From 9bcefb310c09af2cab66a4c96022d9800d14c14a Mon Sep 17 00:00:00 2001 From: Ismail Pelaseyed Date: Wed, 28 Feb 2024 18:44:05 -0800 Subject: [PATCH] Add support for querying code interpreter (#66) * Add support for queryig code interpreter * Fix formatting * Ensure the sandbox close is called on exceptions * Update service/code_interpreter.py Co-authored-by: Tomas Valenta * Update service/code_interpreter.py Co-authored-by: Tomas Valenta * Update service/router.py Co-authored-by: Tomas Valenta * Update service/code_interpreter.py Co-authored-by: Tomas Valenta * Add system prompt * Format code * Bump dependencies * Minor tweaks --------- Co-authored-by: Tomas Valenta --- README.md | 3 +- api/ingest.py | 2 +- models/ingest.py | 2 +- models/query.py | 1 + poetry.lock | 483 ++++++++++++++++++------------------ pyproject.toml | 2 +- service/code_interpreter.py | 102 ++++++-- service/embedding.py | 2 +- service/router.py | 41 +-- utils/file.py | 2 +- 10 files changed, 351 insertions(+), 289 deletions(-) diff --git a/README.md b/README.md index bb5f2f78..48e6dbd7 100644 --- a/README.md +++ b/README.md @@ -49,7 +49,8 @@ Input example: "encoder": { "type": "openai", "name": "text-embedding-3-small", - } + }, + "interpreter_mode": False, # Set to True if you wish to run computation Q&A with a code interpreter "session_id": "my_session_id" # keeps micro-vm sessions and enables caching } ``` diff --git a/api/ingest.py b/api/ingest.py index 4ddee16f..dda04f10 100644 --- a/api/ingest.py +++ b/api/ingest.py @@ -6,7 +6,7 @@ from models.ingest import RequestPayload from service.embedding import EmbeddingService, get_encoder -from service.ingest import handle_urls, handle_google_drive +from service.ingest import handle_google_drive, handle_urls from utils.summarise import SUMMARY_SUFFIX router = APIRouter() diff --git a/models/ingest.py b/models/ingest.py index 161ff5c1..b4ec62ac 100644 --- a/models/ingest.py +++ b/models/ingest.py @@ -4,8 +4,8 @@ from pydantic import BaseModel from models.file import File -from models.vector_database import VectorDatabase from models.google_drive import GoogleDrive +from models.vector_database import VectorDatabase class EncoderEnum(str, Enum): diff --git a/models/query.py b/models/query.py index a7dbfd04..13929277 100644 --- a/models/query.py +++ b/models/query.py @@ -12,6 +12,7 @@ class RequestPayload(BaseModel): index_name: str encoder: Encoder session_id: Optional[str] = None + interpreter_mode: Optional[bool] = False class ResponseData(BaseModel): diff --git a/poetry.lock b/poetry.lock index 53985cd1..b4112dde 100644 --- a/poetry.lock +++ b/poetry.lock @@ -325,13 +325,13 @@ uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "cachetools" -version = "5.3.2" +version = "5.3.3" description = "Extensible memoizing collections and decorators" optional = false python-versions = ">=3.7" files = [ - {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"}, - {file = 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(<=0.6.23)", "unstructured-inference (==0.7.23)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +astra = ["astrapy"] azure = ["adlfs", "fsspec"] azure-cognitive-search = ["azure-search-documents"] bedrock = ["boto3", "langchain-community"] @@ -4253,4 +4254,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.12" -content-hash = "ef6ccb56262679dfff8f47705c65fdd33086c1e5447c45fff577487ac4b504b3" +content-hash = "9fab773e0bb1d4a412cdf10a47ff271056bd99f8b0e76a9309b377c732c50e63" diff --git a/pyproject.toml b/pyproject.toml index 93e03dc8..c0783f2f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -28,7 +28,7 @@ cmake = "^3.28.1" pypdf = "^4.0.1" docx2txt = "^0.8" python-dotenv = "^1.0.1" -e2b = "^0.14.4" +e2b = "^0.14.7" gunicorn = "^21.2.0" unstructured-client = "^0.18.0" unstructured = {extras = ["google-drive"], version = "^0.12.4"} diff --git a/service/code_interpreter.py b/service/code_interpreter.py index 7c456fa5..56b2abc2 100644 --- a/service/code_interpreter.py +++ b/service/code_interpreter.py @@ -1,12 +1,23 @@ import asyncio import logging +import re +import textwrap import time from typing import List +import pandas as pd +from decouple import config from e2b import Sandbox +from openai import AsyncOpenAI logging.getLogger("e2b").setLevel(logging.INFO) +client = AsyncOpenAI( + api_key=config("OPENAI_API_KEY"), +) + +SYSTEM_PROMPT = "You are a world-class python programmer that can complete any data analysis tasks by coding." + class CodeInterpreterService: timeout = 3 * 60 # 3 minutes @@ -61,48 +72,87 @@ def __init__( self.sandbox = self._ensure_sandbox(session_id) async def __aenter__(self): - if not self._is_initialized: - self._is_initialized = True - for file_url in self.file_urls: - await self._upload_file(file_url) + try: + if not self._is_initialized: + self._is_initialized = True + for file_url in self.file_urls: + await self._upload_file(file_url) + except: + self.self.sandbox.close() + raise return self async def __aexit__(self, _exc_type, _exc_value, _traceback): - if self.session_id: - self.sandbox.keep_alive(self.timeout) - self.sandbox.close() + try: + if self.session_id: + self.sandbox.keep_alive(self.timeout) + finally: + self.sandbox.close() - def get_files_code(self): + def get_dataframe(self): """ Get the code to read the files in the sandbox. This can be used for instructing the LLM how to access the loaded files. """ - - # TODO: Add support for xslx, json - files_code = "\n".join( - f'df{i} = pd.read_csv("{self._get_file_path(url)}") # {url}' - for i, url in enumerate(self.file_urls) + # TODO: Add support for multiple dataframes + df = pd.read_csv(self.file_urls[0]) + return df, self.file_urls[0] + + def generate_prompt(self, query: str) -> str: + df, url = self.get_dataframe() + return textwrap.dedent( + f""" + You are provided with a following pandas dataframe (`df`): + {df.info()} + + Using the provided dataframe (`df`), update the following python code using pandas that returns the answer to question: \"{query}\" + + This is the initial python code to be updated: + + ```python + import pandas as pd + + df = pd.read_csv("{url}") + 1. Process: Manipulating data for analysis (grouping, filtering, aggregating, etc.) + 2. Analyze: Conducting the actual analysis + 3. Output: Returning the answer as a string + ``` + """ ) - return f""" -import pandas as pd + def extract_code(self, code: str) -> str: + pattern = r"```(?:python)?(.*?)```" + matches = re.findall(pattern, code, re.DOTALL) + if matches: + return matches[0].strip() + return "" -{files_code} - -""" + async def generate_code( + self, + query: str, + ) -> str: + content = self.generate_prompt(query=query) + completion = await client.chat.completions.create( + messages=[ + { + "role": "system", + "content": SYSTEM_PROMPT, + }, + { + "role": "user", + "content": content, + }, + ], + model="gpt-3.5-turbo-0125", + ) + output = completion.choices[0].message.content + return self.extract_code(code=output) async def run_python(self, code: str): - files_code = self.get_files_code() - - templated_code = f""" -{files_code} -{code} -""" - epoch_time = time.time() codefile_path = f"/tmp/main-{epoch_time}.py" - self.sandbox.filesystem.write(codefile_path, templated_code) + self.sandbox.filesystem.write(codefile_path, code) process = await asyncio.to_thread( self.sandbox.process.start_and_wait, f"python {codefile_path}", diff --git a/service/embedding.py b/service/embedding.py index 68e82ce9..70c7d2bf 100644 --- a/service/embedding.py +++ b/service/embedding.py @@ -21,9 +21,9 @@ from models.file import File from models.google_drive import GoogleDrive from models.ingest import Encoder, EncoderEnum +from utils.file import get_file_extension_from_url from utils.logger import logger from utils.summarise import completion -from utils.file import get_file_extension_from_url from vectordbs import get_vector_service diff --git a/service/router.py b/service/router.py index e2ff9560..964f613c 100644 --- a/service/router.py +++ b/service/router.py @@ -1,3 +1,5 @@ +from uuid import uuid4 + from decouple import config from semantic_router.encoders import CohereEncoder from semantic_router.layer import RouteLayer @@ -5,13 +7,14 @@ from models.document import BaseDocumentChunk from models.query import RequestPayload - -# from service.code_interpreter import CodeInterpreterService +from service.code_interpreter import CodeInterpreterService from service.embedding import get_encoder from utils.logger import logger from utils.summarise import SUMMARY_SUFFIX from vectordbs import BaseVectorDatabase, get_vector_service +STRUTURED_DATA = [".xlsx", ".csv", ".json"] + def create_route_layer() -> RouteLayer: routes = [ @@ -35,12 +38,29 @@ async def get_documents( *, vector_service: BaseVectorDatabase, payload: RequestPayload ) -> list[BaseDocumentChunk]: chunks = await vector_service.query(input=payload.input, top_k=5) - if not len(chunks): logger.error(f"No documents found for query: {payload.input}") return [] - - reranked_chunks = await vector_service.rerank(query=payload.input, documents=chunks) + is_structured = chunks[0].metadata.get("document_type") in STRUTURED_DATA + reranked_chunks = [] + if is_structured and payload.interpreter_mode: + async with CodeInterpreterService( + session_id=payload.session_id, file_urls=[chunks[0].metadata.get("doc_url")] + ) as service: + code = await service.generate_code(query=payload.input) + response = await service.run_python(code=code) + output = response.stdout + reranked_chunks.append( + BaseDocumentChunk( + id=str(uuid4()), + document_id=str(uuid4()), + content=output, + doc_url=chunks[0].metadata.get("doc_url"), + ) + ) + reranked_chunks.extend( + await vector_service.rerank(query=payload.input, documents=chunks) + ) return reranked_chunks @@ -63,15 +83,4 @@ async def query(payload: RequestPayload) -> list[BaseDocumentChunk]: encoder=encoder, ) - # async with CodeInterpreterService( - # session_id=payload.session_id, - # file_urls=[ - # "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv" - # ], - # ) as service: - # code = "df0.info()" - # output = await service.run_python(code=code) - # print(output.stderr) - # print(output.stdout) - return await get_documents(vector_service=vector_service, payload=payload) diff --git a/utils/file.py b/utils/file.py index 0802d33b..1634e80d 100644 --- a/utils/file.py +++ b/utils/file.py @@ -1,5 +1,5 @@ -from urllib.parse import urlparse import os +from urllib.parse import urlparse def get_file_extension_from_url(url: str) -> str: