diff --git a/.gitignore b/.gitignore
index d7747efb..ac5ff190 100644
--- a/.gitignore
+++ b/.gitignore
@@ -75,6 +75,7 @@ target/
# Jupyter Notebook
.ipynb_checkpoints
+**/*.ipynb
# IPython
profile_default/
diff --git a/application/api/answer/routes.py b/application/api/answer/routes.py
index abb2f67c..bd1fa21f 100644
--- a/application/api/answer/routes.py
+++ b/application/api/answer/routes.py
@@ -29,12 +29,15 @@ prompts_collection = db["prompts"]
api_key_collection = db["api_keys"]
answer = Blueprint('answer', __name__)
-if settings.LLM_NAME == "gpt4":
- gpt_model = 'gpt-4'
+gpt_model = ""
+# to have some kind of default behaviour
+if settings.LLM_NAME == "openai":
+ gpt_model = 'gpt-3.5-turbo'
elif settings.LLM_NAME == "anthropic":
gpt_model = 'claude-2'
-else:
- gpt_model = 'gpt-3.5-turbo'
+
+if settings.MODEL_NAME: # in case there is particular model name configured
+ gpt_model = settings.MODEL_NAME
# load the prompts
current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
@@ -102,9 +105,8 @@ def is_azure_configured():
return settings.OPENAI_API_BASE and settings.OPENAI_API_VERSION and settings.AZURE_DEPLOYMENT_NAME
-def complete_stream(question, docsearch, chat_history, prompt_id, conversation_id):
+def complete_stream(question, docsearch, chat_history, prompt_id, conversation_id, chunks=2):
llm = LLMCreator.create_llm(settings.LLM_NAME, api_key=settings.API_KEY)
-
if prompt_id == 'default':
prompt = chat_combine_template
elif prompt_id == 'creative':
@@ -113,8 +115,11 @@ def complete_stream(question, docsearch, chat_history, prompt_id, conversation_i
prompt = chat_combine_strict
else:
prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
-
- docs = docsearch.search(question, k=2)
+
+ if chunks == 0:
+ docs = []
+ else:
+ docs = docsearch.search(question, k=chunks)
if settings.LLM_NAME == "llama.cpp":
docs = [docs[0]]
# join all page_content together with a newline
@@ -202,6 +207,10 @@ def stream():
prompt_id = data["prompt_id"]
else:
prompt_id = 'default'
+ if 'chunks' in data:
+ chunks = int(data["chunks"])
+ else:
+ chunks = 2
# check if active_docs is set
@@ -218,7 +227,8 @@ def stream():
complete_stream(question, docsearch,
chat_history=history,
prompt_id=prompt_id,
- conversation_id=conversation_id), mimetype="text/event-stream"
+ conversation_id=conversation_id,
+ chunks=chunks), mimetype="text/event-stream"
)
@@ -239,6 +249,10 @@ def api_answer():
prompt_id = data["prompt_id"]
else:
prompt_id = 'default'
+ if 'chunks' in data:
+ chunks = int(data["chunks"])
+ else:
+ chunks = 2
if prompt_id == 'default':
prompt = chat_combine_template
@@ -266,7 +280,10 @@ def api_answer():
- docs = docsearch.search(question, k=2)
+ if chunks == 0:
+ docs = []
+ else:
+ docs = docsearch.search(question, k=chunks)
# join all page_content together with a newline
docs_together = "\n".join([doc.page_content for doc in docs])
p_chat_combine = prompt.replace("{summaries}", docs_together)
@@ -361,9 +378,15 @@ def api_search():
vectorstore = get_vectorstore({"active_docs": data["active_docs"]})
else:
vectorstore = ""
+ if 'chunks' in data:
+ chunks = int(data["chunks"])
+ else:
+ chunks = 2
docsearch = VectorCreator.create_vectorstore(settings.VECTOR_STORE, vectorstore, settings.EMBEDDINGS_KEY)
-
- docs = docsearch.search(question, k=2)
+ if chunks == 0:
+ docs = []
+ else:
+ docs = docsearch.search(question, k=chunks)
source_log_docs = []
for doc in docs:
diff --git a/application/core/settings.py b/application/core/settings.py
index 84073b7d..0e1909e6 100644
--- a/application/core/settings.py
+++ b/application/core/settings.py
@@ -9,6 +9,7 @@ current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__
class Settings(BaseSettings):
LLM_NAME: str = "docsgpt"
+ MODEL_NAME: Optional[str] = None # when LLM_NAME is openai, MODEL_NAME can be e.g. gpt-4-turbo-preview or gpt-3.5-turbo
EMBEDDINGS_NAME: str = "huggingface_sentence-transformers/all-mpnet-base-v2"
CELERY_BROKER_URL: str = "redis://localhost:6379/0"
CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"
diff --git a/application/parser/remote/reddit_loader.py b/application/parser/remote/reddit_loader.py
new file mode 100644
index 00000000..0230653a
--- /dev/null
+++ b/application/parser/remote/reddit_loader.py
@@ -0,0 +1,26 @@
+from application.parser.remote.base import BaseRemote
+from langchain_community.document_loaders import RedditPostsLoader
+
+
+class RedditPostsLoaderRemote(BaseRemote):
+ def load_data(self, inputs):
+ data = eval(inputs)
+ client_id = data.get("client_id")
+ client_secret = data.get("client_secret")
+ user_agent = data.get("user_agent")
+ categories = data.get("categories", ["new", "hot"])
+ mode = data.get("mode", "subreddit")
+ search_queries = data.get("search_queries")
+ number_posts = data.get("number_posts", 10)
+ self.loader = RedditPostsLoader(
+ client_id=client_id,
+ client_secret=client_secret,
+ user_agent=user_agent,
+ categories=categories,
+ mode=mode,
+ search_queries=search_queries,
+ number_posts=number_posts,
+ )
+ documents = self.loader.load()
+ print(f"Loaded {len(documents)} documents from Reddit")
+ return documents
diff --git a/application/parser/remote/remote_creator.py b/application/parser/remote/remote_creator.py
index e45333d4..d2a58f8d 100644
--- a/application/parser/remote/remote_creator.py
+++ b/application/parser/remote/remote_creator.py
@@ -1,13 +1,15 @@
from application.parser.remote.sitemap_loader import SitemapLoader
from application.parser.remote.crawler_loader import CrawlerLoader
from application.parser.remote.web_loader import WebLoader
+from application.parser.remote.reddit_loader import RedditPostsLoaderRemote
class RemoteCreator:
loaders = {
- 'url': WebLoader,
- 'sitemap': SitemapLoader,
- 'crawler': CrawlerLoader
+ "url": WebLoader,
+ "sitemap": SitemapLoader,
+ "crawler": CrawlerLoader,
+ "reddit": RedditPostsLoaderRemote,
}
@classmethod
@@ -15,4 +17,4 @@ class RemoteCreator:
loader_class = cls.loaders.get(type.lower())
if not loader_class:
raise ValueError(f"No LLM class found for type {type}")
- return loader_class(*args, **kwargs)
\ No newline at end of file
+ return loader_class(*args, **kwargs)
diff --git a/application/worker.py b/application/worker.py
index 21bb319f..3891fde9 100644
--- a/application/worker.py
+++ b/application/worker.py
@@ -15,23 +15,27 @@ from application.parser.schema.base import Document
from application.parser.token_func import group_split
try:
- nltk.download('punkt', quiet=True)
- nltk.download('averaged_perceptron_tagger', quiet=True)
+ nltk.download("punkt", quiet=True)
+ nltk.download("averaged_perceptron_tagger", quiet=True)
except FileExistsError:
pass
# Define a function to extract metadata from a given filename.
def metadata_from_filename(title):
- store = '/'.join(title.split('/')[1:3])
- return {'title': title, 'store': store}
+ store = "/".join(title.split("/")[1:3])
+ return {"title": title, "store": store}
# Define a function to generate a random string of a given length.
def generate_random_string(length):
- return ''.join([string.ascii_letters[i % 52] for i in range(length)])
+ return "".join([string.ascii_letters[i % 52] for i in range(length)])
+
+
+current_dir = os.path.dirname(
+ os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+)
-current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
# Define the main function for ingesting and processing documents.
def ingest_worker(self, directory, formats, name_job, filename, user):
@@ -62,38 +66,52 @@ def ingest_worker(self, directory, formats, name_job, filename, user):
token_check = True
min_tokens = 150
max_tokens = 1250
- full_path = directory + '/' + user + '/' + name_job
+ full_path = directory + "/" + user + "/" + name_job
import sys
+
print(full_path, file=sys.stderr)
# check if API_URL env variable is set
- file_data = {'name': name_job, 'file': filename, 'user': user}
- response = requests.get(urljoin(settings.API_URL, "/api/download"), params=file_data)
+ file_data = {"name": name_job, "file": filename, "user": user}
+ response = requests.get(
+ urljoin(settings.API_URL, "/api/download"), params=file_data
+ )
# check if file is in the response
print(response, file=sys.stderr)
file = response.content
if not os.path.exists(full_path):
os.makedirs(full_path)
- with open(full_path + '/' + filename, 'wb') as f:
+ with open(full_path + "/" + filename, "wb") as f:
f.write(file)
# check if file is .zip and extract it
- if filename.endswith('.zip'):
- with zipfile.ZipFile(full_path + '/' + filename, 'r') as zip_ref:
+ if filename.endswith(".zip"):
+ with zipfile.ZipFile(full_path + "/" + filename, "r") as zip_ref:
zip_ref.extractall(full_path)
- os.remove(full_path + '/' + filename)
+ os.remove(full_path + "/" + filename)
- self.update_state(state='PROGRESS', meta={'current': 1})
+ self.update_state(state="PROGRESS", meta={"current": 1})
- raw_docs = SimpleDirectoryReader(input_dir=full_path, input_files=input_files, recursive=recursive,
- required_exts=formats, num_files_limit=limit,
- exclude_hidden=exclude, file_metadata=metadata_from_filename).load_data()
- raw_docs = group_split(documents=raw_docs, min_tokens=min_tokens, max_tokens=max_tokens, token_check=token_check)
+ raw_docs = SimpleDirectoryReader(
+ input_dir=full_path,
+ input_files=input_files,
+ recursive=recursive,
+ required_exts=formats,
+ num_files_limit=limit,
+ exclude_hidden=exclude,
+ file_metadata=metadata_from_filename,
+ ).load_data()
+ raw_docs = group_split(
+ documents=raw_docs,
+ min_tokens=min_tokens,
+ max_tokens=max_tokens,
+ token_check=token_check,
+ )
docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
call_openai_api(docs, full_path, self)
- self.update_state(state='PROGRESS', meta={'current': 100})
+ self.update_state(state="PROGRESS", meta={"current": 100})
if sample:
for i in range(min(5, len(raw_docs))):
@@ -101,70 +119,80 @@ def ingest_worker(self, directory, formats, name_job, filename, user):
# get files from outputs/inputs/index.faiss and outputs/inputs/index.pkl
# and send them to the server (provide user and name in form)
- file_data = {'name': name_job, 'user': user}
+ file_data = {"name": name_job, "user": user}
if settings.VECTOR_STORE == "faiss":
- files = {'file_faiss': open(full_path + '/index.faiss', 'rb'),
- 'file_pkl': open(full_path + '/index.pkl', 'rb')}
- response = requests.post(urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data)
- response = requests.get(urljoin(settings.API_URL, "/api/delete_old?path=" + full_path))
+ files = {
+ "file_faiss": open(full_path + "/index.faiss", "rb"),
+ "file_pkl": open(full_path + "/index.pkl", "rb"),
+ }
+ response = requests.post(
+ urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data
+ )
+ response = requests.get(
+ urljoin(settings.API_URL, "/api/delete_old?path=" + full_path)
+ )
else:
- response = requests.post(urljoin(settings.API_URL, "/api/upload_index"), data=file_data)
+ response = requests.post(
+ urljoin(settings.API_URL, "/api/upload_index"), data=file_data
+ )
-
# delete local
shutil.rmtree(full_path)
return {
- 'directory': directory,
- 'formats': formats,
- 'name_job': name_job,
- 'filename': filename,
- 'user': user,
- 'limited': False
+ "directory": directory,
+ "formats": formats,
+ "name_job": name_job,
+ "filename": filename,
+ "user": user,
+ "limited": False,
}
-def remote_worker(self, source_data, name_job, user, directory = 'temp', loader = 'url'):
+
+def remote_worker(self, source_data, name_job, user, loader, directory="temp"):
# sample = False
token_check = True
min_tokens = 150
max_tokens = 1250
- full_path = directory + '/' + user + '/' + name_job
+ full_path = directory + "/" + user + "/" + name_job
if not os.path.exists(full_path):
os.makedirs(full_path)
- self.update_state(state='PROGRESS', meta={'current': 1})
-
+ self.update_state(state="PROGRESS", meta={"current": 1})
+
# source_data {"data": [url]} for url type task just urls
-
+
# Use RemoteCreator to load data from URL
remote_loader = RemoteCreator.create_loader(loader)
raw_docs = remote_loader.load_data(source_data)
- docs = group_split(documents=raw_docs, min_tokens=min_tokens, max_tokens=max_tokens, token_check=token_check)
+ docs = group_split(
+ documents=raw_docs,
+ min_tokens=min_tokens,
+ max_tokens=max_tokens,
+ token_check=token_check,
+ )
- #docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
+ # docs = [Document.to_langchain_format(raw_doc) for raw_doc in raw_docs]
call_openai_api(docs, full_path, self)
- self.update_state(state='PROGRESS', meta={'current': 100})
-
-
+ self.update_state(state="PROGRESS", meta={"current": 100})
# Proceed with uploading and cleaning as in the original function
- file_data = {'name': name_job, 'user': user}
+ file_data = {"name": name_job, "user": user}
if settings.VECTOR_STORE == "faiss":
- files = {'file_faiss': open(full_path + '/index.faiss', 'rb'),
- 'file_pkl': open(full_path + '/index.pkl', 'rb')}
- requests.post(urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data)
+ files = {
+ "file_faiss": open(full_path + "/index.faiss", "rb"),
+ "file_pkl": open(full_path + "/index.pkl", "rb"),
+ }
+ requests.post(
+ urljoin(settings.API_URL, "/api/upload_index"), files=files, data=file_data
+ )
requests.get(urljoin(settings.API_URL, "/api/delete_old?path=" + full_path))
else:
requests.post(urljoin(settings.API_URL, "/api/upload_index"), data=file_data)
shutil.rmtree(full_path)
- return {
- 'urls': source_data,
- 'name_job': name_job,
- 'user': user,
- 'limited': False
- }
\ No newline at end of file
+ return {"urls": source_data, "name_job": name_job, "user": user, "limited": False}
diff --git a/docs/package-lock.json b/docs/package-lock.json
index dc608479..e2c0f301 100644
--- a/docs/package-lock.json
+++ b/docs/package-lock.json
@@ -7,7 +7,7 @@
"license": "MIT",
"dependencies": {
"@vercel/analytics": "^1.1.1",
- "docsgpt": "^0.3.0",
+ "docsgpt": "^0.3.7",
"next": "^14.0.4",
"nextra": "^2.13.2",
"nextra-theme-docs": "^2.13.2",
@@ -422,6 +422,11 @@
"node": ">=6.9.0"
}
},
+ "node_modules/@bpmn-io/snarkdown": {
+ "version": "2.2.0",
+ "resolved": "https://registry.npmjs.org/@bpmn-io/snarkdown/-/snarkdown-2.2.0.tgz",
+ "integrity": "sha512-bVD7FIoaBDZeCJkMRgnBPDeptPlto87wt2qaCjf5t8iLaevDmTPaREd6FpBEGsHlUdHFFZWRk4qAoEC5So2M0Q=="
+ },
"node_modules/@braintree/sanitize-url": {
"version": "6.0.4",
"resolved": "https://registry.npmjs.org/@braintree/sanitize-url/-/sanitize-url-6.0.4.tgz",
@@ -4958,11 +4963,12 @@
}
},
"node_modules/docsgpt": {
- "version": "0.3.0",
- "resolved": "https://registry.npmjs.org/docsgpt/-/docsgpt-0.3.0.tgz",
- "integrity": "sha512-0yT2m+HAlJ+289p278c3Zi07bu2wr6zULOT/bYXtJ/nb59V2Vpfdj2xFB49+lYLSeVe8H+Ij5fFSNZ6RkVRfMQ==",
+ "version": "0.3.7",
+ "resolved": "https://registry.npmjs.org/docsgpt/-/docsgpt-0.3.7.tgz",
+ "integrity": "sha512-VHrXXOEFtjNTcpA8Blf3IzpLlJxOMhm/S5CM4FDjQEkdK9WWhI8yXd/0Rs/FS8oz7YbFrNxO758mlP7OtQtBBw==",
"dependencies": {
"@babel/plugin-transform-flow-strip-types": "^7.23.3",
+ "@bpmn-io/snarkdown": "^2.2.0",
"@parcel/resolver-glob": "^2.12.0",
"@parcel/transformer-svg-react": "^2.12.0",
"@parcel/transformer-typescript-tsc": "^2.12.0",
@@ -4972,6 +4978,7 @@
"@types/react-dom": "^18.2.19",
"class-variance-authority": "^0.7.0",
"clsx": "^2.1.0",
+ "dompurify": "^3.0.9",
"flow-bin": "^0.229.2",
"i": "^0.3.7",
"install": "^0.13.0",
@@ -5029,9 +5036,9 @@
}
},
"node_modules/dompurify": {
- "version": "3.0.7",
- "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.0.7.tgz",
- "integrity": "sha512-BViYTZoqP3ak/ULKOc101y+CtHDUvBsVgSxIF1ku0HmK6BRf+C03MC+tArMvOPtVtZp83DDh5puywKDu4sbVjQ=="
+ "version": "3.0.11",
+ "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.0.11.tgz",
+ "integrity": "sha512-Fan4uMuyB26gFV3ovPoEoQbxRRPfTu3CvImyZnhGq5fsIEO+gEFLp45ISFt+kQBWsK5ulDdT0oV28jS1UrwQLg=="
},
"node_modules/domutils": {
"version": "2.8.0",
@@ -6206,9 +6213,9 @@
"integrity": "sha512-gfFQZrcTc8CnKXp6Y4/CBT3fTc0OVuDofpre4aEeEpSBPV5X5v4+Vmx+8snU7RLPrNHPKSgLxGo9YuQzz20o+w=="
},
"node_modules/katex": {
- "version": "0.16.9",
- "resolved": "https://registry.npmjs.org/katex/-/katex-0.16.9.tgz",
- "integrity": "sha512-fsSYjWS0EEOwvy81j3vRA8TEAhQhKiqO+FQaKWp0m39qwOzHVBgAUBIXWj1pB+O2W3fIpNa6Y9KSKCVbfPhyAQ==",
+ "version": "0.16.10",
+ "resolved": "https://registry.npmjs.org/katex/-/katex-0.16.10.tgz",
+ "integrity": "sha512-ZiqaC04tp2O5utMsl2TEZTXxa6WSC4yo0fv5ML++D3QZv/vx2Mct0mTlRx3O+uUkjfuAgOkzsCmq5MiUEsDDdA==",
"funding": [
"https://opencollective.com/katex",
"https://github.com/sponsors/katex"
diff --git a/frontend/src/Setting.tsx b/frontend/src/Setting.tsx
index 83cf06bf..172691a0 100644
--- a/frontend/src/Setting.tsx
+++ b/frontend/src/Setting.tsx
@@ -9,6 +9,8 @@ import {
setPrompt,
selectSourceDocs,
setSourceDocs,
+ setChunks,
+ selectChunks,
} from './preferences/preferenceSlice';
import { Doc } from './preferences/preferenceApi';
import { useDarkTheme } from './hooks';
@@ -190,10 +192,13 @@ const Setting: React.FC = () => {
const General: React.FC = () => {
const themes = ['Light', 'Dark'];
const languages = ['English'];
+ const chunks = ['0', '2', '4', '6', '8', '10'];
+ const selectedChunks = useSelector(selectChunks);
const [isDarkTheme, toggleTheme] = useDarkTheme();
const [selectedTheme, setSelectedTheme] = useState(
isDarkTheme ? 'Dark' : 'Light',
);
+ const dispatch = useDispatch();
const [selectedLanguage, setSelectedLanguage] = useState(languages[0]);
return (
@@ -208,7 +213,7 @@ const General: React.FC = () => {
}}
/>
-
+
Select Language
@@ -218,6 +223,16 @@ const General: React.FC = () => {
onSelect={setSelectedLanguage}
/>
+
+
+ Chunks processed per query
+
+
dispatch(setChunks(value))}
+ />
+
diff --git a/frontend/src/conversation/conversationApi.ts b/frontend/src/conversation/conversationApi.ts
index 4f789f15..e586366b 100644
--- a/frontend/src/conversation/conversationApi.ts
+++ b/frontend/src/conversation/conversationApi.ts
@@ -10,6 +10,7 @@ export function fetchAnswerApi(
history: Array
= [],
conversationId: string | null,
promptId: string | null,
+ chunks: string,
): Promise<
| {
result: any;
@@ -62,6 +63,7 @@ export function fetchAnswerApi(
active_docs: docPath,
conversation_id: conversationId,
prompt_id: promptId,
+ chunks: chunks,
}),
signal,
})
@@ -91,6 +93,7 @@ export function fetchAnswerSteaming(
history: Array = [],
conversationId: string | null,
promptId: string | null,
+ chunks: string,
onEvent: (event: MessageEvent) => void,
): Promise {
let namePath = selectedDocs.name;
@@ -124,6 +127,7 @@ export function fetchAnswerSteaming(
history: JSON.stringify(history),
conversation_id: conversationId,
prompt_id: promptId,
+ chunks: chunks,
};
fetch(apiHost + '/stream', {
method: 'POST',
@@ -185,6 +189,7 @@ export function searchEndpoint(
selectedDocs: Doc,
conversation_id: string | null,
history: Array = [],
+ chunks: string,
) {
/*
"active_docs": "default",
@@ -216,6 +221,7 @@ export function searchEndpoint(
active_docs: docPath,
conversation_id,
history,
+ chunks: chunks,
};
return fetch(`${apiHost}/api/search`, {
method: 'POST',
diff --git a/frontend/src/conversation/conversationSlice.ts b/frontend/src/conversation/conversationSlice.ts
index ed4e41e4..72cf660b 100644
--- a/frontend/src/conversation/conversationSlice.ts
+++ b/frontend/src/conversation/conversationSlice.ts
@@ -27,6 +27,7 @@ export const fetchAnswer = createAsyncThunk(
state.conversation.queries,
state.conversation.conversationId,
state.preference.prompt.id,
+ state.preference.chunks,
(event) => {
const data = JSON.parse(event.data);
@@ -49,6 +50,7 @@ export const fetchAnswer = createAsyncThunk(
state.preference.selectedDocs!,
state.conversation.conversationId,
state.conversation.queries,
+ state.preference.chunks,
).then((sources) => {
//dispatch streaming sources
dispatch(
@@ -83,6 +85,7 @@ export const fetchAnswer = createAsyncThunk(
state.conversation.queries,
state.conversation.conversationId,
state.preference.prompt.id,
+ state.preference.chunks,
);
if (answer) {
let sourcesPrepped = [];
diff --git a/frontend/src/preferences/preferenceSlice.ts b/frontend/src/preferences/preferenceSlice.ts
index 0aa8b3b5..dc72fae1 100644
--- a/frontend/src/preferences/preferenceSlice.ts
+++ b/frontend/src/preferences/preferenceSlice.ts
@@ -10,6 +10,7 @@ interface Preference {
apiKey: string;
prompt: { name: string; id: string; type: string };
selectedDocs: Doc | null;
+ chunks: string;
sourceDocs: Doc[] | null;
conversations: { name: string; id: string }[] | null;
}
@@ -17,6 +18,7 @@ interface Preference {
const initialState: Preference = {
apiKey: 'xxx',
prompt: { name: 'default', id: 'default', type: 'public' },
+ chunks: '2',
selectedDocs: {
name: 'default',
language: 'default',
@@ -51,6 +53,9 @@ export const prefSlice = createSlice({
setPrompt: (state, action) => {
state.prompt = action.payload;
},
+ setChunks: (state, action) => {
+ state.chunks = action.payload;
+ },
},
});
@@ -60,6 +65,7 @@ export const {
setSourceDocs,
setConversations,
setPrompt,
+ setChunks,
} = prefSlice.actions;
export default prefSlice.reducer;
@@ -91,6 +97,16 @@ prefListenerMiddleware.startListening({
},
});
+prefListenerMiddleware.startListening({
+ matcher: isAnyOf(setChunks),
+ effect: (action, listenerApi) => {
+ localStorage.setItem(
+ 'DocsGPTChunks',
+ JSON.stringify((listenerApi.getState() as RootState).preference.chunks),
+ );
+ },
+});
+
export const selectApiKey = (state: RootState) => state.preference.apiKey;
export const selectApiKeyStatus = (state: RootState) =>
!!state.preference.apiKey;
@@ -105,3 +121,4 @@ export const selectConversations = (state: RootState) =>
export const selectConversationId = (state: RootState) =>
state.conversation.conversationId;
export const selectPrompt = (state: RootState) => state.preference.prompt;
+export const selectChunks = (state: RootState) => state.preference.chunks;
diff --git a/frontend/src/store.ts b/frontend/src/store.ts
index 234cc8e9..c217648e 100644
--- a/frontend/src/store.ts
+++ b/frontend/src/store.ts
@@ -8,11 +8,13 @@ import {
const key = localStorage.getItem('DocsGPTApiKey');
const prompt = localStorage.getItem('DocsGPTPrompt');
const doc = localStorage.getItem('DocsGPTRecentDocs');
+const chunks = localStorage.getItem('DocsGPTChunks');
const store = configureStore({
preloadedState: {
preference: {
apiKey: key ?? '',
+ chunks: JSON.parse(chunks ?? '2').toString(),
selectedDocs: doc !== null ? JSON.parse(doc) : null,
prompt:
prompt !== null
diff --git a/frontend/src/upload/Upload.tsx b/frontend/src/upload/Upload.tsx
index dae5656b..45fc4e1a 100644
--- a/frontend/src/upload/Upload.tsx
+++ b/frontend/src/upload/Upload.tsx
@@ -17,10 +17,18 @@ export default function Upload({
const [docName, setDocName] = useState('');
const [urlName, setUrlName] = useState('');
const [url, setUrl] = useState('');
+ const [redditData, setRedditData] = useState({
+ client_id: '',
+ client_secret: '',
+ user_agent: '',
+ search_queries: [''],
+ number_posts: 10,
+ });
const urlOptions: { label: string; value: string }[] = [
{ label: 'Crawler', value: 'crawler' },
// { label: 'Sitemap', value: 'sitemap' },
{ label: 'Link', value: 'url' },
+ { label: 'Reddit', value: 'reddit' },
];
const [urlType, setUrlType] = useState<{ label: string; value: string }>({
label: 'Link',
@@ -163,7 +171,6 @@ export default function Upload({
};
const uploadRemote = () => {
- console.log('here');
const formData = new FormData();
formData.append('name', urlName);
formData.append('user', 'local');
@@ -171,6 +178,13 @@ export default function Upload({
formData.append('source', urlType?.value);
}
formData.append('data', url);
+ if (
+ redditData.client_id.length > 0 &&
+ redditData.client_secret.length > 0
+ ) {
+ formData.set('name', 'other');
+ formData.set('data', JSON.stringify(redditData));
+ }
const apiHost = import.meta.env.VITE_API_HOST;
const xhr = new XMLHttpRequest();
xhr.upload.addEventListener('progress', (event) => {
@@ -202,6 +216,19 @@ export default function Upload({
['.docx'],
},
});
+ const handleChange = (e: React.ChangeEvent) => {
+ const { name, value } = e.target;
+ if (name === 'search_queries' && value.length > 0) {
+ setRedditData({
+ ...redditData,
+ [name]: value.split(',').map((item) => item.trim()),
+ });
+ } else
+ setRedditData({
+ ...redditData,
+ [name]: value,
+ });
+ };
let view;
if (progress?.type === 'UPLOAD') {
view = ;
@@ -281,30 +308,102 @@ export default function Upload({
setUrlType(value)
}
/>
- setUrlName(e.target.value)}
- >
-
-
- Name
-
-
- setUrl(e.target.value)}
- >
-
-
- Link
-
-
+ {urlType.label !== 'Reddit' ? (
+ <>
+ setUrlName(e.target.value)}
+ >
+
+
+ Name
+
+
+ setUrl(e.target.value)}
+ >
+
+
+ Link
+
+
+
+ ) : (
+ <>
+
+
+
+ Client ID
+
+
+
+
+
+ Client secret
+
+
+
+
+
+ User agent
+
+
+
+
+
+ Search queries
+
+
+
+
+
+ Number of posts
+
+
+
+ )}
)}