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(Refactor) Code Quality improvement - use Common base handler for Cohere (#7117)
* fix use new format for Cohere config * fix base llm http handler * Litellm code qa common config (#7116) * feat(base_llm): initial commit for common base config class Addresses code qa critique https://github.com/andrewyng/aisuite/issues/113#issuecomment-2512369132 * feat(base_llm/): add transform request/response abstract methods to base config class --------- Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com> * use base transform helpers * use base_llm_http_handler for cohere * working cohere using base llm handler * add async cohere chat completion support on base handler * fix completion code * working sync cohere stream * add async support cohere_chat * fix types get_model_response_iterator * async / sync tests cohere * feat cohere using base llm class * fix linting errors * fix _abc error * add cohere params to transformation * remove old cohere file * fix type error * fix merge conflicts * fix cohere merge conflicts * fix linting error * fix litellm.llms.custom_httpx.http_handler.HTTPHandler.post * fix passing cohere specific params --------- Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
This commit is contained in:
Ishaan Jaff
GitHub
parent
5bbf906c83
commit
ff7c95694d
14 changed files with 933 additions and 720 deletions
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@ -695,79 +695,6 @@ async def test_anthropic_no_content_error():
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pytest.fail(f"An unexpected error occurred - {str(e)}")
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def test_completion_cohere_command_r_plus_function_call():
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litellm.set_verbose = True
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
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},
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"required": ["location"],
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},
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},
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}
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]
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messages = [
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{
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"role": "user",
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"content": "What's the weather like in Boston today in Fahrenheit?",
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}
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]
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try:
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# test without max tokens
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response = completion(
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model="command-r-plus",
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messages=messages,
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tools=tools,
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tool_choice="auto",
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)
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# Add any assertions, here to check response args
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print(response)
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assert isinstance(response.choices[0].message.tool_calls[0].function.name, str)
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assert isinstance(
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response.choices[0].message.tool_calls[0].function.arguments, str
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)
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messages.append(
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response.choices[0].message.model_dump()
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) # Add assistant tool invokes
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tool_result = (
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'{"location": "Boston", "temperature": "72", "unit": "fahrenheit"}'
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)
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# Add user submitted tool results in the OpenAI format
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messages.append(
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{
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"tool_call_id": response.choices[0].message.tool_calls[0].id,
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"role": "tool",
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"name": response.choices[0].message.tool_calls[0].function.name,
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"content": tool_result,
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}
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)
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# In the second response, Cohere should deduce answer from tool results
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second_response = completion(
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model="command-r-plus",
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messages=messages,
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tools=tools,
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tool_choice="auto",
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force_single_step=True,
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)
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print(second_response)
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except litellm.Timeout:
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pass
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_parse_xml_params():
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from litellm.llms.prompt_templates.factory import parse_xml_params
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@ -2120,27 +2047,6 @@ def test_ollama_image():
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# hf_test_error_logs()
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# def test_completion_cohere(): # commenting out,for now as the cohere endpoint is being flaky
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# try:
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# litellm.CohereConfig(max_tokens=10, stop_sequences=["a"])
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# response = completion(
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# model="command-nightly", messages=messages, logger_fn=logger_fn
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# )
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# # Add any assertions here to check the response
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# print(response)
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# response_str = response["choices"][0]["message"]["content"]
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# response_str_2 = response.choices[0].message.content
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# if type(response_str) != str:
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# pytest.fail(f"Error occurred: {e}")
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# if type(response_str_2) != str:
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# pytest.fail(f"Error occurred: {e}")
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_cohere()
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def test_completion_openai():
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try:
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litellm.set_verbose = True
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@ -3550,9 +3456,6 @@ def test_completion_bedrock_titan_null_response():
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# test_completion_bedrock_claude()
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# test_completion_bedrock_cohere()
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# def test_completion_bedrock_claude_stream():
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# print("calling claude")
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# litellm.set_verbose = False
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@ -3722,78 +3625,6 @@ def test_completion_anyscale_api():
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# test_completion_anyscale_api()
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# @pytest.mark.skip(reason="flaky test, times out frequently")
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@pytest.mark.flaky(retries=6, delay=1)
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def test_completion_cohere():
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try:
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# litellm.set_verbose=True
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messages = [
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{"role": "system", "content": "You're a good bot"},
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{"role": "assistant", "content": [{"text": "2", "type": "text"}]},
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{"role": "assistant", "content": [{"text": "3", "type": "text"}]},
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{
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"role": "user",
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"content": "Hey",
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},
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]
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response = completion(
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model="command-r",
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messages=messages,
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extra_headers={"Helicone-Property-Locale": "ko"},
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)
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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# FYI - cohere_chat looks quite unstable, even when testing locally
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def test_chat_completion_cohere():
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try:
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litellm.set_verbose = True
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messages = [
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{"role": "system", "content": "You're a good bot"},
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{
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"role": "user",
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"content": "Hey",
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},
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]
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response = completion(
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model="cohere_chat/command-r",
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messages=messages,
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max_tokens=10,
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)
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print(response)
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_chat_completion_cohere_stream():
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try:
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litellm.set_verbose = False
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messages = [
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{"role": "system", "content": "You're a good bot"},
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{
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"role": "user",
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"content": "Hey",
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},
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]
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response = completion(
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model="cohere_chat/command-r",
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messages=messages,
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max_tokens=10,
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stream=True,
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)
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print(response)
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for chunk in response:
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print(chunk)
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except litellm.APIConnectionError as e:
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pass
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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def test_azure_cloudflare_api():
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litellm.set_verbose = True
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try:
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