Spaces:
Sleeping
Sleeping
File size: 3,597 Bytes
ad88099 3b49d05 ad88099 3b49d05 0e5c361 3b49d05 ad88099 423cbd4 3b49d05 423cbd4 3b49d05 0e5c361 c1b6204 ad88099 0e5c361 ad88099 0e5c361 ad65ad1 ad88099 0e5c361 ad88099 3b49d05 ad88099 3b49d05 423cbd4 ad88099 3b49d05 ad88099 b367859 ad88099 3b49d05 ad88099 3b49d05 423cbd4 ad88099 0e5c361 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
import os
import json
import time
import traceback
from dotenv import load_dotenv
from langfuse import Langfuse
from langchain_google_genai import ChatGoogleGenerativeAI
from langfuse.callback import CallbackHandler
from langchain_core.prompts import PromptTemplate
load_dotenv()
langfuse_news_analysis_handler = CallbackHandler(
secret_key=os.getenv("LANGFUSE_SECRET_KEY"),
public_key=os.getenv("LANGFUSE_PUBLIC_KEY"),
host="https://cloud.langfuse.com", # 🇪🇺 EU region
session_id="news_analysis",
)
langfuse_post_generation_handler = CallbackHandler(
secret_key=os.getenv("LANGFUSE_SECRET_KEY"),
public_key=os.getenv("LANGFUSE_PUBLIC_KEY"),
host="https://cloud.langfuse.com", # 🇪🇺 EU region
session_id="post_generation",
)
langfuse = Langfuse()
analysis_llm = ChatGoogleGenerativeAI(
model="gemini-2.0-flash-lite",
temperature=0.8,
timeout=None,
max_retries=2,
api_key=os.getenv("GOOGLE_API_KEY"),
)
post_content_llm = ChatGoogleGenerativeAI(
model="gemini-2.0-flash-lite",
temperature=0.8,
timeout=None,
max_retries=2,
api_key=os.getenv("GOOGLE_POST_GENERATION_API_KEY"),
)
def basic_analysis(news):
prompt = langfuse.get_prompt("news_selector")
for _ in range(5):
try:
response = analysis_llm.invoke(
prompt.compile(news_object = news),
config={"callbacks": [langfuse_news_analysis_handler]}
)
print("################ BASIC ANALYSIS AGENT RESPONSE ################")
print(response.content)
print("################ BASIC ANALYSIS END AGENT RESPONSE ################")
if "</think>" in response.content:
response.content = response.content.split("</think>")[1]
start_index = response.content.find("{")
end_index = response.content.rfind("}")
print("start index:", start_index)
print("end index:", end_index)
abstracted_string = ""
if start_index != -1 and end_index != -1 and start_index < end_index:
abstracted_string = response.content[start_index : end_index + 1]
try:
results = json.loads(abstracted_string)
print(results)
return results
except Exception as e:
print(e)
traceback.print_exc()
except Exception as e:
print(e)
traceback.print_exc()
time.sleep(30)
return {"error": "LLM response is not in correct format."}
def get_text_post_content(details, reference):
try:
prompt = PromptTemplate.from_file(
template_file="prompts/post_generator_without_source.yml",
input_variables=["NEWS_CONTENT", "CHAR_LENGTH"],
)
prompt = langfuse.get_prompt("post_generator")
user_query = prompt.compile(NEWS_CONTENT = details, CHAR_LENGTH = 490- len(reference))
response = post_content_llm.invoke(user_query, config={"callbacks": [langfuse_post_generation_handler]})
print("POST CONTENT RESPONSE:", response)
content = response.content.replace('"', '')
if "</think>" in content:
content = content.split("</think>")[1]
start_indx = content.find("#")
content = f"""{content[:start_indx]}
{reference}
{content[start_indx:]}"""
return content, True
except Exception as e:
print(e)
traceback.print_exc()
return "", False |