Agent abstraction Phase 1:

Author: rcholic

examples/test_local_llm_agent.py

@@ -0,0 +1,86 @@
+"""
+Test script for LocalLLMProvider with Qwen2.5-3B-Instruct
+Demonstrates using a local LLM with SentienceAgent
+"""
+
+from sentience.llm_provider import LocalLLMProvider
+
+def test_local_llm_basic():
+    """Test basic LLM response generation"""
+    print("="*70)
+    print("Testing LocalLLMProvider with Qwen2.5-3B-Instruct")
+    print("="*70)
+
+    # Initialize local LLM
+    # Using the model from your local cache
+    llm = LocalLLMProvider(
+        model_name="Qwen/Qwen2.5-3B-Instruct",
+        device="auto",  # Will use CUDA if available, else CPU
+        load_in_4bit=False,  # Set to True to save memory
+        torch_dtype="auto"
+    )
+
+    print("\n" + "="*70)
+    print("Test 1: Simple question")
+    print("="*70)
+
+    response = llm.generate(
+        system_prompt="You are a helpful web automation assistant.",
+        user_prompt="What is 2+2?",
+        max_new_tokens=50,
+        temperature=0.1
+    )
+
+    print(f"Response: {response.content}")
+    print(f"Tokens: {response.total_tokens} (prompt: {response.prompt_tokens}, completion: {response.completion_tokens})")
+
+    print("\n" + "="*70)
+    print("Test 2: Action parsing (for agent)")
+    print("="*70)
+
+    system_prompt = """You are an AI web automation agent.
+
+GOAL: Click the search box
+
+VISIBLE ELEMENTS (sorted by importance, max 50):
+[1] <button> "Sign In" {PRIMARY,CLICKABLE,color:blue} @ (100,50) (Imp:900)
+[2] <textbox> "" {CLICKABLE} @ (200,100) (Imp:850)
+[3] <link> "Help" {} @ (50,150) (Imp:700)
+
+VISUAL CUES:
+- {PRIMARY}: Main call-to-action element
+- {CLICKABLE}: Element is clickable
+- {color:X}: Background color name
+
+RESPONSE FORMAT (return ONLY the function call):
+- CLICK(id) - Click element by ID
+- TYPE(id, "text") - Type text into element
+- PRESS("key") - Press keyboard key
+- FINISH() - Task complete
+"""
+
+    user_prompt = "What is the next step to achieve the goal?"
+
+    response = llm.generate(
+        system_prompt=system_prompt,
+        user_prompt=user_prompt,
+        max_new_tokens=20,
+        temperature=0.0
+    )
+
+    print(f"Agent Response: {response.content}")
+    print(f"Tokens: {response.total_tokens}")
+
+    # Check if response is parseable
+    if "CLICK(2)" in response.content or "click(2)" in response.content.lower():
+        print("\n✅ SUCCESS: LLM correctly identified textbox (element 2) as search box!")
+    else:
+        print(f"\n⚠️  Response may need adjustment: {response.content}")
+
+    print("\n" + "="*70)
+    print("LocalLLMProvider Test Complete!")
+    print("="*70)
+
+
+if __name__ == "__main__":
+    test_local_llm_basic()

sentience/__init__.py

@@ -15,9 +15,14 @@
 from .read import read
 from .screenshot import screenshot
 
-__version__ = "0.10.6"
+# Agent Layer (Phase 1 & 2)
+from .llm_provider import LLMProvider, LLMResponse, OpenAIProvider, AnthropicProvider, LocalLLMProvider
+from .agent import SentienceAgent
+
+__version__ = "0.10.7"
 
 __all__ = [
+    # Core SDK
     "SentienceBrowser",
     "Snapshot",
     "Element",
@@ -44,5 +49,12 @@
     "generate",
     "read",
     "screenshot",
+    # Agent Layer
+    "LLMProvider",
+    "LLMResponse",
+    "OpenAIProvider",
+    "AnthropicProvider",
+    "LocalLLMProvider",
+    "SentienceAgent",
 ]