b20199a4e3
- Added environment variables for Vertex AI and Azure OpenAI configurations in docker-compose and user configuration models. - Updated the application logic to handle Vertex and Azure as new LLM providers, including validation and API key management. - Enhanced the UI components to support model selection and API key input for Vertex and Azure. - Updated relevant utility functions and constants to accommodate the new providers. - Ensured proper error handling for configuration requirements specific to Vertex and Azure.
225 lines
7.6 KiB
Python
225 lines
7.6 KiB
Python
import time
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from typing import Optional
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from fastapi import HTTPException
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from llmai.shared import (
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AnthropicClientConfig,
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AzureOpenAIClientConfig,
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ChatGPTClientConfig,
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ClientConfig,
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GoogleClientConfig,
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OpenAIApiType,
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OpenAIClientConfig,
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VertexAIClientConfig,
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)
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from enums.llm_provider import LLMProvider
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from utils.get_env import (
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get_azure_openai_api_key_env,
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get_azure_openai_api_version_env,
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get_azure_openai_base_url_env,
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get_azure_openai_deployment_env,
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get_azure_openai_endpoint_env,
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get_anthropic_api_key_env,
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get_codex_access_token_env,
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get_codex_account_id_env,
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get_codex_refresh_token_env,
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get_codex_token_expires_env,
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get_custom_llm_api_key_env,
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get_custom_llm_url_env,
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get_disable_thinking_env,
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get_google_api_key_env,
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get_ollama_url_env,
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get_openai_api_key_env,
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get_vertex_api_key_env,
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get_vertex_base_url_env,
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get_vertex_location_env,
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get_vertex_project_env,
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get_web_grounding_env,
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)
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from utils.llm_provider import get_llm_provider
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from utils.parsers import parse_bool_or_none
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from utils.set_env import (
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set_codex_access_token_env,
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set_codex_account_id_env,
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set_codex_refresh_token_env,
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set_codex_token_expires_env,
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)
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def enable_web_grounding() -> bool:
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return parse_bool_or_none(get_web_grounding_env()) or False
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def disable_thinking() -> bool:
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return parse_bool_or_none(get_disable_thinking_env()) or False
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def _get_codex_access_token() -> str:
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access_token = get_codex_access_token_env()
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if not access_token:
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raise HTTPException(
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status_code=400,
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detail=(
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"Codex OAuth access token is not set. Please authenticate via "
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"/api/v1/ppt/codex/auth/initiate"
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),
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)
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expires_str = get_codex_token_expires_env()
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if expires_str:
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try:
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expires_ms = int(expires_str)
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now_ms = int(time.time() * 1000)
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if now_ms >= expires_ms - 60_000:
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refresh_token = get_codex_refresh_token_env()
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if refresh_token:
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from utils.oauth.openai_codex import (
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TokenSuccess,
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get_account_id,
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refresh_access_token,
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)
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result = refresh_access_token(refresh_token)
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if isinstance(result, TokenSuccess):
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set_codex_access_token_env(result.access)
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set_codex_refresh_token_env(result.refresh)
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set_codex_token_expires_env(str(result.expires))
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account_id = get_account_id(result.access)
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if account_id:
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set_codex_account_id_env(account_id)
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access_token = result.access
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except (TypeError, ValueError):
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pass
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return access_token
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def get_llm_config() -> ClientConfig:
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llm_provider = get_llm_provider()
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match llm_provider:
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case LLMProvider.OPENAI:
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api_key = get_openai_api_key_env()
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if not api_key:
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raise HTTPException(status_code=400, detail="OpenAI API Key is not set")
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return OpenAIClientConfig(
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api_key=api_key,
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api_type=OpenAIApiType.COMPLETIONS,
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)
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case LLMProvider.GOOGLE:
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api_key = get_google_api_key_env()
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if not api_key:
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raise HTTPException(status_code=400, detail="Google API Key is not set")
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return GoogleClientConfig(api_key=api_key)
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case LLMProvider.VERTEX:
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api_key = get_vertex_api_key_env()
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project = get_vertex_project_env()
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location = get_vertex_location_env()
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base_url = get_vertex_base_url_env()
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if api_key and (project or location):
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raise HTTPException(
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status_code=400,
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detail=(
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"Vertex configuration is ambiguous. Configure either "
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"VERTEX_API_KEY or VERTEX_PROJECT/VERTEX_LOCATION, not both."
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),
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)
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if api_key:
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return VertexAIClientConfig(
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api_key=api_key,
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base_url=base_url or None,
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)
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if not project:
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raise HTTPException(
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status_code=400,
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detail=(
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"Vertex configuration is incomplete. Set VERTEX_API_KEY "
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"or VERTEX_PROJECT (optionally with VERTEX_LOCATION)."
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),
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)
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return VertexAIClientConfig(
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project=project,
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location=location or None,
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base_url=base_url or None,
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)
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case LLMProvider.AZURE:
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api_key = get_azure_openai_api_key_env()
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api_version = get_azure_openai_api_version_env()
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endpoint = get_azure_openai_endpoint_env()
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base_url = get_azure_openai_base_url_env()
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deployment = get_azure_openai_deployment_env()
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if not api_key:
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raise HTTPException(
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status_code=400,
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detail="Azure OpenAI API Key is not set",
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)
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if not api_version:
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raise HTTPException(
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status_code=400,
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detail="Azure OpenAI API Version is not set",
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)
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if not endpoint and not base_url:
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raise HTTPException(
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status_code=400,
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detail=(
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"Azure OpenAI endpoint is not set. "
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"Configure AZURE_OPENAI_ENDPOINT or AZURE_OPENAI_BASE_URL."
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),
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)
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return AzureOpenAIClientConfig(
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api_key=api_key,
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api_version=api_version,
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endpoint=endpoint or None,
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base_url=base_url or None,
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deployment=deployment or None,
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)
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case LLMProvider.ANTHROPIC:
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api_key = get_anthropic_api_key_env()
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if not api_key:
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raise HTTPException(
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status_code=400,
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detail="Anthropic API Key is not set",
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)
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return AnthropicClientConfig(api_key=api_key)
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case LLMProvider.OLLAMA:
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return OpenAIClientConfig(
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base_url=(get_ollama_url_env() or "http://localhost:11434") + "/v1",
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api_key="ollama",
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)
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case LLMProvider.CUSTOM:
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base_url = get_custom_llm_url_env()
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if not base_url:
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raise HTTPException(
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status_code=400,
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detail="Custom LLM URL is not set",
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)
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return OpenAIClientConfig(
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base_url=base_url,
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api_key=get_custom_llm_api_key_env() or "null",
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)
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case LLMProvider.CODEX:
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return ChatGPTClientConfig(
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access_token=_get_codex_access_token(),
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account_id=get_codex_account_id_env() or None,
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)
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case _:
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raise HTTPException(
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status_code=400,
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detail=(
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"LLM Provider must be either openai, google, vertex, azure, "
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"anthropic, ollama, custom, or codex"
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),
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)
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def get_extra_body() -> Optional[dict]:
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if get_llm_provider() == LLMProvider.CUSTOM and disable_thinking():
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return {"enable_thinking": False}
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return None
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