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https://github.com/DrizzleTime/Foxel.git
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feat: Implement AI Agent with enhanced tool processing capabilities (#89)
* feat: Implement AI Agent with tool processing capabilities - Added tools for listing and running processors in the agent. - Created data models for agent chat requests and tool calls. - Developed API integration for agent chat and streaming responses. - Built the AI Agent widget with a user interface for interaction. - Styled the agent components for better user experience. * feat: 增强 AI 助手工具功能，添加文件操作和搜索功能，更新界面显示 * feat: 更新 AI 助手组件 * feat: 更新 AiAgentWidget 组件样式，调整背景和边距以提升界面一致性
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时雨
@@ -1,5 +1,7 @@
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import json
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import httpx
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from typing import List, Sequence, Tuple
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from typing import Any, AsyncIterator, Dict, List, Sequence, Tuple
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from models.database import AIModel, AIProvider
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from domain.ai.service import AIProviderService
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@@ -243,3 +245,195 @@ async def _rerank_with_gemini(
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except (TypeError, ValueError):
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scores.append(0.0)
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return scores
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async def chat_completion(
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messages: List[Dict[str, Any]],
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*,
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ability: str = "chat",
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tools: List[Dict[str, Any]] | None = None,
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tool_choice: Any | None = None,
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temperature: float | None = None,
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timeout: float = 60.0,
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) -> Dict[str, Any]:
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model, provider = await _require_model(ability)
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if provider.api_format != "openai":
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raise MissingModelError("当前仅支持 OpenAI 兼容接口的对话模型。")
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return await _chat_with_openai(
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provider,
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model,
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messages,
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tools=tools,
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tool_choice=tool_choice,
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temperature=temperature,
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timeout=timeout,
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)
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async def _chat_with_openai(
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provider: AIProvider,
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model: AIModel,
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messages: List[Dict[str, Any]],
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*,
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tools: List[Dict[str, Any]] | None,
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tool_choice: Any | None,
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temperature: float | None,
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timeout: float,
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) -> Dict[str, Any]:
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url = _openai_endpoint(provider, "/chat/completions")
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payload: Dict[str, Any] = {
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"model": model.name,
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"messages": messages,
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}
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if tools:
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payload["tools"] = tools
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payload["tool_choice"] = tool_choice or "auto"
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if temperature is not None:
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payload["temperature"] = float(temperature)
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async with httpx.AsyncClient(timeout=timeout) as client:
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response = await client.post(url, headers=_openai_headers(provider), json=payload)
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response.raise_for_status()
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body = response.json()
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choices = body.get("choices") or []
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if not choices:
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raise RuntimeError("对话接口返回为空")
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message = choices[0].get("message")
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if not isinstance(message, dict):
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raise RuntimeError("对话接口返回格式异常")
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return message
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async def chat_completion_stream(
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messages: List[Dict[str, Any]],
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*,
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ability: str = "chat",
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tools: List[Dict[str, Any]] | None = None,
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tool_choice: Any | None = None,
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temperature: float | None = None,
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timeout: float = 60.0,
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) -> AsyncIterator[Dict[str, Any]]:
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model, provider = await _require_model(ability)
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if provider.api_format != "openai":
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raise MissingModelError("当前仅支持 OpenAI 兼容接口的对话模型。")
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async for event in _chat_stream_with_openai(
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provider,
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model,
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messages,
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tools=tools,
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tool_choice=tool_choice,
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temperature=temperature,
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timeout=timeout,
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):
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yield event
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async def _chat_stream_with_openai(
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provider: AIProvider,
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model: AIModel,
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messages: List[Dict[str, Any]],
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*,
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tools: List[Dict[str, Any]] | None,
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tool_choice: Any | None,
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temperature: float | None,
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timeout: float,
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) -> AsyncIterator[Dict[str, Any]]:
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url = _openai_endpoint(provider, "/chat/completions")
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payload: Dict[str, Any] = {
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"model": model.name,
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"messages": messages,
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"stream": True,
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}
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if tools:
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payload["tools"] = tools
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payload["tool_choice"] = tool_choice or "auto"
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if temperature is not None:
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payload["temperature"] = float(temperature)
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content_parts: List[str] = []
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tool_call_map: Dict[int, Dict[str, Any]] = {}
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role = "assistant"
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finish_reason: str | None = None
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async with httpx.AsyncClient(timeout=timeout) as client:
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async with client.stream("POST", url, headers=_openai_headers(provider), json=payload) as response:
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response.raise_for_status()
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async for line in response.aiter_lines():
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if not line:
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continue
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if not line.startswith("data:"):
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continue
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data = line[5:].strip()
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if not data:
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continue
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if data == "[DONE]":
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break
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try:
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chunk = json.loads(data)
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except json.JSONDecodeError:
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continue
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choices = chunk.get("choices") or []
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if not choices:
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continue
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choice = choices[0] if isinstance(choices[0], dict) else {}
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delta = choice.get("delta") if isinstance(choice, dict) else None
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delta = delta if isinstance(delta, dict) else {}
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if isinstance(delta.get("role"), str):
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role = delta["role"]
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delta_content = delta.get("content")
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if isinstance(delta_content, str) and delta_content:
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content_parts.append(delta_content)
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yield {"type": "delta", "delta": delta_content}
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delta_tool_calls = delta.get("tool_calls")
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if isinstance(delta_tool_calls, list):
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for item in delta_tool_calls:
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if not isinstance(item, dict):
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continue
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idx = item.get("index")
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if not isinstance(idx, int):
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continue
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entry = tool_call_map.setdefault(
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idx,
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{"id": None, "type": None, "function": {"name": None, "arguments": ""}},
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)
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if isinstance(item.get("id"), str) and item["id"].strip():
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entry["id"] = item["id"]
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if isinstance(item.get("type"), str) and item["type"].strip():
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entry["type"] = item["type"]
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fn = item.get("function")
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if isinstance(fn, dict):
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if isinstance(fn.get("name"), str) and fn["name"].strip():
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entry["function"]["name"] = fn["name"]
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args_part = fn.get("arguments")
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if isinstance(args_part, str) and args_part:
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entry["function"]["arguments"] += args_part
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fr = choice.get("finish_reason") if isinstance(choice, dict) else None
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if isinstance(fr, str) and fr:
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finish_reason = fr
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content = "".join(content_parts)
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message: Dict[str, Any] = {"role": role, "content": content}
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if tool_call_map:
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tool_calls: List[Dict[str, Any]] = []
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for idx in sorted(tool_call_map.keys()):
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item = tool_call_map[idx]
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fn = item.get("function") if isinstance(item.get("function"), dict) else {}
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call_id = item.get("id") if isinstance(item.get("id"), str) and item.get("id") else f"call_{idx}"
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call_type = item.get("type") if isinstance(item.get("type"), str) and item.get("type") else "function"
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tool_calls.append({
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"id": call_id,
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"type": call_type,
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"function": {
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"name": fn.get("name") or "",
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"arguments": fn.get("arguments") or "",
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},
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})
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message["tool_calls"] = tool_calls
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yield {"type": "message", "message": message, "finish_reason": finish_reason}
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