Updating the tutorial to use the V5 API

README.md

@@ -1,6 +1,6 @@
 # Humanloop API Quickstart - Python example app
 
-This is an example app that shows you how to use the Humanloop API in a GPT-3 app. It uses the [Flask](https://flask.palletsprojects.com/en/2.2.x/) web framework and [Humanloop](https://humanloop.com) for data logging and model improvement. Check out the tutorial or follow the instructions below to get set up.
+This is an example app that shows you how to use the Humanloop API in a GPT-4 app. It uses the [Flask](https://flask.palletsprojects.com/en/2.3.x/) web framework and [Humanloop](https://humanloop.com) for data logging and model improvement. Check out the tutorial or follow the instructions below to get set up.
 
 ## Setup
 
@@ -30,15 +30,15 @@ This is an example app that shows you how to use the Humanloop API in a GPT-3 ap
 6. Make a copy of the example environment variables file
 
    ```bash
-   $ cp .env.example .env
+   $ cp .example.env .env
    ```
 
-7. Add your [OpenAI API key](https://beta.openai.com/account/api-keys) and [Humanloop API key](https://app.humanloop.com/llama/settings) to the newly created `.env` file
+7. Add your [OpenAI API key](https://platform.openai.com/api-keys) and [Humanloop API key](https://app.humanloop.com/account/api-keys) to the newly created `.env` file
 
 8. Run the app
 
    ```bash
    $ flask --debug run
    ```
 
-You should now be able to access the app at [http://localhost:5000](http://localhost:5000)! For the full context behind this example app, check out the [tutorial](https://beta.openai.com/docs/quickstart).
+You should now be able to access the app at [http://localhost:5000](http://localhost:5000)! For the full context behind this example app, check out the [tutorial](https://platform.openai.com/docs/quickstart).

app.py

@@ -2,99 +2,111 @@
 
 from humanloop import Humanloop
 from flask import Flask, redirect, render_template, request, url_for
+from dotenv import load_dotenv
 
+
+load_dotenv()
 app = Flask(__name__)
 
 HUMANLOOP_API_KEY = os.getenv("HUMANLOOP_API_KEY")
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-humanloop = Humanloop(
-    api_key=HUMANLOOP_API_KEY,
-)
+hl = Humanloop(api_key=HUMANLOOP_API_KEY)
 
 
 @app.route("/", methods=["GET"])
 def index():
     return render_template(
         "index.html",
         result=request.args.get("result"),
-        data_id=request.args.get("data_id"),
-        feedback=request.args.get("feedback"),
-        copied=request.args.get("copied", False),
+        log_id=request.args.get("log_id"),
+        evaluation=request.args.get("evaluation"),
     )
 
 
 @app.route("/get-question", methods=["POST"])
 def get_question():
-    # Make the request to GPT-3
+    # Make the request to GPT-4
     expert = request.form["Expert"]
     topic = request.form["Topic"]
 
-    # hl.complete automatically logs the data to your project.
-    complete_response = humanloop.complete_deployed(
-        project="learn-anything",
+    # hl.prompts.call automatically logs the data to your prompt.
+    call_response = hl.prompts.call(
+        path="learn-anything",
         inputs={"expert": expert, "topic": topic},
+        # If you havent previously created a prompt, you can uncomment the prompt template below
+        # prompt={
+        #     "template": [
+        #         {
+        #             "role": "system",
+        #             "content": "You are {{expert}}. Write a joke about {{topic}}.",
+        #         }
+        #     ],
+        #     "model": "gpt-4",
+        # },
         provider_api_keys={"openai": OPENAI_API_KEY},
     )
-    data_id = complete_response.body["data"][0]["id"]
-    result = complete_response.body["data"][0]["output"]
 
-    print("data_id from completion: ", data_id)
-    return redirect(url_for("index", result=result, data_id=data_id))
+    # The log_id is the ID of the log on Humanloop that was created by the call
+    log_id = call_response.id
+    log_response = call_response.logs[0]
+
+    return redirect(url_for("index", result=log_response.output, log_id=log_id))
 
 
 @app.route("/actions/thumbs-up", methods=["POST"])
 def thumbs_up():
-    data_id = request.args.get("data_id")
+    log_id = request.args.get("log_id")
+
+    # We fetch the log from Humanloop to find which prompt it's associated with
+    log = hl.logs.get(id=log_id)
+    prompt_id = log.prompt.id
+
+    # We fetch the prompt to find which evaluator it's associated with
+    prompt = hl.prompts.get(id=prompt_id)
 
-    # Send rating feedback to Humanloop
-    humanloop.feedback(type="rating", value="good", data_id=data_id)
-    print(f"Recorded 👍 feedback to datapoint: {data_id}")
+    # Note this will be empty if you haven't assigned a monitoring evaluator to your prompt
+    evaluator_id = prompt.evaluators[0].version_reference.file.id
+
+    # Send rating evaluation to Humanloop using the evaluator_id and log_id
+    hl.evaluators.log(parent_id=log_id, id=evaluator_id, judgment="2")
+    print(f"Recorded 👍 evaluation to log: {log_id}")
 
     return redirect(
         url_for(
             "index",
             result=request.args.get("result"),
-            data_id=data_id,
-            feedback="👍",
+            log_id=log_id,
+            evaluation="👍",
             copied=request.args.get("copied", False),
         )
     )
 
 
 @app.route("/actions/thumbs-down", methods=["POST"])
 def thumbs_down():
-    data_id = request.args.get("data_id")
-
-    # Send rating feedback to Humanloop
-    humanloop.feedback(type="rating", value="bad", data_id=data_id)
-    print(f"Recorded 👎 feedback to datapoint: {data_id}")
+    log_id = request.args.get("log_id")
 
-    return redirect(
-        url_for(
-            "index",
-            result=request.args.get("result"),
-            data_id=data_id,
-            feedback="👎",
-            copied=request.args.get("copied", False),
-        )
-    )
+    # We fetch the log from Humanloop to find which prompt it's associated with
+    log = hl.logs.get(id=log_id)
+    prompt_id = log.prompt.id
 
+    # We fetch the prompt to find which evaluator it's associated with
+    prompt = hl.prompts.get(id=prompt_id)
 
-@app.route("/actions/copy", methods=["POST"])
-def feedback():
-    data_id = request.args.get("data_id")
+    # Note this will be empty if you haven't assigned a monitoring evaluator to your prompt
+    evaluator_id = prompt.evaluators[0].version_reference.file.id
 
-    # Send implicit feedback to Humanloop
-    humanloop.feedback(type="action", value="copy", data_id=data_id)
-    print(f"Recorded implicit feedback that user copied to datapoint: {data_id}")
+    # Send rating evaluation to Humanloop using the evaluator_id and log_id
+    hl.evaluators.log(parent_id=log_id, id=evaluator_id, judgment="1")
+    print(f"Recorded 👎 evaluation to log: {log_id}")
 
     return redirect(
         url_for(
             "index",
             result=request.args.get("result"),
-            data_id=data_id,
-            feedback=request.args.get("feedback"),
-            copied=True,
+            log_id=log_id,
+            evaluation="👎",
+            copied=request.args.get("copied", False),
         )
     )

requirements.txt

@@ -1,4 +1,4 @@
 Flask==2.3.3
-humanloop==0.5.6
-openai==0.27.8
-python-dotenv==1.0.0
+humanloop==0.8.0b6
+openai==1.42.0
+python-dotenv==1.0.1

templates/index.html

@@ -6,56 +6,47 @@
     href="{{ url_for('static', filename='learning.png') }}"
   />
   <link rel="stylesheet" href="{{ url_for('static', filename='main.css') }}" />
-  <script>
-    function copyToClipboard() {
-      const element = document.getElementById("result");
-      navigator.clipboard.writeText(element.textContent);
-    }
-  </script>
 </head>
 
 <body class="column">
   <a href="/" class="column">
-    <img src="{{ url_for('static', filename='learning.png') }}"  width=100 />
+    <img src="{{ url_for('static', filename='learning.png') }}" width="100" />
     <h3>Learn anything from anyone</h3>
   </a>
   <form class="input-form" action="/get-question" method="post">
-    <input type="text" name="Expert" placeholder="Enter the name of an expert" required />
+    <input
+      type="text"
+      name="Expert"
+      placeholder="Enter the name of an expert"
+      required
+    />
     <input type="text" name="Topic" placeholder="Enter a topic" required />
     <input type="submit" class="hover" value="Teach me!" />
   </form>
   {% if result %}
   <div class="result-wrapper">
     <div class="result" style="width: 500px" id="result">{{ result }}</div>
+  </div>
+  <div class="evaluation">
     <form
-      class="submit-form"
-      action="/actions/copy?data_id={{ data_id }}&result={{ result }}&feedback={{ feedback }}"
+      action="/actions/thumbs-up?log_id={{ log_id }}&result={{ result }}"
       method="post"
     >
       <button
         type="submit"
-        class="copy hover {{ 'submitted' if copied == 'True' }}"
-        title="Copy to clipboard"
-        onclick="copyToClipboard()"
+        class="hover {{ 'submitted' if evaluation == '👍' }}"
       >
-        📋
-      </button>
-    </form>
-  </div>
-  <div class="feedback">
-    <form
-      action="/actions/thumbs-up?data_id={{ data_id }}&result={{ result }}&copied={{ copied }}"
-      method="post"
-    >
-      <button type="submit" class="hover {{ 'submitted' if feedback == '👍' }}">
         👍
       </button>
     </form>
     <form
-      action="/actions/thumbs-down?data_id={{ data_id }}&result={{ result }}&copied={{ copied }}"
+      action="/actions/thumbs-down?log_id={{ log_id }}&result={{ result }}"
       method="post"
     >
-      <button type="submit" class="hover {{ 'submitted' if feedback == '👎' }}">
+      <button
+        type="submit"
+        class="hover {{ 'submitted' if evaluation == '👎' }}"
+      >
         👎
       </button>
     </form>