(20241205) LLM endpoint active now.
This commit is contained in:
+123
-52
@@ -10,7 +10,7 @@
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OBJECTIVE:
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To provide a structure to receive auth details of various SMS providers.
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To provide a structure to normalize input to and output from a standardized LLM wrapper.
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REFERENCES:
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@@ -36,8 +36,8 @@ sys.path.append(".")
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sys.path.append("..")
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# For making data behaviour_models:
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from pydantic import BaseModel, Field, field_validator, PastDatetime
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from typing import Optional, Literal, Union
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from pydantic import BaseModel, Field, field_validator, PastDatetime, AwareDatetime
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from typing import Optional, Literal, Union, List
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# My utils:
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from utils_v2.string import regex
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@@ -75,30 +75,15 @@ REGEX_SESSION_TOKEN = r"^[a-f0-9]{8}-[a-f0-9]{4}-[1-5][a-f0-9]{3}-[89ab][a-f0-9]
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# *****************************************************************************************************************
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class NimbusSMSIndiaAuth(BaseModel):
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class LLMInputMessage(BaseModel):
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entityId: str = Field(
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description = "the entity id as registered with DLT",
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min_length = 1,
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role: Literal["system", "ai", "human"] = Field(
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description = "the role of this message",
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frozen = True
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)
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senderId: str = Field(
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description = "the 6-char code that you see in your SMS inbox",
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min_length = 1,
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frozen = True,
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examples = ["HDFCBK", "NSESMS", "ZRODHA"]
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)
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userId: str = Field(
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description = "the 6-digit id that Nimbus has assigned to you",
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min_length = 1,
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frozen = True
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)
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apiKey: str = Field(
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description = "the key generated through Nimbus's portal",
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min_length = 1,
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content: str = Field(
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description = "the message sent by the 'role'",
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frozen = True
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)
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@@ -114,23 +99,63 @@ class NimbusSMSIndiaAuth(BaseModel):
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# ---------------------------------------------------------------------------------------------------------------------
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class SavvyBulkSMSKenyaAuth(BaseModel):
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class LLMInput(BaseModel):
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apiKey: str = Field(
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description = "the key generated through Savvy's portal",
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min_length = 1,
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messages: List[LLMInputMessage]
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# ┏┓ ┏•
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# ┃ ┏┓┏┓╋┓┏┓
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# ┗┛┗┛┛┗┛┗┗┫
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# ┛
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class Config:
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extra = "forbid"
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# ┓┏ ┓• ┓ •
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# ┃┃┏┓┃┓┏┫┏┓╋┓┏┓┏┓
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# ┗┛┗┻┗┗┗┻┗┻┗┗┗┛┛┗
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@field_validator("messages")
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def validate_messages(cls, value):
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# Maintain counter(s):
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system_message_index = -1
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system_message_count = 0
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# Loop through the messages and check them:
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for index, message in enumerate(value):
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# For 'system' messages:
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if message.role == "system":
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system_message_index = index
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system_message_count += 1
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# Verify that there is AT MOST ONE 'system' message,
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# and verify that the 'system' message is the first message:
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if system_message_count > 1: raise ValueError(f"there can be at most 1 'system' message, found {system_message_count}")
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if system_message_index > 0: raise ValueError(f"'system' message must always be at index 0, found it at index {system_message_index}")
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# Done here:
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return value
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# ---------------------------------------------------------------------------------------------------------------------
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class LLMUsageTokens(BaseModel):
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input: int = Field(
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description = "how many tokens were given in the input",
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frozen = True
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)
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partnerId: str = Field(
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description = "the key generated through Savvy's portal",
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min_length = 1,
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output: int = Field(
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description = "how many tokens were generated as the output",
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frozen = True
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)
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shortCode: str = Field(
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description = "your short code with Savvy",
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min_length = 1,
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total: int = Field(
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description = "the sum of the input and output tokens",
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frozen = True
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)
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@@ -146,7 +171,54 @@ class SavvyBulkSMSKenyaAuth(BaseModel):
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# ---------------------------------------------------------------------------------------------------------------------
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class SMSAuthRequestHeaders(BaseModel):
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class LLMOutput(BaseModel):
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ts: AwareDatetime = Field(
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description = "the time at which the llm was invoked",
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default_factory = date_time.get_current_utc_date_time,
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frozen = True
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)
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messages: List[LLMInputMessage] = Field(
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description = "the messages that came in that invoked the llm",
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frozen = True
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)
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output: str | None = Field(
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description = "what the llm generated",
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default = None,
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frozen = True
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)
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client: Literal["openai"] = Field(
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description = "the co./brand that was used to use an llm",
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frozen = True
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)
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model: str = Field(
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description = "to know which model used in the process",
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frozen = True
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)
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tokens: LLMUsageTokens = Field(
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description = "to know how many tokens were used in the process",
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default = LLMUsageTokens(input = 0, output = 0, total = 0),
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frozen = True
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)
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# ┏┓ ┏•
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# ┃ ┏┓┏┓╋┓┏┓
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# ┗┛┗┛┛┗┛┗┗┫
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# ┛
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class Config:
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extra = "forbid"
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# ---------------------------------------------------------------------------------------------------------------------
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class LLMRequestHeaders(BaseModel):
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sessionToken: str = Field(
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description = "the session token of the user who is requesting the service",
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@@ -167,23 +239,6 @@ class SMSAuthRequestHeaders(BaseModel):
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return super().model_dump(*args, by_alias = True, **kwargs)
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# ---------------------------------------------------------------------------------------------------------------------
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class SMSAuthRequestData(BaseModel):
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messageClient: Literal["nimbusSmsIndia", "savvyBulkSmsKenya"]
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auth: Union[NimbusSMSIndiaAuth, SavvyBulkSMSKenyaAuth]
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# ┏┓ ┏•
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# ┃ ┏┓┏┓╋┓┏┓
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# ┗┛┗┛┛┗┛┗┗┫
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# ┛
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class Config:
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extra = "forbid"
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# *****************************************************************************************************************
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# ***** ****
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# *** MAIN PROGRAM ***
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@@ -193,4 +248,20 @@ class SMSAuthRequestData(BaseModel):
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if __name__ == "__main__":
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pass
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llm_messages = [
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{
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"role": "system",
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"content": "You are an office assistant."
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},
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{
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"role": "ai",
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"content": "Hello, sir. How may I help you today?"
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},
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{
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"role": "human",
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"content": "Please summarize this mail for me..."
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}
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]
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llm_input = LLMInput(messages = llm_messages)
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print(llm_input)
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