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langchain: Update Langchain -> Langgraph migration docs for the deprecation of the messages_modifier parameter. (#24839)
**Description:** Updated the Langgraph migration docs to use `state_modifier` rather than `messages_modifier` **Issue:** N/A **Dependencies:** N/A - [ X] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
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@ -41,7 +41,7 @@
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"id": "662fac50",
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"metadata": {},
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"outputs": [],
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@ -50,6 +50,26 @@
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"%pip install -U langgraph langchain langchain-openai"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6f8ec38f",
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"metadata": {},
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"source": [
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"Then, set your OpenAI API key."
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"cell_type": "code",
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"id": "5fca87ef",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = \"sk-...\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "8e50635c-1671-46e6-be65-ce95f8167c2f",
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@ -62,7 +82,7 @@
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"cell_type": "code",
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"id": "1e425fea-2796-4b99-bee6-9a6ffe73f756",
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"metadata": {},
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"outputs": [],
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@ -95,7 +115,7 @@
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"id": "03ea357c-9c36-4464-b2cc-27bd150e1554",
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"metadata": {},
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"outputs": [
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@ -106,7 +126,7 @@
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" 'output': 'The value of `magic_function(3)` is 5.'}"
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]
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},
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"execution_count": 2,
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"execution_count": 3,
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"output_type": "execute_result"
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@ -142,7 +162,7 @@
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"id": "53a3737a-d167-4255-89bf-20ac37f89a3e",
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"metadata": {},
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"outputs": [
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@ -153,7 +173,7 @@
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" 'output': 'The value of `magic_function(3)` is 5.'}"
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]
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},
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"execution_count": 3,
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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@ -173,7 +193,7 @@
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 5,
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"id": "74ecebe3-512e-409c-a661-bdd5b0a2b782",
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"metadata": {},
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"outputs": [
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@ -181,10 +201,10 @@
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"data": {
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"text/plain": [
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"{'input': 'Pardon?',\n",
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" 'output': 'The result of applying `magic_function` to the input 3 is 5.'}"
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" 'output': 'The value you get when you apply `magic_function` to the input 3 is 5.'}"
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]
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},
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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@ -223,7 +243,7 @@
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 6,
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"id": "a9a11ccd-75e2-4c11-844d-a34870b0ff91",
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"metadata": {},
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"outputs": [
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@ -234,7 +254,7 @@
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" 'output': 'El valor de `magic_function(3)` es 5.'}"
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]
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},
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"execution_count": 5,
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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@ -263,19 +283,19 @@
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"source": [
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"Now, let's pass a custom system message to [react agent executor](https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent).\n",
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"\n",
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"LangGraph's prebuilt `create_react_agent` does not take a prompt template directly as a parameter, but instead takes a [`messages_modifier`](https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent) parameter. This modifies messages before they are passed into the model, and can be one of four values:\n",
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"LangGraph's prebuilt `create_react_agent` does not take a prompt template directly as a parameter, but instead takes a [`state_modifier`](https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent) parameter. This modifies the graph state before the llm is called, and can be one of four values:\n",
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"\n",
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"- A `SystemMessage`, which is added to the beginning of the list of messages.\n",
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"- A `string`, which is converted to a `SystemMessage` and added to the beginning of the list of messages.\n",
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"- A `Callable`, which should take in a list of messages. The output is then passed to the language model.\n",
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"- Or a [`Runnable`](/docs/concepts/#langchain-expression-language-lcel), which should should take in a list of messages. The output is then passed to the language model.\n",
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"- A `Callable`, which should take in full graph state. The output is then passed to the language model.\n",
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"- Or a [`Runnable`](/docs/concepts/#langchain-expression-language-lcel), which should take in full graph state. The output is then passed to the language model.\n",
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"\n",
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"Here's how it looks in action:"
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]
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 7,
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"id": "a9486805-676a-4d19-a5c4-08b41b172989",
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"metadata": {},
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"outputs": [],
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@ -287,7 +307,7 @@
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"# This could also be a SystemMessage object\n",
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"# system_message = SystemMessage(content=\"You are a helpful assistant. Respond only in Spanish.\")\n",
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"\n",
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"app = create_react_agent(model, tools, messages_modifier=system_message)\n",
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"app = create_react_agent(model, tools, state_modifier=system_message)\n",
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"\n",
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"\n",
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"messages = app.invoke({\"messages\": [(\"user\", query)]})"
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@ -304,7 +324,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 8,
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"id": "d369ab45-0c82-45f4-9d3e-8efb8dd47e2c",
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"metadata": {},
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"outputs": [
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@ -317,8 +337,8 @@
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}
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],
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"source": [
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"from langchain_core.messages import AnyMessage\n",
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"from langgraph.prebuilt import create_react_agent\n",
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"from langgraph.prebuilt.chat_agent_executor import AgentState\n",
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"\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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@ -328,13 +348,13 @@
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")\n",
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"\n",
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"\n",
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"def _modify_messages(messages: list[AnyMessage]):\n",
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" return prompt.invoke({\"messages\": messages}).to_messages() + [\n",
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"def _modify_state_messages(state: AgentState):\n",
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" return prompt.invoke({\"messages\": state[\"messages\"]}).to_messages() + [\n",
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" (\"user\", \"Also say 'Pandamonium!' after the answer.\")\n",
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" ]\n",
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"\n",
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"\n",
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"app = create_react_agent(model, tools, messages_modifier=_modify_messages)\n",
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"app = create_react_agent(model, tools, state_modifier=_modify_state_messages)\n",
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"\n",
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"\n",
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"messages = app.invoke({\"messages\": [(\"human\", query)]})\n",
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@ -366,8 +386,8 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "1fb52a2c",
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"execution_count": 9,
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"id": "b97beba5-8f74-430c-9399-91b77c8fa15c",
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"metadata": {},
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"outputs": [
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{
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@ -376,7 +396,7 @@
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"text": [
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"Hi Polly! The output of the magic function for the input 3 is 5.\n",
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"---\n",
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"Yes, I remember your name, Polly! How can I assist you further?\n",
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"Yes, your name is Polly!\n",
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"---\n",
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"The output of the magic function for the input 3 is 5.\n"
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]
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@ -384,14 +404,14 @@
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],
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"source": [
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"from langchain.agents import AgentExecutor, create_tool_calling_agent\n",
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"from langchain_community.chat_message_histories import ChatMessageHistory\n",
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"from langchain_core.chat_history import InMemoryChatMessageHistory\n",
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"from langchain_core.prompts import ChatPromptTemplate\n",
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"from langchain_core.runnables.history import RunnableWithMessageHistory\n",
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"from langchain_core.tools import tool\n",
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"from langchain_openai import ChatOpenAI\n",
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"\n",
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"model = ChatOpenAI(model=\"gpt-4o\")\n",
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"memory = ChatMessageHistory(session_id=\"test-session\")\n",
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"memory = InMemoryChatMessageHistory(session_id=\"test-session\")\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\"system\", \"You are a helpful assistant.\"),\n",
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "035e1253",
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"execution_count": 10,
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"id": "baca3dc6-678b-4509-9275-2fd653102898",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Hi Polly! The output of the magic_function for the input 3 is 5.\n",
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"Hi Polly! The output of the magic_function for the input of 3 is 5.\n",
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"---\n",
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"Yes, your name is Polly!\n",
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"---\n",
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"The output of the magic_function for the input 3 was 5.\n"
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"The output of the magic_function for the input of 3 was 5.\n"
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]
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}
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],
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"source": [
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"from langchain_core.messages import SystemMessage\n",
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"from langgraph.checkpoint import MemorySaver # an in-memory checkpointer\n",
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"from langgraph.prebuilt import create_react_agent\n",
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"\n",
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"\n",
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"memory = MemorySaver()\n",
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"app = create_react_agent(\n",
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" model, tools, messages_modifier=system_message, checkpointer=memory\n",
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" model, tools, state_modifier=system_message, checkpointer=memory\n",
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")\n",
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"\n",
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"config = {\"configurable\": {\"thread_id\": \"test-thread\"}}\n",
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "d640feb3",
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"execution_count": 11,
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"id": "e62843c4-1107-41f0-a50b-aea256e28053",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'actions': [ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls'}, id='run-c68fd76f-a3c3-4c3c-bfd7-748c171ed4b8', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'index': 0}])], tool_call_id='call_q9MgGFjqJbV2xSUX93WqxmOt')], 'messages': [AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls'}, id='run-c68fd76f-a3c3-4c3c-bfd7-748c171ed4b8', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'index': 0}])]}\n",
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"{'steps': [AgentStep(action=ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls'}, id='run-c68fd76f-a3c3-4c3c-bfd7-748c171ed4b8', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_q9MgGFjqJbV2xSUX93WqxmOt', 'index': 0}])], tool_call_id='call_q9MgGFjqJbV2xSUX93WqxmOt'), observation=5)], 'messages': [FunctionMessage(content='5', name='magic_function')]}\n",
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"{'actions': [ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518'}, id='run-5664e138-7085-4da7-a49e-5656a87b8d78', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'type': 'tool_call'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'index': 0, 'type': 'tool_call_chunk'}])], tool_call_id='call_1exy0rScfPmo4fy27FbQ5qJ2')], 'messages': [AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518'}, id='run-5664e138-7085-4da7-a49e-5656a87b8d78', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'type': 'tool_call'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'index': 0, 'type': 'tool_call_chunk'}])]}\n",
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"{'steps': [AgentStep(action=ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518'}, id='run-5664e138-7085-4da7-a49e-5656a87b8d78', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'type': 'tool_call'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_1exy0rScfPmo4fy27FbQ5qJ2', 'index': 0, 'type': 'tool_call_chunk'}])], tool_call_id='call_1exy0rScfPmo4fy27FbQ5qJ2'), observation=5)], 'messages': [FunctionMessage(content='5', name='magic_function')]}\n",
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"{'output': 'The value of `magic_function(3)` is 5.', 'messages': [AIMessage(content='The value of `magic_function(3)` is 5.')]}\n"
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]
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}
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "86abbe07",
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"execution_count": 12,
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"id": "076ebc85-f804-4093-a25a-a16334c9898e",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_yTjXXibj76tyFyPRa1soLo0S', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 70, 'total_tokens': 84}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-b275f314-c42e-4e77-9dec-5c23f7dbd53b-0', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_yTjXXibj76tyFyPRa1soLo0S'}])]}}\n",
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"{'tools': {'messages': [ToolMessage(content='5', name='magic_function', id='41c5f227-528d-4483-a313-b03b23b1d327', tool_call_id='call_yTjXXibj76tyFyPRa1soLo0S')]}}\n",
|
||||
"{'agent': {'messages': [AIMessage(content='The value of `magic_function(3)` is 5.', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 93, 'total_tokens': 107}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'stop', 'logprobs': None}, id='run-0ef12b6e-415d-4758-9b62-5e5e1b350072-0')]}}\n"
|
||||
"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_my9rzFSKR4T1yYKwCsfbZB8A', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 61, 'total_tokens': 75}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_bc2a86f5f5', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-dd705555-8fae-4fb1-a033-5d99a23e3c22-0', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_my9rzFSKR4T1yYKwCsfbZB8A', 'type': 'tool_call'}], usage_metadata={'input_tokens': 61, 'output_tokens': 14, 'total_tokens': 75})]}}\n",
|
||||
"{'tools': {'messages': [ToolMessage(content='5', name='magic_function', tool_call_id='call_my9rzFSKR4T1yYKwCsfbZB8A')]}}\n",
|
||||
"{'agent': {'messages': [AIMessage(content='The value of `magic_function(3)` is 5.', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 84, 'total_tokens': 98}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'stop', 'logprobs': None}, id='run-698cad05-8cb2-4d08-8c2a-881e354f6cc7-0', usage_metadata={'input_tokens': 84, 'output_tokens': 14, 'total_tokens': 98})]}}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain_core.messages import AnyMessage\n",
|
||||
"from langgraph.prebuilt import create_react_agent\n",
|
||||
"from langgraph.prebuilt.chat_agent_executor import AgentState\n",
|
||||
"\n",
|
||||
"prompt = ChatPromptTemplate.from_messages(\n",
|
||||
" [\n",
|
||||
@ -611,12 +630,11 @@
|
||||
")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def _modify_messages(messages: list[AnyMessage]):\n",
|
||||
" return prompt.invoke({\"messages\": messages}).to_messages()\n",
|
||||
"def _modify_state_messages(state: AgentState):\n",
|
||||
" return prompt.invoke({\"messages\": state[\"messages\"]}).to_messages()\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"app = create_react_agent(model, tools, messages_modifier=_modify_messages)\n",
|
||||
"\n",
|
||||
"app = create_react_agent(model, tools, state_modifier=_modify_state_messages)\n",
|
||||
"\n",
|
||||
"for step in app.stream({\"messages\": [(\"human\", query)]}, stream_mode=\"updates\"):\n",
|
||||
" print(step)"
|
||||
@ -637,14 +655,14 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "4eff44bc-a620-4c8a-97b1-268692a842bb",
|
||||
"id": "a2f720f3-c121-4be2-b498-92c16bb44b0a",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"[(ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_ABI4hftfEdnVgKyfF6OzZbca', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls'}, id='run-837e794f-cfd8-40e0-8abc-4d98ced11b75', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_ABI4hftfEdnVgKyfF6OzZbca'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_ABI4hftfEdnVgKyfF6OzZbca', 'index': 0}])], tool_call_id='call_ABI4hftfEdnVgKyfF6OzZbca'), 5)]\n"
|
||||
"[(ToolAgentAction(tool='magic_function', tool_input={'input': 3}, log=\"\\nInvoking: `magic_function` with `{'input': 3}`\\n\\n\\n\", message_log=[AIMessageChunk(content='', additional_kwargs={'tool_calls': [{'index': 0, 'id': 'call_uPZ2D1Bo5mdED3gwgaeWURrf', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'finish_reason': 'tool_calls', 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518'}, id='run-a792db4a-278d-4090-82ae-904a30eada93', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_uPZ2D1Bo5mdED3gwgaeWURrf', 'type': 'tool_call'}], tool_call_chunks=[{'name': 'magic_function', 'args': '{\"input\":3}', 'id': 'call_uPZ2D1Bo5mdED3gwgaeWURrf', 'index': 0, 'type': 'tool_call_chunk'}])], tool_call_id='call_uPZ2D1Bo5mdED3gwgaeWURrf'), 5)]\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -667,16 +685,16 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "4f4364ea-dffe-4d25-bdce-ef7d0020b880",
|
||||
"id": "ef23117a-5ccb-42ce-80c3-ea49a9d3a942",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'messages': [HumanMessage(content='what is the value of magic_function(3)?', id='0f63e437-c4d8-4da9-b6f5-b293ebfe4a64'),\n",
|
||||
" AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_S96v28LlI6hNkQrNnIio0JPh', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 64, 'total_tokens': 78}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-ffef7898-14b1-4537-ad90-7c000a8a5d25-0', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_S96v28LlI6hNkQrNnIio0JPh'}]),\n",
|
||||
" ToolMessage(content='5', name='magic_function', id='fbd9df4e-1dda-4d3e-9044-b001f7875476', tool_call_id='call_S96v28LlI6hNkQrNnIio0JPh'),\n",
|
||||
" AIMessage(content='The value of `magic_function(3)` is 5.', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 87, 'total_tokens': 101}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'stop', 'logprobs': None}, id='run-e5d94c54-d9f4-45cd-be8e-a9101a8d88d6-0')]}"
|
||||
"{'messages': [HumanMessage(content='what is the value of magic_function(3)?', id='cd7d0f49-a0e0-425a-b2b0-603a716058ed'),\n",
|
||||
" AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_VfZ9287DuybOSrBsQH5X12xf', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 55, 'total_tokens': 69}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-a1e965cd-bf61-44f9-aec1-8aaecb80955f-0', tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_VfZ9287DuybOSrBsQH5X12xf', 'type': 'tool_call'}], usage_metadata={'input_tokens': 55, 'output_tokens': 14, 'total_tokens': 69}),\n",
|
||||
" ToolMessage(content='5', name='magic_function', id='20d5c2fe-a5d8-47fa-9e04-5282642e2039', tool_call_id='call_VfZ9287DuybOSrBsQH5X12xf'),\n",
|
||||
" AIMessage(content='The value of `magic_function(3)` is 5.', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 78, 'total_tokens': 92}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'stop', 'logprobs': None}, id='run-abf9341c-ef41-4157-935d-a3be5dfa2f41-0', usage_metadata={'input_tokens': 78, 'output_tokens': 14, 'total_tokens': 92})]}"
|
||||
]
|
||||
},
|
||||
"execution_count": 13,
|
||||
@ -708,7 +726,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"execution_count": 16,
|
||||
"id": "16f189a7-fc78-4cb5-aa16-a94ca06401a6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
@ -724,7 +742,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"execution_count": 17,
|
||||
"id": "c96aefd7-6f6e-4670-aca6-1ac3d4e7871f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -739,11 +757,7 @@
|
||||
"Invoking: `magic_function` with `{'input': '3'}`\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[0m\u001b[36;1m\u001b[1;3mSorry, there was an error. Please try again.\u001b[0m\u001b[32;1m\u001b[1;3m\n",
|
||||
"Invoking: `magic_function` with `{'input': '3'}`\n",
|
||||
"responded: Parece que hubo un error al intentar obtener el valor de `magic_function(3)`. Permíteme intentarlo de nuevo.\n",
|
||||
"\n",
|
||||
"\u001b[0m\u001b[36;1m\u001b[1;3mSorry, there was an error. Please try again.\u001b[0m\u001b[32;1m\u001b[1;3mAún no puedo obtener el valor de `magic_function(3)`. ¿Hay algo más en lo que pueda ayudarte?\u001b[0m\n",
|
||||
"\u001b[0m\u001b[36;1m\u001b[1;3mSorry, there was an error. Please try again.\u001b[0m\u001b[32;1m\u001b[1;3mParece que hubo un error al intentar calcular el valor de la función mágica. ¿Te gustaría que lo intente de nuevo?\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
@ -752,10 +766,10 @@
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'input': 'what is the value of magic_function(3)?',\n",
|
||||
" 'output': 'Aún no puedo obtener el valor de `magic_function(3)`. ¿Hay algo más en lo que pueda ayudarte?'}"
|
||||
" 'output': 'Parece que hubo un error al intentar calcular el valor de la función mágica. ¿Te gustaría que lo intente de nuevo?'}"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"execution_count": 17,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -797,7 +811,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"execution_count": 18,
|
||||
"id": "b974a91f-6ae8-4644-83d9-73666258a6db",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -805,12 +819,12 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"('human', 'what is the value of magic_function(3)?')\n",
|
||||
"content='' additional_kwargs={'tool_calls': [{'id': 'call_pFdKcCu5taDTtOOfX14vEDRp', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 64, 'total_tokens': 78}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-25836468-ba7e-43be-a7cf-76bba06a2a08-0' tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_pFdKcCu5taDTtOOfX14vEDRp'}]\n",
|
||||
"content='Sorry, there was an error. Please try again.' name='magic_function' id='1a08b883-9c7b-4969-9e9b-67ce64cdcb5f' tool_call_id='call_pFdKcCu5taDTtOOfX14vEDRp'\n",
|
||||
"content='It seems there was an error when trying to apply the magic function. Let me try again.' additional_kwargs={'tool_calls': [{'id': 'call_DA0lpDIkBFg2GHy4WsEcZG4K', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 34, 'prompt_tokens': 97, 'total_tokens': 131}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-d571b774-0ea3-4e35-8b7d-f32932c3f3cc-0' tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_DA0lpDIkBFg2GHy4WsEcZG4K'}]\n",
|
||||
"content='Sorry, there was an error. Please try again.' name='magic_function' id='0b45787b-c82a-487f-9a5a-de129c30460f' tool_call_id='call_DA0lpDIkBFg2GHy4WsEcZG4K'\n",
|
||||
"content='It appears that there is a consistent issue when trying to apply the magic function to the input \"3.\" This could be due to various reasons, such as the input not being in the correct format or an internal error.\\n\\nIf you have any other questions or if there\\'s something else you\\'d like to try, please let me know!' response_metadata={'token_usage': {'completion_tokens': 66, 'prompt_tokens': 153, 'total_tokens': 219}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'stop', 'logprobs': None} id='run-50a962e6-21b7-4327-8dea-8e2304062627-0'\n"
|
||||
"content='what is the value of magic_function(3)?' id='74e2d5e8-2b59-4820-979c-8d11ecfc14c2'\n",
|
||||
"content='' additional_kwargs={'tool_calls': [{'id': 'call_ihtrH6IG95pDXpKluIwAgi3J', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 55, 'total_tokens': 69}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-5a35e465-8a08-43dd-ac8b-4a76dcace305-0' tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_ihtrH6IG95pDXpKluIwAgi3J', 'type': 'tool_call'}] usage_metadata={'input_tokens': 55, 'output_tokens': 14, 'total_tokens': 69}\n",
|
||||
"content='Sorry, there was an error. Please try again.' name='magic_function' id='8c37c19b-3586-46b1-aab9-a045786801a2' tool_call_id='call_ihtrH6IG95pDXpKluIwAgi3J'\n",
|
||||
"content='It seems there was an error in processing the request. Let me try again.' additional_kwargs={'tool_calls': [{'id': 'call_iF0vYWAd6rfely0cXSqdMOnF', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 31, 'prompt_tokens': 88, 'total_tokens': 119}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-eb88ec77-d492-43a5-a5dd-4cefef9a6920-0' tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_iF0vYWAd6rfely0cXSqdMOnF', 'type': 'tool_call'}] usage_metadata={'input_tokens': 88, 'output_tokens': 31, 'total_tokens': 119}\n",
|
||||
"content='Sorry, there was an error. Please try again.' name='magic_function' id='c9ff261f-a0f1-4c92-a9f2-cd749f62d911' tool_call_id='call_iF0vYWAd6rfely0cXSqdMOnF'\n",
|
||||
"content='I am currently unable to process the request with the input \"3\" for the `magic_function`. If you have any other questions or need assistance with something else, please let me know!' response_metadata={'token_usage': {'completion_tokens': 39, 'prompt_tokens': 141, 'total_tokens': 180}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'stop', 'logprobs': None} id='run-d42508aa-f286-4b57-80fb-f8a76736d470-0' usage_metadata={'input_tokens': 141, 'output_tokens': 39, 'total_tokens': 180}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -847,7 +861,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"execution_count": 19,
|
||||
"id": "4b8498fc-a7af-4164-a401-d8714f082306",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -874,7 +888,7 @@
|
||||
" 'output': 'Agent stopped due to max iterations.'}"
|
||||
]
|
||||
},
|
||||
"execution_count": 17,
|
||||
"execution_count": 19,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -917,7 +931,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 18,
|
||||
"execution_count": 20,
|
||||
"id": "a2b29113-e6be-4f91-aa4c-5c63dea3e423",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -925,7 +939,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_HaQkeCwD5QskzJzFixCBacZ4', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 64, 'total_tokens': 78}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-596c9200-771f-436d-8576-72fcb81620f1-0', tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_HaQkeCwD5QskzJzFixCBacZ4'}])]}}\n",
|
||||
"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_FKiTkTd0Ffd4rkYSzERprf1M', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 55, 'total_tokens': 69}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-b842f7b6-ec10-40f8-8c0e-baa220b77e91-0', tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_FKiTkTd0Ffd4rkYSzERprf1M', 'type': 'tool_call'}], usage_metadata={'input_tokens': 55, 'output_tokens': 14, 'total_tokens': 69})]}}\n",
|
||||
"------\n",
|
||||
"{'input': 'what is the value of magic_function(3)?', 'output': 'Agent stopped due to max iterations.'}\n"
|
||||
]
|
||||
@ -956,7 +970,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 19,
|
||||
"execution_count": 21,
|
||||
"id": "e9eb55f4-a321-4bac-b52d-9e43b411cf92",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -964,7 +978,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_4agJXUHtmHrOOMogjF6ZuzAv', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 64, 'total_tokens': 78}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-a1c77db7-405f-43d9-8d57-751f2ca1a58c-0', tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_4agJXUHtmHrOOMogjF6ZuzAv'}])]}}\n",
|
||||
"{'agent': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_WoOB8juagB08xrP38twYlYKR', 'function': {'arguments': '{\"input\":\"3\"}', 'name': 'magic_function'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 55, 'total_tokens': 69}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-73dee47e-30ab-42c9-bb0c-6f227cac96cd-0', tool_calls=[{'name': 'magic_function', 'args': {'input': '3'}, 'id': 'call_WoOB8juagB08xrP38twYlYKR', 'type': 'tool_call'}], usage_metadata={'input_tokens': 55, 'output_tokens': 14, 'total_tokens': 69})]}}\n",
|
||||
"------\n",
|
||||
"Task Cancelled.\n"
|
||||
]
|
||||
@ -1005,7 +1019,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 20,
|
||||
"execution_count": 22,
|
||||
"id": "3f6e2cf2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -1067,7 +1081,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 21,
|
||||
"execution_count": 23,
|
||||
"id": "73cabbc4",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -1075,10 +1089,10 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"('human', 'what is the value of magic_function(3)?')\n",
|
||||
"content='' additional_kwargs={'tool_calls': [{'id': 'call_bTURmOn9C8zslmn0kMFeykIn', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 64, 'total_tokens': 78}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-0844a504-7e6b-4ea6-a069-7017e38121ee-0' tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_bTURmOn9C8zslmn0kMFeykIn'}]\n",
|
||||
"content='Sorry there was an error, please try again.' name='magic_function' id='00d5386f-eb23-4628-9a29-d9ce6a7098cc' tool_call_id='call_bTURmOn9C8zslmn0kMFeykIn'\n",
|
||||
"content='' additional_kwargs={'tool_calls': [{'id': 'call_JYqvvvWmXow2u012DuPoDHFV', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 96, 'total_tokens': 110}, 'model_name': 'gpt-4o', 'system_fingerprint': 'fp_729ea513f7', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-b73b1b1c-c829-4348-98cd-60b315c85448-0' tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_JYqvvvWmXow2u012DuPoDHFV'}]\n",
|
||||
"content='what is the value of magic_function(3)?' id='4fa7fbe5-758c-47a3-9268-717665d10680'\n",
|
||||
"content='' additional_kwargs={'tool_calls': [{'id': 'call_ujE0IQBbIQnxcF9gsZXQfdhF', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 55, 'total_tokens': 69}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-65d689aa-baee-4342-a5d2-048feefab418-0' tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_ujE0IQBbIQnxcF9gsZXQfdhF', 'type': 'tool_call'}] usage_metadata={'input_tokens': 55, 'output_tokens': 14, 'total_tokens': 69}\n",
|
||||
"content='Sorry there was an error, please try again.' name='magic_function' id='ef8ddf1d-9ad7-4ac0-b784-b673c4d94bbd' tool_call_id='call_ujE0IQBbIQnxcF9gsZXQfdhF'\n",
|
||||
"content='It seems there was an issue with the previous attempt. Let me try that again.' additional_kwargs={'tool_calls': [{'id': 'call_GcsAfCFUHJ50BN2IOWnwTbQ7', 'function': {'arguments': '{\"input\":3}', 'name': 'magic_function'}, 'type': 'function'}]} response_metadata={'token_usage': {'completion_tokens': 32, 'prompt_tokens': 87, 'total_tokens': 119}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_4e2b2da518', 'finish_reason': 'tool_calls', 'logprobs': None} id='run-54527c4b-8ff0-4ee8-8abf-224886bd222e-0' tool_calls=[{'name': 'magic_function', 'args': {'input': 3}, 'id': 'call_GcsAfCFUHJ50BN2IOWnwTbQ7', 'type': 'tool_call'}] usage_metadata={'input_tokens': 87, 'output_tokens': 32, 'total_tokens': 119}\n",
|
||||
"{'input': 'what is the value of magic_function(3)?', 'output': 'Agent stopped due to max iterations.'}\n"
|
||||
]
|
||||
}
|
||||
@ -1118,7 +1132,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 22,
|
||||
"execution_count": 24,
|
||||
"id": "b94bb169",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -1216,12 +1230,12 @@
|
||||
"source": [
|
||||
"### In LangGraph\n",
|
||||
"\n",
|
||||
"We can use the [`messages_modifier`](https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent) just as before when passing in [prompt templates](#prompt-templates)."
|
||||
"We can use the [`state_modifier`](https://langchain-ai.github.io/langgraph/reference/prebuilt/#create_react_agent) just as before when passing in [prompt templates](#prompt-templates)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"execution_count": 25,
|
||||
"id": "b309ba9a",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -1246,9 +1260,9 @@
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain_core.messages import AnyMessage\n",
|
||||
"from langgraph.errors import GraphRecursionError\n",
|
||||
"from langgraph.prebuilt import create_react_agent\n",
|
||||
"from langgraph.prebuilt.chat_agent_executor import AgentState\n",
|
||||
"\n",
|
||||
"magic_step_num = 1\n",
|
||||
"\n",
|
||||
@ -1265,12 +1279,12 @@
|
||||
"tools = [magic_function]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def _modify_messages(messages: list[AnyMessage]):\n",
|
||||
"def _modify_state_messages(state: AgentState):\n",
|
||||
" # Give the agent amnesia, only keeping the original user query\n",
|
||||
" return [(\"system\", \"You are a helpful assistant\"), messages[0]]\n",
|
||||
" return [(\"system\", \"You are a helpful assistant\"), state[\"messages\"][0]]\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"app = create_react_agent(model, tools, messages_modifier=_modify_messages)\n",
|
||||
"app = create_react_agent(model, tools, state_modifier=_modify_state_messages)\n",
|
||||
"\n",
|
||||
"try:\n",
|
||||
" for step in app.stream({\"messages\": [(\"human\", query)]}, stream_mode=\"updates\"):\n",
|
||||
@ -1308,7 +1322,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.2"
|
||||
"version": "3.10.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user