more updates

arch/arch_config_schema.yaml

@@ -13,40 +13,40 @@ properties:
     type: array
     items:
       type: object
-  llm_providers_v2:
-    type: object
   listeners:
-    type: object
-    additionalProperties: false
-    properties:
-      ingress_traffic:
-        type: object
-        properties:
-          address:
-            type: string
-          port:
-            type: integer
-          message_format:
-            type: string
-            enum:
-              - openai
-          timeout:
-            type: string
+    anyOf:
+      - type: array
+      - type: object
         additionalProperties: false
-      egress_traffic:
-        type: object
         properties:
-          address:
-            type: string
-          port:
-            type: integer
-          message_format:
-            type: string
-            enum:
-              - openai
-          timeout:
-            type: string
-        additionalProperties: false
+          ingress_traffic:
+            type: object
+            properties:
+              address:
+                type: string
+              port:
+                type: integer
+              message_format:
+                type: string
+                enum:
+                  - openai
+              timeout:
+                type: string
+            additionalProperties: false
+          egress_traffic:
+            type: object
+            properties:
+              address:
+                type: string
+              port:
+                type: integer
+              message_format:
+                type: string
+                enum:
+                  - openai
+              timeout:
+                type: string
+            additionalProperties: false
   endpoints:
     type: object
     patternProperties:
@@ -276,3 +276,4 @@ properties:
 additionalProperties: false
 required:
   - version
+  - listeners

arch/tools/cli/config_generator.py

@@ -99,38 +99,37 @@ def validate_and_render_schema():
     model_name_keys = set()
     model_usage_name_keys = set()
 
-    llm_gateway_listener = config_yaml.get("listeners", {}).get("egress_traffic", {})
-    if llm_gateway_listener.get("port") == None:
-        llm_gateway_listener["port"] = 12000
-
-    if (
-        llm_gateway_listener is None
-        and llm_gateway_listener
-        and config_yaml["llm_providers_v2"]
-    ):
-        raise Exception(
-            "Please provide either egress_traffic or llm_providers_v2, not both"
-        )
-
-    if config_yaml.get("llm_providers", None):
-        if config_yaml.get("llm_providers_v2", None) is not None:
-            raise Exception(
-                "Please provide either llm_providers or llm_providers_v2, not both"
-            )
-        config_yaml["llm_providers_v2"] = {
-            "default": {
-                "listener": {
-                    "port": llm_gateway_listener["port"],
-                    "protocol": llm_gateway_listener.get("message_format", "openai"),
-                },
-                "providers": config_yaml["llm_providers"],
+    # check if type is array or object
+    # if its dict its legacy format let's convert it to array
+    prompt_gateway_listener = None
+    llm_gateway_listener = None
+    if isinstance(config_yaml["listeners"], dict):
+        egress_traffic = config_yaml["listeners"].get("egress_traffic", None)
+        ingress_traffic = config_yaml["listeners"].get("ingress_traffic", None)
+        config_yaml["listeners"] = []
+        if ingress_traffic:
+            prompt_gateway_listener = {
+                "name": "ingress_traffic",
+                "port": ingress_traffic.get("port", 10000),
+                "address": ingress_traffic.get("address", "0.0.0.0"),
+                "timeout": ingress_traffic.get("timeout", "30s"),
             }
-        }
+            config_yaml["listeners"].append(prompt_gateway_listener)
+        if egress_traffic:
+            llm_gateway_listener = {
+                "name": "egress_traffic",
+                "port": egress_traffic.get("port", 12000),
+                "address": egress_traffic.get("address", "0.0.0.0"),
+                "timeout": egress_traffic.get("timeout", "30s"),
+                "llm_providers": config_yaml.get("llm_providers", []),
+            }
+            config_yaml["listeners"].append(llm_gateway_listener)
 
-    for llm_provider_name, provider_def in config_yaml["llm_providers_v2"].items():
-        provider_listener = provider_def["listener"]
+    for listener in config_yaml["listeners"]:
+        print("Processing listener: ", listener)
+        name = listener.get("name", None)
 
-        for llm_provider in provider_def["providers"]:
+        for llm_provider in listener.get("llm_providers", []):
             if llm_provider.get("usage", None):
                 llms_with_usage.append(llm_provider["name"])
             if llm_provider.get("name") in llm_provider_name_set:
@@ -243,15 +242,15 @@ def validate_and_render_schema():
     arch_config_string = yaml.dump(config_yaml)
     arch_llm_config_string = yaml.dump(config_yaml)
 
-    prompt_gateway_listener = config_yaml.get("listeners", {}).get(
-        "ingress_traffic", {}
-    )
-    if prompt_gateway_listener.get("port") == None:
-        prompt_gateway_listener["port"] = 10000  # default port for prompt gateway
-    if prompt_gateway_listener.get("address") == None:
-        prompt_gateway_listener["address"] = "127.0.0.1"
-    if prompt_gateway_listener.get("timeout") == None:
-        prompt_gateway_listener["timeout"] = "10s"
+    # prompt_gateway_listener = config_yaml.get("listeners", {}).get(
+    #     "ingress_traffic", {}
+    # )
+    # if prompt_gateway_listener.get("port") == None:
+    #     prompt_gateway_listener["port"] = 10000  # default port for prompt gateway
+    # if prompt_gateway_listener.get("address") == None:
+    #     prompt_gateway_listener["address"] = "127.0.0.1"
+    # if prompt_gateway_listener.get("timeout") == None:
+    #     prompt_gateway_listener["timeout"] = "10s"
 
     use_agent_orchestrator = config_yaml.get("overrides", {}).get(
         "use_agent_orchestrator", False

arch/tools/test/test_config_generator.py

@@ -90,45 +90,49 @@ def test_validate_and_render_happy_path_agent_config(monkeypatch):
     monkeypatch.setenv("TEMPLATE_ROOT", "../")
 
     arch_config = """
-version: v0.1.0
+version: v0.2.0
 
 agents:
-  - name: rag_assistant
-    description: t-mobile virtual assistant for device contracts.
-    instructions: |
-      You are a virtual assistant, here to help users answer questions from device contracts team.
-      Use following instructions to process the user request,
-      1. Use query_processor_agent to understand user queries
-      2. Use search_documents to fetch relevant information
-      3. Use response_generator_agent to formulate clear responses
-    model: openai/gpt-4o
-    tools:
-      - name: query_processor_agent
-        # Parses user queries and extracts metadata, also handles clarification workflow
-        protocol: openai
-        endpoint: https://localhost:10500
-      - name: search_documents
-        # Searches the document store for relevant information
-        protocol: openai
-        endpoint: https://localhost:10501
-      - name: response_generator_agent
-        # Generates a final response based on user query and retrieved context
-        protocol: openai
-        endpoint: https://localhost:10502
-    listener:
-      port: 8000
-      protocol: openai
-      path: /v1/chat/completions
+  - name: query_rewriter
+    kind: openai
+    endpoint: openai://localhost:10500
+  - name: context_builder
+    kind: openai
+    endpoint: openai://localhost:10501
+  - name: response_generator
+    kind: openai
+    endpoint: openai://localhost:10502
+  - name: research_agent
+    kind: openai
+    endpoint: https://localhost:10500
+  - name: input_guard_rails
+    kind: openai
+    endpoint: https://localhost:10503
 
-llm_providers_v2:
-  default:
-    listener:
-      port: 12000
-      protocol: openai
-    providers:
-      - access_key: --
+listeners:
+  - name: tmobile
+    router: arch_agent_v2
+    agents:
+      - name: simple_tmobile_rag_agent
+        description: t-mobile virtual assistant for device contracts.
+        filter_chain:
+          - query_rewriter
+          - context_builder
+          - response_generator
+      - name: research_agent
+        description: agent to research and gather information from various sources.
+        filter_chain:
+          - research_agent
+          - response_generator
+    port: 8000
+
+  - name: llm_provider
+    description: llm provider configuration
+    port: 12000
+    protocol: openai
+    llm_providers:
+      - access_key: ${OPENAI_API_KEY}
         model: openai/gpt-4o
-
 """
     arch_config_schema = ""
     with open("../arch_config_schema.yaml", "r") as file:

demos/use_cases/rag_agent/arch_config.yaml

@@ -1,38 +1,43 @@
-version: v0.1.0
+version: v0.2.0
 
 agents:
-  - name: rag_assistant
-    description: t-mobile virtual assistant for device contracts.
-    instructions: |
-      You are a virtual assistant, here to help users answer questions from device contracts team.
-      Use following instructions to process the user request,
-      1. Use query_processor_agent to understand user queries
-      2. Use search_documents to fetch relevant information
-      3. Use response_generator_agent to formulate clear responses
-    model: openai/gpt-4o
-    tools:
-      - name: query_processor_agent
-        # Parses user queries and extracts metadata, also handles clarification workflow
-        protocol: openai
-        endpoint: https://localhost:10500
-      - name: search_documents_agent
-        # Searches the document store for relevant information
-        protocol: openai
-        endpoint: https://localhost:10501
-      - name: response_generator_agent
-        # Generates a final response based on user query and retrieved context
-        protocol: openai
-        endpoint: https://localhost:10502
-    listener:
-      port: 8000
-      protocol: openai
-      path: /v1/chat/completions
+  - name: query_rewriter
+    kind: openai
+    endpoint: openai://localhost:10500
+  - name: context_builder
+    kind: openai
+    endpoint: openai://localhost:10501
+  - name: response_generator
+    kind: openai
+    endpoint: openai://localhost:10502
+  - name: research_agent
+    kind: openai
+    endpoint: https://localhost:10500
+  - name: input_guard_rails
+    kind: openai
+    endpoint: https://localhost:10503
 
-llm_providers_v2:
-  default:
-    listener:
-      port: 12000
-      protocol: openai
-    providers:
+listeners:
+  - name: rag agent
+    router: arch_agent_v2
+    agents:
+      - name: simple_rag_agent
+        description: virtual assistant for device contracts.
+        filter_chain:
+          - query_rewriter
+          - context_builder
+          - response_generator
+      - name: research_agent
+        description: agent to research and gather information from various sources.
+        filter_chain:
+          - research_agent
+          - response_generator
+    port: 8000
+
+  - name: llm_provider
+    description: llm provider configuration
+    port: 12000
+    protocol: openai
+    llm_providers:
       - access_key: ${OPENAI_API_KEY}
         model: openai/gpt-4o