agents

1 ActiveLoop Courses/1 LangChain & Vector Databases in Production/8 Using Language Model as Reasoning Engines with Agents/1 What are Agents: Agents as Content Generators and Reasoning Engines/1_agent.py

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+# Importing necessary modules
+from langchain.agents import load_tools, initialize_agent
+from langchain.agents import AgentType
+from langchain.llms import OpenAI
+
+# Loading the language model to control the agent
+llm = OpenAI(model="gpt-3.5-turbo-instruct", temperature=0)
+
+# Loading some tools to use. The llm-math tool uses an LLM, so we pass that in.
+tools = load_tools(["google-search", "llm-math"], llm=llm)
+
+# Initializing an agent with the tools, the language model, and the type of agent we want to use.
+agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
+
+# Testing the agent
+query = "What's the result of 1000 plus the number of goals scored in the soccer world cup in 2018?"
+response = agent.run(query)
+print(response)

1 ActiveLoop Courses/1 LangChain & Vector Databases in Production/8 Using Language Model as Reasoning Engines with Agents/1 What are Agents: Agents as Content Generators and Reasoning Engines/2_generate_story.py

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+# Importing necessary modules
+from langchain.agents import initialize_agent, AgentType
+from langchain.llms import OpenAI
+from langchain.agents import Tool
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+
+prompt = PromptTemplate(
+    input_variables=["query"],
+    template="You're a renowned science fiction writer. {query}"
+)
+
+# Initialize the language model
+llm = OpenAI(model="gpt-3.5-turbo-instruct", temperature=0)
+llm_chain = LLMChain(llm=llm, prompt=prompt)
+
+tools = [
+    Tool(
+        name='Science Fiction Writer',
+        func=llm_chain.run,
+        description='Use this tool for generating science fiction stories. Input should be a command about generating specific types of stories.'
+    )
+]
+
+# Initializing an agent with the tools, the language model, and the type of agent we want to use.
+agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
+
+# Testing the agent with the new prompt
+response = agent.run("Compose an epic science fiction saga about interstellar explorers")
+print(response)

1 ActiveLoop Courses/1 LangChain & Vector Databases in Production/8 Using Language Model as Reasoning Engines with Agents/1 What are Agents: Agents as Content Generators and Reasoning Engines/requirements.txt

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+pip install numexpr