Added seed and format param to ClaudeBedrockClient.complete

Those param will be ignored but that's not a big issue.

Missing them would cause certain feature to totally fail using this model.

giskard/llm/client/bedrock.py

@@ -1,4 +1,5 @@
 from typing import Optional, Sequence
+
 import json
 
 from ..config import LLMConfigurationError
@@ -15,27 +16,28 @@
 
 
 class ClaudeBedrockClient(LLMClient):
- def __init__(self,
- bedrock_runtime_client,
- model: str = "anthropic.claude-3-sonnet-20240229-v1:0",
- anthropic_version: str = "bedrock-2023-05-31"):
+ def __init__(
+ self,
+ bedrock_runtime_client,
+ model: str = "anthropic.claude-3-sonnet-20240229-v1:0",
+ anthropic_version: str = "bedrock-2023-05-31",
+ ):
  self._client = bedrock_runtime_client
  self.model = model
  self.anthropic_version = anthropic_version
 
  def complete(
- self,
- messages: Sequence[ChatMessage],
- temperature: float = 1,
- max_tokens: Optional[int] = 1000,
- caller_id: Optional[str] = None,
+ self,
+ messages: Sequence[ChatMessage],
+ temperature: float = 1,
+ max_tokens: Optional[int] = 1000,
+ caller_id: Optional[str] = None,
+ seed: Optional[int] = None,
+ format=None,
  ) -> ChatMessage:
-
  # only supporting claude 3 to start
- if 'claude-3' not in self.model:
- raise LLMConfigurationError(
- f"Only claude-3 models are supported as of now, got {self.model}"
- )
+ if "claude-3" not in self.model:
+ raise LLMConfigurationError(f"Only claude-3 models are supported as of now, got {self.model}")
 
  # extract system prompt from messages
  system_prompt = ""
@@ -48,57 +50,37 @@ def complete(
  input_msg_prompt = []
  for msg in messages:
  if msg.role.lower() == "assistant":
- input_msg_prompt.append(
- {
- "role": "assistant",
- "content": [
- {
- "type": "text",
- "text": msg.content
- }
- ]
- }
- )
+ input_msg_prompt.append({"role": "assistant", "content": [{"type": "text", "text": msg.content}]})
  else:
- input_msg_prompt.append(
- {
- "role": "user",
- "content": [
- {
- "type": "text",
- "text": msg.content
- }
- ]
- }
- )
+ input_msg_prompt.append({"role": "user", "content": [{"type": "text", "text": msg.content}]})
 
  # create the json body to send to the API
- body = json.dumps({
- "anthropic_version": "bedrock-2023-05-31",
- "max_tokens": max_tokens,
- "temperature": temperature,
- "system": system_prompt,
- "messages": input_msg_prompt
- })
+ body = json.dumps(
+ {
+ "anthropic_version": "bedrock-2023-05-31",
+ "max_tokens": max_tokens,
+ "temperature": temperature,
+ "system": system_prompt,
+ "messages": input_msg_prompt,
+ }
+ )
 
  # invoke the model and get the response
  try:
- accept = 'application/json'
- contentType = 'application/json'
- response = self._client.invoke_model(
- body=body, modelId=self.model, accept=accept, contentType=contentType
- )
- completion = json.loads(response.get('body').read())
+ accept = "application/json"
+ contentType = "application/json"
+ response = self._client.invoke_model(body=body, modelId=self.model, accept=accept, contentType=contentType)
+ completion = json.loads(response.get("body").read())
  except RuntimeError as err:
  raise LLMConfigurationError("Could not get response from Bedrock API") from err
 
  self.logger.log_call(
- prompt_tokens=completion['usage']['input_tokens'],
- sampled_tokens=completion['usage']['input_tokens'],
+ prompt_tokens=completion["usage"]["input_tokens"],
+ sampled_tokens=completion["usage"]["input_tokens"],
  model=self.model,
  client_class=self.__class__.__name__,
  caller_id=caller_id,
  )
 
- msg = completion['content'][0]['text']
+ msg = completion["content"][0]["text"]
  return ChatMessage(role="assistant", content=msg)