From 620355fecdd726f9523770da720b2de5849fee37 Mon Sep 17 00:00:00 2001 From: HRUSHIKESH DOKALA <96101829+Hk669@users.noreply.github.com> Date: Fri, 12 Jul 2024 16:19:17 +0530 Subject: [PATCH] oai embeddings for more semantic search <> personalized recommendations (#9) * update: intial setUp for oai azure embeddings * update db with embddings * Ui updates * update: dependencies * env update * readme updates * assets * feat: embed the docs before pushing in DB also while fetching recommendations * fix: env files --- .github/workflows/ci-tests.yml | 3 + README.md | 2 +- .../data_level0.bin | Bin 1676000 -> 0 bytes .../header.bin | Bin 100 -> 0 bytes .../length.bin | Bin 4000 -> 0 bytes .../data_level0.bin | Bin 0 -> 6284000 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 4000 bytes .../link_lists.bin | 0 chroma/chroma.sqlite3 | Bin 3043328 -> 3940352 bytes client/package-lock.json | 10 +++ client/package.json | 1 + client/src/App.css | 4 +- client/src/App.jsx | 78 +++++++++--------- client/src/components/Input/Input.css | 25 ++++-- client/src/components/Input/Input.jsx | 11 +++ client/src/components/Login/Login.css | 15 +++- client/src/components/Login/Login.jsx | 4 +- client/src/components/Navbar/Navbar.css | 2 +- .../Recommendation/Recommendation.css | 60 ++++---------- .../Recommendation/Recommendation.jsx | 43 +++++----- example.env | 14 +++- public/application.png | Bin 100542 -> 208017 bytes requirements.txt | 1 + src/api.py | 26 ++++-- src/db.py | 67 ++++++++++++--- src/oai.py | 20 +++++ src/search.py | 1 + 28 files changed, 252 insertions(+), 135 deletions(-) delete mode 100644 chroma/2fb656f8-eea6-4410-9c54-1e6d21ab400c/data_level0.bin delete mode 100644 chroma/2fb656f8-eea6-4410-9c54-1e6d21ab400c/header.bin delete mode 100644 chroma/2fb656f8-eea6-4410-9c54-1e6d21ab400c/length.bin create mode 100644 chroma/a14c490e-0fdc-41af-93aa-dc1de2615a2b/data_level0.bin create mode 100644 chroma/a14c490e-0fdc-41af-93aa-dc1de2615a2b/header.bin create mode 100644 chroma/a14c490e-0fdc-41af-93aa-dc1de2615a2b/length.bin rename chroma/{2fb656f8-eea6-4410-9c54-1e6d21ab400c => a14c490e-0fdc-41af-93aa-dc1de2615a2b}/link_lists.bin (100%) create mode 100644 src/oai.py diff --git a/.github/workflows/ci-tests.yml b/.github/workflows/ci-tests.yml index 49f12da..06771c9 100644 --- a/.github/workflows/ci-tests.yml +++ b/.github/workflows/ci-tests.yml @@ -33,3 +33,6 @@ jobs: GITHUB_CLIENT_SECRET: ${{ secrets.CLIENT_SECRET }} MONGODB_URL: ${{ secrets.MONGODB_URL }} GPAT: ${{ secrets.GPAT }} + AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }} + AZURE_OPENAI_ENDPOINT: ${{ secrets.AZURE_OPENAI_ENDPOINT }} + AZURE_DEPLOYMENT: ${{ secrets.AZURE_DEPLOYMENT }} diff --git a/README.md b/README.md index e4dab8e..b1a2576 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # Open-Source Recommender -![alt text](public/application.png) +![application](public/application.png) This will be a free public-facing web application designed to find 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zren5HWzX*v43gfsHDl+T#)Sa7!EZ^RT3J*a%Q#4>e5_Ef&}%8VS!SwjhQ_C!cbSro z(X_o?YhMK)1hoLgt%0>*-_=-q4S7(BhX+G(gbF*Al*LD`kY;VtcDonKa13L-$_h-tR>XQfKwL3faS2j04 zydCZyPA6M;#5)qTnZCxV>b*P2A}y~;c7*2|;xBh!$HNe>E5}U`_osS8(Eh{e);&J{ Y?uzcyBXc$J8;NVViBwfnYH#QN0(E+vdjJ3c diff --git a/client/package-lock.json b/client/package-lock.json index e2ce8d4..2f90802 100644 --- a/client/package-lock.json +++ b/client/package-lock.json @@ -12,6 +12,7 @@ "@testing-library/react": "^13.4.0", "@testing-library/user-event": "^13.5.0", "axios": "^1.7.2", + "date-fns": "^3.6.0", "hamburger-react": "^2.5.1", "react": "^18.3.1", "react-dom": "^18.3.1", @@ -6838,6 +6839,15 @@ "url": "https://github.com/sponsors/ljharb" } }, + "node_modules/date-fns": { + "version": "3.6.0", + "resolved": "https://registry.npmjs.org/date-fns/-/date-fns-3.6.0.tgz", + "integrity": "sha512-fRHTG8g/Gif+kSh50gaGEdToemgfj74aRX3swtiouboip5JDLAyDE9F11nHMIcvOaXeOC6D7SpNhi7uFyB7Uww==", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/kossnocorp" + } + }, "node_modules/debug": { "version": "4.3.5", "resolved": "https://registry.npmjs.org/debug/-/debug-4.3.5.tgz", diff --git a/client/package.json b/client/package.json index 2523e35..59769a8 100644 --- a/client/package.json +++ b/client/package.json @@ -7,6 +7,7 @@ "@testing-library/react": "^13.4.0", "@testing-library/user-event": "^13.5.0", "axios": "^1.7.2", + "date-fns": "^3.6.0", "hamburger-react": "^2.5.1", "react": "^18.3.1", "react-dom": "^18.3.1", diff --git a/client/src/App.css b/client/src/App.css index 9f07760..a2a1940 100644 --- a/client/src/App.css +++ b/client/src/App.css @@ -59,7 +59,7 @@ body { justify-content: space-between; width: 100%; max-width: 1200px; - margin: 0 auto; + margin-top: auto; padding: 20px; } @@ -96,6 +96,6 @@ body { } .recommendations-container { - margin-top: 20px; + margin-top: 10px; } } diff --git a/client/src/App.jsx b/client/src/App.jsx index c79f011..17d0028 100644 --- a/client/src/App.jsx +++ b/client/src/App.jsx @@ -33,7 +33,7 @@ function App() { if (response.ok) { const data = await response.json(); setIsAuthenticated(true); - setUserData(data); // The backend now returns only necessary user information + setUserData(data); navigate("/recommender"); } else { localStorage.removeItem("jwt_token"); @@ -67,44 +67,44 @@ function App() { navigate("/login"); }; - return ( -

    - -
    - - } /> - } /> - -
    0 ? "with-recommendations" : ""}`}> - -
    -
    0 ? "visible" : ""}`}> - {loading ? ( -
    -
    -

    Loading recommendations...

    -
    - ) : recommendations.length > 0 ? ( - - ) : null} -
    - - ) : ( - - ) - } - /> - } /> -
    -
    - -

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  • diff --git a/example.env b/example.env index 0892ba2..a34a04e 100644 --- a/example.env +++ b/example.env @@ -1 +1,13 @@ -export GPAT = "gh_psa60d34asdjFNKUh53BUorN" \ No newline at end of file +export GPAT = "ghhjhvhvvKUh53BUorN" +export GITHUB_CLIENT_ID = "Osdsdoqw21243JO" +export GITHUB_CLIENT_SECRET = "32413nkfnkfjkW21419413380658" + +export MONGODB_URL = "mongodb+srv://njdjqf" +export JWT_SECRET_KEY = "djqw341294182490dj289838865c98" +export USER = "user" +export PASSWORD = "pass" +export ALLOWED_ORIGINS = ["http://localhost:3000","*"] + +export AZURE_OPENAI_API_KEY = "123njnnnnn34991mdm" +export AZURE_OPENAI_ENDPOINT = "https://deployment.openai.azure.com/" +export AZURE_DEPLOYMENT = "deployment-name" \ No newline at end of file diff --git a/public/application.png b/public/application.png index e9348882ebcba0732f9e7f1499dd64e383321a25..c6e1a7fa34dd09b83061357ffa332c27e75f3f81 100644 GIT binary patch literal 208017 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qv$DO5f-yP1N0;9Hsr^O^mrqg3Qf}gusNe1heI1jl#ea7A<^KTOWR=JO diff --git a/requirements.txt b/requirements.txt index 1c296d3..a1bdc5d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -27,6 +27,7 @@ mdurl==0.1.2 motor==3.5.0 multidict==6.0.5 orjson==3.10.5 +openai==1.35.13 pydantic==2.7.4 pydantic_core==2.18.4 Pygments==2.18.0 diff --git a/src/api.py b/src/api.py index c65ebe8..0b0fd2a 100644 --- a/src/api.py +++ b/src/api.py @@ -4,7 +4,7 @@ import logging import os from dotenv import load_dotenv -from fastapi import FastAPI, HTTPException, Header, Depends +from fastapi import FastAPI, HTTPException, Header, Depends, Request from fastapi.middleware.cors import CORSMiddleware from starlette.responses import RedirectResponse from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm @@ -160,10 +160,15 @@ async def preflight_verify_token(): @app.post('/api/recommendations/') -async def get_recommendations(current_user: dict = Depends(get_current_user)) -> dict: +async def get_recommendations(request: Request, current_user: dict = Depends(get_current_user)) -> dict: try: + body = await request.json() + extra_topics = body.get("extra_topics", []) + languages = body.get("languages", []) + username = body.get("username", current_user.get("username")) urls = [] - user = User(username=current_user["username"], access_token=current_user["access_token"]) + user = User(username=current_user["username"], access_token=current_user["access_token"],extra_topics=extra_topics, extra_languages=languages) + user_details, language_topics = await get_repos(user) if not user_details: logger.info("No repos found for user") @@ -179,13 +184,22 @@ async def get_recommendations(current_user: dict = Depends(get_current_user)) -> if urls and len(urls) < 10: logger.info("Fewer than 10 recommendations found, fetching more repositories based on topics") - fetched_repos = await main(language_topics, access_token=user.access_token, extra_topics=current_user.get("extra_topics", []), extra_languages=current_user.get("languages", [])) + fetched_repos = await main(language_topics, access_token=user.access_token, extra_topics=extra_topics, extra_languages=languages) urls = recommend(user_details, language_topics) - if not urls: + seen_full_names = set() + unique_recommendations = [] + + for rec in urls: + full_name = rec.get("full_name") + if full_name not in seen_full_names: + seen_full_names.add(full_name) + unique_recommendations.append(rec) + + if not unique_recommendations: return {'recommendations': [], 'message': 'No recommendations found'} - return {'recommendations': urls} + return {'recommendations': unique_recommendations} except Exception as e: logger.error(f"Error: {str(e)}") raise HTTPException(status_code=500, detail="An error occurred while generating recommendations") diff --git a/src/db.py b/src/db.py index bfabd4e..5aef46a 100644 --- a/src/db.py +++ b/src/db.py @@ -2,12 +2,17 @@ import chromadb import random import os +import logging from typing import List +from datetime import datetime, timezone from src.models import RepositoryRecommendation -import logging +from src.oai import generate_embeddings +from dotenv import load_dotenv +load_dotenv() logger = logging.getLogger(__name__) + def recommend(user_details, languages_topics) -> List[RepositoryRecommendation]: """generate recommendations for the user""" @@ -16,19 +21,20 @@ def recommend(user_details, recommended_repos = set() collection = get_chromadb_collection() - languages_topics = languages_topics["languages"] + languages_topics["topics"] + lang_topics = languages_topics["languages"] + languages_topics["topics"] for user_proj in user_details: - new_doc = f"{user_proj['project_name']} : {user_proj['description']}" + new_doc = f"{user_proj['project_name']} : {user_proj['description']} : {lang_topics}" - + # print(f"Querying ChromaDB for project: {user_proj}") + embeddings = generate_embeddings(new_doc) + # print(f"Embeddings: {embeddings}") results = collection.query( - query_texts = [new_doc], + query_embeddings = [embeddings], n_results = 10, - where = { - "related_language_or_topic": {"$in": languages_topics} - } ) + logging.info(f"UserProject: {user_proj}, Repositories: {results}") + # print(f"UserProject: {user_proj}, Repositories: {results}") if results['documents'][0]: # Extract repository names and construct GitHub URLs ids = results["ids"][0] @@ -77,8 +83,10 @@ def recommend_by_topics(topics: List[str], collection = get_chromadb_collection() logger.info(f"Querying ChromaDB for topics: {topics}") + embeddings = [generate_embeddings(topic) for topic in topics] + results = collection.query( - query_texts=topics, + query_embeddings=embeddings, n_results=max_recommendations * 2, # Get more results to allow for filtering where={"related_language_or_topic": {"$in": topics}} ) @@ -107,7 +115,7 @@ def recommend_by_topics(topics: List[str], "open_issues_count": metadata.get("open_issues_count"), "avatar_url": metadata.get("owner", {}).get("avatar_url"), "language": metadata.get("language"), - "updated_at": metadata.get("updated_at"), + "updated_at": convert_to_readable_format(metadata.get("updated_at")), "topics": metadata.get("topics", []) }) recommended_repos.add(repo_url) @@ -157,6 +165,7 @@ def upsert_to_chroma_db(collection, unique_repos): ids = [] documents = [] metadatas = [] + embeddings = [] for repo_id, repo_data in unique_repos.items(): # Extract data from repo_data with default values or handling None @@ -179,7 +188,8 @@ def upsert_to_chroma_db(collection, unique_repos): # Append data to respective lists for upsert ids.append(str(repo_id)) - documents.append(f"{full_name}\n{description}") + document = f"{full_name}\n{description}\n{topics}" + documents.append(document) # Prepare metadata dictionary metadata = { @@ -197,11 +207,14 @@ def upsert_to_chroma_db(collection, unique_repos): # Add metadata to the list metadatas.append(metadata) + embed_doc = generate_embeddings(document) + embeddings.append(embed_doc) try: # Upsert data to the collection collection.add( ids=ids, + embeddings=embeddings, documents=documents, metadatas=metadatas ) @@ -217,3 +230,35 @@ def upsert_to_chroma_db(collection, unique_repos): # Catch any unexpected errors during upsert raise Exception(f"Unexpected error upserting data to ChromaDB: {e}") + +def convert_to_readable_format(time_str): + # Parse the input string to a datetime object + dt = datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%SZ") + + dt = dt.replace(tzinfo=timezone.utc) + readable_time_str = dt.strftime("%B %d, %Y at %H:%M %Z") + + return readable_time_str + + +if __name__ == "__main__": + collection = get_chromadb_collection() + print(collection) + + user_details = [ + {'project_name': 'blog', 'description': 'my understanding/ works', 'related_language_or_topic': ['Dockerfile']}, + {'project_name': 'bpetokenizer', 'description': '(py package) train your own tokenizer based on BPE algorithm for the LLMs (supports the regex pattern and special tokens)', 'related_language_or_topic': ['Jupyter Notebook', 'Python']}, + {'project_name': 'HacksArena', 'description': "The django based application classifies user intents using a bag-of-words approach. It predicts intents based on the user's input, retrieves a random response from a predefined set of responses associated with each intent, and generates the appropriate reply.", 'related_language_or_topic': ['Python', 'CSS', 'JavaScript', 'HTML']} +] + + languages_topics = { + 'languages': ['Python', 'JavaScript'], + 'topics': ['agentic-ai', 'openai'] + } + try: + recommendations = recommend(user_details, languages_topics) + logger.info(recommendations) + print('--------') + print(recommendations) + except Exception as e: + print(f"Error Recommending data: {e}") \ No newline at end of file diff --git a/src/oai.py b/src/oai.py new file mode 100644 index 0000000..51d7eea --- /dev/null +++ b/src/oai.py @@ -0,0 +1,20 @@ +from openai import AzureOpenAI +import os +from dotenv import load_dotenv +load_dotenv() + +client = AzureOpenAI( + azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"), + api_key = os.getenv("AZURE_OPENAI_API_KEY"), + azure_deployment=os.getenv("AZURE_DEPLOYMENT"), + api_version = "2023-09-15-preview", +) + +def generate_embeddings(text, model="text-embedding-3-small"): + """Generate embeddings for the given text using the specified model""" + return client.embeddings.create(input = [text], model=model).data[0].embedding + +if __name__ == "__main__": + text = "I am a software engineer" + embeddings = generate_embeddings(text) + print(embeddings) diff --git a/src/search.py b/src/search.py index b6b77da..c25f844 100644 --- a/src/search.py +++ b/src/search.py @@ -123,6 +123,7 @@ async def main(language_topics, results = await asyncio.gather(*tasks) for result in results: unique_repos.update(result) + print(f"Unique Repositories: {unique_repos}") logger.info(f"Found {len(unique_repos)} unique repositories\n--------")

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