Update app.py

app.py

@@ -97,26 +97,16 @@ def get_conversational_chain(retriever):
     Answer:
     """
     #model = ChatGoogleGenerativeAI(model="gemini-pro", temperature=0.3, google_api_key=GOOGLE_API_KEY)
-    #llm = pipeline(task="text-generation", model='google/gemma-1.1-2b-it')
-    #llm= pipeline("text-generation", model="nvidia/Llama3-ChatQA-1.5-8B")
     #repo_id='meta-llama/Meta-Llama-3-70B'
     #repo_id = 'mistralai/Mixtral-8x7B-Instruct-v0.1'
     #repo_id= 'nvidia/Llama3-ChatQA-1.5-8B'
     #repo_id= 'google/gemma-1.1-2b-it'
-    #llm = HuggingFaceEndpoint(repo_id=repo_id, temperature=0.3,token = HUGGINGFACEHUB_API_TOKEN)
-    #tokenizer = AutoTokenizer.from_pretrained("google/gemma-1.1-2b-it")
-    #llm = AutoModelForCausalLM.from_pretrained("google/gemma-1.1-2b-it")
-    #llm = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct", trust_remote_code=True, token=access_token)
-    #llm = pipeline("text-generation", model="google/gemma-1.1-2b-it")
-    #llm = HuggingFacePipeline.from_model_id(
-    #model_id="gpt2",
-    #task="text-generation",
-    #pipeline_kwargs={"max_new_tokens": 10})
-    #from langchain_community.llms import HuggingFaceHub
+
 
     llm = HuggingFaceHub(
     #repo_id="HuggingFaceH4/zephyr-7b-beta",
-    repo_id = "mistralai/Mistral-7B-v0.1",
+    #repo_id = "mistralai/Mistral-7B-v0.1",
+    repo_id="microsoft/Phi-3-small-128k-instruct",
     huggingfacehub_api_token=os.getenv("HUGGINGFACE_API_KEY"),
     task="text-generation",
     )