Upload 2 files

app.py

@@ -1,5 +1,7 @@
-from fastapi import FastAPI
-from transformers import pipeline
+from langchain_huggingface import HuggingFaceEndpoint
+repo_id="mistralai/Mistral-7B-Instruct-v0.2"
+
+llm=HuggingFaceEndpoint(repo_id=repo_id,max_length=128,temperature=0.7)
  
 # Create a new FastAPI app instance
 app = FastAPI()
@@ -7,8 +9,15 @@ app = FastAPI()
 # Initialize the text generation pipeline
 # This function will be able to generate text
 # given an input.
-pipe = pipeline("text2text-generation", 
-model="google/flan-t5-small")
+
+
+from langchain import PromptTemplate, LLMChain
+
+
+template = """Question: {question}
+Answer: Let's think step by step."""
+prompt = PromptTemplate(template=template, input_variables=["question"])
+llm_chain=LLMChain(llm=llm,prompt=prompt)
 
 @app.get("/")
 def read_root():
@@ -26,7 +35,7 @@ def generate(text: str):
     can be found [here](<https://huggingface.co/google/flan-t5-small>).
     """
     # Use the pipeline to generate text from the given input text
-    output = pipe(text)
+    output=llm_chain.invoke(text)
      
     # Return the generated text in a JSON response
-    return {"output": output[0]["generated_text"]}
+    return {"output": output["text"]}

requirements.txt

@@ -3,4 +3,6 @@ requests==2.27.*
 uvicorn[standard]==0.17.*
 sentencepiece==0.1.*
 torch==1.11.*
-transformers==4.*
+transformers==4.*
+langchain-huggingface
+langchain