This repository has been archived on 2026-03-24. You can view files and clone it. You cannot open issues or pull requests or push a commit.
Files
docs/src/backend/core/services/ai_services.py

213 lines
7.3 KiB
Python
Raw Normal View History

"""AI services."""
import json
import logging
from typing import Any, Dict, Generator
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from openai import OpenAIError
from core import enums
if settings.LANGFUSE_PUBLIC_KEY:
from langfuse.openai import OpenAI
else:
from openai import OpenAI
log = logging.getLogger(__name__)
BLOCKNOTE_TOOL_STRICT_PROMPT = """
You are editing a BlockNote document via the tool applyDocumentOperations.
You MUST respond ONLY by calling applyDocumentOperations.
The tool input MUST be valid JSON:
{ "operations": [ ... ] }
Each operation MUST include "type" and it MUST be one of:
- "update" (requires: id, block)
- "add" (requires: referenceId, position, blocks)
- "delete" (requires: id)
VALID SHAPES (FOLLOW EXACTLY):
Update:
{ "type":"update", "id":"<id$>", "block":"<p>...</p>" }
IMPORTANT: "block" MUST be a STRING containing a SINGLE valid HTML element.
Add:
{ "type":"add", "referenceId":"<id$>", "position":"before|after", "blocks":["<p>...</p>"] }
IMPORTANT: "blocks" MUST be an ARRAY OF STRINGS.
Each item MUST be a STRING containing a SINGLE valid HTML element.
Delete:
{ "type":"delete", "id":"<id$>" }
IDs ALWAYS end with "$". Use ids EXACTLY as provided.
Return ONLY the JSON tool input. No prose, no markdown.
"""
AI_ACTIONS = {
"prompt": (
"Answer the prompt using markdown formatting for structure and emphasis. "
"Return the content directly without wrapping it in code blocks or markdown delimiters. "
"Preserve the language and markdown formatting. "
"Do not provide any other information. "
"Preserve the language."
),
"correct": (
"Correct grammar and spelling of the markdown text, "
"preserving language and markdown formatting. "
"Do not provide any other information. "
"Preserve the language."
),
"rephrase": (
"Rephrase the given markdown text, "
"preserving language and markdown formatting. "
"Do not provide any other information. "
"Preserve the language."
),
"summarize": (
"Summarize the markdown text, preserving language and markdown formatting. "
"Do not provide any other information. "
"Preserve the language."
),
"beautify": (
"Add formatting to the text to make it more readable. "
"Do not provide any other information. "
"Preserve the language."
),
"emojify": (
"Add emojis to the important parts of the text. "
"Do not provide any other information. "
"Preserve the language."
),
}
AI_TRANSLATE = (
"Keep the same html structure and formatting. "
"Translate the content in the html to the specified language {language:s}. "
"Check the translation for accuracy and make any necessary corrections. "
"Do not provide any other information."
)
class AIService:
"""Service class for AI-related operations."""
def __init__(self):
"""Ensure that the AI configuration is set properly."""
if (
settings.AI_BASE_URL is None
or settings.AI_API_KEY is None
or settings.AI_MODEL is None
):
raise ImproperlyConfigured("AI configuration not set")
self.client = OpenAI(base_url=settings.AI_BASE_URL, api_key=settings.AI_API_KEY)
def call_ai_api(self, system_content, text):
"""Helper method to call the OpenAI API and process the response."""
response = self.client.chat.completions.create(
model=settings.AI_MODEL,
messages=[
{"role": "system", "content": system_content},
{"role": "user", "content": text},
],
)
content = response.choices[0].message.content
if not content:
raise RuntimeError("AI response does not contain an answer")
return {"answer": content}
def transform(self, text, action):
"""Transform text based on specified action."""
system_content = AI_ACTIONS[action]
return self.call_ai_api(system_content, text)
def translate(self, text, language):
"""Translate text to a specified language."""
language_display = enums.ALL_LANGUAGES.get(language, language)
system_content = AI_TRANSLATE.format(language=language_display)
return self.call_ai_api(system_content, text)
def _normalize_tools(self, tools: list) -> list:
"""
Normalize tool definitions to ensure they have required fields.
"""
normalized = []
for tool in tools:
if isinstance(tool, dict) and tool.get("type") == "function":
fn = tool.get("function") or {}
if isinstance(fn, dict) and not fn.get("description"):
fn["description"] = f"Tool {fn.get('name', 'unknown')}."
tool["function"] = fn
normalized.append(tool)
return normalized
def _harden_payload(
self, payload: Dict[str, Any], stream: bool = False
) -> Dict[str, Any]:
"""Harden the AI API payload to enforce compliance and tool usage."""
payload["stream"] = stream
# Remove stream_options if stream is False
if not stream and "stream_options" in payload:
payload.pop("stream_options")
# Tools normalization
if isinstance(payload.get("tools"), list):
payload["tools"] = self._normalize_tools(payload["tools"])
# Inject strict system prompt once
msgs = payload.get("messages")
if isinstance(msgs, list):
need = True
if msgs and isinstance(msgs[0], dict) and msgs[0].get("role") == "system":
c = msgs[0].get("content") or ""
if (
isinstance(c, str)
and "applyDocumentOperations" in c
and "blocks" in c
):
need = False
if need:
payload["messages"] = [
{"role": "system", "content": BLOCKNOTE_TOOL_STRICT_PROMPT}
] + msgs
return payload
def proxy(self, data: dict, stream: bool = False) -> Generator[str, None, None]:
"""Proxy AI API requests to the configured AI provider."""
payload = self._harden_payload(data, stream=stream)
try:
return self.client.chat.completions.create(**payload)
except OpenAIError as e:
raise RuntimeError(f"Failed to proxy AI request: {e}") from e
def stream(self, data: dict) -> Generator[str, None, None]:
"""Stream AI API requests to the configured AI provider."""
try:
stream = self.proxy(data, stream=True)
for chunk in stream:
try:
chunk_dict = (
chunk.model_dump() if hasattr(chunk, "model_dump") else chunk
)
chunk_json = json.dumps(chunk_dict)
yield f"data: {chunk_json}\n\n"
except (AttributeError, TypeError) as e:
log.error("Error serializing chunk: %s, chunk: %s", e, chunk)
continue
except (OpenAIError, RuntimeError, OSError, ValueError) as e:
log.error("Streaming error: %s", e)
yield "data: [DONE]\n\n"