Paweł Domański
28 lines
914 B
Python
28 lines
914 B
Python
LANGCHAIN_TRACING_V2=True
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LANGCHAIN_ENDPOINT="https://eu.api.smith.langchain.com"
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LANGCHAIN_API_KEY="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"
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LANGCHAIN_PROJECT="pr-crushing-contingency-24"
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import openai
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from langsmith.wrappers import wrap_openai
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from langsmith import traceable
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import os
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os.environ["OPENAI_API_KEY"] = "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"
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# Auto-trace LLM calls in-context
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client = wrap_openai(openai.Client())
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@traceable # Auto-trace this function
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def pipeline(user_input: str):
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result = client.chat.completions.create(
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messages=[{"role": "user", "content": user_input}],
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model="gpt-3.5-turbo"
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)
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return result.choices[0].message.content
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print(pipeline("Hello, world!"))
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# Out: Hello there! How can I assist you today? |