add-assistant #2
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@ -2,6 +2,7 @@ import os
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import io
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from openai import OpenAI
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class ConfigureAssistant:
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"""
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A class to configure an OpenAI assistant for aiding designers using the ArchiMajor project.
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@ -9,9 +10,32 @@ class ConfigureAssistant:
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"""
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SUPPORTED_FORMATS = {
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"c", "cpp", "css", "docx", "gif", "html", "java", "jpeg", "jpg", "js",
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"json", "md", "pdf", "php", "png", "pptx", "py", "rb", "tar", "tex", "ts", "txt",
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"webp", "xlsx", "xml", "zip",
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"c",
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"cpp",
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"css",
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"docx",
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"gif",
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"html",
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"java",
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"jpeg",
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"jpg",
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"js",
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"json",
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"md",
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"pdf",
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"php",
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"png",
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"pptx",
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"py",
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"rb",
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"tar",
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"tex",
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"ts",
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"txt",
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"webp",
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"xlsx",
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"xml",
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"zip",
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# "csv", # CSV is supported but not actually parsed so we're going to treat it as text
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}
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@ -108,8 +132,10 @@ class ConfigureAssistant:
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spoofed_file = io.BytesIO(file_content)
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spoofed_file.name = new_filename # Spoof the filename
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# Upload the file to the vector store
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file_batch = self.client.beta.vector_stores.file_batches.upload_and_poll(
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vector_store_id=self.vector_store.id, files=[spoofed_file]
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file_batch = (
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self.client.beta.vector_stores.file_batches.upload_and_poll(
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vector_store_id=self.vector_store.id, files=[spoofed_file]
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)
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)
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print(f"Successfully uploaded: {new_filename}")
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except Exception as e:
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@ -3,6 +3,7 @@ import logging
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import pandas as pd
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from openai import OpenAI
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class OpenAIResourceManager:
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"""
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A class to manage OpenAI resources such as assistants, vector stores, and files.
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@ -112,14 +113,20 @@ class OpenAIResourceManager:
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:param max_length: The maximum length of the string.
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:return: The truncated string.
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"""
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return (s[:max_length] + '...') if len(s) > max_length else s
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return (s[:max_length] + "...") if len(s) > max_length else s
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def show_all_assistants(self):
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"""
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Display all assistants in a table.
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"""
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assistants = self.get_all_assistants()
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assistant_data = [{k: self.truncate_string(str(v), max_length=25) for k, v in assistant.dict().items()} for assistant in assistants]
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assistant_data = [
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{
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k: self.truncate_string(str(v), max_length=25)
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for k, v in assistant.dict().items()
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}
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for assistant in assistants
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]
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df = pd.DataFrame(assistant_data)
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print("Assistants:")
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print(df.to_markdown(index=False))
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@ -129,7 +136,10 @@ class OpenAIResourceManager:
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Display all vector stores in a table.
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"""
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vector_stores = self.get_all_vector_stores()
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vector_store_data = [{k: self.truncate_string(str(v)) for k, v in vector_store.dict().items()} for vector_store in vector_stores]
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vector_store_data = [
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{k: self.truncate_string(str(v)) for k, v in vector_store.dict().items()}
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for vector_store in vector_stores
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]
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df = pd.DataFrame(vector_store_data)
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print("Vector Stores:")
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print(df.to_markdown(index=False))
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@ -139,7 +149,10 @@ class OpenAIResourceManager:
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Display all files in a table.
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"""
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files = self.get_all_files()
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file_data = [{k: self.truncate_string(str(v)) for k, v in file.dict().items()} for file in files]
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file_data = [
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{k: self.truncate_string(str(v)) for k, v in file.dict().items()}
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for file in files
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]
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df = pd.DataFrame(file_data)
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print("Files:")
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print(df.to_markdown(index=False))
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@ -8,6 +8,7 @@ from typing_extensions import override
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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class QueryAssistant:
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"""
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A class to manage querying an OpenAI assistant.
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@ -72,22 +73,23 @@ class QueryAssistant:
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"""
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logging.info(f"Fetching response for thread {thread_id}...")
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run = self.client.beta.threads.runs.create_and_poll(
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thread_id=thread_id,
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assistant_id=self.assistant_id
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thread_id=thread_id, assistant_id=self.assistant_id
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)
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# Poll the run status with a delay to reduce the number of GET requests
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while run.status != 'completed' and run.status != 'failed':
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while run.status != "completed" and run.status != "failed":
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time.sleep(2) # Add a 2-second delay between checks
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run = self.client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
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run = self.client.beta.threads.runs.retrieve(
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thread_id=thread_id, run_id=run.id
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)
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logging.info(f"Run status: {run.status}")
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if run.status == 'completed':
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if run.status == "completed":
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messages = self.client.beta.threads.messages.list(thread_id=thread_id).data
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for message in messages:
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if message.role == 'assistant':
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if message.role == "assistant":
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for content in message.content:
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if content.type == 'text':
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if content.type == "text":
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print(content.text.value)
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else:
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logging.error(f"Run failed with status: {run.status}")
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@ -144,6 +146,7 @@ class QueryAssistant:
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if output.type == "logs":
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print(f"\n{output.logs}", flush=True)
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def main(query: str, assistant_id: str, context: str, use_streaming: bool):
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"""
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The main function to run the assistant query.
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@ -169,6 +172,7 @@ def main(query: str, assistant_id: str, context: str, use_streaming: bool):
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assistant.fetch_response(thread_id=thread.id)
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print("\n")
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if __name__ == "__main__":
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# Default query and context
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DEFAULT_QUERY = "What are you capable of as an assistant?"
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Reference in New Issue