> 13:RunTypeEnum.llm:ChatOpenAI] [2.89s] Exiting LLM run with output:    {      "generations": [        [          {            "text": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n",            "generation_info": {              "finish_reason": "stop"            },            "message": {              "lc": 1,              "type": "constructor",              "id": [                "langchain",                "schema",                "messages",                "AIMessage"              ],              "kwargs": {                "content": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n",                "additional_kwargs": {}              }            }          }        ]      ],      "llm_output": {        "token_usage": {          "prompt_tokens": 203,          "completion_tokens": 19,          "total_tokens": 222        },        "model_name": "gpt-4"      },      "run": null    }    [chain/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator > 11:RunTypeEnum.chain:LLMMathChain > 12:RunTypeEnum.chain:LLMChain] [2.89s] Exiting Chain run with output:    {      "text": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n"    }    [chain/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator > 11:RunTypeEnum.chain:LLMMathChain] [2.90s] Exiting Chain run with output:    {      "answer": "Answer: 18980"    }    [tool/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator] [2.90s] Exiting Tool run with output:    "Answer: 18980"    [chain/start] [1:RunTypeEnum.chain:AgentExecutor > 14:RunTypeEnum.chain:LLMChain] Entering Chain run with input:    {      "input": "Who directed the 2023 film Oppenheimer and what is their age? What is their age in days (assume 365 days per year)?",      "agent_scratchpad": "I need to find out who directed the 2023 film Oppenheimer and their age. Then, I need to calculate their age in days. I will use DuckDuckGo to find out the director and their
If you're building with LLMs, at some point something will break, and you'll need to debug. A model call will fail, or the model output will be misformatted, or there will be some nested model calls and it won't be clear where along the way an incorrect output was created.
If you're building with LLMs, at some point something will break, and you'll need to debug. A model call will fail, or the model output will be misformatted, or there will be some nested model calls and it won't be clear where along the way an incorrect output was created. ->: > 13:RunTypeEnum.llm:ChatOpenAI] [2.89s] Exiting LLM run with output:    {      "generations": [        [          {            "text": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n",            "generation_info": {              "finish_reason": "stop"            },            "message": {              "lc": 1,              "type": "constructor",              "id": [                "langchain",                "schema",                "messages",                "AIMessage"              ],              "kwargs": {                "content": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n",                "additional_kwargs": {}              }            }          }        ]      ],      "llm_output": {        "token_usage": {          "prompt_tokens": 203,          "completion_tokens": 19,          "total_tokens": 222        },        "model_name": "gpt-4"      },      "run": null    }    [chain/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator > 11:RunTypeEnum.chain:LLMMathChain > 12:RunTypeEnum.chain:LLMChain] [2.89s] Exiting Chain run with output:    {      "text": "```text\n52*365\n```\n...numexpr.evaluate(\"52*365\")...\n"    }    [chain/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator > 11:RunTypeEnum.chain:LLMMathChain] [2.90s] Exiting Chain run with output:    {      "answer": "Answer: 18980"    }    [tool/end] [1:RunTypeEnum.chain:AgentExecutor > 10:RunTypeEnum.tool:Calculator] [2.90s] Exiting Tool run with output:    "Answer: 18980"    [chain/start] [1:RunTypeEnum.chain:AgentExecutor > 14:RunTypeEnum.chain:LLMChain] Entering Chain run with input:    {      "input": "Who directed the 2023 film Oppenheimer and what is their age? What is their age in days (assume 365 days per year)?",      "agent_scratchpad": "I need to find out who directed the 2023 film Oppenheimer and their age. Then, I need to calculate their age in days. I will use DuckDuckGo to find out the director and their