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Doc: modify 2 examples to show OpenAIResponses API (#2525)

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Dev Khant
2025-04-10 10:24:10 +05:30
committed by GitHub
parent 3cc794fb98
commit 44f2490667
2 changed files with 25 additions and 20 deletions
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22
docs/examples/personal-ai-tutor.mdx
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@@ -20,6 +20,7 @@ pip install openai mem0ai
Below is the complete code to create and interact with a Personalized AI Tutor using Mem0: Below is the complete code to create and interact with a Personalized AI Tutor using Mem0:
```python ```python
import os
from openai import OpenAI from openai import OpenAI
from mem0 import Memory from mem0 import Memory
@@ -54,22 +55,21 @@ class PersonalAITutor:
:param question: The question to ask the AI. :param question: The question to ask the AI.
:param user_id: Optional user ID to associate with the memory. :param user_id: Optional user ID to associate with the memory.
""" """
# Start a streaming chat completion request to the AI # Start a streaming response request to the AI
stream = self.client.chat.completions.create( response = self.client.responses.create(
model="gpt-4", model="gpt-4o",
stream=True, instructions="You are a personal AI Tutor.",
messages=[ input=question,
{"role": "system", "content": "You are a personal AI Tutor."}, stream=True
{"role": "user", "content": question}
]
) )
# Store the question in memory # Store the question in memory
self.memory.add(question, user_id=user_id, metadata={"app_id": self.app_id}) self.memory.add(question, user_id=user_id, metadata={"app_id": self.app_id})
# Print the response from the AI in real-time # Print the response from the AI in real-time
for chunk in stream: for event in response:
if chunk.choices[0].delta.content is not None: if event.type == "response.output_text.delta":
print(chunk.choices[0].delta.content, end="") print(event.delta, end="")
def get_memories(self, user_id=None): def get_memories(self, user_id=None):
""" """

23
docs/examples/personal-travel-assistant.mdx
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@@ -63,18 +63,23 @@ class PersonalTravelAssistant:
def ask_question(self, question, user_id): def ask_question(self, question, user_id):
# Fetch previous related memories # Fetch previous related memories
previous_memories = self.search_memories(question, user_id=user_id) previous_memories = self.search_memories(question, user_id=user_id)
prompt = question
if previous_memories:
prompt = f"User input: {question}\n Previous memories: {previous_memories}"
self.messages.append({"role": "user", "content": prompt})
# Generate response using GPT-4o # Build the prompt
response = self.client.chat.completions.create( system_message = "You are a personal AI Assistant."
if previous_memories:
prompt = f"{system_message}\n\nUser input: {question}\nPrevious memories: {', '.join(previous_memories)}"
else:
prompt = f"{system_message}\n\nUser input: {question}"
# Generate response using Responses API
response = self.client.responses.create(
model="gpt-4o", model="gpt-4o",
messages=self.messages input=prompt
) )
answer = response.choices[0].message.content
self.messages.append({"role": "assistant", "content": answer}) # Extract answer from the response
answer = response.output[0].content[0].text
# Store the question in memory # Store the question in memory
self.memory.add(question, user_id=user_id) self.memory.add(question, user_id=user_id)