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Fix config override bug by recreating LMs after load_state

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This commit is contained in:
Farouk Adeleke
2026-01-24 15:41:33 -08:00
parent 33f34e9615
commit 0e27e83b57
2 changed files with 13 additions and 11 deletions
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2
config.json
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@@ -6,6 +6,6 @@
"api_base": "https://openrouter.ai/api/v1", "api_base": "https://openrouter.ai/api/v1",
"max_tokens": 50000, "max_tokens": 50000,
"max_output_chars": 100000, "max_output_chars": 100000,
"verbose": false, "verbose": true,
"track_usage": true "track_usage": true
} }

22
nanocode.py
View File

@@ -170,8 +170,8 @@ def run_bash(cmd: str) -> str:
class RLMReasoningCallback(BaseCallback): class RLMReasoningCallback(BaseCallback):
def on_module_end(self, call_id, outputs, exception): def on_module_end(self, call_id, outputs, exception):
if outputs and hasattr(outputs, "reasoning") and hasattr(outputs, "code"): if outputs and hasattr(outputs, "reasoning") and hasattr(outputs, "code"):
print(f"{DIM}⏺ [REASONING STEP] {outputs.reasoning}\n{RESET}") print(f"{DIM}⏺ [REASONING STEP]\n{outputs.reasoning}\n{RESET}")
print(f"{DIM}⏺ [CODE] {outputs.code}\n{RESET}") print(f"{DIM}⏺ [CODE]\n```\n{outputs.code}\n```\n{RESET}")
# -- Program --- # -- Program ---
@@ -193,7 +193,7 @@ class RLMCodingConfig(PrecompiledConfig):
api_base: str = "https://openrouter.ai/api/v1" api_base: str = "https://openrouter.ai/api/v1"
max_tokens: int = 50000 max_tokens: int = 50000
max_output_chars: int = 100000 max_output_chars: int = 100000
verbose: bool = False verbose: bool = True
track_usage: bool = True track_usage: bool = True
@@ -261,22 +261,22 @@ class RLMCodingProgram(PrecompiledProgram):
def wrapped_q(prompt): # wrap query def wrapped_q(prompt): # wrap query
print( print(
f"{DIM}⏺ [LLM QUERY]: {prompt[:100]}...{RESET}\n" f"{DIM}⏺ [LLM QUERY]:\n{prompt[:100]}...{RESET}\n"
if len(prompt) > 100 if len(prompt) > 100
else f"{DIM}⏺ [LLM QUERY]: {prompt}{RESET}\n" else f"{DIM}⏺ [LLM QUERY]:\n{prompt}{RESET}\n"
) )
res = orig_q(prompt) res = orig_q(prompt)
print( print(
f"{DIM}⏺ [LLM QUERY RESULT]: {str(res)[:200]}...{RESET}\n" f"{DIM}⏺ [LLM QUERY RESULT]:\n{str(res)[:200]}...{RESET}\n"
if len(str(res)) > 200 if len(str(res)) > 200
else f"{DIM}⏺ [LLM QUERY RESULT]: {res}{RESET}\n" else f"{DIM}⏺ [LLM QUERY RESULT]:\n{res}{RESET}\n"
) )
return res return res
def wrapped_b(prompts): # wrap batched query def wrapped_b(prompts): # wrap batched query
print(f"{DIM}⏺ [LLM QUERY BATCHED]: {len(prompts)} prompts{RESET}\n") print(f"{DIM}⏺ [LLM QUERY BATCHED]:\n{len(prompts)} prompts{RESET}\n")
res = orig_b(prompts) res = orig_b(prompts)
print(f"{DIM}⏺ [LLM QUERY BATCHED]: {len(res)} results{RESET}\n") print(f"{DIM}⏺ [LLM QUERY BATCHED]:\n{len(res)} results{RESET}\n")
return res return res
tools["llm_query"] = wrapped_q tools["llm_query"] = wrapped_q
@@ -318,7 +318,7 @@ class RLMCodingProgram(PrecompiledProgram):
tools=self.tools, tools=self.tools,
max_output_chars=self.config.max_output_chars, max_output_chars=self.config.max_output_chars,
max_iterations=self.config.max_iters, max_iterations=self.config.max_iters,
verbose=self.config.verbose, verbose=False, # We add our own verbose logging
) )
new_instance.set_lm(self.lm) new_instance.set_lm(self.lm)
self.agent = new_instance self.agent = new_instance
@@ -358,6 +358,7 @@ class RLMCodingProgram(PrecompiledProgram):
if __name__ == "__main__": if __name__ == "__main__":
agent = RLMCodingProgram(RLMCodingConfig()) agent = RLMCodingProgram(RLMCodingConfig())
#agent(task="explicity call llm_query(who is the ceo of apple?) to get the answer to 'who is the ceo of apple?'")
branches = ["main", "dev", "prod"] branches = ["main", "dev", "prod"]
for branch in branches: for branch in branches:
agent.push_to_hub( agent.push_to_hub(
@@ -366,3 +367,4 @@ if __name__ == "__main__":
branch=branch, branch=branch,
) )