Harikrishna D.

import os
import google.generativeai as genai

genai.configure(api_key=os.environ["GEMINI_API_KEY"])

# Create the model
generation_config = {
  "temperature": 1,
  "top_p": 0.95,
  "top_k": 40,
  "max_output_tokens": 8192,
  "response_mime_type": "text/plain",
}

model = genai.GenerativeModel(
  model_name="gemini-1.5-pro",
  generation_config=generation_config,
  system_instruction="You're a bot which generates only SSML output based on the question. Include pauses and make it a conversation between two people in a podcast.  Use US Voices and add hmmm and umm and make the voices talk over each other. Donot include intro and outro music.",
)

chat_session = model.start_chat(
  history=[])

response = chat_session.send_message("INSERT_INPUT_HERE")

print(response.text)

from langchain_google_genai import ChatGoogleGenerativeAI
llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro-001",
    temperature=0,
    max_tokens=None,
    max_retries=6,
    stop=None,)

from langchain_google_vertexai import VertexAI

# To use model
model = VertexAI(
            model="gemini-1.5-pro-002",
            temperature=0,
            max_tokens=None,
            timeout=None,
            max_retries=2,
            safety_settings=safety_settings,
            )

from openinference.instrumentation.langchain import LangChainInstrumentor

google.cloud.bigquery.opentelemetry_tracing.HAS_OPENTELEMETRY = False

if "PHOENIX_CLIENT_HEADERS" not in os.environ:
    try:
        with open(phoenix_api_path, "r") as file:
            api_key = file.read().strip()
            os.environ['PHOENIX_CLIENT_HEADERS'] = api_key
    except:
        os.environ["PHOENIX_CLIENT_HEADERS"] = getpass.getpass("Enter your Arize Phoenix API key: ")

tracer_provider = register(
  project_name="demo", # Default is 'default'
  endpoint="https://app.phoenix.arize.com/v1/traces",
)
LangChainInstrumentor().instrument(tracer_provider=tracer_provider)