!python --version

Python 3.12.4

from constants import OPENAI_API_KEY

!pip show langchain-openai | grep "Version:"

Version: 0.2.9

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")

#!pip install langchain_anthropic

from langchain_anthropic import ChatAnthropic

from langchain_community.utils.math import cosine_similarity
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import RunnableLambda, RunnablePassthrough
from langchain_openai import OpenAIEmbeddings

physics_template = """You are a very smart physics professor. \
You are great at answering questions about physics in a concise and easy to understand manner. \
When you don't know the answer to a question you admit that you don't know.

Here is a question:
{query}"""

math_template = """You are a very good mathematician. You are great at answering math questions. \
You are so good because you are able to break down hard problems into their component parts, \
answer the component parts, and then put them together to answer the broader question.

Here is a question:
{query}"""

embeddings = OpenAIEmbeddings()
prompt_templates = [physics_template, math_template]
prompt_embeddings = embeddings.embed_documents(prompt_templates)


def prompt_router(input):
    query_embedding = embeddings.embed_query(input["query"])
    similarity = cosine_similarity([query_embedding], prompt_embeddings)[0]
    most_similar = prompt_templates[similarity.argmax()]
    print("Using MATH" if most_similar == math_template else "Using PHYSICS")
    return PromptTemplate.from_template(most_similar)


chain = (
    {"query": RunnablePassthrough()}
    | RunnableLambda(prompt_router)
    | ChatAnthropic(model="claude-3-haiku-20240307")
    | StrOutputParser()
)

chain.invoke("What's a black hole")

Using PHYSICS



---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

Cell In[33], line 1
----> 1 chain.invoke("What's a black hole")


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/runnables/base.py:3024, in RunnableSequence.invoke(self, input, config, **kwargs)
   3022             input = context.run(step.invoke, input, config, **kwargs)
   3023         else:
-> 3024             input = context.run(step.invoke, input, config)
   3025 # finish the root run
   3026 except BaseException as e:


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:286, in BaseChatModel.invoke(self, input, config, stop, **kwargs)
    275 def invoke(
    276     self,
    277     input: LanguageModelInput,
   (...)
    281     **kwargs: Any,
    282 ) -> BaseMessage:
    283     config = ensure_config(config)
    284     return cast(
    285         ChatGeneration,
--> 286         self.generate_prompt(
    287             [self._convert_input(input)],
    288             stop=stop,
    289             callbacks=config.get("callbacks"),
    290             tags=config.get("tags"),
    291             metadata=config.get("metadata"),
    292             run_name=config.get("run_name"),
    293             run_id=config.pop("run_id", None),
    294             **kwargs,
    295         ).generations[0][0],
    296     ).message


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:786, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    778 def generate_prompt(
    779     self,
    780     prompts: list[PromptValue],
   (...)
    783     **kwargs: Any,
    784 ) -> LLMResult:
    785     prompt_messages = [p.to_messages() for p in prompts]
--> 786     return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:643, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)
    641         if run_managers:
    642             run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
--> 643         raise e
    644 flattened_outputs = [
    645     LLMResult(generations=[res.generations], llm_output=res.llm_output)  # type: ignore[list-item]
    646     for res in results
    647 ]
    648 llm_output = self._combine_llm_outputs([res.llm_output for res in results])


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:633, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)
    630 for i, m in enumerate(messages):
    631     try:
    632         results.append(
--> 633             self._generate_with_cache(
    634                 m,
    635                 stop=stop,
    636                 run_manager=run_managers[i] if run_managers else None,
    637                 **kwargs,
    638             )
    639         )
    640     except BaseException as e:
    641         if run_managers:


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_core/language_models/chat_models.py:851, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs)
    849 else:
    850     if inspect.signature(self._generate).parameters.get("run_manager"):
--> 851         result = self._generate(
    852             messages, stop=stop, run_manager=run_manager, **kwargs
    853         )
    854     else:
    855         result = self._generate(messages, stop=stop, **kwargs)


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/langchain_anthropic/chat_models.py:796, in ChatAnthropic._generate(self, messages, stop, run_manager, **kwargs)
    794     return generate_from_stream(stream_iter)
    795 payload = self._get_request_payload(messages, stop=stop, **kwargs)
--> 796 data = self._client.messages.create(**payload)
    797 return self._format_output(data, **kwargs)


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_utils/_utils.py:275, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs)
    273             msg = f"Missing required argument: {quote(missing[0])}"
    274     raise TypeError(msg)
--> 275 return func(*args, **kwargs)


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/resources/messages.py:888, in Messages.create(self, max_tokens, messages, model, metadata, stop_sequences, stream, system, temperature, tool_choice, tools, top_k, top_p, extra_headers, extra_query, extra_body, timeout)
    881 if model in DEPRECATED_MODELS:
    882     warnings.warn(
    883         f"The model '{model}' is deprecated and will reach end-of-life on {DEPRECATED_MODELS[model]}.\nPlease migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.",
    884         DeprecationWarning,
    885         stacklevel=3,
    886     )
--> 888 return self._post(
    889     "/v1/messages",
    890     body=maybe_transform(
    891         {
    892             "max_tokens": max_tokens,
    893             "messages": messages,
    894             "model": model,
    895             "metadata": metadata,
    896             "stop_sequences": stop_sequences,
    897             "stream": stream,
    898             "system": system,
    899             "temperature": temperature,
    900             "tool_choice": tool_choice,
    901             "tools": tools,
    902             "top_k": top_k,
    903             "top_p": top_p,
    904         },
    905         message_create_params.MessageCreateParams,
    906     ),
    907     options=make_request_options(
    908         extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
    909     ),
    910     cast_to=Message,
    911     stream=stream or False,
    912     stream_cls=Stream[RawMessageStreamEvent],
    913 )


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_base_client.py:1277, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
   1263 def post(
   1264     self,
   1265     path: str,
   (...)
   1272     stream_cls: type[_StreamT] | None = None,
   1273 ) -> ResponseT | _StreamT:
   1274     opts = FinalRequestOptions.construct(
   1275         method="post", url=path, json_data=body, files=to_httpx_files(files), **options
   1276     )
-> 1277     return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_base_client.py:954, in SyncAPIClient.request(self, cast_to, options, remaining_retries, stream, stream_cls)
    951 else:
    952     retries_taken = 0
--> 954 return self._request(
    955     cast_to=cast_to,
    956     options=options,
    957     stream=stream,
    958     stream_cls=stream_cls,
    959     retries_taken=retries_taken,
    960 )


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_base_client.py:980, in SyncAPIClient._request(self, cast_to, options, retries_taken, stream, stream_cls)
    977 options = self._prepare_options(options)
    979 remaining_retries = options.get_max_retries(self.max_retries) - retries_taken
--> 980 request = self._build_request(options, retries_taken=retries_taken)
    981 self._prepare_request(request)
    983 kwargs: HttpxSendArgs = {}


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_base_client.py:465, in BaseClient._build_request(self, options, retries_taken)
    462     else:
    463         raise RuntimeError(f"Unexpected JSON data type, {type(json_data)}, cannot merge with `extra_body`")
--> 465 headers = self._build_headers(options, retries_taken=retries_taken)
    466 params = _merge_mappings(self.default_query, options.params)
    467 content_type = headers.get("Content-Type")


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_base_client.py:413, in BaseClient._build_headers(self, options, retries_taken)
    411 custom_headers = options.headers or {}
    412 headers_dict = _merge_mappings(self.default_headers, custom_headers)
--> 413 self._validate_headers(headers_dict, custom_headers)
    415 # headers are case-insensitive while dictionaries are not.
    416 headers = httpx.Headers(headers_dict)


File ~/miniconda3/envs/ml312/lib/python3.12/site-packages/anthropic/_client.py:189, in Anthropic._validate_headers(self, headers, custom_headers)
    186 if isinstance(custom_headers.get("Authorization"), Omit):
    187     return
--> 189 raise TypeError(
    190     '"Could not resolve authentication method. Expected either api_key or auth_token to be set. Or for one of the `X-Api-Key` or `Authorization` headers to be explicitly omitted"'
    191 )


TypeError: "Could not resolve authentication method. Expected either api_key or auth_token to be set. Or for one of the `X-Api-Key` or `Authorization` headers to be explicitly omitted"