Delete prompt_chain.py

prompt_chain.py

@@ -1,114 +0,0 @@
-from typing import Dict, Any, List
-import yaml
-
-class SimplePromptChain:
-    """A flexible prompt chain implementation using an AIAssistant wrapper."""
-
-    def __init__(self, assistant: AIAssistant, prompts_path: str):
-        """
-        Initialize chain with AI assistant and prompts.
-        
-        Args:
-            assistant: Configured AIAssistant instance
-            prompts_path: Path to YAML prompts file
-        """
-        self.assistant = assistant
-        self.prompts = PromptLoader.load_prompts(prompts_path)
-
-    def execute_step(self,
-                    prompt_name: str,
-                    generation_params: Dict[str, Any] = None,
-                    variables: Dict[str, Any] = None) -> str:
-        """
-        Execute single chain step using the AI assistant.
-        
-        Args:
-            prompt_name: Name of prompt template to use
-            generation_params: Optional parameters for generation
-            variables: Variables to format the prompt
-            
-        Returns:
-            Processed response content
-            
-        Raises:
-            ValueError: If prompt template not found
-        """
-        # Validate prompt exists
-        if prompt_name not in self.prompts:
-            raise ValueError(f"Prompt '{prompt_name}' not found in loaded templates")
-
-        prompt_template = self.prompts[prompt_name]
-        
-        try:
-            # Generate response using assistant
-            response = self.assistant.generate_response(
-                prompt_template=prompt_template,
-                generation_params=generation_params,
-                stream=True,
-                **variables or {}
-            )
-            
-            # Extract and return content from response
-            return response.choices[0].message.content
-            
-        except Exception as e:
-            raise Exception(f"Error in step execution: {str(e)}")
-
-    def run_chain(self, steps: List[Dict[str, Any]]) -> Dict[str, str]:
-        """
-        Execute chain of prompts using the AI assistant.
-
-        Args:
-            steps: List of steps to execute, each containing:
-                - prompt_name: Name of prompt template
-                - variables: Variables for the prompt
-                - output_key: Key to store step output
-                - generation_params: Optional generation parameters
-                
-        Returns:
-            Dict of step outputs keyed by output_key
-            
-        Example:
-            steps = [
-                {
-                    "prompt_name": "analyze",
-                    "variables": {"text": "Sample text"},
-                    "output_key": "analysis",
-                    "generation_params": {"temperature": 0.7}
-                },
-                {
-                    "prompt_name": "summarize",
-                    "variables": {"text": "{analysis}"},
-                    "output_key": "summary"
-                }
-            ]
-        """
-        results = {}
-        
-        for step in steps:
-            prompt_name = step["prompt_name"]
-            output_key = step["output_key"]
-            generation_params = step.get("generation_params", None)
-            
-            # Process variables, handling references to previous outputs
-            variables = {}
-            for key, value in step.get("variables", {}).items():
-                if isinstance(value, str) and value.startswith("{") and value.endswith("}"):
-                    # Extract referenced output key
-                    ref_key = value[1:-1]
-                    if ref_key not in results:
-                        raise ValueError(f"Referenced output '{ref_key}' not found in previous results")
-                    variables[key] = results[ref_key]
-                else:
-                    variables[key] = value
-
-            # Execute step and store result
-            print(f"\nExecuting step: {prompt_name}...")
-            result = self.execute_step(
-                prompt_name=prompt_name,
-                generation_params=generation_params,
-                variables=variables
-            )
-            results[output_key] = result
-
-        return results