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Running
on
Zero
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import os
import shutil
import hmac
import hashlib
import base64
import subprocess
import time
from mysite.logger import logger
import async_timeout
import asyncio
import mysite.interpreter.interpreter_config
GENERATION_TIMEOUT_SEC=60
def set_environment_variables():
os.environ["OPENAI_API_BASE"] = "https://api.groq.com/openai/v1"
os.environ["OPENAI_API_KEY"] = "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"
os.environ["MODEL_NAME"] = "llama3-8b-8192"
os.environ["LOCAL_MODEL"] = "true"
# Set the environment variable.
def chat_with_interpreter(
message, history, a=None, b=None, c=None, d=None
): # , openai_api_key):
# Set the API key for the interpreter
# interpreter.llm.api_key = openai_api_key
if message == "reset":
interpreter.reset()
return "Interpreter reset", history
full_response = ""
# add_conversation(history,20)
user_entry = {"role": "user", "type": "message", "content": message}
#messages.append(user_entry)
# Call interpreter.chat and capture the result
messages = []
recent_messages = history[-20:]
for conversation in recent_messages:
user_message = conversation[0]
user_entry = {"role": "user", "content": user_message}
messages.append(user_entry)
assistant_message = conversation[1]
assistant_entry = {"role": "assistant", "content": assistant_message}
messages.append(assistant_entry)
user_entry = {"role": "user", "content": message}
messages.append(user_entry)
#system_prompt = {"role": "system", "content": "あなたは日本語の優秀なアシスタントです。"}
#messages.insert(0, system_prompt)
for chunk in interpreter.chat(messages, display=False, stream=True):
# print(chunk)
# output = '\n'.join(item['content'] for item in result if 'content' in item)
full_response = format_response(chunk, full_response)
yield full_response # chunk.get("content", "")
yield full_response + rows # , history
return full_response, history
async def completion(message: str, history, c=None, d=None):
from groq import Groq
client = Groq(api_key=os.getenv("api_key"))
messages = []
recent_messages = history[-20:]
for conversation in recent_messages:
user_message = conversation[0]
user_entry = {"role": "user", "content": user_message}
messages.append(user_entry)
assistant_message = conversation[1]
assistant_entry = {"role": "assistant", "content": assistant_message}
messages.append(assistant_entry)
user_entry = {"role": "user", "content": message}
messages.append(user_entry)
system_prompt = {"role": "system", "content": "あなたは日本語の優秀なアシスタントです。"}
messages.insert(0, system_prompt)
async with async_timeout.timeout(GENERATION_TIMEOUT_SEC):
try:
stream = client.chat.completions.create(
model="llama3-8b-8192",
messages=messages,
temperature=1,
max_tokens=1024,
top_p=1,
stream=True,
stop=None,
)
all_result = ""
for chunk in stream:
current_content = chunk.choices[0].delta.content or ""
all_result += current_content
yield current_content
yield all_result
#return all_result
except asyncio.TimeoutError:
raise HTTPException(status_code=504, detail="Stream timed out")
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