mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-09-01 04:39:01 +02:00
* Update LLMCompiler.ipynb
The code didn't actually handle when there's more than one dependency listed in an argument. The example of multi-step math used in the code doesn't work because the third step has more than one dependency in its args and the code only handles one:
```
User query: "What's ((3*(4+5)/0.5)+3245) + 8? What's 32/4.23? What's the sum of those two values?"
1. math(problem="((3*(4+5)/0.5)+3245) + 8")
2. math(problem="32/4.23")
3. math(problem="${1}+${2}")
4. join()<END_OFPLAN>
```
Step 3 fails, and does so silently too. It correctly parses strings that are "${1}", but not multi-argument strings like "${1}+${2}"
This fixes it to handle any number of dependencies listed in one arg. It uses the regex pattern already defined in output_parser.py.
* Fix looping function calls because no arg context
Task Fetching Unit, when it inserts the tool_messages, the function args don't get logged with function calls, this causes the replanner to loop and use the same function parameters and never corrects itself.
* Fix tool index count and range
In the planner prompt formatting, the 'num_tools' variable needs to have a +1 added to it because we're appending the join() function, without +1 it says there's one less available tools than there actually is because it only counts the passed in functions and not the join() function. And add +1 for listing otherwise it starts at a 0 offset.
* Fix unhandled empty iterator exception
Task fetching unit: When it calls the tools it doesn't handle when there's no tasks. next() is called and fails. This fixes it by wrapping in a try/except. On exception we set tasks to an empty list since next() failed, there's no tasks.
This commit is contained in:
Misraaks
@@ -222,11 +222,11 @@
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" llm: BaseChatModel, tools: Sequence[BaseTool], base_prompt: ChatPromptTemplate\n",
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"):\n",
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" tool_descriptions = \"\\n\".join(\n",
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" f\"{i}. {tool.description}\\n\" for i, tool in enumerate(tools)\n",
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" f\"{i+1}. {tool.description}\\n\" for i, tool in enumerate(tools) # +1 to offset the 0 starting index, we want it count normally from 1.\n",
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" )\n",
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" planner_prompt = base_prompt.partial(\n",
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" replan=\"\",\n",
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" num_tools=len(tools),\n",
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" num_tools=len(tools)+1, # Add one because we're adding the join() tool at the end.\n",
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" tool_descriptions=tool_descriptions,\n",
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" )\n",
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" replanner_prompt = base_prompt.partial(\n",
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@@ -236,7 +236,7 @@
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" ' - When starting the Current Plan, you should start with \"Thought\" that outlines the strategy for the next plan.\\n'\n",
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" \" - In the Current Plan, you should NEVER repeat the actions that are already executed in the Previous Plan.\\n\"\n",
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" \" - You must continue the task index from the end of the previous one. Do not repeat task indices.\",\n",
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" num_tools=len(tools),\n",
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" num_tools=len(tools)+1,\n",
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" tool_descriptions=tool_descriptions,\n",
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" )\n",
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"\n",
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@@ -338,6 +338,7 @@
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"source": [
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"from typing import Any, Union, Iterable, List, Tuple, Dict\n",
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"from typing_extensions import TypedDict\n",
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"import re\n",
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"\n",
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"from langchain_core.runnables import (\n",
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" chain as as_runnable,\n",
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@@ -391,13 +392,20 @@
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"\n",
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"\n",
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"def _resolve_arg(arg: Union[str, Any], observations: Dict[int, Any]):\n",
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" if isinstance(arg, str) and arg.startswith(\"$\"):\n",
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" try:\n",
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" stripped = arg[1:].replace(\".output\", \"\").strip(\"{}\")\n",
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" idx = int(stripped)\n",
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" except Exception:\n",
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" return str(arg)\n",
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" return str(observations[idx])\n",
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" # $1 or ${1} -> 1\n",
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" ID_PATTERN = r\"\\$\\{?(\\d+)\\}?\"\n",
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"\n",
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" def replace_match(match):\n",
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" # If the string is ${123}, match.group(0) is ${123}, and match.group(1) is 123.\n",
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"\n",
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" # Return the match group, in this case the index, from the string. This is the index\n",
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" # number we get back.\n",
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" idx = int(match.group(1))\n",
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" return str(observations.get(idx, match.group(0)))\n",
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"\n",
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" # For dependencies on other tasks\n",
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" if isinstance(arg, str):\n",
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" return re.sub(ID_PATTERN, replace_match, arg)\n",
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" elif isinstance(arg, list):\n",
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" return [_resolve_arg(a, observations) for a in arg]\n",
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" else:\n",
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@@ -440,6 +448,7 @@
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" # adjust to do a proper topological sort (not-stream)\n",
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" # or use a more complicated data structure\n",
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" tasks = scheduler_input[\"tasks\"]\n",
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" args_for_tasks = {}\n",
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" messages = scheduler_input[\"messages\"]\n",
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" # If we are re-planning, we may have calls that depend on previous\n",
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" # plans. Start with those.\n",
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@@ -456,6 +465,7 @@
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" task_names[task[\"idx\"]] = (\n",
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" task[\"tool\"] if isinstance(task[\"tool\"], str) else task[\"tool\"].name\n",
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" )\n",
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" args_for_tasks[task[\"idx\"]] = (task[\"args\"])\n",
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" if (\n",
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" # Depends on other tasks\n",
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" deps\n",
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@@ -477,12 +487,12 @@
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" wait(futures)\n",
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" # Convert observations to new tool messages to add to the state\n",
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" new_observations = {\n",
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" k: (task_names[k], observations[k])\n",
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" k: (task_names[k], args_for_tasks[k], observations[k])\n",
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" for k in sorted(observations.keys() - originals)\n",
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" }\n",
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" tool_messages = [\n",
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" FunctionMessage(name=name, content=str(obs), additional_kwargs={\"idx\": k})\n",
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" for k, (name, obs) in new_observations.items()\n",
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" FunctionMessage(name=name, content=str(obs), additional_kwargs={\"idx\": k, 'args':task_args})\n",
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" for k, (name, task_args, obs) in new_observations.items()\n",
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" ]\n",
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" return tool_messages"
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]
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@@ -501,7 +511,11 @@
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"def plan_and_schedule(messages: List[BaseMessage], config):\n",
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" tasks = planner.stream(messages, config)\n",
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" # Begin executing the planner immediately\n",
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" tasks = itertools.chain([next(tasks)], tasks)\n",
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" try:\n",
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" tasks = itertools.chain([next(tasks)], tasks)\n",
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" except StopIteration:\n",
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" # Handle the case where tasks is empty.\n",
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" tasks = iter([])\n",
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" scheduled_tasks = schedule_tasks.invoke(\n",
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" {\n",
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" \"messages\": messages,\n",
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