github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-08-09 13:00:34 +00:00
Code Issues Packages Projects Releases Wiki Activity

refactor: remove references to unsupported model claude-3-sonnet-20240229 (#32281)

Browse Source 
Addresses some (but not all) test issues brought about in #32280
This commit is contained in:
Mason Daugherty 2025-07-28 11:57:43 -04:00 committed by GitHub
parent f0b6baa0ef
commit a07d2c5016
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
20 changed files with 323 additions and 418 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
cookbook/tool_call_messages.ipynb
View File

@ -34,7 +34,7 @@
"tools = [multiply, exponentiate, add]\n",
"\n",
"gpt35 = ChatOpenAI(model=\"gpt-3.5-turbo-0125\", temperature=0).bind_tools(tools)\n",
"claude3 = ChatAnthropic(model=\"claude-3-sonnet-20240229\").bind_tools(tools)\n",
"claude3 = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\").bind_tools(tools)\n",
"llm_with_tools = gpt35.configurable_alternatives(\n",
" ConfigurableField(id=\"llm\"), default_key=\"gpt35\", claude3=claude3\n",
")"
@ -113,14 +113,15 @@
{
"data": {
"text/plain": [
"{'messages': [HumanMessage(content=\"what's 3 plus 5 raised to the 2.743. also what's 17.24 - 918.1241\"),\n",
" AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_6yMU2WsS4Bqgi1WxFHxtfJRc', 'function': {'arguments': '{\"x\": 8, \"y\": 2.743}', 'name': 'exponentiate'}, 'type': 'function'}, {'id': 'call_GAL3dQiKFF9XEV0RrRLPTvVp', 'function': {'arguments': '{\"x\": 17.24, \"y\": -918.1241}', 'name': 'add'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 58, 'prompt_tokens': 168, 'total_tokens': 226}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': 'fp_b28b39ffa8', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-528302fc-7acf-4c11-82c4-119ccf40c573-0', tool_calls=[{'name': 'exponentiate', 'args': {'x': 8, 'y': 2.743}, 'id': 'call_6yMU2WsS4Bqgi1WxFHxtfJRc'}, {'name': 'add', 'args': {'x': 17.24, 'y': -918.1241}, 'id': 'call_GAL3dQiKFF9XEV0RrRLPTvVp'}]),\n",
" ToolMessage(content='300.03770462067547', tool_call_id='call_6yMU2WsS4Bqgi1WxFHxtfJRc'),\n",
" ToolMessage(content='-900.8841', tool_call_id='call_GAL3dQiKFF9XEV0RrRLPTvVp'),\n",
" AIMessage(content='The result of \\\\(3 + 5^{2.743}\\\\) is approximately 300.04, and the result of \\\\(17.24 - 918.1241\\\\) is approximately -900.88.', response_metadata={'token_usage': {'completion_tokens': 44, 'prompt_tokens': 251, 'total_tokens': 295}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': 'fp_b28b39ffa8', 'finish_reason': 'stop', 'logprobs': None}, id='run-d1161669-ed09-4b18-94bd-6d8530df5aa8-0')]}"
"{'messages': [HumanMessage(content=\"what's 3 plus 5 raised to the 2.743. also what's 17.24 - 918.1241\", additional_kwargs={}, response_metadata={}),\n",
" AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_xuNXwm2P6U2Pp2pAbC1sdIBz', 'function': {'arguments': '{\"x\": 3, \"y\": 5}', 'name': 'add'}, 'type': 'function'}, {'id': 'call_0pImUJUDlYa5zfBcxxuvWyYS', 'function': {'arguments': '{\"x\": 8, \"y\": 2.743}', 'name': 'exponentiate'}, 'type': 'function'}, {'id': 'call_yaownQ9TZK0dkqD1KSFyax4H', 'function': {'arguments': '{\"x\": 17.24, \"y\": -918.1241}', 'name': 'add'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 75, 'prompt_tokens': 131, 'total_tokens': 206, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'id': 'chatcmpl-ByJm2qxSWU3oTTSZQv64J4XQKZhA6', 'service_tier': 'default', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run--35fad027-47f7-44d3-aa8b-99f4fc24098c-0', tool_calls=[{'name': 'add', 'args': {'x': 3, 'y': 5}, 'id': 'call_xuNXwm2P6U2Pp2pAbC1sdIBz', 'type': 'tool_call'}, {'name': 'exponentiate', 'args': {'x': 8, 'y': 2.743}, 'id': 'call_0pImUJUDlYa5zfBcxxuvWyYS', 'type': 'tool_call'}, {'name': 'add', 'args': {'x': 17.24, 'y': -918.1241}, 'id': 'call_yaownQ9TZK0dkqD1KSFyax4H', 'type': 'tool_call'}], usage_metadata={'input_tokens': 131, 'output_tokens': 75, 'total_tokens': 206, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}}),\n",
" ToolMessage(content='8.0', tool_call_id='call_xuNXwm2P6U2Pp2pAbC1sdIBz'),\n",
" ToolMessage(content='300.03770462067547', tool_call_id='call_0pImUJUDlYa5zfBcxxuvWyYS'),\n",
" ToolMessage(content='-900.8841', tool_call_id='call_yaownQ9TZK0dkqD1KSFyax4H'),\n",
" AIMessage(content='The results are:\\n1. 3 plus 5 is 8.\\n2. 5 raised to the power of 2.743 is approximately 300.04.\\n3. 17.24 minus 918.1241 is approximately -900.88.', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 55, 'prompt_tokens': 236, 'total_tokens': 291, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-3.5-turbo-0125', 'system_fingerprint': None, 'id': 'chatcmpl-ByJm345MYnpowGS90iAZAlSs7haed', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--5fa66d47-d80e-45d0-9c32-31348c735d72-0', usage_metadata={'input_tokens': 236, 'output_tokens': 55, 'total_tokens': 291, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}"
]
},
"execution_count": 4,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@ -146,17 +147,17 @@
{
"data": {
"text/plain": [
"{'messages': [HumanMessage(content=\"what's 3 plus 5 raised to the 2.743. also what's 17.24 - 918.1241\"),\n",
" AIMessage(content=[{'text': \"Okay, let's break this down into two parts:\", 'type': 'text'}, {'id': 'toolu_01DEhqcXkXTtzJAiZ7uMBeDC', 'input': {'x': 3, 'y': 5}, 'name': 'add', 'type': 'tool_use'}], response_metadata={'id': 'msg_01AkLGH8sxMHaH15yewmjwkF', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 450, 'output_tokens': 81}}, id='run-f35bfae8-8ded-4f8a-831b-0940d6ad16b6-0', tool_calls=[{'name': 'add', 'args': {'x': 3, 'y': 5}, 'id': 'toolu_01DEhqcXkXTtzJAiZ7uMBeDC'}]),\n",
" ToolMessage(content='8.0', tool_call_id='toolu_01DEhqcXkXTtzJAiZ7uMBeDC'),\n",
" AIMessage(content=[{'id': 'toolu_013DyMLrvnrto33peAKMGMr1', 'input': {'x': 8.0, 'y': 2.743}, 'name': 'exponentiate', 'type': 'tool_use'}], response_metadata={'id': 'msg_015Fmp8aztwYcce2JDAFfce3', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 545, 'output_tokens': 75}}, id='run-48aaeeeb-a1e5-48fd-a57a-6c3da2907b47-0', tool_calls=[{'name': 'exponentiate', 'args': {'x': 8.0, 'y': 2.743}, 'id': 'toolu_013DyMLrvnrto33peAKMGMr1'}]),\n",
" ToolMessage(content='300.03770462067547', tool_call_id='toolu_013DyMLrvnrto33peAKMGMr1'),\n",
" AIMessage(content=[{'text': 'So 3 plus 5 raised to the 2.743 power is 300.04.\\n\\nFor the second part:', 'type': 'text'}, {'id': 'toolu_01UTmMrGTmLpPrPCF1rShN46', 'input': {'x': 17.24, 'y': -918.1241}, 'name': 'add', 'type': 'tool_use'}], response_metadata={'id': 'msg_015TkhfRBENPib2RWAxkieH6', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'input_tokens': 638, 'output_tokens': 105}}, id='run-45fb62e3-d102-4159-881d-241c5dbadeed-0', tool_calls=[{'name': 'add', 'args': {'x': 17.24, 'y': -918.1241}, 'id': 'toolu_01UTmMrGTmLpPrPCF1rShN46'}]),\n",
" ToolMessage(content='-900.8841', tool_call_id='toolu_01UTmMrGTmLpPrPCF1rShN46'),\n",
" AIMessage(content='Therefore, 17.24 - 918.1241 = -900.8841', response_metadata={'id': 'msg_01LgKnRuUcSyADCpxv9tPoYD', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 759, 'output_tokens': 24}}, id='run-1008254e-ccd1-497c-8312-9550dd77bd08-0')]}"
"{'messages': [HumanMessage(content=\"what's 3 plus 5 raised to the 2.743. also what's 17.24 - 918.1241\", additional_kwargs={}, response_metadata={}),\n",
" AIMessage(content=[{'text': \"I'll solve these calculations for you.\\n\\nFor the first part, I need to calculate 3 plus 5 raised to the power of 2.743.\\n\\nLet me break this down:\\n1) First, I'll calculate 5 raised to the power of 2.743\\n2) Then add 3 to the result\", 'type': 'text'}, {'id': 'toolu_01L1mXysBQtpPLQ2AZTaCGmE', 'input': {'x': 5, 'y': 2.743}, 'name': 'exponentiate', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01HCbDmuzdg9ATMyKbnecbEE', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 563, 'output_tokens': 146, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--9f6469fb-bcbb-4c1c-9eec-79f6979c38e6-0', tool_calls=[{'name': 'exponentiate', 'args': {'x': 5, 'y': 2.743}, 'id': 'toolu_01L1mXysBQtpPLQ2AZTaCGmE', 'type': 'tool_call'}], usage_metadata={'input_tokens': 563, 'output_tokens': 146, 'total_tokens': 709, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}),\n",
" ToolMessage(content='82.65606421491815', tool_call_id='toolu_01L1mXysBQtpPLQ2AZTaCGmE'),\n",
" AIMessage(content=[{'text': \"Now I'll add 3 to this result:\", 'type': 'text'}, {'id': 'toolu_01NARC83e9obV35mZ6jYzBiN', 'input': {'x': 3, 'y': 82.65606421491815}, 'name': 'add', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01ELwyCtVLeGC685PUFqmdz2', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 727, 'output_tokens': 87, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--d5af3d7c-e8b7-4cc2-997a-ad2dafd08751-0', tool_calls=[{'name': 'add', 'args': {'x': 3, 'y': 82.65606421491815}, 'id': 'toolu_01NARC83e9obV35mZ6jYzBiN', 'type': 'tool_call'}], usage_metadata={'input_tokens': 727, 'output_tokens': 87, 'total_tokens': 814, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}),\n",
" ToolMessage(content='85.65606421491815', tool_call_id='toolu_01NARC83e9obV35mZ6jYzBiN'),\n",
" AIMessage(content=[{'text': \"For the second part, you asked for 17.24 - 918.1241. I don't have a subtraction function available, but I can rewrite this as adding a negative number: 17.24 + (-918.1241)\", 'type': 'text'}, {'id': 'toolu_01Q6fLcZkBWZpMPCZ55WXR3N', 'input': {'x': 17.24, 'y': -918.1241}, 'name': 'add', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01WkmDwUxWjjaKGnTtdLGJnN', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 832, 'output_tokens': 130, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--39a6fbda-4c81-47a6-b361-524bd4ee5823-0', tool_calls=[{'name': 'add', 'args': {'x': 17.24, 'y': -918.1241}, 'id': 'toolu_01Q6fLcZkBWZpMPCZ55WXR3N', 'type': 'tool_call'}], usage_metadata={'input_tokens': 832, 'output_tokens': 130, 'total_tokens': 962, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}),\n",
" ToolMessage(content='-900.8841', tool_call_id='toolu_01Q6fLcZkBWZpMPCZ55WXR3N'),\n",
" AIMessage(content='So, the answers are:\\n1) 3 plus 5 raised to the 2.743 = 85.65606421491815\\n2) 17.24 - 918.1241 = -900.8841', additional_kwargs={}, response_metadata={'id': 'msg_015Yoc62CvdJbANGFouiQ6AQ', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 978, 'output_tokens': 58, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--174c0882-6180-47ea-8f63-d7b747302327-0', usage_metadata={'input_tokens': 978, 'output_tokens': 58, 'total_tokens': 1036, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}"
]
},
"execution_count": 5,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -177,7 +178,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -191,7 +192,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
"version": "3.10.16"
}
},
"nbformat": 4,

14
docs/docs/concepts/streaming.mdx
View File

@ -52,7 +52,7 @@ In addition, there is a **legacy** async [astream_log](https://python.langchain.
The `stream()` method returns an iterator that yields chunks of output synchronously as they are produced. You can use a `for` loop to process each chunk in real-time. For example, when using an LLM, this allows the output to be streamed incrementally as it is generated, reducing the wait time for users.
The type of chunk yielded by the `stream()` and `astream()` methods depends on the component being streamed. For example, when streaming from an [LLM](/docs/concepts/chat_models) each component will be an [AIMessageChunk](/docs/concepts/messages#aimessagechunk); however, for other components, the chunk may be different.
The type of chunk yielded by the `stream()` and `astream()` methods depends on the component being streamed. For example, when streaming from an [LLM](/docs/concepts/chat_models) each component will be an [AIMessageChunk](/docs/concepts/messages#aimessagechunk); however, for other components, the chunk may be different.
The `stream()` method returns an iterator that yields these chunks as they are produced. For example,
@ -99,7 +99,7 @@ If you compose multiple Runnables using [LangChain’s Expression Language (LCEL
<span data-heading-keywords="astream_events,stream_events,stream events"></span>
:::tip
Use the `astream_events` API to access custom data and intermediate outputs from LLM applications built entirely with [LCEL](/docs/concepts/lcel).
Use the `astream_events` API to access custom data and intermediate outputs from LLM applications built entirely with [LCEL](/docs/concepts/lcel).
While this API is available for use with [LangGraph](/docs/concepts/architecture#langgraph) as well, it is usually not necessary when working with LangGraph, as the `stream` and `astream` methods provide comprehensive streaming capabilities for LangGraph graphs.
:::
@ -119,7 +119,7 @@ from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_anthropic import ChatAnthropic
model = ChatAnthropic(model="claude-3-sonnet-20240229")
model = ChatAnthropic(model="claude-3-7-sonnet-20250219")
prompt = ChatPromptTemplate.from_template("tell me a joke about {topic}")
parser = StrOutputParser()
@ -148,7 +148,7 @@ LangChain simplifies streaming from [chat models](/docs/concepts/chat_models) by
### How It Works
When you call the `invoke` (or `ainvoke`) method on a chat model, LangChain will automatically switch to streaming mode if it detects that you are trying to stream the overall application.
When you call the `invoke` (or `ainvoke`) method on a chat model, LangChain will automatically switch to streaming mode if it detects that you are trying to stream the overall application.
Under the hood, it'll have `invoke` (or `ainvoke`) use the `stream` (or `astream`) method to generate its output. The result of the invocation will be the same as far as the code that was using `invoke` is concerned; however, while the chat model is being streamed, LangChain will take care of invoking `on_llm_new_token` events in LangChain's [callback system](/docs/concepts/callbacks). These callback events
allow LangGraph `stream`/`astream` and `astream_events` to surface the chat model's output in real-time.
@ -158,14 +158,14 @@ Example:
```python
def node(state):
...
# The code below uses the invoke method, but LangChain will
# The code below uses the invoke method, but LangChain will
# automatically switch to streaming mode
# when it detects that the overall
# when it detects that the overall
# application is being streamed.
ai_message = model.invoke(state["messages"])
...
for chunk in compiled_graph.stream(..., mode="messages"):
for chunk in compiled_graph.stream(..., mode="messages"):
...
```
## Async Programming

39
docs/docs/how_to/callbacks_async.ipynb
View File

@ -56,32 +56,13 @@
"text": [
"zzzz....\n",
"Hi! I just woke up. Your llm is starting\n",
"Sync handler being called in a `thread_pool_executor`: token: Here\n",
"Sync handler being called in a `thread_pool_executor`: token: 's\n",
"Sync handler being called in a `thread_pool_executor`: token: a\n",
"Sync handler being called in a `thread_pool_executor`: token: little\n",
"Sync handler being called in a `thread_pool_executor`: token: joke\n",
"Sync handler being called in a `thread_pool_executor`: token: for\n",
"Sync handler being called in a `thread_pool_executor`: token: you\n",
"Sync handler being called in a `thread_pool_executor`: token: :\n",
"Sync handler being called in a `thread_pool_executor`: token: \n",
"Sync handler being called in a `thread_pool_executor`: token: Why\n",
"Sync handler being called in a `thread_pool_executor`: token: don't scientists trust atoms?\n",
"\n",
"Why\n",
"Sync handler being called in a `thread_pool_executor`: token: can\n",
"Sync handler being called in a `thread_pool_executor`: token: 't\n",
"Sync handler being called in a `thread_pool_executor`: token: a\n",
"Sync handler being called in a `thread_pool_executor`: token: bicycle\n",
"Sync handler being called in a `thread_pool_executor`: token: stan\n",
"Sync handler being called in a `thread_pool_executor`: token: d up\n",
"Sync handler being called in a `thread_pool_executor`: token: by\n",
"Sync handler being called in a `thread_pool_executor`: token: itself\n",
"Sync handler being called in a `thread_pool_executor`: token: ?\n",
"Sync handler being called in a `thread_pool_executor`: token: Because\n",
"Sync handler being called in a `thread_pool_executor`: token: it\n",
"Sync handler being called in a `thread_pool_executor`: token: 's\n",
"Sync handler being called in a `thread_pool_executor`: token: two\n",
"Sync handler being called in a `thread_pool_executor`: token: -\n",
"Sync handler being called in a `thread_pool_executor`: token: tire\n",
"Because they make up\n",
"Sync handler being called in a `thread_pool_executor`: token: everything!\n",
"Sync handler being called in a `thread_pool_executor`: token: \n",
"zzzz....\n",
"Hi! I just woke up. Your llm is ending\n"
]
@ -89,10 +70,10 @@
{
"data": {
"text/plain": [
"LLMResult(generations=[[ChatGeneration(text=\"Here's a little joke for you:\\n\\nWhy can't a bicycle stand up by itself? Because it's two-tire\", message=AIMessage(content=\"Here's a little joke for you:\\n\\nWhy can't a bicycle stand up by itself? Because it's two-tire\", id='run-8afc89e8-02c0-4522-8480-d96977240bd4-0'))]], llm_output={}, run=[RunInfo(run_id=UUID('8afc89e8-02c0-4522-8480-d96977240bd4'))])"
"LLMResult(generations=[[ChatGeneration(text=\"Why don't scientists trust atoms?\\n\\nBecause they make up everything!\", message=AIMessage(content=\"Why don't scientists trust atoms?\\n\\nBecause they make up everything!\", additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None}, id='run--a596349d-8a7c-45fe-8691-bb1f9cfd6c08-0', usage_metadata={'input_tokens': 11, 'output_tokens': 17, 'total_tokens': 28, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}}))]], llm_output={}, run=[RunInfo(run_id=UUID('a596349d-8a7c-45fe-8691-bb1f9cfd6c08'))], type='LLMResult')"
]
},
"execution_count": 2,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
@ -134,7 +115,7 @@
"# To enable streaming, we pass in `streaming=True` to the ChatModel constructor\n",
"# Additionally, we pass in a list with our custom handler\n",
"chat = ChatAnthropic(\n",
" model=\"claude-3-sonnet-20240229\",\n",
" model=\"claude-3-7-sonnet-20250219\",\n",
" max_tokens=25,\n",
" streaming=True,\n",
" callbacks=[MyCustomSyncHandler(), MyCustomAsyncHandler()],\n",
@ -157,7 +138,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -171,7 +152,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.6"
"version": "3.10.16"
}
},
"nbformat": 4,

22
docs/docs/how_to/callbacks_attach.ipynb
View File

@ -49,22 +49,28 @@
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Error in LoggingHandler.on_chain_start callback: AttributeError(\"'NoneType' object has no attribute 'get'\")\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Chain RunnableSequence started\n",
"Chain ChatPromptTemplate started\n",
"Chain ended, outputs: messages=[HumanMessage(content='What is 1 + 2?')]\n",
"Chain ended, outputs: messages=[HumanMessage(content='What is 1 + 2?', additional_kwargs={}, response_metadata={})]\n",
"Chat model started\n",
"Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0'))]] llm_output={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} run=None\n",
"Chain ended, outputs: content='1 + 2 = 3' response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0'\n"
"Chat model ended, response: generations=[[ChatGeneration(text='The sum of 1 + 2 is 3.', message=AIMessage(content='The sum of 1 + 2 is 3.', additional_kwargs={}, response_metadata={'id': 'msg_01F1qPrmBD9igfzHdqVipmKX', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 17, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--71edddf3-2474-42dc-ad43-fadb4882c3c8-0', usage_metadata={'input_tokens': 16, 'output_tokens': 17, 'total_tokens': 33, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}))]] llm_output={'id': 'msg_01F1qPrmBD9igfzHdqVipmKX', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 17, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'} run=None type='LLMResult'\n",
"Chain ended, outputs: content='The sum of 1 + 2 is 3.' additional_kwargs={} response_metadata={'id': 'msg_01F1qPrmBD9igfzHdqVipmKX', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 17, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'} id='run--71edddf3-2474-42dc-ad43-fadb4882c3c8-0' usage_metadata={'input_tokens': 16, 'output_tokens': 17, 'total_tokens': 33, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0')"
"AIMessage(content='The sum of 1 + 2 is 3.', additional_kwargs={}, response_metadata={'id': 'msg_01F1qPrmBD9igfzHdqVipmKX', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 17, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--71edddf3-2474-42dc-ad43-fadb4882c3c8-0', usage_metadata={'input_tokens': 16, 'output_tokens': 17, 'total_tokens': 33, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 1,
@ -101,7 +107,7 @@
"\n",
"\n",
"callbacks = [LoggingHandler()]\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\")\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\")\n",
"prompt = ChatPromptTemplate.from_template(\"What is 1 + {number}?\")\n",
"\n",
"chain = prompt | llm\n",
@ -127,7 +133,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -141,7 +147,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.16"
}
},
"nbformat": 4,

12
docs/docs/how_to/callbacks_constructor.ipynb
View File

@ -52,16 +52,16 @@
"output_type": "stream",
"text": [
"Chat model started\n",
"Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01CdKsRmeS9WRb8BWnHDEHm7', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-2d7fdf2a-7405-4e17-97c0-67e6b2a65305-0'))]] llm_output={'id': 'msg_01CdKsRmeS9WRb8BWnHDEHm7', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} run=None\n"
"Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', additional_kwargs={}, response_metadata={'id': 'msg_01DQMbSk263KpY2vouHM5gsC', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--ab896e4e-c3fd-48b1-a41a-b6b525cbc041-0', usage_metadata={'input_tokens': 16, 'output_tokens': 13, 'total_tokens': 29, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}))]] llm_output={'id': 'msg_01DQMbSk263KpY2vouHM5gsC', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'} run=None type='LLMResult'\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01CdKsRmeS9WRb8BWnHDEHm7', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-2d7fdf2a-7405-4e17-97c0-67e6b2a65305-0')"
"AIMessage(content='1 + 2 = 3', additional_kwargs={}, response_metadata={'id': 'msg_01DQMbSk263KpY2vouHM5gsC', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--ab896e4e-c3fd-48b1-a41a-b6b525cbc041-0', usage_metadata={'input_tokens': 16, 'output_tokens': 13, 'total_tokens': 29, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 18,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
@ -95,7 +95,7 @@
"\n",
"\n",
"callbacks = [LoggingHandler()]\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", callbacks=callbacks)\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", callbacks=callbacks)\n",
"prompt = ChatPromptTemplate.from_template(\"What is 1 + {number}?\")\n",
"\n",
"chain = prompt | llm\n",
@ -119,7 +119,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -133,7 +133,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.16"
}
},
"nbformat": 4,

24
docs/docs/how_to/callbacks_runtime.ipynb
View File

@ -42,25 +42,31 @@
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Error in LoggingHandler.on_chain_start callback: AttributeError(\"'NoneType' object has no attribute 'get'\")\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Chain RunnableSequence started\n",
"Chain ChatPromptTemplate started\n",
"Chain ended, outputs: messages=[HumanMessage(content='What is 1 + 2?')]\n",
"Chain ended, outputs: messages=[HumanMessage(content='What is 1 + 2?', additional_kwargs={}, response_metadata={})]\n",
"Chat model started\n",
"Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01D8Tt5FdtBk5gLTfBPm2tac', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-bb0dddd8-85f3-4e6b-8553-eaa79f859ef8-0'))]] llm_output={'id': 'msg_01D8Tt5FdtBk5gLTfBPm2tac', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} run=None\n",
"Chain ended, outputs: content='1 + 2 = 3' response_metadata={'id': 'msg_01D8Tt5FdtBk5gLTfBPm2tac', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} id='run-bb0dddd8-85f3-4e6b-8553-eaa79f859ef8-0'\n"
"Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', additional_kwargs={}, response_metadata={'id': 'msg_019ieJt8K32iC77qBbQmSa9m', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--2f596356-99c9-45ef-94ff-fb170072abdf-0', usage_metadata={'input_tokens': 16, 'output_tokens': 13, 'total_tokens': 29, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}))]] llm_output={'id': 'msg_019ieJt8K32iC77qBbQmSa9m', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'} run=None type='LLMResult'\n",
"Chain ended, outputs: content='1 + 2 = 3' additional_kwargs={} response_metadata={'id': 'msg_019ieJt8K32iC77qBbQmSa9m', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'} id='run--2f596356-99c9-45ef-94ff-fb170072abdf-0' usage_metadata={'input_tokens': 16, 'output_tokens': 13, 'total_tokens': 29, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}}\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01D8Tt5FdtBk5gLTfBPm2tac', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-bb0dddd8-85f3-4e6b-8553-eaa79f859ef8-0')"
"AIMessage(content='1 + 2 = 3', additional_kwargs={}, response_metadata={'id': 'msg_019ieJt8K32iC77qBbQmSa9m', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--2f596356-99c9-45ef-94ff-fb170072abdf-0', usage_metadata={'input_tokens': 16, 'output_tokens': 13, 'total_tokens': 29, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 4,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
@ -94,7 +100,7 @@
"\n",
"\n",
"callbacks = [LoggingHandler()]\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\")\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\")\n",
"prompt = ChatPromptTemplate.from_template(\"What is 1 + {number}?\")\n",
"\n",
"chain = prompt | llm\n",
@ -118,7 +124,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -132,7 +138,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.5"
"version": "3.10.16"
}
},
"nbformat": 4,

36
docs/docs/how_to/custom_callbacks.ipynb
View File

@ -49,33 +49,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
"My custom handler, token: Here\n",
"My custom handler, token: 's\n",
"My custom handler, token: a\n",
"My custom handler, token: bear\n",
"My custom handler, token: joke\n",
"My custom handler, token: for\n",
"My custom handler, token: you\n",
"My custom handler, token: :\n",
"My custom handler, token: \n",
"My custom handler, token: Why\n",
"My custom handler, token: don't bears wear shoes?\n",
"\n",
"Why\n",
"My custom handler, token: di\n",
"My custom handler, token: d the\n",
"My custom handler, token: bear\n",
"My custom handler, token: dissol\n",
"My custom handler, token: ve\n",
"My custom handler, token: in\n",
"My custom handler, token: water\n",
"My custom handler, token: ?\n",
"My custom handler, token: \n",
"Because\n",
"My custom handler, token: it\n",
"My custom handler, token: was\n",
"My custom handler, token: a\n",
"My custom handler, token: polar\n",
"My custom handler, token: bear\n",
"My custom handler, token: !\n"
"Because they\n",
"My custom handler, token: prefer to go bear-foot!\n",
"My custom handler, token: \n"
]
}
],
@ -95,7 +75,7 @@
"# To enable streaming, we pass in `streaming=True` to the ChatModel constructor\n",
"# Additionally, we pass in our custom handler as a list to the callbacks parameter\n",
"model = ChatAnthropic(\n",
" model=\"claude-3-sonnet-20240229\", streaming=True, callbacks=[MyCustomHandler()]\n",
" model=\"claude-3-7-sonnet-20250219\", streaming=True, callbacks=[MyCustomHandler()]\n",
")\n",
"\n",
"chain = prompt | model\n",
@ -119,7 +99,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -133,7 +113,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.5"
"version": "3.10.16"
}
},
"nbformat": 4,

21
docs/docs/how_to/dynamic_chain.ipynb
View File

@ -35,7 +35,7 @@
"\n",
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\")"
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\")"
]
},
{
@ -47,10 +47,10 @@
{
"data": {
"text/plain": [
"\"According to the context provided, Egypt's population in 2024 is estimated to be about 111 million.\""
"\"Egypt's population in 2024 is about 111 million.\""
]
},
"execution_count": 10,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -142,13 +142,10 @@
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"What\n",
" is\n",
" the\n",
" population\n",
" of\n",
" Egypt\n",
"?\n"
" is the population of Egypt?\n",
"\n"
]
}
],
@ -168,9 +165,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "poetry-venv-2",
"display_name": "langchain",
"language": "python",
"name": "poetry-venv-2"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
@ -182,7 +179,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.10.16"
}
},
"nbformat": 4,

18
docs/docs/how_to/extraction_parse.ipynb
View File

@ -42,7 +42,7 @@
"\n",
"from langchain_anthropic.chat_models import ChatAnthropic\n",
"\n",
"model = ChatAnthropic(model_name=\"claude-3-sonnet-20240229\", temperature=0)"
"model = ChatAnthropic(model_name=\"claude-3-7-sonnet-20250219\", temperature=0)"
]
},
{
@ -200,7 +200,7 @@
{
"data": {
"text/plain": [
"People(people=[Person(name='Anna', height_in_meters=1.83)])"
"People(people=[Person(name='Anna', height_in_meters=1.8288)])"
]
},
"execution_count": 5,
@ -242,7 +242,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "b1f11912-c1bb-4a2a-a482-79bf3996961f",
"metadata": {
"execution": {
@ -359,14 +359,6 @@
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/bagatur/langchain/.venv/lib/python3.11/site-packages/pydantic/_internal/_fields.py:201: UserWarning: Field name \"schema\" in \"PromptInput\" shadows an attribute in parent \"BaseModel\"\n",
" warnings.warn(\n"
]
},
{
"data": {
"text/plain": [
@ -397,7 +389,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -411,7 +403,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
"version": "3.10.16"
}
},
"nbformat": 4,

39
docs/docs/how_to/filter_messages.ipynb
View File

@ -23,11 +23,11 @@
{
"data": {
"text/plain": [
"[HumanMessage(content='example input', name='example_user', id='2'),\n",
" HumanMessage(content='real input', name='bob', id='4')]"
"[HumanMessage(content='example input', additional_kwargs={}, response_metadata={}, name='example_user', id='2'),\n",
" HumanMessage(content='real input', additional_kwargs={}, response_metadata={}, name='bob', id='4')]"
]
},
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -60,12 +60,12 @@
{
"data": {
"text/plain": [
"[SystemMessage(content='you are a good assistant', id='1'),\n",
" HumanMessage(content='real input', name='bob', id='4'),\n",
" AIMessage(content='real output', name='alice', id='5')]"
"[SystemMessage(content='you are a good assistant', additional_kwargs={}, response_metadata={}, id='1'),\n",
" HumanMessage(content='real input', additional_kwargs={}, response_metadata={}, name='bob', id='4'),\n",
" AIMessage(content='real output', additional_kwargs={}, response_metadata={}, name='alice', id='5')]"
]
},
"execution_count": 2,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@ -83,12 +83,12 @@
{
"data": {
"text/plain": [
"[HumanMessage(content='example input', name='example_user', id='2'),\n",
" HumanMessage(content='real input', name='bob', id='4'),\n",
" AIMessage(content='real output', name='alice', id='5')]"
"[HumanMessage(content='example input', additional_kwargs={}, response_metadata={}, name='example_user', id='2'),\n",
" HumanMessage(content='real input', additional_kwargs={}, response_metadata={}, name='bob', id='4'),\n",
" AIMessage(content='real output', additional_kwargs={}, response_metadata={}, name='alice', id='5')]"
]
},
"execution_count": 3,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -126,10 +126,10 @@
{
"data": {
"text/plain": [
"AIMessage(content=[], response_metadata={'id': 'msg_01Wz7gBHahAwkZ1KCBNtXmwA', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 3}}, id='run-b5d8a3fe-004f-4502-a071-a6c025031827-0', usage_metadata={'input_tokens': 16, 'output_tokens': 3, 'total_tokens': 19})"
"AIMessage(content=[], additional_kwargs={}, response_metadata={'id': 'msg_01At8GtCiJ79M29yvNwCiQaB', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 16, 'output_tokens': 3, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--b3db2b91-0edf-4c48-99e7-35e641b8229d-0', usage_metadata={'input_tokens': 16, 'output_tokens': 3, 'total_tokens': 19, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@ -137,7 +137,7 @@
"source": [
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", temperature=0)\n",
"# Notice we don't pass in messages. This creates\n",
"# a RunnableLambda that takes messages as input\n",
"filter_ = filter_messages(exclude_names=[\"example_user\", \"example_assistant\"])\n",
@ -164,8 +164,9 @@
{
"data": {
"text/plain": [
"[HumanMessage(content='real input', name='bob', id='4'),\n",
" AIMessage(content='real output', name='alice', id='5')]"
"[SystemMessage(content='you are a good assistant', additional_kwargs={}, response_metadata={}, id='1'),\n",
" HumanMessage(content='real input', additional_kwargs={}, response_metadata={}, name='bob', id='4'),\n",
" AIMessage(content='real output', additional_kwargs={}, response_metadata={}, name='alice', id='5')]"
]
},
"execution_count": 6,
@ -190,9 +191,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "poetry-venv-2",
"display_name": "langchain",
"language": "python",
"name": "poetry-venv-2"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
@ -204,7 +205,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.10.16"
}
},
"nbformat": 4,

29
docs/docs/how_to/merge_message_runs.ipynb
View File

@ -97,20 +97,13 @@
"id": "6d5a0283-11f8-435b-b27b-7b18f7693592",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Note: you may need to restart the kernel to use updated packages.\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content=[], additional_kwargs={}, response_metadata={'id': 'msg_01KNGUMTuzBVfwNouLDpUMwf', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 84, 'output_tokens': 3}}, id='run-b908b198-9c24-450b-9749-9d4a8182937b-0', usage_metadata={'input_tokens': 84, 'output_tokens': 3, 'total_tokens': 87})"
"AIMessage(content='\\n\\nAs for the actual answer, LangChain is named for connecting (chaining) language models together with other components. And Harrison Chase is one of the co-founders of LangChain, not someone being chased! \\n\\nBut I like to think he\\'s running after runaway tokens that escaped from the embedding space. \"Come back here, you vectors!\"', additional_kwargs={}, response_metadata={'id': 'msg_018MF8xBrM1ztw69XTx3Uxcy', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 84, 'output_tokens': 80, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--caa1b9d6-a554-40ad-95cd-268938d8223b-0', usage_metadata={'input_tokens': 84, 'output_tokens': 80, 'total_tokens': 164, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 9,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -118,7 +111,7 @@
"source": [
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", temperature=0)\n",
"# Notice we don't pass in messages. This creates\n",
"# a RunnableLambda that takes messages as input\n",
"merger = merge_message_runs()\n",
@ -150,7 +143,7 @@
" AIMessage(content='Well, I guess they thought \"WordRope\" and \"SentenceString\" just didn\\'t have the same ring to it!\\nWhy, he\\'s probably chasing after the last cup of coffee in the office!', additional_kwargs={}, response_metadata={})]"
]
},
"execution_count": 10,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@ -176,10 +169,10 @@
{
"data": {
"text/plain": [
"AIMessage(content='A convergent series is an infinite series whose partial sums approach a finite value as more terms are added. In other words, the sequence of partial sums has a limit.\\n\\nMore formally, an infinite series Σ an (where an are the terms of the series) is said to be convergent if the sequence of partial sums:\\n\\nS1 = a1\\nS2 = a1 + a2 \\nS3 = a1 + a2 + a3\\n...\\nSn = a1 + a2 + a3 + ... + an\\n...\\n\\nconverges to some finite number S as n goes to infinity. We write:\\n\\nlim n→∞ Sn = S\\n\\nThe finite number S is called the sum of the convergent infinite series.\\n\\nIf the sequence of partial sums does not approach any finite limit, the infinite series is said to be divergent.\\n\\nSome key properties:\\n- A series converges if and only if the sequence of its partial sums is a Cauchy sequence.\\n- Absolute/conditional convergence criteria help determine if a given series converges.\\n- Convergent series have many important applications in mathematics, physics, engineering etc.', additional_kwargs={}, response_metadata={'id': 'msg_01MfV6y2hep7ZNvDz24A36U4', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 29, 'output_tokens': 267}}, id='run-9d925f58-021e-4bd0-94fc-f8f5e91010a4-0', usage_metadata={'input_tokens': 29, 'output_tokens': 267, 'total_tokens': 296})"
"AIMessage(content=\"# Definition of a Convergent Series\\n\\nA series is a sum of terms in a sequence, typically written as:\\n\\n$$\\\\sum_{n=1}^{\\\\infty} a_n = a_1 + a_2 + a_3 + \\\\ldots$$\\n\\nA series is called **convergent** if the sequence of partial sums approaches a finite limit.\\n\\n## Formal Definition\\n\\nLet's define the sequence of partial sums:\\n$$S_N = \\\\sum_{n=1}^{N} a_n = a_1 + a_2 + \\\\ldots + a_N$$\\n\\nA series $\\\\sum_{n=1}^{\\\\infty} a_n$ is convergent if and only if:\\n- The limit of the partial sums exists and is finite\\n- That is, there exists a finite number $S$ such that $\\\\lim_{N \\\\to \\\\infty} S_N = S$\\n\\nIf this limit exists, we say the series converges to $S$, and we write:\\n$$\\\\sum_{n=1}^{\\\\infty} a_n = S$$\\n\\nIf the limit doesn't exist or is infinite, the series is called divergent.\", additional_kwargs={}, response_metadata={'id': 'msg_018ypyi2MTjV6S7jCydSqDn9', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 29, 'output_tokens': 273, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-7-sonnet-20250219'}, id='run--5de0ca29-d031-48f7-bc75-671eade20b74-0', usage_metadata={'input_tokens': 29, 'output_tokens': 273, 'total_tokens': 302, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})"
]
},
"execution_count": 14,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -203,7 +196,7 @@
"id": "51ba533a-43c7-4e5f-bd91-a4ec23ceeb34",
"metadata": {},
"source": [
"LangSmith Trace: https://smith.langchain.com/public/432150b6-9909-40a7-8ae7-944b7e657438/r/f4ad5fb2-4d38-42a6-b780-25f62617d53f"
"[LangSmith Trace](https://smith.langchain.com/public/432150b6-9909-40a7-8ae7-944b7e657438/r/f4ad5fb2-4d38-42a6-b780-25f62617d53f)"
]
},
{
@ -213,15 +206,15 @@
"source": [
"## API reference\n",
"\n",
"For a complete description of all arguments head to the API reference: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.utils.merge_message_runs.html"
"For a complete description of all arguments head to the [API reference](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.utils.merge_message_runs.html)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "poetry-venv-2",
"display_name": "langchain",
"language": "python",
"name": "poetry-venv-2"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
@ -233,7 +226,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
"version": "3.10.16"
}
},
"nbformat": 4,

27
docs/docs/how_to/response_metadata.ipynb
View File

@ -23,17 +23,18 @@
{
"data": {
"text/plain": [
"{'token_usage': {'completion_tokens': 110,\n",
"{'token_usage': {'completion_tokens': 93,\n",
" 'prompt_tokens': 16,\n",
" 'total_tokens': 126,\n",
" 'total_tokens': 109,\n",
" 'completion_tokens_details': {'accepted_prediction_tokens': 0,\n",
" 'audio_tokens': 0,\n",
" 'reasoning_tokens': 0,\n",
" 'rejected_prediction_tokens': 0},\n",
" 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}},\n",
" 'model_name': 'gpt-4o-mini-2024-07-18',\n",
" 'system_fingerprint': 'fp_b8bc95a0ac',\n",
" 'id': 'chatcmpl-BDrISvLar6AqcZngBmhajFZXVc2u9',\n",
" 'system_fingerprint': 'fp_34a54ae93c',\n",
" 'id': 'chatcmpl-ByJtse6I3U1lmVyPscLCjzydCvfDO',\n",
" 'service_tier': 'default',\n",
" 'finish_reason': 'stop',\n",
" 'logprobs': None}"
]
@ -68,15 +69,17 @@
{
"data": {
"text/plain": [
"{'id': 'msg_01JHnvPqgERY7MZwrvfkmq52',\n",
" 'model': 'claude-3-5-sonnet-20241022',\n",
"{'id': 'msg_017S9H7GMwA5RdZ1wHxzXoeX',\n",
" 'model': 'claude-3-7-sonnet-20250219',\n",
" 'stop_reason': 'end_turn',\n",
" 'stop_sequence': None,\n",
" 'usage': {'cache_creation_input_tokens': 0,\n",
" 'cache_read_input_tokens': 0,\n",
" 'input_tokens': 17,\n",
" 'output_tokens': 221},\n",
" 'model_name': 'claude-3-5-sonnet-20241022'}"
" 'output_tokens': 180,\n",
" 'server_tool_use': None,\n",
" 'service_tier': 'standard'},\n",
" 'model_name': 'claude-3-7-sonnet-20250219'}"
]
},
"execution_count": 2,
@ -87,7 +90,7 @@
"source": [
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"llm = ChatAnthropic(model=\"claude-3-5-sonnet-latest\")\n",
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\")\n",
"msg = llm.invoke(\"What's the oldest known example of cuneiform\")\n",
"msg.response_metadata"
]
@ -173,7 +176,7 @@
"source": [
"from langchain_aws import ChatBedrockConverse\n",
"\n",
"llm = ChatBedrockConverse(model=\"anthropic.claude-3-sonnet-20240229-v1:0\")\n",
"llm = ChatBedrockConverse(model=\"anthropic.claude-3-7-sonnet-20250219-v1:0\")\n",
"msg = llm.invoke(\"What's the oldest known example of cuneiform\")\n",
"msg.response_metadata"
]
@ -301,7 +304,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -315,7 +318,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
"version": "3.10.16"
}
},
"nbformat": 4,

14
docs/docs/how_to/sequence.ipynb
View File

@ -61,7 +61,7 @@
"if \"ANTHROPIC_API_KEY\" not in os.environ:\n",
" os.environ[\"ANTHROPIC_API_KEY\"] = getpass()\n",
"\n",
"model = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)"
"model = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", temperature=0)"
]
},
{
@ -93,7 +93,7 @@
{
"data": {
"text/plain": [
"\"Here's a bear joke for you:\\n\\nWhy did the bear dissolve in water?\\nBecause it was a polar bear!\""
"\"Why don't bears wear shoes?\\n\\nBecause they prefer to go bear-foot!\""
]
},
"execution_count": 3,
@ -128,7 +128,7 @@
{
"data": {
"text/plain": [
"'Haha, that\\'s a clever play on words! Using \"polar\" to imply the bear dissolved or became polar/polarized when put in water. Not the most hilarious joke ever, but it has a cute, groan-worthy pun that makes it mildly amusing. I appreciate a good pun or wordplay joke.'"
"'Yes, that\\'s a funny joke! It\\'s a classic pun that plays on the homophone pair \"bare-foot\" and \"bear-foot.\" The humor comes from:\\n\\n1. The wordplay between \"barefoot\" (not wearing shoes) and \"bear-foot\" (the foot of a bear)\\n2. The logical connection to the setup (bears don\\'t wear shoes)\\n3. It\\'s family-friendly and accessible\\n4. It\\'s a simple, clean pun that creates an unexpected but satisfying punchline\\n\\nIt\\'s the kind of joke that might make you groan and smile at the same time - what people often call a \"dad joke.\"'"
]
},
"execution_count": 4,
@ -161,7 +161,7 @@
{
"data": {
"text/plain": [
"\"Haha, that's a cute and punny joke! I like how it plays on the idea of beets blushing or turning red like someone blushing. Food puns can be quite amusing. While not a total knee-slapper, it's a light-hearted, groan-worthy dad joke that would make me chuckle and shake my head. Simple vegetable humor!\""
"'Yes, that\\'s a cute and funny joke! It works well because:\\n\\n1. It plays on the double meaning of \"roots\" - both the literal roots of the beet plant and the metaphorical sense of knowing one\\'s origins or foundation\\n2. It\\'s a simple, clean pun that doesn\\'t rely on offensive content\\n3. It has a satisfying logical connection (beets are root vegetables)\\n\\nIt\\'s the kind of wholesome food pun that might make people groan a little but also smile. Perfect for sharing in casual conversation or with kids!'"
]
},
"execution_count": 5,
@ -205,7 +205,7 @@
{
"data": {
"text/plain": [
"\"I cannot reproduce any copyrighted material verbatim, but I can try to analyze the humor in the joke you provided without quoting it directly.\\n\\nThe joke plays on the idea that the Cylon raiders, who are the antagonists in the Battlestar Galactica universe, failed to locate the human survivors after attacking their home planets (the Twelve Colonies) due to using an outdated and poorly performing operating system (Windows Vista) for their targeting systems.\\n\\nThe humor stems from the juxtaposition of a futuristic science fiction setting with a relatable real-world frustration – the use of buggy, slow, or unreliable software or technology. It pokes fun at the perceived inadequacies of Windows Vista, which was widely criticized for its performance issues and other problems when it was released.\\n\\nBy attributing the Cylons' failure to locate the humans to their use of Vista, the joke creates an amusing and unexpected connection between a fictional advanced race of robots and a familiar technological annoyance experienced by many people in the real world.\\n\\nOverall, the joke relies on incongruity and relatability to generate humor, but without reproducing any copyrighted material directly.\""
"\"This joke is moderately funny! It plays on Battlestar Galactica lore where Cylons are robots with 12 different models trying to infiltrate human society. The humor comes from the idea of a Cylon accidentally revealing their non-human nature through a pickup line that references their artificial origins. It's a decent nerd-culture joke that would land well with fans of the show, though someone unfamiliar with Battlestar Galactica might not get the reference. The punchline effectively highlights the contradiction in a Cylon trying to blend in while simultaneously revealing their true identity.\""
]
},
"execution_count": 6,
@ -256,7 +256,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -270,7 +270,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.10.16"
}
},
"nbformat": 4,

326
docs/docs/how_to/streaming.ipynb
View File

@ -79,18 +79,7 @@
"execution_count": 1,
"id": "f123bdcb-8c8b-440c-9bbd-aa5ed4e9cd17",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.0\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"outputs": [],
"source": [
"# | output: false\n",
"# | echo: false\n",
@ -110,7 +99,7 @@
"\n",
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"model = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)"
"model = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", temperature=0)"
]
},
{
@ -131,7 +120,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"The| sky| appears| blue| during| the| day|.|"
"|The sky typically| appears blue during the day due to a phenomenon| called Rayleigh scattering, where| air molecules scatter sunlight, with| blue light being scattered more than other colors. However|, the sky's color can vary|:\n",
"\n",
"- At sunrise/sunset:| Red, orange, pink, or purple\n",
"-| During storms: Gray or dark blue|\n",
"- At night: Dark| blue to black\n",
"- In certain| atmospheric conditions: White, yellow, or green| (rare)\n",
"\n",
"The color we perceive depends| on weather conditions, time of day, pollution| levels, and our viewing angle.||"
]
}
],
@ -160,7 +156,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"The| sky| appears| blue| during| the| day|.|"
"|The sky typically| appears blue during the day due to a phenomenon called Rayleigh| scattering, where air molecules scatter sunlight,| with blue light being scattered more than other colors. However|, the sky's color can vary - appearing re|d, orange, or pink during sunrise and sunset,| gray on cloudy days, and black at night.| The color you see depends on the time of| day, weather conditions, and your location.||"
]
}
],
@ -188,10 +184,10 @@
{
"data": {
"text/plain": [
"AIMessageChunk(content='The', id='run-b36bea64-5511-4d7a-b6a3-a07b3db0c8e7')"
"AIMessageChunk(content='', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--c4f01565-8bb4-4f07-9b23-acfe46cbeca3', usage_metadata={'input_tokens': 13, 'output_tokens': 0, 'total_tokens': 13, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})"
]
},
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@ -219,10 +215,10 @@
{
"data": {
"text/plain": [
"AIMessageChunk(content='The sky appears blue during', id='run-b36bea64-5511-4d7a-b6a3-a07b3db0c8e7')"
"AIMessageChunk(content='The sky typically appears blue during the day due to a phenomenon called Rayleigh scattering, where air molecules scatter sunlight, with blue light being scattered more than other colors. However', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--c4f01565-8bb4-4f07-9b23-acfe46cbeca3', usage_metadata={'input_tokens': 13, 'output_tokens': 0, 'total_tokens': 13, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})"
]
},
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@ -259,17 +255,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Here|'s| a| joke| about| a| par|rot|:|\n",
"|Why| don't parrots use the internet?\n",
"\n",
"A man| goes| to| a| pet| shop| to| buy| a| par|rot|.| The| shop| owner| shows| him| two| stunning| pa|rr|ots| with| beautiful| pl|um|age|.|\n",
"\n",
"\"|There|'s| a| talking| par|rot| an|d a| non|-|talking| par|rot|,\"| the| owner| says|.| \"|The| talking| par|rot| costs| $|100|,| an|d the| non|-|talking| par|rot| is| $|20|.\"|\n",
"\n",
"The| man| says|,| \"|I|'ll| take| the| non|-|talking| par|rot| at| $|20|.\"|\n",
"\n",
"He| pays| an|d leaves| with| the| par|rot|.| As| he|'s| walking| down| the| street|,| the| par|rot| looks| up| at| him| an|d says|,| \"|You| know|,| you| really| are| a| stupi|d man|!\"|\n",
"\n",
"The| man| is| stun|ne|d an|d looks| at| the| par|rot| in| dis|bel|ief|.| The| par|rot| continues|,| \"|Yes|,| you| got| r|ippe|d off| big| time|!| I| can| talk| just| as| well| as| that| other| par|rot|,| an|d you| only| pai|d $|20| |for| me|!\"|"
"They|'re afraid of getting a virus from all the tweets|!||"
]
}
],
@ -337,26 +325,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{}\n",
"{'countries': []}\n",
"{'countries': [{}]}\n",
"{'countries': [{'name': ''}]}\n",
"{'countries': [{'name': 'France'}]}\n",
"{'countries': [{'name': 'France', 'population': 67}]}\n",
"{'countries': [{'name': 'France', 'population': 67413}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': ''}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain'}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {'name': ''}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {'name': 'Japan'}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {'name': 'Japan', 'population': 125}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {'name': 'Japan', 'population': 125584}]}\n",
"{'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351567}, {'name': 'Japan', 'population': 125584000}]}\n"
"{'countries': [{'name': 'France', 'population': 67750}]}\n",
"{'countries': [{'name': 'France', 'population': 67750000}, {}]}\n",
"{'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain'}]}\n",
"{'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {}]}\n",
"{'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan'}]}\n",
"{'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700000}]}\n"
]
}
],
@ -539,11 +515,11 @@
{
"data": {
"text/plain": [
"[[Document(page_content='harrison worked at kensho'),\n",
" Document(page_content='harrison likes spicy food')]]"
"[[Document(id='2740a247-9738-48c4-8c8f-d879d4ed39f7', metadata={}, page_content='harrison worked at kensho'),\n",
" Document(id='1d3d012f-1cb0-4bee-928a-c8bf0f8b1b92', metadata={}, page_content='harrison likes spicy food')]]"
]
},
"execution_count": 10,
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
@ -614,15 +590,15 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Base|d on| the| given| context|,| Harrison| worke|d at| K|ens|ho|.|\n",
"|Base|d on the provided context, Harrison worked at Kens|ho.\n",
"\n",
"Here| are| |3| |made| up| sentences| about| this| place|:|\n",
"Three made up sentences about Kens|ho:\n",
"\n",
"1|.| K|ens|ho| was| a| cutting|-|edge| technology| company| known| for| its| innovative| solutions| in| artificial| intelligence| an|d data| analytics|.|\n",
"1. Kensho is a| cutting-edge technology company that specializes in| AI and data analytics for financial institutions.\n",
"\n",
"2|.| The| modern| office| space| at| K|ens|ho| feature|d open| floor| plans|,| collaborative| work|sp|aces|,| an|d a| vib|rant| atmosphere| that| fos|tere|d creativity| an|d team|work|.|\n",
"2|. The Kensho office features| an open floor plan with panoramic views of the city| skyline, creating an inspiring environment for its| employees.\n",
"\n",
"3|.| With| its| prime| location| in| the| heart| of| the| city|,| K|ens|ho| attracte|d top| talent| from| aroun|d the| worl|d,| creating| a| diverse| an|d dynamic| work| environment|.|"
"3. At Kensho,| team members often collaborate in innovative brainstorming sessions while| enjoying complimentary gourmet coffee from| their in-house café.||"
]
}
],
@ -763,38 +739,38 @@
" 'data': {'input': 'hello'},\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': [],\n",
" 'run_id': 'b18d016d-8b9b-49e7-a555-44db498fcf66',\n",
" 'run_id': 'c35a72be-a5af-4bd5-bd9b-206135c28ef6',\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-sonnet-20240229',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'parent_ids': []},\n",
" {'event': 'on_chat_model_stream',\n",
" 'run_id': 'b18d016d-8b9b-49e7-a555-44db498fcf66',\n",
" 'run_id': 'c35a72be-a5af-4bd5-bd9b-206135c28ef6',\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': [],\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-sonnet-20240229',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={}, id='run-b18d016d-8b9b-49e7-a555-44db498fcf66', usage_metadata={'input_tokens': 8, 'output_tokens': 4, 'total_tokens': 12, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})},\n",
" 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--c35a72be-a5af-4bd5-bd9b-206135c28ef6', usage_metadata={'input_tokens': 8, 'output_tokens': 0, 'total_tokens': 8, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})},\n",
" 'parent_ids': []},\n",
" {'event': 'on_chat_model_stream',\n",
" 'run_id': 'b18d016d-8b9b-49e7-a555-44db498fcf66',\n",
" 'run_id': 'c35a72be-a5af-4bd5-bd9b-206135c28ef6',\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': [],\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-sonnet-20240229',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'data': {'chunk': AIMessageChunk(content='Hello! How can', additional_kwargs={}, response_metadata={}, id='run-b18d016d-8b9b-49e7-a555-44db498fcf66')},\n",
" 'data': {'chunk': AIMessageChunk(content='Hello! How', additional_kwargs={}, response_metadata={}, id='run--c35a72be-a5af-4bd5-bd9b-206135c28ef6')},\n",
" 'parent_ids': []}]"
]
},
"execution_count": 14,
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
@ -813,30 +789,30 @@
"data": {
"text/plain": [
"[{'event': 'on_chat_model_stream',\n",
" 'run_id': 'b18d016d-8b9b-49e7-a555-44db498fcf66',\n",
" 'run_id': 'c35a72be-a5af-4bd5-bd9b-206135c28ef6',\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': [],\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-sonnet-20240229',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'stop_reason': 'end_turn', 'stop_sequence': None}, id='run-b18d016d-8b9b-49e7-a555-44db498fcf66', usage_metadata={'input_tokens': 0, 'output_tokens': 12, 'total_tokens': 12, 'input_token_details': {}})},\n",
" 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'stop_reason': 'end_turn', 'stop_sequence': None}, id='run--c35a72be-a5af-4bd5-bd9b-206135c28ef6', usage_metadata={'input_tokens': 0, 'output_tokens': 40, 'total_tokens': 40})},\n",
" 'parent_ids': []},\n",
" {'event': 'on_chat_model_end',\n",
" 'data': {'output': AIMessageChunk(content='Hello! How can I assist you today?', additional_kwargs={}, response_metadata={'stop_reason': 'end_turn', 'stop_sequence': None}, id='run-b18d016d-8b9b-49e7-a555-44db498fcf66', usage_metadata={'input_tokens': 8, 'output_tokens': 16, 'total_tokens': 24, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})},\n",
" 'run_id': 'b18d016d-8b9b-49e7-a555-44db498fcf66',\n",
" 'data': {'output': AIMessageChunk(content=\"Hello! How can I assist you today? Whether you have questions, need information, or just want to chat, I'm here to help. What would you like to talk about?\", additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None}, id='run--c35a72be-a5af-4bd5-bd9b-206135c28ef6', usage_metadata={'input_tokens': 8, 'output_tokens': 40, 'total_tokens': 48, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})},\n",
" 'run_id': 'c35a72be-a5af-4bd5-bd9b-206135c28ef6',\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': [],\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-sonnet-20240229',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'parent_ids': []}]"
]
},
"execution_count": 15,
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
@ -903,23 +879,34 @@
" 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'},\n",
" 'name': 'RunnableSequence',\n",
" 'tags': [],\n",
" 'run_id': '4765006b-16e2-4b1d-a523-edd9fd64cb92',\n",
" 'metadata': {}},\n",
" 'run_id': 'f859e56f-a760-4670-a24e-040e11bcd7fc',\n",
" 'metadata': {},\n",
" 'parent_ids': []},\n",
" {'event': 'on_chat_model_start',\n",
" 'data': {'input': {'messages': [[HumanMessage(content='output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`')]]}},\n",
" 'data': {'input': {'messages': [[HumanMessage(content='output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`', additional_kwargs={}, response_metadata={})]]}},\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': ['seq:step:1'],\n",
" 'run_id': '0320c234-7b52-4a14-ae4e-5f100949e589',\n",
" 'metadata': {}},\n",
" 'run_id': '2aa8c9e6-a5cd-4e94-b994-cb0e9bd8ab21',\n",
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'parent_ids': ['f859e56f-a760-4670-a24e-040e11bcd7fc']},\n",
" {'event': 'on_chat_model_stream',\n",
" 'data': {'chunk': AIMessageChunk(content='{', id='run-0320c234-7b52-4a14-ae4e-5f100949e589')},\n",
" 'run_id': '0320c234-7b52-4a14-ae4e-5f100949e589',\n",
" 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--2aa8c9e6-a5cd-4e94-b994-cb0e9bd8ab21', usage_metadata={'input_tokens': 56, 'output_tokens': 0, 'total_tokens': 56, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})},\n",
" 'run_id': '2aa8c9e6-a5cd-4e94-b994-cb0e9bd8ab21',\n",
" 'name': 'ChatAnthropic',\n",
" 'tags': ['seq:step:1'],\n",
" 'metadata': {}}]"
" 'metadata': {'ls_provider': 'anthropic',\n",
" 'ls_model_name': 'claude-3-7-sonnet-20250219',\n",
" 'ls_model_type': 'chat',\n",
" 'ls_temperature': 0.0,\n",
" 'ls_max_tokens': 1024},\n",
" 'parent_ids': ['f859e56f-a760-4670-a24e-040e11bcd7fc']}]"
]
},
"execution_count": 18,
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
@ -955,25 +942,25 @@
"output_type": "stream",
"text": [
"Chat model chunk: ''\n",
"Chat model chunk: '{'\n",
"Parser chunk: {}\n",
"Chat model chunk: '\\n \"countries'\n",
"Chat model chunk: '\": [\\n '\n",
"Chat model chunk: '```'\n",
"Chat model chunk: 'json\\n{\\n \"countries\": ['\n",
"Parser chunk: {'countries': []}\n",
"Chat model chunk: '{\\n \"'\n",
"Parser chunk: {'countries': [{}]}\n",
"Chat model chunk: 'name\": \"France'\n",
"Chat model chunk: '\\n {\\n \"name\": \"France\",'\n",
"Parser chunk: {'countries': [{'name': 'France'}]}\n",
"Chat model chunk: '\",\\n \"'\n",
"Chat model chunk: 'population\": 67'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67}]}\n",
"Chat model chunk: '413'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413}]}\n",
"Chat model chunk: '000\\n },'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}]}\n",
"Chat model chunk: '\\n {'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}, {}]}\n",
"Chat model chunk: '\\n \"name\":'\n",
"Chat model chunk: '\\n \"population\": 67750000\\n },'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}]}\n",
"Chat model chunk: '\\n {\\n \"name\": \"Spain\",'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain'}]}\n",
"Chat model chunk: '\\n \"population\": 47350'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350}]}\n",
"Chat model chunk: '000\\n },\\n {\\n \"'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {}]}\n",
"Chat model chunk: 'name\": \"Japan\",\\n \"population\":'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan'}]}\n",
"Chat model chunk: ' 125700000\\n }'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700000}]}\n",
"Chat model chunk: '\\n ]\\n}\\n```'\n",
"Chat model chunk: ''\n",
"...\n"
]
}
@ -1033,18 +1020,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_parser_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'my_parser', 'tags': ['seq:step:2'], 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'metadata': {}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France'}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67413}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67413000}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67413000}, {}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain'}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"{'event': 'on_parser_stream', 'run_id': '37ee9e85-481c-415e-863b-c9e132d24948', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47}]}}, 'parent_ids': ['5a0bc625-09fd-4bdf-9932-54909a9a8c29']}\n",
"...\n"
"{'event': 'on_parser_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'my_parser', 'tags': ['seq:step:2'], 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'metadata': {}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France'}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750000}, {}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain'}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan'}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_stream', 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700000}]}}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n",
"{'event': 'on_parser_end', 'data': {'output': {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700000}]}}, 'run_id': '781af9b6-31f8-47f2-ab79-52d17b000857', 'name': 'my_parser', 'tags': ['seq:step:2'], 'metadata': {}, 'parent_ids': ['82c918c6-d5f6-4d2d-b710-4668509fe2f0']}\n"
]
}
],
@ -1086,17 +1071,17 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_chat_model_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'model', 'tags': ['seq:step:1'], 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c', usage_metadata={'input_tokens': 56, 'output_tokens': 1, 'total_tokens': 57, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='{', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n \"countries', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\": [\\n ', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='{\\n \"', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='name\": \"France', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\",\\n \"', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='population\": 67', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='413', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='000\\n },', additional_kwargs={}, response_metadata={}, id='run-156c3e40-82fb-49ff-8e41-9e998061be8c')}, 'run_id': '156c3e40-82fb-49ff-8e41-9e998061be8c', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['7b927055-bc1b-4b50-a34c-10d3cfcb3899']}\n",
"{'event': 'on_chat_model_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'model', 'tags': ['seq:step:1'], 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5', usage_metadata={'input_tokens': 56, 'output_tokens': 0, 'total_tokens': 56, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='```', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='json\\n{\\n \"countries\": [', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n {\\n \"name\": \"France\",', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n \"population\": 67750', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='000\\n },\\n {\\n \"', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='name\": \"Spain\",\\n \"population\":', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' 47350000\\n },', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n {\\n \"name\": \"Japan\",', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n \"population\": 125700', additional_kwargs={}, response_metadata={}, id='run--b7a08416-a629-4b42-b5d5-dbe48566e5d5')}, 'run_id': 'b7a08416-a629-4b42-b5d5-dbe48566e5d5', 'name': 'model', 'tags': ['seq:step:1'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['116a6506-5a19-4f60-a8c2-7b728d4b8248']}\n",
"...\n"
]
}
@ -1144,17 +1129,17 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_chain_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'RunnableSequence', 'tags': ['my_chain'], 'run_id': '58d1302e-36ce-4df7-a3cb-47cb73d57e44', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chat_model_start', 'data': {'input': {'messages': [[HumanMessage(content='output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`', additional_kwargs={}, response_metadata={})]]}}, 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'run_id': '8222e8a1-d978-4f30-87fc-b2dba838774b', 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={}, id='run-8222e8a1-d978-4f30-87fc-b2dba838774b', usage_metadata={'input_tokens': 56, 'output_tokens': 1, 'total_tokens': 57, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})}, 'run_id': '8222e8a1-d978-4f30-87fc-b2dba838774b', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_parser_start', 'data': {}, 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'run_id': '75604c84-e1e6-494a-8b2a-950f45d932e8', 'metadata': {}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='{', additional_kwargs={}, response_metadata={}, id='run-8222e8a1-d978-4f30-87fc-b2dba838774b')}, 'run_id': '8222e8a1-d978-4f30-87fc-b2dba838774b', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_parser_stream', 'run_id': '75604c84-e1e6-494a-8b2a-950f45d932e8', 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'metadata': {}, 'data': {'chunk': {}}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_chain_stream', 'run_id': '58d1302e-36ce-4df7-a3cb-47cb73d57e44', 'name': 'RunnableSequence', 'tags': ['my_chain'], 'metadata': {}, 'data': {'chunk': {}}, 'parent_ids': []}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n \"countries', additional_kwargs={}, response_metadata={}, id='run-8222e8a1-d978-4f30-87fc-b2dba838774b')}, 'run_id': '8222e8a1-d978-4f30-87fc-b2dba838774b', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\": [\\n ', additional_kwargs={}, response_metadata={}, id='run-8222e8a1-d978-4f30-87fc-b2dba838774b')}, 'run_id': '8222e8a1-d978-4f30-87fc-b2dba838774b', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-sonnet-20240229', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_parser_stream', 'run_id': '75604c84-e1e6-494a-8b2a-950f45d932e8', 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': ['58d1302e-36ce-4df7-a3cb-47cb73d57e44']}\n",
"{'event': 'on_chain_stream', 'run_id': '58d1302e-36ce-4df7-a3cb-47cb73d57e44', 'name': 'RunnableSequence', 'tags': ['my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': []}\n",
"{'event': 'on_chain_start', 'data': {'input': 'output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`'}, 'name': 'RunnableSequence', 'tags': ['my_chain'], 'run_id': '3e4f8c37-a44a-46b7-a7e5-75182d1cca31', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chat_model_start', 'data': {'input': {'messages': [[HumanMessage(content='output a list of the countries france, spain and japan and their populations in JSON format. Use a dict with an outer key of \"countries\" which contains a list of countries. Each country should have the key `name` and `population`', additional_kwargs={}, response_metadata={})]]}}, 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'run_id': '778846c9-acd3-43b7-b9c0-ac718761b2bc', 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', additional_kwargs={}, response_metadata={'model_name': 'claude-3-7-sonnet-20250219'}, id='run--778846c9-acd3-43b7-b9c0-ac718761b2bc', usage_metadata={'input_tokens': 56, 'output_tokens': 0, 'total_tokens': 56, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})}, 'run_id': '778846c9-acd3-43b7-b9c0-ac718761b2bc', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_parser_start', 'data': {}, 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'run_id': '2c46d24f-231c-4062-a7ab-b7954840986d', 'metadata': {}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='```', additional_kwargs={}, response_metadata={}, id='run--778846c9-acd3-43b7-b9c0-ac718761b2bc')}, 'run_id': '778846c9-acd3-43b7-b9c0-ac718761b2bc', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='json\\n{\\n \"countries\": [', additional_kwargs={}, response_metadata={}, id='run--778846c9-acd3-43b7-b9c0-ac718761b2bc')}, 'run_id': '778846c9-acd3-43b7-b9c0-ac718761b2bc', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_parser_stream', 'run_id': '2c46d24f-231c-4062-a7ab-b7954840986d', 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_chain_stream', 'run_id': '3e4f8c37-a44a-46b7-a7e5-75182d1cca31', 'name': 'RunnableSequence', 'tags': ['my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': []}}, 'parent_ids': []}\n",
"{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='\\n {\\n \"name\": \"France\",', additional_kwargs={}, response_metadata={}, id='run--778846c9-acd3-43b7-b9c0-ac718761b2bc')}, 'run_id': '778846c9-acd3-43b7-b9c0-ac718761b2bc', 'name': 'ChatAnthropic', 'tags': ['seq:step:1', 'my_chain'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-7-sonnet-20250219', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_parser_stream', 'run_id': '2c46d24f-231c-4062-a7ab-b7954840986d', 'name': 'JsonOutputParser', 'tags': ['seq:step:2', 'my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France'}]}}, 'parent_ids': ['3e4f8c37-a44a-46b7-a7e5-75182d1cca31']}\n",
"{'event': 'on_chain_stream', 'run_id': '3e4f8c37-a44a-46b7-a7e5-75182d1cca31', 'name': 'RunnableSequence', 'tags': ['my_chain'], 'metadata': {}, 'data': {'chunk': {'countries': [{'name': 'France'}]}}, 'parent_ids': []}\n",
"...\n"
]
}
@ -1271,32 +1256,27 @@
"output_type": "stream",
"text": [
"Chat model chunk: ''\n",
"Chat model chunk: '{'\n",
"Parser chunk: {}\n",
"Chat model chunk: '\\n \"countries'\n",
"Chat model chunk: '\": [\\n '\n",
"Chat model chunk: '```'\n",
"Chat model chunk: 'json\\n{\\n \"countries\": ['\n",
"Parser chunk: {'countries': []}\n",
"Chat model chunk: '{\\n \"'\n",
"Parser chunk: {'countries': [{}]}\n",
"Chat model chunk: 'name\": \"France'\n",
"Chat model chunk: '\\n {\\n \"name\": \"France\",'\n",
"Parser chunk: {'countries': [{'name': 'France'}]}\n",
"Chat model chunk: '\",\\n \"'\n",
"Chat model chunk: 'population\": 67'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67}]}\n",
"Chat model chunk: '413'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413}]}\n",
"Chat model chunk: '000\\n },'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}]}\n",
"Chat model chunk: '\\n {'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}, {}]}\n",
"Chat model chunk: '\\n \"name\":'\n",
"Chat model chunk: ' \"Spain\",'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain'}]}\n",
"Chat model chunk: '\\n \"population\":'\n",
"Chat model chunk: ' 47'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47}]}\n",
"Chat model chunk: '351'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67413000}, {'name': 'Spain', 'population': 47351}]}\n",
"Chat model chunk: '\\n \"population\": 67750'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750}]}\n",
"Chat model chunk: '000\\n },\\n {\\n \"'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {}]}\n",
"Chat model chunk: 'name\": \"Spain\",\\n \"population\":'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain'}]}\n",
"Chat model chunk: ' 47350000\\n },'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}]}\n",
"Chat model chunk: '\\n {\\n \"name\": \"Japan\",'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan'}]}\n",
"Chat model chunk: '\\n \"population\": 125700'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700}]}\n",
"Chat model chunk: '000\\n }\\n ]\\n}'\n",
"Parser chunk: {'countries': [{'name': 'France', 'population': 67750000}, {'name': 'Spain', 'population': 47350000}, {'name': 'Japan', 'population': 125700000}]}\n",
"Chat model chunk: '\\n```'\n",
"Chat model chunk: ''\n",
"...\n"
]
}
@ -1350,10 +1330,10 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_tool_start', 'data': {'input': 'hello'}, 'name': 'bad_tool', 'tags': [], 'run_id': 'ea900472-a8f7-425d-b627-facdef936ee8', 'metadata': {}}\n",
"{'event': 'on_chain_start', 'data': {'input': 'hello'}, 'name': 'reverse_word', 'tags': [], 'run_id': '77b01284-0515-48f4-8d7c-eb27c1882f86', 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': 'olleh', 'input': 'hello'}, 'run_id': '77b01284-0515-48f4-8d7c-eb27c1882f86', 'name': 'reverse_word', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_tool_end', 'data': {'output': 'olleh'}, 'run_id': 'ea900472-a8f7-425d-b627-facdef936ee8', 'name': 'bad_tool', 'tags': [], 'metadata': {}}\n"
"{'event': 'on_tool_start', 'data': {'input': 'hello'}, 'name': 'bad_tool', 'tags': [], 'run_id': 'b1c6b79d-f94b-432f-a289-1ea68a7c3cea', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chain_start', 'data': {'input': 'hello'}, 'name': 'reverse_word', 'tags': [], 'run_id': 'e661c1ec-e6d2-4f9a-9620-b50645f2b194', 'metadata': {}, 'parent_ids': ['b1c6b79d-f94b-432f-a289-1ea68a7c3cea']}\n",
"{'event': 'on_chain_end', 'data': {'output': 'olleh', 'input': 'hello'}, 'run_id': 'e661c1ec-e6d2-4f9a-9620-b50645f2b194', 'name': 'reverse_word', 'tags': [], 'metadata': {}, 'parent_ids': ['b1c6b79d-f94b-432f-a289-1ea68a7c3cea']}\n",
"{'event': 'on_tool_end', 'data': {'output': 'olleh'}, 'run_id': 'b1c6b79d-f94b-432f-a289-1ea68a7c3cea', 'name': 'bad_tool', 'tags': [], 'metadata': {}, 'parent_ids': []}\n"
]
}
],
@ -1397,10 +1377,10 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_tool_start', 'data': {'input': 'hello'}, 'name': 'correct_tool', 'tags': [], 'run_id': 'd5ea83b9-9278-49cc-9f1d-aa302d671040', 'metadata': {}}\n",
"{'event': 'on_chain_start', 'data': {'input': 'hello'}, 'name': 'reverse_word', 'tags': [], 'run_id': '44dafbf4-2f87-412b-ae0e-9f71713810df', 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': 'olleh', 'input': 'hello'}, 'run_id': '44dafbf4-2f87-412b-ae0e-9f71713810df', 'name': 'reverse_word', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_tool_end', 'data': {'output': 'olleh'}, 'run_id': 'd5ea83b9-9278-49cc-9f1d-aa302d671040', 'name': 'correct_tool', 'tags': [], 'metadata': {}}\n"
"{'event': 'on_tool_start', 'data': {'input': 'hello'}, 'name': 'correct_tool', 'tags': [], 'run_id': '399c91f5-a40b-4173-943f-a9c583a04003', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chain_start', 'data': {'input': 'hello'}, 'name': 'reverse_word', 'tags': [], 'run_id': 'e9cc7db1-4587-40af-9c35-2d787b3f0956', 'metadata': {}, 'parent_ids': ['399c91f5-a40b-4173-943f-a9c583a04003']}\n",
"{'event': 'on_chain_end', 'data': {'output': 'olleh', 'input': 'hello'}, 'run_id': 'e9cc7db1-4587-40af-9c35-2d787b3f0956', 'name': 'reverse_word', 'tags': [], 'metadata': {}, 'parent_ids': ['399c91f5-a40b-4173-943f-a9c583a04003']}\n",
"{'event': 'on_tool_end', 'data': {'output': 'olleh'}, 'run_id': '399c91f5-a40b-4173-943f-a9c583a04003', 'name': 'correct_tool', 'tags': [], 'metadata': {}, 'parent_ids': []}\n"
]
}
],
@ -1433,11 +1413,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_and_double', 'tags': [], 'run_id': '03b0e6a1-3e60-42fc-8373-1e7829198d80', 'metadata': {}}\n",
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_word', 'tags': [], 'run_id': '5cf26fc8-840b-4642-98ed-623dda28707a', 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': '4321', 'input': '1234'}, 'run_id': '5cf26fc8-840b-4642-98ed-623dda28707a', 'name': 'reverse_word', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_chain_stream', 'data': {'chunk': '43214321'}, 'run_id': '03b0e6a1-3e60-42fc-8373-1e7829198d80', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': '43214321'}, 'run_id': '03b0e6a1-3e60-42fc-8373-1e7829198d80', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}}\n"
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_and_double', 'tags': [], 'run_id': '04726e2e-f508-4f90-9d4f-f88e588f0b39', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chain_stream', 'run_id': '04726e2e-f508-4f90-9d4f-f88e588f0b39', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}, 'data': {'chunk': '43214321'}, 'parent_ids': []}\n",
"{'event': 'on_chain_end', 'data': {'output': '43214321'}, 'run_id': '04726e2e-f508-4f90-9d4f-f88e588f0b39', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}, 'parent_ids': []}\n"
]
}
],
@ -1475,11 +1453,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_and_double', 'tags': [], 'run_id': '1bfcaedc-f4aa-4d8e-beee-9bba6ef17008', 'metadata': {}}\n",
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_word', 'tags': [], 'run_id': '64fc99f0-5d7d-442b-b4f5-4537129f67d1', 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': '4321', 'input': '1234'}, 'run_id': '64fc99f0-5d7d-442b-b4f5-4537129f67d1', 'name': 'reverse_word', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_chain_stream', 'data': {'chunk': '43214321'}, 'run_id': '1bfcaedc-f4aa-4d8e-beee-9bba6ef17008', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}}\n",
"{'event': 'on_chain_end', 'data': {'output': '43214321'}, 'run_id': '1bfcaedc-f4aa-4d8e-beee-9bba6ef17008', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}}\n"
"{'event': 'on_chain_start', 'data': {'input': '1234'}, 'name': 'reverse_and_double', 'tags': [], 'run_id': '25f72976-aa79-408d-bb42-6d0f038cde52', 'metadata': {}, 'parent_ids': []}\n",
"{'event': 'on_chain_stream', 'run_id': '25f72976-aa79-408d-bb42-6d0f038cde52', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}, 'data': {'chunk': '43214321'}, 'parent_ids': []}\n",
"{'event': 'on_chain_end', 'data': {'output': '43214321'}, 'run_id': '25f72976-aa79-408d-bb42-6d0f038cde52', 'name': 'reverse_and_double', 'tags': [], 'metadata': {}, 'parent_ids': []}\n"
]
}
],
@ -1513,7 +1489,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -1527,7 +1503,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
"version": "3.10.16"
}
},
"nbformat": 4,

11
docs/docs/how_to/tools_human.ipynb
View File

@ -94,7 +94,7 @@
"\n",
"from langchain_anthropic import ChatAnthropic\n",
"\n",
"llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=0)"
"llm = ChatAnthropic(model=\"claude-3-7-sonnet-20250219\", temperature=0)"
]
},
{
@ -108,11 +108,12 @@
"text/plain": [
"[{'name': 'count_emails',\n",
" 'args': {'last_n_days': 5},\n",
" 'id': 'toolu_01QYZdJ4yPiqsdeENWHqioFW',\n",
" 'id': 'toolu_01XrE4AU9QLo4imbriDDkmXm',\n",
" 'type': 'tool_call',\n",
" 'output': 10}]"
]
},
"execution_count": 3,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -299,7 +300,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "langchain",
"language": "python",
"name": "python3"
},
@ -313,7 +314,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.16"
}
},
"nbformat": 4,

7
libs/core/langchain_core/runnables/base.py
View File

@ -97,10 +97,7 @@ if TYPE_CHECKING:
from langchain_core.runnables.retry import ExponentialJitterParams
from langchain_core.runnables.schema import StreamEvent
from langchain_core.tools import BaseTool
from langchain_core.tracers.log_stream import (
RunLog,
RunLogPatch,
)
from langchain_core.tracers.log_stream import RunLog, RunLogPatch
from langchain_core.tracers.root_listeners import AsyncListener
from langchain_core.tracers.schemas import Run
@ -2570,7 +2567,7 @@ class RunnableSerializable(Serializable, Runnable[Input, Output]):
from langchain_openai import ChatOpenAI
model = ChatAnthropic(
model_name="claude-3-sonnet-20240229"
model_name="claude-3-7-sonnet-20250219"
).configurable_alternatives(
ConfigurableField(id="llm"),
default_key="anthropic",

9
libs/core/langchain_core/runnables/fallbacks.py
View File

@ -5,12 +5,7 @@ import inspect
import typing
from collections.abc import AsyncIterator, Iterator, Sequence
from functools import wraps
from typing import (
TYPE_CHECKING,
Any,
Optional,
Union,
)
from typing import TYPE_CHECKING, Any, Optional, Union
from pydantic import BaseModel, ConfigDict
from typing_extensions import override
@ -599,7 +594,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
from langchain_anthropic import ChatAnthropic
gpt_4o = ChatOpenAI(model="gpt-4o")
claude_3_sonnet = ChatAnthropic(model="claude-3-sonnet-20240229")
claude_3_sonnet = ChatAnthropic(model="claude-3-7-sonnet-20250219")
llm = gpt_4o.with_fallbacks([claude_3_sonnet])
llm.model_name

6
libs/langchain/tests/unit_tests/chat_models/test_base.py
View File

@ -196,17 +196,17 @@ def test_configurable_with_default() -> None:
model_with_config = model_with_tools.with_config(
RunnableConfig(tags=["foo"]),
configurable={"bar_model": "claude-3-sonnet-20240229"},
configurable={"bar_model": "claude-3-7-sonnet-20250219"},
)
assert model_with_config.model == "claude-3-sonnet-20240229" # type: ignore[attr-defined]
assert model_with_config.model == "claude-3-7-sonnet-20250219" # type: ignore[attr-defined]
assert model_with_config.model_dump() == { # type: ignore[attr-defined]
"name": None,
"bound": {
"name": None,
"disable_streaming": False,
"model": "claude-3-sonnet-20240229",
"model": "claude-3-7-sonnet-20250219",
"mcp_servers": None,
"max_tokens": 1024,
"temperature": None,

6
libs/langchain_v1/tests/unit_tests/chat_models/test_chat_models.py
View File

@ -196,17 +196,17 @@ def test_configurable_with_default() -> None:
model_with_config = model_with_tools.with_config(
RunnableConfig(tags=["foo"]),
configurable={"bar_model": "claude-3-sonnet-20240229"},
configurable={"bar_model": "claude-3-7-sonnet-20250219"},
)
assert model_with_config.model == "claude-3-sonnet-20240229" # type: ignore[attr-defined]
assert model_with_config.model == "claude-3-7-sonnet-20250219" # type: ignore[attr-defined]
assert model_with_config.model_dump() == { # type: ignore[attr-defined]
"name": None,
"bound": {
"name": None,
"disable_streaming": False,
"model": "claude-3-sonnet-20240229",
"model": "claude-3-7-sonnet-20250219",
"mcp_servers": None,
"max_tokens": 1024,
"temperature": None,

44
libs/partners/anthropic/langchain_anthropic/chat_models.py
View File

@ -7,14 +7,7 @@ import warnings
from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
from functools import cached_property
from operator import itemgetter
from typing import (
Any,
Callable,
Literal,
Optional,
Union,
cast,
)
from typing import Any, Callable, Literal, Optional, Union, cast
import anthropic
from langchain_core._api import beta, deprecated
@ -42,33 +35,16 @@ from langchain_core.messages import (
)
from langchain_core.messages.ai import InputTokenDetails, UsageMetadata
from langchain_core.messages.tool import tool_call_chunk as create_tool_call_chunk
from langchain_core.output_parsers import (
JsonOutputKeyToolsParser,
PydanticToolsParser,
)
from langchain_core.output_parsers import JsonOutputKeyToolsParser, PydanticToolsParser
from langchain_core.output_parsers.base import OutputParserLike
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
from langchain_core.runnables import (
Runnable,
RunnableMap,
RunnablePassthrough,
)
from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
from langchain_core.tools import BaseTool
from langchain_core.utils import (
from_env,
get_pydantic_field_names,
secret_from_env,
)
from langchain_core.utils import from_env, get_pydantic_field_names, secret_from_env
from langchain_core.utils.function_calling import convert_to_openai_tool
from langchain_core.utils.pydantic import is_basemodel_subclass
from langchain_core.utils.utils import _build_model_kwargs
from pydantic import (
BaseModel,
ConfigDict,
Field,
SecretStr,
model_validator,
)
from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
from typing_extensions import NotRequired, TypedDict
from langchain_anthropic._client_utils import (
@ -517,7 +493,7 @@ class ChatAnthropic(BaseChatModel):
Key init args — completion params:
model: str
Name of Anthropic model to use. e.g. ``'claude-3-sonnet-20240229'``.
Name of Anthropic model to use. e.g. ``'claude-3-7-sonnet-20250219'``.
temperature: float
Sampling temperature. Ranges from ``0.0`` to ``1.0``.
max_tokens: int
@ -543,7 +519,7 @@ class ChatAnthropic(BaseChatModel):
from langchain_anthropic import ChatAnthropic
llm = ChatAnthropic(
model="claude-3-sonnet-20240229",
model="claude-3-7-sonnet-20250219",
temperature=0,
max_tokens=1024,
timeout=None,
@ -583,7 +559,7 @@ class ChatAnthropic(BaseChatModel):
.. code-block:: python
AIMessage(content="J'aime la programmation.", response_metadata={'id': 'msg_01Trik66aiQ9Z1higrD5XFx3', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 25, 'output_tokens': 11}}, id='run-5886ac5f-3c2e-49f5-8a44-b1e92808c929-0', usage_metadata={'input_tokens': 25, 'output_tokens': 11, 'total_tokens': 36})
AIMessage(content="J'aime la programmation.", response_metadata={'id': 'msg_01Trik66aiQ9Z1higrD5XFx3', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 25, 'output_tokens': 11}}, id='run-5886ac5f-3c2e-49f5-8a44-b1e92808c929-0', usage_metadata={'input_tokens': 25, 'output_tokens': 11, 'total_tokens': 36})
Stream:
.. code-block:: python
@ -627,7 +603,7 @@ class ChatAnthropic(BaseChatModel):
.. code-block:: python
AIMessage(content="J'aime la programmation.", response_metadata={'id': 'msg_01Trik66aiQ9Z1higrD5XFx3', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 25, 'output_tokens': 11}}, id='run-5886ac5f-3c2e-49f5-8a44-b1e92808c929-0', usage_metadata={'input_tokens': 25, 'output_tokens': 11, 'total_tokens': 36})
AIMessage(content="J'aime la programmation.", response_metadata={'id': 'msg_01Trik66aiQ9Z1higrD5XFx3', 'model': 'claude-3-7-sonnet-20250219', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 25, 'output_tokens': 11}}, id='run-5886ac5f-3c2e-49f5-8a44-b1e92808c929-0', usage_metadata={'input_tokens': 25, 'output_tokens': 11, 'total_tokens': 36})
Tool calling:
.. code-block:: python
@ -1156,7 +1132,7 @@ class ChatAnthropic(BaseChatModel):
.. code-block:: python
{'id': 'msg_013xU6FHEGEq76aP4RgFerVT',
'model': 'claude-3-sonnet-20240229',
'model': 'claude-3-7-sonnet-20250219',
'stop_reason': 'end_turn',
'stop_sequence': None,
'usage': {'input_tokens': 25, 'output_tokens': 11}}