wehub-resource-sync
fed8b2eed7
Build and push multi-arch DocsGPT Docker image / build (linux/amd64, ubuntu-latest, amd64) (push) Has been cancelled
Backend release / release (push) Has been cancelled
Bandit Security Scan / bandit_scan (push) Has been cancelled
Build and push multi-arch DocsGPT Docker image / build (linux/arm64, ubuntu-24.04-arm, arm64) (push) Has been cancelled
Build and push multi-arch DocsGPT Docker image / manifest (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / build (linux/amd64, ubuntu-latest, amd64) (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / build (linux/arm64, ubuntu-24.04-arm, arm64) (push) Has been cancelled
Build and push DocsGPT FE Docker image for development / manifest (push) Has been cancelled
Python linting / ruff (push) Has been cancelled
Run python tests with pytest / Run tests and count coverage (3.12) (push) Has been cancelled
React Widget Build / build (push) Has been cancelled
71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
from typing import Any, Dict, Generator
|
|
|
|
from application.llm.handlers.base import LLMHandler, LLMResponse, ToolCall
|
|
from application.llm.openai import OpenAILLM
|
|
|
|
|
|
class OpenAILLMHandler(LLMHandler):
|
|
"""Handler for OpenAI API."""
|
|
|
|
def parse_response(self, response: Any) -> LLMResponse:
|
|
"""Parse OpenAI response into standardized format."""
|
|
if isinstance(response, str):
|
|
return LLMResponse(
|
|
content=response,
|
|
tool_calls=[],
|
|
finish_reason="stop",
|
|
raw_response=response,
|
|
)
|
|
|
|
message = getattr(response, "message", None) or getattr(response, "delta", None)
|
|
|
|
tool_calls = []
|
|
if hasattr(message, "tool_calls"):
|
|
tool_calls = [
|
|
ToolCall(
|
|
id=getattr(tc, "id", ""),
|
|
name=getattr(tc.function, "name", ""),
|
|
arguments=getattr(tc.function, "arguments", ""),
|
|
index=getattr(tc, "index", None),
|
|
)
|
|
for tc in message.tool_calls or []
|
|
]
|
|
# Reasoning lives on the message object for non-streaming and
|
|
# on the delta for streaming. DeepSeek thinking mode requires
|
|
# this to be echoed back on the next turn.
|
|
reasoning_content = OpenAILLM._extract_reasoning_text(message)
|
|
return LLMResponse(
|
|
content=getattr(message, "content", ""),
|
|
tool_calls=tool_calls,
|
|
finish_reason=getattr(response, "finish_reason", ""),
|
|
raw_response=response,
|
|
reasoning_content=reasoning_content,
|
|
)
|
|
|
|
def create_tool_message(self, tool_call: ToolCall, result: Any) -> Dict:
|
|
"""Create a tool result message in the standard internal format."""
|
|
import json as _json
|
|
|
|
from application.storage.db.serialization import PGNativeJSONEncoder
|
|
|
|
# PostgresTool results commonly include PG-native types
|
|
# (datetime / UUID / Decimal / bytea) when SELECT touches
|
|
# timestamptz / numeric / uuid / bytea columns. The shared
|
|
# encoder handles all five — bytes get base64 (lossless) instead
|
|
# of the ``str(b'...')`` repr that ``default=str`` would emit.
|
|
content = (
|
|
_json.dumps(result, cls=PGNativeJSONEncoder)
|
|
if not isinstance(result, str)
|
|
else result
|
|
)
|
|
return {
|
|
"role": "tool",
|
|
"tool_call_id": tool_call.id,
|
|
"content": content,
|
|
}
|
|
|
|
def _iterate_stream(self, response: Any) -> Generator:
|
|
"""Iterate through OpenAI streaming response."""
|
|
for chunk in response:
|
|
yield chunk
|