call it on a copy when you want to preserve the full trajectory.
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"""
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if self.max_context_tokens is None:
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return messages
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def estimate_tokens(msgs):
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total = 0
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for m in msgs:
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content = m.get("content", "") or ""
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total += len(content) // 4 + 10 # ~4 chars per token + overhead
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if "tool_calls" in m:
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total += 50 * len(m["tool_calls"]) # tool call overhead
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return total
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if estimate_tokens(messages) <= self.max_context_tokens:
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return messages
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protect_head = 2
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protect_tail = max(0, min(6, len(messages) - protect_head))
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middle_start = protect_head
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middle_end = len(messages) - protect_tail
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# Phase 1: truncate tool outputs in the middle
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if middle_start < middle_end:
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for i in range(middle_start, middle_end):
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if messages[i].get("role") == "tool":
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content = messages[i].get("content", "") or ""
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if len(content) > 200:
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messages[i] = dict(messages[i])
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messages[i]["content"] = content[:100] + "\n...[truncated]...\n" + content[-50:]
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if estimate_tokens(messages) <= self.max_context_tokens:
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return messages
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# Phase 2: drop oldest middle messages (try to keep assistant+tool pairs)
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while middle_start < middle_end and estimate_tokens(messages) > self.max_context_tokens:
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msg = messages[middle_start]
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messages.pop(middle_start)
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middle_end -= 1
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if msg.get("role") == "assistant" and msg.get("tool_calls"):
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tool_ids = {
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tc.get("id") or tc.get("tool_call_id", "")
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for tc in msg.get("tool_calls", [])
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if isinstance(tc, dict)
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}
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i = middle_start
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while i < middle_end:
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if messages[i].get("role") == "tool" and messages[i].get("tool_call_id", "") in tool_ids:
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messages.pop(i)
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middle_end -= 1
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else:
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i += 1
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return messages
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def _normalize_tool_args(self, tool_name: str, tool_args_raw: str) -> (Dict[str, Any], bool):
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"""Normalize tool arguments into a dict.
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Returns: (args_dict, schema_valid)
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schema_valid is True only when arguments decode directly into a dict
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(no double-decoding and no coercion/wrapping required).
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Goal: keep environments robust (never crash on args format drift) while
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still allowing reward functions to penalize malformed formats if desired.
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"""
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try:
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decoded = json.loads(tool_args_raw)
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except json.JSONDecodeError:
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# Not JSON at all — treat as a plain string
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if tool_name == "terminal":
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return {"command": tool_args_raw}, False
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return {"input": tool_args_raw}, False
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if isinstance(decoded, dict):
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if tool_name == "terminal":
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cmd = decoded.get("command")
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if isinstance(cmd, str) and cmd.strip():
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return decoded, True
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if isinstance(decoded.get("input"), str):
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return {"command": decoded.get("input")}, False
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return decoded, False
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return decoded, True
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if isinstance(decoded, str):
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s = decoded.strip()
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if (s.startswith("{") and s.endswith("}")) or (s.startswith("[") and s.endswith("]")):
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try:
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decoded2 = json.loads(s)
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except json.JSONDecodeError:
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decoded2 = None
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if isinstance(decoded2, dict):
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return decoded2, False
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if tool_name == "terminal":
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return {"command": decoded}, False
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return {"input": decoded}, False
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if tool_name == "terminal":
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return {"command": str(decoded)}, False
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return {"input": decoded}, False
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async def run(self, messages: List[Dict[str, Any]]) -> AgentResult:
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"""
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@@ -176,14 +308,22 @@ class HermesAgentLoop:
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reasoning_per_turn = []
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tool_errors: List[ToolError] = []
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tool_calls_attempted = 0
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tool_calls_schema_valid = 0
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tool_calls_executed_ok = 0
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tool_calls_exec_error = 0
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import time as _time
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for turn in range(self.max_turns):
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turn_start = _time.monotonic()
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# Truncate prompt view on a copy (preserve full trajectory in `messages`)
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prompt_messages = self._truncate_context(list(messages))
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# Build the chat_completion kwargs
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chat_kwargs = {
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"messages": messages,
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"messages": prompt_messages,
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"n": 1,
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"temperature": self.temperature,
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}
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@@ -215,6 +355,10 @@ class HermesAgentLoop:
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finished_naturally=False,
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reasoning_per_turn=reasoning_per_turn,
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tool_errors=tool_errors,
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tool_calls_attempted=tool_calls_attempted,
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tool_calls_schema_valid=tool_calls_schema_valid,
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tool_calls_executed_ok=tool_calls_executed_ok,
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tool_calls_exec_error=tool_calls_exec_error,
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)
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api_elapsed = _time.monotonic() - api_start
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@@ -228,6 +372,10 @@ class HermesAgentLoop:
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finished_naturally=False,
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reasoning_per_turn=reasoning_per_turn,
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tool_errors=tool_errors,
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tool_calls_attempted=tool_calls_attempted,
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tool_calls_schema_valid=tool_calls_schema_valid,
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tool_calls_executed_ok=tool_calls_executed_ok,
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tool_calls_exec_error=tool_calls_exec_error,
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)
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assistant_msg = response.choices[0].message
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@@ -270,6 +418,7 @@ class HermesAgentLoop:
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# Validate tool name
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if tool_name not in self.valid_tool_names:
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tool_calls_exec_error += 1
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tool_result = json.dumps(
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{
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"error": f"Unknown tool '{tool_name}'. "
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@@ -287,35 +436,35 @@ class HermesAgentLoop:
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tool_name, turn + 1,
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)
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else:
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# Parse arguments and dispatch
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try:
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args = json.loads(tool_args_raw)
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except json.JSONDecodeError:
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args = {}
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logger.warning(
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"Invalid JSON in tool call arguments for '%s': %s",
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tool_name, tool_args_raw[:200],
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)
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tool_calls_attempted += 1
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args, schema_valid = self._normalize_tool_args(tool_name, tool_args_raw)
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if schema_valid:
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tool_calls_schema_valid += 1
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try:
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if tool_name == "terminal":
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backend = os.getenv("TERMINAL_ENV", "local")
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cmd_preview = args.get("command", "")[:80]
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cmd_preview = str(args.get("command", ""))[:80]
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logger.info(
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"[%s] $ %s", self.task_id[:8], cmd_preview,
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)
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# Run tool calls in a thread pool so backends that use
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# asyncio.run() internally (modal, docker) get a clean
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# event loop instead of deadlocking inside Atropos's loop.
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tool_submit_time = _time.monotonic()
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loop = asyncio.get_event_loop()
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tool_result = await loop.run_in_executor(
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_tool_executor,
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lambda: handle_function_call(
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tool_name, args, task_id=self.task_id
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),
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)
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if self.tool_handler:
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tool_result = await self.tool_handler(tool_name, args, self.task_id)
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else:
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# Run tool calls in a thread pool so backends that use
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# asyncio.run() internally (modal, docker) get a clean
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# event loop instead of deadlocking inside Atropos's loop.
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loop = asyncio.get_event_loop()
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tool_result = await loop.run_in_executor(
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_tool_executor,
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lambda: handle_function_call(
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tool_name, args, task_id=self.task_id
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),
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)
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tool_elapsed = _time.monotonic() - tool_submit_time
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# Log slow tools and thread pool stats for debugging
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@@ -327,6 +476,7 @@ class HermesAgentLoop:
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tool_elapsed, pool_active,
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)
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except Exception as e:
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tool_calls_exec_error += 1
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tool_result = json.dumps(
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{"error": f"Tool execution failed: {type(e).__name__}: {str(e)}"}
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)
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@@ -340,22 +490,31 @@ class HermesAgentLoop:
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"Tool '%s' execution failed on turn %d: %s",
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tool_name, turn + 1, e,
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)
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else:
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tool_err = False
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try:
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result_data = json.loads(tool_result)
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if isinstance(result_data, dict):
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err = result_data.get("error")
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if err:
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tool_err = True
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# Also check if the tool returned an error in its JSON result
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try:
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result_data = json.loads(tool_result)
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if isinstance(result_data, dict):
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err = result_data.get("error")
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exit_code = result_data.get("exit_code")
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if err and exit_code and exit_code < 0:
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tool_errors.append(ToolError(
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turn=turn + 1, tool_name=tool_name,
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arguments=tool_args_raw[:200],
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error=str(err),
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tool_result=tool_result[:500],
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))
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except (json.JSONDecodeError, TypeError):
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pass
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exit_code = result_data.get("exit_code")
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if exit_code is not None and isinstance(exit_code, int) and exit_code < 0:
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tool_err = True
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tool_errors.append(ToolError(
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turn=turn + 1, tool_name=tool_name,
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arguments=tool_args_raw[:200],
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error=str(err) if err else "nonzero exit_code",
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tool_result=tool_result[:500],
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))
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except (json.JSONDecodeError, TypeError):
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pass
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if tool_err:
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tool_calls_exec_error += 1
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else:
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tool_calls_executed_ok += 1
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# Add tool response to conversation
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messages.append(
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@@ -396,6 +555,10 @@ class HermesAgentLoop:
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finished_naturally=True,
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reasoning_per_turn=reasoning_per_turn,
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tool_errors=tool_errors,
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tool_calls_attempted=tool_calls_attempted,
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tool_calls_schema_valid=tool_calls_schema_valid,
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tool_calls_executed_ok=tool_calls_executed_ok,
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tool_calls_exec_error=tool_calls_exec_error,
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)
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# Hit max turns without the model stopping
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@@ -407,6 +570,10 @@ class HermesAgentLoop:
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finished_naturally=False,
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reasoning_per_turn=reasoning_per_turn,
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tool_errors=tool_errors,
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tool_calls_attempted=tool_calls_attempted,
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tool_calls_schema_valid=tool_calls_schema_valid,
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tool_calls_executed_ok=tool_calls_executed_ok,
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tool_calls_exec_error=tool_calls_exec_error,
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)
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def _get_managed_state(self) -> Optional[Dict[str, Any]]:
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@@ -478,6 +478,7 @@ class HermesAgentBaseEnv(BaseEnv):
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tokenizer=self.tokenizer,
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tool_call_parser=tc_parser,
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) as managed:
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_max_ctx = self.config.max_token_length if (self.config.max_token_length and self.config.max_token_length > 0) else None
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agent = HermesAgentLoop(
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server=managed,
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tool_schemas=tools,
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@@ -487,6 +488,7 @@ class HermesAgentBaseEnv(BaseEnv):
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temperature=self.config.agent_temperature,
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max_tokens=self.config.max_token_length,
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extra_body=self.config.extra_body,
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max_context_tokens=_max_ctx,
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)
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result = await agent.run(messages)
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except NotImplementedError:
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@@ -495,6 +497,7 @@ class HermesAgentBaseEnv(BaseEnv):
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"ManagedServer not available (OpenAI server?). "
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"Falling back to direct server mode."
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)
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_max_ctx = self.config.max_token_length if (self.config.max_token_length and self.config.max_token_length > 0) else None
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agent = HermesAgentLoop(
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server=self.server,
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tool_schemas=tools,
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@@ -504,10 +507,12 @@ class HermesAgentBaseEnv(BaseEnv):
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temperature=self.config.agent_temperature,
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max_tokens=self.config.max_token_length,
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extra_body=self.config.extra_body,
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max_context_tokens=_max_ctx,
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)
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result = await agent.run(messages)
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else:
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# Phase 1: OpenAI server -- native tool_calls, placeholder tokens
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_max_ctx = self.config.max_token_length if (self.config.max_token_length and self.config.max_token_length > 0) else None
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agent = HermesAgentLoop(
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server=self.server,
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tool_schemas=tools,
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@@ -517,6 +522,7 @@ class HermesAgentBaseEnv(BaseEnv):
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temperature=self.config.agent_temperature,
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max_tokens=self.config.max_token_length,
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extra_body=self.config.extra_body,
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max_context_tokens=_max_ctx,
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)
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result = await agent.run(messages)
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@@ -49,15 +49,22 @@ class HermesToolCallParser(ToolCallParser):
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continue
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tc_data = json.loads(raw_json)
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# Handle arguments: could be dict or already a JSON string
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raw_args = tc_data.get("arguments", {})
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if isinstance(raw_args, str):
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# Already a string — pass through as-is.
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# It may be a JSON string ("{...}") or a plain string ("ls").
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args_str = raw_args
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else:
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# Dict — serialize to JSON
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args_str = json.dumps(raw_args, ensure_ascii=False)
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tool_calls.append(
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ChatCompletionMessageToolCall(
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id=f"call_{uuid.uuid4().hex[:8]}",
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type="function",
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function=Function(
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name=tc_data["name"],
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arguments=json.dumps(
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tc_data.get("arguments", {}), ensure_ascii=False
|
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),
|
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arguments=args_str,
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),
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)
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||||
)
|
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|
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