chore: cleanup
made bdi match incoming messages changed llm from test agent to llm agent in config. ref: N25B-207
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@@ -21,10 +21,10 @@ uv sync
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To run a LLM locally download https://lmstudio.ai
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When installing select developer mode, download a model (it will already suggest one) and run it (see developer window, status: running)
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copy the url at the top right and replace LOCAL_LLM_URL with it + v1/chat/completions.
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copy the url at the top right and replace local_llm_url with it + v1/chat/completions.
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This + part might differ based on what model you choose.
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copy the model name in the module loaded and replace LOCAL_LLM_MODEL.
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copy the model name in the module loaded and replace local_llm_modelL. In settings.
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## Running
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@@ -59,7 +59,7 @@ class BDICoreAgent(BDIAgent):
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class SendBehaviour(OneShotBehaviour):
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async def run(self) -> None:
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msg = Message(
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to= settings.agent_settings.test_agent_name + '@' + settings.agent_settings.host,
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to= settings.agent_settings.llm_agent_name + '@' + settings.agent_settings.host,
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body= text,
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thread= "llm_request",
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)
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@@ -81,13 +81,16 @@ class BDICoreAgent(BDIAgent):
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if not msg:
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return
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content = msg.body
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self.agent.logger.info("Received LLM response: %s", content)
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sender = msg.sender.node
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match sender:
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case settings.agent_settings.llm_agent_name:
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content = msg.body
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self.agent.logger.info("Received LLM response: %s", content)
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#Here the BDI can pass the message back as a response
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case _:
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self.logger.debug("Not from the llm, discarding message")
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pass
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# TODO: Convert response into a belief (optional future feature)
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# Example:
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# self.agent.add_belief("llm_response", content)
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# self.agent.logger.debug("Added belief: llm_response(%s)", content)
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template = Template()
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template.thread = "llm_response"
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