- Implementation of specialist execution api, including SSE protocol

- eveai_chat becomes deprecated and should be replaced with SSE
- Adaptation of STANDARD_RAG specialist
- Base class definition allowing to realise specialists with crewai framework
- Implementation of SPIN_SPECIALIST
- Implementation of test app for testing specialists (test_specialist_client). Also serves as an example for future SSE-based client
- Improvements to startup scripts to better handle and scale multiple connections
- Small improvements to the interaction forms and views
- Caching implementation improved and augmented with additional caches

eveai_chat_workers/outputs/spin/spin_v1_0.py

@@ -0,0 +1,24 @@
+from typing import List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class SPINOutput(BaseModel):
+    situation: Optional[str] = Field(None, description="Situation information")
+    problem: Optional[str] = Field(None, description="Problem information")
+    implication: Optional[str] = Field(None, description="Implication information")
+    need: Optional[str] = Field(None, description="Need-payoff information")
+    additional_info: Optional[str] = Field(None, description="Additional sales-related information.")
+    questions: Optional[str] = Field(None, description="Additional questions to further clarify SPIN")
+    potential_customer: Optional[bool] = Field(False, description="Indication if this could be a good customer")
+
+    def __str__(self):
+        """Custom string output for usage in agents and tasks"""
+        return (f"Situation: {self.situation or 'N/A'}\n"
+                f"Problem: {self.problem or 'N/A'}\n"
+                f"Implication: {self.implication or 'N/A'}\n"
+                f"Need: {self.need or 'N/A'}\n"
+                f"Additional Info: {self.additional_info or 'N/A'}\n"
+                f"Questions: {self.questions or 'N/A'}\n"
+                f"Potential Customer: {self.potential_customer or 'N/A'}\n")
+