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community: fix compatibility issue in kinetica chat model integration for Pydantic 2 (#28252)

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Fixed a compatibility issue in the `load_messages_from_context()`
function for the Kinetica chat model integration. The issue was caused
by stricter validation introduced in Pydantic 2.
This commit is contained in:
Priyanshi Garg 2024-11-21 20:03:00 +05:30 committed by GitHub
parent 96c67230aa
commit f5f53d1101
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1 changed files with 4 additions and 1 deletions
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5
libs/community/langchain_community/chat_models/kinetica.py
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@ -78,7 +78,7 @@ class _KdtSuggestContext(BaseModel):
class _KdtSuggestPayload(BaseModel):
"""pydantic API request type"""
question: Optional[str]
question: Optional[str] = None
context: List[_KdtSuggestContext]
def get_system_str(self) -> str:
@ -410,17 +410,20 @@ class ChatKinetica(BaseChatModel):
# query kinetica for the prompt
sql = f"GENERATE PROMPT WITH OPTIONS (CONTEXT_NAMES = '{context_name}')"
result = self._execute_sql(sql)
prompt = result["Prompt"]
prompt_json = json.loads(prompt)
# convert the prompt to messages
# request = SuggestRequest.model_validate(prompt_json) # pydantic v2
request = _KdtoSuggestRequest.model_validate(prompt_json)
payload = request.payload
dict_messages = []
dict_messages.append(dict(role="system", content=payload.get_system_str()))
dict_messages.extend(payload.get_messages())
messages = [self._convert_message_from_dict(m) for m in dict_messages]
return messages