Agent is not stopping after each answer
Labels: name: area: agent, name: auto:bug

### System Info

Hi, 

I am working on a student teacher model . I am running into a problem where I agent does not generate final answer after the expected observations. Below is my code and output

Code
```
assignment_instruction_2 = """
1. Ask his name and then welcome him
2. Ask the topic he wants to understand
3. Ask about his understanding about the topic
3. Let him answer 
4. Then take out the relevant information from the get_next_content tool
5. If it is incomplete then tell him complete answer
"""

FORMAT_INSTRUCTIONS = f"""Use the following format:

        Question: the input question you must answer
        Thought: you should always think about what to do
        Action: the action to take, should be one of [{'get_topics', 'get_next_content', 'get_topic_tool'}]
        Action Input: the input to the action
        Observation: the detailed,at most comprehensive result of the action
        ... (this Thought/Action/Action Input/Observation can repeat N times)
        Thought: I now know the final answer based on my observation, i do not need anything more 
        Final Answer: the final answer to the original input question is the full detailed explanation from the Observation provided as bullet points.

        
        You have to provide the answer maximum after 2 Thoughts. 
        """

content_assignment = f"""You are the author of the book, You will be asked an assigenment by the user, which are typically students only.
                    help them to understand the topic according to the instructions delimited by /* */. follow them sequestially
                    /*{assignment_instruction_2} */

memory_assignment = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
llm_assignment = ChatOpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), temperature=0, model = "gpt-4")


agent_chain_assignment = initialize_agent(
    tools, 
    llm_assignment, 
    agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION, 
    verbose=True,
    memory=memory_assignment,
    max_iterations=3,
    # early_stopping_method="generate",
    format_instructions=FORMAT_INSTRUCTIONS,
    agent_kwargs={"system_message": content_assignment},
    handle_parsing_errors=_handle_error
)

print("<================= TOPIC Understand AGENT ====================>")
while(True):
    user_message = input("User: ")
    if user_message == 'exit':
        break
    response = agent_chain_assignment.run(user_message)
    print("LLM : ",response)
    print("===============================")
```

Ouput:

``` ```
<================= TOPIC Understand AGENT ====================>
User:  hi, sagar


> Entering new AgentExecutor chain...
```json
{
    "action": "Final Answer",
    "action_input": "Hello Sagar, welcome! What topic would you like to understand better today?"
}
```

> Finished chain.
LLM :  Hello Sagar, welcome! What topic would you like to understand better today?
===============================
User:  farming


> Entering new AgentExecutor chain...
Could not parse LLM output: That's a broad topic, Sagar. Could you tell me what you already understand about farming? This will help me provide you with the most relevant information.
Observation: Could not parse LLM output: That's a broad topic, 
Thought:Could not parse LLM output: I'm sorry for the confusion, Sagar. You mentioned that you want to understand more about farming. Could you please specify what exactly you know about farming? This will help me to provide you with the most relevant information.
Observation: Could not parse LLM output: I'm sorry for the conf
Thought:Could not parse LLM output: I'm sorry for the confusion, Sagar. You mentioned that you want to understand more about farming. Could you please specify what exactly you know about farming? This will help me to provide you with the most relevant information.
Observation: Could not parse LLM output: I'm sorry for the conf
Thought:

> Finished chain.
LLM :  Agent stopped due to iteration limit or time limit.
===============================
``` ```

It was supposed to output the final answer after the first answer (right after the user said "farming"). But it is running in loop and sometime it also consider that the user have already answered.

Can I make some corrections in the code where I can agent produce final answer right where it needs too. 

Thanks,
Sagar

### Who can help?

@hwchase17  @agola11 

### Information

- [ ] The official example notebooks/scripts
- [ ] My own modified scripts

### Related Components

- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [X] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

Provided in the question itself


### Expected behavior

provided in the explaination