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import aiohttp
import asyncio, pprint
import google.generativeai as palm
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain import PromptTemplate
import os
from poe_api_wrapper import PoeApi
import pprint
client = PoeApi("sXvCnfYy8CHnXNTRlxhmVg==")
bot = "Assistant"
PALM_API = ""
API_KEY = os.environ.get("PALM_API", PALM_API)
palm.configure(api_key=API_KEY)
text_splitter = RecursiveCharacterTextSplitter(
separators=["\n\n", "\n", "."], chunk_size=40_000, chunk_overlap=500
)
map_prompt = """
Write a verbose summary like a masters student of the following:
"{text}"
CONCISE SUMMARY:
"""
combine_prompt = """
Write a concise summary of the following text delimited by triple backquotes.
Return your response in a detailed verbose paragraph which covers the text. Make it as insightful to the reader as possible, write like a masters student.
```{text}```
SUMMARY:
"""
def count_tokens(text):
return palm.count_message_tokens(prompt=text)["token_count"]
# async def PalmTextModel(text, candidates=1):
# url = f"https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001:generateText?key={API_KEY}"
# headers = {
# "Content-Type": "application/json",
# }
# data = {
# "prompt": {"text": text},
# "temperature": 0.95,
# "top_k": 100,
# "top_p": 0.95,
# "candidate_count": candidates,
# "max_output_tokens": 1024,
# "stop_sequences": ["</output>"],
# "safety_settings": [
# {"category": "HARM_CATEGORY_DEROGATORY", "threshold": 4},
# {"category": "HARM_CATEGORY_TOXICITY", "threshold": 4},
# {"category": "HARM_CATEGORY_VIOLENCE", "threshold": 4},
# {"category": "HARM_CATEGORY_SEXUAL", "threshold": 4},
# {"category": "HARM_CATEGORY_MEDICAL", "threshold": 4},
# {"category": "HARM_CATEGORY_DANGEROUS", "threshold": 4},
# ],
# }
# async with aiohttp.ClientSession() as session:
# async with session.post(url, json=data, headers=headers) as response:
# if response.status == 200:
# result = await response.json()
# # print(result)
# if candidates > 1:
# temp = [candidate["output"] for candidate in result["candidates"]]
# return temp
# temp = result["candidates"][0]["output"]
# return temp
# else:
# print(f"Error: {response.status}\n{await response.text()}")
async def PalmTextModel(message):
for chunk in client.send_message(bot, message,chatCode='TWVzc2FnZTozMDY2MzYwNjQ5OQ=='):
pass
return chunk["text"]
async def Summarizer(essay):
docs = text_splitter.create_documents([essay])
# for 1 large document
if len(docs) == 1:
tasks = [
PalmTextModel(combine_prompt.format(text=doc.page_content)) for doc in docs
]
# Gather and execute the tasks concurrently
responses = await asyncio.gather(*tasks)
ans = " ".join(responses)
return ans
tasks = [PalmTextModel(map_prompt.format(text=doc.page_content)) for doc in docs]
# Gather and execute the tasks concurrently
responses = await asyncio.gather(*tasks)
main = " ".join(responses)
ans = await PalmTextModel(combine_prompt.format(text=main), candidates=1)
return ans
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