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https://github.com/hwchase17/langchain.git
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Bagatur/docs smith context (#13139)
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@@ -134,7 +134,7 @@
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" name=\"langchain assistant\",\n",
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" instructions=\"You are a personal math tutor. Write and run code to answer math questions.\",\n",
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" tools=[{\"type\": \"code_interpreter\"}],\n",
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" model=\"gpt-4-1106-preview\"\n",
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" model=\"gpt-4-1106-preview\",\n",
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")\n",
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"output = interpreter_assistant.invoke({\"content\": \"What's 10 - 4 raised to the 2.7\"})\n",
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"output"
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@@ -184,7 +184,7 @@
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" instructions=\"You are a personal math tutor. Write and run code to answer math questions. You can also search the internet.\",\n",
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" tools=tools,\n",
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" model=\"gpt-4-1106-preview\",\n",
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" as_agent=True\n",
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" as_agent=True,\n",
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")"
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]
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},
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@@ -241,7 +241,7 @@
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" instructions=\"You are a personal math tutor. Write and run code to answer math questions.\",\n",
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" tools=tools,\n",
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" model=\"gpt-4-1106-preview\",\n",
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" as_agent=True\n",
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" as_agent=True,\n",
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")"
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]
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},
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@@ -254,6 +254,7 @@
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"source": [
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"from langchain.schema.agent import AgentFinish\n",
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"\n",
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"\n",
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"def execute_agent(agent, tools, input):\n",
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" tool_map = {tool.name: tool for tool in tools}\n",
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" response = agent.invoke(input)\n",
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@@ -262,9 +263,17 @@
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" for action in response:\n",
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" tool_output = tool_map[action.tool].invoke(action.tool_input)\n",
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" print(action.tool, action.tool_input, tool_output, end=\"\\n\\n\")\n",
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" tool_outputs.append({\"output\": tool_output, \"tool_call_id\": action.tool_call_id})\n",
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" response = agent.invoke({\"tool_outputs\": tool_outputs, \"run_id\": action.run_id, \"thread_id\": action.thread_id})\n",
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" \n",
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" tool_outputs.append(\n",
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" {\"output\": tool_output, \"tool_call_id\": action.tool_call_id}\n",
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" )\n",
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" response = agent.invoke(\n",
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" {\n",
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" \"tool_outputs\": tool_outputs,\n",
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" \"run_id\": action.run_id,\n",
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" \"thread_id\": action.thread_id,\n",
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" }\n",
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" )\n",
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"\n",
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" return response"
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]
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},
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@@ -306,7 +315,9 @@
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}
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],
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"source": [
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"next_response = execute_agent(agent, tools, {\"content\": \"now add 17.241\", \"thread_id\": response.thread_id})\n",
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"next_response = execute_agent(\n",
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" agent, tools, {\"content\": \"now add 17.241\", \"thread_id\": response.thread_id}\n",
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")\n",
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"print(next_response.return_values[\"output\"])"
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]
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},
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@@ -449,16 +460,22 @@
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"from langchain.prompts import ChatPromptTemplate\n",
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"from langchain.pydantic_v1 import BaseModel, Field\n",
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"\n",
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"\n",
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"class GetCurrentWeather(BaseModel):\n",
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" \"\"\"Get the current weather in a location.\"\"\"\n",
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"\n",
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" location: str = Field(description=\"The city and state, e.g. San Francisco, CA\")\n",
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" unit: Literal[\"celsius\", \"fahrenheit\"] = Field(default=\"fahrenheit\", description=\"The temperature unit, default to fahrenheit\")\n",
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" \n",
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"prompt = ChatPromptTemplate.from_messages([\n",
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" (\"system\", \"You are a helpful assistant\"),\n",
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" (\"user\", \"{input}\")\n",
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"])\n",
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"model = ChatOpenAI(model=\"gpt-3.5-turbo-1106\").bind(tools=[convert_pydantic_to_openai_tool(GetCurrentWeather)])\n",
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" unit: Literal[\"celsius\", \"fahrenheit\"] = Field(\n",
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" default=\"fahrenheit\", description=\"The temperature unit, default to fahrenheit\"\n",
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" )\n",
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"\n",
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"\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [(\"system\", \"You are a helpful assistant\"), (\"user\", \"{input}\")]\n",
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")\n",
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"model = ChatOpenAI(model=\"gpt-3.5-turbo-1106\").bind(\n",
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" tools=[convert_pydantic_to_openai_tool(GetCurrentWeather)]\n",
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")\n",
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"chain = prompt | model | PydanticToolsParser(tools=[GetCurrentWeather])\n",
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"\n",
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"chain.invoke({\"input\": \"what's the weather in NYC, LA, and SF\"})"
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