feat: Uploaded Documentation, Updated Prompts & Some Code for model demo (#144)

* Added three new keys on hypothesis reasoning

* Updated two scenario rich text

* Uploaded Documentation & Further Improved Demo of Models

* Add docs

---------

Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>

rdagent/app/model_extraction_and_code/GeneralModel.py

@@ -31,7 +31,7 @@ class GeneralModelScenario(Scenario):
     @property
     def rich_style_description(self) -> str:
         return """
-# [General Model Research Co-Pilot] (#_scenario)
+# [Model Research & Development Co-Pilot] (#_scenario)
  
 ## [Overview](#_summary)
  

rdagent/components/proposal/prompts.yaml

@@ -10,12 +10,12 @@ hypothesis_gen:
     Here are the specifications: {{ hypothesis_specification }}
 
   user_prompt: |-
-    The user has made several hypothesis on this scenario and did several evaluation on them.
+    If it is not the first round, then the user has made several hypothesis on this scenario and did several evaluation on them.
     The former hypothesis and the corresponding feedbacks are as follows (focus on the last one & the new hypothesis that it provides and reasoning to see if you agree):
     {{ hypothesis_and_feedback }}
     To help you generate new {{targets}}, we have prepared the following information for you:
     {{ RAG }}
-    Please generate the new hypothesis based on the information above. Also generate the relevant keys for the reasoning and the distilled knowledge that follows. 
+    Please generate the new hypothesis based on the information above. Also generate the relevant keys for the reasoning and the distilled knowledge that follows. For those keys, in particular for knowledge, explain in the context of the specific scenario to build up domain knowledge in the specific field rather than genearl knowledge.
 
 hypothesis2experiment:
   system_prompt: |-

rdagent/scenarios/qlib/prompts.yaml

@@ -12,12 +12,12 @@ hypothesis_and_feedback: |-
 hypothesis_output_format: |-
   The output should follow JSON format. The schema is as follows:
   {
-    "hypothesis": "The new hypothesis generated based on the information provided.",
+    "hypothesis": "The new hypothesis generated based on the information provided.",  # Note that this should focus on model architecture, not training process or feature engineering or anything else
     "reason": "The reason why you generate this hypothesis. It should be comprehensive and logical. It should cover the other keys below and extend them.",
     "concise_reason": Two line summary. First line focuses on the a concise justification for the change. 2nd Line learns from first line and previous experiences (hypothesis & experiments & code & feedbacks) to generalise a knowledge statement (use tend to/because/if/generally/etc. ). This is the summary of the three keys below. 
     "concise_observation": One line summary. It focuses on the observation of the given scenario, data characteristics, or previous experiences (failures & succeses).
     "concise_justification": One line summary. It focuses on the justification for the change in new hypothesis and the route of exploration supporting the growth of the hypothesis, based on the observation. 
-    "concise_knowledge": One line summary. It focuses on a transferable knowledege that comes with the new hypothesis. Use conditional grammar. eg. "If...., ..; When..., .; and etc"
+    "concise_knowledge": One line summary. It focuses on a transferable knowledege that comes with the new hypothesis. Use conditional grammar. eg. "If...., ..; When..., .; and etc" Make sure that you state things clearly without ambiguity. Eg. avoid saying "previous hypothesis", because one wouldn't know what that is.
   }
 
 model_hypothesis_specification: |-