support open models

ra_aid/__main__.py

@@ -28,6 +28,7 @@ from ra_aid.prompts import (
 from ra_aid.exceptions import TaskCompletedException
 import time
 from anthropic import APIError, APITimeoutError, RateLimitError, InternalServerError
+from ra_aid.llm import initialize_llm
 
 def parse_arguments():
     parser = argparse.ArgumentParser(
@@ -49,18 +50,40 @@ Examples:
         action='store_true',
         help='Only perform research without implementation'
     )
+    parser.add_argument(
+        '--provider',
+        type=str,
+        default='anthropic',
+        choices=['anthropic', 'openai', 'openrouter', 'openai-compatible'],
+        help='The LLM provider to use'
+    )
+    parser.add_argument(
+        '--model',
+        type=str,
+        help='The model name to use (required for non-Anthropic providers)'
+    )
     parser.add_argument(
         '--cowboy-mode',
         action='store_true',
         help='Skip interactive approval for shell commands'
     )
-    return parser.parse_args()
+    
+    args = parser.parse_args()
+    
+    # Set default model for Anthropic, require model for other providers
+    if args.provider == 'anthropic':
+        if not args.model:
+            args.model = 'claude-3-5-sonnet-20241022'
+    elif not args.model:
+        parser.error(f"--model is required when using provider '{args.provider}'")
+    
+    return args
 
 # Create console instance
 console = Console()
 
 # Create the base model
-model = ChatAnthropic(model_name="claude-3-5-sonnet-20241022")
+model = initialize_llm(parse_arguments().provider, parse_arguments().model)
 
 # Create individual memory objects for each agent
 research_memory = MemorySaver()
@@ -239,22 +262,31 @@ def validate_environment():
     """Validate required environment variables and dependencies."""
     missing = []
     
-    # Check API keys
+    args = parse_arguments()
+    provider = args.provider
+
+    # Check API keys based on provider
+    if provider == "anthropic":
         if not os.environ.get('ANTHROPIC_API_KEY'):
             missing.append('ANTHROPIC_API_KEY environment variable is not set')
+    elif provider == "openai":
         if not os.environ.get('OPENAI_API_KEY'):
             missing.append('OPENAI_API_KEY environment variable is not set')
-    
+    elif provider == "openrouter":
-    # Check for aider binary
+        if not os.environ.get('OPENROUTER_API_KEY'):
-    if not shutil.which('aider'):
+            missing.append('OPENROUTER_API_KEY environment variable is not set')
-        missing.append('aider binary not found in PATH. Please install aider: pip install aider')
+    elif provider == "openai-compatible":
+        if not os.environ.get('OPENAI_API_KEY'):
+            missing.append('OPENAI_API_KEY environment variable is not set')
+        if not os.environ.get('OPENAI_API_BASE'):
+            missing.append('OPENAI_API_BASE environment variable is not set')
 
     if missing:
-        error_list = "\n".join(f"- {error}" for error in missing)
+        print_error("Missing required dependencies:")
-        print_error(f"Missing required dependencies:\n\n{error_list}")
+        for item in missing:
+            print_error(f"- {item}")
         sys.exit(1)
 
-
 def main():
     """Main entry point for the ra-aid command line tool."""
     try:

ra_aid/console/output.py

@@ -20,7 +20,8 @@ def print_agent_output(chunk: Dict[str, Any]) -> None:
                 # Handle text content
                 if isinstance(msg.content, list):
                     for content in msg.content:
-                        if content['type'] == 'text':
+                        if content['type'] == 'text' and content['text'].strip():
                             console.print(Panel(Markdown(content['text']), title="🤖 Assistant"))
                 else:
+                    if msg.content.strip():
                         console.print(Panel(Markdown(msg.content), title="🤖 Assistant"))

ra_aid/llm.py

@@ -0,0 +1,37 @@
+import os
+from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_core.language_models import BaseChatModel
+
+def initialize_llm(provider: str, model_name: str) -> BaseChatModel:
+    if provider == "openai":
+        api_key = os.getenv("OPENAI_API_KEY")
+        if not api_key:
+            raise ValueError("OPENAI_API_KEY environment variable is not set.")
+        return ChatOpenAI(openai_api_key=api_key, model=model_name)
+    elif provider == "anthropic":
+        api_key = os.getenv("ANTHROPIC_API_KEY")
+        if not api_key:
+            raise ValueError("ANTHROPIC_API_KEY environment variable is not set.")
+        return ChatAnthropic(anthropic_api_key=api_key, model=model_name)
+    elif provider == "openrouter":
+        api_key = os.getenv("OPENROUTER_API_KEY")
+        if not api_key:
+            raise ValueError("OPENROUTER_API_KEY environment variable is not set.")
+        return ChatOpenAI(
+            openai_api_key=api_key,
+            openai_api_base="https://openrouter.ai/api/v1",
+            model=model_name
+        )
+    elif provider == "openai-compatible":
+        api_key = os.getenv("OPENAI_API_KEY")
+        api_base = os.getenv("OPENAI_API_BASE")
+        if not api_key or not api_base:
+            raise ValueError("Both OPENAI_API_KEY and OPENAI_API_BASE environment variables must be set.")
+        return ChatOpenAI(
+            openai_api_key=api_key,
+            openai_api_base=api_base,
+            model=model_name
+        )
+    else:
+        raise ValueError(f"Unsupported provider: {provider}")

ra_aid/tools/fuzzy_find.py

@@ -27,8 +27,8 @@ def fuzzy_find_project_files(
     repo_path: str = ".",
     threshold: int = 60,
     max_results: int = 10,
-    include_paths: Optional[List[str]] = None,
+    include_paths: List[str] = None,
-    exclude_patterns: Optional[List[str]] = None
+    exclude_patterns: List[str] = None
 ) -> List[Tuple[str, int]]:
     """Fuzzy find files in a git repository matching the search term.
     

ra_aid/tools/list_directory.py

@@ -151,7 +151,7 @@ def list_directory_tree(
     follow_links: bool = False,
     show_size: bool = False,  # Default to not showing size
     show_modified: bool = False,  # Default to not showing modified time
-    exclude_patterns: Optional[List[str]] = None
+    exclude_patterns: List[str] = None
 ) -> str:
     """List directory contents in a tree format with optional metadata.
     

ra_aid/tools/ripgrep.py

@@ -28,11 +28,11 @@ DEFAULT_EXCLUDE_DIRS = [
 def ripgrep_search(
     pattern: str,
     *,
-    file_type: Optional[str] = None,
+    file_type: str = None,
     case_sensitive: bool = True,
     include_hidden: bool = False,
     follow_links: bool = False,
-    exclude_dirs: Optional[List[str]] = None
+    exclude_dirs: List[str] = None
 ) -> Dict[str, Union[str, int, bool]]:
     """Execute a ripgrep (rg) search with formatting and common options.
 

ra_aid/tools/shell.py

@@ -30,15 +30,6 @@ def run_shell_command(command: str) -> Dict[str, Union[str, int, bool]]:
        - Environment: .env, venv, env
        - IDE: .idea, .vscode
     3. Avoid doing recursive lists, finds, etc. that could be slow and have a ton of output. Likewise, avoid flags like '-l' that needlessly increase the output. But if you really need to, you can.
-    
-    Args:
-        command: List of command arguments. First item is the command, rest are arguments.
-        
-    Returns:
-        A dictionary containing:
-            - output: The command output (stdout + stderr combined)
-            - return_code: The process return code (0 typically means success)
-            - success: Boolean indicating if the command succeeded (return code == 0)
     """
     # Check if we need approval
     cowboy_mode = _global_memory.get('config', {}).get('cowboy_mode', False)