fixes

Author: Zvi Fried

src/mcp_as_a_judge/constants.py renamed to src/mcp_as_a_judge/core/constants.py

@@ -10,7 +10,7 @@
 from mcp.server.fastmcp import Context
 from pydantic import BaseModel, Field
 
-from mcp_as_a_judge.constants import MAX_TOKENS
+from mcp_as_a_judge.core.constants import MAX_TOKENS
 from mcp_as_a_judge.core.logging_config import get_logger
 from mcp_as_a_judge.llm.llm_integration import load_llm_config_from_env
 from mcp_as_a_judge.messaging.llm_provider import llm_provider
@@ -228,3 +228,6 @@ def create_pydantic_model_from_fields(fields_dict: dict) -> type[BaseModel]:
     )
 
     return dynamic_elicitation_model
+
+
+# (Removed rule-based decision extraction and gating to keep HITL LLM-driven)

src/mcp_as_a_judge/core/server_helpers.py

@@ -8,7 +8,7 @@
 from sqlalchemy import Engine, func
 from sqlmodel import Session, select
 
-from mcp_as_a_judge.constants import MAX_TOTAL_SESSIONS
+from mcp_as_a_judge.core.constants import MAX_TOTAL_SESSIONS
 from mcp_as_a_judge.core.logging_config import get_logger
 from mcp_as_a_judge.db.interface import ConversationRecord
 

src/mcp_as_a_judge/db/cleanup_service.py

@@ -5,7 +5,7 @@
 and configuration classes.
 """
 
-from mcp_as_a_judge.constants import (
+from mcp_as_a_judge.core.constants import (
     DATABASE_URL,
     MAX_SESSION_RECORDS,
     MAX_TOTAL_SESSIONS,

src/mcp_as_a_judge/db/db_config.py

@@ -8,7 +8,7 @@
 
 from dataclasses import dataclass
 
-from mcp_as_a_judge.constants import MAX_CONTEXT_TOKENS, MAX_RESPONSE_TOKENS
+from mcp_as_a_judge.core.constants import MAX_CONTEXT_TOKENS, MAX_RESPONSE_TOKENS
 from mcp_as_a_judge.core.logging_config import get_logger
 
 # Set up logger

src/mcp_as_a_judge/db/dynamic_token_limits.py

@@ -11,7 +11,7 @@
 from sqlalchemy import create_engine, func
 from sqlmodel import Session, SQLModel, asc, desc, select
 
-from mcp_as_a_judge.constants import MAX_CONTEXT_TOKENS
+from mcp_as_a_judge.core.constants import MAX_CONTEXT_TOKENS
 from mcp_as_a_judge.core.logging_config import get_logger
 from mcp_as_a_judge.db.cleanup_service import ConversationCleanupService
 from mcp_as_a_judge.db.interface import ConversationHistoryDB, ConversationRecord

src/mcp_as_a_judge/db/providers/sqlite_provider.py

@@ -182,7 +182,7 @@ async def filter_records_by_token_limit(
         return []
 
     # Use configured MAX_CONTEXT_TOKENS for filtering
-    from mcp_as_a_judge.constants import MAX_CONTEXT_TOKENS as _MAX
+    from mcp_as_a_judge.core.constants import MAX_CONTEXT_TOKENS as _MAX
 
     context_limit = _MAX
 

src/mcp_as_a_judge/db/token_utils.py

@@ -0,0 +1,21 @@
+"""
+Elicitation provider package.
+
+This package provides a factory pattern for creating elicitation providers
+that handle user input elicitation through various methods (MCP elicitation,
+fallback prompts, etc.).
+"""
+
+from mcp_as_a_judge.elicitation.factory import ElicitationProviderFactory, elicitation_provider
+from mcp_as_a_judge.elicitation.fallback_provider import FallbackElicitationProvider
+from mcp_as_a_judge.elicitation.interface import ElicitationProvider, ElicitationResult
+from mcp_as_a_judge.elicitation.mcp_provider import MCPElicitationProvider
+
+__all__ = [
+    "ElicitationProvider",
+    "ElicitationResult", 
+    "MCPElicitationProvider",
+    "FallbackElicitationProvider",
+    "ElicitationProviderFactory",
+    "elicitation_provider",
+]

src/mcp_as_a_judge/elicitation/__init__.py

@@ -0,0 +1,84 @@
+"""
+Elicitation provider factory for smart provider selection.
+
+This module implements the factory pattern for creating the appropriate
+elicitation provider based on capabilities and preferences. It automatically
+detects MCP elicitation capability and selects the best available provider.
+"""
+
+from mcp.server.fastmcp import Context
+from pydantic import BaseModel
+
+from mcp_as_a_judge.elicitation.fallback_provider import FallbackElicitationProvider
+from mcp_as_a_judge.elicitation.interface import ElicitationResult
+from mcp_as_a_judge.elicitation.mcp_provider import MCPElicitationProvider
+
+
+class ElicitationProviderFactory:
+    """
+    Unified elicitation provider that automatically selects the best available method.
+
+    Similar to the messaging provider, this checks for elicitation capability and
+    provides appropriate fallbacks when not available.
+    """
+
+    def __init__(self, prefer_elicitation: bool = True):
+        """
+        Initialize the elicitation provider factory.
+
+        Args:
+            prefer_elicitation: Whether to prefer MCP elicitation when available
+        """
+        self.prefer_elicitation = prefer_elicitation
+        self._mcp_provider = MCPElicitationProvider()
+        self._fallback_provider = FallbackElicitationProvider()
+
+    async def elicit_user_input(
+        self, message: str, schema: type[BaseModel], ctx: Context
+    ) -> ElicitationResult:
+        """
+        Elicit user input using the best available method.
+
+        Args:
+            message: Message to display to the user
+            schema: Pydantic model schema defining expected fields
+            ctx: MCP context
+
+        Returns:
+            ElicitationResult with success status and data/message
+        """
+
+        # Check if MCP elicitation is available and preferred
+        if self.prefer_elicitation and self._mcp_provider.check_capability(ctx):
+            result = await self._mcp_provider.elicit(message, schema, ctx)
+
+            # If MCP elicitation succeeds, return the result
+            if result.success:
+                return result
+
+        # Use fallback provider
+        return await self._fallback_provider.elicit(message, schema, ctx)
+
+    def get_available_providers(self, ctx: Context) -> dict[str, dict[str, object]]:
+        """Get information about all available providers.
+        
+        Args:
+            ctx: MCP context for capability checking
+            
+        Returns:
+            Dictionary with provider availability information
+        """
+        return {
+            "mcp_elicitation": {
+                "available": self._mcp_provider.check_capability(ctx),
+                "provider_type": self._mcp_provider.provider_type,
+            },
+            "fallback_elicitation": {
+                "available": True,  # Always available
+                "provider_type": self._fallback_provider.provider_type,
+            }
+        }
+
+
+# Global elicitation provider instance
+elicitation_provider = ElicitationProviderFactory(prefer_elicitation=True)

src/mcp_as_a_judge/elicitation/factory.py

@@ -0,0 +1,63 @@
+"""
+Fallback elicitation provider that returns a message for the AI assistant.
+
+This provider generates a structured message that the AI assistant can use
+to prompt the user when MCP elicitation is not available.
+"""
+
+from mcp.server.fastmcp import Context
+from pydantic import BaseModel
+
+from mcp_as_a_judge.elicitation.interface import ElicitationProvider, ElicitationResult
+from mcp_as_a_judge.models import ElicitationFallbackUserVars
+from mcp_as_a_judge.prompting.loader import prompt_loader
+
+
+class FallbackElicitationProvider(ElicitationProvider):
+    """Fallback provider that returns a message for the AI assistant to prompt the user."""
+
+    @property
+    def provider_type(self) -> str:
+        """Return the provider type identifier."""
+        return "fallback_elicitation"
+
+    async def _elicit(
+        self, message: str, schema: type[BaseModel], ctx: Context
+    ) -> ElicitationResult:
+        """Generate a fallback message for the AI assistant to prompt the user.
+        
+        Args:
+            message: Original message to display to the user
+            schema: Pydantic model schema defining expected fields
+            ctx: MCP context
+            
+        Returns:
+            ElicitationResult with success=False and a formatted message
+        """
+
+        # Extract field information from the schema
+        required_fields = []
+        optional_fields = []
+
+        for field_name, field_info in schema.model_fields.items():
+            field_desc = field_info.description or field_name.replace("_", " ").title()
+
+            if field_info.is_required():
+                required_fields.append(f"- **{field_desc}**")
+            else:
+                optional_fields.append(f"- **{field_desc}**")
+
+        # Create template variables
+        template_vars = ElicitationFallbackUserVars(
+            original_message=message,
+            required_fields=required_fields,
+            optional_fields=optional_fields,
+        )
+
+        # Generate fallback message using prompt template
+        fallback_message = prompt_loader.render_prompt(
+            "user/elicitation_fallback.md",
+            **template_vars.model_dump(exclude_none=True),
+        )
+
+        return ElicitationResult(success=False, message=fallback_message)