adding support for gemini on linux/wsl distros

.gitignore

@@ -120,6 +120,7 @@ celerybeat.pid
 *.sage.py
 
 # Environments
+examples/pipelines/demo-question-answering/.env
 **/.env
 .venv
 env/

examples/pipelines/demo-question-answering/.env.example

@@ -0,0 +1 @@
+GEMINI_API_KEY=YOUR_GEMINI_API_KEY

examples/pipelines/demo-question-answering/app.py

@@ -1,10 +1,11 @@
 import logging
 import sys
-
+import os
 import click
 import pathway as pw
 import yaml
 from dotenv import load_dotenv
+
 from pathway.udfs import DiskCache, ExponentialBackoffRetryStrategy
 from pathway.xpacks.llm import embedders, llms, parsers, splitters
 from pathway.xpacks.llm.question_answering import BaseRAGQuestionAnswerer
@@ -23,7 +24,6 @@
 
 load_dotenv()
 
-
 def data_sources(source_configs) -> list[pw.Table]:
     sources = []
     for source_config in source_configs:
@@ -55,27 +55,25 @@ def data_sources(source_configs) -> list[pw.Table]:
 
     return sources
 
-
 @click.command()
 @click.option("--config_file", default="config.yaml", help="Config file to be used.")
-def run(
-    config_file: str = "config.yaml",
-):
+def run(config_file: str = "config.yaml"):
     with open(config_file) as config_f:
         configuration = yaml.safe_load(config_f)
 
-    GPT_MODEL = configuration["llm_config"]["model"]
+    LLM_MODEL = configuration["llm_config"]["model"]
 
-    embedder = embedders.OpenAIEmbedder(
-        model="text-embedding-ada-002",
-        cache_strategy=DiskCache(),
+    embedding_model = "avsolatorio/GIST-small-Embedding-v0"
+
+    embedder = embedders.SentenceTransformerEmbedder(
+        embedding_model,
+        call_kwargs={"show_progress_bar": False}
     )
 
-    chat = llms.OpenAIChat(
-        model=GPT_MODEL,
+    chat = llms.LiteLLMChat(
+        model=LLM_MODEL,
         retry_strategy=ExponentialBackoffRetryStrategy(max_retries=6),
         cache_strategy=DiskCache(),
-        temperature=0.05,
     )
 
     host_config = configuration["host_config"]
@@ -94,6 +92,5 @@ def run(
 
     rag_app.run_server(with_cache=True, terminate_on_error=False)
 
-
 if __name__ == "__main__":
-    run()
+    run()

examples/pipelines/demo-question-answering/config.yaml

@@ -1,5 +1,5 @@
 llm_config:
-  model: "gpt-3.5-turbo"
+  model: "gemini/gemini-pro"
 host_config:
   host: "0.0.0.0"
   port: 8000

examples/pipelines/demo-question-answering/requirements.txt

@@ -1,3 +1,6 @@
 pathway[all]>=0.11.0
 python-dotenv==1.0.1
 mpmath==1.3.0
+litellm>=1.35
+Google-generativeai
+Sentence-transformers