fixed issue for smaller models due to instructions prompt

src/crewai/utilities/converter.py

@@ -23,7 +23,7 @@ class Converter(OutputConverter):
             if self.is_gpt:
                 return self._create_instructor().to_pydantic()
             else:
-                return self._create_chain().invoke({"query": self.text})
+                return self._create_chain().invoke({})
         except Exception as e:
             if current_attempt < self.max_attempts:
                 return self.to_pydantic(current_attempt + 1)

src/crewai/utilities/crew_pydantic_output_parser.py

@@ -20,6 +20,8 @@ class CrewPydanticOutputParser(PydanticOutputParser):
 
         # Treating edge case of function calling llm returning the name instead of tool_name
         json_object = json.loads(result[0].text)
+        if "tool_name" not in json_object:
+            json_object["tool_name"] = json_object.get("name", "")
         result[0].text = json.dumps(json_object)
 
         json_object = super().parse_result(result)

src/crewai/utilities/evaluators/task_evaluator.py

@@ -66,11 +66,11 @@ class TaskEvaluator:
             "- Entities extracted from the task output, if any, their type, description, and relationships"
         )
 
-        instructions = "I'm gonna convert this raw text into valid JSON."
+        instructions = "Convert this raw text into valid JSON."
 
         if not self._is_gpt(self.llm):
             model_schema = PydanticSchemaParser(model=TaskEvaluation).get_schema()
-            instructions = f"{instructions}\n\nThe json should have the following structure, with the following keys:\n{model_schema}"
+            instructions = f"{instructions}\n\nYou must return json with the following schema:\n{model_schema}"
 
         converter = Converter(
             llm=self.llm,