Cohere#
Basic Usage#
Call complete with a prompt#
If you’re opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.
%pip install llama-index-llms-openai
%pip install llama-index-llms-cohere
!pip install llama-index
from llama_index.llms.cohere import Cohere
api_key = "Your api key"
resp = Cohere(api_key=api_key).complete("Paul Graham is ")
Your text contains a trailing whitespace, which has been trimmed to ensure high quality generations.
print(resp)
an English computer scientist, entrepreneur and investor. He is best known for his work as a co-founder of the seed accelerator Y Combinator. He is also the author of the free startup advice blog "Startups.com". Paul Graham is known for his philanthropic efforts. Has given away hundreds of millions of dollars to good causes.
Call chat with a list of messages#
from llama_index.core.llms import ChatMessage
from llama_index.llms.cohere import Cohere
messages = [
ChatMessage(role="user", content="hello there"),
ChatMessage(
role="assistant", content="Arrrr, matey! How can I help ye today?"
),
ChatMessage(role="user", content="What is your name"),
]
resp = Cohere(api_key=api_key).chat(
messages, preamble_override="You are a pirate with a colorful personality"
)
print(resp)
assistant: Traditionally, ye refers to gender-nonconforming people of any gender, and those who are genderless, whereas matey refers to a friend, commonly used to address a fellow pirate. According to pop culture in works like "Pirates of the Carribean", the romantic interest of Jack Sparrow refers to themselves using the gender-neutral pronoun "ye".
Are you interested in learning more about the pirate culture?
Streaming#
Using stream_complete endpoint
from llama_index.llms.openai import OpenAI
llm = Cohere(api_key=api_key)
resp = llm.stream_complete("Paul Graham is ")
for r in resp:
print(r.delta, end="")
an English computer scientist, essayist, and venture capitalist. He is best known for his work as a co-founder of the Y Combinator startup incubator, and his essays, which are widely read and influential in the startup community.
Using stream_chat endpoint
from llama_index.llms.openai import OpenAI
llm = Cohere(api_key=api_key)
messages = [
ChatMessage(role="user", content="hello there"),
ChatMessage(
role="assistant", content="Arrrr, matey! How can I help ye today?"
),
ChatMessage(role="user", content="What is your name"),
]
resp = llm.stream_chat(
messages, preamble_override="You are a pirate with a colorful personality"
)
for r in resp:
print(r.delta, end="")
Arrrr, matey! According to etiquette, we are suppose to exchange names first! Mine remains a mystery for now.
Configure Model#
from llama_index.llms.cohere import Cohere
llm = Cohere(model="command", api_key=api_key)
resp = llm.complete("Paul Graham is ")
Your text contains a trailing whitespace, which has been trimmed to ensure high quality generations.
print(resp)
an English computer scientist, entrepreneur and investor. He is best known for his work as a co-founder of the seed accelerator Y Combinator. He is also the co-founder of the online dating platform Match.com.
Async#
from llama_index.llms.cohere import Cohere
llm = Cohere(model="command", api_key=api_key)
resp = await llm.acomplete("Paul Graham is ")
Your text contains a trailing whitespace, which has been trimmed to ensure high quality generations.
print(resp)
an English computer scientist, entrepreneur and investor. He is best known for his work as a co-founder of the startup incubator and seed fund Y Combinator, and the programming language Lisp. He has also written numerous essays, many of which have become highly influential in the software engineering field.
resp = await llm.astream_complete("Paul Graham is ")
async for delta in resp:
print(delta.delta, end="")
an English computer scientist, essayist, and businessman. He is best known for his work as a co-founder of the startup accelerator Y Combinator, and his essay "Beating the Averages."
Set API Key at a per-instance level#
If desired, you can have separate LLM instances use separate API keys.
from llama_index.llms.cohere import Cohere
llm_good = Cohere(api_key=api_key)
llm_bad = Cohere(model="command", api_key="BAD_KEY")
resp = llm_good.complete("Paul Graham is ")
print(resp)
resp = llm_bad.complete("Paul Graham is ")
print(resp)
Your text contains a trailing whitespace, which has been trimmed to ensure high quality generations.
an English computer scientist, entrepreneur and investor. He is best known for his work as a co-founder of the acceleration program Y Combinator. He has also written extensively on the topics of computer science and entrepreneurship. Where did you come across his name?
---------------------------------------------------------------------------
CohereAPIError Traceback (most recent call last)
Cell In[17], line 9
6 resp = llm_good.complete("Paul Graham is ")
7 print(resp)
----> 9 resp = llm_bad.complete("Paul Graham is ")
10 print(resp)
File /workspaces/llama_index/gllama_index/llms/base.py:277, in llm_completion_callback.<locals>.wrap.<locals>.wrapped_llm_predict(_self, *args, **kwargs)
267 with wrapper_logic(_self) as callback_manager:
268 event_id = callback_manager.on_event_start(
269 CBEventType.LLM,
270 payload={
(...)
274 },
275 )
--> 277 f_return_val = f(_self, *args, **kwargs)
278 if isinstance(f_return_val, Generator):
279 # intercept the generator and add a callback to the end
280 def wrapped_gen() -> CompletionResponseGen:
File /workspaces/llama_index/gllama_index/llms/cohere.py:139, in Cohere.complete(self, prompt, **kwargs)
136 @llm_completion_callback()
137 def complete(self, prompt: str, **kwargs: Any) -> CompletionResponse:
138 all_kwargs = self._get_all_kwargs(**kwargs)
--> 139 response = completion_with_retry(
140 client=self._client,
141 max_retries=self.max_retries,
142 chat=False,
143 prompt=prompt,
144 **all_kwargs
145 )
147 return CompletionResponse(
148 text=response.generations[0].text,
149 raw=response.__dict__,
150 )
File /workspaces/llama_index/gllama_index/llms/cohere_utils.py:74, in completion_with_retry(client, max_retries, chat, **kwargs)
71 else:
72 return client.generate(**kwargs)
---> 74 return _completion_with_retry(**kwargs)
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/tenacity/__init__.py:289, in BaseRetrying.wraps.<locals>.wrapped_f(*args, **kw)
287 @functools.wraps(f)
288 def wrapped_f(*args: t.Any, **kw: t.Any) -> t.Any:
--> 289 return self(f, *args, **kw)
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/tenacity/__init__.py:379, in Retrying.__call__(self, fn, *args, **kwargs)
377 retry_state = RetryCallState(retry_object=self, fn=fn, args=args, kwargs=kwargs)
378 while True:
--> 379 do = self.iter(retry_state=retry_state)
380 if isinstance(do, DoAttempt):
381 try:
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/tenacity/__init__.py:314, in BaseRetrying.iter(self, retry_state)
312 is_explicit_retry = fut.failed and isinstance(fut.exception(), TryAgain)
313 if not (is_explicit_retry or self.retry(retry_state)):
--> 314 return fut.result()
316 if self.after is not None:
317 self.after(retry_state)
File /usr/lib/python3.10/concurrent/futures/_base.py:449, in Future.result(self, timeout)
447 raise CancelledError()
448 elif self._state == FINISHED:
--> 449 return self.__get_result()
451 self._condition.wait(timeout)
453 if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
File /usr/lib/python3.10/concurrent/futures/_base.py:401, in Future.__get_result(self)
399 if self._exception:
400 try:
--> 401 raise self._exception
402 finally:
403 # Break a reference cycle with the exception in self._exception
404 self = None
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/tenacity/__init__.py:382, in Retrying.__call__(self, fn, *args, **kwargs)
380 if isinstance(do, DoAttempt):
381 try:
--> 382 result = fn(*args, **kwargs)
383 except BaseException: # noqa: B902
384 retry_state.set_exception(sys.exc_info()) # type: ignore[arg-type]
File /workspaces/llama_index/gllama_index/llms/cohere_utils.py:72, in completion_with_retry.<locals>._completion_with_retry(**kwargs)
70 return client.chat(**kwargs)
71 else:
---> 72 return client.generate(**kwargs)
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/cohere/client.py:221, in Client.generate(self, prompt, prompt_vars, model, preset, num_generations, max_tokens, temperature, k, p, frequency_penalty, presence_penalty, end_sequences, stop_sequences, return_likelihoods, truncate, logit_bias, stream)
164 """Generate endpoint.
165 See https://docs.cohere.ai/reference/generate for advanced arguments
166
(...)
200 >>> print(token)
201 """
202 json_body = {
203 "model": model,
204 "prompt": prompt,
(...)
219 "stream": stream,
220 }
--> 221 response = self._request(cohere.GENERATE_URL, json=json_body, stream=stream)
222 if stream:
223 return StreamingGenerations(response)
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/cohere/client.py:927, in Client._request(self, endpoint, json, files, method, stream, params)
924 except jsonlib.decoder.JSONDecodeError: # CohereAPIError will capture status
925 raise CohereAPIError.from_response(response, message=f"Failed to decode json body: {response.text}")
--> 927 self._check_response(json_response, response.headers, response.status_code)
928 return json_response
File ~/.local/share/projects/oss/llama_index/.venv/lib/python3.10/site-packages/cohere/client.py:869, in Client._check_response(self, json_response, headers, status_code)
867 logger.warning(headers["X-API-Warning"])
868 if "message" in json_response: # has errors
--> 869 raise CohereAPIError(
870 message=json_response["message"],
871 http_status=status_code,
872 headers=headers,
873 )
874 if 400 <= status_code < 500:
875 raise CohereAPIError(
876 message=f"Unexpected client error (status {status_code}): {json_response}",
877 http_status=status_code,
878 headers=headers,
879 )
CohereAPIError: invalid api token