langchain[patch]: support binding oustide create_react_agent

libs/langchain/langchain/agents/react/agent.py

@@ -2,9 +2,10 @@ from __future__ import annotations
 
 from typing import Sequence
 
-from langchain_core.language_models import BaseLanguageModel
+from langchain_core.language_models import LanguageModelLike
 from langchain_core.prompts import BasePromptTemplate
 from langchain_core.runnables import Runnable, RunnablePassthrough
+from langchain_core.runnables.base import RunnableBindingBase
 from langchain_core.tools import BaseTool
 
 from langchain.agents.format_scratchpad import format_log_to_str
@@ -13,7 +14,7 @@ from langchain.tools.render import render_text_description
 
 
 def create_react_agent(
-    llm: BaseLanguageModel, tools: Sequence[BaseTool], prompt: BasePromptTemplate
+    llm: LanguageModelLike, tools: Sequence[BaseTool], prompt: BasePromptTemplate
 ) -> Runnable:
     """Create an agent that uses ReAct prompting.
 
@@ -32,11 +33,12 @@ def create_react_agent(
         .. code-block:: python
 
             from langchain import hub
-            from langchain_community.llms import OpenAI
+            from langchain_core.messages import AIMessage, HumanMessage
+            from langchain_openai import ChatOpenAI
             from langchain.agents import AgentExecutor, create_react_agent
 
             prompt = hub.pull("hwchase17/react")
-            model = OpenAI()
+            model = ChatOpenAI(model="gpt-3.5-turbo", temperature=0)
             tools = ...
 
             agent = create_react_agent(model, tools, prompt)
@@ -45,7 +47,6 @@ def create_react_agent(
             agent_executor.invoke({"input": "hi"})
 
             # Use with chat history
-            from langchain_core.messages import AIMessage, HumanMessage
             agent_executor.invoke(
                 {
                     "input": "what's my name?",
@@ -55,6 +56,11 @@ def create_react_agent(
                 }
             )
 
+            # Binding additional stop words to llm
+            model_with_stop = model.bind(stop=["Question"])
+            agent = create_react_agent(model_with_stop, tools, prompt)
+            ...
+            
     Prompt:
 
         The prompt must have input keys:
@@ -100,7 +106,15 @@ def create_react_agent(
         tools=render_text_description(list(tools)),
         tool_names=", ".join([t.name for t in tools]),
     )
-    llm_with_stop = llm.bind(stop=["\nObservation"])
+    if (
+        isinstance(llm, RunnableBindingBase)
+        and (stop := llm.kwargs.get("stop"))
+        and "\nObservation" not in stop
+    ):
+        stop = stop + ["\nObservation"]
+    else:
+        stop = ["\nObservation"]
+    llm_with_stop = llm.bind(stop=stop)
     agent = (
         RunnablePassthrough.assign(
             agent_scratchpad=lambda x: format_log_to_str(x["intermediate_steps"]),