chore: consolidate install, fix CLI portability, normalize LLM responses

- 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

tradingagents/llm_clients/google_client.py

@@ -2,30 +2,19 @@ from typing import Any, Optional
 
 from langchain_google_genai import ChatGoogleGenerativeAI
 
-from .base_client import BaseLLMClient
+from .base_client import BaseLLMClient, normalize_content
 from .validators import validate_model
 
 
 class NormalizedChatGoogleGenerativeAI(ChatGoogleGenerativeAI):
     """ChatGoogleGenerativeAI with normalized content output.
 
-    Gemini 3 models return content as list: [{'type': 'text', 'text': '...'}]
+    Gemini 3 models return content as list of typed blocks.
     This normalizes to string for consistent downstream handling.
     """
 
-    def _normalize_content(self, response):
-        content = response.content
-        if isinstance(content, list):
-            texts = [
-                item.get("text", "") if isinstance(item, dict) and item.get("type") == "text"
-                else item if isinstance(item, str) else ""
-                for item in content
-            ]
-            response.content = "\n".join(t for t in texts if t)
-        return response
-
     def invoke(self, input, config=None, **kwargs):
-        return self._normalize_content(super().invoke(input, config, **kwargs))
+        return normalize_content(super().invoke(input, config, **kwargs))
 
 
 class GoogleClient(BaseLLMClient):