forked from phoenix/litellm-mirror
docs(input.md): add clarifai supported input params to docs
This commit is contained in:
Krrish Dholakia
parent
1ec289bfbe
commit
9698fc77fd
3 changed files with 93 additions and 96 deletions
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@ -60,6 +60,7 @@ Use `litellm.get_supported_openai_params()` for an updated list of params for ea
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|Petals| ✅ | ✅ | | ✅ | | | | | | |
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|Ollama| ✅ | ✅ | ✅ | ✅ | ✅ | | | ✅ | | | | | ✅ | | |
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|Databricks| ✅ | ✅ | ✅ | ✅ | ✅ | | | | | | | | | | |
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|ClarifAI| ✅ | ✅ | | | | | | | | | | | | | |
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:::note
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@ -55,7 +55,7 @@ response = completion(
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```
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## Clarifai models
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liteLLM supports non-streaming requests to all models on [Clarifai community](https://clarifai.com/explore/models?filterData=%5B%7B%22field%22%3A%22use_cases%22%2C%22value%22%3A%5B%22llm%22%5D%7D%5D&page=1&perPage=24)
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liteLLM supports all models on [Clarifai community](https://clarifai.com/explore/models?filterData=%5B%7B%22field%22%3A%22use_cases%22%2C%22value%22%3A%5B%22llm%22%5D%7D%5D&page=1&perPage=24)
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Example Usage - Note: liteLLM supports all models deployed on Clarifai
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@ -14,28 +14,25 @@ class ClarifaiError(Exception):
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def __init__(self, status_code, message, url):
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self.status_code = status_code
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self.message = message
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self.request = httpx.Request(
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method="POST", url=url
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)
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self.request = httpx.Request(method="POST", url=url)
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self.response = httpx.Response(status_code=status_code, request=self.request)
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super().__init__(
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self.message
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)
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super().__init__(self.message)
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class ClarifaiConfig:
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"""
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Reference: https://clarifai.com/meta/Llama-2/models/llama2-70b-chat
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TODO fill in the details
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"""
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max_tokens: Optional[int] = None
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temperature: Optional[int] = None
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top_k: Optional[int] = None
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def __init__(
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self,
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max_tokens: Optional[int] = None,
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temperature: Optional[int] = None,
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top_k: Optional[int] = None,
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self,
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max_tokens: Optional[int] = None,
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temperature: Optional[int] = None,
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top_k: Optional[int] = None,
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) -> None:
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locals_ = locals()
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for key, value in locals_.items():
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@ -60,6 +57,7 @@ class ClarifaiConfig:
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and v is not None
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}
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def validate_environment(api_key):
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headers = {
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"accept": "application/json",
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@ -69,42 +67,37 @@ def validate_environment(api_key):
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headers["Authorization"] = f"Bearer {api_key}"
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return headers
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def completions_to_model(payload):
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# if payload["n"] != 1:
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# raise HTTPException(
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# status_code=422,
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# detail="Only one generation is supported. Please set candidate_count to 1.",
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# )
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params = {}
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if temperature := payload.get("temperature"):
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params["temperature"] = temperature
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if max_tokens := payload.get("max_tokens"):
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params["max_tokens"] = max_tokens
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return {
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"inputs": [{"data": {"text": {"raw": payload["prompt"]}}}],
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"model": {"output_info": {"params": params}},
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}
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def completions_to_model(payload):
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# if payload["n"] != 1:
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# raise HTTPException(
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# status_code=422,
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# detail="Only one generation is supported. Please set candidate_count to 1.",
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# )
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params = {}
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if temperature := payload.get("temperature"):
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params["temperature"] = temperature
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if max_tokens := payload.get("max_tokens"):
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params["max_tokens"] = max_tokens
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return {
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"inputs": [{"data": {"text": {"raw": payload["prompt"]}}}],
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"model": {"output_info": {"params": params}},
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}
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def process_response(
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model,
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prompt,
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response,
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model_response,
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api_key,
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data,
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encoding,
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logging_obj
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):
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model, prompt, response, model_response, api_key, data, encoding, logging_obj
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):
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logging_obj.post_call(
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input=prompt,
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api_key=api_key,
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original_response=response.text,
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additional_args={"complete_input_dict": data},
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)
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## RESPONSE OBJECT
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input=prompt,
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api_key=api_key,
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original_response=response.text,
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additional_args={"complete_input_dict": data},
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)
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## RESPONSE OBJECT
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try:
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completion_response = response.json()
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completion_response = response.json()
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except Exception:
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raise ClarifaiError(
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message=response.text, status_code=response.status_code, url=model
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@ -119,7 +112,7 @@ def process_response(
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message_obj = Message(content=None)
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choice_obj = Choices(
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finish_reason="stop",
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index=idx + 1, #check
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index=idx + 1, # check
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message=message_obj,
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)
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choices_list.append(choice_obj)
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@ -143,53 +136,56 @@ def process_response(
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)
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return model_response
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def convert_model_to_url(model: str, api_base: str):
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user_id, app_id, model_id = model.split(".")
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return f"{api_base}/users/{user_id}/apps/{app_id}/models/{model_id}/outputs"
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def get_prompt_model_name(url: str):
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clarifai_model_name = url.split("/")[-2]
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if "claude" in clarifai_model_name:
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return "anthropic", clarifai_model_name.replace("_", ".")
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if ("llama" in clarifai_model_name)or ("mistral" in clarifai_model_name):
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if ("llama" in clarifai_model_name) or ("mistral" in clarifai_model_name):
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return "", "meta-llama/llama-2-chat"
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else:
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return "", clarifai_model_name
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async def async_completion(
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model: str,
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prompt: str,
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api_base: str,
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custom_prompt_dict: dict,
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model_response: ModelResponse,
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print_verbose: Callable,
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encoding,
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api_key,
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logging_obj,
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data=None,
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optional_params=None,
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litellm_params=None,
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logger_fn=None,
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headers={}):
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async_handler = AsyncHTTPHandler(
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timeout=httpx.Timeout(timeout=600.0, connect=5.0)
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)
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model: str,
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prompt: str,
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api_base: str,
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custom_prompt_dict: dict,
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model_response: ModelResponse,
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print_verbose: Callable,
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encoding,
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api_key,
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logging_obj,
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data=None,
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optional_params=None,
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litellm_params=None,
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logger_fn=None,
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headers={},
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):
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async_handler = AsyncHTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0))
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response = await async_handler.post(
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api_base, headers=headers, data=json.dumps(data)
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)
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return process_response(
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model=model,
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prompt=prompt,
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response=response,
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model_response=model_response,
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api_key=api_key,
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data=data,
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encoding=encoding,
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logging_obj=logging_obj,
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api_base, headers=headers, data=json.dumps(data)
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)
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return process_response(
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model=model,
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prompt=prompt,
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response=response,
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model_response=model_response,
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api_key=api_key,
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data=data,
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encoding=encoding,
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logging_obj=logging_obj,
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)
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def completion(
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model: str,
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messages: list,
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@ -207,14 +203,12 @@ def completion(
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):
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headers = validate_environment(api_key)
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model = convert_model_to_url(model, api_base)
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prompt = " ".join(message["content"] for message in messages) # TODO
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prompt = " ".join(message["content"] for message in messages) # TODO
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## Load Config
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config = litellm.ClarifaiConfig.get_config()
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for k, v in config.items():
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if (
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k not in optional_params
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):
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if k not in optional_params:
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optional_params[k] = v
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custom_llm_provider, orig_model_name = get_prompt_model_name(model)
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@ -223,14 +217,14 @@ def completion(
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model=orig_model_name,
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messages=messages,
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api_key=api_key,
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custom_llm_provider="clarifai"
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custom_llm_provider="clarifai",
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)
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else:
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prompt = prompt_factory(
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model=orig_model_name,
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messages=messages,
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api_key=api_key,
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custom_llm_provider=custom_llm_provider
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custom_llm_provider=custom_llm_provider,
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)
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# print(prompt); exit(0)
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@ -240,7 +234,6 @@ def completion(
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}
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data = completions_to_model(data)
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## LOGGING
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logging_obj.pre_call(
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input=prompt,
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@ -251,7 +244,7 @@ def completion(
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"api_base": api_base,
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},
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)
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if acompletion==True:
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if acompletion == True:
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return async_completion(
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model=model,
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prompt=prompt,
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@ -271,15 +264,17 @@ def completion(
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else:
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## COMPLETION CALL
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response = requests.post(
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model,
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headers=headers,
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data=json.dumps(data),
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)
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model,
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headers=headers,
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data=json.dumps(data),
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)
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# print(response.content); exit()
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if response.status_code != 200:
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raise ClarifaiError(status_code=response.status_code, message=response.text, url=model)
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raise ClarifaiError(
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status_code=response.status_code, message=response.text, url=model
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)
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if "stream" in optional_params and optional_params["stream"] == True:
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completion_stream = response.iter_lines()
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stream_response = CustomStreamWrapper(
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@ -287,11 +282,11 @@ def completion(
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model=model,
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custom_llm_provider="clarifai",
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logging_obj=logging_obj,
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)
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)
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return stream_response
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else:
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return process_response(
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return process_response(
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model=model,
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prompt=prompt,
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response=response,
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@ -299,8 +294,9 @@ def completion(
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api_key=api_key,
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data=data,
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encoding=encoding,
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logging_obj=logging_obj)
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logging_obj=logging_obj,
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)
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class ModelResponseIterator:
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def __init__(self, model_response):
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@ -325,4 +321,4 @@ class ModelResponseIterator:
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if self.is_done:
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raise StopAsyncIteration
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self.is_done = True
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return self.model_response
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return self.model_response
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