mirror of
https://github.com/farcasclaudiu/TradingAgents.git
synced 2026-06-22 05:01:20 +03:00
Yijia-Xiao
77755f0431
- Point requirements.txt to pyproject.toml as single source of truth - Resolve welcome.txt path relative to module for CLI portability - Include cli/static files in package build - Extract shared normalize_content for OpenAI Responses API and Gemini 3 list-format responses into base_client.py - Update README install and CLI usage instructions
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
from abc import ABC, abstractmethod
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from typing import Any, Optional
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def normalize_content(response):
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"""Normalize LLM response content to a plain string.
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Multiple providers (OpenAI Responses API, Google Gemini 3) return content
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as a list of typed blocks, e.g. [{'type': 'reasoning', ...}, {'type': 'text', 'text': '...'}].
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Downstream agents expect response.content to be a string. This extracts
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and joins the text blocks, discarding reasoning/metadata blocks.
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"""
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content = response.content
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if isinstance(content, list):
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texts = [
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item.get("text", "") if isinstance(item, dict) and item.get("type") == "text"
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else item if isinstance(item, str) else ""
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for item in content
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]
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response.content = "\n".join(t for t in texts if t)
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return response
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class BaseLLMClient(ABC):
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"""Abstract base class for LLM clients."""
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def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
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self.model = model
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self.base_url = base_url
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self.kwargs = kwargs
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@abstractmethod
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def get_llm(self) -> Any:
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"""Return the configured LLM instance."""
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pass
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@abstractmethod
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def validate_model(self) -> bool:
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"""Validate that the model is supported by this client."""
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pass
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