dev/select-model (#3)

- update store (8d3ec3eb656cf071e2323996c56efe4a24038ac7)
- added NVDA User guide content and added filter QA (227586c56da02b455a5ae582995b32f51edf0553)
- update setup db setting (3ec177b9d193839dbf26cc86c0fd62713d982b72)
- can select model for GPT-4 (33db1831f7ee68f99d4ee9537dbfe7ea8b923ce3)
- Merge branch 'main' into dev/select-model (36dfa843b54092feeec7e9fd9000c29a89df8f08)

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from langchain.chains import RetrievalQA
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.llms import OpenAI
+from langchain.chat_models import ChatOpenAI
 from langchain.vectorstores import Qdrant
 from openai.error import InvalidRequestError
 from qdrant_client import QdrantClient
@@ -9,13 +10,24 @@ from config import DB_CONFIG
 
 
 PERSIST_DIR_NAME = "nvdajp-book"
+# MODEL_NAME = "text-davinci-003"
+# MODEL_NAME = "gpt-3.5-turbo"
+# MODEL_NAME = "gpt-4"
 
 
-def get_retrieval_qa(temperature: int, option: str) -> RetrievalQA:
+def get_retrieval_qa(model_name: str | None, temperature: int, option: str | None) -> RetrievalQA:
     embeddings = OpenAIEmbeddings()
     db_url, db_api_key, db_collection_name = DB_CONFIG
     client = QdrantClient(url=db_url, api_key=db_api_key)
     db = Qdrant(client=client, collection_name=db_collection_name, embeddings=embeddings)
+    if model_name is None:
+        model = "gpt-3.5-turbo"
+    elif model_name == "GPT-3.5":
+        model = "gpt-3.5-turbo"
+    elif model_name == "GPT-4":
+        model = "gpt-4"
+    else:
+        model = "gpt-3.5-turbo"
     if option is None or option == "All":
         retriever = db.as_retriever()
     else:
@@ -25,7 +37,13 @@ def get_retrieval_qa(temperature: int, option: str) -> RetrievalQA:
             }
         )
     return RetrievalQA.from_chain_type(
-        llm=OpenAI(temperature=temperature), chain_type="stuff", retriever=retriever, return_source_documents=True,
+        llm=ChatOpenAI(
+            model=model,
+            temperature=temperature
+        ),
+        chain_type="stuff",
+        retriever=retriever,
+        return_source_documents=True,
     )
 
 
@@ -42,8 +60,8 @@ def get_related_url(metadata):
         yield f'<p>URL: <a href="{url}">{url}</a> (category: {category})</p>'
 
 
-def main(query: str, option: str, temperature: int):
-    qa = get_retrieval_qa(temperature, option)
+def main(query: str, model_name: str, option: str, temperature: int):
+    qa = get_retrieval_qa(model_name, temperature, option)
     try:
         result = qa(query)
     except InvalidRequestError as e:
@@ -59,6 +77,7 @@ nvdajp_book_qa = gr.Interface(
     fn=main,
     inputs=[
         gr.Textbox(label="query"),
+        gr.Radio(["GPT-3.5", "GPT-4"], label="Model", info="選択なしで「3.5」を使用"),
         gr.Radio(["All", "ja-book", "ja-nvda-user-guide", "en-nvda-user-guide"], label="絞り込み", info="ドキュメント制限する?"),
         gr.Slider(0, 2)
     ],