Callbacks Refactor [base] (#3256)

Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com> Co-authored-by: Zander Chase <130414180+vowelparrot@users.noreply.github.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2026-01-25 14:35:49 +00:00 · 2023-04-30 11:14:09 -07:00
parent 18ec22fe56
commit d3ec00b566
208 changed files with 6394 additions and 3353 deletions
--- a/docs/ecosystem/aim_tracking.ipynb
+++ b/docs/ecosystem/aim_tracking.ipynb
@@ -61,7 +61,6 @@
    "from datetime import datetime\n",
    "\n",
    "from langchain.llms import OpenAI\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.callbacks import AimCallbackHandler, StdOutCallbackHandler"
   ]
  },
@@ -109,8 +108,8 @@
    "    experiment_name=\"scenario 1: OpenAI LLM\",\n",
    ")\n",
    "\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), aim_callback])\n",
-    "llm = OpenAI(temperature=0, callback_manager=manager, verbose=True)"
+    "callbacks = [StdOutCallbackHandler(), aim_callback]\n",
+    "llm = OpenAI(temperature=0, callbacks=callbacks)"
   ]
  },
  {
@@ -177,7 +176,7 @@
    "Title: {title}\n",
    "Playwright: This is a synopsis for the above play:\"\"\"\n",
    "prompt_template = PromptTemplate(input_variables=[\"title\"], template=template)\n",
-    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callback_manager=manager)\n",
+    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callbacks=callbacks)\n",
    "\n",
    "test_prompts = [\n",
    "    {\"title\": \"documentary about good video games that push the boundary of game design\"},\n",
@@ -249,13 +248,12 @@
   ],
   "source": [
    "# scenario 3 - Agent with Tools\n",
-    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callback_manager=manager)\n",
+    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callbacks=callbacks)\n",
    "agent = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,\n",
-    "    callback_manager=manager,\n",
-    "    verbose=True,\n",
+    "    callbacks=callbacks,\n",
    ")\n",
    "agent.run(\n",
    "    \"Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?\"\n",
--- a/docs/ecosystem/clearml_tracking.ipynb
+++ b/docs/ecosystem/clearml_tracking.ipynb
@@ -79,7 +79,6 @@
   "source": [
    "from datetime import datetime\n",
    "from langchain.callbacks import ClearMLCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.llms import OpenAI\n",
    "\n",
    "# Setup and use the ClearML Callback\n",
@@ -93,9 +92,9 @@
    "    complexity_metrics=True,\n",
    "    stream_logs=True\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), clearml_callback])\n",
+    "callbacks = [StdOutCallbackHandler(), clearml_callback]\n",
    "# Get the OpenAI model ready to go\n",
-    "llm = OpenAI(temperature=0, callback_manager=manager, verbose=True)"
+    "llm = OpenAI(temperature=0, callbacks=callbacks)"
   ]
  },
  {
@@ -523,13 +522,12 @@
    "from langchain.agents import AgentType\n",
    "\n",
    "# SCENARIO 2 - Agent with Tools\n",
-    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callback_manager=manager)\n",
+    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callbacks=callbacks)\n",
    "agent = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,\n",
-    "    callback_manager=manager,\n",
-    "    verbose=True,\n",
+    "    callbacks=callbacks,\n",
    ")\n",
    "agent.run(\n",
    "    \"Who is the wife of the person who sang summer of 69?\"\n",
--- a/docs/ecosystem/comet_tracking.ipynb
+++ b/docs/ecosystem/comet_tracking.ipynb
@@ -121,7 +121,6 @@
    "from datetime import datetime\n",
    "\n",
    "from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.llms import OpenAI\n",
    "\n",
    "comet_callback = CometCallbackHandler(\n",
@@ -131,8 +130,8 @@
    "    tags=[\"llm\"],\n",
    "    visualizations=[\"dep\"],\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), comet_callback])\n",
-    "llm = OpenAI(temperature=0.9, callback_manager=manager, verbose=True)\n",
+    "callbacks = [StdOutCallbackHandler(), comet_callback]\n",
+    "llm = OpenAI(temperature=0.9, callbacks=callbacks, verbose=True)\n",
    "\n",
    "llm_result = llm.generate([\"Tell me a joke\", \"Tell me a poem\", \"Tell me a fact\"] * 3)\n",
    "print(\"LLM result\", llm_result)\n",
@@ -153,7 +152,6 @@
   "outputs": [],
   "source": [
    "from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.chains import LLMChain\n",
    "from langchain.llms import OpenAI\n",
    "from langchain.prompts import PromptTemplate\n",
@@ -164,15 +162,14 @@
    "    stream_logs=True,\n",
    "    tags=[\"synopsis-chain\"],\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), comet_callback])\n",
-    "\n",
-    "llm = OpenAI(temperature=0.9, callback_manager=manager, verbose=True)\n",
+    "callbacks = [StdOutCallbackHandler(), comet_callback]\n",
+    "llm = OpenAI(temperature=0.9, callbacks=callbacks)\n",
    "\n",
    "template = \"\"\"You are a playwright. Given the title of play, it is your job to write a synopsis for that title.\n",
    "Title: {title}\n",
    "Playwright: This is a synopsis for the above play:\"\"\"\n",
    "prompt_template = PromptTemplate(input_variables=[\"title\"], template=template)\n",
-    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callback_manager=manager)\n",
+    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callbacks=callbacks)\n",
    "\n",
    "test_prompts = [{\"title\": \"Documentary about Bigfoot in Paris\"}]\n",
    "print(synopsis_chain.apply(test_prompts))\n",
@@ -194,7 +191,6 @@
   "source": [
    "from langchain.agents import initialize_agent, load_tools\n",
    "from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.llms import OpenAI\n",
    "\n",
    "comet_callback = CometCallbackHandler(\n",
@@ -203,15 +199,15 @@
    "    stream_logs=True,\n",
    "    tags=[\"agent\"],\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), comet_callback])\n",
-    "llm = OpenAI(temperature=0.9, callback_manager=manager, verbose=True)\n",
+    "callbacks = [StdOutCallbackHandler(), comet_callback]\n",
+    "llm = OpenAI(temperature=0.9, callbacks=callbacks)\n",
    "\n",
-    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callback_manager=manager)\n",
+    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callbacks=callbacks)\n",
    "agent = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=\"zero-shot-react-description\",\n",
-    "    callback_manager=manager,\n",
+    "    callbacks=callbacks,\n",
    "    verbose=True,\n",
    ")\n",
    "agent.run(\n",
@@ -255,7 +251,6 @@
    "from rouge_score import rouge_scorer\n",
    "\n",
    "from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.chains import LLMChain\n",
    "from langchain.llms import OpenAI\n",
    "from langchain.prompts import PromptTemplate\n",
@@ -298,10 +293,10 @@
    "    tags=[\"custom_metrics\"],\n",
    "    custom_metrics=rouge_score.compute_metric,\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), comet_callback])\n",
-    "llm = OpenAI(temperature=0.9, callback_manager=manager, verbose=True)\n",
+    "callbacks = [StdOutCallbackHandler(), comet_callback]\n",
+    "llm = OpenAI(temperature=0.9)\n",
    "\n",
-    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callback_manager=manager)\n",
+    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template)\n",
    "\n",
    "test_prompts = [\n",
    "    {\n",
@@ -323,7 +318,7 @@
    "                 \"\"\"\n",
    "    }\n",
    "]\n",
-    "print(synopsis_chain.apply(test_prompts))\n",
+    "print(synopsis_chain.apply(test_prompts, callbacks=callbacks))\n",
    "comet_callback.flush_tracker(synopsis_chain, finish=True)"
   ]
  }
--- a/docs/ecosystem/gpt4all.md
+++ b/docs/ecosystem/gpt4all.md
@@ -3,6 +3,7 @@
 This page covers how to use the `GPT4All` wrapper within LangChain. The tutorial is divided into two parts: installation and setup, followed by usage with an example.

 ## Installation and Setup
+
 - Install the Python package with `pip install pyllamacpp`
 - Download a [GPT4All model](https://github.com/nomic-ai/pyllamacpp#supported-model) and place it in your desired directory

@@ -28,16 +29,16 @@ To stream the model's predictions, add in a CallbackManager.

 ```python
 from langchain.llms import GPT4All
-from langchain.callbacks.base import CallbackManager
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+
 # There are many CallbackHandlers supported, such as
 # from langchain.callbacks.streamlit import StreamlitCallbackHandler

-callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])
-model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8, callback_handler=callback_handler, verbose=True)
+callbacks = [StreamingStdOutCallbackHandler()]
+model = GPT4All(model="./models/gpt4all-model.bin", n_ctx=512, n_threads=8)

 # Generate text. Tokens are streamed through the callback manager.
-model("Once upon a time, ")
+model("Once upon a time, ", callbacks=callbacks)
 ```

 ## Model File
--- a/docs/ecosystem/wandb_tracking.ipynb
+++ b/docs/ecosystem/wandb_tracking.ipynb
@@ -50,7 +50,6 @@
   "source": [
    "from datetime import datetime\n",
    "from langchain.callbacks import WandbCallbackHandler, StdOutCallbackHandler\n",
-    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.llms import OpenAI"
   ]
  },
@@ -196,8 +195,8 @@
    "    name=\"llm\",\n",
    "    tags=[\"test\"],\n",
    ")\n",
-    "manager = CallbackManager([StdOutCallbackHandler(), wandb_callback])\n",
-    "llm = OpenAI(temperature=0, callback_manager=manager, verbose=True)"
+    "callbacks = [StdOutCallbackHandler(), wandb_callback]\n",
+    "llm = OpenAI(temperature=0, callbacks=callbacks)"
   ]
  },
  {
@@ -484,7 +483,7 @@
    "Title: {title}\n",
    "Playwright: This is a synopsis for the above play:\"\"\"\n",
    "prompt_template = PromptTemplate(input_variables=[\"title\"], template=template)\n",
-    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callback_manager=manager)\n",
+    "synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callbacks=callbacks)\n",
    "\n",
    "test_prompts = [\n",
    "    {\n",
@@ -577,16 +576,15 @@
   ],
   "source": [
    "# SCENARIO 3 - Agent with Tools\n",
-    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm, callback_manager=manager)\n",
+    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n",
    "agent = initialize_agent(\n",
    "    tools,\n",
    "    llm,\n",
    "    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,\n",
-    "    callback_manager=manager,\n",
-    "    verbose=True,\n",
    ")\n",
    "agent.run(\n",
-    "    \"Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?\"\n",
+    "    \"Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?\",\n",
+    "    callbacks=callbacks,\n",
    ")\n",
    "wandb_callback.flush_tracker(agent, reset=False, finish=True)"
   ]