Deprecate direct access to globals like debug and verbose.

cookbook/forward_looking_retrieval_augmented_generation.ipynb

@@ -135,9 +135,9 @@
    "outputs": [],
    "source": [
     "# We set this so we can see what exactly is going on\n",
-    "import langchain\n",
+    "from langchain.globals import set_verbose\n",
     "\n",
-    "langchain.verbose = True"
+    "set_verbose(True)"
    ]
   },
   {
@@ -489,7 +489,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.1"
   }
  },
  "nbformat": 4,

cookbook/learned_prompt_optimization.ipynb

@@ -214,7 +214,7 @@
     "\n",
     "The way the chain is learning that Tom prefers veggetarian meals is via an AutoSelectionScorer that is built into the chain. The scorer will call the LLM again and ask it to evaluate the selection (`ToSelectFrom`) using the information wrapped in (`BasedOn`).\n",
     "\n",
-    "You can set `langchain.debug=True` if you want to see the details of the auto-scorer, but you can also define the scoring prompt yourself."
+    "You can set `set_debug(True)` if you want to see the details of the auto-scorer, but you can also define the scoring prompt yourself."
    ]
   },
   {
@@ -778,8 +778,9 @@
    ],
    "source": [
     "from langchain.prompts.prompt import PromptTemplate\n",
-    "import langchain\n",
-    "langchain.debug = True\n",
+    "from langchain.globals import set_debug\n",
+    "\n",
+    "set_debug(True)\n",
     "\n",
     "REWARD_PROMPT_TEMPLATE = \"\"\"\n",
     "\n",
@@ -812,9 +813,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "poetry-venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "poetry-venv"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -826,7 +827,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.1"
   }
  },
  "nbformat": 4,

docs/docs/guides/debugging.md

@@ -14,7 +14,7 @@ For anyone building production-grade LLM applications, we highly recommend using
 
 ![LangSmith run](/img/run_details.png)
 
-## `langchain.debug` and `langchain.verbose`
+## `set_debug` and `set_verbose`
 
 If you're prototyping in Jupyter Notebooks or running Python scripts, it can be helpful to print out the intermediate steps of a Chain run. 
 
@@ -45,15 +45,15 @@ agent.run("Who directed the 2023 film Oppenheimer and what is their age? What is
 
 </CodeOutputBlock>
 
-### `langchain.debug = True`
+### `set_debug(True)`
 
 Setting the global `debug` flag will cause all LangChain components with callback support (chains, models, agents, tools, retrievers) to print the inputs they receive and outputs they generate. This is the most verbose setting and will fully log raw inputs and outputs.
 
 
 ```python
-import langchain
+from langchain.globals import set_debug
 
-langchain.debug = True
+set_debug(True)
 
 agent.run("Who directed the 2023 film Oppenheimer and what is their age? What is their age in days (assume 365 days per year)?")
 ```
@@ -376,15 +376,15 @@ agent.run("Who directed the 2023 film Oppenheimer and what is their age? What is
 
 </details>
 
-### `langchain.verbose = True`
+### `set_vebose(True)`
 
 Setting the `verbose` flag will print out inputs and outputs in a slightly more readable format and will skip logging certain raw outputs (like the token usage stats for an LLM call) so that you can focus on application logic.
 
 
 ```python
-import langchain
+from langchain.globals import set_verbose
 
-langchain.verbose = True
+set_verbose(True)
 
 agent.run("Who directed the 2023 film Oppenheimer and what is their age? What is their age in days (assume 365 days per year)?")
 ```

docs/docs/integrations/llms/bittensor.ipynb

@@ -30,12 +30,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import langchain\n",
     "from langchain.llms import NIBittensorLLM\n",
     "import json\n",
     "from pprint import pprint\n",
     "\n",
-    "langchain.debug = True\n",
+    "from langchain.globals import set_debug\n",
+    "\n",
+    "set_debug(True)\n",
     "\n",
     "# System parameter in NIBittensorLLM is optional but you can set whatever you want to perform with model\n",
     "llm_sys = NIBittensorLLM(\n",
@@ -79,11 +80,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import langchain\n",
-    "from langchain.prompts import PromptTemplate\nfrom langchain.chains import LLMChain\n",
+    "from langchain.prompts import PromptTemplate\n",
+    "from langchain.chains import LLMChain\n",
     "from langchain.llms import NIBittensorLLM\n",
     "\n",
-    "langchain.debug = True\n",
+    "from langchain.globals import set_debug\n",
+    "\n",
+    "set_debug(True)\n",
     "\n",
     "template = \"\"\"Question: {question}\n",
     "\n",
@@ -123,7 +126,8 @@
     "    AgentExecutor,\n",
     ")\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain.chains import LLMChain\nfrom langchain.prompts import PromptTemplate\n",
+    "from langchain.chains import LLMChain\n",
+    "from langchain.prompts import PromptTemplate\n",
     "from langchain.utilities import GoogleSearchAPIWrapper, SerpAPIWrapper\n",
     "from langchain.llms import NIBittensorLLM\n",
     "\n",
@@ -174,7 +178,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.1"
   }
  },
  "nbformat": 4,