tutorial 74

tutorial74/doc1.txt

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+
+Aiden Blake lives in San Francisco, California. He works as a software engineer at a leading tech company. Aiden is 28 years old.

tutorial74/doc10.txt

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+Ella Parker resides in Portland, Oregon. She is a chef at a popular local restaurant. Ella is 26 years old.

tutorial74/doc2.txt

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+Harper Quinn resides in Austin, Texas. She is employed as a marketing manager for a renowned fashion brand. Harper is 32 years old.

tutorial74/doc3.txt

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+Liam Carter lives in New York City, New York. He works as an investment banker on Wall Street. Liam is 35 years old.

tutorial74/doc4.txt

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+Ava Morgan resides in Seattle, Washington. She is a graphic designer at a prominent design firm. Ava is 27 years old.

tutorial74/doc5.txt

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+Ethan Hayes lives in Chicago, Illinois. He works as a mechanical engineer at a major manufacturing company. Ethan is 30 years old.

tutorial74/doc6.txt

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+Chloe Bennett resides in Denver, Colorado. She is a school teacher at a well-known elementary school. Chloe is 29 years old.

tutorial74/doc7.txt

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+Noah Riley lives in Miami, Florida. He works as a real estate agent for a top realty company. Noah is 33 years old.

tutorial74/doc8.txt

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+Grace Taylor** resides in Boston, Massachusetts. She is a research scientist at a leading pharmaceutical company. Grace is 31 years old.

tutorial74/doc9.txt

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+Mason Brooks lives in Los Angeles, California. He works as a film director in the Hollywood industry. Mason is 37 years old.

tutorial74/main.py

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+from langchain_openai import ChatOpenAI
+from langchain_community.document_loaders import DirectoryLoader
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains.combine_documents import create_stuff_documents_chain
+import os
+
+prompt=ChatPromptTemplate.from_messages(
+    [
+        ("system","what are everyone's age:\n\n{context}")
+    ]
+)
+llm=ChatOpenAI(model="gpt-4o")
+chain=create_stuff_documents_chain(llm,prompt)
+loader=DirectoryLoader(path=os.getcwd(),glob="**/*.txt")
+docs=loader.load()
+print(len(docs))
+response=chain.invoke({"context":docs})
+print(response)