add gile list example

examples/filter_list_example.py

@@ -0,0 +1,23 @@
+import asyncio
+from core.filter_list_agent import FilterListAgent
+
+async def run_filter_list_example():
+    goal = "Remove items that are unhealthy snacks."
+    items_to_filter = [
+        "Apple",
+        "Chocolate bar",
+        "Carrot",
+        "Chips",
+        "Orange"
+    ]
+
+    agent = FilterListAgent(goal=goal, items_to_filter=items_to_filter)
+    filtered_results = await agent.filter()
+
+    print("Original list:", items_to_filter)
+    print("Filtered results:")
+    for result in filtered_results:
+        print(result)
+
+if __name__ == "__main__":
+    asyncio.run(run_filter_list_example())

requirements.txt

@@ -18,3 +18,4 @@ tiktoken
 anyio
 trio
 openai
+jsonschema

src/core/filter_list_agent.py

@@ -0,0 +1,76 @@
+import asyncio
+import json
+import jsonschema
+from typing import List, Dict
+from .openai_api import OpenAIClient
+
+class FilterListAgent:
+    def __init__(self, goal: str, items_to_filter: List[str], max_tokens: int = 500, temperature: float = 0.0):
+        self.goal = goal
+        self.items = items_to_filter
+        self.max_tokens = max_tokens
+        self.temperature = temperature
+        self.openai_client = OpenAIClient()
+
+    # JSON schema for validation
+    schema = {
+        "type": "object",
+        "properties": {
+            "explanation": {"type": "string"},
+            "remove_item": {"type": "boolean"}
+        },
+        "required": ["explanation", "remove_item"]
+    }
+
+    async def filter(self) -> List[Dict]:
+        return await self.filter_list(self.items)
+
+    async def filter_list(self, items: List[str]) -> List[Dict]:
+        # System prompt with multi-shot examples to guide the model
+        system_prompt = (
+            "You are an assistant tasked with filtering a list of items. The goal is: "
+            f"{self.goal}. For each item, decide if it should be removed based on whether it is a healthy snack.\n"
+            "Respond in the following structured format:\n\n"
+            "Example:\n"
+            "{\"explanation\": \"The apple is a healthy snack option, as it is low in calories...\",\n"
+            " \"remove_item\": false}\n\n"
+            "Example:\n"
+            "{\"explanation\": \"A chocolate bar is generally considered an unhealthy snack...\",\n"
+            " \"remove_item\": true}\n\n"
+        )
+
+        tasks = []
+        for index, item in enumerate(items):
+            user_prompt = f"Item {index+1}: {item}. Should it be removed? Answer with explanation and 'remove_item': true/false."
+            tasks.append(self.filter_item(system_prompt, user_prompt))
+
+        # Run all tasks in parallel
+        results = await asyncio.gather(*tasks)
+
+        # Show the final list of items that were kept
+        filtered_items = [self.items[i] for i, result in enumerate(results) if not result.get('remove_item', False)]
+        print("\nFinal Filtered List:", filtered_items)
+
+        return results
+
+    async def filter_item(self, system_prompt: str, user_prompt: str) -> Dict:
+        response = await self.openai_client.complete_chat([
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt}
+        ], max_tokens=self.max_tokens)
+
+        return await self.process_response(response, system_prompt, user_prompt)
+
+    async def process_response(self, response: str, system_prompt: str, user_prompt: str, retry: bool = True) -> Dict:
+        try:
+            # Parse the response as JSON
+            result = json.loads(response)
+            # Validate against the schema
+            jsonschema.validate(instance=result, schema=self.schema)
+            return result
+        except (json.JSONDecodeError, jsonschema.ValidationError) as e:
+            if retry:
+                # Retry once if validation fails
+                return await self.filter_item(system_prompt, user_prompt)
+            else:
+                return {"error": f"Failed to parse response after retry: {str(e)}", "response": response, "item": user_prompt}