added trials

app.py

@@ -10,6 +10,27 @@ from enum import Enum
 os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
 client = OpenAI()
 
+# These are the necessary components that make up the Trials 
+class Variables(BaseModel):
+    controlled: List[str] = Field(..., title="Controlled Variables", description="A list of controlled variables, which will be constant (controlled) across all trials")
+    independent: List[str] = Field(..., title="Independent Variables", description="A list of independent variables (ie treatments), which will be intentionally varied across one or more trials")
+    outcome: List[str] = Field(..., title="Outcome Variables", description="A list of outcome variables (ie dependent or response variables)")
+
+class Treatment(BaseModel):
+    name: str = Field(..., title="Name", description="The treatment name")
+    description: str = Field(..., title="Description", description="The treatment description, including the conditions within this treatment")
+    crops: List[str] = Field(..., title="Crops", description="A list of crops being tested in this treatment")
+    fields: List[str] = Field(..., title="Fields", description="A list of fields in which this treatment has occured or will occur")
+    learnings: List[str] = Field(..., title="Learnings", description="A list of lessons learned from this experiment")
+    variables: Variable = Field(..., title="Variables", description="Variables (ie factors) in this experiment. Some variables are constant (controlled) and some will vary in order to learn something (independent)")
+    confoundingFactors = List[str] = Field(..., title="Confounding Factors", description="A list of factors which may impact the outcomes of the experiment that were not planned for")
+
+class Trial(BaseModel):
+    name: str = Field(..., title="Name", description="The name of this trial") 
+    description: str = Field(..., title="Description", description="A description of this trial") 
+    treatments: List[Treatment] = Field(..., title="Treatments", description="A list of different treatments (strips or blocks with the same conditions applied) performed by the partner") 
+
+#################################################################################
 # These are the necessary components that make up the Interactions
 class Role(str, Enum):
     PARTNER = 'partner'
@@ -28,6 +49,7 @@ class Interactions(BaseModel):
     nextSteps: List[str] = Field(..., title="Next Steps", description="List of individual next steps derived from the interaction")
     summary: str = Field(..., title="Summary", description="Summary of the interaction")
 
+#################################################################################
 # These are the components for Farm Activities, Fields, and Plantings
 class Status(str, Enum):
     ACTIVE = 'active'
@@ -119,7 +141,7 @@ def generate_json(specification, model_version):
 
     try:
         # Call OpenAI API to generate structured output based on prompt
-        response = client.beta.chat.completions.parse(
+        farm_info_response = client.beta.chat.completions.parse(
             model=model_version,  # Use GPT model that supports structured output
             messages=[
                 {"role": "system", "content": "Extract the farm information."},
@@ -128,29 +150,46 @@ def generate_json(specification, model_version):
             response_format=FarmActivities,
         )
         
-        generated_json = response.choices[0].message.parsed
-        print(generated_json) # debugging
+        farm_generated_json = farm_info_response.choices[0].message.parsed
+        print(farm_generated_json) # debugging
 
-        pretty_json = generated_json.json()
+        farm_pretty_json = farm_generated_json.json()
 
-        another_response = client.beta.chat.completions.parse(
+        interactions_response = client.beta.chat.completions.parse(
             model=model_version,  # Use GPT model that supports structured output
             messages=[
-                {"role": "system", "content": "Extract the farm information."},
+                {"role": "system", "content": "Extract the interactions information."},
                 {"role": "user", "content": specification}
             ],
             response_format=Interactions,
         )
         
-        another_generated_json = another_response.choices[0].message.parsed
-        print(another_generated_json) # debugging 2
+        interactions_generated_json = interactions_response.choices[0].message.parsed
+        print(interactions_generated_json) # debugging 2
+
+        interactions_pretty_json = interactions_generated_json.json()
+
+        if 'error' in response:
+            raise ValueError(f"API error: {response['error']['message']}")
+
+        trial_response = client.beta.chat.completions.parse(
+            model=model_version,  # Use GPT model that supports structured output
+            messages=[
+                {"role": "system", "content": "Extract the trial information."},
+                {"role": "user", "content": specification}
+            ],
+            response_format=Trial,
+        )
+        
+        trial_generated_json = trial_response.choices[0].message.parsed
+        print(trial_generated_json) # debugging 2
 
-        another_pretty_json = another_generated_json.json()
+        trial_pretty_json = trial_generated_json.json()
 
         if 'error' in response:
             raise ValueError(f"API error: {response['error']['message']}")
             
-        return pretty_json, another_pretty_json
+        return farm_pretty_json, interactions_pretty_json, trial_pretty_json
 
     except ValidationError as e:
         return {"error": str(e)}
@@ -265,8 +304,9 @@ with gr.Blocks() as demo:
     soil_data_input = gr.Textbox(label="Enter your soil data", placeholder="Description, Structure, Biology", visible=False)
     yield_data_input = gr.Textbox(label="Enter your yield data", placeholder="Quantity, Quality", visible=False)
     
-    output_box = gr.Textbox(label="Fields and Activities Output Data")
-    another_output_box = gr.Textbox(label="Interactions Output Data")
+    farm_output_box = gr.Textbox(label="Fields and Activities Output Data")
+    interactions_output_box = gr.Textbox(label="Interactions Output Data")
+    trials_output_box = gr.Textbox(label="Trials Output Data")
     
     def update_visibility(radio, additional_options):
         value = radio 
@@ -291,7 +331,7 @@ with gr.Blocks() as demo:
     submit_button.click(
         fn=process_specifications,
         inputs=[data_input, model_version_input, json_creation_input, additional_json_creation_options, field_data_input, planting_data_input, logs_data_input, soil_data_input, yield_data_input],
-        outputs=[output_box, another_output_box]
+        outputs=[farm_output_box, interactions_output_box, trials_output_box]
     )
 
     clear_button = gr.ClearButton(components=[data_input, model_version_input, json_creation_input, additional_json_creation_options, field_data_input, planting_data_input, logs_data_input, soil_data_input, yield_data_input])