feat: update code-graph notebook

This commit is contained in:
Boris Arzentar 2024-12-03 23:48:12 +01:00
parent dd423ebc3d
commit d49ab4c3b5
6 changed files with 419 additions and 92 deletions

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@ -1,9 +1,9 @@
from functools import lru_cache
# from functools import lru_cache
from .config import get_relational_config
from .create_relational_engine import create_relational_engine
@lru_cache
# @lru_cache
def get_relational_engine():
relational_config = get_relational_config()

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@ -1,4 +1,6 @@
import asyncio
import logging
import math
from typing import List, Optional
import litellm
from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine
@ -36,11 +38,26 @@ class LiteLLMEmbeddingEngine(EmbeddingEngine):
api_base = self.endpoint,
api_version = self.api_version
)
except litellm.exceptions.BadRequestError as error:
return [data["embedding"] for data in response.data]
except litellm.exceptions.ContextWindowExceededError as error:
if isinstance(text, list):
parts = [text[0:math.ceil(len(text)/2)], text[math.ceil(len(text)/2):]]
parts_futures = [self.embed_text(part) for part in parts]
embeddings = await asyncio.gather(*parts_futures)
all_embeddings = []
for embeddings_part in embeddings:
all_embeddings.extend(embeddings_part)
return [data["embedding"] for data in all_embeddings]
logger.error("Context window exceeded for embedding text: %s", str(error))
raise error
except Exception as error:
logger.error("Error embedding text: %s", str(error))
raise error
return [data["embedding"] for data in response.data]
def get_vector_size(self) -> int:
return self.dimensions

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@ -7,20 +7,19 @@ from pathlib import Path
from swebench.harness.utils import load_swebench_dataset
from swebench.inference.make_datasets.create_instance import PATCH_EXAMPLE
import cognee
from cognee.api.v1.search import SearchType
from cognee.infrastructure.llm.get_llm_client import get_llm_client
from cognee.infrastructure.llm.prompts import read_query_prompt
from cognee.modules.pipelines import Task, run_tasks
from cognee.modules.retrieval.brute_force_triplet_search import \
brute_force_triplet_search
from cognee.shared.data_models import SummarizedContent
# from cognee.shared.data_models import SummarizedContent
from cognee.shared.utils import render_graph
from cognee.tasks.repo_processor import (enrich_dependency_graph,
expand_dependency_graph,
get_repo_file_dependencies)
from cognee.tasks.storage import add_data_points
from cognee.tasks.summarization import summarize_code
# from cognee.tasks.summarization import summarize_code
from evals.eval_utils import download_github_repo, retrieved_edges_to_string
@ -43,8 +42,21 @@ def check_install_package(package_name):
async def generate_patch_with_cognee(instance, llm_client, search_type=SearchType.CHUNKS):
import os
import pathlib
import cognee
from cognee.infrastructure.databases.relational import create_db_and_tables
file_path = Path(__file__).parent
data_directory_path = str(pathlib.Path(os.path.join(file_path, ".data_storage/code_graph")).resolve())
cognee.config.data_root_directory(data_directory_path)
cognee_directory_path = str(pathlib.Path(os.path.join(file_path, ".cognee_system/code_graph")).resolve())
cognee.config.system_root_directory(cognee_directory_path)
await cognee.prune.prune_data()
await cognee.prune.prune_system()
await cognee.prune.prune_system(metadata = True)
await create_db_and_tables()
# repo_path = download_github_repo(instance, '../RAW_GIT_REPOS')

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@ -17,60 +17,63 @@
"metadata": {},
"outputs": [],
"source": [
"from cognee.modules.users.methods import get_default_user\n",
"import os\n",
"import pathlib\n",
"import cognee\n",
"from cognee.infrastructure.databases.relational import create_db_and_tables\n",
"\n",
"from cognee.modules.data.methods import get_datasets\n",
"from cognee.modules.data.methods.get_dataset_data import get_dataset_data\n",
"from cognee.modules.data.models import Data\n",
"notebook_path = os.path.abspath(\"\")\n",
"data_directory_path = str(pathlib.Path(os.path.join(notebook_path, \".data_storage/code_graph\")).resolve())\n",
"cognee.config.data_root_directory(data_directory_path)\n",
"cognee_directory_path = str(pathlib.Path(os.path.join(notebook_path, \".cognee_system/code_graph\")).resolve())\n",
"cognee.config.system_root_directory(cognee_directory_path)\n",
"\n",
"from cognee.modules.pipelines.tasks.Task import Task\n",
"from cognee.tasks.documents import classify_documents, check_permissions_on_documents, extract_chunks_from_documents\n",
"from cognee.tasks.graph import extract_graph_from_code\n",
"await cognee.prune.prune_data()\n",
"await cognee.prune.prune_system(metadata = True)\n",
"\n",
"await create_db_and_tables()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from os import path\n",
"from pathlib import Path\n",
"from cognee.infrastructure.files.storage import LocalStorage\n",
"import git\n",
"\n",
"notebook_path = path.abspath(\"\")\n",
"repo_clone_location = path.join(notebook_path, \"data/graphrag\")\n",
"\n",
"LocalStorage.remove_all(repo_clone_location)\n",
"\n",
"git.Repo.clone_from(\n",
" \"git@github.com:microsoft/graphrag.git\",\n",
" Path(repo_clone_location),\n",
" branch = \"main\",\n",
" single_branch = True,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from cognee.tasks.repo_processor import enrich_dependency_graph, expand_dependency_graph, get_repo_file_dependencies\n",
"from cognee.tasks.storage import add_data_points\n",
"from cognee.shared.SourceCodeGraph import SourceCodeGraph\n",
"from cognee.modules.pipelines.tasks.Task import Task\n",
"\n",
"from cognee.modules.pipelines import run_tasks\n",
"\n",
"from cognee.shared.utils import render_graph\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"user = await get_default_user()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"existing_datasets = await get_datasets(user.id)\n",
"\n",
"datasets = {}\n",
"for dataset in existing_datasets:\n",
" dataset_name = dataset.name.replace(\".\", \"_\").replace(\" \", \"_\")\n",
" data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id)\n",
" datasets[dataset_name] = data_documents\n",
"print(datasets.keys())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"tasks = [\n",
" Task(classify_documents),\n",
" Task(check_permissions_on_documents, user = user, permissions = [\"write\"]),\n",
" Task(extract_chunks_from_documents), # Extract text chunks based on the document type.\n",
" Task(add_data_points, task_config = { \"batch_size\": 10 }),\n",
" Task(extract_graph_from_code, graph_model = SourceCodeGraph, task_config = { \"batch_size\": 10 }), # Generate knowledge graphs from the document chunks.\n",
" Task(get_repo_file_dependencies),\n",
" Task(add_data_points, task_config = { \"batch_size\": 50 }),\n",
" Task(enrich_dependency_graph, task_config = { \"batch_size\": 50 }),\n",
" Task(expand_dependency_graph, task_config = { \"batch_size\": 50 }),\n",
" Task(add_data_points, task_config = { \"batch_size\": 50 }),\n",
"]"
]
},
@ -80,21 +83,15 @@
"metadata": {},
"outputs": [],
"source": [
"async def run_codegraph_pipeline(tasks, data_documents):\n",
" pipeline = run_tasks(tasks, data_documents, \"code_graph_pipeline\")\n",
" results = []\n",
" async for result in pipeline:\n",
" results.append(result)\n",
" return(results)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"results = await run_codegraph_pipeline(tasks, datasets[\"main_dataset\"])"
"from cognee.modules.pipelines import run_tasks\n",
"\n",
"notebook_path = os.path.abspath(\"\")\n",
"repo_clone_location = os.path.join(notebook_path, \"data/graphrag\")\n",
"\n",
"pipeline = run_tasks(tasks, repo_clone_location, \"code_graph_pipeline\")\n",
"\n",
"async for result in pipeline:\n",
" print(result)"
]
},
{
@ -103,6 +100,7 @@
"metadata": {},
"outputs": [],
"source": [
"from cognee.shared.utils import render_graph\n",
"await render_graph(None, include_nodes = True, include_labels = True)"
]
},
@ -116,7 +114,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "cognee",
"display_name": ".venv",
"language": "python",
"name": "python3"
},
@ -130,7 +128,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.10"
"version": "3.11.8"
}
},
"nbformat": 4,

332
poetry.lock generated
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@ -6424,6 +6424,138 @@ botocore = ">=1.33.2,<2.0a.0"
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python-versions = ">=3.8.0"
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[[package]]
name = "tweepy"
version = "4.14.0"
@ -7840,4 +8138,4 @@ weaviate = ["weaviate-client"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.9.0,<3.12"
content-hash = "e2360f4be222743bb83b1e7316185c5f62bd73c0baaab3eee984e1c84f1cea65"
content-hash = "54118c733c3852c7685873a6a75789544475df45117488fa9c7071fd5bde1e8b"

View file

@ -71,6 +71,7 @@ pgvector = "^0.3.5"
psycopg2 = {version = "^2.9.10", optional = true}
llama-index-core = {version = "^0.11.22", optional = true}
deepeval = {version = "^2.0.1", optional = true}
transformers = "^4.46.3"
[tool.poetry.extras]
filesystem = ["s3fs", "botocore"]
@ -96,6 +97,7 @@ debugpy = "1.8.2"
pylint = "^3.0.3"
ruff = "^0.2.2"
tweepy = "4.14.0"
gitpython = "^3.1.43"
[tool.poetry.group.docs.dependencies]
mkdocs-material = "^9.5.42"