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Example: ```python import anthropic from langsmith import wrappers client = wrappers.wrap_anthropic(anthropic.Anthropic()) # Use Anthropic client same as you normally would: system = "You are a helpful assistant." messages = [ { "role": "user", "content": "What physics breakthroughs do you predict will happen by 2300?", } ] completion = client.messages.create( model="claude-3-5-sonnet-latest", messages=messages, max_tokens=1000, system=system, ) print(completion.content) # With raw response to access headers: raw_response = client.messages.with_raw_response.create( model="claude-3-5-sonnet-latest", messages=messages, max_tokens=1000, system=system, ) print(raw_response.headers) # Access HTTP headers message = raw_response.parse() # Get parsed response # You can also use the streaming context manager: with client.messages.stream( model="claude-3-5-sonnet-latest", messages=messages, max_tokens=1000, system=system, ) as stream: for text in stream.text_stream: print(text, end="", flush=True) message = stream.get_final_message() ``` rr^c&i|]\}}|dk ||S)rr<r=s r%r6z"wrap_anthropic..+s*(((A!z//1///r2betar:rr)r(rBrCr>rr:rrrUrL completionsrrr`r)rrr[r\rrFtracing_extra_rests r%wrap_anthropicrcs~"'RMM%%j117R88H%-\\2H"%M%M"((&,,..(((2)1:&)& FO1& FO !-!& !!F   FK , ,   FK(( 3 3  '3 K '   *  ' '  #   FK , ,   FK(' 2 2  &2 K &   *  & &  " Mr2)rr)r'r(rr()rFr(rGr()rrc)rir(rr)rrrr()rrrr()rrrr()rr) rr rr_rr rFr(rrrr ) rr rr_rFr(rrrr ) rrrr]r[r_r\r_rr): __future__rrloggingrcollections.abcrrrtypingrrr r r r typing_extensionsr r langsmithr ls_clientrlangsmith._internal._orjsonrrlangsmith.schemasrrhttpxrSrranthropic.lib.streamingrranthropic.typesrrrr getLoggerr'r@ lru_cacher&rErbrhr~rrrrrrUrrcr<r2r%rrs""""""<<<<<<<<<<.-------))))))!!!!!!777777>>>>>>>>HLLL33333333IIIIIIIIGGGGGGGGGG GCu[*:C?@AAA  8 $ $ 9999&####L ####L((((V----&     ####"*H*H*H*HZ|,|,|,|,~'''''9E''''-1$' {{{{{{{{r2