Rag Updates

llama_toolchain/agentic_system/meta_reference/agent_instance.py

@@ -8,7 +8,7 @@ import asyncio
 import copy
 import uuid
 from datetime import datetime
-from typing import AsyncGenerator, List
+from typing import AsyncGenerator, List, Tuple
 
 from termcolor import cprint
 
@@ -53,6 +53,44 @@ class ChatAgent(ShieldRunnerMixin):
             output_shields=agent_config.output_shields,
         )
 
+    def turn_to_messages(self, turn: Turn) -> List[Message]:
+        messages = []
+
+        # We do not want to keep adding RAG context to the input messages
+        # May be this should be a parameter of the agentic instance
+        # that can define its behavior in a custom way
+        for m in turn.input_messages:
+            msg = m.copy()
+            if isinstance(msg, UserMessage):
+                msg.context = None
+            messages.append(msg)
+
+        # messages.extend(turn.input_messages)
+        for step in turn.steps:
+            if step.step_type == StepType.inference.value:
+                messages.append(step.model_response)
+            elif step.step_type == StepType.tool_execution.value:
+                for response in step.tool_responses:
+                    messages.append(
+                        ToolResponseMessage(
+                            call_id=response.call_id,
+                            tool_name=response.tool_name,
+                            content=response.content,
+                        )
+                    )
+            elif step.step_type == StepType.shield_call.value:
+                response = step.response
+                if response.is_violation:
+                    # CompletionMessage itself in the ShieldResponse
+                    messages.append(
+                        CompletionMessage(
+                            content=response.violation_return_message,
+                            stop_reason=StopReason.end_of_turn,
+                        )
+                    )
+        # print_dialog(messages)
+        return messages
+
     def create_session(self, name: str) -> Session:
         session_id = str(uuid.uuid4())
         session = Session(
@@ -75,32 +113,7 @@ class ChatAgent(ShieldRunnerMixin):
 
         messages = []
         for i, turn in enumerate(session.turns):
-            # print(f"turn {i}")
+            messages.extend(self.turn_to_messages(turn))
-            # print_dialog(turn.input_messages)
-            messages.extend(turn.input_messages)
-            for step in turn.steps:
-                if step.step_type == StepType.inference.value:
-                    messages.append(step.model_response)
-                elif step.step_type == StepType.tool_execution.value:
-                    for response in step.tool_responses:
-                        messages.append(
-                            ToolResponseMessage(
-                                call_id=response.call_id,
-                                tool_name=response.tool_name,
-                                content=response.content,
-                            )
-                        )
-                elif step.step_type == StepType.shield_call.value:
-                    response = step.response
-                    if response.is_violation:
-                        # TODO: Properly persist the
-                        # CompletionMessage itself in the ShieldResponse
-                        messages.append(
-                            CompletionMessage(
-                                content=response.violation_return_message,
-                                stop_reason=StopReason.end_of_turn,
-                            )
-                        )
 
         messages.extend(request.messages)
 
@@ -325,15 +338,8 @@ class ChatAgent(ShieldRunnerMixin):
             )
 
             if rag_context:
-                system_message = next(
+                last_message = input_messages[-1]
-                    (m for m in input_messages if m.role == "system"), None
+                last_message.context = "\n".join(rag_context)
-                )
-                if system_message:
-                    system_message.content = system_message.content + "\n" + rag_context
-                else:
-                    input_messages = [
-                        SystemMessage(content=rag_context)
-                    ] + input_messages
 
         elif attachments and AgenticSystemTool.code_interpreter.value in enabled_tools:
             urls = [a.content for a in attachments if isinstance(a.content, URL)]
@@ -610,7 +616,7 @@ class ChatAgent(ShieldRunnerMixin):
 
     async def _retrieve_context(
         self, session: Session, messages: List[Message], attachments: List[Attachment]
-    ) -> Optional[InterleavedTextMedia]:
+    ) -> Tuple[List[str], List[int]]:  # (rag_context, bank_ids)
         bank_ids = []
 
         memory = self._memory_tool_definition()
@@ -671,10 +677,10 @@ class ChatAgent(ShieldRunnerMixin):
                     "red",
                 )
                 break
-            picked.append(c.content)
+            picked.append(f"id:{c.document_id}; content:{c.content}")
 
         return [
-            "The following context was retrieved from the memory bank:\n=== START-RETRIEVED-CONTEXT ===\n",
+            "Here are the retrieved documents for relevant context:\n=== START-RETRIEVED-CONTEXT ===\n",
             *picked,
             "\n=== END-RETRIEVED-CONTEXT ===\n",
         ], bank_ids

llama_toolchain/distribution/registry.py

@@ -49,7 +49,7 @@ def available_distribution_specs() -> List[DistributionSpec]:
                 Api.inference: providers[Api.inference]["meta-ollama"],
                 Api.safety: providers[Api.safety]["meta-reference"],
                 Api.agentic_system: providers[Api.agentic_system]["meta-reference"],
-                Api.memory: remote_spec(Api.memory),
+                Api.memory: providers[Api.memory]["meta-reference-faiss"],
             },
         ),
         DistributionSpec(

llama_toolchain/memory/api/api.py

@@ -68,6 +68,7 @@ MemoryBankConfig = Annotated[
 class Chunk(BaseModel):
     content: InterleavedTextMedia
     token_count: int
+    document_id: str
 
 
 @json_schema_type

llama_toolchain/memory/meta_reference/faiss/faiss.py

@@ -89,6 +89,7 @@ class BankState:
                 self.chunk_by_index[indexlen + i] = Chunk(
                     content=chunk[0],
                     token_count=chunk[1],
+                    document_id=doc.document_id,
                 )
                 print(f"Adding chunk #{indexlen + i} tokens={chunk[1]}")
                 self.id_by_index[indexlen + i] = doc.document_id