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tinytroupe/openai_utils.py

@@ -267,11 +267,24 @@ class OpenAIClient:
             # complete message
             logger.debug(f"   --> Complete messages sent to LLM: {chat_api_params['messages']}")
 
-            result_message = self.client.beta.chat.completions.parse(
-                    **chat_api_params
-                )
-
-            return result_message 
+            try:
+                result_message = self.client.beta.chat.completions.parse(
+                        **chat_api_params
+                    )
+                return result_message
+            except Exception as e:
+                logger.warning(f"Error while parsing LLM response with .parse(): {e}. Falling back to .create().")
+                # Fallback to regular create if parse fails (e.g. due to messy JSON with <think> tags)
+                # We need to remove response_format if it's a Pydantic model for create()
+                # but wait, completions.create also supports response_format={"type": "json_object"}
+                
+                # If it was a Pydantic model, we convert it to json_object for the fallback
+                if not isinstance(chat_api_params["response_format"], dict):
+                    chat_api_params["response_format"] = {"type": "json_object"}
+                
+                return self.client.chat.completions.create(
+                            **chat_api_params
+                        ) 
         
         else:
             logger.debug(f"Calling LLM model with these parameters: {logged_params}. Not showing 'messages' parameter.")

tinytroupe/utils/llm.py

@@ -850,6 +850,10 @@ def extract_json(text: str) -> dict:
     try:
         logger.debug(f"Extracting JSON from text: {text}")
 
+        # Remove <think>...</think> blocks if they exist
+        if isinstance(text, str):
+            text = re.sub(r"<think>.*?</think>", "", text, flags=re.DOTALL)
+
         # if it already is a dictionary or list, return it
         if isinstance(text, dict) or isinstance(text, list):
 

tinytroupe/utils/validation.py

@@ -4,6 +4,7 @@ import unicodedata
 
 from pydantic import ValidationError, BaseModel
 from tinytroupe.utils import logger
+from tinytroupe.utils.llm import extract_json
 
 ################################################################################
 # Validation
@@ -58,7 +59,7 @@ def to_pydantic_or_sanitized_dict(value: dict, model: BaseModel=None) -> dict:
     if model is not None and (isinstance(model, type) and issubclass(model, BaseModel)):
         # If a model is provided, try to validate the value against the model
         try:
-            res = model.model_validate(sanitize_dict(json.loads(value['content'])))
+            res = model.model_validate(sanitize_dict(extract_json(value['content'])))
             return res
         except ValidationError as e:
             logger.warning(f"Validation error: {e}")

utils/llm.py

@@ -721,7 +721,7 @@ class LLMChat:
 
     def _request_list_of_dict_llm_message(self):
             return {"role": "user",
-                    "content": "The `value` field you generate **must** be a list of dictionaries, specified as a JSON structure embedded in a string. For example, `[\{...\}, \{...\}, ...]`. This is critical for later processing."}
+                    "content": "The `value` field you generate **must** be a list of dictionaries, specified as a JSON structure embedded in a string. For example, `[\\{...\\}, \\{...\\}, ...]`. This is critical for later processing."}
 
     def _coerce_to_list(self, llm_output:str):
         """
@@ -850,6 +850,10 @@ def extract_json(text: str) -> dict:
     try:
         logger.debug(f"Extracting JSON from text: {text}")
 
+        # Remove <think>...</think> blocks if they exist
+        if isinstance(text, str):
+            text = re.sub(r"<think>.*?</think>", "", text, flags=re.DOTALL)
+
         # if it already is a dictionary or list, return it
         if isinstance(text, dict) or isinstance(text, list):
 

utils/validation.py

@@ -4,6 +4,7 @@ import unicodedata
 
 from pydantic import ValidationError, BaseModel
 from tinytroupe.utils import logger
+from tinytroupe.utils.llm import extract_json
 
 ################################################################################
 # Validation
@@ -58,7 +59,7 @@ def to_pydantic_or_sanitized_dict(value: dict, model: BaseModel=None) -> dict:
     if model is not None and (isinstance(model, type) and issubclass(model, BaseModel)):
         # If a model is provided, try to validate the value against the model
         try:
-            res = model.model_validate(sanitize_dict(json.loads(value['content'])))
+            res = model.model_validate(sanitize_dict(extract_json(value['content'])))
             return res
         except ValidationError as e:
             logger.warning(f"Validation error: {e}")