feat: Add OpenAI Conversations API (#3429)

# What does this PR do?

Initial implementation for `Conversations` and `ConversationItems` using
`AuthorizedSqlStore` with endpoints to:
- CREATE
- UPDATE
- GET/RETRIEVE/LIST
- DELETE

Set `level=LLAMA_STACK_API_V1`.

NOTE: This does not currently incorporate changes for Responses, that'll
be done in a subsequent PR.

Closes https://github.com/llamastack/llama-stack/issues/3235

## Test Plan
- Unit tests
- Integration tests

Also comparison of [OpenAPI spec for OpenAI
API](https://github.com/openai/openai-openapi/tree/manual_spec)
```bash
oasdiff breaking --fail-on ERR docs/static/llama-stack-spec.yaml https://raw.githubusercontent.com/openai/openai-openapi/refs/heads/manual_spec/openapi.yaml --strip-prefix-base "/v1/openai/v1" \
--match-path '(^/v1/openai/v1/conversations.*|^/conversations.*)'
```

Note I still have some uncertainty about this, I borrowed this info from
@cdoern on https://github.com/llamastack/llama-stack/pull/3514 but need
to spend more time to confirm it's working, at the moment it suggests it
does.

UPDATE on `oasdiff`, I investigated the OpenAI spec further and it looks
like currently the spec does not list Conversations, so that analysis is
useless. Noting for future reference.

---------

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

llama_stack/strong_typing/schema.py

@@ -484,12 +484,19 @@ class JsonSchemaGenerator:
                 }
             return ret
         elif origin_type is Literal:
-            if len(typing.get_args(typ)) != 1:
-                raise ValueError(f"Literal type {typ} has {len(typing.get_args(typ))} arguments")
-            (literal_value,) = typing.get_args(typ)  # unpack value of literal type
-            schema = self.type_to_schema(type(literal_value))
-            schema["const"] = literal_value
-            return schema
+            literal_args = typing.get_args(typ)
+            if len(literal_args) == 1:
+                (literal_value,) = literal_args
+                schema = self.type_to_schema(type(literal_value))
+                schema["const"] = literal_value
+                return schema
+            elif len(literal_args) > 1:
+                first_value = literal_args[0]
+                schema = self.type_to_schema(type(first_value))
+                schema["enum"] = list(literal_args)
+                return schema
+            else:
+                return {"enum": []}
         elif origin_type is type:
             (concrete_type,) = typing.get_args(typ)  # unpack single tuple element
             return {"const": self.type_to_schema(concrete_type, force_expand=True)}