diff --git a/docs/extras/expression_language/interface.ipynb b/docs/extras/expression_language/interface.ipynb
index 47a3efaf82..418bc86f60 100644
--- a/docs/extras/expression_language/interface.ipynb
+++ b/docs/extras/expression_language/interface.ipynb
@@ -8,7 +8,7 @@
     "---\n",
     "sidebar_position: 0\n",
     "title: Interface\n",
-    "---"
+    "---\n"
    ]
   },
   {
@@ -18,15 +18,16 @@
    "source": [
     "In an effort to make it as easy as possible to create custom chains, we've implemented a [\"Runnable\"](https://api.python.langchain.com/en/latest/schema/langchain.schema.runnable.Runnable.html#langchain.schema.runnable.Runnable) protocol that most components implement. This is a standard interface with a few different methods, which makes it easy to define custom chains as well as making it possible to invoke them in a standard way. The standard interface exposed includes:\n",
     "\n",
-    "- `stream`: stream back chunks of the response\n",
-    "- `invoke`: call the chain on an input\n",
-    "- `batch`: call the chain on a list of inputs\n",
+    "- [`stream`](#stream): stream back chunks of the response\n",
+    "- [`invoke`](#invoke): call the chain on an input\n",
+    "- [`batch`](#batch): call the chain on a list of inputs\n",
     "\n",
     "These also have corresponding async methods:\n",
     "\n",
-    "- `astream`: stream back chunks of the response async\n",
-    "- `ainvoke`: call the chain on an input async\n",
-    "- `abatch`: call the chain on a list of inputs async\n",
+    "- [`astream`](#async-stream): stream back chunks of the response async\n",
+    "- [`ainvoke`](#async-invoke): call the chain on an input async\n",
+    "- [`abatch`](#async-batch): call the chain on a list of inputs async\n",
+    "- [`astream_log`](#async-stream-intermediate-steps): stream back intermediate steps as they happen, in addition to the final response\n",
     "\n",
     "The type of the input varies by component:\n",
     "\n",
@@ -49,6 +50,10 @@
     "| Tool | Depends on the tool |\n",
     "| OutputParser | Depends on the parser |\n",
     "\n",
+    "All runnables expose properties to inspect the input and output types:\n",
+    "- [`input_schema`](#input-schema): an input Pydantic model auto-generated from the structure of the Runnable\n",
+    "- [`output_schema`](#output-schema): an output Pydantic model auto-generated from the structure of the Runnable\n",
+    "\n",
     "Let's take a look at these methods! To do so, we'll create a super simple PromptTemplate + ChatModel chain."
    ]
   },
@@ -60,7 +65,7 @@
    "outputs": [],
    "source": [
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.chat_models import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n"
    ]
   },
   {
@@ -70,7 +75,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = ChatOpenAI()"
+    "model = ChatOpenAI()\n"
    ]
   },
   {
@@ -80,7 +85,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "prompt = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\")"
+    "prompt = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\")\n"
    ]
   },
   {
@@ -90,7 +95,156 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "chain = prompt | model"
+    "chain = prompt | model\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5cccdf0b-2d89-4f74-9530-bf499610e9a5",
+   "metadata": {},
+   "source": [
+    "## Input Schema\n",
+    "\n",
+    "A description of the inputs accepted by a Runnable.\n",
+    "This is a Pydantic model dynamically generated from the structure of any Runnable.\n",
+    "You can call `.schema()` on it to obtain a JSONSchema representation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "25e146d4-60da-40a2-9026-b5dfee106a3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'title': 'PromptInput',\n",
+       " 'type': 'object',\n",
+       " 'properties': {'topic': {'title': 'Topic', 'type': 'string'}}}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# The input schema of the chain is the input schema of its first part, the prompt.\n",
+    "chain.input_schema.schema()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5059a5dc-d544-4add-85bd-78a3f2b78b9a",
+   "metadata": {},
+   "source": [
+    "## Output Schema\n",
+    "\n",
+    "A description of the outputs produced by a Runnable.\n",
+    "This is a Pydantic model dynamically generated from the structure of any Runnable.\n",
+    "You can call `.schema()` on it to obtain a JSONSchema representation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a0e41fd3-77d8-4911-af6a-d4d3aad5f77b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'title': 'ChatOpenAIOutput',\n",
+       " 'anyOf': [{'$ref': '#/definitions/HumanMessageChunk'},\n",
+       "  {'$ref': '#/definitions/AIMessageChunk'},\n",
+       "  {'$ref': '#/definitions/ChatMessageChunk'},\n",
+       "  {'$ref': '#/definitions/FunctionMessageChunk'},\n",
+       "  {'$ref': '#/definitions/SystemMessageChunk'}],\n",
+       " 'definitions': {'HumanMessageChunk': {'title': 'HumanMessageChunk',\n",
+       "   'description': 'A Human Message chunk.',\n",
+       "   'type': 'object',\n",
+       "   'properties': {'content': {'title': 'Content', 'type': 'string'},\n",
+       "    'additional_kwargs': {'title': 'Additional Kwargs', 'type': 'object'},\n",
+       "    'type': {'title': 'Type',\n",
+       "     'default': 'human',\n",
+       "     'enum': ['human'],\n",
+       "     'type': 'string'},\n",
+       "    'example': {'title': 'Example', 'default': False, 'type': 'boolean'},\n",
+       "    'is_chunk': {'title': 'Is Chunk',\n",
+       "     'default': True,\n",
+       "     'enum': [True],\n",
+       "     'type': 'boolean'}},\n",
+       "   'required': ['content']},\n",
+       "  'AIMessageChunk': {'title': 'AIMessageChunk',\n",
+       "   'description': 'A Message chunk from an AI.',\n",
+       "   'type': 'object',\n",
+       "   'properties': {'content': {'title': 'Content', 'type': 'string'},\n",
+       "    'additional_kwargs': {'title': 'Additional Kwargs', 'type': 'object'},\n",
+       "    'type': {'title': 'Type',\n",
+       "     'default': 'ai',\n",
+       "     'enum': ['ai'],\n",
+       "     'type': 'string'},\n",
+       "    'example': {'title': 'Example', 'default': False, 'type': 'boolean'},\n",
+       "    'is_chunk': {'title': 'Is Chunk',\n",
+       "     'default': True,\n",
+       "     'enum': [True],\n",
+       "     'type': 'boolean'}},\n",
+       "   'required': ['content']},\n",
+       "  'ChatMessageChunk': {'title': 'ChatMessageChunk',\n",
+       "   'description': 'A Chat Message chunk.',\n",
+       "   'type': 'object',\n",
+       "   'properties': {'content': {'title': 'Content', 'type': 'string'},\n",
+       "    'additional_kwargs': {'title': 'Additional Kwargs', 'type': 'object'},\n",
+       "    'type': {'title': 'Type',\n",
+       "     'default': 'chat',\n",
+       "     'enum': ['chat'],\n",
+       "     'type': 'string'},\n",
+       "    'role': {'title': 'Role', 'type': 'string'},\n",
+       "    'is_chunk': {'title': 'Is Chunk',\n",
+       "     'default': True,\n",
+       "     'enum': [True],\n",
+       "     'type': 'boolean'}},\n",
+       "   'required': ['content', 'role']},\n",
+       "  'FunctionMessageChunk': {'title': 'FunctionMessageChunk',\n",
+       "   'description': 'A Function Message chunk.',\n",
+       "   'type': 'object',\n",
+       "   'properties': {'content': {'title': 'Content', 'type': 'string'},\n",
+       "    'additional_kwargs': {'title': 'Additional Kwargs', 'type': 'object'},\n",
+       "    'type': {'title': 'Type',\n",
+       "     'default': 'function',\n",
+       "     'enum': ['function'],\n",
+       "     'type': 'string'},\n",
+       "    'name': {'title': 'Name', 'type': 'string'},\n",
+       "    'is_chunk': {'title': 'Is Chunk',\n",
+       "     'default': True,\n",
+       "     'enum': [True],\n",
+       "     'type': 'boolean'}},\n",
+       "   'required': ['content', 'name']},\n",
+       "  'SystemMessageChunk': {'title': 'SystemMessageChunk',\n",
+       "   'description': 'A System Message chunk.',\n",
+       "   'type': 'object',\n",
+       "   'properties': {'content': {'title': 'Content', 'type': 'string'},\n",
+       "    'additional_kwargs': {'title': 'Additional Kwargs', 'type': 'object'},\n",
+       "    'type': {'title': 'Type',\n",
+       "     'default': 'system',\n",
+       "     'enum': ['system'],\n",
+       "     'type': 'string'},\n",
+       "    'is_chunk': {'title': 'Is Chunk',\n",
+       "     'default': True,\n",
+       "     'enum': [True],\n",
+       "     'type': 'boolean'}},\n",
+       "   'required': ['content']}}}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# The output schema of the chain is the output schema of its last part, in this case a ChatModel, which outputs a ChatMessage\n",
+    "chain.output_schema.schema()"
    ]
   },
   {
@@ -103,7 +257,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "bea9639d",
    "metadata": {},
    "outputs": [
@@ -111,9 +265,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sure, here's a bear-themed joke for you:\n",
-      "\n",
-      "Why don't bears wear shoes?\n",
+      "Why don't bears wear shoes? \n",
       "\n",
       "Because they have bear feet!"
      ]
@@ -121,7 +273,7 @@
    ],
    "source": [
     "for s in chain.stream({\"topic\": \"bears\"}):\n",
-    "    print(s.content, end=\"\", flush=True)"
+    "    print(s.content, end=\"\", flush=True)\n"
    ]
   },
   {
@@ -134,23 +286,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "470e483f",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they already have bear feet!\", additional_kwargs={}, example=False)"
+       "AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\")"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "chain.invoke({\"topic\": \"bears\"})"
+    "chain.invoke({\"topic\": \"bears\"})\n"
    ]
   },
   {
@@ -163,24 +315,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 9,
    "id": "9685de67",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[AIMessage(content=\"Why don't bears ever wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False),\n",
-       " AIMessage(content=\"Why don't cats play poker in the wild?\\n\\nToo many cheetahs!\", additional_kwargs={}, example=False)]"
+       "[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\"),\n",
+       " AIMessage(content=\"Why don't cats play poker in the wild?\\n\\nToo many cheetahs!\")]"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}])"
+    "chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}])\n"
    ]
   },
   {
@@ -193,24 +345,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 10,
    "id": "a08522f6",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False),\n",
-       " AIMessage(content=\"Why don't cats play poker in the wild?\\n\\nToo many cheetahs!\", additional_kwargs={}, example=False)]"
+       "[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\"),\n",
+       " AIMessage(content=\"Sure, here's a cat joke for you:\\n\\nWhy don't cats play poker in the wild?\\n\\nToo many cheetahs!\")]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}], config={\"max_concurrency\": 5})"
+    "chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}], config={\"max_concurrency\": 5})\n"
    ]
   },
   {
@@ -223,7 +375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
    "id": "ea35eee4",
    "metadata": {},
    "outputs": [
@@ -231,6 +383,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Sure, here's a bear joke for you:\n",
+      "\n",
       "Why don't bears wear shoes?\n",
       "\n",
       "Because they have bear feet!"
@@ -239,7 +393,7 @@
    ],
    "source": [
     "async for s in chain.astream({\"topic\": \"bears\"}):\n",
-    "    print(s.content, end=\"\", flush=True)"
+    "    print(s.content, end=\"\", flush=True)\n"
    ]
   },
   {
@@ -252,23 +406,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 12,
    "id": "ef8c9b20",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "AIMessage(content=\"Sure, here you go:\\n\\nWhy don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False)"
+       "AIMessage(content=\"Why don't bears wear shoes? \\n\\nBecause they have bear feet!\")"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "await chain.ainvoke({\"topic\": \"bears\"})"
+    "await chain.ainvoke({\"topic\": \"bears\"})\n"
    ]
   },
   {
@@ -281,28 +435,360 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 13,
    "id": "eba2a103",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False)]"
+       "[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\")]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "await chain.abatch([{\"topic\": \"bears\"}])"
+    "await chain.abatch([{\"topic\": \"bears\"}])\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "0a1c409d",
+   "id": "f9cef104",
+   "metadata": {},
+   "source": [
+    "## Async Stream Intermediate Steps\n",
+    "\n",
+    "All runnables also have a method `.astream_log()` which can be used to stream (as they happen) all or part of the intermediate steps of your chain/sequence. \n",
+    "\n",
+    "This is useful eg. to show progress to the user, to use intermediate results, or even just to debug your chain.\n",
+    "\n",
+    "You can choose to stream all steps (default), or include/exclude steps by name, tags or metadata.\n",
+    "\n",
+    "This method yields [JSONPatch](https://jsonpatch.com) ops that when applied in the same order as received build up the RunState.\n",
+    "\n",
+    "```python\n",
+    "class LogEntry(TypedDict):\n",
+    "    id: str\n",
+    "    \"\"\"ID of the sub-run.\"\"\"\n",
+    "    name: str\n",
+    "    \"\"\"Name of the object being run.\"\"\"\n",
+    "    type: str\n",
+    "    \"\"\"Type of the object being run, eg. prompt, chain, llm, etc.\"\"\"\n",
+    "    tags: List[str]\n",
+    "    \"\"\"List of tags for the run.\"\"\"\n",
+    "    metadata: Dict[str, Any]\n",
+    "    \"\"\"Key-value pairs of metadata for the run.\"\"\"\n",
+    "    start_time: str\n",
+    "    \"\"\"ISO-8601 timestamp of when the run started.\"\"\"\n",
+    "\n",
+    "    streamed_output_str: List[str]\n",
+    "    \"\"\"List of LLM tokens streamed by this run, if applicable.\"\"\"\n",
+    "    final_output: Optional[Any]\n",
+    "    \"\"\"Final output of this run.\n",
+    "    Only available after the run has finished successfully.\"\"\"\n",
+    "    end_time: Optional[str]\n",
+    "    \"\"\"ISO-8601 timestamp of when the run ended.\n",
+    "    Only available after the run has finished.\"\"\"\n",
+    "\n",
+    "\n",
+    "class RunState(TypedDict):\n",
+    "    id: str\n",
+    "    \"\"\"ID of the run.\"\"\"\n",
+    "    streamed_output: List[Any]\n",
+    "    \"\"\"List of output chunks streamed by Runnable.stream()\"\"\"\n",
+    "    final_output: Optional[Any]\n",
+    "    \"\"\"Final output of the run, usually the result of aggregating (`+`) streamed_output.\n",
+    "    Only available after the run has finished successfully.\"\"\"\n",
+    "\n",
+    "    logs: Dict[str, LogEntry]\n",
+    "    \"\"\"Map of run names to sub-runs. If filters were supplied, this list will\n",
+    "    contain only the runs that matched the filters.\"\"\"\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a146a5df-25be-4fa2-a7e4-df8ebe55a35e",
+   "metadata": {},
+   "source": [
+    "### Streaming JSONPatch chunks\n",
+    "\n",
+    "This is useful eg. to stream the JSONPatch in an HTTP server, and then apply the ops on the client to rebuild the run state there. See [LangServe](https://github.com/langchain-ai/langserve) for tooling to make it easier to build a webserver from any Runnable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "21c9019e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RunLogPatch({'op': 'replace',\n",
+      "  'path': '',\n",
+      "  'value': {'final_output': None,\n",
+      "            'id': 'fd6fcf62-c92c-4edf-8713-0fc5df000f62',\n",
+      "            'logs': {},\n",
+      "            'streamed_output': []}})\n",
+      "RunLogPatch({'op': 'add',\n",
+      "  'path': '/logs/Docs',\n",
+      "  'value': {'end_time': None,\n",
+      "            'final_output': None,\n",
+      "            'id': '8c998257-1ec8-4546-b744-c3fdb9728c41',\n",
+      "            'metadata': {},\n",
+      "            'name': 'Docs',\n",
+      "            'start_time': '2023-10-05T12:52:35.668',\n",
+      "            'streamed_output_str': [],\n",
+      "            'tags': ['map:key:context', 'FAISS'],\n",
+      "            'type': 'retriever'}})\n",
+      "RunLogPatch({'op': 'add',\n",
+      "  'path': '/logs/Docs/final_output',\n",
+      "  'value': {'documents': [Document(page_content='harrison worked at kensho')]}},\n",
+      " {'op': 'add',\n",
+      "  'path': '/logs/Docs/end_time',\n",
+      "  'value': '2023-10-05T12:52:36.033'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': ''})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': 'H'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': 'arrison'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': ' worked'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': ' at'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': ' Kens'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': 'ho'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': '.'})\n",
+      "RunLogPatch({'op': 'add', 'path': '/streamed_output/-', 'value': ''})\n",
+      "RunLogPatch({'op': 'replace',\n",
+      "  'path': '/final_output',\n",
+      "  'value': {'output': 'Harrison worked at Kensho.'}})\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain.vectorstores import FAISS\n",
+    "\n",
+    "template = \"\"\"Answer the question based only on the following context:\n",
+    "{context}\n",
+    "\n",
+    "Question: {question}\n",
+    "\"\"\"\n",
+    "prompt = ChatPromptTemplate.from_template(template)\n",
+    "\n",
+    "vectorstore = FAISS.from_texts([\"harrison worked at kensho\"], embedding=OpenAIEmbeddings())\n",
+    "retriever = vectorstore.as_retriever()\n",
+    "\n",
+    "retrieval_chain = (\n",
+    "    {\"context\": retriever.with_config(run_name='Docs'), \"question\": RunnablePassthrough()}\n",
+    "    | prompt \n",
+    "    | model \n",
+    "    | StrOutputParser()\n",
+    ")\n",
+    "\n",
+    "async for chunk in retrieval_chain.astream_log(\"where did harrison work?\", include_names=['Docs']):\n",
+    "    print(chunk)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19570f36-7126-4fe2-b209-0cc6178b4582",
+   "metadata": {},
+   "source": [
+    "### Streaming the incremental RunState\n",
+    "\n",
+    "You can simply pass diff=False to get incremental values of RunState."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "5c26b731-b4eb-4967-a42a-dec813249ecb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {},\n",
+      " 'streamed_output': []})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': None,\n",
+      "                   'final_output': None,\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': []})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': []})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison', ' worked']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison', ' worked', ' at']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison', ' worked', ' at', ' Kens']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison', ' worked', ' at', ' Kens', 'ho']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['', 'H', 'arrison', ' worked', ' at', ' Kens', 'ho', '.']})\n",
+      "RunLog({'final_output': None,\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['',\n",
+      "                     'H',\n",
+      "                     'arrison',\n",
+      "                     ' worked',\n",
+      "                     ' at',\n",
+      "                     ' Kens',\n",
+      "                     'ho',\n",
+      "                     '.',\n",
+      "                     '']})\n",
+      "RunLog({'final_output': {'output': 'Harrison worked at Kensho.'},\n",
+      " 'id': 'f95ccb87-31f1-48ea-a51c-d2dadde44185',\n",
+      " 'logs': {'Docs': {'end_time': '2023-10-05T12:52:37.217',\n",
+      "                   'final_output': {'documents': [Document(page_content='harrison worked at kensho')]},\n",
+      "                   'id': '621597dd-d716-4532-938d-debc21a453d1',\n",
+      "                   'metadata': {},\n",
+      "                   'name': 'Docs',\n",
+      "                   'start_time': '2023-10-05T12:52:36.935',\n",
+      "                   'streamed_output_str': [],\n",
+      "                   'tags': ['map:key:context', 'FAISS'],\n",
+      "                   'type': 'retriever'}},\n",
+      " 'streamed_output': ['',\n",
+      "                     'H',\n",
+      "                     'arrison',\n",
+      "                     ' worked',\n",
+      "                     ' at',\n",
+      "                     ' Kens',\n",
+      "                     'ho',\n",
+      "                     '.',\n",
+      "                     '']})\n"
+     ]
+    }
+   ],
+   "source": [
+    "async for chunk in retrieval_chain.astream_log(\"where did harrison work?\", include_names=['Docs'], diff=False):\n",
+    "    print(chunk)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7006f1aa",
    "metadata": {},
    "source": [
     "## Parallelism\n",
@@ -313,7 +799,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "e3014c7a",
+   "id": "0a1c409d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -323,7 +809,7 @@
     "combined = RunnableMap({\n",
     "    \"joke\": chain1,\n",
     "    \"poem\": chain2,\n",
-    "})"
+    "})\n"
    ]
   },
   {
@@ -353,7 +839,7 @@
    ],
    "source": [
     "%%time\n",
-    "chain1.invoke({\"topic\": \"bears\"})"
+    "chain1.invoke({\"topic\": \"bears\"})\n"
    ]
   },
   {
@@ -383,7 +869,7 @@
    ],
    "source": [
     "%%time\n",
-    "chain2.invoke({\"topic\": \"bears\"})"
+    "chain2.invoke({\"topic\": \"bears\"})\n"
    ]
   },
   {
@@ -414,7 +900,7 @@
    ],
    "source": [
     "%%time\n",
-    "combined.invoke({\"topic\": \"bears\"})"
+    "combined.invoke({\"topic\": \"bears\"})\n"
    ]
   },
   {
@@ -442,7 +928,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,
diff --git a/libs/langchain/langchain/callbacks/tracers/base.py b/libs/langchain/langchain/callbacks/tracers/base.py
index f270a5ec55..10fd1d701f 100644
--- a/libs/langchain/langchain/callbacks/tracers/base.py
+++ b/libs/langchain/langchain/callbacks/tracers/base.py
@@ -49,7 +49,7 @@ class BaseTracer(BaseCallbackHandler, ABC):
     def _start_trace(self, run: Run) -> None:
         """Start a trace for a run."""
         if run.parent_run_id:
-            parent_run = self.run_map[str(run.parent_run_id)]
+            parent_run = self.run_map.get(str(run.parent_run_id))
             if parent_run:
                 self._add_child_run(parent_run, run)
                 parent_run.child_execution_order = max(
diff --git a/libs/langchain/langchain/callbacks/tracers/log_stream.py b/libs/langchain/langchain/callbacks/tracers/log_stream.py
index 2440d5feca..33827b5dbb 100644
--- a/libs/langchain/langchain/callbacks/tracers/log_stream.py
+++ b/libs/langchain/langchain/callbacks/tracers/log_stream.py
@@ -54,13 +54,12 @@ class RunState(TypedDict):
     streamed_output: List[Any]
     """List of output chunks streamed by Runnable.stream()"""
     final_output: Optional[Any]
-    """Final output of the run, usually the result of aggregating streamed_output.
+    """Final output of the run, usually the result of aggregating (`+`) streamed_output.
     Only available after the run has finished successfully."""
 
     logs: Dict[str, LogEntry]
-    """List of sub-runs contained in this run, if any, in the order they were started.
-    If filters were supplied, this list will contain only the runs that matched the 
-    filters."""
+    """Map of run names to sub-runs. If filters were supplied, this list will
+    contain only the runs that matched the filters."""
 
 
 class RunLogPatch:
@@ -74,7 +73,7 @@ class RunLogPatch:
     def __init__(self, *ops: Dict[str, Any]) -> None:
         self.ops = list(ops)
 
-    def __add__(self, other: Union[RunLogPatch, Any]) -> RunLogPatch:
+    def __add__(self, other: Union[RunLogPatch, Any]) -> RunLog:
         if type(other) == RunLogPatch:
             ops = self.ops + other.ops
             state = jsonpatch.apply_patch(None, ops)
@@ -102,7 +101,7 @@ class RunLog(RunLogPatch):
         super().__init__(*ops)
         self.state = state
 
-    def __add__(self, other: Union[RunLogPatch, Any]) -> RunLogPatch:
+    def __add__(self, other: Union[RunLogPatch, Any]) -> RunLog:
         if type(other) == RunLogPatch:
             ops = self.ops + other.ops
             state = jsonpatch.apply_patch(self.state, other.ops)
diff --git a/libs/langchain/langchain/schema/runnable/base.py b/libs/langchain/langchain/schema/runnable/base.py
index 57a93d8f7c..6bfef3ed44 100644
--- a/libs/langchain/langchain/schema/runnable/base.py
+++ b/libs/langchain/langchain/schema/runnable/base.py
@@ -26,16 +26,17 @@ from typing import (
     TypeVar,
     Union,
     cast,
+    overload,
 )
 
-from typing_extensions import get_args
+from typing_extensions import Literal, get_args
 
 if TYPE_CHECKING:
     from langchain.callbacks.manager import (
         AsyncCallbackManagerForChainRun,
         CallbackManagerForChainRun,
     )
-    from langchain.callbacks.tracers.log_stream import RunLogPatch
+    from langchain.callbacks.tracers.log_stream import RunLog, RunLogPatch
     from langchain.schema.runnable.fallbacks import (
         RunnableWithFallbacks as RunnableWithFallbacksT,
     )
@@ -290,11 +291,13 @@ class Runnable(Generic[Input, Output], ABC):
         """
         yield await self.ainvoke(input, config, **kwargs)
 
-    async def astream_log(
+    @overload
+    def astream_log(
         self,
         input: Any,
         config: Optional[RunnableConfig] = None,
         *,
+        diff: Literal[True] = True,
         include_names: Optional[Sequence[str]] = None,
         include_types: Optional[Sequence[str]] = None,
         include_tags: Optional[Sequence[str]] = None,
@@ -303,6 +306,39 @@ class Runnable(Generic[Input, Output], ABC):
         exclude_tags: Optional[Sequence[str]] = None,
         **kwargs: Optional[Any],
     ) -> AsyncIterator[RunLogPatch]:
+        ...
+
+    @overload
+    def astream_log(
+        self,
+        input: Any,
+        config: Optional[RunnableConfig] = None,
+        *,
+        diff: Literal[False],
+        include_names: Optional[Sequence[str]] = None,
+        include_types: Optional[Sequence[str]] = None,
+        include_tags: Optional[Sequence[str]] = None,
+        exclude_names: Optional[Sequence[str]] = None,
+        exclude_types: Optional[Sequence[str]] = None,
+        exclude_tags: Optional[Sequence[str]] = None,
+        **kwargs: Optional[Any],
+    ) -> AsyncIterator[RunLog]:
+        ...
+
+    async def astream_log(
+        self,
+        input: Any,
+        config: Optional[RunnableConfig] = None,
+        *,
+        diff: bool = True,
+        include_names: Optional[Sequence[str]] = None,
+        include_types: Optional[Sequence[str]] = None,
+        include_tags: Optional[Sequence[str]] = None,
+        exclude_names: Optional[Sequence[str]] = None,
+        exclude_types: Optional[Sequence[str]] = None,
+        exclude_tags: Optional[Sequence[str]] = None,
+        **kwargs: Optional[Any],
+    ) -> Union[AsyncIterator[RunLogPatch], AsyncIterator[RunLog]]:
         """
         Stream all output from a runnable, as reported to the callback system.
         This includes all inner runs of LLMs, Retrievers, Tools, etc.
@@ -317,6 +353,7 @@ class Runnable(Generic[Input, Output], ABC):
         from langchain.callbacks.base import BaseCallbackManager
         from langchain.callbacks.tracers.log_stream import (
             LogStreamCallbackHandler,
+            RunLog,
             RunLogPatch,
         )
 
@@ -370,8 +407,14 @@ class Runnable(Generic[Input, Output], ABC):
 
         try:
             # Yield each chunk from the output stream
-            async for log in stream:
-                yield log
+            if diff:
+                async for log in stream:
+                    yield log
+            else:
+                state = RunLog(state=None)  # type: ignore[arg-type]
+                async for log in stream:
+                    state = state + log
+                    yield state
         finally:
             # Wait for the runnable to finish, if not cancelled (eg. by break)
             try:
diff --git a/libs/langchain/langchain/schema/runnable/passthrough.py b/libs/langchain/langchain/schema/runnable/passthrough.py
index 874123c394..ce893b6a52 100644
--- a/libs/langchain/langchain/schema/runnable/passthrough.py
+++ b/libs/langchain/langchain/schema/runnable/passthrough.py
@@ -171,7 +171,9 @@ class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]):
         config: Optional[RunnableConfig] = None,
         **kwargs: Any,
     ) -> Dict[str, Any]:
-        assert isinstance(input, dict)
+        assert isinstance(
+            input, dict
+        ), "The input to RunnablePassthrough.assign() must be a dict."
         return {
             **input,
             **self.mapper.invoke(input, config, **kwargs),
@@ -183,7 +185,9 @@ class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]):
         config: Optional[RunnableConfig] = None,
         **kwargs: Any,
     ) -> Dict[str, Any]:
-        assert isinstance(input, dict)
+        assert isinstance(
+            input, dict
+        ), "The input to RunnablePassthrough.assign() must be a dict."
         return {
             **input,
             **await self.mapper.ainvoke(input, config, **kwargs),
@@ -204,10 +208,16 @@ class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]):
         # get executor to start map output stream in background
         with get_executor_for_config(config or {}) as executor:
             # start map output stream
-            first_map_chunk_future = executor.submit(next, map_output)  # type: ignore
+            first_map_chunk_future = executor.submit(
+                next,
+                map_output,  # type: ignore
+                None,
+            )
             # consume passthrough stream
             for chunk in for_passthrough:
-                assert isinstance(chunk, dict)
+                assert isinstance(
+                    chunk, dict
+                ), "The input to RunnablePassthrough.assign() must be a dict."
                 # remove mapper keys from passthrough chunk, to be overwritten by map
                 filtered = AddableDict(
                     {k: v for k, v in chunk.items() if k not in mapper_keys}
@@ -233,11 +243,13 @@ class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]):
         map_output = self.mapper.atransform(for_map, config, **kwargs)
         # start map output stream
         first_map_chunk_task: asyncio.Task = asyncio.create_task(
-            py_anext(map_output),  # type: ignore[arg-type]
+            py_anext(map_output, None),  # type: ignore[arg-type]
         )
         # consume passthrough stream
         async for chunk in for_passthrough:
-            assert isinstance(chunk, dict)
+            assert isinstance(
+                chunk, dict
+            ), "The input to RunnablePassthrough.assign() must be a dict."
             # remove mapper keys from passthrough chunk, to be overwritten by map output
             filtered = AddableDict(
                 {k: v for k, v in chunk.items() if k not in mapper_keys}
diff --git a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py
index 680df3c4d3..81da3b0c97 100644
--- a/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py
+++ b/libs/langchain/tests/unit_tests/schema/runnable/test_runnable.py
@@ -1260,6 +1260,42 @@ async def test_prompt() -> None:
         RunLogPatch({"op": "add", "path": "/streamed_output/-", "value": expected}),
     ]
 
+    stream_log_state = [
+        part
+        async for part in prompt.astream_log(
+            {"question": "What is your name?"}, diff=False
+        )
+    ]
+
+    # remove random id
+    stream_log[0].ops[0]["value"]["id"] = "00000000-0000-0000-0000-000000000000"
+    stream_log_state[-1].ops[0]["value"]["id"] = "00000000-0000-0000-0000-000000000000"
+    stream_log_state[-1].state["id"] = "00000000-0000-0000-0000-000000000000"
+
+    # assert output with diff=False matches output with diff=True
+    assert stream_log_state[-1].ops == [op for chunk in stream_log for op in chunk.ops]
+    assert stream_log_state[-1] == RunLog(
+        *[op for chunk in stream_log for op in chunk.ops],
+        state={
+            "final_output": ChatPromptValue(
+                messages=[
+                    SystemMessage(content="You are a nice assistant."),
+                    HumanMessage(content="What is your name?"),
+                ]
+            ),
+            "id": "00000000-0000-0000-0000-000000000000",
+            "logs": {},
+            "streamed_output": [
+                ChatPromptValue(
+                    messages=[
+                        SystemMessage(content="You are a nice assistant."),
+                        HumanMessage(content="What is your name?"),
+                    ]
+                )
+            ],
+        },
+    )
+
 
 def test_prompt_template_params() -> None:
     prompt = ChatPromptTemplate.from_template(