Create resource.py

resource.py

@@ -0,0 +1,31 @@
+from langchain import PromptTemplate, LLMChain
+from huggingface_hub import hf_hub_download
+from langchain.llms import GPT4All
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+import os
+
+
+template ="""
+You are a friendly chatbot assistant you are going to evaluate a Github Repo i analysed all the repos and made a report
+i'm gonna give a report you just refer the below table
+Table:
+score                 Risk
+1 - 5                 Low - Simple block
+6 - 10                Low - Well structured and stable block
+11 - 20               Moderate - Slightly complex block
+21 - 30               More than moderate - More complex block
+31 - 40               High - Complex block, alarming
+41+                   Very high - Error-prone, unstable block
+based on the score and you have to return only one most complex repo which has more score from report 
+when the score is high thats the complex repo and
+if all the repos are at the same score choose randomly one
+Report: {question}
+Answer:"""
+
+
+prompt = PromptTemplate(template=template, input_variables=["question"])
+
+#hf_hub_download(repo_id="dnato/ggml-gpt4all-j-v1.3-groovy.bin", filename="ggml-gpt4all-j-v1.3-groovy.bin", local_dir="/code")
+local_path= os.getcwd() + "/ggml-gpt4all-j-v1.3-groovy.bin"
+llm = GPT4All(model=local_path,callbacks=[StreamingStdOutCallbackHandler()] )
+llm_chain = LLMChain(prompt=prompt, llm=llm)