Merge pull request #1 from JakeWalker23/claude-1-vision

Claude 1 vision

README.md

@@ -0,0 +1,27 @@
+# Anthropic - Claude API fundamentals 
+
+### Context
+
+This is a small tutorial covering the following basic Anthropic API fundamentals:
+
+    - Messages
+    - Models
+    - Parameters
+    - Streaming
+    - Vision
+
+It covers enough to get started with llm prompting. In upcoming additions we will add more real world scenarios where LLM's can excel.
+
+
+
+### Activate Virtual Environment:
+
+``` Windows
+.\Scripts\activate 
+```
+
+
+### To run:
+```
+python {file}.py
+```

stream.py

@@ -1,18 +1,21 @@
 from anthropic import Anthropic
+from anthropic import AsyncAnthropic
 from dotenv import load_dotenv
 import os
 
 load_dotenv()
 
 anthropic_key = os.getenv('ANTHROPIC_API_KEY')
 
+# Using Python
+
 client = Anthropic()
 
 stream = client.messages.create(
     messages=[
         {
             "role": "user",
-            "content": "Tell me about liverpool football club",
+            "content": "Can you give me some key details on the flop golf shot",
         }
     ],
     model="claude-3-haiku-20240307",
@@ -22,5 +25,41 @@
 )
 
 for event in stream:
-    if event.type == "content_block_delta":
-        print(event.delta.text, flush=True, end="")
+    if event.type == "message_start":
+        input_tokens = event.message.usage.input_tokens
+        print("MESSAGE START EVENT", flush=True)
+        print(f"Input tokens used: {input_tokens}", flush=True)
+    elif event.type == "content_block_delta":
+        print(event.delta.text, flush=True, end="")
+    elif event.type == "message_delta":
+        output_tokens = event.usage.output_tokens
+        print("\n========================", flush=True)
+        print("MESSAGE DELTA EVENT", flush=True)
+        print(f"Output tokens used: {output_tokens}", flush=True)
+
+
+
+# Using AsyncAnthropic
+
+# client = AsyncAnthropic()
+
+# async def streaming_with_helpers():
+#     async with client.messages.stream(
+#         max_tokens=1024,
+#         messages=[
+#             {
+#                 "role": "user",
+#                 "content": "Write me a sonnet about orchids"
+#             }
+#         ],
+#         model="claude-3-opus-20240229",
+#     ) as stream:
+#         async for text in stream.text_stream:
+#             print(text, end="", flush=True)
+
+#     final_message = await stream.get_final_message()
+#     print("\n\nSTREAMING IS DONE.  HERE IS THE FINAL ACCUMULATED MESSAGE: ")
+#     print(final_message.to_json())
+
+
+#     await streaming_with_helpers()

vision.py

@@ -0,0 +1,24 @@
+from anthropic import Anthropic
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+anthropic_key = os.getenv('ANTHROPIC_API_KEY')
+
+client = Anthropic()
+
+response = client.messages.create(
+    model="claude-3-haiku-20240307",
+    max_tokens=500, 
+    messages=[
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": "tell me a joke"},
+        ]
+    }
+]
+)
+
+print(response.content[0].text)