fix: guard LLM response access in 39 cookbook examples

cookbook/pocketflow-a2a/utils.py

@@ -8,6 +8,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 def search_web(query):

cookbook/pocketflow-agent-skills/utils.py

@@ -19,4 +19,7 @@ def call_llm(prompt: str) -> str:
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}],
     )
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.choices[0].message.content

cookbook/pocketflow-agent/utils.py

@@ -9,6 +9,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 def search_web_duckduckgo(query):

cookbook/pocketflow-agentic-rag/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-chat-guardrail/utils.py

@@ -10,6 +10,12 @@ def call_llm(messages):
         temperature=0.7
     )
 
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+
+        raise ValueError("LLM returned empty or filtered response")
+
+
     return response.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-chat-memory/utils/call_llm.py

@@ -10,6 +10,12 @@ def call_llm(messages):
         temperature=0.7
     )
 
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+
+        raise ValueError("LLM returned empty or filtered response")
+
+
     return response.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-chat/utils.py

@@ -10,6 +10,12 @@ def call_llm(messages):
         temperature=0.7
     )
 
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+
+        raise ValueError("LLM returned empty or filtered response")
+
+
     return response.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-cli-hitl/utils/call_llm.py

@@ -10,6 +10,9 @@ def call_llm(prompt: str) -> str:
             {"role": "user", "content": prompt}
         ]
     )
+    if not response.content or response.content[0].text is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.content[0].text
 
 if __name__ == "__main__":

cookbook/pocketflow-code-generator/utils/call_llm.py

@@ -10,6 +10,9 @@ def call_llm(prompt):
             {"role": "user", "content": prompt}
         ]
     )
+    if not response.content or response.content[0].text is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.content[0].text
 
 if __name__ == "__main__":

cookbook/pocketflow-coding-agent/utils/call_llm.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-debate/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-deep-research/utils.py

@@ -10,6 +10,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-fastapi-background/utils/call_llm.py

@@ -7,6 +7,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-gradio-hitl/utils/call_llm.py

@@ -14,6 +14,9 @@ def call_llm(message: str):
     response: ChatCompletion = client.chat.completions.create(
         model=model, messages=[{"role": "user", "content": message}]
     )
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.choices[0].message.content
 
 

cookbook/pocketflow-heartbeat/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-hello-world/utils/call_llm.py

@@ -6,6 +6,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-invoice/utils.py

@@ -10,6 +10,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai
@@ -31,6 +35,10 @@ def call_llm_with_image(prompt, image_base64):
                 {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_base64}"}}
             ]}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-judge/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-lead-generation/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-majority-vote/utils.py

@@ -10,6 +10,9 @@ def call_llm(prompt):
             {"role": "user", "content": prompt}
         ]
     )
+    if not response.content or response.content[0].text is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.content[0].text
 
 if __name__ == "__main__":

cookbook/pocketflow-map-reduce/utils.py

@@ -7,6 +7,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 # Example usage

cookbook/pocketflow-mcp/utils.py

@@ -13,6 +13,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 def get_tools(server_script_path=None):
@@ -126,6 +128,10 @@ async def _call_tool():
             async with ClientSession(read, write) as session:
                 await session.initialize()
                 result = await session.call_tool(tool_name, arguments)
+                if not result.content or result.content[0].text is None:
+
+                    raise ValueError("LLM returned empty or filtered response")
+
                 return result.content[0].text
 
     return asyncio.run(_call_tool())

cookbook/pocketflow-multi-agent/utils.py

@@ -7,6 +7,8 @@ def call_llm(prompt):
         model="gpt-4o-mini",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 # Example usage

cookbook/pocketflow-newsletter/utils.py

@@ -10,6 +10,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-node/utils/call_llm.py

@@ -6,6 +6,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-notebook-lm/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-rag/utils.py

@@ -8,6 +8,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 def get_embedding(text):

cookbook/pocketflow-self-healing-mermaid/utils.py

@@ -9,6 +9,10 @@ def call_llm(prompt):
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return r.choices[0].message.content
     elif os.environ.get("GEMINI_API_KEY"):
         from google import genai

cookbook/pocketflow-structured-output/utils.py

@@ -7,6 +7,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 # Example usage

cookbook/pocketflow-supervisor/utils.py

@@ -8,6 +8,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 def search_web(query):

cookbook/pocketflow-tao/utils.py

@@ -9,6 +9,8 @@ def call_llm(prompt):
         model=os.environ.get("OPENAI_MODEL", "openai/gpt-4.1-nano"),
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-text2sql/utils/call_llm.py

@@ -7,6 +7,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 # Example usage

cookbook/pocketflow-thinking/utils.py

@@ -10,6 +10,9 @@ def call_llm(prompt):
             {"role": "user", "content": prompt}
         ]
     )
+    if not response.content or response.content[0].text is None:
+
+        raise ValueError("LLM returned empty or filtered response")
     return response.content[0].text
 
 if __name__ == "__main__":

cookbook/pocketflow-tool-crawler/utils/call_llm.py

@@ -18,6 +18,10 @@ def call_llm(prompt: str) -> str:
             model="gpt-4",
             messages=[{"role": "user", "content": prompt}]
         )
+        if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+            raise ValueError("LLM returned empty or filtered response")
+
         return response.choices[0].message.content
 
     except Exception as e:

cookbook/pocketflow-tool-embeddings/utils/call_llm.py

@@ -9,6 +9,8 @@ def call_llm(prompt):
         model="gpt-4o",
         messages=[{"role": "user", "content": prompt}]
     )
+    if not r.choices or r.choices[0].message is None or r.choices[0].message.content is None:
+        raise ValueError("LLM returned empty or filtered response")
     return r.choices[0].message.content
 
 if __name__ == "__main__":

cookbook/pocketflow-tool-pdf-vision/tools/vision.py

@@ -31,6 +31,12 @@ def extract_text_from_image(image: Image.Image, prompt: str = None) -> str:
         }]
     )
 
+    if not response.choices or response.choices[0].message is None or response.choices[0].message.content is None:
+
+
+        raise ValueError("LLM returned empty or filtered response")
+
+
     return response.choices[0].message.content
 
 if __name__ == "__main__":