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| import json | |
| import os | |
| import gradio as gr | |
| os.environ['OPENAI_API_KEY']=os.getenv('OpenAI_KEY') | |
| os.environ["LANGCHAIN_API_KEY"]=os.getenv('LANGCHAIN_API_KEY') | |
| os.environ["LANGCHAIN_TRACING_V2"]="true" | |
| os.environ["LANGCHAIN_ENDPOINT"]="https://api.smith.langchain.com" | |
| os.environ["LANGCHAIN_PROJECT"]=os.getenv('LANGCHAIN_PROJECT') | |
| import openai | |
| from langsmith.wrappers import wrap_openai | |
| from langsmith import traceable | |
| # Auto-trace LLM calls in-context | |
| client = wrap_openai(openai.Client()) | |
| FakeNewsAggregator = client.beta.assistants.retrieve(os.getenv('OPENAI_ASSISTANT_ID')) | |
| thread= client.beta.threads.create() | |
| # Auto-trace this function | |
| def FakeNewsAggregatorRequest(text): | |
| global FakeNewsAggregator | |
| global thread | |
| message = client.beta.threads.messages.create( | |
| thread_id=thread.id, | |
| role="user", | |
| content=text | |
| ) | |
| run = client.beta.threads.runs.create_and_poll( | |
| thread_id=thread.id, | |
| assistant_id=FakeNewsAggregator.id | |
| ) | |
| if run.status == 'completed': | |
| messages = client.beta.threads.messages.list( | |
| thread_id=thread.id | |
| ) | |
| gpt_response=messages.data[0].content[0].text.value | |
| return gpt_response | |
| else: | |
| return run.status | |
| gr.Interface(fn=FakeNewsAggregatorRequest, | |
| inputs=["text"], | |
| outputs=["text"], | |
| flagging_mode='never', | |
| title="I am the TruthBot", | |
| description="I am virtual assistant to help you verify rumors or news", | |
| theme="soft", | |
| examples=['How to spot misinformation?','What are the views of Trump and Kamala on climate change?', 'Can Trump serve a third term?', 'What is disinformation?'] | |
| ).launch(share=False) | |