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fix: Update broken imports on tracing and analysis example #2672

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Mar 22, 2024
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fix: Update broken imports on tracing and analysis example #2672

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48 changes: 23 additions & 25 deletions tutorials/llm_application_tracing_evaluating_and_analysis.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -46,26 +46,32 @@
"metadata": {},
"outputs": [],
"source": [
"!pip install -qq \"arize-phoenix[experimental,llama-index]\" \"openai>=1\" gcsfs nest_asyncio\n",
"\n",
"# Import Statements\n",
"!pip install -qq \"arize-phoenix[evals,llama-index]\" \"openai>=1\" gcsfs nest_asyncio llama-index-llms-openai"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"from getpass import getpass\n",
"from typing import List, cast\n",
"from urllib.request import urlopen\n",
"\n",
"import pandas as pd\n",
"import phoenix as px\n",
"import requests\n",
"from gcsfs import GCSFileSystem\n",
"from llama_index import (\n",
"from llama_index.core import (\n",
" ServiceContext,\n",
" StorageContext,\n",
" load_index_from_storage,\n",
" set_global_handler,\n",
")\n",
"from llama_index.embeddings import OpenAIEmbedding\n",
"from llama_index.graph_stores.simple import SimpleGraphStore\n",
"from llama_index.llms import OpenAI\n",
"from llama_index.embeddings.openai import OpenAIEmbedding\n",
"from llama_index.core.graph_stores import SimpleGraphStore\n",
"from llama_index.llms.openai import OpenAI\n",
"from phoenix import TraceDataset\n",
"from phoenix.trace import DocumentEvaluations, SpanEvaluations\n",
"from phoenix.trace.utils import json_lines_to_df\n",
Expand All @@ -85,18 +91,10 @@
"qa_correctness_eval_url = \"https://storage.googleapis.com/arize-phoenix-assets/datasets/unstructured/llm/context-retrieval/qa_correctness_eval.parquet\"\n",
"retrieved_documents_eval_url = \"https://storage.googleapis.com/arize-phoenix-assets/datasets/unstructured/llm/context-retrieval/retrieved_documents_eval.parquet\"\n",
"\n",
"response = requests.get(trace_jsonl_url)\n",
"\n",
"if response.status_code == 200:\n",
" with open(\"trace.jsonl\", \"wb\") as f:\n",
" f.write(response.content)\n",
" json_lines = []\n",
" with open(\"trace.jsonl\", \"r\") as f:\n",
" json_lines = cast(List[str], f.readlines())\n",
" trace_ds = TraceDataset(json_lines_to_df(json_lines))\n",
" px.launch_app(trace=trace_ds)\n",
"else:\n",
" print(f\"Failed to download the file. Status code: {response.status_code}\")\n",
"with urlopen(trace_jsonl_url) as response:\n",
" lines = [line.decode(\"utf-8\") for line in response.readlines()]\n",
"trace_ds = TraceDataset(json_lines_to_df(lines))\n",
"px.launch_app(trace=trace_ds)\n",
"\n",
"hallucination_eval_df = pd.read_parquet(hallucination_eval_url)\n",
"qa_correctness_eval_df = pd.read_parquet(qa_correctness_eval_url)\n",
Expand Down Expand Up @@ -244,7 +242,7 @@
"# Generating the Hallucination & Q&A Eval\n",
"\n",
"import nest_asyncio\n",
"from phoenix.experimental.evals import (\n",
"from phoenix.evals import (\n",
" HALLUCINATION_PROMPT_RAILS_MAP,\n",
" HALLUCINATION_PROMPT_TEMPLATE,\n",
" QA_PROMPT_RAILS_MAP,\n",
Expand All @@ -258,7 +256,7 @@
"# Creating Hallucination Eval which checks if the application hallucinated\n",
"hallucination_eval = llm_classify(\n",
" dataframe=queries_df,\n",
" model=OpenAIModel(\"gpt-4\", temperature=0.0),\n",
" model=OpenAIModel(model=\"gpt-4\", temperature=0.0),\n",
" template=HALLUCINATION_PROMPT_TEMPLATE,\n",
" rails=list(HALLUCINATION_PROMPT_RAILS_MAP.values()),\n",
" provide_explanation=True, # Makes the LLM explain its reasoning\n",
Expand All @@ -271,7 +269,7 @@
"# Creating Q&A Eval which checks if the application answered the question correctly\n",
"qa_correctness_eval = llm_classify(\n",
" dataframe=queries_df,\n",
" model=OpenAIModel(\"gpt-4\", temperature=0.0),\n",
" model=OpenAIModel(model=\"gpt-4\", temperature=0.0),\n",
" template=QA_PROMPT_TEMPLATE,\n",
" rails=list(QA_PROMPT_RAILS_MAP.values()),\n",
" provide_explanation=True, # Makes the LLM explain its reasoning\n",
Expand Down Expand Up @@ -326,7 +324,7 @@
"source": [
"# Generating Retrieval Relevance Eval\n",
"\n",
"from phoenix.experimental.evals import (\n",
"from phoenix.evals import (\n",
" RAG_RELEVANCY_PROMPT_RAILS_MAP,\n",
" RAG_RELEVANCY_PROMPT_TEMPLATE,\n",
" OpenAIModel,\n",
Expand All @@ -335,7 +333,7 @@
"\n",
"retrieved_documents_eval = llm_classify(\n",
" dataframe=retrieved_documents_df,\n",
" model=OpenAIModel(\"gpt-4\", temperature=0.0),\n",
" model=OpenAIModel(model=\"gpt-4\", temperature=0.0),\n",
" template=RAG_RELEVANCY_PROMPT_TEMPLATE,\n",
" rails=list(RAG_RELEVANCY_PROMPT_RAILS_MAP.values()),\n",
" provide_explanation=True,\n",
Expand Down
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