refactor(agent): Refactor & improve create_chat_completion (Signifi…

…cant-Gravitas#7082)

* refactor(agent/core): Rearrange and split up `OpenAIProvider.create_chat_completion`
   - Rearrange to reduce complexity, improve separation/abstraction of concerns, and allow multiple points of failure during parsing
   - Move conversion from `ChatMessage` to `openai.types.ChatCompletionMessageParam` to `_get_chat_completion_args`
   - Move token usage and cost tracking boilerplate code to `_create_chat_completion`
   - Move tool call conversion/parsing to `_parse_assistant_tool_calls` (new)

* fix(agent/core): Handle decoding of function call arguments in `create_chat_completion`
   - Amend `model_providers.schema`: change type of `arguments` from `str` to `dict[str, Any]` on `AssistantFunctionCall` and `AssistantFunctionCallDict`
   - Implement robust and transparent parsing in `OpenAIProvider._parse_assistant_tool_calls`
   - Remove now unnecessary `json_loads` calls throughout codebase

* feat(agent/utils): Improve conditions and errors in `json_loads`
   - Include all decoding errors when raising a ValueError on decode failure
   - Use errors returned by `return_errors` instead of an error buffer
   - Fix check for decode failure

autogpts/autogpt/autogpt/agent_factory/profile_generator.py

@@ -15,7 +15,6 @@
     CompletionModelFunction,
 )
 from autogpt.core.utils.json_schema import JSONSchema
-from autogpt.core.utils.json_utils import json_loads
 
 logger = logging.getLogger(__name__)
 
@@ -203,9 +202,7 @@ def parse_response_content(
                     f"LLM did not call {self._create_agent_function.name} function; "
                     "agent profile creation failed"
                 )
-            arguments: object = json_loads(
-                response_content.tool_calls[0].function.arguments
-            )
+            arguments: object = response_content.tool_calls[0].function.arguments
             ai_profile = AIProfile(
                 ai_name=arguments.get("name"),
                 ai_role=arguments.get("description"),

autogpts/autogpt/autogpt/agents/prompt_strategies/one_shot.py

@@ -26,7 +26,7 @@
     CompletionModelFunction,
 )
 from autogpt.core.utils.json_schema import JSONSchema
-from autogpt.core.utils.json_utils import extract_dict_from_json, json_loads
+from autogpt.core.utils.json_utils import extract_dict_from_json
 from autogpt.prompts.utils import format_numbered_list, indent
 
 
@@ -436,7 +436,7 @@ def extract_command(
             raise InvalidAgentResponseError("No 'tool_calls' in assistant reply")
         assistant_reply_json["command"] = {
             "name": assistant_reply.tool_calls[0].function.name,
-            "args": json_loads(assistant_reply.tool_calls[0].function.arguments),
+            "args": assistant_reply.tool_calls[0].function.arguments,
         }
     try:
         if not isinstance(assistant_reply_json, dict):

autogpts/autogpt/autogpt/core/planning/prompt_strategies/initial_plan.py

@@ -11,7 +11,6 @@
     CompletionModelFunction,
 )
 from autogpt.core.utils.json_schema import JSONSchema
-from autogpt.core.utils.json_utils import json_loads
 
 logger = logging.getLogger(__name__)
 
@@ -195,9 +194,7 @@ def parse_response_content(
                     f"LLM did not call {self._create_plan_function.name} function; "
                     "plan creation failed"
                 )
-            parsed_response: object = json_loads(
-                response_content.tool_calls[0].function.arguments
-            )
+            parsed_response: object = response_content.tool_calls[0].function.arguments
             parsed_response["task_list"] = [
                 Task.parse_obj(task) for task in parsed_response["task_list"]
             ]

autogpts/autogpt/autogpt/core/planning/prompt_strategies/name_and_goals.py

@@ -9,7 +9,6 @@
     CompletionModelFunction,
 )
 from autogpt.core.utils.json_schema import JSONSchema
-from autogpt.core.utils.json_utils import json_loads
 
 logger = logging.getLogger(__name__)
 
@@ -141,9 +140,7 @@ def parse_response_content(
                     f"LLM did not call {self._create_agent_function} function; "
                     "agent profile creation failed"
                 )
-            parsed_response = json_loads(
-                response_content.tool_calls[0].function.arguments
-            )
+            parsed_response = response_content.tool_calls[0].function.arguments
         except KeyError:
             logger.debug(f"Failed to parse this response content: {response_content}")
             raise

autogpts/autogpt/autogpt/core/planning/prompt_strategies/next_ability.py

@@ -11,7 +11,6 @@
     CompletionModelFunction,
 )
 from autogpt.core.utils.json_schema import JSONSchema
-from autogpt.core.utils.json_utils import json_loads
 
 logger = logging.getLogger(__name__)
 
@@ -188,9 +187,7 @@ def parse_response_content(
                 raise ValueError("LLM did not call any function")
 
             function_name = response_content.tool_calls[0].function.name
-            function_arguments = json_loads(
-                response_content.tool_calls[0].function.arguments
-            )
+            function_arguments = response_content.tool_calls[0].function.arguments
             parsed_response = {
                 "motivation": function_arguments.pop("motivation"),
                 "self_criticism": function_arguments.pop("self_criticism"),