From 680cfc055ec5f4b0b496cebccd680d84418168f8 Mon Sep 17 00:00:00 2001 From: Josh Bradley Date: Thu, 19 Sep 2024 01:09:26 -0400 Subject: [PATCH] Update frontend UI app (#174) Co-authored-by: dorbaker --- .devcontainer/devcontainer.json | 19 +- backend/manage-indexing-jobs.py | 1 + poetry.lock => backend/poetry.lock | 951 ++---- pyproject.toml => backend/pyproject.toml | 9 +- backend/src/api/index.py | 4 +- backend/src/main.py | 8 +- backend/src/tests/api/test_azure_clients.py | 1 + docker/Dockerfile-backend | 6 +- docker/Dockerfile-frontend | 6 +- frontend/app.py | 34 +- frontend/poetry.lock | 3109 +++++++++++++++++++ frontend/pyproject.toml | 55 + frontend/src/components/index_pipeline.py | 2 - frontend/src/components/login_sidebar.py | 4 +- frontend/src/components/query.py | 80 +- frontend/src/components/tabs.py | 21 +- frontend/src/enums.py | 10 +- frontend/src/functions.py | 8 +- frontend/src/graphrag_api.py | 29 +- 19 files changed, 3657 insertions(+), 700 deletions(-) rename poetry.lock => backend/poetry.lock (87%) rename pyproject.toml => backend/pyproject.toml (89%) create mode 100644 frontend/poetry.lock create mode 100644 frontend/pyproject.toml diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index 03ed2b5..f6e7c34 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -12,15 +12,16 @@ ], "remoteUser": "vscode", "remoteEnv": { - // We add the .venv to the beginning of the path env in the Dockerfile - // so that we use the proper python, however vscode rewrites/overwrites - // the PATH in the image and puts /usr/local/bin in front of our .venv - // path. This fixes that issue. - "PATH": "${containerEnv:PATH}", - // Add src folder to PYTHONPATH so that we can import modules that - // are in the source dir - "PYTHONPATH": "/graphrag-accelerator/backend/:$PATH" - }, + // We add the .venv to the beginning of the path env in the Dockerfile + // so that we use the proper python, however vscode rewrites/overwrites + // the PATH in the image and puts /usr/local/bin in front of our .venv + // path. This fixes that issue. + "PATH": "${containerEnv:PATH}", + // Add src folder to PYTHONPATH so that we can import modules that + // are in the source dir + "PYTHONPATH": "/graphrag-accelerator/backend/:$PATH", + "AZURE_CLI_DISABLE_CONNECTION_VERIFICATION": "1" + }, "mounts": [ // NOTE: we reference both HOME and USERPROFILE environment variables to simultaneously support both Windows and Unix environments // in most default situations, only one variable will exist (Windows has USERPROFILE and unix has HOME) and a reference to the other variable will result in an empty string diff --git a/backend/manage-indexing-jobs.py b/backend/manage-indexing-jobs.py index 97ccd40..7dffddb 100644 --- a/backend/manage-indexing-jobs.py +++ b/backend/manage-indexing-jobs.py @@ -16,6 +16,7 @@ from kubernetes import ( client, config, ) + from src.api.azure_clients import AzureStorageClientManager from src.api.common import sanitize_name from src.models import PipelineJob diff --git a/poetry.lock b/backend/poetry.lock similarity index 87% rename from poetry.lock rename to backend/poetry.lock index c7df51f..497b769 100644 --- a/poetry.lock +++ b/backend/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "adlfs" @@ -182,29 +182,6 @@ files = [ [package.dependencies] frozenlist = ">=1.1.0" -[[package]] -name = "altair" -version = "5.4.1" -description = "Vega-Altair: A declarative statistical visualization library for Python." -optional = false -python-versions = ">=3.8" -files = [ - {file = "altair-5.4.1-py3-none-any.whl", hash = "sha256:0fb130b8297a569d08991fb6fe763582e7569f8a04643bbd9212436e3be04aef"}, - {file = "altair-5.4.1.tar.gz", hash = "sha256:0ce8c2e66546cb327e5f2d7572ec0e7c6feece816203215613962f0ec1d76a82"}, -] - -[package.dependencies] -jinja2 = "*" -jsonschema = ">=3.0" -narwhals = ">=1.5.2" -packaging = "*" -typing-extensions = {version = ">=4.10.0", markers = "python_version < \"3.13\""} - -[package.extras] -all = ["altair-tiles (>=0.3.0)", "anywidget (>=0.9.0)", "numpy", "pandas (>=0.25.3)", "pyarrow (>=11)", "vega-datasets (>=0.9.0)", "vegafusion[embed] (>=1.6.6)", "vl-convert-python (>=1.6.0)"] -dev = ["geopandas", "hatch", "ibis-framework[polars]", "ipython[kernel]", "mistune", "mypy", "pandas (>=0.25.3)", "pandas-stubs", "polars (>=0.20.3)", "pytest", "pytest-cov", "pytest-xdist[psutil] (>=3.5,<4.0)", "ruff (>=0.6.0)", "types-jsonschema", "types-setuptools"] -doc = ["docutils", "jinja2", "myst-parser", "numpydoc", "pillow (>=9,<10)", "pydata-sphinx-theme (>=0.14.1)", "scipy", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinxext-altair"] - [[package]] name = "annotated-types" version = "0.7.0" @@ -442,13 +419,13 @@ files = [ [[package]] name = "azure-core" -version = "1.30.2" +version = "1.31.0" description = "Microsoft Azure Core Library for Python" optional = false python-versions = ">=3.8" files = [ - {file = "azure-core-1.30.2.tar.gz", hash = "sha256:a14dc210efcd608821aa472d9fb8e8d035d29b68993819147bc290a8ac224472"}, - {file = "azure_core-1.30.2-py3-none-any.whl", hash = "sha256:cf019c1ca832e96274ae85abd3d9f752397194d9fea3b41487290562ac8abe4a"}, + {file = "azure_core-1.31.0-py3-none-any.whl", hash = "sha256:22954de3777e0250029360ef31d80448ef1be13b80a459bff80ba7073379e2cd"}, + {file = "azure_core-1.31.0.tar.gz", hash = "sha256:656a0dd61e1869b1506b7c6a3b31d62f15984b1a573d6326f6aa2f3e4123284b"}, ] [package.dependencies] @@ -527,23 +504,23 @@ typing-extensions = ">=4.6.0" [[package]] name = "azure-storage-blob" -version = "12.22.0" +version = "12.23.0" description = "Microsoft Azure Blob Storage Client Library for Python" optional = false python-versions = ">=3.8" files = [ - {file = "azure-storage-blob-12.22.0.tar.gz", hash = "sha256:b3804bb4fe8ab1c32771fa464053da772a682c2737b19da438a3f4e5e3b3736e"}, - {file = "azure_storage_blob-12.22.0-py3-none-any.whl", hash = "sha256:bb7d2d824ce3f11f14a27ee7d9281289f7e072ac8311c52e3652672455b7d5e8"}, + {file = "azure_storage_blob-12.23.0-py3-none-any.whl", hash = "sha256:8ac4b34624ed075eda1e38f0c6dadb601e1b199e27a09aa63edc429bf4a23329"}, + {file = "azure_storage_blob-12.23.0.tar.gz", hash = "sha256:2fadbceda1d99c4a72dfd32e0122d7bca8b5e8d2563f5c624d634aeaff49c9df"}, ] [package.dependencies] -azure-core = ">=1.28.0" +azure-core = ">=1.30.0" cryptography = ">=2.1.4" isodate = ">=0.6.1" typing-extensions = ">=4.6.0" [package.extras] -aio = ["azure-core[aio] (>=1.28.0)"] +aio = ["azure-core[aio] (>=1.30.0)"] [[package]] name = "babel" @@ -616,17 +593,6 @@ webencodings = "*" [package.extras] css = ["tinycss2 (>=1.1.0,<1.3)"] -[[package]] -name = "blinker" -version = "1.8.2" -description = "Fast, simple object-to-object and broadcast signaling" -optional = false -python-versions = ">=3.8" -files = [ - {file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"}, - {file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"}, -] - [[package]] name = "cachetools" version = "5.5.0" @@ -1153,13 +1119,13 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"] [[package]] name = "dask" -version = "2024.8.2" +version = "2024.9.0" description = "Parallel PyData with Task Scheduling" optional = false python-versions = ">=3.10" files = [ - {file = "dask-2024.8.2-py3-none-any.whl", hash = "sha256:484c317ee870140dbeccc759a91fd98821bba98d71a43eda7856fc9e859b03a1"}, - {file = "dask-2024.8.2.tar.gz", hash = "sha256:1d05e09166ac7927a54401e998aa1599e86aac666edbdaeb3096bf4b957029e0"}, + {file = "dask-2024.9.0-py3-none-any.whl", hash = "sha256:ceede9cfd418178a01ec3d11a0cde3f46678bd4a292ba84b57bbb401ce3f1cb8"}, + {file = "dask-2024.9.0.tar.gz", hash = "sha256:bfbe5b6c3b7937426539be27029800178ce63cea4da8d7e7de836a98384aa1d6"}, ] [package.dependencies] @@ -1179,23 +1145,23 @@ toolz = ">=0.10.0" array = ["numpy (>=1.24)"] complete = ["dask[array,dataframe,diagnostics,distributed]", "lz4 (>=4.3.2)", "pyarrow (>=14.0.1)"] dataframe = ["dask-expr (>=1.1,<1.2)", "dask[array]", "pandas (>=2.0)"] -diagnostics = ["bokeh (>=2.4.2)", "jinja2 (>=2.10.3)"] -distributed = ["distributed (==2024.8.2)"] +diagnostics = ["bokeh (>=3.1.0)", "jinja2 (>=2.10.3)"] +distributed = ["distributed (==2024.9.0)"] test = ["pandas[test]", "pre-commit", "pytest", "pytest-cov", "pytest-rerunfailures", "pytest-timeout", "pytest-xdist"] [[package]] name = "dask-expr" -version = "1.1.13" +version = "1.1.14" description = "High Level Expressions for Dask" optional = false python-versions = ">=3.10" files = [ - {file = "dask_expr-1.1.13-py3-none-any.whl", hash = "sha256:0a68a8d18cae72b172ee3afc3f33253f065becbf8fbf9f3ee43e665ec5499112"}, - {file = "dask_expr-1.1.13.tar.gz", hash = "sha256:7e00b2c6538e6c633e22db262abfe3aeb6dc65c1de4a8eadcb2bbf44ad8729da"}, + {file = "dask_expr-1.1.14-py3-none-any.whl", hash = "sha256:86a59c51a84d88b6a653f5b4e2c578213a349a963206dcd29219e4826560ada2"}, + {file = "dask_expr-1.1.14.tar.gz", hash = "sha256:c67c0c190d933e253f85674da71615f23ed8ba08f3abcc0cd160080643feb40a"}, ] [package.dependencies] -dask = "2024.8.2" +dask = "2024.9.0" pandas = ">=2" pyarrow = ">=14.0.1" @@ -1404,13 +1370,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "fastapi" -version = "0.114.1" +version = "0.115.0" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" optional = false python-versions = ">=3.8" files = [ - {file = "fastapi-0.114.1-py3-none-any.whl", hash = "sha256:5d4746f6e4b7dff0b4f6b6c6d5445645285f662fe75886e99af7ee2d6b58bb3e"}, - {file = "fastapi-0.114.1.tar.gz", hash = "sha256:1d7bbbeabbaae0acb0c22f0ab0b040f642d3093ca3645f8c876b6f91391861d8"}, + {file = "fastapi-0.115.0-py3-none-any.whl", hash = "sha256:17ea427674467486e997206a5ab25760f6b09e069f099b96f5b55a32fb6f1631"}, + {file = "fastapi-0.115.0.tar.gz", hash = "sha256:f93b4ca3529a8ebc6fc3fcf710e5efa8de3df9b41570958abf1d97d843138004"}, ] [package.dependencies] @@ -1489,18 +1455,18 @@ lzo = ["python-lzo"] [[package]] name = "filelock" -version = "3.16.0" +version = "3.16.1" description = "A platform independent file lock." optional = false python-versions = ">=3.8" files = [ - {file = "filelock-3.16.0-py3-none-any.whl", hash = "sha256:f6ed4c963184f4c84dd5557ce8fece759a3724b37b80c6c4f20a2f63a4dc6609"}, - {file = "filelock-3.16.0.tar.gz", hash = "sha256:81de9eb8453c769b63369f87f11131a7ab04e367f8d97ad39dc230daa07e3bec"}, + {file = "filelock-3.16.1-py3-none-any.whl", hash = "sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0"}, + {file = "filelock-3.16.1.tar.gz", hash = "sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435"}, ] [package.extras] -docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"] -testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.1.1)", "pytest (>=8.3.2)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.3)"] +docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints 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version = "2.19.2" @@ -2034,13 +1968,13 @@ scipy = ">=1.4.0" [[package]] name = "identify" -version = "2.6.0" +version = "2.6.1" description = "File identification library for Python" optional = false python-versions = ">=3.8" files = [ - {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"}, - {file = "identify-2.6.0.tar.gz", hash = "sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf"}, + {file = "identify-2.6.1-py2.py3-none-any.whl", hash = "sha256:53863bcac7caf8d2ed85bd20312ea5dcfc22226800f6d6881f232d861db5a8f0"}, + {file = "identify-2.6.1.tar.gz", hash = "sha256:91478c5fb7c3aac5ff7bf9b4344f803843dc586832d5f110d672b19aa1984c98"}, ] [package.extras] @@ -2048,33 +1982,40 @@ license = ["ukkonen"] [[package]] name = "idna" -version = "3.8" +version = "3.10" description = "Internationalized Domain Names in Applications (IDNA)" optional = false python-versions = ">=3.6" files = [ - {file = 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"Chris Sanchez ", - "Katy Smith ", "Shane Solomon ", ] readme = "README.md" @@ -33,7 +32,7 @@ pytest = ">=8.2.1" wikipedia = ">=1.4.0" [tool.poetry.group.backend.dependencies] -adlfs = ">=2023.10.0" +adlfs = ">=2024.7.0" applicationinsights = ">=0.11.10" attrs = ">=23.2.0" azure-core = ">=1.30.1" @@ -66,12 +65,6 @@ tiktoken = ">=0.6.0" uvicorn = ">=0.23.2" urllib3 = ">=2.2.2" -[tool.poetry.group.frontend.dependencies] -python-dotenv = ">=0.19.1" -requests = "*" -streamlit = ">=0.88.0" -streamlit-nested-layout = "==0.1.3" - [tool.ruff] target-version = "py310" line-length = 88 diff --git a/backend/src/api/index.py b/backend/src/api/index.py index 98d0717..ee049be 100644 --- a/backend/src/api/index.py +++ b/backend/src/api/index.py @@ -127,7 +127,9 @@ async def setup_indexing_pipeline( ) # if indexing job is in a failed state, delete the associated K8s job and pod to allow for a new job to be scheduled if PipelineJobState(existing_job.status) == PipelineJobState.FAILED: - _delete_k8s_job(f"indexing-job-{sanitized_index_name}", os.environ["AKS_NAMESPACE"]) + _delete_k8s_job( + f"indexing-job-{sanitized_index_name}", os.environ["AKS_NAMESPACE"] + ) # reset the pipeline job details existing_job._status = PipelineJobState.SCHEDULED existing_job._percent_complete = 0 diff --git a/backend/src/main.py b/backend/src/main.py index ab1c240..5ce50e3 100644 --- a/backend/src/main.py +++ b/backend/src/main.py @@ -68,11 +68,15 @@ async def lifespan(app: FastAPI): ] = pod.spec.service_account_name # retrieve list of existing cronjobs batch_v1 = client.BatchV1Api() - namespace_cronjobs = batch_v1.list_namespaced_cron_job(namespace=os.environ["AKS_NAMESPACE"]) + namespace_cronjobs = batch_v1.list_namespaced_cron_job( + namespace=os.environ["AKS_NAMESPACE"] + ) cronjob_names = [cronjob.metadata.name for cronjob in namespace_cronjobs.items] # create cronjob if it does not exist if manifest["metadata"]["name"] not in cronjob_names: - batch_v1.create_namespaced_cron_job(namespace=os.environ["AKS_NAMESPACE"], body=manifest) + batch_v1.create_namespaced_cron_job( + namespace=os.environ["AKS_NAMESPACE"], body=manifest + ) except Exception as e: print("Failed to create graphrag cronjob.") reporter = ReporterSingleton().get_instance() diff --git a/backend/src/tests/api/test_azure_clients.py b/backend/src/tests/api/test_azure_clients.py index ea96231..8b53d7c 100644 --- a/backend/src/tests/api/test_azure_clients.py +++ b/backend/src/tests/api/test_azure_clients.py @@ -10,6 +10,7 @@ from azure.cosmos import ( ) from azure.storage.blob import BlobServiceClient from azure.storage.blob.aio import BlobServiceClient as BlobServiceClientAsync + from src.api.azure_clients import AzureStorageClientManager diff --git a/docker/Dockerfile-backend b/docker/Dockerfile-backend index 2dbd850..938473b 100644 --- a/docker/Dockerfile-backend +++ b/docker/Dockerfile-backend @@ -11,11 +11,11 @@ ENV PIP_DISABLE_PIP_VERSION_CHECK=1 ENV SETUPTOOLS_USE_DISTUTILS=stdlib ENV PYTHONPATH=/backend -COPY poetry.lock pyproject.toml / COPY backend /backend -RUN pip install poetry \ +RUN cd backend \ + && pip install poetry \ && poetry config virtualenvs.create false \ - && poetry install --without frontend + && poetry install # download all nltk data that graphrag requires RUN python -m nltk.downloader punkt averaged_perceptron_tagger maxent_ne_chunker words wordnet diff --git a/docker/Dockerfile-frontend b/docker/Dockerfile-frontend index 08c8ab1..2e525e1 100644 --- a/docker/Dockerfile-frontend +++ b/docker/Dockerfile-frontend @@ -7,11 +7,11 @@ ENV PIP_ROOT_USER_ACTION=ignore ENV PIP_DISABLE_PIP_VERSION_CHECK=1 ENV SETUPTOOLS_USE_DISTUTILS=stdlib -COPY poetry.lock pyproject.toml / COPY frontend /frontend -RUN pip install poetry \ +RUN cd frontend \ + && pip install poetry \ && poetry config virtualenvs.create false \ - && poetry install --without backend + && poetry install WORKDIR /frontend EXPOSE 8080 diff --git a/frontend/app.py b/frontend/app.py index efc7d92..a8979db 100644 --- a/frontend/app.py +++ b/frontend/app.py @@ -4,6 +4,7 @@ import os import streamlit as st + from src.components import tabs from src.components.index_pipeline import IndexPipeline from src.enums import EnvVars @@ -16,29 +17,28 @@ st.session_state["initialized"] = True if initialized else False def graphrag_app(initialized: bool): - # main entry point for app interface st.title("Microsoft GraphRAG Copilot") - main_tab, prompt_gen_tab, prompt_edit_tab, index_tab, query_tab = st.tabs( - [ - "**Intro**", - "**1. Prompt Generation**", - "**2. Prompt Configuration**", - "**3. Index**", - "**4. Query**", - ] - ) + main_tab, prompt_gen_tab, prompt_edit_tab, index_tab, query_tab = st.tabs([ + "**Intro**", + "**1. Prompt Generation**", + "**2. Prompt Configuration**", + "**3. Index**", + "**4. Query**", + ]) + # display only the main tab if a connection to an existing APIM has not been initialized with main_tab: tabs.get_main_tab(initialized) - - # if not initialized, only main tab is displayed if initialized: - # assign API request information + # setup API request information COLUMN_WIDTHS = [0.275, 0.45, 0.275] - api_url = st.session_state[EnvVars.DEPLOYMENT_URL.value] + apim_url = st.session_state[EnvVars.DEPLOYMENT_URL.value] apim_key = st.session_state[EnvVars.APIM_SUBSCRIPTION_KEY.value] - client = GraphragAPI(api_url, apim_key) + # perform health check to verify connectivity + client = GraphragAPI(apim_url, apim_key) + if not client.health_check_passed(): + st.error("APIM Connection Error") + st.stop() indexPipe = IndexPipeline(client, COLUMN_WIDTHS) - # display tabs with prompt_gen_tab: tabs.get_prompt_generation_tab(client, COLUMN_WIDTHS) @@ -48,9 +48,7 @@ def graphrag_app(initialized: bool): tabs.get_index_tab(indexPipe) with query_tab: tabs.get_query_tab(client) - deployer_email = os.getenv("DEPLOYER_EMAIL", "deployer@email.com") - footer = f"""

Responses may be inaccurate; please review all responses for accuracy. Learn more about Azure OpenAI code of conduct here.
For feedback, email us at {deployer_email}.

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+flake8 = ">=6.1.0" +ipython = "*" +jupyter = "*" +pre-commit = ">=3.6.0" +ruff = ">=0.1.13" + +[tool.poetry.group.test.dependencies] +pytest = ">=8.2.1" +wikipedia = ">=1.4.0" + +[tool.poetry.group.frontend.dependencies] +requests = "*" +streamlit = ">=1.38.0" +streamlit-nested-layout = "*" + +[tool.ruff] +target-version = "py310" +line-length = 88 +indent-width = 4 + +[tool.ruff.format] +preview = true +quote-style = "double" + +[tool.ruff.lint] +preview = true +select = ["E", "F", "I"] +ignore = ["E402", "E501", "F821"] + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/frontend/src/components/index_pipeline.py b/frontend/src/components/index_pipeline.py index 88292b1..f51d088 100644 --- a/frontend/src/components/index_pipeline.py +++ b/frontend/src/components/index_pipeline.py @@ -50,7 +50,6 @@ class IndexPipeline: key_prefix="index", disable_other_input=disable_other_input, ) - if select_storage_name != "": disable_other_input = True @@ -138,7 +137,6 @@ class IndexPipeline: divider=True, help="Select an index to check the status of what stage indexing is in. Indexing must be complete in order to be able to execute queries.", ) - options_indexes = self.client.get_index_names() # create logic for defaulting to running job index if one exists new_index_name = st.session_state["index-name-input"] diff --git a/frontend/src/components/login_sidebar.py b/frontend/src/components/login_sidebar.py index 5bdbff5..f0315eb 100644 --- a/frontend/src/components/login_sidebar.py +++ b/frontend/src/components/login_sidebar.py @@ -26,8 +26,7 @@ def login(): form_submit = st.form_submit_button("Login") if form_submit: client = GraphragAPI(apim_url, apim_sub_key) - status_code = client.health_check() - if status_code == 200: + if client.health_check_passed(): st.success("Login Successful") st.session_state[EnvVars.DEPLOYMENT_URL.value] = apim_url st.session_state[EnvVars.APIM_SUBSCRIPTION_KEY.value] = apim_sub_key @@ -36,4 +35,3 @@ def login(): else: st.error("Login Failed") st.error("Please check the APIM Gateway URL and Subscription Key") - return status_code diff --git a/frontend/src/components/query.py b/frontend/src/components/query.py index ec5aa5b..5486a34 100644 --- a/frontend/src/components/query.py +++ b/frontend/src/components/query.py @@ -20,7 +20,7 @@ class GraphQuery: def search( self, - query_type: Literal["Global Streaming", "Global", "Local"], + query_type: Literal["Global Streaming", "Local Streaming", "Global", "Local"], search_index: str | list[str], query: str, ) -> None: @@ -51,6 +51,8 @@ class GraphQuery: match query_type: case "Global Streaming": _ = self.global_streaming_search(search_index, query) + case "Local Streaming": + _ = self.local_streaming_search(search_index, query) case "Global": _ = self.global_search(search_index, query) case "Local": @@ -109,7 +111,73 @@ class GraphQuery: "Double-click on content to expand text", "red", False ) ) - self._build_st_dataframe(context_list) + self._build_st_dataframe( + context_list[0]["reports"], drop_columns=[] + ) + else: + print(query_response.reason, query_response.content) + raise Exception("Received unexpected response from server") + + def local_streaming_search(self, search_index: str | list[str], query: str) -> None: + """ + Executes a local streaming query on the specified index. + Handles the response and displays the results in the Streamlit app. + """ + query_response = self.client.local_streaming_query(search_index, query) + assistant_response = "" + context_list = [] + + if query_response.status_code == 200: + text_placeholder = st.empty() + for chunk in query_response.iter_lines( + # allow up to 256KB to avoid excessive many reads + chunk_size=256 * GraphQuery.KILOBYTE, + decode_unicode=True, + ): + try: + payload = json.loads(chunk) + except json.JSONDecodeError as e: + # In the event that a chunk is not a complete JSON object, + # document it for further analysis. + print(chunk) + raise e + + token = payload["token"] + context = payload["context"] + if (token != "") and (context is None): + assistant_response += token + text_placeholder.write(assistant_response) + elif (token == "") and (context is not None): + context_list.append(context) + + if not assistant_response: + st.write( + self.format_md_text( + "Not enough contextual data to support your query: No results found.\tTry another query.", + "red", + True, + ) + ) + return + else: + with self._create_section_expander("Query Context"): + st.write( + self.format_md_text( + "Double-click on content to expand text", "red", False + ) + ) + self._build_st_dataframe( + context_list[0]["reports"], drop_columns=[] + ) + self._build_st_dataframe( + context_list[0]["entities"], drop_columns=[] + ) + self._build_st_dataframe( + context_list[0]["relationships"], drop_columns=[] + ) + self._build_st_dataframe( + context_list[0]["sources"], drop_columns=[] + ) else: print(query_response.reason, query_response.content) raise Exception("Received unexpected response from server") @@ -216,14 +284,12 @@ class GraphQuery: drop_columns: list[str] = ["id", "index_id", "index_name", "in_context"], entity_df: bool = False, rel_df: bool = False, - ) -> st.dataframe: + ) -> st.dataframe: # type: ignore df_context = ( data if isinstance(data, pd.DataFrame) else pd.DataFrame.from_records(data) ) if any(drop_columns): - for column in drop_columns: - if column in df_context.columns: - df_context = df_context.drop(column, axis=1) + df_context.drop(columns=drop_columns, inplace=True, axis=1, errors="ignore") if entity_df: return st.dataframe( df_context, @@ -267,7 +333,7 @@ class GraphQuery: def _create_section_expander( self, title: str, color: str = "blue", bold: bool = True, expanded: bool = False - ) -> st.expander: + ) -> st.expander: # type: ignore """ Creates an expander in the Streamlit app with the specified title and content. """ diff --git a/frontend/src/components/tabs.py b/frontend/src/components/tabs.py index a4b0335..e225d52 100644 --- a/frontend/src/components/tabs.py +++ b/frontend/src/components/tabs.py @@ -63,8 +63,6 @@ def get_prompt_generation_tab( """ Displays content of Prompt Generation Tab """ - # hard set limit to 5 files to reduce overly long processing times and to reduce over sampling errors. - num_chunks = num_chunks if num_chunks <= 5 else 5 _, col2, _ = st.columns(column_widths) with col2: st.header( @@ -133,24 +131,10 @@ def get_prompt_generation_tab( "Prompts generated successfully! Move on to the next tab to configure the prompts." ) else: - # assume limit parameter is too high + # limit parameter was too high st.warning( "You do not have enough data to generate prompts. Retrying with a smaller sample size." ) - while num_chunks > 1: - num_chunks -= 1 - generated = generate_and_extract_prompts( - client=client, - storage_name=select_prompt_storage, - limit=num_chunks, - ) - if not isinstance(generated, Exception): - st.success( - "Prompts generated successfully! Move on to the next tab to configure the prompts." - ) - break - else: - st.warning(f"Retrying with sample size: {num_chunks}") def get_prompt_configuration_tab( @@ -237,7 +221,7 @@ def get_query_tab(client: GraphragAPI) -> None: with col1: query_type = st.selectbox( "Query Type", - ["Global Streaming", "Global", "Local"], + ["Global Streaming", "Local Streaming", "Global", "Local"], help="Select the query type - Each yeilds different results of specificity. Global queries focus on the entire graph structure. Local queries focus on a set of communities (subgraphs) in the graph that are more connected to each other than they are to the rest of the graph structure and can focus on very specific entities in the graph. Global streaming is a global query that displays results as they appear live.", ) with col2: @@ -253,7 +237,6 @@ def get_query_tab(client: GraphragAPI) -> None: disabled = True if not any(select_index_search) else False col3, col4 = st.columns([0.8, 0.2]) - with col3: search_bar = st.text_input("Query", key="search-query", disabled=disabled) with col4: diff --git a/frontend/src/enums.py b/frontend/src/enums.py index a08cbaa..b83c674 100644 --- a/frontend/src/enums.py +++ b/frontend/src/enums.py @@ -4,30 +4,30 @@ from enum import Enum -class PromptKeys(Enum): +class PromptKeys(str, Enum): ENTITY = "entity_extraction" SUMMARY = "summarize_descriptions" COMMUNITY = "community_report" -class PromptFileNames(Enum): +class PromptFileNames(str, Enum): ENTITY = "entity_extraction_prompt.txt" SUMMARY = "summarize_descriptions_prompt.txt" COMMUNITY = "community_report_prompt.txt" -class PromptTextAreas(Enum): +class PromptTextAreas(str, Enum): ENTITY = "entity_text_area" SUMMARY = "summary_text_area" COMMUNITY = "community_text_area" -class StorageIndexVars(Enum): +class StorageIndexVars(str, Enum): SELECTED_STORAGE = "selected_storage" INPUT_STORAGE = "input_storage" SELECTED_INDEX = "selected_index" -class EnvVars(Enum): +class EnvVars(str, Enum): APIM_SUBSCRIPTION_KEY = "APIM_SUBSCRIPTION_KEY" DEPLOYMENT_URL = "DEPLOYMENT_URL" diff --git a/frontend/src/functions.py b/frontend/src/functions.py index 8c93bc3..6ca45bf 100644 --- a/frontend/src/functions.py +++ b/frontend/src/functions.py @@ -7,7 +7,6 @@ from typing import Optional from zipfile import ZipFile import streamlit as st -from dotenv import find_dotenv, load_dotenv from src.enums import EnvVars, PromptKeys, StorageIndexVars from src.graphrag_api import GraphragAPI @@ -17,7 +16,7 @@ This module contains functions that are used across the Streamlit app. """ -def initialize_app(env_file: str = ".env", css_file: str = "style.css") -> bool: +def initialize_app(css_file: str = "style.css") -> bool: """ Initialize the Streamlit app with the necessary configurations. """ @@ -31,10 +30,7 @@ def initialize_app(env_file: str = ".env", css_file: str = "style.css") -> bool: # initialize session state variables set_session_state_variables() - # load environment variables - _ = load_dotenv(find_dotenv(filename=env_file) or None, override=True) - - # either load from .env file or from session state + # load settings from environment variables st.session_state[EnvVars.APIM_SUBSCRIPTION_KEY.value] = os.getenv( EnvVars.APIM_SUBSCRIPTION_KEY.value, st.session_state[EnvVars.APIM_SUBSCRIPTION_KEY.value], diff --git a/frontend/src/graphrag_api.py b/frontend/src/graphrag_api.py index ce08e2b..f18e6e4 100644 --- a/frontend/src/graphrag_api.py +++ b/frontend/src/graphrag_api.py @@ -131,17 +131,16 @@ class GraphragAPI: except Exception as e: print(f"Error: {str(e)}") - def health_check(self) -> int | Response: + def health_check_passed(self) -> bool: """ Check the health of the APIM endpoint. """ url = self.api_url + "/health" try: response = requests.get(url, headers=self.headers) - return response.status_code - except Exception as e: - print(f"Error: {str(e)}") - return e + return response.ok + except Exception: + return False def query_index(self, index_name: str | list[str], query_type: str, query: str): """ @@ -174,7 +173,25 @@ class GraphragAPI: """ Returns a streaming response object for a global query. """ - url = f"{self.api_url}/experimental/query/global/streaming" + url = f"{self.api_url}/query/streaming/global" + try: + query_response = requests.post( + url, + json={"index_name": index_name, "query": query}, + headers=self.headers, + stream=True, + ) + return query_response + except Exception as e: + print(f"Error: {str(e)}") + + def local_streaming_query( + self, index_name: str | list[str], query: str + ) -> Response | None: + """ + Returns a streaming response object for a global query. + """ + url = f"{self.api_url}/query/streaming/local" try: query_response = requests.post( url,