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| import time | |
| import openai | |
| import requests | |
| import streamlit as st | |
| OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"] # app.pinecone.io | |
| OPENAI_ORGANIZATION_ID = st.secrets["OPENAI_ORGANIZATION_ID"] | |
| headers = {"Content-Type": "application/json", | |
| "Authorization": f"Bearer {OPENAI_API_KEY}" | |
| } | |
| SEED = 42 | |
| def get_client(): | |
| return openai.OpenAI(api_key = OPENAI_API_KEY,organization=OPENAI_ORGANIZATION_ID) | |
| def call_openai(prompt, engine="gpt-3.5-turbo", temp=0, top_p=1.0, max_tokens=4048): | |
| if st.session_state.report_type=="assistant": | |
| try: | |
| thread = st.session_state.assistant_thread | |
| assistant_id = st.session_state.assistant_id | |
| message = st.session_state.openai_client.beta.threads.messages.create( | |
| thread.id, | |
| role="user", | |
| content=prompt, | |
| ) | |
| run = st.session_state.openai_client.beta.threads.runs.create( | |
| thread_id=thread.id, | |
| assistant_id=assistant_id, | |
| instructions="Please address the user as Dan" | |
| ) | |
| messages = [] | |
| while True: | |
| # Retrieve the run status | |
| run_status = st.session_state.openai_client.beta.threads.runs.retrieve( | |
| thread_id=thread.id, | |
| run_id=run.id | |
| ) | |
| # Check and print the step details | |
| run_steps = st.session_state.openai_client.beta.threads.runs.steps.list( | |
| thread_id=thread.id, | |
| run_id=run.id | |
| ) | |
| for step in run_steps.data: | |
| if step.type == 'tool_calls': | |
| print(f"Tool {step.type} invoked.") | |
| # If step involves code execution, print the code | |
| if step.type == 'code_interpreter': | |
| print(f"Python Code Executed: {step.step_details['code_interpreter']['input']}") | |
| if run_status.status == 'completed': | |
| # Retrieve all messages from the thread | |
| messages = st.session_state.openai_client.beta.threads.messages.list( | |
| thread_id=thread.id | |
| ) | |
| # Print all messages from the thread | |
| for msg in messages.data: | |
| role = msg.role | |
| content = msg.content[0].text.value | |
| print(f"{role.capitalize()}: {content}") | |
| break # Exit the polling loop since the run is complete | |
| elif run_status.status in ['queued', 'in_progress']: | |
| print(f'{run_status.status.capitalize()}... Please wait.') | |
| time.sleep(1.5) # Wait before checking again | |
| else: | |
| print(f"Run status: {run_status.status}") | |
| break # Exit the polling loop if the status is neither 'in_progress' nor 'completed' | |
| print(f"====================\nOpen AI response\n {messages}\n====================\n") | |
| text = "" | |
| for message in messages: | |
| text = text + "\n" + message.content[0].text.value | |
| return text | |
| except Exception as e: | |
| #except openai.error.OpenAIError as e: | |
| print(f"An error occurred: {str(e)}") | |
| else: | |
| try: | |
| response = st.session_state.openai_client.chat.completions.create( | |
| model=engine, | |
| messages=st.session_state.messages + [{"role": "user", "content": prompt}], | |
| temperature=temp, | |
| seed = SEED, | |
| max_tokens=max_tokens | |
| ) | |
| print(f"====================\nOpen AI response\n {response}\n====================\n") | |
| text = response.choices[0].message.content.strip() | |
| return text | |
| except Exception as e: | |
| #except openai.error.OpenAIError as e: | |
| print(f"An error occurred: {str(e)}") | |
| return "Failed to generate a response." | |
| def get_assistant(assistant_id): | |
| return st.session_state.openai_client.beta.assistants.retrieve(assistant_id) | |
| def send_message(role, content): | |
| message = st.session_state.openai_client.beta.threads.messages.create( | |
| thread_id=st.session_state.assistant_thread.id, | |
| role=role, | |
| content=content | |
| ) | |
| def start_conversation(): | |
| st.session_state.assistant_thread = st.session_state.openai_client.beta.threads.create() | |
| def run_assistant(): | |
| run = st.session_state.openai_client.beta.threads.runs.create( | |
| thread_id=st.session_state.assistant_thread.id, | |
| assistant_id=st.session_state.assistant.id, | |
| ) | |
| while run.status == "queued" or run.status == "in_progress": | |
| run = st.session_state.openai_client.beta.threads.runs.retrieve( | |
| thread_id=st.session_state.assistant_thread.id, | |
| run_id=run.id, | |
| ) | |
| time.sleep(0.5) | |
| return run | |