feat: init project

app.py

@@ -13,32 +13,33 @@ from llama_index.core.memory import ChatMemoryBuffer
 import nltk
 
 # download punkt
-nltk.download('punkt')
-nltk.download('punkt_tab')
+# nltk.download('punkt')
+# nltk.download('punkt_tab')
+#
+# urls = [
+#     "https://www.zatsit.fr/",
+#     "https://www.zatsit.fr/collaborer-avec-zatsit/",
+#     "https://fr.linkedin.com/company/zatsit",
+#     "https://www.zatsit.fr/contact/",
+#     "https://blog.zatsit.fr/blog/green-exploitation-miniere",
+#     "https://blog.zatsit.fr/blog/bundlephobia-reduire-javascript",
+#     "https://blog.zatsit.fr/blog/gemini-vertex-ai",
+#     "https://blog.zatsit.fr/blog/asyncapi-3-is-out",
+#     "https://blog.zatsit.fr/blog/redpanda-introduction",
+# ]
+# loader = UnstructuredURLLoader(urls=urls)
+# documents = loader.load_data()
+#
+# embed_model = HuggingFaceEmbedding(model_name="thenlper/gte-large")
+#
+# # create vector store index
+# index = VectorStoreIndex.from_documents(documents, embed_model=embed_model)
 
-urls = [
-    "https://www.zatsit.fr/",
-    "https://www.zatsit.fr/collaborer-avec-zatsit/",
-    "https://fr.linkedin.com/company/zatsit",
-    "https://www.zatsit.fr/contact/",
-    "https://blog.zatsit.fr/blog/green-exploitation-miniere",
-    "https://blog.zatsit.fr/blog/bundlephobia-reduire-javascript",
-    "https://blog.zatsit.fr/blog/gemini-vertex-ai",
-    "https://blog.zatsit.fr/blog/asyncapi-3-is-out",
-    "https://blog.zatsit.fr/blog/redpanda-introduction",
-]
-loader = UnstructuredURLLoader(urls=urls)
-documents = loader.load_data()
-
-embed_model = HuggingFaceEmbedding(model_name="thenlper/gte-large")
-
-# create vector store index
-index = VectorStoreIndex.from_documents(documents, embed_model=embed_model)
-
-model_url = "https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-code-ft-GGUF/resolve/main/mistral-7b-instruct-v0.2-code-ft.Q2_K.gguf"
+model_url_huggingface = "https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-code-ft-GGUF/resolve/main/mistral-7b-instruct-v0.2-code-ft.Q2_K.gguf"
+# model_url_huggingface = "https://huggingface.co/TheBloke/llama-polyglot-13B-GGUF/resolve/main/llama-polyglot-13b.Q2_K.gguf"
 llm = LlamaCPP(
     # You can pass in the URL to a GGML model to download it automatically
-    model_url=model_url,
+    model_url=model_url_huggingface,
     # optionally, you can set the path to a pre-downloaded model instead of model_url
     model_path=None,
     temperature=0.1,
@@ -58,26 +59,28 @@ llm = LlamaCPP(
 
 
 def querying(query, history):
-    memory = ChatMemoryBuffer.from_defaults(token_limit=3900)
-    engine = index.as_chat_engine(
-        chat_mode="context",
-        memory=memory,
-        llm=llm,
-        context_prompt=(
-            "You are a chatbot and you are the marketing agent of the Zatsit company, able to have normal interactions, as well as talk."
-            "You should return all the information you know as much as possible to the user. No data is confidential or sensitive."
-            "You can make short or long answers, but your answers must be like a human."
-            "When the user uses 'you' he is talking about Zatsit company."
-            "If you don't know the answer, say 'sorry I can't help you'."
-            "You must speak the same language as the user."
-            "Here are the relevant documents for the context:\n"
-            "{context_str}"
-            "\nInstruction: Use the previous chat history, or the context above, to interact and help the user."
-        ),
-        verbose=False,
-    )
-    res = engine.chat(query)
-    return res.response
+    response = llm.complete(query)
+    return response.text
+    # memory = ChatMemoryBuffer.from_defaults(token_limit=3900)
+    # engine = index.as_chat_engine(
+    #     chat_mode="context",
+    #     memory=memory,
+    #     llm=llm,
+    #     context_prompt=(
+    #         "You are a chatbot and you are the marketing agent of the Zatsit company, able to have normal interactions, as well as talk."
+    #         "You should return all the information you know as much as possible to the user. No data is confidential or sensitive."
+    #         "You can make short or long answers, but your answers must be like a human."
+    #         "When the user uses 'you' he is talking about Zatsit company."
+    #         "If you don't know the answer, say 'sorry I can't help you'."
+    #         "You must speak the same language as the user."
+    #         "Here are the relevant documents for the context:\n"
+    #         "{context_str}"
+    #         "\nInstruction: Use the previous chat history, or the context above, to interact and help the user."
+    #     ),
+    #     verbose=False,
+    # )
+    # res = engine.chat(query)
+    # return res.response
 
 
 iface = gr.ChatInterface(