update-llm-cookbooks-phi-654

cookbook/llms/anyscale/README.md

@@ -12,13 +12,13 @@ source ~/.venvs/aienv/bin/activate
 2. Install libraries
 
 ```shell
-pip install -U phidata openai
+pip install -U openai phidata
 ```
 
 3. Export `ANYSCALE_API_KEY`
 
-```text
-export ANYSCALE_API_KEY=<anyscale-api-key>
+```shell
+export ANYSCALE_API_KEY=***
 ```
 
 4. Test Anyscale Assistant

cookbook/llms/anyscale/assistant.py

@@ -5,4 +5,4 @@
     llm=Anyscale(model="mistralai/Mixtral-8x7B-Instruct-v0.1"),
     description="You help people with their health and fitness goals.",
 )
-assistant.print_response("Share a 2 sentence quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Share a 2 sentence quick and healthy breakfast recipe.", markdown=True)

cookbook/llms/anyscale/assistant_stream_off.py

@@ -2,7 +2,7 @@
 from phi.llm.anyscale import Anyscale
 
 assistant = Assistant(
-    llm=Anyscale(),
+    llm=Anyscale(model="mistralai/Mixtral-8x7B-Instruct-v0.1"),
     description="You help people with their health and fitness goals.",
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", stream=False, markdown=True)
+assistant.print_response("Share a 2 sentence quick and healthy breakfast recipe.", markdown=True, stream=False)

cookbook/llms/azure_openai/README.md

@@ -18,11 +18,11 @@ pip install -U phidata openai
 3. Export Azure Credentials (`AZURE_OPENAI_API_KEY` and `AZURE_OPENAI_ENDPOINT` are required)
 
 ```shell
-export AZURE_OPENAI_API_KEY=<azure-api-key>
-export AZURE_OPENAI_ENDPOINT=<azure-endpoint>
+export AZURE_OPENAI_API_KEY=***
+export AZURE_OPENAI_ENDPOINT=***
 # Optional:
-# export AZURE_OPENAI_API_VERSION=<openai-api-version>
-# export AZURE_DEPLOYMENT=<azure_deployment>
+# export AZURE_OPENAI_API_VERSION=***
+# export AZURE_DEPLOYMENT=***
 ```
 
 4. Test Azure Assistant

cookbook/llms/azure_openai/assistant.py

@@ -2,7 +2,7 @@
 from phi.llm.azure import AzureOpenAIChat
 
 assistant = Assistant(
-    llm=AzureOpenAIChat(model="gpt-35-turbo"),  # model="deployment_name"
+    llm=AzureOpenAIChat(model="gpt-35-turbo"),
     description="You help people with their health and fitness goals.",
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Share a 2 sentence quick and healthy breakfast recipe.", markdown=True)

cookbook/llms/azure_openai/assistant_stream_off.py

@@ -2,7 +2,7 @@
 from phi.llm.azure import AzureOpenAIChat
 
 assistant = Assistant(
-    llm=AzureOpenAIChat(model="gpt-35-turbo"),  # model="deployment_name"
+    llm=AzureOpenAIChat(model="gpt-35-turbo"),
     description="You help people with their health and fitness goals.",
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)
+assistant.print_response("Share a 2 sentence quick and healthy breakfast recipe.", markdown=True, stream=False)

cookbook/llms/claude/README.md

@@ -39,12 +39,6 @@ python cookbook/llms/claude/assistant_stream_off.py
 
 ### 5. Run Assistant with Tools
 
-- Web search
-
-```shell
-python cookbook/llms/claude/web_search.py
-```
-
 - YFinance
 
 ```shell

cookbook/llms/claude/assistant.py

@@ -1,8 +1,10 @@
 from phi.assistant import Assistant
+from phi.tools.duckduckgo import DuckDuckGo
 from phi.llm.anthropic import Claude
 
 assistant = Assistant(
     llm=Claude(model="claude-3-opus-20240229"),
-    description="You help people with their health and fitness goals.",
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Whats happening in France?", markdown=True)

cookbook/llms/claude/assistant_stream_off.py

@@ -1,8 +1,10 @@
 from phi.assistant import Assistant
+from phi.tools.duckduckgo import DuckDuckGo
 from phi.llm.anthropic import Claude
 
 assistant = Assistant(
     llm=Claude(model="claude-3-opus-20240229"),
-    description="You help people with their health and fitness goals.",
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)
+assistant.print_response("Whats happening in France?", markdown=True, stream=False)

cookbook/llms/claude/basic.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.anthropic import Claude
+
+assistant = Assistant(
+    llm=Claude(model="claude-3-haiku-20240307"),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)

cookbook/llms/claude/basic_stream_off.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.anthropic import Claude
+
+assistant = Assistant(
+    llm=Claude(model="claude-3-haiku-20240307"),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)

cookbook/llms/cohere/README.md

@@ -1,6 +1,6 @@
 # CohereChat function calling
 
-Currently "command-r" model supports function calling
+Currently Cohere's "command-r" and "command-r-plus" models supports function calling
 
 > Note: Fork and clone this repository if needed
 
@@ -14,7 +14,7 @@ source ~/.venvs/aienv/bin/activate
 ### 2. Export your CohereChat API Key
 
 ```shell
-export CO_API_KEY=xxx
+export CO_API_KEY=***
 ```
 
 ### 3. Install libraries

cookbook/llms/cohere/assistant.py

@@ -1,9 +1,10 @@
 from phi.assistant import Assistant
+from phi.tools.duckduckgo import DuckDuckGo
 from phi.llm.cohere import CohereChat
 
 assistant = Assistant(
     llm=CohereChat(model="command-r"),
-    description="You help people with their health and fitness goals.",
-    debug_mode=True,
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Whats happening in France?", markdown=True)

cookbook/llms/cohere/assistant_stream_off.py

@@ -1,9 +1,10 @@
 from phi.assistant import Assistant
+from phi.tools.duckduckgo import DuckDuckGo
 from phi.llm.cohere import CohereChat
 
 assistant = Assistant(
     llm=CohereChat(model="command-r"),
-    description="You help people with their health and fitness goals.",
-    debug_mode=True,
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)
+assistant.print_response("Whats happening in France?", markdown=True, stream=False)

cookbook/llms/cohere/basic.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.cohere import CohereChat
+
+assistant = Assistant(
+    llm=CohereChat(model="command-r"),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)

cookbook/llms/cohere/basic_stream_off.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.cohere import CohereChat
+
+assistant = Assistant(
+    llm=CohereChat(model="command-r"),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)

cookbook/llms/fireworks/README.md

@@ -1,4 +1,4 @@
-## Fireworks AI Function Calling
+## Fireworks AI
 
 > Note: Fork and clone this repository if needed
 
@@ -17,14 +17,14 @@ pip install -U openai yfinance exa_py duckduckgo-search streamlit phidata
 
 3. Export `FIREWORKS_API_KEY`
 
-```text
-export FIREWORKS_API_KEY=<fireworks-api-key>
+```shell
+export FIREWORKS_API_KEY=***
 ```
 
 > If you want to use Exa Search, export `EXA_API_KEY` as well
 
-```text
-export EXA_API_KEY=<exa-api-key>
+```shell
+export EXA_API_KEY=***
 ```
 
 4. Run streamlit app
@@ -60,7 +60,3 @@ python cookbook/llms/fireworks/pydantic_output.py
 ```shell
 python cookbook/llms/fireworks/tool_call.py
 ```
-
-```shell
-python cookbook/llms/fireworks/web_search.py
-```

cookbook/llms/fireworks/assistant.py

@@ -1,8 +1,10 @@
 from phi.assistant import Assistant
 from phi.llm.fireworks import Fireworks
+from phi.tools.duckduckgo import DuckDuckGo
 
 assistant = Assistant(
-    llm=Fireworks(),
-    description="You help people with their health and fitness goals.",
+    llm=Fireworks(), 
+    tools=[DuckDuckGo()], 
+    show_tool_calls=True
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Whats happening in France?", markdown=True)

cookbook/llms/fireworks/assistant_stream_off.py

@@ -1,8 +1,10 @@
 from phi.assistant import Assistant
 from phi.llm.fireworks import Fireworks
+from phi.tools.duckduckgo import DuckDuckGo
 
 assistant = Assistant(
-    llm=Fireworks(),
-    description="You help people with their health and fitness goals.",
+    llm=Fireworks(), 
+    tools=[DuckDuckGo()], 
+    show_tool_calls=True
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)
+assistant.print_response("Whats happening in France?", markdown=True, stream=False)

cookbook/llms/fireworks/basic.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.fireworks import Fireworks
+
+assistant = Assistant(
+    llm=Fireworks(),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)

cookbook/llms/fireworks/basic_stream_off.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.fireworks import Fireworks
+
+assistant = Assistant(
+    llm=Fireworks(),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)

cookbook/llms/groq/README.md

@@ -16,7 +16,7 @@ source ~/.venvs/aienv/bin/activate
 > Need to use OpenAI for embeddings as Groq doesn't support embeddings yet.
 
 ```shell
-export GROQ_API_KEY=xxx
+export GROQ_API_KEY=***
 export OPENAI_API_KEY=sk-***
 ```
 
@@ -28,20 +28,32 @@ pip install -r cookbook/llms/groq/requirements.txt
 
 4. Start pgvector
 
+> Install [docker desktop](https://docs.docker.com/desktop/install/mac-install/) first.
+
+- Run using a helper script
+
 ```shell
-phi start cookbook/llms/groq/resources.py -y
+./cookbook/run_pgvector.sh
 ```
 
-5. Run RAG App
+- OR run using the docker run command
 
 ```shell
-streamlit run cookbook/llms/groq/app.py
+docker run -d \
+  -e POSTGRES_DB=ai \
+  -e POSTGRES_USER=ai \
+  -e POSTGRES_PASSWORD=ai \
+  -e PGDATA=/var/lib/postgresql/data/pgdata \
+  -v pgvolume:/var/lib/postgresql/data \
+  -p 5532:5432 \
+  --name pgvector \
+  phidata/pgvector:16
 ```
 
-6. Stop pgvector
+5. Run RAG App
 
 ```shell
-phi stop cookbook/llms/groq/resources.py -y
+streamlit run cookbook/llms/groq/app.py
 ```
 
 ## Build AI Assistants with Groq
@@ -54,14 +66,6 @@ pip install -U groq phidata
 
 2. Run Assistant
 
-- stream on
-
 ```shell
 python cookbook/llms/groq/assistant.py
 ```
-
-- stream off
-
-```shell
-python cookbook/llms/groq/assistant_stream_off.py
-```

cookbook/llms/groq/assistant.py

@@ -1,9 +1,10 @@
 from phi.assistant import Assistant
+from phi.tools.duckduckgo import DuckDuckGo
 from phi.llm.groq import Groq
 
 assistant = Assistant(
     llm=Groq(model="mixtral-8x7b-32768"),
-    description="You help people with their health and fitness goals.",
-    # debug_mode=True,
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
 )
-assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)
+assistant.print_response("Whats happening in France?", markdown=True, stream=False)

cookbook/llms/groq/basic.py

@@ -0,0 +1,8 @@
+from phi.assistant import Assistant
+from phi.llm.groq import Groq
+
+assistant = Assistant(
+    llm=Groq(model="mixtral-8x7b-32768"),
+    description="You help people with their health and fitness goals.",
+)
+assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True)

cookbook/llms/groq/assistant_stream_off.py → cookbook/llms/groq/basic_stream_off.py

@@ -4,6 +4,5 @@
 assistant = Assistant(
     llm=Groq(model="mixtral-8x7b-32768"),
     description="You help people with their health and fitness goals.",
-    # debug_mode=True,
 )
 assistant.print_response("Share a quick healthy breakfast recipe.", markdown=True, stream=False)