gurfinha

README.md

@@ -1,13 +1,12 @@
 ---
 title: Gurfagpt
-emoji: 🐢
+emoji: 🧠
 colorFrom: blue
-colorTo: yellow
+colorTo: pink
 sdk: gradio
 sdk_version: 3.28.2
 app_file: app.py
 pinned: false
-license: gpl-3.0
+license: openrail++
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,74 @@
+
+
+import os
+
+import gradio as gr
+
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import FAISS
+from langchain.document_loaders import TextLoader
+
+embeddings = OpenAIEmbeddings()
+
+db = FAISS.load_local("./faiss_index", embeddings)
+
+query = "Who is responsible for conducting the pre-flight briefing to the Cabin Crew?"
+docs = db.similarity_search(query)
+docs[1]
+
+from langchain.memory import ConversationBufferMemory
+memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True,output_key='answer')
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.llms import OpenAI
+from langchain.chains import ConversationalRetrievalChain
+from langchain import PromptTemplate
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import RetrievalQAWithSourcesChain
+from langchain.chains import ChatVectorDBChain
+
+
+chainqa = RetrievalQAWithSourcesChain.from_chain_type(
+    ChatOpenAI(temperature=0,model_name="gpt-3.5-turbo",max_tokens=150), 
+    chain_type="stuff", 
+    reduce_k_below_max_tokens=True,
+    memory=memory,
+    retriever=db.as_retriever())
+
+def bambolini(query):
+  bambolini_result = chainqa({"question": query }, return_only_outputs=True)
+  return bambolini_result
+
+title = 'GURFAGPT'
+description = """ Made with AI Lobs"""
+
+
+with gr.Blocks() as demo:
+
+    gr.Markdown(f'# {title}')
+    gr.Markdown(f'### {description}')
+
+    gr.Markdown("")
+    text_input = gr.Textbox(label="Question")
+
+    with gr.Tab("Bambolini AI"):
+        bambo_output = gr.JSON()
+        bambo_button = gr.Button("Ask Bambolini")
+    # with gr.Tab("Carabinieri AI"):
+    #     cari_output = gr.JSON()
+    #     cari_button = gr.Button("Ask Caribinieri")
+    # with gr.Tab("Gurfa AI"):
+    #     gurfa_output = gr.JSON()
+    #     gurfa_button = gr.Button("Ask Gurfinha")
+
+
+    bambo_button.click(bambolini, inputs=text_input, outputs=bambo_output)
+    # cari_button.click(bambolini, inputs=text_input, outputs=cari_output)
+    # gurfa_button.click(bambolini, inputs=text_input, outputs=gurfa_output)
+
+        
+demo.launch(share=True,debug=True)

requirements.txt

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+langchain
+pypdf
+openai
+faiss-cpu
+tiktoken
+gradio