Merge branch 'master' into add-run-id-in-chain

Signed-off-by: HoangNguyen689 <ndhoang.bk.hedspi@gmail.com>

libs/langchain/langchain/agents/agent.py

@@ -1,4 +1,5 @@
 """Chain that takes in an input and produces an action and action input."""
+
 from __future__ import annotations
 
 import asyncio
@@ -346,11 +347,11 @@ class RunnableAgent(BaseSingleActionAgent):
     input_keys_arg: List[str] = []
     return_keys_arg: List[str] = []
     stream_runnable: bool = True
-    """Whether to stream from the runnable or not. 
+    """Whether to stream from the runnable or not.
 
-    If True then underlying LLM is invoked in a streaming fashion to make it possible 
-        to get access to the individual LLM tokens when using stream_log with the Agent 
-        Executor. If False then LLM is invoked in a non-streaming fashion and 
+    If True then underlying LLM is invoked in a streaming fashion to make it possible
+        to get access to the individual LLM tokens when using stream_log with the Agent
+        Executor. If False then LLM is invoked in a non-streaming fashion and
         individual LLM tokens will not be available in stream_log.
     """
 
@@ -455,11 +456,11 @@ class RunnableMultiActionAgent(BaseMultiActionAgent):
     input_keys_arg: List[str] = []
     return_keys_arg: List[str] = []
     stream_runnable: bool = True
-    """Whether to stream from the runnable or not. 
-    
-    If True then underlying LLM is invoked in a streaming fashion to make it possible 
-        to get access to the individual LLM tokens when using stream_log with the Agent 
-        Executor. If False then LLM is invoked in a non-streaming fashion and 
+    """Whether to stream from the runnable or not.
+
+    If True then underlying LLM is invoked in a streaming fashion to make it possible
+        to get access to the individual LLM tokens when using stream_log with the Agent
+        Executor. If False then LLM is invoked in a non-streaming fashion and
         individual LLM tokens will not be available in stream_log.
     """
 
@@ -926,7 +927,7 @@ class AgentExecutor(Chain):
     max_iterations: Optional[int] = 15
     """The maximum number of steps to take before ending the execution
     loop.
-    
+
     Setting to 'None' could lead to an infinite loop."""
     max_execution_time: Optional[float] = None
     """The maximum amount of wall clock time to spend in the execution
@@ -938,7 +939,7 @@ class AgentExecutor(Chain):
 
     `"force"` returns a string saying that it stopped because it met a
         time or iteration limit.
-    
+
     `"generate"` calls the agent's LLM Chain one final time to generate
         a final answer based on the previous steps.
     """
@@ -1565,6 +1566,7 @@ class AgentExecutor(Chain):
             tags=config.get("tags"),
             metadata=config.get("metadata"),
             run_name=config.get("run_name"),
+            run_id=config.get("run_id"),
             yield_actions=True,
             **kwargs,
         )
@@ -1586,6 +1588,7 @@ class AgentExecutor(Chain):
             tags=config.get("tags"),
             metadata=config.get("metadata"),
             run_name=config.get("run_name"),
+            run_id=config.get("run_id"),
             yield_actions=True,
             **kwargs,
         )

libs/langchain/langchain/agents/agent_iterator.py

@@ -14,6 +14,7 @@ from typing import (
     Tuple,
     Union,
 )
+from uuid import UUID
 
 from langchain_core.agents import (
     AgentAction,
@@ -54,6 +55,7 @@ class AgentExecutorIterator:
         tags: Optional[list[str]] = None,
         metadata: Optional[Dict[str, Any]] = None,
         run_name: Optional[str] = None,
+        run_id: Optional[UUID] = None,
         include_run_info: bool = False,
         yield_actions: bool = False,
     ):
@@ -67,6 +69,7 @@ class AgentExecutorIterator:
         self.tags = tags
         self.metadata = metadata
         self.run_name = run_name
+        self.run_id = run_id
         self.include_run_info = include_run_info
         self.yield_actions = yield_actions
         self.reset()
@@ -76,6 +79,7 @@ class AgentExecutorIterator:
     tags: Optional[list[str]]
     metadata: Optional[Dict[str, Any]]
     run_name: Optional[str]
+    run_id: Optional[UUID]
     include_run_info: bool
     yield_actions: bool
 
@@ -162,6 +166,7 @@ class AgentExecutorIterator:
         run_manager = callback_manager.on_chain_start(
             dumpd(self.agent_executor),
             self.inputs,
+            self.run_id,
             name=self.run_name,
         )
         try:
@@ -227,6 +232,7 @@ class AgentExecutorIterator:
         run_manager = await callback_manager.on_chain_start(
             dumpd(self.agent_executor),
             self.inputs,
+            self.run_id,
             name=self.run_name,
         )
         try:

libs/langchain/langchain/chains/base.py

@@ -1,4 +1,5 @@
 """Base interface that all chains should implement."""
+
 import inspect
 import json
 import logging
@@ -127,6 +128,7 @@ class Chain(RunnableSerializable[Dict[str, Any], Dict[str, Any]], ABC):
         tags = config.get("tags")
         metadata = config.get("metadata")
         run_name = config.get("run_name") or self.get_name()
+        run_id = config.get("run_id")
         include_run_info = kwargs.get("include_run_info", False)
         return_only_outputs = kwargs.get("return_only_outputs", False)
 
@@ -145,6 +147,7 @@ class Chain(RunnableSerializable[Dict[str, Any], Dict[str, Any]], ABC):
         run_manager = callback_manager.on_chain_start(
             dumpd(self),
             inputs,
+            run_id,
             name=run_name,
         )
         try:
@@ -178,6 +181,7 @@ class Chain(RunnableSerializable[Dict[str, Any], Dict[str, Any]], ABC):
         tags = config.get("tags")
         metadata = config.get("metadata")
         run_name = config.get("run_name") or self.get_name()
+        run_id = config.get("run_id")
         include_run_info = kwargs.get("include_run_info", False)
         return_only_outputs = kwargs.get("return_only_outputs", False)
 
@@ -195,6 +199,7 @@ class Chain(RunnableSerializable[Dict[str, Any], Dict[str, Any]], ABC):
         run_manager = await callback_manager.on_chain_start(
             dumpd(self),
             inputs,
+            run_id,
             name=run_name,
         )
         try: