Update app.py

app.py

@@ -88,39 +88,51 @@ def data_ingestion(file_path):
 ########## CHAIN 1 norm text
 
 def chain1():
-    prompt_template = """Please provide a summary of the given study material. Summarize the key concepts, findings, and important details. 
-    Pay special attention to any definitions, theories, or conclusions presented in the text. 
-    Your summary should be concise yet comprehensive, capturing the main points of the study material.
-    Your job is to write a summary of the document such that every summary of the text is of 2 sentences.
-    here is the content of the section:
-    "{text}"
-
-    SUMMARY:"""
-    prompt = PromptTemplate.from_template(prompt_template)
-
-    refine_template = (
-        "Your job is to produce a final summary\n"
-        # "We have provided an existing summary up to a certain point: {existing_answer}\n"
-        "We have the opportunity to refine the existing summary"
-        "(only if needed) with some more context below.\n"
-        "------------\n"
-        "{text}\n"
-        "------------\n"
-        "Given the new context, refine the original summary in English"
-        "If the context isn't useful, return the original summary." )
-
-    refine_prompt = PromptTemplate.from_template(refine_template)
+    # prompt_template = """Please provide a summary of the given study material. Summarize the key concepts, findings, and important details. 
+    # Pay special attention to any definitions, theories, or conclusions presented in the text. 
+    # Your summary should be concise yet comprehensive, capturing the main points of the study material.
+    # Your job is to write a summary of the document such that every summary of the text is of 2 sentences.
+    # here is the content of the section:
+    # "{text}"
+
+    # SUMMARY:"""
+    # prompt = PromptTemplate.from_template(prompt_template)
+
+    # refine_template = (
+    #     "Your job is to produce a final summary\n"
+    #     # "We have provided an existing summary up to a certain point: {existing_answer}\n"
+    #     "We have the opportunity to refine the existing summary"
+    #     "(only if needed) with some more context below.\n"
+    #     "------------\n"
+    #     "{text}\n"
+    #     "------------\n"
+    #     "Given the new context, refine the original summary in English"
+    #     "If the context isn't useful, return the original summary." )
+
+    # refine_prompt = PromptTemplate.from_template(refine_template)
+    # chain1 = load_summarize_chain(
+    #     llm=HuggingFaceHub(repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
+    #                     model_kwargs={"temperature":1, "max_length":10000},
+    #                     huggingfacehub_api_token=api_token),
+    #     chain_type="refine",
+    #     question_prompt=prompt,
+    #     # refine_prompt=refine_prompt,
+    #     return_intermediate_steps=False,
+    #     input_key="input_documents",
+    #     output_key="output_text",
+    # )
     chain1 = load_summarize_chain(
-        llm=HuggingFaceHub(repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        llm=HuggingFaceHub(repo_id="sshleifer/distilbart-cnn-12-6",
                         model_kwargs={"temperature":1, "max_length":10000},
                         huggingfacehub_api_token=api_token),
-        chain_type="refine",
-        question_prompt=prompt,
-        # refine_prompt=refine_prompt,
-        return_intermediate_steps=False,
+        chain_type="stuff",
+    #     question_prompt=prompt,
+    #     # refine_prompt=refine_prompt,
+    #     return_intermediate_steps=False,
         input_key="input_documents",
         output_key="output_text",
     )
+    
     return chain1
 
 # result = chain({"input_documents":split_docs}, return_only_outputs=True)