Comet

%pip install --upgrade --quiet  comet_ml langchain langchain-openai google-search-results spacy textstat pandas


!{sys.executable} -m spacy download en_core_web_sm

import comet_ml

comet_ml.init(project_name="comet-example-langchain")

import os

os.environ["OPENAI_API_KEY"] = "..."
# os.environ["OPENAI_ORGANIZATION"] = "..."
os.environ["SERPAPI_API_KEY"] = "..."

from langchain_community.callbacks import CometCallbackHandler
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_openai import OpenAI

comet_callback = CometCallbackHandler(
    project_name="comet-example-langchain",
    complexity_metrics=True,
    stream_logs=True,
    tags=["llm"],
    visualizations=["dep"],
)
callbacks = [StdOutCallbackHandler(), comet_callback]
llm = OpenAI(temperature=0.9, callbacks=callbacks, verbose=True)

llm_result = llm.generate(["Tell me a joke", "Tell me a poem", "Tell me a fact"] * 3)
print("LLM result", llm_result)
comet_callback.flush_tracker(llm, finish=True)

from langchain.chains import LLMChain
from langchain_community.callbacks import CometCallbackHandler
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

comet_callback = CometCallbackHandler(
    complexity_metrics=True,
    project_name="comet-example-langchain",
    stream_logs=True,
    tags=["synopsis-chain"],
)
callbacks = [StdOutCallbackHandler(), comet_callback]
llm = OpenAI(temperature=0.9, callbacks=callbacks)

template = """You are a playwright. Given the title of play, it is your job to write a synopsis for that title.
Title: {title}
Playwright: This is a synopsis for the above play:"""
prompt_template = PromptTemplate(input_variables=["title"], template=template)
synopsis_chain = LLMChain(llm=llm, prompt=prompt_template, callbacks=callbacks)

test_prompts = [{"title": "Documentary about Bigfoot in Paris"}]
print(synopsis_chain.apply(test_prompts))
comet_callback.flush_tracker(synopsis_chain, finish=True)

from langchain.agents import initialize_agent, load_tools
from langchain_community.callbacks import CometCallbackHandler
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_openai import OpenAI

comet_callback = CometCallbackHandler(
    project_name="comet-example-langchain",
    complexity_metrics=True,
    stream_logs=True,
    tags=["agent"],
)
callbacks = [StdOutCallbackHandler(), comet_callback]
llm = OpenAI(temperature=0.9, callbacks=callbacks)

tools = load_tools(["serpapi", "llm-math"], llm=llm, callbacks=callbacks)
agent = initialize_agent(
    tools,
    llm,
    agent="zero-shot-react-description",
    callbacks=callbacks,
    verbose=True,
)
agent.run(
    "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?"
)
comet_callback.flush_tracker(agent, finish=True)

%pip install --upgrade --quiet  rouge-score

from langchain.chains import LLMChain
from langchain_community.callbacks import CometCallbackHandler
from langchain_core.callbacks import StdOutCallbackHandler
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI
from rouge_score import rouge_scorer


class Rouge:
    def __init__(self, reference):
        self.reference = reference
        self.scorer = rouge_scorer.RougeScorer(["rougeLsum"], use_stemmer=True)

    def compute_metric(self, generation, prompt_idx, gen_idx):
        prediction = generation.text
        results = self.scorer.score(target=self.reference, prediction=prediction)

        return {
            "rougeLsum_score": results["rougeLsum"].fmeasure,
            "reference": self.reference,
        }


reference = """
The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building.
It was the first structure to reach a height of 300 metres.

It is now taller than the Chrysler Building in New York City by 5.2 metres (17 ft)
Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France .
"""
rouge_score = Rouge(reference=reference)

template = """Given the following article, it is your job to write a summary.
Article:
{article}
Summary: This is the summary for the above article:"""
prompt_template = PromptTemplate(input_variables=["article"], template=template)

comet_callback = CometCallbackHandler(
    project_name="comet-example-langchain",
    complexity_metrics=False,
    stream_logs=True,
    tags=["custom_metrics"],
    custom_metrics=rouge_score.compute_metric,
)
callbacks = [StdOutCallbackHandler(), comet_callback]
llm = OpenAI(temperature=0.9)

synopsis_chain = LLMChain(llm=llm, prompt=prompt_template)

test_prompts = [
    {
        "article": """
                 The tower is 324 metres (1,063 ft) tall, about the same height as
                 an 81-storey building, and the tallest structure in Paris. Its base is square,
                 measuring 125 metres (410 ft) on each side.
                 During its construction, the Eiffel Tower surpassed the
                 Washington Monument to become the tallest man-made structure in the world,
                 a title it held for 41 years until the Chrysler Building
                 in New York City was finished in 1930.

                 It was the first structure to reach a height of 300 metres.
                 Due to the addition of a broadcasting aerial at the top of the tower in 1957,
                 it is now taller than the Chrysler Building by 5.2 metres (17 ft).

                 Excluding transmitters, the Eiffel Tower is the second tallest
                 free-standing structure in France after the Millau Viaduct.
                 """
    }
]
print(synopsis_chain.apply(test_prompts, callbacks=callbacks))
comet_callback.flush_tracker(synopsis_chain, finish=True)

from langchain_community.callbacks.tracers.comet import CometTracer